Using Bird Distributions to Assess Extinction Risk and Identify Conservation Priorities In

Home , Alagoas tyrannulet, Andean solitaire, Antioquia bristle tyrant, Apical flycatcher, Azure jay, Bahia spinetail

Using Bird Distributions to Assess Extinction Risk and Identify Conservation Priorities in

Biodiversity Hotspots

Natalia Ocampo-Peñuela

Nicholas School of the Environment Duke University

Date: ______

Approved:

______Stuart L. Pimm, Supervisor

______Jennifer Swenson

______Nicholas Haddad

______John R. Poulsen

Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Duke University

2016

ABSTRACT

Using Bird Distributions to Assess Extinction Risk and Identify Conservation Priorities

in Biodiversity Hotspots

Natalia Ocampo-Peñuela

Nicholas School of the Environment Duke University

Date: ______

Approved:

1 ______Stuart L. Pimm, Supervisor

______Jennifer Swenson

______

Nicholas Haddad

______John Poulsen

An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Duke University

2016

Abstract

Habitat loss, fragmentation, and degradation threaten the World’s ecosystems and species. These, and other threats, will likely be exacerbated by climate change. Due to a limited budget for conservation, we are forced to prioritize a few areas over others.

These places are selected based on their uniqueness and vulnerability. One of the most famous examples is the biodiversity hotspots: areas where large quantities of endemic species meet alarming rates of habitat loss. Most of these places are in the tropics, where species have smaller ranges, diversity is higher, and ecosystems are most threatened.

Species distributions are useful to understand ecological theory and evaluate

iv extinction risk. Small-ranged species, or those endemic to one place, are more vulnerable to extinction than widely distributed species. However, current range maps often overestimate the distribution of species, including areas that are not within the suitable

elevation or habitat for a species. Consequently, assessment of extinction risk using these maps could underestimate vulnerability.

In order to be effective in our quest to conserve the World’s most important places we must: 1) Translate global and national priorities into practical local actions, 2)

Find synergies between biodiversity conservation and human welfare, 3) Evaluate the different dimensions of threats, in order to design effective conservation measures and prepare for future threats, and 4) Improve the methods used to evaluate species’

extinction risk and prioritize areas for conservation. The purpose of this dissertation is to address these points in Colombia and other global biodiversity hotspots.

In Chapter 2, I identified the global, strategic conservation priorities and then downscaled to practical local actions within the selected priorities in Colombia. I used existing range maps of 171 bird species to identify priority conservation areas that would protect the greatest number of species at risk in Colombia (endemic and small- ranged species). The Western Andes had the highest concentrations of such species—100 in total—but the lowest densities of national parks. I then adjusted the priorities for this

region by refining these species ranges by selecting only areas of suitable elevation and

v remaining habitat. The estimated ranges of these species shrank by 18–100% after accounting for habitat and suitable elevation. Setting conservation priorities on the basis of currently available range maps excluded priority areas in the Western Andes and, by

extension, likely elsewhere and for other taxa. By incorporating detailed maps of remaining natural habitats, I made practical recommendations for conservation actions.

One recommendation was to restore forest connections to a patch of cloud forest about to become isolated from the main Andes.

For Chapter 3, I identified areas where bird conservation met ecosystem service protection in the Central Andes of Colombia. Inspired by the November 11th (2011) landslide event near Manizales, and the current poor results of Colombia’s Article 111 of

Law 99 of 1993 as a conservation measure in this country, I set out to prioritize conservation and restoration areas where landslide prevention would complement bird conservation in the Central Andes. This area is one of the most biodiverse places on

Earth, but also one of the most threatened. Using the case of the Rio Blanco Reserve, near

Manizales, I identified areas for conservation where endemic and small-range bird diversity was high, and where landslide risk was also high. I further prioritized restoration areas by overlapping these conservation priorities with a forest cover map.

Restoring forests in bare areas of high landslide risk and important bird diversity yields

benefits for both biodiversity and people. I developed a simple landslide susceptibility

vi model using slope, forest cover, aspect, and stream proximity. Using publicly available bird range maps, refined by elevation, I mapped concentrations of endemic and small- range bird species. I identified 1.54 km2 of potential restoration areas in the Rio Blanco

Reserve, and 886 km2 in the Central Andes region. By prioritizing these areas, I facilitate the application of Article 111 which requires local and regional governments to invest in land purchases for the conservation of watersheds.

Chapter 4 dealt with elevational ranges of montane birds and the impact of lowland deforestation on their ranges in the Western Andes of Colombia, an important biodiversity hotspot. Using point counts and mist-nets, I surveyed six altitudinal transects spanning 2200 to 2800m. Three transects were forested from 2200 to 2800m,

and three were partially deforested with forest cover only above 2400m. I compared abundance-weighted mean elevation, minimum elevation, and elevational range width.

In addition to analyzing the effect of deforestation on 134 species, I tested its impact within trophic guilds and habitat preference groups. Abundance-weighted mean and minimum elevations were not significantly different between forested and partially deforested transects. Range width was marginally different: as expected, ranges were larger in forested transects. Species in different trophic guilds and habitat preference categories showed different trends. These results suggest that deforestation may affect

species’ elevational ranges, even within the forest that remains. Climate change will

vii likely exacerbate harmful impacts of deforestation on species’ elevational distributions.

Future conservation strategies need to account for this by protecting connected forest tracts across a wide range of elevations.

In Chapter 5, I refine the ranges of 726 species from six biodiversity hotspots by suitable elevation and habitat. This set of 172 bird species for the Atlantic Forest, 138 for

Central America, 100 for the Western Andes of Colombia, 57 for Madagascar, 102 for

Sumatra, and 157 for Southeast Asia met the criteria for range size, endemism, threat, and forest use. Of these 586 species, the Red List deems 108 to be threatened: 15 critically endangered, 29 endangered, and 64 vulnerable. When ranges are refined by elevational limits and remaining forest cover, 10 of those critically endangered species have ranges <

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100km2, but then so do 2 endangered species, seven vulnerable, and eight non- threatened ones. Similarly, 4 critically endangered species, 20 endangered, and 12 vulnerable species have refined ranges < 5000km2, but so do 66 non-threatened species.

A striking 89% of these species I have classified in higher threat categories have <50% of their refined ranges inside protected areas. I find that for 43% of the species I assessed, refined range sizes fall within thresholds that typically have higher threat categories than their current assignments. I recommend these species for closer inspection by those who assess risk. These assessments are not only important on a species-by-species basis,

but by combining distributions of threatened species, I create maps of conservation

viii priorities. They differ significantly from those created from unrefined ranges.

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Dedication

To my parents, who inspired me to care for nature from the beginning and now support my quest to help protect the World’s birds.

Contents

Abstract ...... iv

List of Tables ...... xiv

List of Figures ...... xv

Acknowledgements ...... xx

1. Assessing threat and conservation priorities for birds in the tropics ...... 1

1.1 Conservation priorities and hotspots ...... 1

1.2 Colombia, a biodiversity hotspot ...... 2

1.3 Species’ ranges ...... 3

1.4 Elevational ranges ...... 5 x

1.5 Species ranges in conservation ...... 6

1.6 International Union for Conservation of Nature (IUCN) ...... 6

1.7 This dissertation ...... 7

2. Setting practical conservation priorities for birds in the Western Andes of Colombia .. 9

2.1 Introduction ...... 9

2.2 Methods ...... 12

2.2.1 Study area and species ...... 12

2.2.2 Range update ...... 14

2.2.3 Range refining ...... 15

2.2.4 Bird conservation priorities and reassessing threat level ...... 17

2.3 Results ...... 18

2.3.1 Initial map for Colombia ...... 18

2.3.2 Impacts of better knowledge and range refinement ...... 20

2.3.3 Re-assessing threat levels with refined ranges ...... 22

2.4 Discussion ...... 22

2.4.1 Importance of range updating ...... 23

2.4.2 Justification for refining ranges ...... 23

2.4.3 Reclassifying threat ...... 24

2.4.4 Western Andes conservation actions ...... 25

3. Bird conservation complements landslide prevention in the Central Andes of

Colombia ...... 31

3.1 Introduction ...... 31 xi

3.2 Methods ...... 34

3.2.1 Study area ...... 34

3.2.2 Landslide susceptibility index ...... 37

3.2.3 Birds...... 39

3.2.4 Conservation and restoration areas ...... 40

3.3 Results ...... 41

3.4 Discussion ...... 48

4. Elevational ranges of montane birds and deforestation in the Western Andes of Colombia ...... 53

4.1 Introduction ...... 53

4.2 Materials and methods ...... 57

4.2.1 Study area ...... 57

4.2.2 Field Methods ...... 60

4.2.3 Data preparation ...... 62

4.2.4 Data analysis ...... 64

4.3 Results ...... 65

4.4 Discussion ...... 72

4.4.1 Range width ...... 74

4.4.2 Trophic guilds ...... 75

4.4.3 Habitat categories ...... 77

4.4.4 Recommendations ...... 78 xii 4.4.5 Conservation implications ...... 78

4.4.6 Conclusions ...... 79

5. Evaluation of threatened bird species using land-cover data in biodiversity hotspots 81

5.1 Introduction ...... 81

5.2 Materials and Methods ...... 82

5.2.1 Study area ...... 82

5.2.2 Study species ...... 83

5.2.3 Range refinement ...... 84

5.2.4 Threat category re-assessment ...... 87

5.2.5 Protected areas ...... 88

5.3 Results and discussion ...... 88

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5.3.1 Threat category reassessment ...... 89

5.3.2 Refining of conservation priorities...... 100

5.4 Conclusions ...... 109

6. Final remarks ...... 111

Appendix 1 ...... 114

Appendix 2 ...... 119

Appendix 3 ...... 120

Appendix 4 ...... 123

Appendix 5 ...... 126

Appendix 6 ...... 128 xiii Appendix 7 ...... 135

Appendix 8 ...... 142

Appendix 9 ...... 147

Appendix 10 ...... 149

Appendix 11 ...... 154

Appendix 12 ...... 157

References ...... 161

Biography ...... 177

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List of Tables

Table 1: Input variables to the landslide susceptibility index, and their associated weighted values, for the Rio Blanco Reserve ...... 37

Table 2: Confusion matrix for landslide susceptibility index in the Rio Blanco Reserve. 43

Table 3: Results from one-tailed ANOVA test comparing elevational range width of different trophic guilds, in forested and partially deforested transects...... 69

Table 4: Results from one-tailed ANOVA test comparing abundance-weighted mean elevations of different habitat preference categories, in forested and partially deforested transects...... 70

Table 5: Results from TukeyHSD test showing differences in abundance-weighted mean elevation between habitat preference categories, and forest and no-forest transects...... 71

Table 6: Results from ANOVA test comparing elevational range widths of different habitat preference categories, in forest and no-forest transects...... 71 xiv

Table 7: Comparison of forest areas for 250 and 30m forest cover products, and areas covered by the highest concentrations of endemic and small-ranged bird species (10% and 25%) after range refinement steps...... 101

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List of Figures

Figure 1: Range maps for the Multicolored Tanager (Chlorochrysa nitidissima), a Colombian endemic: (a) BirdLife range (b) range updated on the basis of presence data (c) range as refined by elevation (d) range refined by both elevation and habitat (i.e., forest)...... 17

Figure 2: Concentration of (a) endemic and small-range bird species (n = 171) and (b) threatened bird species (N = 42) in Colombia on the basis of BirdLife and NatureServe maps (2011)...... 19

Figure 3: Concentration of 100 endemic and small-range bird species for the Western Andes of Colombia (a) BirdLife maps, (b) after our range updates based on presence data, (c) refined by suitable elevation, and (d) refined by elevation and habitat...... 20

Figure 4: Rank of 100 Western Andes birds by range size (smallest to largest) on the basis of the original BirdLife range map, ranges updated on the basis of presence data,

ranges refined by elevation, and ranges refined by elevation and habitat...... 21 xv

Figure 5: Thirteen Western Andes endemic species ranked by increasing range size (top to bottom) on the basis of BirdLife ranges, ranges we updated with presence data, ranges refined by suitable elevation, and ranges refined by elevation and habitat...... 25

Figure 6: Mesenia-Paramillo Reserve (green) and protected areas around it on a satellite image provided by Earthstar Geographics...... 28

Figure 7: Study area. (A) Map of Colombia (B) Localized study area near Manizales. .... 36

Figure 8: Input layers for the landslide susceptibility index in and near the Rio Blanco Reserve. All values are standardized to the 100-point scale of the landslide susceptibility index. (A) Slope derived from Digital elevation Index (Jarvis et al., 2008). (B) Forest cover derived from the Hansen et al. (2013) forest map. (C) Stream proximity derived from a stream layer. (D) Aspect derived from Digital elevation index (Jarvis et al., 2008)...... 42

Figure 9: (A) Landslide susceptibility index for the Rio Blanco Reserve and its surroundings. (B) Simplified landslide susceptibility (0–60, and 60–100). (C) Concentration of endemic and threatened bird species. (D) Simplified concentration of endemic and threatened bird species (0–6, and 7–14 species). (E) Areas with high

landslide susceptibility, high concentrations of endemic and threatened bird species, both (conservation priorities), or none...... 45

Figure 10: Restoration priority areas that lack forest cover and have high landslide risk and high landslide risk and high endemic and small-range bird concentrations (first, second, and general priority) in the Rio Blanco Reserve. Paramo ecosystem (above 3500 m) shown in gray...... 46

Figure 11: Conservation and restoration priorities, and human population density for the Central Andes. Conservation and restoration areas in the Central Andes in Colombia overlaid on layers of population density (as people per pixel, from the WorldPop dataset (Tatem et al., 2013)), and roads for the coffee-growing region (A), and the Medellin area (B)...... 47

dates 28/12/2013-01/04/2014. Displayed here with permission from Saving Species xvi (www.savingspecies.org) and in line with agreement from seller BlackBridge...... 59

Figure 13: Comparison of elevational range variables for forested and partially deforested transects (p values shown are for one-factor ANOVAs). a) Abundance- weighted mean elevation. b) Minimum elevation. c) Elevational range width. Dots represent outliers...... 67

Figure 14: Comparison of elevational range variables per trophic guild for forested and partially deforested transects (p values shown are for one-tailed two-factor ANOVAs). a) Abundance-weighted mean elevation. b) Minimum elevation. c) Elevational range width. Dots represent outliers...... 69

Figure 15: Comparison of elevational range variables per habitat preference category for forested and partially deforested transects (p values shown are for one-tailed two-factor ANOVAs). a) Abundance-weighted mean elevation. b) Minimum elevation. c) Elevational range width. Dots represent outliers...... 72

Figure 16: Study area. Six study regions highlighted with black outlines overlaid on a map of concentration of small-ranged bird species (n=4964, species with ranges smaller than the median) from Jenkins et al. (2013)...... 83

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Figure 17: Range refinement process. A) Original range for the Yellow-breasted Antpitta (Grallaria flavotincta) as determined by BirdLife International and NatureServe (2014), and updated by Ocampo-Peñuela and Pimm (2014). B) Range map refined by elevation using 90m digital elevation model (Jarvis et al. 2008). C) Range map refined by elevation and forest at 250m. D) Range map refined by elevation and forest at 30m...... 87

Figure 18: Atlantic Forest of Brazil. Patterned boxes show threat categories suggested based on range size thresholds established by IUCN. Solid filled boxes reflect current global IUCN categories. Arrows show changes in threat category as the range is refined by elevation and forest, their width depicts the number of species that changed categories...... 91

Figure 19: Central America. Patterned boxes show threat categories suggested based on range size thresholds established by IUCN. Solid filled boxes reflect current global IUCN categories. Arrows show changes in threat category as the range is refined by elevation and forest, their width depicts the number of species that changed categories.

...... 92

Figure 20: Madagascar. Patterned boxes show threat categories suggested based on xvii range size thresholds established by IUCN. Solid filled boxes reflect current global IUCN categories. Arrows show changes in threat category as the range is refined by elevation and forest, their width depicts the number of species that changed categories...... 93

Figure 21: Southeast Asia. Patterned boxes show threat categories suggested based on range size thresholds established by IUCN. Solid filled boxes reflect current global

IUCN categories. Arrows show changes in threat category as the range is refined by elevation and forest, their width depicts the number of species that changed categories...... 94

Figure 22: Sumatra. Patterned boxes show threat categories suggested based on range size thresholds established by IUCN. Solid filled boxes reflect current global IUCN categories. Arrows show changes in threat category as the range is refined by elevation and forest, their width depicts the number of species that changed categories...... 95

Figure 23: Western Andes of Colombia. Patterned boxes show threat categories suggested based on range size thresholds established by IUCN. Solid filled boxes reflect current global IUCN categories. Arrows show changes in threat category as the range is

xvii

refined by elevation and forest, their width depicts the number of species that changed categories...... 96

Figure 24: Six biodiversity hotspots (Atlantic forest, Western Andes of Colombia, Sumatra, Madagascar, Central America, and Southeast Asia). Patterned boxes show threat categories suggested based on range size thresholds established by IUCN. Solid filled boxes reflect current global IUCN categories. Arrows show changes in threat category as the range is refined by elevation and forest, their width depicts the number of species that changed categories...... 98

Figure 25: Percent of range protected in all categpories of protected areas for species classified as critically endangered, endangered, or vulnerable solely based on range size, and after refining their range by elevation and forest (30m)...... 100

Figure 26: Concentrations of endemic, threatened, and small-ranged bird species in the Atlantic Forest, Brazil. A) Original ranges from BirdLife International and NatureServe (2011). B) Ranges refined by elevation using 90m digital elevation model (Jarvis et al.

2008). C) Ranges refined by elevation and forest at 250m scale. D) Ranges refined by

elevation and forest at 30m scale...... 103 xviii

Figure 27: Concentrations of endemic, threatened, and small-ranged bird species in Central America. A) Original ranges from BirdLife International and NatureServe (2011). B) Ranges refined by elevation using 90m digital elevation model (Jarvis et al. 2008). C) Ranges refined by elevation and forest at 250m scale. D) Ranges refined by elevation and forest at 30m scale...... 104

Figure 28: Concentrations of endemic, threatened, and small-ranged bird species in Madagascar. A) Original ranges from BirdLife International and NatureServe (2011). B) Ranges refined by elevation using 90m digital elevation model (Jarvis et al. 2008). C) Ranges refined by elevation and forest at 250m scale. D) Ranges refined by elevation and forest at 30m scale...... 105

Figure 29: Concentrations of endemic, threatened, and small-ranged bird species in Southeast Asia. A) Original ranges from BirdLife International and NatureServe (2011). B) Ranges refined by elevation using 90m digital elevation model (Jarvis et al. 2008). C) Ranges refined by elevation and forest at 250m scale. D) Ranges refined by elevation and forest at 30m scale...... 106

xviii

Figure 30: Concentrations of endemic, threatened, and small-ranged bird species in Sumatra. A) Original ranges from BirdLife International and NatureServe (2011). B) Ranges refined by elevation using 90m digital elevation model (Jarvis et al. 2008). C) Ranges refined by elevation and forest at 250m scale. D) Ranges refined by elevation and forest at 30m scale...... 107

Figure 31: Concentrations of endemic, threatened, and small-ranged bird species in the Western Andes of Colombia. A) Original ranges from BirdLife International and NatureServe (2011). B) Ranges refined by elevation using 90m digital elevation model (Jarvis et al. 2008). C) Ranges refined by elevation and forest at 250m scale. D) Ranges refined by elevation and forest at 30m scale...... 108

xix

Acknowledgements

Thanks to my adviser Stuart L. Pimm for outstanding training and support during my PhD. I especially appreciated the respect he had for my work and the numerous times we worked together to produce amazing conservation science, that then turned into practice.

I’d like to thank my committee: Nick Haddad, Jennifer Swenson, and John

Poulsen for their invaluable support and advice during this process.

Special thanks to Fulbright and Colciencias for providing a full PhD scholarship

that allowed me to undergo my research at Duke. xx

Institutions that funded my field seasons were fundamental to achieve my goals.

Thanks to the National Science Foundation, Duke Graduate School, Duke CLACS, The

Explorer’s club, IdeaWild, and Cristian Samper and family for providing funds for my

many field seasons in the Colombian Andes.

I thank all the staff at the Graduate School and at the Nicholas School for the help and support during my PhD, and for providing a fun environment to conduct research.

Special thanks to Meg Stephens, Anne Jones, Mike Burnett, Chris Erlien, and Susan

Brown. Without them I would have never been able to make it through the administrative maze, would have frozen to death in my office, wouldn’t have smiled at

my beautiful plants, and wouldn’t have enjoyed myself as much as I did. Meg’s friendship was a huge plus for my PhD.

Thanks to the amazing scientists that supported my ideas and helped me grow them into good science. To Clinton Jenkins and Mariano Gonzalez for their unconditional support, especially with GIS and remote sensing. And to John Terborgh and Lisa Davenport for endless conversations about science and fieldwork, which made my research a lot better.

My many field crews were instrumental in the data gathering stages of my PhD.

I thank all my field assistants for their invaluable help during the tough months living in

xxi the Andean forest. They not only helped me collect great scientific data, but also made it fun!

Thanks to my NC birding friends for good breaks during my PhD to score some

life birds in this wonderful state. I truly enjoyed birding here, and it wouldn’t have been the same without such a fun gang.

Thanks to my fellow colleagues at the Pimm Lab, German Forero, Andrew

Jacobson, Joe Lemeris, Colin Hutton, Binbin Li, Varsha Vijay, Alexandra Sutton, Ryan

Huang, Dani Moreira, and visiting scholars for the valuable feedback on my research and for fun times in the office.

xxi

This PhD wouldn’t have been the same without the Latin Group who made this journey much more loud, exciting, and unforgettable.

Thanks to the Winton family for inviting me to be part of such an amazing clan, I have truly enjoyed my time in Durham and have it now feels like home.

I am most grateful to my family, and especially my parents Alvaro y Lourdes, for always believing in me, for supporting me through this PhD journey, and for always encouraging me to go further.

Thanks to Ricardo and Maria Isabel for their unconditional support and their

trust in me as a person and a scientist.

My biggest thanks to Scott Winton, who has walked this path with me cheering xxii me on at all times, and believing in me and the great things I could do. He has inspired me to go further and be better every time, but especially to find happiness in all that I

do. This journey wouldn’t have been as fun and relaxed without him.

xxii

1. Assessing threat and conservation priorities for birds in the tropics

1.1 Conservation priorities and hotspots

Conservation biology seeks to understand, protect, and perpetuate all levels of biodiversity, and the goods and services they provide, in the face of fast-moving threats and a limited budget (Sodhi and Ehrlich 2010). Conservation strategies are diverse and need to be contextual. The two main strategies are proactive, and reactive conservation.

Proactive conservation prioritizes areas of low vulnerability, normally with larger

extensions of habitat left, and fewer threats; it also seeks conservation of species that are not necessarily threatened. Reactive conservation, on the contrary, seeks to conserve 1 very vulnerable places and species, those with little habitat left, severe fragmentation, and large concentrations of endemic and restricted range species (Brooks et al. 2006). To address the latter circumstances, conservation biologists focus on areas that contain

large numbers of species that are vulnerable to extinction - those that have restricted ranges, or are threatened (Pimm et al. 1995, Pimm and Lawton 1998), which tend to be locally rare (Gaston 1994). Since these endemism centers have also lost great portions of their habitat (>70%), conservation biologists call them “hotspots” (Myers et al. 2000). The information fed into many of these conservation priority setting methods is often too coarse spatially, making their outputs limiting when seeking tactical conservation actions. The use of equal-area grids, ecoregions (Brooks et al. 2006), or even country 1

boundaries (Mittermeier et al. 1997) makes setting local conservation priorities harder since, in practice, conservation actions unfold across much smaller geographic extents.

Moreover, the key insight from hotspots is that threatened species concentrate in places where most of the habitat has already been destroyed (Myers et al. 2000) or soon will be

(Jenkins et al. 2013).

Tropical forests are a hotspot for biodiversity and a conservation priority. For instance, global bird conservation priorities often focus on the tropics, where two thirds of the world’s bird species live, including 79% of the species deemed threatened by the

International Union for the Conservation of Nature (IUCN) (Sodhi et al. 2011).

1.2 Colombia, a biodiversity hotspot

Colombia is part of the Tropical Andes, Chocó-Darién, and Caribbean biodiversity hotspots (Myers et al. 2000). The country’s rich biodiversity is partly a result

of a privileged geographic location and elevations that range from sea level to 5800 m.

Bird diversity is exceptional with over 1800 species (72 endemic) and a rate of discovery of 1 new species per year (Franco et al. 2009), compared to a global 2.4 per year (Long et al. 1996). This is 18% of the world bird species, in less than 1% of its ice-free land surface; more than any other country. The diversity of mammals and amphibians is also exceptional (Jenkins et al. 2013), while the northern Andes more generally hold one of the largest numbers of flowering plant species in the world (Kier et al. 2005), and the

largest numbers of species predicted yet to be described by taxonomist (Joppa et al.

2011). Although the country still keeps intact portions of ecosystems in the Amazon, the

Chocó, and the Orinoco, the Andes have lost 70% of the original forest cover (Etter and

Van Wyngaarden 2000) and most species with small geographic ranges live here (Renjifo et al. 2001). National parks cover 12% of the national surface, but most parks, and the largest ones, are located outside the Andes (Sistema de Parques Nacionales Naturales de

Colombia 2013).

1.3 Species’ ranges

Identifying and understanding the geographic distribution of species has been 3 fundamental to macroecology (Blackburn and Gaston 1996). By studying species’ geographical ranges, biogeographers examine the expression of a species’ ecological niche in space (Sexton et al. 2009).

The frequency distribution of range sizes is right-skewed: large quantities of species have small ranges, and few species have large ranges (Blackburn and Gaston

1996). In space, this distribution follows Rapoport’s rule: species from higher latitudes have larger ranges, than those with tropical distributions (Stevens 1989). This also applies to altitude: as elevation increases, the altitudinal range widens (Stevens 1992) and species richness decreases (Rahbek 1995).

As Stevens (1992) explained, ranges of species at higher altitudes and latitudes are perhaps larger because these species have a wider tolerance to environmental variations throughout the year, or during the day. Historically, abiotic factors, such as climate, have been found to limit the ranges of species at higher latitudes, and biotic factors have played a more important role with decreasing latitude (Dobzhansky 1950,

MacArthur 1972). Furthermore, biotic factors may have a more important role when the ranges are small and species diversity is high (Brown et al. 1996), as is the case with New

World birds (Blackburn and Gaston 1996). Studies of species ranges have been mostly

driven by the motivation to understand range limits for commercially important plants,

4 invasive weeds and pests, and biological control agents (Brown et al. 1996). Few studies have explored ecological patterns of range limits.

Research about species ranges has focused mainly on its relation to: body size,

latitude, and abundance (Blackburn and Gaston 1996): fewer studies have studied the effect of altitude (Stevens 1992). Elevational data for most organisms is generated by extrapolating from a small number of observations, while hardly any studies have looked at determining the lower and upper altitudinal limits of species ranges (Stevens

1992). Due to the intense fieldwork involved in an altitudinal transect, very few have been completed, and even fewer have been resampled. Plants and temperate localities have dominated the research on species ranges on environmental gradients, whereas

few studies have focused on animals or tropical areas (Fischer et al. 2011). Examples of altitudinal transects in the tropics include: vegetation studies in Borneo (Kitayama 1992), soil development in Bolivia (Schawe et al. 2007), liana distribution in Ecuador (Homeier et al. 2010), and insect diversity in Panama (Wolda 1987).

1.4 Elevational ranges

Biogeographers and ecologists have mapped species’ ranges using Geographical

Information System (GIS) technology, recognizing how species are distributed two- dimensionally (Franklin 2009). However, they are still working to understand the

altitudinal distribution component, especially in places with very high diversity (Stevens 5

1992) like the tropical Andes.

The study of birds along altitudinal transects on tropical and subtropical areas has been going on for several decades: in Costa Rica (Loiselle and Blake 1991), in Mexico

(Navarro 1992), Vanuatu (Diamond and Marshall 1977), and Peru (Terborgh 1977,

Forero-Medina et al. 2011). Identification of species’ range limits allows ecologists to understand how species distribute in space. We can use this information subsequently to assess the patterns of the impact of habitat loss on species’ ranges (expansion, compression, and extirpation) and how species composition changes at certain sites.

Ultimately, we can determine how species ranges will shift in response to warming.

1.5 Species ranges in conservation

Ecologists and conservation biologists strive not only to understand how species ranges are spatially distributed, but also to determine range shifts in response to landcover and climate change. Elevational ranges have been found to explain the probability of a species becoming threatened, and ultimately extinct (Sekercioglu et al.

2008). It is also known that Andean birds cannot survive in the absence of forest (O’Dea and Whittaker 2007), and that birds will be more likely to track habitat changes, than temperature (Forero-Medina et al. 2011). Along altitudinal gradients in Venezuela,

Colombia, and Ecuador Thiollay (1996) found that habitat loss and fragmentation

6 reduced raptor’s ranges. Climate change will intensify these effects of landcover change, which will produce alterations in temperature and rainfall seasonality. Range contractions and species extirpations in polar areas and mountaintops are already being

documented (Parmesan 2006), and even conservative climate change scenarios result in the predicted extinction of 100 to 500 land birds (Sekercioglu et al. 2008).

1.6 International Union for Conservation of Nature (IUCN)

The International Union for Conservation of Nature (IUCN) is a global, international organization whose mission is to “influence, encourage and assist societies throughout the world to conserve the integrity of nature and to ensure that any use of natural resources is equitable and ecologically sustainable” (International Union for

Conservation of Nature (IUCN) 2016). One of its more important programmes is the Red

List. In here, species are classified into various categories that reflect their risk of extinction(IUCN 2012). It employs rigorously objective criteria, is transparent, and democratic in soliciting comments on individual species decisions. The process updates species status regularly and all the associated data are publicly accessible

1.7 This dissertation

In this dissertation I study distributions of endemic, threatened and small-ranged birds in biodiversity hotspots to assess their usefulness in assessing extinction risk, and

setting conservation priorities. Through intensive use of Geographic Information 7

Systems, I map areas of high concentrations of birds of conservation concern in the most biodiverse places, to inform conservation decisions and refine the process that assigns species to threat categories.

Chapters 2, 3 and 4 of this document examine bird conservation in Colombia from three different angles. Chapter 2 looks at national priorities for bird conservation, identifies the Western Andes as a priority, and downscales this priority to on-the- ground conservation actions. In Chapter 3, I combine priorities for bird conservation with landslide prevention to identify areas where forest restoration would benefit both biodiversity and people in the Central Andes. Focusing on the Western Andes, and specifically the area identified as priority on Chapter 2, I examine the impacts of

deforestation on bird elevational ranges in Chapter 4. Using fieldwork to provide original data, I compare altitudinal transects with different extents of forest to evaluate impacts of lowland deforestation on the ranges of remnant bird populations.

Chapter 5 presents a global analysis of bird conservation priorities in six biodiversity hotspots. By refining ranges by elevation and forest, I show that the

International Union for the Conservation of Nature (IUCN) should incorporate habitat data in the assessment of species’ extinction risk. Refining ranges significantly changes conservation priorities and the assignment of threat categories for forest birds.

Some of these chapters, and additional research I undertook while at Duke

8 University, have been published in peer-reviewed journals. Chapter 2 was published in the flagship journal Conservation Biology in 2014, Chapter 3 was published in PeerJ in

2015, Chapter 4 was published in PloS One in 2015, and Chapter 5 will be submitted to

Nature after the completion of this defense. I have also published additional research on birds in naturally fragmented landscapes in the journal Neotropical Ornithology in 2013

(Ocampo-Peñuela, N & A. Etter. 2013. Contribution of different forest types to the bird community of a savanna landscape in Colombia. Neotropical Ornithology 24: 35-53.), and on bird-window collisions in PeerJ in 2016 (Ocampo-Peñuela, N., R.S. Winton, C.

Wu, E. Zambello, T. Wittig & N. Cagle. 2015. Patterns of bird-window collisions inform mitigation on a university campus. PeerJ 4:e1652; DOI 10.7717/peerj.1652).

2. Setting practical conservation priorities for birds in the Western Andes of Colombia

2.1 Introduction

Priority setting in conservation looks at where all species are supposed to live, or at those that are at risk or special in some way, and then optimally selects sites that capture the largest fraction of species in a specified total area (Pimm and Lawton 1998).

Such methods are strategically useful because they identify regions that need consideration and investment. Biodiversity hotspots (Myers et al. 2000) are the most

cited example. We have found that the information that informs these methods is often unhelpful in effecting local, tactical conservation actions. The information is often too 9 coarse spatially; that is, it is based on equal-area grids, ecoregions (Brooks et al. 2006), or even country boundaries. Practical conservation actions unfold across much smaller geographic extents. Moreover, the key insight from hotspots is that threatened species

concentrate in places where most of the habitat has already been destroyed (Myers et al.

2000) or soon will be (Jenkins et al. 2013). For 95% of the world’s threatened bird species, their status is due to habitat loss (Sodhi et al. 2011). Consequently, tactical conservation actions must reflect the habitat loss and fragmentation that have sharply restricted where species now live. We hoped to identify and map areas of global, strategic conservation priority and then downscale these maps to a local scale to implement practical conservation actions that would be globally significant. 9

Colombia contains parts of the Tropical Andes, Chocó-Darién, and Caribbean biodiversity hotspots (Myers et al. 2000). The country’s rich biodiversity is partly a result of its geographic location and elevations that range from sea level to 5800 m. It has over

1800 species and 1 new species is discovered per year (Franco et al. 2009). This is 18% of the world bird species, in <1% of its ice-free land surface. Globally, on average 2.4 bird species are discovered per year (Long et al. 1996). The diversity of mammals and amphibians is also exceptional (Jenkins et al. 2013). More generally, the Northern Andes house the largest numbers of flowering plant species in the world (Kier et al. 2005) and

the largest numbers of species predicted to be as-yet undescribed by taxonomists (Joppa

10 et al. 2011). Although the country still contains intact portions of ecosystems in the

Amazon, the Chocó, and the Orinoco, the Andes have lost 70% of their original forest cover (Etter and Van Wyngaarden 2000). Most species with small geographic ranges live

in the remaining forest (Renjifo 2001). National parks cover 12% of the nation’s surface, but most parks, and all the largest ones, are outside the Andes (Sistema de Parques

Nacionales Naturales de Colombia 2013).

We considered how to set conservation priorities that might lead to direct conservation actions in Colombia. We recognized previous efforts to set priorities for birds in Colombia such as Terborgh and Winter (1982), national efforts such as the

National Bird Conservation Strategy (Renjifo et al. 2001), and species modeling work by

Velásquez-Tibatá et al. (2013) and Verhelst (2011). We complement these with our analyses.

Conservation priorities are usually based on species with small geographical ranges (Long et al. 1996), endemic species (Stotz 1996) or species threatened with extinction (Jenkins et al. 2010). The latter group includes all species the International

Union for the Conservation of Nature (IUCN) (IUCN 2012) classified as vulnerable, endangered, and critically endangered. Using all small-ranged species in a priority scheme means including both species that are already threatened and those that will

likely be threatened soon because of their range size and continuing habitat loss.

11 For endemic and small-range bird species, we followed methods that were successfully applied to the coastal forests of Brazil (Harris et al. 2005, Jenkins et al. 2010,

Pimm and Jenkins 2010, Jenkins et al. 2011). Expecting the remaining habitats to be

severely fragmented, we sought areas to reconnect forest fragments in the Western

Andes of Colombia that would have the highest concentrations of endemic and small- ranged bird species.

First, we considered how recent surveys expanded known bird distributions.

Although birds are relatively well known, there are uncertainties in range maps (Harris and Pimm 2008). In particular, decades of politically motivated violence in Colombia have severely restricted biological exploration.

Second, we created realistic species range maps given the elevational limits of species, informed by remote sensing of where their habitats remain. We then compared priority areas based on existing range maps (BirdLife International and NatureServe

2011) with those extended by recent surveys, and by those refined by the elevational limits and remaining habitats. Finally, we show how to employ these priorities to reconnect forest fragments. Our approach and methods have great potential to enhance the existing protected areas’ network.

2.2 Methods 12 2.2.1 Study area and species

Seventy bird species and 2 genera are endemic to Colombia (Franco et al. 2009).

Of these, 40 species are threatened (BirdLife International 2014) as are a further 47 that

are not endemic. Four endemic bird areas are exclusively in Colombia and another 10 are shared with neighboring countries (Stattersfield et al. 2005). Nationally, 116 important bird areas (IBA) cover 7% of Colombia’s 1,142,000 km2. Over 50% of the IBAs are completely protected, and 18% are partially protected (Franco et al. 2009). The national park system includes 56 protected areas that cover 12% of Colombia (Sistema de Parques Nacionales Naturales de Colombia 2013). A system of regional, local, and private reserves (RESNATUR 2013) complements the national parks.

In the southwestern corner of Colombia, the Andean mountain range divides into 3 cordilleras (Western, Central, Eastern) with two river valleys between them

(Cauca and Magdalena). Of the three, the Western Andes has the highest species richness and the most endemic rodents, bats, butterflies, frogs, and birds (Cuervo et al.

2003, Kattan et al. 2004). In this cordillera, the western slope is extremely humid due to the interception of winds from the Pacific Ocean (Kattan et al. 2004), while the eastern slope’s more arid climate is the result of a rain shadow. A lack of road access on the western slope has minimized deforestation (Robbins and Stiles 1999), but human

disturbance deforests much of the eastern slope (Cuervo et al. 2003).

13 In setting conservation priorities, we considered only terrestrial bird species endemic to Colombia and species with a known geographic range of <100,000 km2

(BirdLife International and NatureServe 2011), species that we called small-range

species. We chose the 100,000 km2 threshold based on IUCN criteria (IUCN 2012); species with smaller ranges are sometimes classified as near threatened, while species with larger ranges are generally classified as of least concern. The species we chose are in urgent need of conservation, given continuing threats of habitat loss and fragmentation (Etter et al. 2006). Of the 171 species that met the criteria, 69 are endemics.

We excluded one endemic species (Arremon basilicus) from our analyses because it is a recent taxonomic split (Remsen et al. 2013) and a range map was not available. We used

the species ranges, follow the taxonomy, and employ the threat status provided by

BirdLife International and NatureServe (BirdLife International and NatureServe 2011).

We mapped priority conservation areas for all 171 bird species in Colombia.

Subsequent detailed analyses of practical conservation priorities focused only on the

Western Andes, including just 100 birds. Within this region, analysis of IUCN categories comprised only 13 species endemic to the Western Andes (Stiles et al. 2014).

2.2.2 Range update

We updated only species’ ranges on the Western Andes because this area had the

highest concentration of endemic and small-range bird species. Within the Western 14 Andes, we found that 73 of the 100 available range maps excluded localities with known presences. We updated these ranges from inventories and fieldwork. To update the ranges, we created a bounding polygon around the Western Andes. For the 100 species

whose ranges fell within this polygon, we gathered locality data from the Global

Biodiversity Information Facility (GBIF) (Global Biodiversity Information Facility 2013), the Sistema de Información sobre Biodiversidad (SIB) (Instituto de Investigacion de

Recursos Biologicos Alexander von Humboldt 2013), and published and unpublished bird inventories. These inventories included 13 localities (Appendix 1).

We updated the ranges in a similar way to BirdLife International and

NatureServe (2011). For each species, we displayed the localities where it is present, the

current range map, and the preferred elevation. Using ArcMap 10 (ESRI 1999-2013), and following the techniques for expert-drawn range maps (Graham and Hijmans 2006), we drew an extension of the existing polygon that included the new localities, following the elevation limits of the range. The polygon was the most conservative possible without assuming the presence of the species in areas lacking data. If a locality was >50 km away from the current polygon, we created a 10 km buffer around it (Appendix 2).

2.2.3 Range refining

Published range maps, and those drawn following the expert-drawn techniques,

often include areas unsuitable for the species (Harris et al. 2005). Two steps refined the 15 ranges to achieve more accurate and realistic maps. First, we refined the updated range maps with the known limits of elevation with a 90 m digital elevation model (Jarvis et al.

2008). The preferred elevation for each species was the minimum and maximum

elevations recorded for the species (Hilty and Brown 1986, Restall et al. 2006) or on the species’ factsheets from BirdLife International and NatureServe (2011). We understand that the elevational limits of a species may vary along its distribution (Terborgh 1977).

Second, we further refined the range by remaining habitat. We used the most recent land cover map of Colombia (Sanchez-Cuervo et al. 2012) and selected only natural cover as habitat (mature and secondary forest). We called the final map resulting from this process a species’ habitat map.

For example, Figure 1 shows the range modifications for the Multicolored

Tanager (Chlorochrysa nitidissima), a vulnerable and endemic species found in the

Western and Central Andes (Hilty and Brown 1986, BirdLife International 2012). We refined BirdLife’s map (Figure 1a) to include new observations of its occurrence (Figure

1b). This species prefers elevations between 1,300 and 2,200 m, so we then refined the map to include areas within this elevational range (Figure 1c). Unless one does so, the implied ranges can often be many times larger than is possible given the known elevational limits of the species (Harris and Pimm 2008). Using this new range, we

further refined the map by selecting only areas still covered by forest, the tanager’s

habitat (Figure 1d) (Hilty and Brown 1986).

(i.e., forest).

2.2.4 Bird conservation priorities and reassessing threat level

We overlaid 171 BirdLife range maps (BirdLife International and NatureServe

2011) and repeated the process with only threatened species (IUCN 2012). We then summed the number of species to map high concentrations of endemic, small-range, and threatened bird species. 17

BirdLife International is IUCN’s designated partner to determine the threat category of birds. Thresholds are set for the following criteria: reduction of population size, reduction in geographic range (extent of occurrence or area of occupancy), decreasing estimates of mature individuals in the population, and known extinction probability (IUCN 2012). Most of these criteria are difficult to assess and estimating population sizes and trends for all species is far from practical (Freile et al. 2010).

Geographic range is an accessible measure that serves as a proxy of them. Following the range refining process, we evaluated the threat categories for 13 species of birds whose

total ranges are entirely within the Western Andes of Colombia.

18 2.3 Results

2.3.1 Initial map for Colombia

Small ranged species concentrate in the isolated Sierra Nevada de Santa Marta

and in the Eastern, Central, and especially the Western Andes (Figure 2a). The pattern of threatened species was similar (Figure 2b). The Western Andes housed the highest concentrations of endemic and small-range species and threatened species (35 and 12 species, respectively). The largest national parks, which are in the Amazon lowlands, contained no endemic or small-range bird species. Along the Andes, and especially on the Western Andes, there are few parks and they do not protect most of the species

concentrations (Figure 2). Henceforth, we consider only the Western Andes. Figure 3a is

the detail of Figure 2a for this region.

Figure 2: Concentration of (a) endemic and small-range bird species (n = 171) and (b) threatened bird species (N = 42) in Colombia on the basis of BirdLife and NatureServe maps (2011).

We knew from our and others’ fieldwork that the map in Figure 3a had substantial omissions. For example, for the Mesenia-Paramillo Reserve (Figure 3), Suarez

(2013) reported at least 23 species of endemic and threatened bird species. Figure 3a shows only 3 endemic and 2 threatened species.

Figure 3: Concentration of 100 endemic and small-range bird species for the 20 Western Andes of Colombia (a) BirdLife maps, (b) after our range updates based on presence data, (c) refined by suitable elevation, and (d) refined by elevation and habitat.

2.3.2 Impacts of better knowledge and range refinement

The highest concentration of bird species in the Western Andes changed from 41 to 46 when we updated the range maps, and high concentrations of species extended much farther north: compare Figure 3a and 3b.

Although the general patterns of concentration of endemic and small-range birds were similar, with range refinement, these areas became smaller and highly fragmented: compare Figure 3b and Figure 3d. Our updates to the ranges resulted in generally larger

ranges than those reported by BirdLife (Figure 4: top grey line compared to the black line below it). Once refined by elevation, however, the range sizes decreased (Figure 4. dashed line), and then decreased substantially when refined by habitat (Figure 4 dotted line) (Appendix3).

Figure 4: Rank of 100 Western Andes birds by range size (smallest to largest) on the basis of the original BirdLife range map, ranges updated on the basis of presence data, ranges refined by elevation, and ranges refined by elevation and habitat.

2.3.3 Re-assessing threat levels with refined ranges

The combination of limited elevational range and extensive habitat loss means these species have much smaller ranges than previously thought. Inevitably, range updates resulted in larger ranges (Figure 4), while the refining process resulted in smaller ranges because remaining habitat did not cover all the area within the chosen elevations. Scytalopus canus, Picumnus granadensis, Habia cristata, and Bucco noanamae are all of least concern or near threatened. After we trimmed the ranges by elevation and habitat, all their ranges were <20,000 km2. In extreme cases, such as Picumnus granadensis

and Bucco noanamae, the species lost 83% and 54% of their estimated range respectively

22 after we refined by suitable elevation and habitat. P. granadensis is of less concern because it uses forest borders, secondary plantations, and coffee plantations extensively.

Comparatively, B. noanamae is a forest-restricted species. A recently rediscovered species

presents another interesting case. The original BirdLife range for Coeligena orina was 25 km2; after updates it was 1,084 km2. Its estimated range dropped when we refined by elevation to 55 km2 and by and habitat to 45 km2.

2.4 Discussion

The Western Andes had the highest concentration of endemic and small-range bird species. This finding updates priorities set by the National Bird Conservation

Strategy (Renjifo et al. 2001) that suggested the Central and Eastern Andes as areas of the highest conservation priority. Velásquez-Tibatá et al. (2013) also identified the

Western Andes as of the highest conservation priority for birds.

2.4.1 Importance of range updating

Updating the species’ ranges with new data showed that BirdLife International and NatureServe (2011)’s range maps underestimated important areas such as the northern part of the Western Andes: compare Figure 3a to 3b. This area was poorly studied for most of the twentieth century. Various studies in the last decade have

resulted in rediscoveries (Krabbe et al. 2006), species’ range extensions (Cuervo et al. 23 2003) and discoveries of new species (Robbins and Stiles 1999, Salaman and Stiles 2008,

Carantón-Ayala and Certuche-Cubillos 2010). Our study was limited by the limited locality data for some species, especially endemics, as has been the case with other

studies (Graham and Hijmans 2006, Velásquez-Tibatá et al. 2013). Updating bird ranges in all other areas of Colombia remains an important task because we may still be underestimating priority areas for conservation in Colombia.

2.4.2 Justification for refining ranges

The original range map for the Multicolored Tanager generally follows the known elevation limits of the species. Our refining by a detailed map of elevation only decreases the estimate range by 38%: compare Fig 1b and 1c.Without such refining, the

implied ranges sometimes be many times larger than is possible given the known elevational limits of the species (Harris and Pimm 2008). Much of the tanager’s currently proposed range lacks forest cover, however. Fragmentation and land use conversion severely reduce this species’ range because it is seldom found outside native forests

(Renjifo 2001).

After refining species’ ranges by elevation and remaining habitat, ,the overall distributions of endemic and small-range species are broadly the same: compare the four panels of Figure 3 The ranges became smaller and were highly fragmented, however

(Figure 3c-d). The majority of the BirdLife ranges included areas that no longer contain

24 habitat for the species due to recent severe deforestation and fragmentation. This finding is consistent with results of studies in the Atlantic forest in Brazil (Jenkins et al. 2010) and in Central America (Harris and Pimm 2008).

2.4.3 Reclassifying threat

For 13 Western Andes endemics, Birdlife considers 11 to be threatened. We recommend the remaining 4 species be reassessed. When we refined the ranges by elevation and remaining habitat, their sizes fell within the broad limits of other species

Birdlife deems threatened (Figure 5). We suggest this exercise be replicated for all endemic and small-range species in Colombia because their threat status could also be currently underestimated. Analyses of range fragmentation and threat categories have

been done successfully for the Atlantic Coast forest of Brazil, where Schnell et al. (2013) found that in addition to the 28 species already deemed threatened by IUCN, 30 more

might also be categorized as threatened.

habitat.

2.4.4 Western Andes conservation actions

The Western Andes had the highest concentrations of endemic and small-range bird species. Long et al. (1996) showed the Chocó Endemic Bird Area had more restricted range species than any other in the world. The western slope starts with lowland rainforest, rises to paramo, and extends through very humid cloud forests. 25

These areas are some of the best preserved in Colombia; the forests are almost completely intact (Cuervo et al. 2003). On the other slope, the landscape is extremely fragmented and covered by agricultural fields and urban areas (Forero-Medina and

Joppa 2010).

Between the 5 national parks in the Western Andes, large unprotected gaps remain (Figure 3, d). The southern part of the cordillera, bordering Ecuador, is also unprotected. Between Munchique and Farallones is a gap that could potentially connect these 2 important parks. Landmines cover some of this region. These prevent direct

conservation action, but they also impede logging and hunting and have allowed the

26 forest to remain intact. To the north of Farallones, ranges are evidently fragmented and lack protection. Land acquisition here is expensive due to dense human settlement and agriculture (Etter et al. 2011). Another large unprotected area is between Tatamá and

Orquideas, a region that has recently opened up for research after many years of social unrest.

Other than identifying particular large areas that one might hope the Colombian government might protect, we suggest the creation and enlargement of private protected areas that could complement the government’s efforts. Mesenia-Paramillo is a private reserve located between Tatamá and Orquideas National Parks, an area in need of conservation with high concentrations of endemic, small-range, and threatened species

(Figure 3). In Figure 6, satellite imagery shows a large continuous forest west of

Mesenia-Paramillo Reserve (star in Figure 3) that is protected by indigenous peoples and the regional authorities. To the east of the reserve is an approximately 10,000 ha area of forest under regional protection, with some private conservation areas. Deforestation threatens to isolate it. This situation encouraged Fundación Colibrí, a Colombian nonprofit organization, to acquire land for conservation in the crucial area between these forests. It purchased Mesenia-Paramillo Reserve (630 ha) in 2007. Currently, two foundations SavingSpecies (SavingSecies 2014) and SPN-The Netherlands (SPN 2013)

have contributed resources for acquiring more land. The reserve is currently 2500 ha and

27 continues to expand with new purchases. This private reserve will maintain the existing fragile connection between these forests and, through forest restoration, broaden it. This will provide more habitat for dozens of threatened and endemic species and thus

improve their conservation status.

Figure 6: Mesenia-Paramillo Reserve (green) and protected areas around it on a satellite image provided by Earthstar Geographics.

There are broad consequences of these protection actions. Many studies highlight global conservation priorities (e.g., Myers et al. 2000; Jenkins et al. 2013). Joppa et al.

(2011) asked the obvious question of how one can downscale from global strategic studies to practical actions. Jenkins et al. (2011) provide a case history for coastal Brazil, and here we provide another for Colombia. Four key recommendations emerge as likely having international relevance.

First, regional or international conservation priorities must be downscaled to practical geographical extents that allow conservation actions. Merely saying the

Northern Andes of South America or the Western Andes of Colombia is a priority is not enough.

Second, while strategic conservation priorities may change slightly as better data on vertebrates (Jenkins et al. 2013) and quantitative information on other taxa (such as plants (Joppa et al. 2011)) become available, there is broad agreement on the location of the hotspots. Most priority setting studies assume species occur across their entire

original ranges. Based on our work, we recommend demarcating these ranges by

29 elevation and by remaining habitat. Such information is extremely important in making tactical recommendations for land protection. Habitat cover is continually changing, of course.

Third, inadequate knowledge of species ranges affect these priorities, as is the case in Colombia because of its recent history. We recommend updating these conservation priorities as knowledge of species’ ranges improves.

Finally, we recommend complementing national protected areas, such as national parks, with smaller, strategically positioned, private reserves. Mesenia-

Paramillo Reserve provides an example. Enactment of private reserves would be a small-scale effort, but it would likely be highly effective at preventing the isolation of

large areas of habitat and restoring their habitat connections. Restoration of degraded land and reconnection of forest fragments may involve land acquisitions small enough

for regional conservation organizations and even individuals to effect.

3. Bird conservation complements landslide prevention in the Central Andes of Colombia

3.1 Introduction

From October 19th to 29th, 2011, an estimated 400,000 people in the city of

Manizales, in the Central Andes of Colombia, lost all access to their water supply. The cause was a major landslide that broke two main pipes transporting water from the cloud forests and paramos to the city, causing millions of dollars of economic loss.

In montane areas with abundant rainfall, seismic activity, volcano-ice

interactions and natural erosion processes, landslides are a natural process and key

disturbances (Restrepo and Alvarez 2006, Huggel et al. 2007). The overexploitation of 31 natural resources and deforestation increase the magnitude and frequency of landslides by removing the vegetation and root matrix that hold soil in place, however (Allan 2004,

Keefer and Larsen 2007). Climate change will likely worsen the frequency and magnitude of landsides (Nadim et al. 2006). Cleared forests on steep slopes are especially vulnerable to landslides, while areas affected by landslides are ideal for restoration of forest cover. Restoring forests would reduce the risk of further disasters.

Tropical montane areas also house high levels of biodiversity. The northern

Andes have high numbers of endemic and threatened vertebrate taxa (Jenkins et al.

(2013). Similarly, Joppa et al. (2010) showed the region to have exceptional numbers of plant species, many of which are endemic, and they predicted it to have large numbers 31

of undiscovered species. In particular, the Central Andes holds 56 endemic and small- ranged bird species (Ocampo-Peñuela and Pimm 2014). Human settlement and land clearing for agriculture (Etter et al. 2006, Etter et al. 2011) have extensively fragmented their ranges (Ocampo-Peñuela and Pimm 2014), so many species are at risk of extinction.

Forest restoration in areas of high endemism and small-ranged bird species would have the greatest conservation benefit as exemplified also by Important Bird Areas (Franco et al. 2009).

We prioritize conservation and restoration areas in the Central Andes of

Colombia, with a localized case study in the Rio Blanco Reserve, near the city of

32 Manizales. Our aim is to find places where conserving or restoring an area would provide habitat for endemic and threatened bird species, while contributing to landslide prevention. We then extrapolate this exercise to the entire Central Andes ecoregion

where comparable landslide occurrence data were not available.

Colombia’a Article 111 of Law 99 of 1993 provides for the purchase of land for conservation and restoration in watersheds that provide water to towns and cities. We conducted this priority setting exercise to facilitate the implementation of Article 111 at the Rio Blanco Reserve (Aguas de Manizales), and at other municipalities in Colombia.

Article 111 states that “all municipalities and departments must invest at least 1% of their revenue in purchasing or maintaining land that protects watersheds, or in paying

for ecosystem services that contribute to the same goal during 15 years, starting in 1999”

(Ministerio del Medio Ambiente 1993). Although this Article provides an avenue for the conservation of biodiverse lands, it has rarely been implemented.

Local and regional governments have largely neglected the law. After 15 years, only 0.12% of the revenue was invested in land purchasing and fewer than half of the municipalities, and a third of the departments implemented the law (Rudas 2010). In some cases, the revenue funds have been spent on other activities. In other cases, local governments have found it difficult to identify the land to purchase for conservation

(Rudas 2010). In response, Decree 0953 delineated new guidelines for Article 111 and

33 was published in 2013 (Ministerio de Ambiente y Desarrollo Sostenible 2013). The new decree details the source of the 1% of the revenue and lays out specific investment rules.

The new Decree allows local governments to pay for ecosystem services, such as

hydrological regulation and sediment and erosion control, as they ready for land purchases.

Prioritization strategies are highlighted to include: improvement of water quality, presence of water sources, aquifer conservation, natural land cover, areas vulnerable to anthropogenic pressure, and ecosystem connectivity (Ministerio de

Ambiente y Desarrollo Sostenible 2013). The goal of our study was to contribute to developing these strategies for identifying lands that should be purchased for

conservation. We do this by mapping areas important for conservation of existing forest, and restoration to natural forest of current cattle pasture and croplands.

3.2 Methods

3.2.1 Study area

Bird diversity in Colombia is the World’s highest with 1834 species, with 77 endemic species (Stiles et al. 2014). Of the total, 106 species are listed as threatened by the International Union for Conservation of Nature (IUCN) (BirdLife International 2014).

The high diversity is partly explained by the unique geography of the Andes in

Southwestern Colombia, where it divides into three cordilleras: the Eastern, Western,

34 and Central. All three are identified as priority areas for biodiversity (Jenkins et al. 2013) and are inside the Tropical Andes biodiversity hotspot (Myers et al. 2000), one of the three hotspots found in Colombia. The Western Andes hold the highest numbers of

endemic and small-range bird species, followed by the Eastern cordillera (Cuervo et al.

2003, Kattan et al. 2004, Ocampo-Peñuela and Pimm 2014). Although the Central Andes are not as diverse as the other two cordilleras (Kattan et al. 2004), they house 16 endemic and 6 threatened species in a given place (Ocampo-Peñuela and Pimm 2014).

Importantly, the Central Andes is the most threatened cordillera: over 70% of

Colombia’s population has settled on the Andes with highest densities in the Central

Andes (Etter and Van Wyngaarden 2000), resulting in significant land conversion for agriculture (Etter et al. 2011), and habitat fragmentation (Etter et al. 2006).

Coupled with high bird diversity, the Andes are prone to landslides and avalanches due to their steep terrain and high rainfall (Nadim et al. 2006, Huggel et al.

2010). The Central Andes are specifically vulnerable to these phenomena due to their characteristic geological and geomorphic conditions, wet climate, and location. Our specific study area is located near the Ruiz and Bravo volcanoes, on a seismically active region, increasing its vulnerability to erosion and landslides locally (Westen and Terlien

1996).

35 We studied the Reserva Forestal Protectora de Río Blanco y Quebrada Olivares

(hereafter the Rio Blanco Reserve), located 3.5 km from the city of Manizales, on the western slope of the Central Andes of Colombia, in the department of Caldas (Figure 7).

The Rio Blanco Reserve covers 49.32 km2, with 17.76 km2 (36%) in pasture for cattle and

0.8 km2 in pasture for cattle rotating with potato crops. The rest is forest (62%). The elevation rises from 2,000 to 3,800 meters above sea level and the dominant ecosystem is cloud forest. It has some paramo areas at higher elevations and houses 409 species of plants, 344 birds, and 41 mammals (Corpocaldas et al. 2010).

Rio Blanco Reserve was declared a protected area in 1990 as part of the conservation corridor around Los Nevados National Park, which conserves 49 km2 of

paramo, Andean forests, and glaciers (Figure 7, b). The reserve currently provides 35% of the potable water to the city of Manizales. Some of the threats to the forests of the area include landslides, cattle ranching, potato plantations, and densely planted introduced

trees (Corpocaldas et al. 2010).

Figure 7: Study area. (A) Map of Colombia (B) Localized study area near Manizales.

3.2.2 Landslide susceptibility index

A landslide susceptibility index expresses the likelihood of landslide occurrence in an area based on local terrain conditions (Brabb 1984). We developed a simple landslide susceptibility index for the Rio Blanco Reserve using slope, aspect, stream proximity, and the presence or absence of forest cover. Other studies have developed susceptibility indices using a suite of variables, including rainfall (Farahmand and

AghaKouchak 2013), slope, aspect, stream proximity, and landcover (Perotto-Baldiviezo et al. 2004). Landcover, slope and aspect tend to be the strongest predictors of landslide

hazard (Perotto-Baldiviezo et al. 2004).

37 Our landslide susceptibility index ranges from 0 to 100, with 100 indicating the highest risk. All input variables were transformed into weighted index values following guidelines used by Perotto-Baldiviezo et al. (2004), but adapting the weights to the local

context. The variable with the highest weight was slope (40), followed by forest cover

(30), stream proximity (20), and aspect (10) (Table 1).

Table 1: Input variables to the landslide susceptibility index, and their associated weighted values, for the Rio Blanco Reserve

Layer Categories Index Value 0-12 % 0 12-30 % 10 Slope 30-60 % 20 60-100% 30 >100 % 40 Forest 10 Forest cover No forest (grass, crops, bare soil) 30 Stream Proximity 0-300 m 20 37

300-500 m 10 >500 m 0 N 0 E 5 Aspect W 5 S 10

We derived the slope and aspect from a 90m Digital Elevation Index (Jarvis et al.

2008) using tools from ArcMap 10.2 (ESRI 1999-2010) and downscaling the resolution to

30 m using nearest neighbor cell resampling. We generated a slope scale of 0-100% steepness, and divided the aspect into 4 directions (Table 1). We derived the forest cover

(forest/not forest) from data produced by Hansen et al. (2013) at a 30 m resolution for the

world using LANDSAT images. Stream proximity was calculated in three categories 38 using the Kernel Density tool in ArcMap 10.2 (ESRI 1999-2013). The resulting landslide susceptibility index has a 30 m resolution.

We tested the accuracy of the landslide susceptibility index using georeferenced data collected in 2013 for landslide occurrence. We used 68 points for landslide presence and 29 for landslide absence (Appendix 4). Aguas de Manizales personnel collected these points both inside the Rio Blanco Reserve and in areas 10 km to the south of it. In

January of 2014, we collected data in different types of landcover (forest, open grass, elfin forest, and paramo), where landslides had not occurred in order to test our landslide susceptibility index. We used a confusion matrix to determine the overall accuracy of our landslide susceptibility index as well as user and producer’s accuracy 38

(also known as commission and omission error).This is the most widely used method in remote sensing (Foody 2002). We could not test the index’s accuracy more widely in the

Central Andes regions due to the lack of publically available georeferenced landslide data.

3.2.3 Birds

For the purpose of this study, we considered only terrestrial diurnal bird species that were either endemic or had a range smaller than 100,000 km2, and whose range included the Central Andes region (Appendix 5). We started with the range maps

provided by BirdLife International and NatureServe (2013) and refined it by suitable 39 elevation following each species’ altitudinal requirements. (The detailed methods are in

Harris et al. (2005) and Ocampo-Peñuela and Pimm (2014)). The resulting range included only areas that were within the lowest and highest elevational limits ever

recorded for the species in field guides or in the BirdLife factsheet (Hilty and Brown

1986, Restall et al. 2006, BirdLife International 2012). Refining by elevation prevents us from including areas that are potentially not occupied by a species (Harris and Pimm

2008).

Finally, we mapped the ranges of the 56 endemic and small-range bird species whose distributions were restricted to or included the Central Andes. We then looked for areas that had high concentrations of species.

3.2.4 Conservation and restoration areas

We consider potentially good conservation areas those that have a high risk of landslides (as shown by our landslide susceptibility index), and high concentrations of endemic and small-range bird species (as depicted by our bird maps) in areas covered by forest. We define restoration areas as those that have these same characteristics, but lack forest cover. To visualize the results, we divided landslides into two categories based on our landslide susceptibility index: 0-60 and 60-100; and, divided bird concentrations into two categories: 0-6 species and 7-14 species. Then, we compared

these two layers to find conservation areas where high landslide risk and a high

40 concentration of endemic and small-range birds overlapped. To identify restoration areas in the Rio Blanco reserve, we overlapped our conservation priorities with forest cover to find potential areas for restoration. We narrowed the priorities further by

ordering areas according to their restoration urgency using kernel density in ArcMap

10.2 (ESRI 1999-2010). Areas very close to known landslides, we selected as first priority, and second and general priorities are further away from the landslide center.

For the Central Andes, we mapped human population density (Tatem et al. 2013) and main roads in relation to the conservation and restoration areas prioritized in our exercise. We would have liked to have mapped the main water pipe conducts but this information is not publicly available. Our aim was to evaluate the extent to which

restoring the proposed areas would prevent landslides on main roads or near populated areas, thus providing an ecosystem service.

3.3 Results

To identify landslide susceptibility in the Central Andes of Colombia, we created an index using slope, aspect, stream proximity, and forest cover (Figure 8). For landslide sites, the forest layer showed that 77% of the points lacked forest. As for slope, 4.5% sites were on slopes with a weighted value of 30, 50% a 20 value, and 43% a 10 value. Thirty-

four percent were located near a stream (0-300m). Twenty-eight percent were on the 41 southern aspect, which is most vulnerable to landslides. Sites without a landslide showed a different pattern. Although for forest cover the values were similar, with 70% of the points lacking forest for the absence points, only 6.9% of the points were in the 30

slope category and 24% in the 20 slope category, less steep in general. Only 7% of the points fell within the most vulnerable stream proximity category, and 15% within the most susceptible aspect.

proximity derived from a stream layer. (D) Aspect derived from Digital elevation index (Jarvis et al., 2008).

Our landslide susceptibility index had an overall accuracy of 55% based on the confusion matrix (Table 2). The index predicted past landslides correctly 90% of the time, but it tended to overestimate landslide presence, i.e. the commission error. In 39% of the time landslide absence was predicted accurately, i.e. omission error. Nonetheless,

90% of the time the index predicted a lack of landslides where observed points confirmed the absence. Two factors affected the accuracy of the model: (1) some landslide absence points are in paramos, naturally tree-less ecosystems (van der

Hammen and Cleef 1986); and, (2) some landslide presence points were inside the forest, in areas that not visible to remote sensors, but clearly identified as dangerous by field workers.

Table 2: Confusion matrix for landslide susceptibility index in the Rio Blanco Reserve.

Observed Landslide No Landslide

Landslide 27 41 0.40 Predicted User’s Accuracy No Landslide 3 26 0.90 43 0.90 0.39 0.55 Overall Accuracy Producer’s Accuracy

To compliment landslide susceptibility, we mapped endemic and small-ranged

bird concentration (Figure 9c-d). Maximum concentration in a given place was 14

species and it was mostly concentrated at mid-elevations, excluding paramos (above

3000) and sub-Andean forests. Over half of the Rio Blanco Reserve fell within the 7-14 species category indicating the importance of this site for bird conservation.

We simplified endemic and small-range bird concentration and the landslide susceptibility index layers (Figure 9). Purple pixels correspond to areas that we consider appropriate for conservation due to high landslide susceptibility and endemic and small-range bird concentration. We identified 5.5 km2 as potential conservation areas.

Some of these conservation areas were inside forest (72%), and a few were in cattle 45 pasture or crop land (28%). We overlapped these conservation priorities with a forest cover map to further prioritize restoration areas lacking forest (Figure 10), leaving 1.57 km2 as high priority for restoration. Of these 0.21 km2 are first priority, 0.24 km2 are of

secondary priority, and the remaining 1.12 km2 are of general priority.

ecosystem (above 3500 m) shown in gray.

Using the method that we developed for the Rio Blanco Reserve, we mapped conservation and restoration priorities for the Central Andes using the same criteria: landslide susceptibility, endemic and small-ranged bird concentrations, and forest cover, but added population density and roads (Figure 11).

from the WorldPop dataset (Tatem et al., 2013)), and roads for the coffee-growing region (A), and the Medellin area (B).

We identified 1980 km2 of potential conservation areas in the Central Andes region that present high landslide susceptibility and high concentrations of endemic and small-ranged bird species. This accounts for 27% of the total area. After overlaying these priorities on areas lacking forest, 886 km2 (12%) remained potential areas of forest cover restoration. To further prioritize restoration areas, we examined the location of the restoration areas in relation to roads and human population density. We consider those

areas close to densely populated areas and roads, of crucial importance. Areas we 48 highlight (Figure 11A-B) include major cities of Colombia like Medellin, Pereira,

Manizales, Armenia, and Ibague, all with populations above 400,000.

3.4 Discussion

Inspired by the November 11th landslide event near Manizales, and the current poor results of Article 111 as a conservation measure (Rudas 2010), we set out to prioritize conservation and restoration areas where landslide prevention would be coupled with bird conservation.

We found landslides to be common on steep slopes and areas that lack forest cover. Lack of forest cover is a main contributor to landslide susceptibility, and a major

triggering effect (Dai and Lee 2002, Keefer and Larsen 2007, Huggel et al. 2010).

Steepness is often associated with landslide susceptibility (Carrara et al. 1991, Dai et al.

2002). Additionally, Perotto-Baldiviezo et al. (2004) found slope and landcover to be the main determinants for landslide hazard in Honduras, in accordance with our data in

Colombia.

Our landslide susceptibility index had an overall accuracy of 55%. Although not the ideal 85% accuracy proposed for landcover classification (Congalton 1991, Nishii and

Tanaka 1999), our index predicts 90% the known landslides acting as a strong

susceptibility measure and exhibiting great potential for restoration to prevent

49 landslides.

Landslides are serious threats to human lives, social welfare, and local economies

(Huggel et al. 2010). Preventing them is important. The risk is highest in countries with

large portions of arable land and significant resulting forest conversion, but overall high national forest cover like Colombia (Nadim, Kjekstad et al. 2006, Farahmand and

AghaKouchak 2013).

Montane areas with high landslide susceptibility also house high concentrations of endemic and small-range bird species. We identified 5.5 km2 as potential conservation areas where these two conditions overlapped in the Rio Blanco Reserve. We further prioritized restoration areas by overlapping our conservation priorities with a forest

cover map. A smaller area of 1.57 km2 is ideal for forest cover restoration, with 0.21 km2 being first priority, and 0.24 km2 second priority.

Few studies combine the protection of vulnerable species with the provision of ecosystem services as we have done for the Central Andes. Successful examples in

Ecuador, Costa Rica, and New York City show watershed protection to benefit ecosystem services like potable water availability in cities (Postel and Thompson 2005).

However, the goal is often species conservation (Kattan 1992, Orsi et al. 2011), setting new protected areas (Jenkins et al. 2010), or the protection of ecosystem services alone

(Costanza et al. 1997, Chan et al. 2006, Naidoo et al. 2008). Ecosystem services are

50 fundamental for the survivorship of all species, but the provision of these is imperiled by anthropogenic activities (Daily et al. 2000). For instance, we know that whenever human activities, such as agriculture and cattle grazing, are associated with watersheds,

bank stability may decrease (Allan 2004) and soil water retention capacity increases

(Harden 2006), causing landslides. We also know that Andean birds cannot survive in the absence of forest (O’Dea and Whittaker 2007).

As conservation biologists, we would like to purchase and set aside the 5.5 km2 we identified as priority for conservation. However, we know this is not possible, especially here because land is very expensive. In light of Article 111 and recent decree

0953, Aguas de Manizales has the responsibility to expand the Rio Blanco Reserve each

year. With our priority setting exercise we have downsized the priority areas from 17.76 km2 that are currently pasture or crops to 5.5 km2 (31%) which are conservation priorities, and further to 1.57 km2 which are restoration priorities, and 0.21 km2 which are the most urgent sites. Rio Blanco is one of the most popular bird watching sites in

Colombia thanks to the presence of endemics like the Masked Saltator and the

Bicoloured Antpitta, restoration of degraded land would expand the area for bird watching and other nature-related activities. Although restoration might take several years, Aguas de Manizales has conducted paramo restoration at higher elevations and

have been successful at recovering organic matter cover by using appropriate plant

51 species. We invite other montane municipalities in Colombia to replicate this exercise.

This will contribute to guide the investment of the US$20 million that are available for land purchase in the country, about one third of the National System of Protected Areas’

annual budget (Rudas 2010).

As a first step towards the use of this method in other montane areas, we extrapolated our priority setting exercise from the Rio Blanco Reserve to the Central

Andes (Figure 11). We identified 27% of the Central Andes as potential conservation areas, and 12% as potential restoration areas. However, 886 km2 is a large area to purchase and restore, so we further narrowed our priorities by mapping population density and roads. Restoring priority areas near cities would enhance ecosystem services

bringing economical and social benefits to the cities (Daily et al. 2000). Landslide prevention near roads contributes to lower human deaths and operation costs. In

Colombia, landslides are the main cause for road closing (INVIAS-Instituto Nacional de

Vias 2014) and have been shown to generate significant damage locally (Huggel et al.

2010). Figure 5 shows several potential restoration areas in the vicinity and within the cities of Manizales, Pereira, Armenia, Ibague, and Medellin, some of Colombia’s largest populated centers. Land near cities is probably more expensive but also in more urgent need of restoration.

We presented a simple priority setting exercise for selecting conservation and

52 restoration areas that could be purchased following Article 111 and Decree 0953’s guidelines and enhancing biodiversity and ecosystem service conservation. We understand the limitations of applying a local index to a general region like the Central

Andes and encourage the application of this index in other places using complimentary variables (soil, precipitation, volcanic influence, etc.) and updated georeferenced landslide data.

4. Elevational ranges of montane birds and deforestation in the Western Andes of Colombia

4.1 Introduction

Deforestation causes habitat loss, fragmentation, and degradation, and can ultimately cause the extinction of the remnant species (Brooks et al. 1999b, Brooks et al.

1999c, Laurance 1999, Pimm and Jenkins 2005, Moura et al. 2013). In the tropics, these are the main drivers of immediate and delayed extinction in birds (Sodhi et al. 2004).

Researchers have studied the effects of habitat loss and fragmentation and identified

edge effects (Robinson et al. 1995, Laurance et al. 2011a, Haddad et al. 2015), loss of

landscape connectivity (Krosby et al. 2010), reductions of population sizes (Andren 53

1994), and ultimately influence on genetic structures of populations (Moore et al. 2008,

Dixo et al. 2009) as the major contributors to species vulnerability to extinction.

Endangerment and extinction are likely not the result of one of these causes, but rather a

synergy of processes which will likely be exacerbated by climate change (Brook et al.

2008).

Geographic ranges of species have been used to study species vulnerability

(BirdLife International 2014) and inform conservation decisions with a wide range of success (Orme et al. 2006, Jenkins et al. 2011, Ocampo-Peñuela and Pimm 2014). From previous studies, we know that species with the smallest geographical ranges, such as those found on mountains or islands (Orme et al. 2006), are the most threatened with 53

extinction (Renjifo et al. 1997, Brooks et al. 1999b), and will be more severely affected by climate change (Shoo et al. 2005, White and Bennett 2015). Remnant populations of birds, for instance, are often restricted to mountain ranges (Channell and Lomolino

2000) and thus we expect the larger number of future extinctions to be on mountain tops

(Sekercioglu et al. 2008, Forero-Medina et al. 2011). Projections of range contraction in response to climate change anticipate 400 bird species reducing their ranges by half, although in the tropics the main cause of range contractions remains land-use change

(Jetz et al. 2007).

We know that specialized bird species disappear soon after the disturbance from

54 deforested areas, and slowly from remaining forest fragments (Brooks et al. 1999c).

Here, we explore one neglected question: do species adjust their elevational ranges in response to the loss of natural habitat below them? We compare species ranges from

completely forested transects to those that have lost forest from lower elevations. We anticipated differences, expecting that across comparable elevational spans species would have larger ranges when there was forest below than when there was not. Some species might well be absent near the lower end of their range if there is a forest edge because of the added harm that befalls them there (Restrepo and Gómez 1998, Laurance

2004).

Our motivation is both to add to the body of literature on the effects of habitat loss and to understand the effect of lowland deforestation on the elevational ranges of species. An increasing number of studies search for long-term changes in species distributions along elevational transects driven by changes in the global climate

(Böhning-Gaese and Lemoine 2004, Shoo et al. 2005, Peh 2007, Velásquez-Tibatá et al.

2013). We still need to understand the potentially confounding effect of lowland deforestation in the face of climate change (Brook et al. 2008).

We chose the Northern Andes as our study area as it is one of the most diverse

areas in the world (Myers et al. 2000, Jenkins et al. 2013). In the Western Andes of

55 Colombia, concentrations of endemic and threatened birds peak at 46 species in specific areas (Ocampo-Peñuela and Pimm 2014) and the diversity of other taxa is also high

(Kattan et al. 2004).

In addition, Neotropical birds, and especially those preferring higher elevations, have narrower ranges than birds in other regions, making them more vulnerable to extinction (Blackburn and Gaston 1996, Sekercioglu et al. 2008, Sorte and Jetz 2010,

Laurance et al. 2011b, White and Bennett 2015). When faced with habitat loss and climate change, species with narrow niches and poor dispersal ability will be severely affected (Travis 2003), while generalists and mobile species may thrive (Warren et al.

2001).

We evaluate the effects of deforestation on the elevational ranges of montane birds, specifically their mean and minimum elevations, and elevational range width. In addition to analysing the effect on species, we tested its impact across different trophic guilds and habitat preferences. We are unaware of previous studies designed to use extensive elevational transect fieldwork to evaluate impacts of lowland deforestation in the species that remain at the still forested higher elevations.

Previous studies have found bird extinction risk increases as elevational ranges become smaller. We predicted that deforestation in the lower portion of an altitudinal

transect might disproportionately impact the elevational ranges of bird species with

56 narrow elevational ranges and those that prefer forest interiors, or depend on seasonal food resources (such as nectar or fruit). Species with narrower elevational ranges lack the option to find refuges from anthropogenic disturbances, increasing their extinction

risk (Laurance et al. 2011b, White and Bennett 2015). We expected species’ mean and minimum elevations to be at higher elevations in transects lacking forest in the lowlands, since some montane birds are altitudinal migrants and will likely be forced to move up in search of resources, especially fruit and nectar-eating birds. As for elevational range width, we expected a contraction in partially deforested transects, in accordance to previous studies that predict range contractions due to habitat loss

(Rodríguez 2002).

4.2 Materials and methods

4.2.1 Study area

Colombia’s Andes have three main cordilleras; the Western lies between the

Pacific Ocean and the Cauca Valley. The Western Andes of Colombia have the highest diversity and endemism of birds (Cuervo et al. 2003, Lee et al. 2005, Ocampo-Peñuela and Pimm 2014), rodents, bats, butterflies, and frogs in the country (Cuervo et al. 2003,

Kattan et al. 2004). The east and west slopes of this cordillera differ in their climate and

conservation status. The east slope is located in a rain shadow, making its climate more

57 arid than the moist west slope which receives winds from the Pacific Ocean (Kattan et al.

2004). Most of the human population in the Western Andes lives on its east slope and causes severe disturbances from agricultural use and cattle grazing (Cuervo et al. 2003).

Forests remain large and connected along the west slope, due to the lack of road access

(Robbins and Stiles 1999, Forero-Medina and Joppa 2010), and the presence of groups of political insurgents.

Our study took place in the Mesenia-Paramillo Nature Reserve (henceforth

Mesenia-Paramillo) located in the municipality of Jardín, in Antioquia (Figures 12a, b). It lies between Tatamá and Orquídeas National Parks, and currently covers 3000 ha.

Mesenia-Paramillo was purchased by Fundación Colibrí in 2007 and continues to

expand its conservation area. Elevations span 2200 to 3200 meters above sea level (masl), ranging from Andean cloud forests to paramos. The reserve conserves large concentrations of endemic and small-ranged bird species (Ocampo-Peñuela and Pimm

2014), as well as significant diversity of other taxa (Fundación Colibrí 2015).

Figure 12: a) Location of Colombia in South America. . b) Location of Mesenia- Paramillo Nature Reserve over a forest cover map from Hansen, Potapov (45). c) Location of forested and partially deforested transects and their respective mist-net and point count locations in Mesenia-Paramillo Reserve. Background image from satellite RapidEye for dates 28/12/2013-01/04/2014. Displayed here with permission from Saving Species (www.savingspecies.org) and in line with agreement from seller BlackBridge.

4.2.2 Field Methods

Between April 2014 and March 2015, we surveyed six altitudinal transects for bird species richness and abundance using point counts and mist-nets. Three transects had forest from 2200 to 2800 m (Figure 12 c, teal). The other three transects only had forest between 2400 and 2800 m; between 2200 and 2400 there were pastures (Figure 12 c, orange). Henceforth, we will refer to these transects as “forested” and “partially deforested”, respectively. Partially deforested transects have not had forest cover for at least 40 years, with no forest regeneration, as we observed in historical satellite imagery.

In a similar way, forested transects have remained forested for at least 40 years. The

60 forest in all transects had no obvious differences in plant structure and composition, but we acknowledge the fact that other factors could be influencing bird communities in these transects. We conducted all surveys inside forest, excluding paramos and pastures.

Although we collected bird data from 2200 to 2800m, we only compared bird data from the forested part of both transects (2400-2800m) because we were interested in the changes to the elevational ranges of birds in the remaining forest. Bird diversity and structure was strikingly different below 2400m due to the lack of forest in partially deforested transects.

Point counts are generally the preferred method for assessing bird richness and abundance (Bibby et al. 1993). Although measuring distance to each observation is

recommended (Buckland et al. 2001), this was not possible in the dense and complex cloud forest of the study site, especially because montane birds often move in mixed species flocks (Bohórquez 2003). To keep abundance estimates as accurate as possible, we had fixed-distance point counts with a 25 m radius.

We placed point counts every 150 linear meters spanning 2400 to 2800 m following methods suggested by (Ralph et al. 1993). We measured the elevations and distance using a handheld GPS. Due to differences in topography, some transects had more point counts than others: the three forested transects had a total of 24 point counts

while partially deforested transects had a combined 27 point counts. Point survey

61 started at 0600 h and generally went until 1000 h. In each point count, a single observer recorded every bird seen or heard during 12 minutes; within and outside the fixed distance of 25 m. Observers were experienced with the region’s birds and especially

their calls. We surveyed each point 20 times, alternating the order of the surveys to keep the effort standard. To control for unknown impacts of altitudinal migrations, repetitions of point count surveys for all six transects were distributed along one year as follows: 8 repetitions between May and October of 2014, 6 in November and December of 2014, and an additional 6 between January and February of 2015. We did not survey during rain or severe winds.

At each transect we had five mist-netting stations located every 100 altitudinal meters (2400, 2500, 2600, 2700, and 2800) inside forest. We operated fifteen 12 m, 36mm mesh size, mist-nets at each station for a total of 600 net/hours, generally lasting 4 to 5 days. Operating protocol generally followed (Ralph et al. 1993). We mist-netted on 2 transects at the same time, using two separate field teams, between April and September of 2014. We opened nets before sunrise at 0530 and closed them before sunset at 1730, except in the presence of rain or severe winds. One experienced bander and an assistant checked nets every 30 minutes and identified, banded, and released each captured

individual.

62 4.2.3 Data preparation

We used two different types of data to answer our research questions: species richness, and species relative abundance. For species richness (presence/absence), we

used data from both point counts (inside and outside the fixed distance) and mist-nets.

When analysing species relative abundance, we only employed data from inside the 25m point count radius because this method had more repetitions and thus better seasonal representation. Additionally, we only captured 18 species in mist-nets that were not observed in point counts. Most of these mist-net exclusive species we captured only once.

For all analyses, we grouped the three forested transects, and the three partially deforested transects and treated them as forested and partially deforested respectively.

For each point count, we considered relative abundance as the sum of the counts on the

20 repetitions. We compared the two types of transects based on elevational range variables: mean, minimum, and elevational range width. For the mean elevation, we used abundance from point counts to weight the mean by taking the sum of each count, multiplying it by its elevation, and then dividing that sum by the sum of all elevations.

Abundance-weighted mean elevations are more appropriate for understanding the

distribution of the species along the altitudinal transect (Forero-Medina et al. 2011). The

63 minimum and maximum elevations were the extreme observations of a species on any transect replicate. The elevational range width is the subtraction of the minimum elevation from the maximum. We determined range width for each species as the

average of the three transect replicates.

Following analyses at the species level, we compared ecologically meaningful groups classifying each species in a specific trophic guild and habitat preference category. We assigned groups based on information found in the “Handbook of the

Birds of the World Alive” (del Hoyo et al. 2015), and the “Guide to the Birds of

Colombia” (Hilty and Brown 1986). We assigned a trophic guild category to each species based on accounts of its major food source: nectar, fruit, seeds, insects, or meat. For

analyses, we excluded raptors that have very broad ranges and are likely not as constrained by changes in land cover at different altitudes. We also excluded seed eating species because this category had only 11 species.

We also classified species into one of four habitat categories according to their habitat use accounts from (del Hoyo et al. 2015): interior (only when the word “interior” was explicitly used and when the text indicated edge avoidance), edge (only when the word “edge” was explicitly used), forest (when the species uses forest but there is no statement of interior or edge), and non-forest (when explicitly stated as not using forest).

We excluded the non-forest category because it only had two species, both present only

64 in partially deforested transects.

4.2.4 Data analysis

Using 134 species found in both forested and partially deforested transects, we

tested if species’ elevational ranges were higher in partially deforested transects. We ran one-tailed, one-factor ANOVAs for variables: abundance-weighted mean, minimum elevation, and range width using the statistics package R (R Core Team 2015). For the range width, we excluded species that we only recorded once. This process eliminated

37 species from forested transects, and 31 from partially deforested transects.

We also tested if the presence of forest below 2400 m affected species in the various trophic guilds and habitat preference categories differently. We analysed these

effects using two-factor ANOVAs in R (R Core Team 2015). Using the previously established elevation variables (abundance-weighted mean, minimum, and elevational range width) as response variables, we evaluated the factors trophic guild/habitat preference, and presence of forest below 2400 m. When the ANOVAs were at least marginally significant (p<0.1), we ran TukeyHSD tests for more detail on the effect analysed. We treated range width as in the species analyses and eliminated zero values.

4.3 Results

During our field season, including point counts and mist-nets, we recorded 227 65 species in 39 families in Mesenia-Paramillo (Appendix 6). Nine of the species recorded are deemed threatened by the International Union for the Conservation of Nature

(BirdLife International 2014): the critically endangered Munchique Wood-wren

(Henicorhina negreti), the endangered Chestnut-bellied Flowerpiercer (Diglossa gloriosissima), Yellow-eared Parrot (Ognorhynchus icterotis), Magdalena Tapaculo

(Scytalopus rodriguezi), and the vulnerable Bicoloured Antvireo (Dysithamnus occidentalis),

Tanager Finch (Oreothraupis arremonops), Ruddy Pigeon (Patagioenas subvinacea), White- capped Tanager (Sericossypha albocristata), and Red-bellied Grackle (Hypopyrrhus pyrohypogaster). Of these threatened species, four are endemic to Colombia (Munchique

Wood-wren, Chestnut-bellied Flowerpiercer, Magdalena Tapaculo, Red-bellied

Grackle), and an additional three non-threatened species are also endemic: Stiles’

Tapaculo (Scytalopus stilesi), Paramo Tapaculo (Scytalopus canus), and Chestnut Wood- quail (Odontophorus hyperythrus). As far as we know, this is the first time the Magdalena

Tapaculo has been recorded this far north.

Forested transects had 179 species (171 in point counts and mist-nets, 8 incidental observations outside standardized point counts) in 37 families, while partially deforested transects had 192 species (177 in point counts and mist-nets, 15 incidental observations outside standardized point counts) in 36 families. Differences between

species composition and families of the two types of transects were not statistically

66 significant (two sample t-tests, t = 0.409, df = 37, p-value = 0.685). Of the endemic species, five were present in both types of transects (Chestnut Wood-quail, Paramo Tapaculo,

Munchique Wood-wren, Chestnut-bellied Flowerpiercer, Red-bellied Grackle), and two

were unique to forested transects (Magdalena Tapaculo, Stiles’ Tapaculo).

We predicted that species’ mean elevational ranges and minimum elevations would be higher and elevational ranges narrower in partially deforested transects. A comparison of 134 species shared by forested and partially deforested transects showed no statistically significant differences between the abundance-weighted mean and minimum elevations (Figures13a, b). Figure 13c shows that species in forested transects had mean range width 208±77 m, while those in partially deforested transects had

marginally narrower elevational ranges with average 186±83 m (F= 2.575, p=0.055).An additional 26 species, not included in the analyses, had at least two observations in forested transects but only one in partially deforested transects (13 species), or at least two in partially deforested transects but only one observation in forested transects (13

species).

We tested if species of distinct trophic guilds or habitat preference categories showed significant differences in their elevational range variables. Figure 14 shows the elevational range variables for different trophic guilds for forested and partially deforested transects. Results from two-factor ANOVAs showed no statistical significance of trophic guild in the abundance-weighted mean and minimum elevations of the two types of transects (Figures 14a, b). It is important to note, however, that nectar-eating birds had considerably higher abundance-weighted mean elevations in partially deforested transects than other guilds. Elevational range width, in contrast, was

marginally significantly different between forested and partially deforested transects,

68 but the differences were explained mostly by the type of transect (F=2.613, p=0.054), and not the trophic guild (F=0.708, p=0.494) (Table 3). Fruit-eating birds showed no discernible trend, while insect and nectar-eating birds had considerably wider ranges in

forested transects. These results confirm those in Figure 13c, in that forested transects ranges are wider.

Figure 14: Comparison of elevational range variables per trophic guild for 69 forested and partially deforested transects (p values shown are for one-tailed two- factor ANOVAs). a) Abundance-weighted mean elevation. b) Minimum elevation. c) Elevational range width. Dots represent outliers.

Table 3: Results from one-tailed ANOVA test comparing elevational range width of different trophic guilds, in forested and partially deforested transects.

Df Sum Sq Mean Sq F value Pr(>F) Guild 2 13195 6597 0.708 0.494 Forest 1 24349 24349 2.613 0.054 . Residuals 189 1761327 9319 *** ** p<0.001 p<0.01 * p<0.05 . p<0.1

Habitat preference categories were more important than trophic guilds when we analysed the differences between transects. Abundance-weighted mean was

significantly different between habitat preference categories (F= 4.654, p=0.01), regardless of transect type (F= 0.004, p=0.476) (Table 4). Within the habitat preference categories, a post-hoc Tukey test showed the strongest differences in abundance- weighted mean elevation were between interior-edge (p=0.013) and interior-forest species (p=0.024) (Table 5). Interior birds had means at generally higher elevations in both transects, but highest in partially deforested transects. We found edge species at lower mean elevations in partially deforested transects (Figure 15a, Table 6). Minimum elevation only showed a trend for edge species, which were at lower elevations in

partially deforested transects. Elevational range width was marginally significantly

70 different between transect type (F= 1.829, p=0.089) but not between habitat preference categories (F= 0.295, p=0.745) (Figure 15c, Table 6).

Table 4: Results from one-tailed ANOVA test comparing abundance-weighted mean elevations of different habitat preference categories, in forested and partially

deforested transects.

Df Sum Sq Mean Sq F value Pr(>F) Habitat 2 56509 28254 4.654 0.01 * Forest 1 23 23 0.004 0.476 Residuals 256 1554094 6071

*** p<0.001 ** p<0.01 * p<0.05 . p<0.1

Table 5: Results from TukeyHSD test showing differences in abundance- weighted mean elevation between habitat preference categories, and forest and no- forest transects.

Habitat diff lwr upr p adj Forest-Edge 13.9 -18.2 46.1 0.562 Interior-Edge 49.9 8.8 91.0 0.013 * Interior-Forest 36.0 3.8 68.1 0.024 * Deforested-Forested 0.6 -18.6 19.7 0.477 * p<0.05 ** p<0.01 *** p<0.001

Table 6: Results from ANOVA test comparing elevational range widths of different habitat preference categories, in forest and no-forest transects.

Df Sum Sq Mean Sq F value Pr(>F) 71 Habitat 2 5345 2673 0.295 0.745 Forest 1 16551 16551 1.829 0.089 . Residuals 194 1755846 9051 ** *** p<0.001 p<0.01 * p<0.05 . p<0.1

Figure 15: Comparison of elevational range variables per habitat preference category for forested and partially deforested transects (p values shown are for one- tailed two-factor ANOVAs). a) Abundance-weighted mean elevation. b) Minimum elevation. c) Elevational range width. Dots represent outliers.

4.4 Discussion

We had expected abundance-weighted mean, and minimum elevations to be significantly higher in partially deforested transects in response to deforestation below

2400 m. When analysing species and trophic guilds, we found no significant difference in these elevational variables between transects. Habitat preference categories, in

contrast, presented significant differences in abundance-weighted mean elevation, but habitat categories, not deforestation, explained these.

Range width, however, showed marginally significant differences in all analyses: per species, trophic guild, and habitat categories. These differences, though slight, are nonetheless consistent: overall range widths were larger in the forest transects (Figure

13c). They were larger for insect- and nectar-feeding species, essentially the same for fruit-eating species (Figure 14c), and also larger for edge, forest and interior species

(Figure 15c).

First, we discuss why mean and minimum elevations were similar in forested

73 and partially deforested transects. Two factors might explain this pattern:

1) Bird distributions are not only affected by forest cover locally, but also by the landscape configuration (Villard et al. 1999) and matrix (Renjifo 2001). Areas adjacent to

our partially deforested transects had significant forest cover, so species probably moved to available nearby forests at similar elevation, instead of upslope. The existence of refuges can dampen the effects of deforestation since species that are affected by a disturbance can persist in the refugia, and then colonize larger areas that arise or exist nearby (Brash 1987). If our study was replicated in an area with higher rates of deforestation, we might see different results or even results in accordance to our predictions.

2) Different abiotic or biotic factors that we did not account for, at both local and global scales, could also affect the mean and minimum elevations of montane birds.

These species might be tracking microclimates, may be displaced by competitors

(Altshuler 2006, Jankowski et al. 2010), or respond to global scale climate change

(Şekercioğlu et al. 2012). Range shifts due to habitat change are local and difficult to tease apart from other factors affecting species’ distributions. The amount of deforestation we used to classify our transect types (200m) might not be enough to separate impacts of deforestation on elevational ranges from those of the above-

mentioned factors that also play a role.

74 4.4.1 Range width

Now we discuss the impacts of deforestation on elevational range widths, in accordance to our predictions. Montane birds, regardless of species, trophic guild, and

habitat preference had narrower elevational ranges when faced with deforestation below

2400 m (Figures 13c, 14c, 15c). Although the effects were marginally significant (p<0.1), they are consistent in their direction. We discuss this trend because it could have important conservation implications for these species.

Scientists have documented geographical and elevational range contractions of species in response to climate change (Parmesan 2006, Popy et al. 2010), and predicted alarming consequences (Shoo et al. 2005, Chen et al. 2011, Şekercioğlu et al. 2012).

Climate change could exacerbate the slight range contractions we found in montane birds. As a result of a large-scale model, (Jetz et al. 2007) found an estimated 400 of 8750 species analysed should lose >50% of their current range due to land cover changes resulting from climate change.

Montane birds in our study site likely migrate altitudinally as studies on quetzals

(Powell and Bjork 1994), bellbirds (Powell and Bjork 2004), and manakins (Rosselli 1994) have documented in other tropical mountains. Altitudinal migrants in our forested transects had larger suitable areas for altitudinal movements, while partially deforested

transects only offered a portion of that elevational span covered by forest. Looking at the

75 records of our banded birds, we found evidence of 100-400 m altitudinal movement of birds along forested transects, which were scarcer in partially deforested transects.

Range contractions resulting from deforestation could harm these, still unknown,

migration patterns (Kattan et al. 1994).

4.4.2 Trophic guilds

Nectar-eating birds had higher mean and minimum elevations, and slightly narrower range in partially deforested transects (Figures 14a, b, c). We expected this response because birds that depend on highly variable and seasonal resources often need to move along larger areas and are more susceptible to fragmentation (Loiselle and

Blake 1992). In this case, we suspect hummingbirds moved upslope in partially

deforested transects in search of food. Although hummingbirds have also been described as less sensitive to fragmentation and crossing of forest gaps (Moore et al.

2008), their movements through landscapes are affected by forest availability, as a study of the Green Hermit (Pheathornis guy) showed (Hadley and Betts 2009).

We found insect-eating birds had considerably lower minimum elevations and narrower ranges in partially deforested transects (Figures 14a, c). These bird species preferred the edge of the forest in our study, probably due to higher availability of insects. Restrepo and Gómez (1998) also found more insectivores near forest edges in

wet months in a similar montane forest. While another study at similar elevations in

76 Ecuador showed insectivores had highest densities in second growth and agricultural land, compared to primary forest (O’Dea and Whittaker 2007). This trend for montane insectivores contrasts with results for Amazonian forests that show loss of understory

insectivores after fragmentation (Canaday 1996) but the life histories of these

Amazonian birds are different from most Andean insectivores.

Fruit-eating species and, in general, differences between trophic guilds were not significantly different between transect types in our study (Figure 14). A study in the

Atlantic Forest of Brazil found trophic guild to be a good predictor of vulnerability

(Ribon et al. 2003), and research from the Colombian Andes found large frugivores to be most vulnerable (Kattan et al. 1994). This similarity might be because the forests we

studied offer a wide array of feeding resources. The 200m of deforestation might not be a significant loss of food resources for the species found in this forest, and they could also complement their diet by visiting the surrounding mostly forested matrix.

4.4.3 Habitat categories

Our analyses of habitat preference categories showed edge specialists at lower elevations, and with narrower ranges, while interior birds were at higher elevations in partially deforested transects (Figures 15a,b,c). Birds that prefer forest interior are very vulnerable to fragmentation and habitat loss (Turner 1996, O’Dea and Whittaker 2007).

As we predicted, in partially deforested transects the species in our interior habitat 77 preference category were likely forced upslope in search for suitable habitat and away from harmful edge effects (Wilcove 1985). The similarity between mean and minimum elevations on forested and partially deforested transects might be a result of the large

amounts of forest in this region. Studies in fragmented landscapes in both Andean forests (Kattan et al. 1994), and Amazonia (Laurance 2004) have shown marked differences in species found in forest edges and interior. However, the geometry of a fragment and its edges are different from those of elevational transects where the edge is only found at one end of the forest. Because the majority of the species we classified in a habitat preference category were forest generalists, these species are probably driving the statistical tests and making it hard to see signals for edge and interior species.

4.4.4 Recommendations

This study should be replicated in the future in areas with higher rates of deforestation, and comparing transects with a larger difference between forest availability (more than 200m), which may lead to different results. Ideally, an experiment could be conducted where the same transects are compared before and after lowland deforestation to document species loss over time and extinction debt. We recommend that researchers in the future control for other variables that could affect the results of this experiment such as food availability, plant composition and structure,

microclimate, predator abundance, presence of invasive species, and other factors

78 identified as important. This was the main limitation of our study. In addition, it was hard to tease apart the impact of lowland deforestation when the rest of the matrix was mostly forested, perhaps the impact would have a stronger signal in an area with a non-

forested matrix.

4.4.5 Conservation implications

Limited elevational range increases extinction risk (Manne and Pimm 2001,

White and Bennett 2015). Species with narrow elevational ranges are more sensitive to landcover change and will be severely affected by climate change (Sorte and Jetz 2010).

The conservation of forest along elevational ranges is essential for present and future species conservation. Protected areas would ideally provide continuous altitudinal

corridors to allow upslope range shifts (Channell and Lomolino 2000, Becker et al. 2007,

Sekercioglu et al. 2008, Forero-Medina et al. 2011, Laurance et al. 2011b). In addition, evaluation of species’ threat status should include elevational range width as a predictor for extinction, in addition to geographic range, as was also suggested by (White and

Bennett 2015). Studies that incorporate elevational ranges into the assessment of threat have found that species’ ranges are smaller than previously thought, and thus species are more threatened than their current categories suggest (Harris et al. 2005, Ocampo-

Peñuela and Pimm 2014).

4.4.6 Conclusions 79 We compared elevational ranges of montane birds in altitudinal gradients with different amounts of forest between 2200 and 2800 m. Forested transects had forest from

2200 to 2800m , while partially deforested transects only had forest between 2400 and

2800m. Abundance-weighted mean and minimum elevations were not significantly different between forested and partially deforested transects. Range width was marginally but consistently different, with wider ranges in forested transects. Species of different trophic guilds and habitat preference categories showed different trends. These results suggest a small, but harmful impact of deforestation on species’ ranges, but we encourage further research. Future studies should include the assessment of other factors that could influence elevational distribution of species, as well as temporal

comparisons of transects, and the evaluation of this effect within different landscape matrices.

5. Evaluation of threatened bird species using landcover data in biodiversity hotspots

5.1 Introduction

Conservation assessments inform the overall state of biodiversity through estimates of extinction rates (Pimm et al. 2014) and the progressive increase in risk species suffer over time. Individual assessments are vital to understand the threats to particular species and so which to prioritise and how to mitigate those threats.

Moreover, practitioners are often faced with limited budgets that force them to prioritize

some areas over others. One of the most commonly used prioritization schemes are

biodiversity hotspots, first described by Myers et al. (2000) and revisited both globally 81

(Grenyer et al. 2006, Jenkins et al. 2013) and locally (Jenkins et al. 2010, Ocampo-Peñuela and Pimm 2014, Li and Pimm 2015) by other researchers. Areas where high concentrations of endemic and endangered species meet habitat loss and growing

threats are priority for conservation (Margules and Pressey 2000). The principles and mechanisms we use to determine species’ vulnerability to extinction, and those used to quantify the extent of habitat loss and fragmentation are thus fundamental to the conservation decisions we make.

5.2 Materials and Methods

5.2.1 Study area

We selected six geographic regions in three different continents (Figure 16). All regions are part of the currently described biodiversity hotspots (Myers et al. 2000,

Jenkins et al. 2013) and house significant concentrations of small-ranged birds, as shown by the background map on Figure 16. These regions are biogeographically distinct and so are their bird communities. Our study focused on endemic, threatened, and small- ranged forest birds. The supplementary materials provide details of how we defined

such species. We focused our analyses on birds of tropical moist forests because such

82 forests hold the majority of terrestrial animal (Jenkins et al. 2013) and plants species and

global forest cover products are readily available (Sexton et al. 2016).

5.2.2 Study species

To classify birds as forest species, we applied a set of criteria to the “Habitats and altitude” category in BirdLife International’s species factsheets (BirdLife International

2014). There are two levels of habitat categories (level 1 and 2) and a measure of importance (major, suitable). We selected only species that had “forest” listed as their

“major” habitat regardless of the level (and including species that also had additional 83

habitats listed as “major”), or had forest listed as “suitable” habitat but no other habitat type was listed as “major”. If a habitat different than forest was listed as “major”, we did not include the species. Using these criteria, we are analysing species that need forest for all or some part of their life cycle.

We selected endemic and small-ranged species based on lists of Endemic Bird

Areas (Stattersfield et al. 2005) for each region and included all the species listed there that were endemic, threatened, or had a range smaller than 100,000 Km2. Because these lists only include species that already threatened, we complemented this list with lists

published by AVIBASE, and in scientific papers by other researchers (Harris et al. 2005,

84 Jenkins et al. 2011, Jenkins et al. 2015).

5.2.3 Range refinement

We started with current range maps published by BirdLife International and

NatureServe (2014) for the 726 bird species in the 6 study regions (Figure 17A). Those maps often included areas that were not suitable for the species because they were not at the right elevation, or have lost available habitat (Harris et al. 2005). We refined ranges by the known elevational ranges of each species and by remaining forest cover. To refine by elevation, we used a 90m digital elevation model (Jarvis et al. 2008) and selected only areas that were within the preferred elevation for each species (Figure 17B). We determined these preferred elevations as the maximum and minimum elevation at

which the species has been observed as described by BirdLife International (2014) and the Handbook of the Birds of the World Alive (del Hoyo et al. 2015).

Once we refined the range map by elevation, we used forest cover maps at two different scales to further refine the ranges by forest (Figure 17D). We evaluated forest cover at two spatial resolutions: 250m and 30m. The 250m forest cover classification was produced using the MODerate-resolution Imaging Spectroradiometer (MODIS) 250m

Vegetation Continuous Fields (VCF) tree cover dataset Version 5 2010 (DiMiceli 2011) for 2014. For all regions except Western Andes and Atlantic Forest, we created the 30m

forest cover classification using the Hansen Global Forest Change Dataset Version 1.2

85 (Hansen et al. 2013). To create binary classifications for both forest cover datasets we used a threshold of 60% to define forest/ no forest classifications. For the Hansen dataset, we used this threshold on the continuous tree cover data for 2000 and used loss and gain

products to estimate forest cover in 2014. For the Western Andes and the Atlantic Forest we used in-country forest cover maps which had been ground-truthed to check classification accuracy. For the Western Andes, we used a forest cover product at 30m scale published by Sanchez-Cuervo et al. (2012), and for the Atlantic Forest we used a land cover map produced by Fundacao SOS Mata Atlantica (2013) and selected regions classified as “forest” and “restinga”.

As a result of these refinements, we had four different range maps for each species: the original BirdLife International range map (Figure 17A), one refined by 90m elevation layer (Figure 17B), one refined by elevation and forest at a 250m scale (Figure

17C), and a last one refined by elevation and forest but at the 30m scale (Figure 17D). We then calculate the range size for each of these maps and compare the totals. For each study region, we add the ranges of all selected species at each process step to show areas of high concentration of endemic, small-ranged species, and threatened species. To compare how areas of high concentrations of endemic and small-ranged bird species

changed throughout the refining process, we calculated the area of the highest

86 concentrations of species after the 30m-forest refinement at thresholds 10% and 25%. For example, if concentrations of species ranged from 0-100 after refining by forest at 30m, we calculated the area covered by the top 10% (90-100 species), and by the top 25% (75-

100 species).

Figure 17: Range refinement process. A) Original range for the Yellow- breasted Antpitta (Grallaria flavotincta) as determined by BirdLife International and NatureServe (2014), and updated by Ocampo-Peñuela and Pimm (2014). B) Range map refined by elevation using 90m digital elevation model (Jarvis et al. 2008). C) Range map refined by elevation and forest at 250m. D) Range map refined by elevation and forest at 30m.

5.2.4 Threat category re-assessment

Using the refined ranges, we assessed threat using IUCN’s thresholds for “extent of occurrence” for threatened categories: critically endangered (<100Km2), endangered

(<5000Km2), and vulnerable (<20000Km2). For all analyses of threat, we only included

species whose original range was at least 80% within our study regions, assuring that our assumptions of threat were applicable to the majority of the species’ range.

We calculated the range size for each species on every step of the refining process: original range, refined by elevation, refined by forest (Figure 17 A, B, D). For the threat analysis we chose to used forest cover maps at the 30m scale because our experience in some of these regions tells us that these are more accurate, especially when using in-country forest cover products versus global assessments (Ocampo-Peñuela and

Pimm 2014).

5.2.5 Protected areas 88 Following the re-assessment of threat for all species within the study regions, we selected only those that resulted in one of the threatened categories (critically endangered, endangered, vulnerable) after their range was refined by forest at 30m. For

this subset of species, we calculated the percentage of the range that was within the boundaries of protected areas. We used the protected area layer from IUCN (2015) and included all categories of protection.

5.3 Results and discussion

We selected a set of 172 bird species for the Atlantic Forest (Appendix 7), 138 for

Central America (Appendix 8), 57 for Madagascar (Appendix 9), 157 for Southeast Asia

(Appendix 10), 102 for Sumatra (Appendix 11), and 100 for the Western Andes of

Colombia (Appendix 12) that met the criteria for range size, endemism, threat, and forest use. Of these 586 species, the Red List deems 108 to be threatened: 15 critically endangered, 29 endangered, and 64 vulnerable.

5.3.1 Threat category reassessment

We used IUCN thresholds for extent of occurrence to re-assign threat categories to

486 species whose range was 80% within our study region based solely on range size. We used the original ranges from BirdLife International (2014), those refined by elevation, and

only ranges refined by forest using the 30m forest product. During the process, we kept

current IUCN categories to examine how these changed after our refining process. Figures 89

18-22 show graphs of change in threat categories based on range size throughout the refining process for each region. The last column of the graph (Refined by forest (30m)) shows our recommended threat category and those boxes outlines in black represent

agreement between current IUCN categories and those suggested by us. On the contrary, boxes that are not outlined in black represent a mismatch between current and recommended threat categories.

For the Atlantic Forest, in the case of 57 species, IUCN’s current category matches the category we assigned based solely on range size. Fifteen species are placed in higher threat categories than those based only on range size (3 critically endangered, 6 endangered, and 6 vulnerable) (Figure 18).

IUCN uses five criteria to evaluate extinction risk, and range size is only one of those. For species suffering from hunting pressure, like the Red-billed Curassow (Crax blumenbachii) in the Atlantic Forest, IUCN classifies it as endangered, and we place it in the vulnerable category based on range size (Figure 18). Other cases in which IUCN assigns a higher threat category are those for parrots and related species (Psittacidae) which might be threatened by the pet trade. These cases are evidence of the completeness of the IUCN classification scheme. The use of this additional information is essential.

Habitat loss and degradation are, however, the biggest threat to most species in

90 the World’s most biodiverse places (Brooks et al. 2002, Baillie et al. 2004), and especially in the Atlantic Forest (Brooks et al. 1999a, Jenkins et al. 2010). Our refining process recommends that some species be placed on higher threat categories based on the

available forest. For twenty three species currently deemed near threatened or least concern, range size suggest they should be recognized as vulnerable (18), and endangered (5). This is also the case for 4 species currently classified as vulnerable, which should be endangered (2), and critically endangered (2). One of the species currently classified as vulnerable, which we recommend be listed as critically endangered, is the Grey-winged Cotinga (Tijuca condita), one of the least known birds

and one that we have recommended be uplisted — given a higher risk of extinction — due to its fragmented habitat and small population size (Alves et al. 2008).

In Central America, we suggest 78 species be placed on higher threat categories, while IUCN does not classify any of them as more threatened than we suggest (Figure

19).

In the case of Madagascar, IUCN classifies 5 species in a higher threat category, while we suggest that 29 be up-listed (Figure 20).

Figure 20: Madagascar. Patterned boxes show threat categories suggested based on range size thresholds established by IUCN. Solid filled boxes reflect current global IUCN categories. Arrows show changes in threat category as the range is refined by elevation and forest, their width depicts the number of species that changed categories.

Southeast Asia shows that no species were assigned to a higher threat category by IUCN, but that 49 should be placed in higher threat categories based on our assessment (Figure 21).

Figure 21: Southeast Asia. Patterned boxes show threat categories suggested based on range size thresholds established by IUCN. Solid filled boxes reflect current global IUCN categories. Arrows show changes in threat category as the range is refined by elevation and forest, their width depicts the number of species that changed categories.

In the island of Sumatra, IUCN recommends that 5 species be placed on a higher threat category, while we suggest that 14 need to be up-listed (Figure 22).

In the Western Andes two species are classified under a higher threat category than that assigned by us based on range size, and 13 should be in higher threat categories when assessing range size (Figure 23).

Figure 24 summarises this process for all the regions. The question that follows is whether elevation range, remaining forest cover, and extent to which ranges are protected are factors already implicitly incorporated into the IUCN criteria. For example,

IUCN classifies some birds as critically endangered when their original ranges are

>20,000km2 and some as vulnerable when their original ranges are >100,000 km2. The expert opinion system that IUCN employs factors in specific knowledge of diverse 96

additional threats that could involve whether the species is hunted, how specific are its habitat requirements, how many mature individuals are in the populations, how much habitat remains within its broad range, and how well it is protected. In short, some might assert that decisions on the risks experienced by individual species may be the correct even if the assessors did not use geographical data explicitly.

Even in cases in which this assertion is correct, using explicit quantitative criteria would greatly improve this process.

We understand that the criteria for endangerment that IUCN employs are based

on the original ranges, not our refined ones, which are inevitably smaller. IUCN uses an

97 original range of 20,000km2 as an important benchmark. Our use of the same extent is not to confuse it, but merely to identify species of concern — species that IUCN does not deem threatened and yet have small geographical ranges once remaining habitat is

assessed.

Figure 24 shows that there are substantial numbers of species of concern. For example, in addition to 10 species that are already recognised as being critically endangered, there are an additional 2, 7, and 8 that are endangered, vulnerable, and non-threatened that have refined ranges < 100km2.

The most parsimonious interpretation of our results it that there are more species at risk than first thought. Were we to apply range criteria based on refined ranges, 27

species (6% of all species evaluated) would be placed in higher threat categories by

IUCN than what we suggest by solely range size. In the case of 249 species (51%), our suggested threat categories match those determined by IUCN currently. And for 210 species (43%), we suggest a higher threat category than that currently proposed by

IUCN. In this group of species, a striking 189 species are currently classified as near threatened and least concern, when their refined range size indicates they might be vulnerable (115), endangered (66), and critically endangered (8) (Figure 24).

IUCN. Solid filled boxes reflect current global IUCN categories. Arrows show changes in threat category as the range is refined by elevation and forest, their width depicts the number of species that changed categories.

This is a double-edged result: first, the actual ranges of many non-threatened species are small, indeed small enough that most other similar species are deemed to be threatened. Second, they are much smaller than one might expect them to be because so much habitat has been lost. (It is likely to be continuing to be lost — something that remote sensing can best confirm.)

One might counter this by arguing that those species that IUCN does not

99 consider threatened, but that have small refined ranges, might be disproportionately protected by the network of protected areas. We show that this is not the case. Figure 25 shows results of our calculations of the fraction of the range which is protected for those

species that we consider more threatened than IUCN. This is particularly important because even species whose ranges within protected areas might suffer from illegal threats. A recent study has shown that there is huge variation on the amount of deforestation prevented in protected areas across the tropics, showing some areas to be successfully protected, and others with significant forest loss (Spracklen et al. 2015).

Figure 25: Percent of range protected in all categpories of protected areas for species classified as critically endangered, endangered, or vulnerable solely based on 100 range size, and after refining their range by elevation and forest (30m).

5.3.2 Refining of conservation priorities

In addition to being useful to assess species’ extinction risk, range maps are also vital to identify conservation priorities. These too differ when species ranges are refined by elevation and remaining habitat in our study regions. These are also affected by the forest product used to refine the ranges by habitat.

When we refine by elevation, areas of high concentrations of species shrink and often mountainous features are highlighted, such as in the Western Andes (Figure 31), and the Ankaratra mountains of Madagascar (Figure 28).

100

The digital elevation model used to refine the ranges by elevation is usually standard, but the layer used to refine by forest (or other habitat types) may vary according to availability and spatial scale (Harris et al. 2005). We compared results of refined ranges using two of the most commonly used, freely available, global forest cover maps at 250 and 30 m. Panels C and D of Figures 26-31 show the differences in the concentration of endemic and small-ranged species when refined by these two forest cover maps. The 250m-scale forest product had less area classified as forest than the

30m-scale product in all cases except for the Atlantic Forest (Table 7), resulting in

different maps of concentrations of endemic and small-ranged birds.

Table 7: Comparison of forest areas for 250 and 30m forest cover products, and 101 areas covered by the highest concentrations of endemic and small-ranged bird species (10% and 25%) after range refinement steps.

Forest area (Km2) Area top 10% species (Km2) Area top 25% species (Km2) Ref. Region Ref. for. Ref.for. Ref. Ref.for. 250m 30m Original Ref. elev Original for. (250m) (30m) elev (30m) (250m)

Atlantic Forest 160,211 146,720 121,542 10,688 3,463 3,122 232,058 108,130 34,563 31,324 Central America 223,616 421,863 5,971 411 284 394 15,514 5,843 3,863 5,367 Western Andes 40,782 90,892 4,954 147 38 125 3,777 1,666 507 2,206 Madagascar 53,516 73,842 84,509 693 376 540 162,361 3,708 894 4,499 Southeast Asia 689,398 1,462,396 565,386 61 21 29 866,312 855 208 405 Sumatra 235,529 410,174 189,639 92,054 33,291 50,492 275,067 154,357 60,353 85,973

After we refine by forest, an even more striking reduction of areas of concentration of endemic and small-ranges species is evident. These areas are not only

101

reduced, but become fragmented as a result of the state of the forests. In places like the

Atlantic Forest, where less than 10% of the original forest remains, the range maps change drastically and it is obvious that most species are confined to small fragments near the coast (Figure 26 C-D). Madagascar also shows a marked difference in the ranges when refined by forest, with most species confined to the mountains (Figure 28). In other cases, like that of Central America and the Western Andes (Figures 27 and 31), the ranges are reduced by refining by forest, but not as drastically due to larger, continuous,

forested areas.

102

103

Ranges refined by elevation and forest at 30m scale.

103

104

105

refined by elevation and forest at 30m scale.

105

106

refined by elevation and forest at 30m scale.

106

107

elevation and forest at 30m scale.

107

108

at 250m scale. D) Ranges refined by elevation and forest at 30m scale.

We calculated the area covered by the top 10 and 25% concentrations of species in every step of the refining process (Table 7). After refining by elevation, the area covered by the top 10% is reduced an average of 89% from the original range, when further refined by forest at 250m scale the average percent reduction is 96%, and 94% when refined by forest at 30m. When following the same process for the top 25%

108

concentration of species, we found an average reduction of 69% from the original range after refined by elevation, 87% when refined by forest at 250m, and 77% when refined by forest at 30m. Areas of high concentration of species are reduced significantly when ranges are refined by elevation, but especially when we refine them by forest cover.

When we used the forest cover map at 250m to refine the ranges, the reduction was larger than when we used the 30m product.

5.4 Conclusions

We have refined ranges of endemic, threatened, and small-ranges bird species by

109 elevation and forest cover in six of the most biodiverse places on Earth and found that their distributions are smaller than previously thought. We then use these new ranges, which are a better representation of the species’ actual distribution, to reassess threat

categories and refine conservation priorities. Our analyses show that a large number of species are more threatened than currently recognized by IUCN, and that large areas of their ranges do not fall within protected areas. Furthermore, we show that conservation priorities need to be refined in order to improve the decision making process.

As individuals who contribute to IUCN assessments and encourage species- specific research to address limited data, we nonetheless worry that important data do not enter this process as effectively as they might. This chapter asks: what quantitative

109

measures can we derive from widely available, remotely sensed data that sensibly inform a species’ risk of extinction? Some of these inputs may informally contribute to existing Red List determinations, but we show that we can succinctly and easily present additional quantitative data for each species. Our goal is not to replace the existing process, nor even subject it to unwarranted criticism, but to add additional tools to the process. Our results suggest species of concern — those at considerably greater risk than hitherto appreciated. We would recommend these species for closer inspection by those who assess risk. In particular, even if one kept the current evaluation process, it would

not prevent including simple statements about what fraction of a species range lies

within its known elevational limits, has remaining habitat, and is protected. 110

Furthermore, knowledge from remote sensing modifies conservation priorities.

Finally, we can establish a quick and simple method to identify and modify the priority

setting in a landscape where human actions are rapidly expanding and so where conventional species’ assessments might be too slow to respond.

110

6. Final remarks

The study of bird distributions can provide better understanding of extinction risk and refine conservation priorities. At global, national, regional, and local scales, I show how refining bird ranges with available elevation and habitat data can improve threat assessment and inform conservation priorities. Using available bird ranges from

BirdLife International and NatureServe (2014), I refine them by suitable elevation and forest cover to show that the areas available to these birds are smaller than previously thought. By doing this, conservation priorities can focus on areas with urgent needs of

reconnection and restoration. Given that species’ ranges are one of the main inputs into

111 the evaluation of extinction risk by IUCN, I show that if refined ranges are assessed, species should be placed in higher threat categories than current assignments.

The Western Andes of Colombia are an example of proactive conservation. I

identified this region as priority for Colombia, based on concentrations of endemic and small-ranges species, and downscaled conservation priorities to a local action that prevented the disconnection of large forest fragments. In contrast, the Central Andes of

Colombia show a scenario in need of reactive conservation, due to the vast amounts of habitat loss and fragmentation. Here, I show how conservation priorities for birds can be coupled with landslide prevention to achieve conservation goals within existing policies.

111

From the study of two-dimensional ranges, I advanced to analyzing the altitudinal dimension of species’ ranges and its contribution to understanding distributions and assessing threat. I show that lowland deforestation shrinks altitudinal ranges of birds, but that this effect is not as large in areas with significant tracts of available habitat.

Moving from a more local perspective to a global one, I refine bird ranges by elevation and forest, reassess threat categories, and map conservation priorities for six biodiversity hotspots: Atlantic forest in Brazil, Central America, Madagascar, Southeast

Asia, Sumatra, and the Western Andes of Colombia. Results from this study show that

bird ranges are much smaller than current maps suggest, that species should be placed 112 on higher threat categories, and that most species with small ranges are not currently protected by protected areas.

I present these methods and approaches as a contribution to conservation biology but especially to the organizations and individuals that evaluate species risk and make conservation decisions at various scales.

The World’s biodiversity is threatened, especially in the most biodiverse places: the tropics. Habitat loss and fragmentation have reduced species ranges and populations. Yet our current methods for determining which species should be

112

protected, and what areas should be priority, fail to include sophisticated and redily available geographical information.

113

Appendix 1

Data collection for presence of species along Western Andes to update range maps

We collected presence data in the localities depicted by stars in the figure below.

In each locality we spent three days (0600 – 1700 hrs) recording data by sight and sounds and two days mist-netting. The observations followed a single route transects following existing trails, as recommended by Bibby et al. (2000) for quick presence surveys. All birds seen or heard were recorded and only presence data were collected. For captures we used ten 12m long, 36mm mesh-size mist nets. We ran mist nets from 0600 to 1700

hrs during two days. All birds captured were identified, photographed, and released. 114 Integrating observations, vocalizations, and captures, we created rapid inventories for the localities and were able to record many endemic and small-ranged species found in

these localities. Data from these inventories was used to update range maps.

114

115

Locality Name Reference

Carmen de Atrato (Cortes 2012)

Cerro Montezuma (Ayerbe-Quiñones et al. 2008)

Parque Nacional Natural Munchique (Ayerbe-Quiñones et al. 2008)

Reserva Natural Cerro el Inglés (Corporacion Serraniagua 2012)

115

Reserva Natural La Planada (Bohórquez 2003, Asociacion GAICA 2012)

Reserva Natural Rio Ñambí (Asociacion GAICA 2012)

Reserva Natural Tambito (Ayerbe-Quiñones et al. 2008)

Parque Nacional Natural Orquídeas (Caranton 2012)

Reserva Natural de las Aves Las Tangaras (Calderon 2012, Parra 2012)

Paramo de Frontino (Krabbe et al. 2006)

Reserva Natural de las Aves Arrierito Antioqueño (Salaman et al. 2008)

Reserva Natural de las Aves Pangan (Salaman et al. 2008)

Reserva Natural de las Aves Loro Orejiamarillo (Salaman et al. 2008) 116

RN Mesenia-Paramillo Location from our fieldwork

Anchicayá Location from our fieldwork

Peñas Blancas and Anchicaya in the Parque Nacional Location from our fieldwork

Natural Farallones

Reserva Natural La Irlanda Location from our fieldwork

KM 18 on the road Cali-Buenaventura Location from our fieldwork

References

Asociacion GAICA. 2012. Base de datos de Aves de Nariño, Nariño, Colombia.

116

Ayerbe-Quiñones, F., J. P. López-Ordóñez, M. F. González-Rojas, F. A. Estela, M.

B. Ramírez-Burbano, J. V. Sandoval-Sierra, and L. G. Gómez-Bernal. 2008. Aves del departamento del Cauca-Colombia. Biota Colombiana 9:77-132.

Bibby, C.J., N.D. Burgess, D.A. Hill, and S.H. Mustoe. 2000. Bird Census

Techniques. Academic Press, UK.

Bohórquez, C. I. 2003. Mixed-species bird flocks in a montane cloud forest of

Colombia. Ornitologia Neotropical 14:67-78.

Calderon, D. 2012. Lista de Aves de la RN Las Tangaras. Colombia Birding,

Medellin, Colombia.

Caranton, D. 2012. Aves del Parque Nacional Natural Las Orquideas. 117

Corporacion Serraniagua. 2012. Listado de Aves de tres sitios de importancia para la conservación en la Serranía de los Paraguas, Colombia. Corporacion Serraniagua,

El Cairo, Valle del Cauca.

Cortes, O. 2012. Lista de Aves de Carmen de Atrato, Choco.

Krabbe, N. K., P. Flórez, G. Suárez, J. Castaño, J. D. Arango, and A. Duque. 2006.

The birds of Páramo de Frontino, Western Andes of Colombia. Ornitología Colombiana

4:37-48.

Parra, J. L. 2012. Lista de Aves de la RN Las Tangaras, Choco. Salida de campo del curso de Ecologia de Poblaciones. Universidad de Antioquia, Medellin, Colombia.

117

Salaman, P. G. W., T. M. Donegan, and D. Caro. 2008. Listado de las Aves de

Colombia Conservacion Colombiana 5:5-85.

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Appendix 2

Method for updating range maps in the Western Andes of Colombia

Range maps for Munchique Wood-wren (Henicorhina negreti): left, 2012 BirdLife

International (BirdLife International and NatureServe 2011) range polygons; center, localities reported by Global Biodiversity Information Facility (GBIF), Sistema de

Informacion sobre Biodiversidad (SIB), published and unpublished literature, and fieldwork we conducted and the original (2011) Birdlife range polygon; right, updated

range polygons. Munchique Wood-wrens prefer elevations of 2250-2640 m.

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Appendix 3

List of 100 bird species from the Western Andes and their range sizes during the range refining process.

BirdLife Refined by Refined by IUCN Updated Species Range elevation elevation and Category (km2) (km2) (km2) habitat (km2)

Aglaiocercus coelestis LC 16887 24505 11383 8154 Amazilia rosenbergi LC 57706 57706 54298 46882 Andigena laminirostris NT 2318 2318 1589 1205 Anisognathus notabilis LC 14207 14207 5187 3964 Atlapetes blancae* CR 43 43 12 5 Bangsia aureocincta* EN 924 3030 2088 1545

Bangsia edwardsi LC 12804 12804 4713 3556

Bangsia melanochlamys* VU 8220 8976 6645 3226 120 Bangsia rothschildi LC 17653 19826 15483 12960 Basileuterus ignotus VU 20 20 9 8 Boissonneaua jardini LC 26920 35140 27216 17084 Bucco noanamae* NT 30979 30979 21733 16584 Calliphlox mitchellii LC 22434 33992 15342 8844 Capito hypoleucus* EN 2128 3656 2454 724 Capito quinticolor VU 39343 39343 34766 29587

Capito squamatus NT 8384 8384 7960 4670 Cephalopterus penduliger VU 35142 36988 21073 16798 Cercomacra parkeri* LC 5601 9151 4122 1125 Chlorochrysa nitidissima* VU 9911 12705 7860 2125 Chlorochrysa phoenicotis LC 16922 28231 17698 11413 Chlorophonia flavirostris LC 10229 27037 20277 14963 Chlorospingus flavovirens VU 4942 4942 3480 2732 Chlorospingus semifuscus LC 19759 31256 13168 8077 Cinclodes excelsior LC 702 1367 389 31 Clytoctantes alixii EN 12277 12277 11249 5896 Coeligena orina* CR 25 1084 55 45 Coeligena wilsoni LC 18360 28441 14254 9721 Crax alberti* CR 13221 13221 12636 3532 120

Crypturellus berlepschi LC 46289 49472 48109 40440 Cyanolyca pulchra NT 16045 16045 8365 6114 Dacnis berlepschi VU 2538 2538 2512 1274 Dacnis hartlaubi* VU 15 2404 1106 250 Diglossa gloriosissima* EN 1006 3104 1015 785 Diglossa indigotica LC 14905 31340 19829 12984 Dysithamnus occidentalis VU 5255 10675 7125 4836 Entomodestes coracinus LC 15256 29323 18704 12995 Eriocnemis derbyi NT 313 2310 1413 200 Eriocnemis isabellae* CR 44 44 8 7 Eriocnemis mirabilis* CR 34 34 14 8 Eriocnemis mosquera LC 1565 24435 20056 9788 Geotrygon goldmani NT 3639 3639 2612 2105 Grallaria alleni VU 926 926 438 192 Grallaria flavotincta LC 19907 19907 8882 5324 Grallaria gigantea VU 298 298 297 10

Grallaria rufocinerea VU 7 721 640 33

Grallaria urraoensis* CR 80 80 57 39 121 Grallaricula cucullata VU 314 314 231 38 Habia cristata* LC 16953 21142 10880 6107 Habia gutturalis* NT 18050 20495 10642 5634 Haplophaedia lugens NT 1602 3116 2110 1084 Heliangelus strophianus LC 790 790 382 234 Heliodoxa imperatrix LC 17392 17392 12661 8561 Henicorhina negreti* CR 83 6908 874 561

Hylocharis grayi LC 21673 23846 17051 3900 Hypopyrrhus pyrohypogaster* EN 14167 16236 12242 2675 Iridosornis porphyrocephalus NT 12172 27378 12594 5506 Lipaugus weberi* EN 559 739 366 109 Machaeropterus deliciosus LC 17168 28091 20750 16257 Margarornis stellatus NT 18790 18790 7680 3916 Megascops colombianus NT 10465 10465 6450 2592 Melanerpes pulcher* LC 1124 1124 669 488 Micrastur plumbeus VU 60569 60569 15318 11592 Myiarchus apicalis* LC 8199 14729 13513 2474 Myioborus ornatus LC 21427 35484 6292 3244 Myrmeciza berlepschi LC 47010 47010 44730 38038 Myrmeciza nigricauda LC 36714 36714 10571 9106 121

Neomorphus radiolosus EN 9919 9919 8092 6090 Nyctiphrynus rosenbergi NT 48125 48965 46732 37763 Odontophorus dialeucos VU 39 39 27 24 Odontophorus hyperythrus* NT 23952 29696 17905 6545 Odontophorus melanonotus VU 867 867 532 377 Ognorhynchus icterotis EN 15652 20032 17674 5860 Oreothraupis arremonops VU 13837 14833 10220 5725 Ortalis columbiana* LC 10007 12008 10733 1266 Ortalis garrula* LC 36523 43379 32217 6036 Patagioenas goodsoni LC 57788 59842 56906 48306 Penelope ortoni EN 40974 40974 30005 26059 Penelope perspicax* EN 8007 8007 7388 601 Phalcoboenus carunculatus LC 2535 2535 949 83 Phylloscartes lanyoni* EN 2651 2651 999 210 Picumnus granadensis* LC 17266 27015 20355 4465 Pipreola jucunda LC 6176 6176 2983 2657

Pittasoma rufopileatum NT 56845 58075 56118 47678

Psarocolius cassini* EN 8398 9108 3902 3584 122 Pyrilia pulchra LC 52538 58090 54734 47059 Scytalopus canus* LC 941 941 527 422 Scytalopus stilesi* LC 2343 2832 1641 334 Scytalopus vicinior LC 12064 24387 12770 7661 Semnornis ramphastinus NT 25783 25783 17459 7206 Tangara fucosa NT 1496 1496 8 1 Tangara johannae NT 58037 62579 60679 51097

Tangara rufigula LC 11711 27784 19570 14801 Thripadectes ignobilis LC 24823 24823 14587 12485 Thryothorus spadix LC 26597 28936 13845 9468 Tinamus osgoodi VU 963 1466 160 31 Urosticte benjamini LC 141 22019 10206 7288 Urothraupis stolzmanni LC 556 1116 337 15 Veniliornis chocoensis NT 68600 68600 65620 55756 Vireo masteri EN 4585 5590 3704 2554 Xenopipo flavicapilla NT 13209 14021 9492 2788

* Colombian endemic

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Appendix 4

Values of landslide susceptibility index for presence and absent landslide points.

Landslide presence Slope Index Forest Index Stream Prox Index Aspect Index 1 10 10 0 0 1 10 10 0 0 1 10 10 0 0 1 10 10 0 0 1 10 10 0 0 1 10 10 0 0 1 10 10 0 0 1 10 10 0 0 1 20 10 0 0 1 20 10 0 0 1 20 10 0 0 1 20 10 0 0 1 20 10 0 0 1 20 30 0 0 1 20 30 10 0

1 0 10 20 0

1 10 10 20 0

1 20 10 20 0 123 1 20 10 20 0 1 20 10 20 0 1 20 10 20 0 1 30 10 20 0 1 10 30 20 0 1 0 10 0 5 1 10 10 0 5 1 10 10 0 5 1 10 10 0 5

1 10 10 0 5 1 10 10 0 5 1 20 10 0 5 1 20 10 0 5 1 20 10 0 5 1 30 10 0 5 1 10 30 0 5 1 20 30 0 5 1 20 30 0 5 1 20 10 10 5 1 20 10 10 5 1 20 10 10 5 1 20 30 10 5 1 10 10 20 5 1 20 10 20 5 1 20 10 20 5 1 20 10 20 5 123

1 20 10 20 5 1 10 30 20 5 1 10 30 20 5 1 20 30 20 5 1 30 30 20 5 1 10 10 0 10 1 10 10 0 10 1 10 10 0 10 1 20 10 0 10 1 20 10 0 10 1 20 10 0 10 1 20 10 0 10 1 20 10 0 10 1 10 30 0 10 1 20 30 0 10 1 10 10 10 10 1 10 30 10 10 1 20 30 10 10 1 10 10 20 10 1 10 10 20 10 1 10 10 20 10 1 20 10 20 10

1 20 10 20 10

1 10 30 20 10 124 0 10 30 0 0 0 20 30 0 10 0 10 30 0 5 0 10 30 0 0 0 0 30 0 0 0 0 30 0 10 0 10 30 0 5 0 10 10 0 0 0 10 10 0 0

0 0 10 0 5

0 20 10 0 0 0 10 10 0 10 0 30 10 0 10 0 10 10 0 5 0 30 10 0 10 0 0 10 0 10 0 10 30 0 5 0 10 10 0 5 0 10 10 0 5 0 10 10 0 10 0 0 10 0 10 0 20 10 0 10 0 10 10 0 0 0 20 10 0 0 0 10 10 0 0 0 20 10 0 0

124

0 20 10 0 5 0 20 10 0 5 0 10 10 0 10

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Appendix 5

List of bird species used for analysis of conservation priorities in the Central Andes in

Colombia.

Elevation Endemic to Family Species IUCN Min Max Colombia Trochilidae Amazilia cyanifrons 400 2000 LC Tyrannidae Anairetes agilis 1800 3400 LC Trochilidae Anthocephala floriceps 600 2300 VU 1 Emberizidae Atlapetes blancae 2400 2800 CR 1 Emberizidae Atlapetes flaviceps 1300 2500 EN 1 Emberizidae Atlapetes fuscoolivaceus 1600 2400 NT 1 Emberizidae Atlapetes leucopis 2100 3200 LC Thraupidae Bangsia melanochlamys 1000 2300 VU 1 Psittacidae Bolborhynchus ferrugineifrons 2800 4000 VU 1 Thraupidae Buthraupis wetmorei 2900 3550 VU Trochilidae Campylopterus villaviscensio 1050 1500 NT Ramphastidae Capito hypoleucus 400 1600 VU 1

Thamnophilidae Cercomacra parkeri 1130 1950 LC 1

Formicariidae Chamaeza turdina 900 2600 LC 126 Thraupidae Chlorochrysa nitidissima 900 2200 VU 1 Furnariidae Cinclodes excelsior 3200 5200 LC Thamnophilidae Clytoctantes alixii 185 1750 EN Cracidae Crax alberti 0 1200 CR 1 Thraupidae Diglossa gloriosissima 2500 3800 EN 1 Cotingidae Doliornis remseni 2875 3650 VU Trochilidae Eriocnemis derbyi 2500 3600 NT Trochilidae Eriocnemis mosquera 1200 4000 LC Galbulidae Galbula pastazae 600 1700 VU

Formicariidae Grallaria alleni 1800 2500 VU

Formicariidae Grallaria gigantea 2200 3000 VU Formicariidae Grallaria milleri 1800 3150 VU 1 Formicariidae Grallaria rufocinerea 1950 3150 VU Formicariidae Grallaricula cucullata 1500 2700 VU Cardinalidae Habia gutturalis 100 1000 NT 1 Psittacidae Hapalopsittaca amazonina 2000 3000 VU Psittacidae Hapalopsittaca fuertesi 2600 3600 CR 1 Troglodytidae Henicorhina negreti 2250 2640 CR 1 Trochilidae Hylocharis grayi 500 2000 LC Icteridae Hypopyrrhus pyrohypogaster 800 2400 VU 1 Thraupidae Iridosornis porphyrocephalus 1500 2700 NT Columbidae Leptotila conoveri 1600 2500 EN 1 Cotingidae Lipaugus weberi 1500 1850 EN 1 Furnariidae Margarornis stellatus 1200 2200 NT Picidae Melanerpes pulcher 170 1500 LC 1 Tyrannidae Myiarchus apicalis 400 2500 LC 1

126

Parulidae Myioborus ornatus 2400 3400 LC Odontophoridae Odontophorus hyperythrus 1300 2700 NT 1 Psittacidae Ognorhynchus icterotis 1200 3400 EN Cracidae Ortalis columbiana 0 2500 LC 1 Trochilidae Oxypogon guerinii 3000 5200 LC Cracidae Penelope perspicax 650 2200 EN 1 Falconidae Phalcoboenus carunculatus 3000 4000 LC Tyrannidae Phylloscartes lanyoni 450 900 EN 1 Cotingidae Pipreola lubomirskii 1200 2300 LC Rhinocryptidae Scytalopus rodriguezi 2000 2300 EN 1 Rhinocryptidae Scytalopus stilesi 1420 2130 LC 1 Ramphastidae Semnornis ramphastinus 1000 2400 NT Troglodytidae Thryothorus spadix 400 1800 LC Trochilidae Urosticte ruficrissa 1350 2400 LC Emberizidae Urothraupis stolzmanni 3000 3600 LC Pipridae Xenopipo flavicapilla 1200 2400 NT

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Appendix 6

Data for point counts and mist-netting in forested and partially deforested altitudinal transects in the Mesenia-Paramillo Reserve

in the Western Andes of Colombia

Forested Partially deforested English name Scientific name Guild Habitat IUCN End Inc PC MN Mean Min Max RW PC MN Mean Min Max RW Tinamidae

Highland Tinamou Nothocercus bonapartei Fruit Forest LC x 2675 2675 2675 0 - - 0 - Tawny-breasted Tinamou Nothocercus julius Fruit Forest LC x 2629 2557 2686 258 x 2639 2581 2696 346 Cracidae Sickle-winged Guan Chamaepetes goudotii Fruit Forest LC x 2618 2489 2697 312 x 2609 2531 2676 218 Odontophoridae Chestnut Wood-quail Odontophorus hyperythrus Seeds Forest NT x x 2463 2390 2535 145 x 2546 2451 2627 176 Ardeidae Cattle Egret Bubulcus ibis All Non-forest LC NF - - 0 - - - 0 -

128 Fasciated Tiger-heron Tigrisoma fasciatum All Forest LC F - - 0 - - - 0 - Accipitridae

Sharp-shinned Hawk Accipiter striatus Meat Forest LC - - 0 - x - - 0 - Broad-winged Hawk Buteo platypterus Meat Forest LC F - - 0 - - - 0 - Hook-billed Kite Chondrohierax uncinatus Meat Forest LC NF - - 0 - - - 0 - White-rumped Hawk Parabuteo leucorrhous Meat Forest LC - - 0 - x 2560 2547 2622 75 Roadside Hawk Rupornis magnirostris Meat Edge LC x 2419 2419 2419 0 x 2427 2427 2427 0 Charadriidae Southern Lapwing Vanellus chilensis Insects Non-forest LC NF - - 0 - - - 0 - Columbidae White-throated Quail-dove Zentrygon frenata Seeds Interior LC x x 2535 2535 2535 0 x x 2796 2796 2796 0 Southern Band-tailed Pigeon Patagioenas albilinea Fruit Edge LC x 2578 2497 2653 234 x 2569 2511 2708 197 Plumbeous Pigeon Patagioenas plumbea Fruit Forest LC x 2675 2675 2675 0 x 2450 2450 2450 0 Ruddy Pigeon Patagioenas subvinacea Fruit Forest VU x 2550 2510 2602 184 x 2564 2564 2564 0 Cuculidae Common Squirrel-cuckoo Piaya cayana Insects Forest LC x 2675 2675 2675 0 - - 0 - Strigidae Rufous-banded Owl Ciccaba albitarsis Meat Forest LC x 2480 2480 2480 0 x 2796 2796 2796 0 Andean Pygmy-owl Glaucidium jardini Meat Forest LC x x 2644 2632 2657 49 - - 0 - White-throated Screech-owl Megascops albogularis Insects Forest LC x 2713 2713 2713 0 - - 0 - Caprimulgidae Rufous-bellied Nighthawk Lurocalis rufiventris Insects Forest LC - - 0 - x 2800 2800 2800 0 Trochilidae Speckeled Hummingbird Adelomyia melanogenys Nectar Forest LC x x 2531 2424 2718 295 x x 2608 2419 2737 317

Violet-tailed Sylph Aglaiocercus coelestis Nectar Forest LC x x 2524 2401 2600 199 x x 2595 2595 2595 0 Long-tailed Sylph Aglaiocercus kingii Nectar Forest LC x x 2523 2470 2562 138 x x 2592 2550 2607 86 Andean Emerald Amazilia franciae Nectar Edge LC - - 0 - x - - 0 - Steely-vented Hummingbird Amazilia saucerrottei Nectar Edge LC - - 0 - x 2382 2382 2382 0 Buff-tailed Coronet Boissonneaua flavescens Nectar Forest LC x x 2484 2468 2568 199 x x 2559 2480 2683 203 Velvet-purple Coronet Boissonneaua jardini Nectar Forest LC x 2508 2508 2508 0 - - 0 - White-bellied Woodstar Chaetocercus mulsant Nectar Edge LC x 2450 2450 2450 - - - 0 - Bronzy Inca Coeligena coeligena Nectar Forest LC x x 2473 2424 2519 285 x x 2519 2394 2714 321 Collared Inca Coeligena torquata Nectar Forest LC x x 2653 2594 2733 208 x x 2635 2568 2718 150 Brown Inca Coeligena wilsoni Nectar Forest LC x 2553 2503 2618 172 2633 2469 2727 258 Sparkling Violet-ear Colibri coruscans Nectar Edge LC - - 0 - x 2452 2405 2476 71 Brown Violet-ear Colibri delphinae Nectar Edge LC NF - - 0 - - - 0 - Green Violet-ear Colibri thalassinus Nectar Edge LC x x 2538 2538 2538 0 x x 2446 2432 2448 49 Green-fronted Lancebill Doryfera ludoviciae Nectar Forest LC x - - 0 - x x 2564 2564 2564 0 Sword-billed Hummingbird Ensifera ensifera Nectar Forest LC x 2465 2465 2465 0 x 2715 2715 2715 0 Glowing Puffleg Eriocnemis vestita Nectar Edge LC - - 0 - x 2753 2753 2753 0 White-tipped Sicklebill Eutoxeres aquila Nectar Forest LC - - 0 - x - - 0 - Greenish Puffleg Haplophaedia aureliae Nectar Forest LC x x 2445 2423 2467 132 x x 2446 2420 2472 52 Tourmaline Sunangel Heliangelus exortis Nectar Forest LC x x 2666 2570 2735 165 x x 2662 2488 2751 263 Empress Brilliant Heliodoxa imperatrix Nectar Forest LC x x 2516 2469 2562 93 x 2511 2511 2511 0 Fawn-breasted Brilliant Heliodoxa rubinoides Nectar Forest LC x - - 0 - x x 2451 2451 2451 0 Mountain Velvetbreast Lafresnaya lafresnayi Nectar Edge LC x - - 0 - x - - 0 - 129 Tyrian Metaltail Metallura tyrianthina Nectar Interior LC x x 2666 2639 2689 150 x x 2758 2635 2796 161 Booted Racket-tail Ocreatus underwoodii Nectar Forest LC x x 2455 2396 2538 285 x x 2503 2462 2568 106 Tawny-bellied Hermit Phaethornis syrmatophorus Nectar Forest LC x x 2433 2401 2508 107 x x 2471 2442 2505 95 Rufous-gaped Hillstar Urochroa bougueri Nectar Forest LC - - 0 - x - - 0 - Trogonidae Golden-headed Quetzal Pharomachrus auriceps Fruit Interior LC x 2667 2600 2719 120 x 2546 2514 2618 156 Masked Trogon Trogon personatus Fruit Forest LC x x 2557 2501 2619 177 x x 2533 2498 2608 331 Momotidae Highland Motmot Momotus aequatorialis Insects Forest LC x 2725 2725 2725 0 - - 0 - Bucconidae White-faced Nunbird Hapaloptila castanea Insects Forest LC x x 2542 2517 2567 149 x x 2508 2410 2557 294 Ramphastidae Black-billed Mountain-toucan Andigena nigrirostris Fruit Forest LC x x 2561 2465 2661 196 x 2644 2528 2704 176 Emerald Toucanet Aulacorhynchus prasinus Fruit Forest LC x x 2535 2505 2552 140 x x 2561 2451 2699 248 Picidae Powerful Woodpecker Campephilus pollens Insects Forest LC x 2573 2524 2653 194 x 2640 2631 2645 28 Spot-breasted Woodpecker Colaptes punctigula Insects Forest LC x 2603 2603 2603 0 - - 0 - Crimson-mantled Woodpecker Colaptes rivolii Insects Forest LC x 2489 2423 2540 175 x 2649 2579 2773 194 Golden-olive Woodpecker Colaptes rubiginosus Insects Forest LC x x 2600 2450 2675 225 x 2437 2405 2534 129 Yellow-vented Woodpecker Veniliornis dignus Insects Interior LC - - 0 - x - - 0 - Falconidae Crested Caracara Caracara cheriway Meat Non-forest LC NF - - 0 - - - 0 - American Kestrel Falco sparverius Insects Non-forest LC NF - - 0 - - - 0 - Psittacidae

Scaly-naped Amazon Amazona mercernarius Seeds Forest LC x 2480 2480 2480 0 x 2544 2450 2614 164 Barred Parakeet Bolborhynchus lineola Seeds Forest LC x 2675 2675 2675 0 x 2716 2716 2716 0 Yellow-eared Parrot Ognorhynchus icterotis Seeds Forest EN x 2582 2529 2636 160 x 2556 2523 2696 260 Speckle-faced Parrot Pionus tumultuosus Seeds Forest LC - - 0 - x 2747 2715 2773 58 Thamnophilidae Streak-headed Antbird Drymophila striaticeps Insects Forest LC x - - 0 - x x 2716 2716 2716 0 Bicoloured Antvireo Dysithamnus occidentalis Insects Interior VU x x 2675 2675 2675 0 x x 2507 2507 2507 0 Uniform Antshrike Thamnophilus unicolor Insects Forest LC - - 0 - x x 2444 2419 2452 33 Grallariidae Yellow-breasted Antpitta Grallaria flavotincta Insects Forest LC x 2526 2439 2565 189 x 2426 2414 2439 49 Chestnut-naped Antpitta Grallaria nuchalis Insects Forest LC - - 0 - x 2796 2796 2796 0 Chestnut-crowned Antpitta Grallaria ruficapilla Insects Edge LC - - 0 - x 2571 2571 2571 0 Rufous Antpitta Grallaria rufula Insects Forest LC x 2697 2619 2746 128 x 2702 2690 2715 76 Undulated Antpitta Grallaria squamigera Insects Forest LC x 2600 2600 2600 0 x 2529 2419 2622 203 Slate-crowned Antpitta Grallaricula nana Insects Interior LC x x 2571 2444 2643 300 x x 2681 2569 2751 182 Rhinocryptidae Ocellated Tapaculo Acropternis orthonyx Insects Interior LC x 2563 2547 2579 63 x 2519 2488 2581 93 Ash-coloured Tapaculo Myornis senilis Insects Forest LC - - 0 - x 2614 2614 2614 0 Paramo Tapaculo Scytalopus canus Insects Forest EN x x 2740 2740 2740 0 x x 2753 2753 2753 0 Choco Tapaculo Scytalopus chocoensis Insects Interior LC x 2675 2675 2675 0 x - - 0 - Blackish Tapaculo Scytalopus latrans Insects Forest LC x x 2595 2447 2733 286 x x 2574 2408 2751 343 Magdalena Tapaculo Scytalopus rodriguezi Insects Forest EN x x - - 0 - - - 0 - 130 Stiles’s Tapaculo Scytalopus stilesi Insects Edge LC x x - - 0 - - - 0 - Spillmann's Tapaculo Scytalopus spillmanni Insects Forest LC x x 2524 2403 2718 315 x x 2604 2408 2751 343 Narino Tapaculo Scytalopus vicinior Insects Forest LC x 2536 2410 2663 253 x 2657 2657 2657 0 Formicariidae Rufous-breasted Antthrush Formicarius rufipectus Insects Interior LC F - - 0 - - - 0 - Furnariidae Montane Foliage-gleaner Anabacerthia striaticollis Insects Forest LC x 2700 2675 2725 50 x x 2468 2468 2468 0 Brown-billed Scythebill Campylorhamphus pusillus Insects Forest LC x 2638 2600 2675 75 x - - 0 - Tyrannine Woodcreeper Dendrocincla tyrannina Insects Interior LC x x 2531 2521 2541 60 x x 2613 2613 2613 0 Black-banded Woodcreeper Dendrocolaptes picumnus Insects Interior LC x 2450 2419 2480 61 - - 0 - Striped Woodhaunter Hyloctistes subulatus Insects Forest LC x - - 0 - - - 0 - Montane Woodcreeper Lepidocolaptes lacrymiger Insects Forest LC x x 2626 2613 2638 50 x x 2493 2477 2527 101 Pearled Treerunner Margarornis squamiger Insects Forest LC x x 2529 2491 2571 121 x x 2553 2477 2676 199 Fulvous-dotted Treerunner Margarornis stellatus Insects Interior NT x - - 0 - x 2556 2476 2715 239 Spotted Barbtail Premnoplex brunnescens Insects Interior LC x x 2600 2554 2624 140 x x 2492 2468 2517 98 Rusty-winged Barbtail Premnornis guttuligera Insects Interior LC x - - 0 - x - - 0 - Streaked Tuftedcheek Pseudocolaptes boissonneautii Insects Interior LC x x 2548 2510 2607 146 x x 2632 2589 2669 121 Azara's Spinetail Synallaxis azarae Insects Edge LC - - 0 - x x 2409 2405 2427 22 Rufous Spinetail Synallaxis unirufa Insects Edge LC x x 2595 2410 2735 325 x x 2670 2593 2723 130 Flammulated Treehunter Thripadectes flammulatus Insects Forest LC x x 2600 2600 2600 0 x - - 0 - Striped Treehunter Thripadectes holostictus Insects Forest LC x x 2537 2510 2591 162 x x 2533 2533 2533 0 Streaked Xenops Xenops rutilans Insects Forest LC - - 0 - x 2477 2477 2477 0 Spotted Woodcreeper Xiphorhynchus erythropygius Insects Interior LC x x 2675 2675 2675 0 - - 0 - Black-striped Woodcreeper Xiphorhynchus lachrymosus Insects Interior LC x - - 0 - - - 0 -

Olive-backed Woodcreeper Xiphorhynchus triangularis Insects Interior LC x x 2607 2450 2725 275 2599 2429 2698 269 Tyrannidae Smoke-coloured Pewee Contopus fumigatus Insects Forest LC x 2613 2613 2613 0 x 2436 2429 2440 22 Mountain Elaenia Elaenia frantzii Fruit Edge LC x 2419 2419 2419 0 x 2411 2408 2416 22 Black-throated Tody-tyrant Hemitriccus granadensis Insects Forest LC x x 2610 2510 2693 184 x x 2667 2559 2751 192 Rufous-breasted Flycatcher Leptopogon rufipectus Insects Forest LC x 2525 2466 2558 275 x x 2486 2382 2622 240 White-throated Tyrannulet Mecocerculus leucophrys Insects Forest LC x 2390 2390 2390 0 - - 0 - White-tailed Tyrannulet Mecocerculus poecilocercus Insects Forest LC x 2450 2450 2450 0 - - 0 - White-banded Tyrannulet Mecocerculus stictopterus Insects Forest LC - - 0 - x 2630 2547 2713 166 Ochre-bellied Flycatcher Mionectes oleagineus Fruit Forest LC - - 0 - x 2450 2450 2450 0 Streak-necked Flycatcher Mionectes striaticollis Insects Interior LC x x 2539 2403 2666 262 x x 2571 2420 2709 289 Pale-edged Flycatcher Myiarchus cephalotes Insects Edge LC x 2688 2675 2725 50 x 2423 2408 2443 52 Golden-crowned Flycatcher Myiodynastes chrysocephalus Insects Edge LC x 2531 2435 2597 162 x 2482 2476 2487 22 Flavescent Flycatcher Myiophobus flavicans Insects Forest LC x x 2521 2521 2521 0 x x 2449 2428 2492 129 Smoky Bush-tyrant Myiotheretes fumigatus Insects Edge LC x x 2627 2557 2740 366 x x 2677 2602 2727 125 Handsome Flycatcher Nephelomyias pulcher Insects Forest LC x - - 0 - - - 0 - Slaty-backed Chat-tyrant Ochthoeca cinnamomeiventris Insects Forest LC x x 2467 2420 2562 284 x x 2465 2449 2468 37 Yellow-bellied Chat-tyrant Ochthoeca diadema Insects Interior LC x x 2586 2494 2693 300 x x 2638 2459 2743 284 Ashy-headed Tyrannulet Phyllomyias cinereiceps Insects Forest LC x 2552 2481 2624 285 x x 2502 2458 2545 174 Black-capped Tyrannulet Phyllomyias nigrocapillus Insects Forest LC x x 2642 2595 2698 155 x x 2548 2461 2621 160 Plumbeous-crowned Tyrannulet Phyllomyias plumbeiceps Insects Forest LC x - - 0 - x - - 0 -

131 Marble-faced Bristle-tyrant Phylloscartes ophthalmicus Insects Interior LC - - 0 - x 2452 2452 2452 0 Variegated Bristle-tyrant Phylloscartes poecilotis Insects Forest LC x 2725 2725 2725 0 x 2419 2419 2419 0 Rufous-crowned Tody-tyrant Poecilotriccus ruficeps Insects Edge LC x x 2556 2556 2556 0 x 2614 2614 2614 0 Variegated Bristle-tyrant Pogonotriccus poecilotis Insects Forest LC x 2480 2480 2480 0 x x 2578 2578 2578 0 Rufous-headed Pygmy-tyrant Pseudotriccus ruficeps Insects Forest LC x x 2545 2403 2693 290 x x 2665 2546 2715 170 Cinnamon Flycatcher Pyrrhomyias cinnamomeus Insects Edge LC x x 2509 2410 2693 284 x x 2590 2420 2751 331 Black Phoebe Sayornis nigricans Insects Non-forest LC NF - - 0 - - - 0 - Torrent Tyrannulet Serpophaga cinerea Insects Edge LC F/NF - - 0 - - - 0 - Tropical Kingbird Tyrannus melancholicus Insects Non-forest LC x 2572 2572 2572 0 x 2410 2403 2414 22 Golden-faced Tyrannulet Zimmerius chrysops Insects Forest LC x x 2592 2403 2718 315 x x 2545 2408 2751 343 Cotingidae Red-crested Cotinga Ampelion rubrocristatus Fruit Edge LC x 2707 2707 2707 0 - - 0 - Chestnut-crested Cotinga Ampelion rufaxilla Fruit Forest LC x 2390 2390 2390 0 x 2584 2507 2672 165 Dusky Piha Lipaugus fuscocinereus Fruit Interior LC x 2549 2549 2549 0 x x 2714 2714 2714 0 Barred Fruiteater Pipreola arcuata Fruit Forest LC x x 2622 2569 2663 94 x 2709 2691 2729 76 Green-and-black Fruiteater Pipreola riefferii Fruit Forest LC x x 2562 2410 2733 323 x x 2578 2425 2729 304 Andean Cock-of-the-rock Rupicola peruvianus Fruit Forest LC - - 0 - x 2382 2382 2382 0 Pipridae Yellow-headed Manakin Chloropipo flavicapilla Fruit Interior NT x - - 0 - - - 0 - Tityridae Barred Becard Pachyramphus versicolor Insects Forest LC x 2592 2592 2592 0 x x 2500 2452 2547 95 Vireonidae Black-billed Peppershrike Cyclarhis nigrirostris Insects Forest LC x 2505 2495 2525 59 x 2466 2437 2495 174 Brown-capped Vireo Vireo leucophrys Insects Forest LC x 2621 2535 2675 140 x x 2461 2403 2543 418

Corvidae Green Jay Cyanocorax yncas Insects Edge LC x 2477 2477 2477 0 x x 2443 2443 2443 0 Black-collared Jay Cyanolyca armillata Insects Forest LC x 2551 2551 2554 7 x 2610 2469 2654 369 Hirundinidae Blue-and-white Swallow Pygochelidon cyanoleuca Insects Non-forest LC - - 0 - x 2405 2405 2405 0 Troglodytidae Sharpe's Wren Cinnycerthia olivascens Insects Forest LC x x 2555 2423 2663 239 x x 2643 2586 2695 164 Rufous Wren Cinnycerthia unirufa Insects Forest LC x x 2651 2597 2721 124 x 2557 2527 2608 161 Chestnut-breasted Wren Cyphorhinus thoracicus Insects Interior LC x 2486 2430 2525 143 x 2589 2412 2676 264 Grey-breasted Wood-wren Henicorhina leucophrys Insects Forest LC x x 2470 2403 2515 335 x x 2486 2396 2621 225 Munchique Wood-wren Henicorhina negreti Insects Interior CR x x x 2610 2538 2721 366 x x 2615 2543 2659 174 Whiskered Wren Pheugopedius mystacalis Insects Edge LC - - 0 - x 2427 2427 2427 0 House Wren Troglodytes aedon Insects Edge LC NF - - 0 - - - 0 - Mountain Wren Troglodytes solstitialis Insects Forest LC - - 0 - x x 2554 2511 2614 103 Cinclidae White-capped Dipper Cinclus leucocephalus Insects Non-forest LC F/NF - - 0 - 2382 2382 2382 0 Turdidae Swainson's Thrush Catharus ustulatus All Forest LC - - 0 - x 2405 2405 2405 0 Black Solitaire Entomodestes coracinus Fruit Forest LC x x 2512 2512 2512 0 x x 2534 2534 2534 0 Andean Solitaire Myadestes ralloides All Forest LC x x 2567 2403 2714 311 x x 2537 2425 2726 301 Great Thrush Turdus fuscater All Edge LC x x 2638 2566 2657 275 x x 2484 2396 2751 355 Black-billed Thrush Turdus ignobilis All Non-forest LC NF - - 0 - - - 0 - 132 Pale-eyed Thrush Turdus leucops Fruit Forest LC x x 2441 2441 2441 0 x x 2534 2534 2534 0 Glossy-black Thrush Turdus serranus Fruit Forest LC x x 2539 2505 2572 102 x x 2668 2600 2723 184 Thraupidae Lacrimose Mountain-tanager Anisognathus lacrymosus Fruit Forest LC x x 2645 2583 2691 162 x x 2743 2724 2751 81 Blue-winged Mountain-tanager Anisognathus somptuosus Fruit Forest LC x x 2566 2460 2668 312 x x 2481 2408 2630 222 Hooded Mountain-tanager Buthraupis montana Insects Forest LC x x 2632 2464 2737 274 x x 2635 2488 2657 169 Plushcap Catamblyrhynchus diadema Insects Forest LC x x 2636 2635 2640 10 x x 2605 2605 2605 0 Grass-green Tanager Chlorornis riefferii Fruit Forest LC x x 2549 2403 2718 315 x x 2659 2535 2751 216 Grey-hooded Bush-tanager Cnemoscopus rubrirostris Insects Forest LC x x 2541 2531 2551 61 x x 2559 2534 2635 101 Capped Conebill Conirostrum albifrons Insects Edge LC x 2598 2588 2618 61 x x 2593 2583 2602 38 Rufous-crested Tanager Creurgops verticalis Insects Forest LC - - 0 - x x 2477 2477 2477 0 White-sided Flowerpiercer Diglossa albilatera Nectar Edge LC x x 2548 2403 2733 330 x x 2612 2535 2643 162 Bluish Flowerpiercer Diglossa caerulescens Insects Forest LC x x 2534 2403 2693 290 x x 2625 2458 2751 293 Masked Flowerpiercer Diglossa cyanea Fruit Forest LC x x 2569 2410 2733 323 x x 2579 2408 2751 343 Chestnut-bellied Flowerpiercer Diglossa gloriosissima Nectar Forest EN x x x 2588 2588 2588 0 x x 2689 2689 2689 0 Buff-breasted Mountain- tanager Dubusia taeniata Fruit Forest LC x 2531 2486 2618 133 x 2614 2614 2614 0 Slaty Finch Haplospiza rustica Seeds Edge LC x x 2767 2767 2767 0 x - - 0 - Black-capped Hemispingus Hemispingus atropileus Insects Interior LC x x 2534 2507 2551 131 x x 2553 2511 2597 86 Oleaginous Hemispingus Hemispingus frontalis Insects Interior LC x - - 0 - - - 0 - Black-eared Hemispingus Hemispingus melanotis Insects Forest LC x 2562 2562 2562 0 - - 0 - Golden-crowned Tanager Iridosornis rufivertex Fruit Forest LC x x 2600 2600 2600 0 x 2775 2753 2796 43 Purplish-mantled Tanager Iridosornis porphyrocephalus Fruit Forest NT x x 2615 2424 2735 311 x x 2612 2462 2698 235 Fawn-breasted Tanager Pipraidea melanonota Fruit Edge LC F - - 0 - - - 0 -

White-capped Tanager Sericossypha albocristata Fruit Interior VU x 2557 2557 2557 0 x 2601 2534 2753 219 Golden Tanager Tangara arthus Fruit Forest LC x 2663 2600 2725 125 x 2452 2452 2452 0 Black-capped Tanager Tangara heinei Fruit Forest LC x 2683 2600 2725 125 x 2473 2462 2479 49 Metallic-green Tanager Tangara labradorides Fruit Edge LC x 2526 2439 2668 229 x x 2501 2416 2621 206 Golden-hooded Tanager Tangara larvata Fruit Edge LC NF - - 0 - - - 0 - Beryl-spangled Tanager Tanagara nigroviridis Fruit Edge LC x x 2604 2487 2698 210 x x 2486 2427 2609 183 Golden-naped Tanager Tangara ruficervix Fruit Edge LC x 2500 2405 2579 174 x 2503 2425 2586 242 Blue-and-black Tanager Tangara vassorii Fruit Forest LC x x 2565 2510 2593 167 x x 2671 2574 2697 369 Scrub Tanager Tangara vitriolina Fruit Edge LC NF - - 0 - - - 0 - Saffron-crowned Tanager Tangara xanthocephala Fruit Forest LC x x 2527 2527 2527 0 x x 2467 2436 2499 190 Blue-capped Tanager Thraupis cyanocephala Fruit Edge LC x x 2627 2457 2735 278 x 2488 2408 2615 207 Blue-grey Tanager Thraupis episcopus Fruit Non-forest LC NF - - 0 - - - 0 - Yellow-faced Grassquit Tiaris olivaceus Seeds Non-forest LC NF - - 0 - - - 0 - Emberizidae White-browed Brush-finch Arremon torquatus Insects Forest LC x x 2535 2535 2535 0 - - 0 - Lesser Goldfinch Astragalinus psaltria Seeds Edge LC x 2609 2502 2709 207 x 2405 2405 2405 0 White-naped Brush-finch Atlapetes albinucha Insects Edge LC - - 0 - x - - 0 - Chestnut-capped Brush-finch Atlapetes brunneinucha Insects Forest LC x x 2481 2444 2517 111 x x 2555 2528 2583 166 Slaty Brush-finch Atlapetes schistaceus Insects Edge LC x x 2681 2663 2718 167 x x 2721 2715 2723 23 Common Bush-tanager Chlorospingus ophthalmicus Fruit Forest LC x x 2704 2704 2704 0 - - 0 - Dusky Bush-tanager Chlorospingus semifuscus Insects Interior LC x x 2638 2464 2706 242 x x 2614 2614 2614 0 Tanager Finch Oreothraupis arremonops Insects Interior VU x x 2634 2458 2733 275 x x 2650 2619 2692 217 133 Rufous-collared Sparrow Zonotrichia capensis Seeds Non-forest LC x 2419 2419 2419 0 x x 2411 2405 2427 22 Cardinalidae Summer Tanager Piranga rubra Insects Edge LC - - 0 - x 2419 2419 2419 0 Red-hooded Tanager Piranga rubriceps Fruit Forest LC - - 0 - x 2599 2586 2613 27 Parulidae Russet-crowned Warbler Basileuterus coronatus Insects Forest LC x x 2556 2403 2735 332 x x 2566 2432 2737 305 Three-striped Warbler Basileuterus tristriatus Insects Forest LC x x 2605 2534 2679 219 x x 2569 2530 2642 334 Canada Warbler Cardellina canadensis Insects Edge LC x 2725 2725 2725 0 - - 0 - Citrine Warbler Basileuterus luteoviridis Insects Forest LC x x 2656 2600 2767 167 x - - 0 - Black-and-white Warbler Mniotilta varia Insects Forest LC x 2630 2535 2725 190 x 2419 2419 2419 0 Slate-throated Whitestart Myioborus miniatus Insects Forest LC x x 2533 2465 2603 275 x x 2521 2451 2567 116 Golden-fronted Whitestart Myioborus ornatus Insects Interior LC x x 2561 2403 2735 332 x x 2613 2412 2723 311 Blackburnian Warbler Setophaga fusca Insects Forest LC x 2572 2497 2664 335 x 2491 2396 2690 294 Tropical Parula Setophaga pitiayumi Insects Forest LC x 2600 2600 2600 0 - - 0 - Icteridae Yellow-billed Cacique Amblycercus holosericeus Insects Forest LC F - - 0 - - - 0 - Mountain Cacique Cacicus chrysonotus Insects Forest LC x 2529 2476 2588 112 x x 2551 2498 2667 255 Subtropical Cacique Cacicus uropygialis Insects Forest LC F - - 0 - - - 0 - Red-bellied Grackle Hypopyrrhus pyrohypogaster Insects Forest EN x x 2525 2396 2563 335 x 2410 2403 2432 43 Russet-backed Oropendola Psarocolius angustifrons All Edge LC - - 0 - x 2428 2423 2448 49 Fringillidae Yellow-bellied Siskin Carduelis xanthogastra Seeds Edge LC - - 0 - x 2401 2401 2401 0 Blue-naped Chlorophonia Chlorophonia cyanea Fruit Forest LC x 2551 2551 2551 0 x 2541 2541 2541 0 Chestnut-breasted Chlorophonia pyrrhophrys Fruit Forest LC x 2450 2450 2450 0 x 2527 2484 2569 0

Chlorophonia Golden-rumped Euphonia Euphonia cyanocephala Fruit Edge LC - - 0 - x 2534 2534 2534 0 Orange-crowned Euphonia Euphonia saturata Fruit Edge LC - - 0 - x - - 0 - Orange-bellied Euphonia Euphonia xanthogaster Fruit Edge LC x x 2576 2576 2576 0 x x 2419 2419 2419 0 Total/method 157 100 162 105 Total/transect 171 177

134

Appendix 7

Bird species used in maps of conservation priorities for the Atlantic Forest in Brazil, including range size and threat category

reassessment during the range refining process.

BirdLife % Species Common name IUCN min max TC Ref_elev TC For_30m TC1 For_250m TC Range region2

Acrobatornis fonsecai Pink-legged Graveteiro VU 0 550 2284 EN 2033 EN 89 CR 1508 EN 100 Amaurospiza moesta Blackish-blue Seedeater NT 0 1600 530176 NT/LC 527175 NT/LC 87354 NT/LC 108955 NT/LC 87 Amazona brasiliensis Red-tailed Amazon VU 0 700 4673 EN 4366 EN 3520 EN 3543 EN 98 Amazona rhodocorytha Red-browed Amazon EN 0 1000 26968 NT/LC 26109 NT/LC 4142 EN 10852 VU 99 White-browed Foliage- Anabacerthia amaurotis gleaner NT 100 1500 417687 NT/LC 394379 NT/LC 63241 NT/LC 85390 NT/LC 83 135 White-collared Foliage-

Anabazenops fuscus gleaner LC 350 1250 335338 NT/LC 215047 NT/LC 37001 NT/LC 34881 NT/LC 89 Arremon semitorquatus Half-collared Sparrow LC 0 1000 144190 NT/LC 126473 NT/LC 31136 NT/LC 30794 NT/LC 99 Attila rufus Grey-hooded Attila LC 0 1500 335569 NT/LC 330704 NT/LC 67139 NT/LC 80893 NT/LC 97 Baryphthengus ruficapillus Rufous-capped Motmot LC 0 1250 921733 NT/LC 904093 NT/LC 119623 NT/LC 132994 NT/LC 59 Biatas nigropectus White-bearded Antshrike VU 0 1200 153857 NT/LC 145838 NT/LC 43613 NT/LC 51485 NT/LC 95 Brotogeris tirica Plain Parakeet LC 0 1300 276295 NT/LC 272841 NT/LC 61123 NT/LC 76450 NT/LC 95 Buteogallus aequinoctialis Rufous Crab-hawk NT 0 100 144016 NT/LC 78052 NT/LC 15461 VU 14194 VU 44 Buteogallus lacernulatus White-necked Hawk VU 0 2890 148162 NT/LC 147120 NT/LC 34054 NT/LC 33322 NT/LC 69 Calyptura cristata Kinglet Calyptura CR 0 900 2935 EN 1534 EN 335 EN 280 EN 100 Campephilus robustus Robust Woodpecker LC 0 2200 994459 NT/LC 993273 NT/LC 125176 NT/LC 139949 NT/LC 52 Campylorhamphus falcularius Black-billed Scythebill LC 0 1600 670265 NT/LC 667250 NT/LC 103476 NT/LC 128290 NT/LC 76 Carpornis cucullata Hooded Berryeater NT 400 1600 209218 NT/LC 143768 NT/LC 34851 NT/LC 44059 NT/LC 83 Carpornis melanocephala Black-headed Berryeater VU 0 500 80745 NT/LC 52414 NT/LC 15809 VU 19396 VU 97 Cercomacra brasiliana Rio de Janeiro Antbird NT 600 950 114215 NT/LC 18353 VU 3239 EN 2614 EN 99

Chamaeza meruloides Such's Antthrush LC 500 1900 99503 NT/LC 67071 NT/LC 17451 VU 19966 VU 100 Chamaeza ruficauda Rufous-tailed Antthrush LC 600 2200 361283 NT/LC 206707 NT/LC 38487 NT/LC 52610 NT/LC 97 Chiroxiphia caudata Swallow-tailed Manakin LC 0 1900 900246 NT/LC 898644 NT/LC 116367 NT/LC 127016 NT/LC 61 Cichlocolaptes leucophrus Pale-browed Treehunter LC 0 1450 283763 NT/LC 279513 NT/LC 55767 NT/LC 64101 NT/LC 95 Purple-winged Ground- Claravis geoffroyi dove CR 0 2300 198279 NT/LC 197152 NT/LC 46682 NT/LC 49093 NT/LC 79 Clibanornis dendrocolaptoides Canebrake Groundcreeper NT 0 800 371221 NT/LC 252795 NT/LC 34346 NT/LC 35745 NT/LC 82 Clytolaema rubricauda Brazilian Ruby LC 750 1000 338331 NT/LC 70504 NT/LC 15274 VU 18456 VU 95 Conopophaga lineata Rufous Gnateater LC 300 2400 977766 NT/LC 821744 NT/LC 103174 NT/LC 115561 NT/LC 52 Cotinga maculata Banded Cotinga EN 0 200 154981 NT/LC 78353 NT/LC 9490 VU 13431 VU 100 Cranioleuca obsoleta Olive Spinetail LC 0 1000 404351 NT/LC 366995 NT/LC 55110 NT/LC 69467 NT/LC 62 Cranioleuca pallida Pallid Spinetail LC 700 2200 374747 NT/LC 168097 NT/LC 25942 NT/LC 25916 NT/LC 54 Crax blumenbachii Red-billed Curassow EN 0 500 138374 NT/LC 99766 NT/LC 10027 VU 12559 VU 100 Crax fasciolata Bare-faced Curassow VU 0 900 190923 NT/LC 186450 NT/LC 12855 VU 3372 EN 6

136 Cyanocorax caeruleus Azure Jay NT 0 1000 334388 NT/LC 297354 NT/LC 56347 NT/LC 74935 NT/LC 64

Dacnis nigripes Black-legged Dacnis NT 0 800 51130 NT/LC 38941 NT/LC 11385 VU 11515 VU 99 Drymophila ferruginea Ferruginous Antbird LC 0 1250 431167 NT/LC 419855 NT/LC 64997 NT/LC 71669 NT/LC 85 Drymophila genei Rufous-tailed Antbird LC 1000 2200 22422 NT/LC 9821 VU 3816 EN 4549 EN 100 Drymophila malura Dusky-tailed Antbird LC 0 1900 548196 NT/LC 547064 NT/LC 90902 NT/LC 113789 NT/LC 71 Drymophila ochropyga Ochre-rumped Antbird NT 600 1300 161575 NT/LC 76736 NT/LC 16453 VU 21697 NT/LC 88 Drymophila rubricollis Bertoni's Antbird LC 0 2000 281070 NT/LC 280873 NT/LC 37602 NT/LC 50641 NT/LC 85 Drymophila squamata Scaled Antbird LC 0 900 283098 NT/LC 262636 NT/LC 42984 NT/LC 47907 NT/LC 94 Dysithamnus plumbeus Plumbeous Antvireo VU 0 800 60297 NT/LC 58799 NT/LC 5182 VU 4644 EN 100 Dysithamnus stictothorax Spot-breasted Antvireo NT 0 1200 406800 NT/LC 395117 NT/LC 67549 NT/LC 82549 NT/LC 97 Dysithamnus xanthopteru Rufous-backed Antvireo LC 750 1700 60681 NT/LC 24395 NT/LC 6367 VU 9373 VU 100 Elaenia ridleyana Noronha Elaenia VU 0 0 15 CR 0 CR 0 CR 0 CR 76 Eleoscytalopus indigoticus White-breasted Tapaculo NT 0 1000 455608 NT/LC 406039 NT/LC 66119 NT/LC 76720 NT/LC 91 Eleoscytalopus psychopompus Bahia Tapaculo CR 15 200 7899 VU 6059 VU 1428 EN 3979 EN 100

Euphonia chalybea Green-throated Euphonia NT 0 950 565418 NT/LC 503865 NT/LC 75863 NT/LC 84630 NT/LC 75 Florisuga fusca Black Jacobin LC 0 1400 439657 NT/LC 431987 NT/LC 72886 NT/LC 77507 NT/LC 65 Formicivora erythronotos Black-hooded Antwren EN 0 50 79 CR 39 CR 16 CR 10 CR 60 Glaucidium minutissimum Least Pygmy-owl LC 0 1100 788793 NT/LC 757033 NT/LC 92968 NT/LC 92962 NT/LC 65 Glaucis dohrnii Hook-billed Hermit EN 0 500 109122 NT/LC 92815 NT/LC 10035 VU 15050 VU 100 Haplospiza unicolor Uniform Finch LC 0 2100 684590 NT/LC 683655 NT/LC 101640 NT/LC 120691 NT/LC 70 Heliobletus contaminatus Sharp-billed Treehunter LC 750 1830 596854 NT/LC 233083 NT/LC 35115 NT/LC 54802 NT/LC 76 Drab-breasted Bamboo- Hemitriccus diops tyrant LC 0 1300 609853 NT/LC 599775 NT/LC 85826 NT/LC 98419 NT/LC 82 Hemitriccus furcatus Fork-tailed Pygmy-tyrant VU 0 1200 60798 NT/LC 52368 NT/LC 10768 VU 11027 VU 100 Brown-breasted Bamboo- Hemitriccus obsoletus tyrant LC 500 2300 243662 NT/LC 197749 NT/LC 28589 NT/LC 50958 NT/LC 92 Hemitriccus orbitatus Eye-ringed Tody-tyrant NT 0 600 534731 NT/LC 275237 NT/LC 35798 NT/LC 28808 NT/LC 80 Hylatomus galeatus Helmeted Woodpecker VU 0 950 380072 NT/LC 353383 NT/LC 50332 NT/LC 55663 NT/LC 69

137 Hylopezus nattereri Speckle-breasted Antpitta LC 300 1900 395091 NT/LC 336546 NT/LC 56794 NT/LC 84954 NT/LC 80 Hylophilus poicilotis Rufous-crowned Greenlet LC 0 1900 513557 NT/LC 512996 NT/LC 64582 NT/LC 82286 NT/LC 73

Hypoedaleus guttatus Spot-backed Antshrike LC 0 900 778872 NT/LC 647935 NT/LC 78068 NT/LC 71101 NT/LC 64 Ilicura militaris Pin-tailed Manakin LC 0 1250 624921 NT/LC 611964 NT/LC 82003 NT/LC 91391 NT/LC 74 Iodopleura pipra Buff-throated Purpletuft NT 0 900 238014 NT/LC 213377 NT/LC 37525 NT/LC 41013 NT/LC 92 Jacamaralcyon tridactyla Three-toed Jacamar VU 240 1100 294793 NT/LC 258138 NT/LC 29907 NT/LC 30774 NT/LC 75 Lepidocolaptes falcinellus Scalloped Woodcreeper LC 0 1600 302668 NT/LC 302236 NT/LC 60874 NT/LC 85218 NT/LC 69 Lepidocolaptes squamatus Scaled Woodcreeper LC 0 1600 383822 NT/LC 381642 NT/LC 37111 NT/LC 27949 NT/LC 51 Leptasthenura setaria Araucaria Tit-spinetail NT 750 1900 364424 NT/LC 172776 NT/LC 28015 NT/LC 50072 NT/LC 92 Leptasthenura striolata Striolated Tit-spinetail LC 500 1200 208047 NT/LC 180227 NT/LC 27665 NT/LC 49208 NT/LC 99 Leptodon forbesi White-collared Kite CR 0 600 12554 VU 12165 VU 1331 EN 366 EN 100 White-throated Leucochloris albicollis Hummingbird LC 0 1000 839904 NT/LC 754648 NT/LC 97639 NT/LC 100471 NT/LC 38 Lipaugus lanioides Cinnamon-vented Piha NT 0 1000 219402 NT/LC 201297 NT/LC 45932 NT/LC 47303 NT/LC 89 Mackenziaena severa Tufted Antshrike LC 0 1400 759617 NT/LC 752503 NT/LC 99862 NT/LC 106893 NT/LC 79

Macropsalis forcipata Long-trained Nightjar LC 600 2000 463198 NT/LC 295195 NT/LC 48391 NT/LC 68658 NT/LC 89 Greater Crescent-chested Malacoptila striata Puffbird NT 0 2100 616235 NT/LC 614935 NT/LC 81283 NT/LC 83587 NT/LC 84 Yellow-fronted Melanerpes flavifrons Woodpecker LC 0 1800 964302 NT/LC 961827 NT/LC 127686 NT/LC 144901 NT/LC 62 Merulaxis ater Slaty Bristlefront NT 800 1800 164312 NT/LC 29245 NT/LC 9115 VU 11717 VU 100 Merulaxis stresemanni Stresemann's Bristlefront CR 0 800 89 CR 83 CR 16 CR 25 CR 92 Mionectes rufiventris Grey-hooded Flycatcher LC 0 1000 783012 NT/LC 698363 NT/LC 95092 NT/LC 99937 NT/LC 74 Muscipipra vetula Shear-tailed Grey-tyrant LC 0 2200 620964 NT/LC 620113 NT/LC 95589 NT/LC 117391 NT/LC 75 Myrmeciza loricata White-bibbed Antbird LC 700 1300 158738 NT/LC 31962 NT/LC 6454 VU 6244 VU 89 Myrmeciza ruficauda Scalloped Antbird EN 0 600 129193 NT/LC 117418 NT/LC 13653 VU 19409 VU 99 Myrmeciza squamosa Squamate Antbird LC 0 1000 215939 NT/LC 191068 NT/LC 50529 NT/LC 65023 NT/LC 89 Myrmotherula fluminensis Rio de Janeiro Antwren CR 35 200 76 CR 30 CR 11 CR 10 CR 100 Myrmotherula gularis Star-throated Antwren LC 400 1550 466252 NT/LC 336069 NT/LC 55725 NT/LC 69919 NT/LC 93

138 Myrmotherula minor Salvadori's Antwren VU 0 800 40486 NT/LC 36838 NT/LC 8052 VU 7871 VU 99 Myrmotherula snowi Alagoas Antwren CR 400 550 146 EN 22 CR 12 CR 8 CR 95

Myrmotherula unicolor Unicoloured Antwren NT 0 500 70887 NT/LC 49884 NT/LC 16272 VU 16372 VU 97 Myrmotherula urosticta Band-tailed Antwren VU 0 100 115336 NT/LC 43157 NT/LC 6636 VU 7641 VU 100 Nemosia rourei Cherry-throated Tanager CR 900 1100 508 EN 175 EN 46 CR 20 CR 100 Rufous-vented Ground- Neomorphus geoffroyi cuckoo VU 0 1200 304079 NT/LC 300976 NT/LC 35408 NT/LC 40263 NT/LC 10 Neopelma aurifrons Wied's Tyrant-manakin VU 0 1000 261114 NT/LC 254401 NT/LC 29705 NT/LC 34696 NT/LC 92 Serra do Mar Tyrant- Neopelma chrysolophum manakin NT 1150 1750 158671 NT/LC 14312 VU 3454 EN 3981 EN 99 Notharchus swainsoni Buff-bellied Puffbird LC 0 100 661926 NT/LC 36869 NT/LC 8134 VU 7234 VU 71 Odontophorus capueira Spot-winged Wood-quail LC 0 1600 1066460 NT/LC 1061822 NT/LC 140739 NT/LC 155837 NT/LC 61 Onychorhynchus swainsoni Atlantic Royal Flycatcher VU 0 1200 194236 NT/LC 186410 NT/LC 39362 NT/LC 45009 NT/LC 97 Orchesticus abeillei Brown Tanager NT 900 1500 136010 NT/LC 26059 NT/LC 5630 VU 8497 VU 93 Orthogonys chloricterus Olive-green Tanager LC 700 1800 121575 NT/LC 46480 NT/LC 14394 VU 18640 VU 100 Phacellodomus erythrophthalmus Orange-eyed Thornbird LC 0 1250 361846 NT/LC 353148 NT/LC 47235 NT/LC 49369 NT/LC 91

Phaethornis eurynome Scale-throated Hermit LC 100 2250 737802 NT/LC 699589 NT/LC 99648 NT/LC 116235 NT/LC 79 Phaethornis idaliae Minute Hermit LC 0 500 155653 NT/LC 109953 NT/LC 10900 VU 11364 VU 100 Phaethornis squalidus Dusky-throated Hermit LC 0 2250 266646 NT/LC 265783 NT/LC 55131 NT/LC 54669 NT/LC 97 Black-capped Foliage- Philydor atricapillus gleaner LC 0 1050 859007 NT/LC 796927 NT/LC 107144 NT/LC 119499 NT/LC 76 Ochre-breasted Foliage- Philydor lichtensteini gleaner LC 0 800 813843 NT/LC 599627 NT/LC 67370 NT/LC 58012 NT/LC 51 Philydor novaesi Alagoas Foliage-gleaner CR 400 550 36 CR 11 CR 3 CR 3 CR 100 Phyllomyias griseocapilla Grey-capped Tyrannulet NT 750 1850 182864 NT/LC 59020 NT/LC 15236 VU 19772 VU 100 Phyllomyias virescens Greenish Tyrannulet LC 0 1800 725371 NT/LC 723557 NT/LC 103165 NT/LC 117849 NT/LC 70 Phylloscartes beckeri Bahia Tyrannulet EN 800 1200 865 EN 216 EN 74 CR 76 CR 37 Phylloscartes ceciliae Alagoas Tyrannulet EN 400 550 81 CR 38 CR 9 CR 7 CR 72 Phylloscartes difficilis Serra do Mar Tyrannulet NT 950 2150 152553 NT/LC 24770 NT/LC 7772 VU 10646 VU 99 Phylloscartes eximius Southern Bristle-tyrant NT 0 600 713372 NT/LC 345334 NT/LC 44116 NT/LC 34455 NT/LC 70

139 Phylloscartes oustaleti Oustalet's Tyrannulet NT 500 900 74773 NT/LC 23218 NT/LC 7032 VU 7482 VU 99 Phylloscartes paulista Sao Paulo Tyrannulet NT 0 500 419050 NT/LC 161823 NT/LC 28854 NT/LC 24386 NT/LC 84

Phylloscartes sylviolus Bay-ringed Tyrannulet NT 0 600 341246 NT/LC 150576 NT/LC 29957 NT/LC 28572 NT/LC 78 Yellow-browed Piculus aurulentus Woodpecker NT 750 2000 516228 NT/LC 195435 NT/LC 33420 NT/LC 53798 NT/LC 69 Picumnus fulvescens Tawny Piculet LC 0 950 22722 NT/LC 22600 NT/LC 2306 EN 529 EN 19 Picumnus temminckii Ochre-collared Piculet LC 0 800 406630 NT/LC 272457 NT/LC 48268 NT/LC 55190 NT/LC 79 Pionopsitta pileata Pileated Parrot LC 0 2100 500169 NT/LC 498907 NT/LC 90033 NT/LC 115101 NT/LC 68 Pipile jacutinga Black-fronted Piping-guan EN 0 900 792741 NT/LC 647903 NT/LC 89560 NT/LC 94563 NT/LC 72 Piprites pileata Black-capped Piprites VU 500 2000 182891 NT/LC 161808 NT/LC 26812 NT/LC 46046 NT/LC 94 Platyrinchus leucoryphus Russet-winged Spadebill VU 0 900 380074 NT/LC 297992 NT/LC 58329 NT/LC 66278 NT/LC 78 Creamy-bellied Polioptila lactea Gnatcatcher NT 0 400 270903 NT/LC 71809 NT/LC 16105 VU 14675 VU 61 Procnias nudicollis Bare-throated Bellbird VU 0 1150 981416 NT/LC 948285 NT/LC 124430 NT/LC 139254 NT/LC 66 Pseudastur polionotus Mantled Hawk NT 0 1500 685787 NT/LC 679907 NT/LC 111908 NT/LC 139215 NT/LC 84 Psilorhamphus guttatus Spotted Bamboowren NT 300 900 259277 NT/LC 159166 NT/LC 27286 NT/LC 32466 NT/LC 94

Pteroglossus bailloni Saffron Toucanet NT 0 1550 524457 NT/LC 521596 NT/LC 75622 NT/LC 87633 NT/LC 79 Pyriglena atra Fringe-backed Fire-eye EN 20 250 5202 VU 4352 EN 445 EN 569 EN 100 Pyriglena leucoptera White-shouldered Fire-eye LC 0 1250 915194 NT/LC 897801 NT/LC 121815 NT/LC 137882 NT/LC 74 Pyrrhocoma ruficeps Chestnut-headed Tanager LC 0 1200 452544 NT/LC 437020 NT/LC 76615 NT/LC 101433 NT/LC 74 Pyrrhura cruentata Ochre-marked Parakeet VU 0 960 232993 NT/LC 224805 NT/LC 26136 NT/LC 28510 NT/LC 99 Pyrrhura frontalis Maroon-bellied Parakeet LC 0 1400 929582 NT/LC 921967 NT/LC 123701 NT/LC 134476 NT/LC 54 Pyrrhura griseipectus Grey-breasted Parakeet CR 500 1100 4548 EN 1 CR 0 CR 0 CR 44 Pyrrhura leucotis White-eared Parakeet NT 0 600 261254 NT/LC 180740 NT/LC 16837 VU 18042 VU 95 Ramphastos dicolorus Red-breasted Toucan LC 100 1500 811075 NT/LC 775796 NT/LC 99193 NT/LC 111355 NT/LC 58 Ramphodon naevius Saw-billed Hermit NT 0 900 217900 NT/LC 179832 NT/LC 41808 NT/LC 45823 NT/LC 98 Saltator fuliginosus Black-throated Grosbeak LC 0 1200 664820 NT/LC 645273 NT/LC 94033 NT/LC 112601 NT/LC 87 Saltator maxillosus Thick-billed Saltator LC 900 2200 389166 NT/LC 82843 NT/LC 15897 VU 30824 NT/LC 89 Schiffornis virescens Greenish Schiffornis LC 0 1700 855775 NT/LC 853485 NT/LC 111428 NT/LC 124124 NT/LC 51

140 Rufous-breasted Sclerurus scansor Leaftosser LC 0 1500 969683 NT/LC 964239 NT/LC 124766 NT/LC 132183 NT/LC 35

Scytalopus speluncae Mouse-coloured Tapaculo LC 750 2500 385376 NT/LC 182638 NT/LC 33900 NT/LC 54046 NT/LC 99 Selenidera maculirostris Spot-billed Toucanet LC 0 1000 764085 NT/LC 679634 NT/LC 96027 NT/LC 108954 NT/LC 82 Sporophila falcirostris Temminck's Seedeater VU 0 1200 23826 NT/LC 22369 NT/LC 9150 VU 9634 VU 54 Sporophila frontalis Buffy-fronted Seedeater VU 0 1500 110034 NT/LC 108676 NT/LC 34745 NT/LC 40149 NT/LC 62 Strix hylophila Rusty-barred Owl NT 0 1000 503910 NT/LC 436504 NT/LC 74543 NT/LC 88799 NT/LC 70 Synallaxis infuscata Pinto's Spinetail EN 0 550 21136 NT/LC 19521 VU 2234 EN 702 EN 84 Synallaxis ruficapilla Rufous-capped Spinetail LC 0 1400 807454 NT/LC 799494 NT/LC 109706 NT/LC 122673 NT/LC 68 Synallaxis whitneyi Bahia Spinetail VU 750 1200 507 EN 88 CR 34 CR 61 CR 25 Tachyphonus coronatus Ruby-crowned Tanager LC 0 1200 828220 NT/LC 804512 NT/LC 107262 NT/LC 117580 NT/LC 61 Tangara cyanoventris Gilt-edged Tanager LC 0 1000 354513 NT/LC 306640 NT/LC 38402 NT/LC 34022 NT/LC 74 Tangara desmaresti Brassy-breasted Tanager LC 800 1800 203958 NT/LC 90950 NT/LC 14667 VU 17853 VU 92 Tangara fastuosa Seven-coloured Tanager VU 0 550 14613 VU 13170 VU 1796 EN 624 EN 92 Tangara seledon Green-headed Tanager LC 0 900 582165 NT/LC 459410 NT/LC 76998 NT/LC 87043 NT/LC 86

Terenura maculata Streak-capped Antwren LC 0 1250 668008 NT/LC 654644 NT/LC 95569 NT/LC 110947 NT/LC 85 Terenura sicki Orange-bellied Antwren EN 400 700 11293 VU 4503 EN 448 EN 133 EN 83 Violet-capped Thalurania glaucopis Woodnymph 0 850 908478 NT/LC 710960 NT/LC 89766 NT/LC 85164 NT/LC 64

Thamnophilus ambiguus Sooretama Slaty-antshrike LC 0 700 210314 NT/LC 170705 NT/LC 19710 VU 20685 NT/LC 100 Thraupis cyanoptera Azure-shouldered Tanager NT 200 950 213413 NT/LC 117376 NT/LC 33583 NT/LC 38730 NT/LC 95 Golden-chevroned Thraupis ornata Tanager LC 0 1750 381792 NT/LC 379672 NT/LC 64626 NT/LC 70341 NT/LC 97 Thripophaga macroura Striated Softtail VU 0 1000 145336 NT/LC 142293 NT/LC 16919 VU 23389 NT/LC 100 Tijuca atra Black-and-gold Cotinga NT 1100 2100 31731 NT/LC 6067 VU 2032 EN 2905 EN 100 Tijuca condita Grey-winged Cotinga VU 1650 2010 3930 EN 69 CR 23 CR 40 CR 100 Tinamus solitarius Solitary Tinamou NT 0 1200 896445 NT/LC 872974 NT/LC 119827 NT/LC 137552 NT/LC 83 Yellow-lored Tody- Todirostrum poliocephalum flycatcher LC 0 1200 357321 NT/LC 341919 NT/LC 56036 NT/LC 53693 NT/LC 76 Touit melanonotus Brown-backed Parrotlet EN 0 1400 25248 NT/LC 22999 NT/LC 11064 VU 11824 VU 99

141 Touit surdus Golden-tailed Parrotlet VU 0 1000 87135 NT/LC 81630 NT/LC 23576 NT/LC 24870 NT/LC 87

Triclaria malachitacea Blue-bellied Parrot NT 300 1000 44156 NT/LC 16110 VU 4883 EN 7423 VU 89 Trogon surrucura Southern Surucua Trogon LC 0 2000 708121 NT/LC 707173 NT/LC 89343 NT/LC 101793 NT/LC 52 Veniliornis maculifrons Yellow-eared Woodpecker LC 0 1300 243198 NT/LC 240024 NT/LC 29742 NT/LC 30261 NT/LC 95 White-spotted Veniliornis spilogaster Woodpecker LC 0 2000 686827 NT/LC 685759 NT/LC 95211 NT/LC 111447 NT/LC 44 Vireo gracilirostris Noronha Vireo NT 0 60 12 CR 0 CR 0 CR 0 CR 57 White-throated Xiphocolaptes albicollis Woodcreeper LC 0 2000 1030287 NT/LC 1028611 NT/LC 133979 NT/LC 148938 NT/LC 49 Xipholena atropurpurea White-winged Cotinga EN 0 900 196518 NT/LC 191111 NT/LC 21844 NT/LC 25141 NT/LC 91 Xiphorhynchus fuscus Lesser Woodcreeper LC 0 1300 1005004 NT/LC 991293 NT/LC 132899 NT/LC 146655 NT/LC 45

Appendix 8

Bird species used in maps of conservation priorities for Central America, including range size and threat category reassessment

during the range refining process.

BirdLife % Species Common name IUCN min max TC Ref_elev TC For_30m TC1 For_250m TC Range region2

Acanthidops bairdi Peg-billed Finch LC 1500 3000 4777 EN 3844 EN 3744 EN 2914 EN 100 Amazilia boucardi Mangrove Hummingbird EN 0 100 1121 EN 888 EN 519 EN 303 EN 85 Amazilia decora Charming Hummingbird LC 0 100 12974 VU 3790 EN 2202 EN 1444 EN 98 Amazona auropalliata Yellow-naped Amazon VU 0 600 126636 VU 105447 VU 41327 VU 18443 VU 98 Amazona guatemalae Northern Mealy Amazon NT 0 1500 332325 NT/LC 311748 NT/LC 201182 NT/LC 121603 NT/LC 90 Antrostomus saturatus Dusky Nightjar LC 1500 3100 5420 VU 4618 EN 4485 EN 3471 EN 100

142 Ara ambiguus Great Green Macaw EN 0 1500 97963 EN 92656 EN 73694 EN 43106 NT/LC 64

Arremon crassirostris Sooty-faced Finch LC 600 2000 9547 VU 5883 VU 5656 VU 3229 EN 100 Aspatha gularis Blue-throated Motmot LC 1300 3000 99744 NT/LC 39005 NT/LC 26431 NT/LC 12925 VU 100 Atthis ellioti Wine-throated Hummingbird LC 1500 3500 95624 NT/LC 29817 NT/LC 19882 VU 9699 VU 100 Bangsia arcaei Blue-and-gold Tanager NT 300 1500 9012 VU 7288 VU 6844 VU 4123 EN 100 Basileuterus ignotus Pirre Warbler VU 1200 1650 161 EN 77 CR 80 CR 6 CR 88 Basileuterus melanogenys Black-cheeked Warbler LC 2500 3500 4867 EN 1319 EN 1307 EN 1157 EN 100 Buteogallus solitarius Black Solitary Eagle NT 600 2200 187469 NT/LC 117214 NT/LC 66670 NT/LC 33391 NT/LC 19 Calliphlox bryantae Magenta-throated Woodstar LC 700 1900 9252 VU 7710 VU 5970 VU 2327 EN 100 Campephilus splendens Splendid Woodpecker NT 0 2200 27481 NT/LC 26137 NT/LC 24600 NT/LC 11980 VU 15 Carduelis atriceps Black-capped Siskin LC 2300 3100 50383 NT/LC 6282 VU 3963 EN 1761 EN 100 Carpodectes antoniae Yellow-billed Cotinga EN 0 760 1491 EN 1345 EN 967 EN 636 EN 89 Carpodectes nitidus Snowy Cotinga LC 0 750 102587 NT/LC 95587 NT/LC 63433 NT/LC 36276 NT/LC 99 Catharus gracilirostris Black-billed Nightingale-thrush LC 1800 3500 3855 EN 3421 EN 3308 EN 2571 EN 100 Cephalopterus glabricollis Bare-necked Umbrellabird EN 100 2000 32100 EN 21244 EN 18634 EN 11043 VU 100 Chamaepetes unicolor Black Guan NT 450 2250 15686 VU 14136 VU 12157 VU 6147 VU 100 Chlorophonia callophrys Golden-browed Chlorophonia LC 750 2500 17557 VU 14432 VU 12809 VU 7017 VU 100 Chlorospingus inornatus Pirre Bush-tanager LC 800 1550 987 EN 173 EN 175 EN 92 CR 99 Chlorospingus pileatus Sooty-capped Bush-tanager LC 1500 3000 3970 EN 3367 EN 3219 EN 2341 EN 100

Chlorospingus tacarcunae Tacarcuna Bush-tanager LC 850 1500 1422 EN 176 EN 183 EN 39 CR 100 Chlorostilbon assimilis Garden Emerald LC 0 800 48781 NT/LC 43644 NT/LC 22785 NT/LC 8373 VU 98 Chrysothlypis chrysomelas Black-and-yellow Tanager LC 350 1600 15762 VU 11109 VU 10444 VU 4577 EN 100 Contopus lugubris Dark Pewee LC 900 2700 8260 VU 7370 VU 6952 VU 4328 EN 100 Contopus ochraceus Ochraceous Pewee LC 2200 3000 3168 EN 1980 EN 1982 EN 1657 EN 100 Cotinga ridgwayi Turquoise Cotinga VU 0 1850 12668 VU 11981 VU 7766 VU 3645 EN 98 Crax rubra Great Curassow VU 0 1900 436160 VU 408845 VU 271512 VU 163324 NT/LC 65 Cryptoleucopteryx plumbea Plumbeous Hawk VU 0 800 20395 VU 18306 VU 17582 VU 8413 VU 12 Crypturellus kerriae Choco Tinamou VU 0 1500 6980 VU 6640 VU 6735 VU 3380 EN 37 Cyanocorax melanocyaneus Bushy-crested Jay LC 600 2450 118688 NT/LC 84541 NT/LC 41491 NT/LC 17418 VU 100 Cyanolyca argentigula Silvery-throated Jay LC 2000 3200 3954 EN 2803 EN 2776 EN 2209 EN 100 Cyrtonyx ocellatus Ocellated Quail VU 750 3050 131706 VU 86237 VU 53430 VU 25129 NT/LC 100 Dacnis viguieri Viridian Dacnis NT 0 600 7270 VU 5557 VU 5722 VU 4071 EN 34 Deconychura longicauda Long-tailed Woodcreeper NT 400 1700 41780 NT/LC 9210 VU 8874 VU 3412 EN 1 Doricha enicura Slender Sheartail LC 1000 3000 79115 NT/LC 42095 NT/LC 23775 NT/LC 9257 VU 100 Dysithamnus striaticeps Streak-crowned Antvireo LC 0 900 87729 NT/LC 83424 NT/LC 55406 NT/LC 32540 NT/LC 99 Electron carinatum Keel-billed Motmot VU 0 1555 39984 VU 37784 VU 28053 VU 20558 NT/LC 92 Elvira chionura White-tailed Emerald LC 750 2000 9669 VU 5732 VU 4316 EN 1421 EN 100

143 Elvira cupreiceps Coppery-headed Emerald LC 700 1500 5261 VU 1937 EN 1734 EN 1143 EN 100 Empidonax atriceps Black-capped Flycatcher LC 2100 3300 3688 EN 2604 EN 2578 EN 2104 EN 100 Ergaticus versicolor Pink-headed Warbler VU 1800 3500 17140 VU 15313 VU 9509 VU 4125 EN 100 Eupherusa nigriventris Black-bellied Hummingbird LC 900 2000 14444 VU 6409 VU 6088 VU 3470 EN 100 Euphonia anneae Tawny-capped Euphonia LC 600 1500 16947 VU 6443 VU 6104 VU 2761 EN 84 Euphonia imitans Spot-crowned Euphonia LC 0 1350 14694 VU 13677 VU 8739 VU 4229 EN 98 Goethalsia bella Pirre Hummingbird NT 600 1650 1873 EN 759 EN 779 EN 221 EN 98 Goldmania violiceps Violet-capped Hummingbird LC 600 1200 2496 EN 896 EN 919 EN 130 EN 87 Grallaricula flavirostris Ochre-breasted Antpitta NT 500 2750 6443 VU 5998 VU 5194 VU 2867 EN 3 Harpia harpyja Harpy Eagle NT 0 900 189693 NT/LC 166862 NT/LC 109602 NT/LC 64260 NT/LC 2 Heterospingus rubrifrons Sulphur-rumped Tanager LC 0 900 21443 NT/LC 20127 NT/LC 18200 VU 10509 VU 99 Hylorchilus navai Nava's Wren VU 75 800 3878 EN 3119 EN 2261 EN 1519 EN 100 Lampornis calolaemus Purple-throated Mountain-gem LC 1200 2500 11068 VU 3919 EN 3251 EN 1636 EN 100 Lampornis hemileucus White-bellied Mountain-gem LC 400 1400 9424 VU 6869 VU 6491 VU 4069 EN 100 Lampornis sybillae Green-breasted Mountain-gem LC 1000 2400 45497 NT/LC 14446 VU 9644 VU 5535 VU 100 Lampornis viridipallens Green-throated Mountain-gem LC 900 3100 92372 NT/LC 54863 NT/LC 36865 NT/LC 17851 VU 100 Lanio leucothorax White-throated Shrike-tanager LC 0 750 92219 NT/LC 86026 NT/LC 58752 NT/LC 35268 NT/LC 99 Leptotila battyi Brown-backed Dove VU 0 100 1772 EN 1 CR 0 CR 0 CR 98 Lophornis adorabilis White-crested Coquette LC 300 1200 16655 VU 7379 VU 4595 EN 1600 EN 98

Margarornis bellulus Beautiful Treerunner NT 1350 1600 235 EN 45 CR 46 CR 3 CR 86 Margarornis rubiginosus Ruddy Treerunner LC 1200 3000 5643 VU 4927 EN 4675 EN 3251 EN 100 Megascops barbarus Bearded Screech-owl VU 1800 2500 18483 VU 5325 VU 4118 EN 2171 EN 100 Megascops clarkii Bare-shanked Screech-owl LC 900 3300 8951 VU 8183 VU 7518 VU 4891 EN 90 Melanerpes chrysauchen Golden-naped Woodpecker LC 0 1500 15084 VU 13799 VU 8899 VU 4336 EN 98 Melanotis hypoleucus Blue-and-white Mockingbird LC 900 3000 93419 NT/LC 59450 NT/LC 37362 NT/LC 17040 VU 100 Meleagris ocellata Ocellated Turkey NT 0 300 161642 NT/LC 145992 NT/LC 107823 NT/LC 70706 NT/LC 100 Microchera albocoronata Snowcap LC 300 1650 76508 NT/LC 7953 VU 7192 VU 5127 VU 99 Morphnus guianensis Crested Eagle NT 0 1200 255145 NT/LC 237646 NT/LC 160473 NT/LC 92609 NT/LC 2 Myadestes coloratus Varied Solitaire LC 800 2200 449 EN 281 EN 289 EN 35 CR 97 Myadestes melanops Black-faced Solitaire LC 754 2940 32152 NT/LC 19649 VU 16711 VU 9145 VU 100 Myioborus torquatus Collared Redstart LC 1400 3500 5300 VU 4237 EN 4060 EN 2874 EN 100 Myiodynastes hemichrysus Golden-bellied Flycatcher LC 700 2300 16728 VU 10724 VU 9875 VU 5319 VU 100 Myrmornis torquata Wing-banded Antbird NT 0 1300 31929 NT/LC 30231 NT/LC 27537 NT/LC 12221 VU 1 Neomorphus geoffroyi Rufous-vented Ground-cuckoo VU 0 1200 102264 VU 96996 VU 70935 VU 35251 NT/LC 3 Notiochelidon pileata Black-capped Swallow LC 1600 3100 75775 NT/LC 24077 NT/LC 16028 VU 7468 VU 100 Odontophorus dialeucos Tacarcuna Wood-quail VU 1050 1500 195 EN 104 EN 109 EN 12 CR 83 Odontophorus gujanensis Marbled Wood-quail NT 0 1800 41402 NT/LC 39214 NT/LC 33334 NT/LC 15238 VU 1

144 Odontophorus leucolaemus Black-breasted Wood-quail LC 700 1850 9551 VU 7048 VU 6856 VU 4233 EN 100 Odontophorus melanotis Black-eared Wood-quail LC 0 1600 127726 NT/LC 121398 NT/LC 85186 NT/LC 47915 NT/LC 99 Oreophasis derbianus Horned Guan EN 1400 3500 31342 EN 24407 EN 15656 EN 7754 VU 100 Panterpe insignis Fiery-throated Hummingbird LC 1600 3200 8331 VU 5401 VU 5176 VU 3752 EN 100 Parula gutturalis Flame-throated Warbler LC 1800 3000 3942 EN 3272 EN 3159 EN 2433 EN 100 Passerina rositae Rose-bellied Bunting NT 150 800 4960 EN 2139 EN 925 EN 423 EN 71 Patagioenas leucocephala White-crowned Pigeon NT 0 1500 14375 VU 12283 VU 8486 VU 5702 VU 6 Penelopina nigra Highland Guan VU 700 3300 103668 VU 74004 VU 42698 VU 17947 VU 100 Pezopetes capitalis Large-footed Finch LC 2150 3350 3427 EN 2430 EN 2412 EN 2007 EN 100 Phainoptila melanoxantha Black-and-yellow Silky-flycatcher LC 1000 3400 6613 VU 5602 VU 5304 VU 3246 EN 100 Pharomachrus mocinno Resplendent Quetzal NT 1300 3000 150088 NT/LC 51429 NT/LC 37354 NT/LC 20510 NT/LC 100 Pheucticus tibialis Black-thighed Grosbeak LC 750 2600 19749 VU 12943 VU 11899 VU 7074 VU 100 Phylloscartes flavovirens Yellow-green Tyrannulet LC 900 2000 17273 VU 70 CR 71 CR 5 CR 99 Piculus callopterus Stripe-cheeked Woodpecker LC 300 900 5562 VU 3028 EN 3110 EN 546 EN 100 Piculus simplex Rufous-winged Woodpecker LC 0 900 91320 NT/LC 86558 NT/LC 59728 NT/LC 36886 NT/LC 98 Pittasoma michleri Black-crowned Antpitta LC 0 1050 37419 NT/LC 34874 NT/LC 31875 NT/LC 16912 VU 76 Procnias tricarunculatus Three-wattled Bellbird VU 0 3000 149842 VU 142099 VU 85228 VU 39789 NT/LC 99 Psarocolius guatimozinus Black Oropendola LC 0 800 8433 VU 7498 VU 6684 VU 3489 EN 8 Pselliophorus luteoviridis Yellow-green Finch VU 1200 1800 1379 EN 625 EN 574 EN 48 CR 100

Pselliophorus tibialis Yellow-thighed Finch LC 1500 3400 6606 VU 5329 VU 5117 VU 3809 EN 100 Psittacara finschi Crimson-fronted Parakeet LC 0 1600 92439 NT/LC 86321 NT/LC 50126 NT/LC 20424 NT/LC 99 Pteroglossus frantzi Fiery-billed Araçari LC 0 1200 19461 VU 17259 VU 10304 VU 4652 EN 98 Ptilogonys caudatus Long-tailed Silky-flycatcher LC 1800 3000 9614 VU 4290 EN 4153 EN 3078 EN 100 Pyrilia pyrilia Saffron-headed Parrot NT 0 1650 3651 EN 3477 EN 3596 EN 2860 EN 2 Pyrrhura eisenmanni Azuero Parakeet EN 100 2000 1523 EN 1046 EN 801 EN 394 EN 98 Pyrrhura hoffmanni Sulphur-winged Parakeet LC 1200 3000 8060 VU 6676 VU 6509 VU 4312 EN 100 Ramphastos ambiguus Yellow-throated Toucan NT 400 2670 135738 NT/LC 19490 VU 16889 VU 8193 VU 23 Sclerurus albigularis Grey-throated Leaftosser NT 50 2200 6858 VU 6504 VU 6114 VU 4062 EN 2 Scytalopus panamensis Tacarcuna Tapaculo VU 1020 1460 195 EN 100 CR 104 EN 11 CR 83 Selasphorus ardens Glow-throated Hummingbird EN 750 1850 3188 EN 2144 EN 1742 EN 267 EN 100 Selenidera spectabilis Yellow-eared Toucanet LC 300 1100 113022 NT/LC 21265 NT/LC 18493 VU 9263 VU 73 Semnornis frantzii Prong-billed Barbet LC 1200 2450 15989 VU 7765 VU 7235 VU 4389 EN 100 Spizaetus ornatus Ornate Hawk-eagle NT 0 1800 478162 NT/LC 440096 NT/LC 300062 NT/LC 176724 NT/LC 5 Strix fulvescens Fulvous Owl LC 1200 3100 116627 NT/LC 48164 NT/LC 32117 NT/LC 15823 VU 100 Tangara cabanisi Azure-rumped Tanager EN 850 1850 4542 EN 2900 EN 2680 EN 2036 EN 100 Tangara dowii Spangle-cheeked Tanager LC 1300 2700 12171 VU 7042 VU 6674 VU 4369 EN 100 Tangara fucosa Green-naped Tanager NT 1400 2000 1534 EN 61 CR 63 CR 3 CR 50

145 Thamnophilus bridgesi Black-hooded Antshrike LC 0 1150 27957 NT/LC 26094 NT/LC 13557 VU 5456 VU 98 Thripadectes rufobrunneus Streak-breasted Treehunter LC 700 3000 17723 VU 13857 VU 13159 VU 8371 VU 100 Thryothorus atrogularis Black-throated Wren LC 0 1100 32852 NT/LC 31239 NT/LC 21530 NT/LC 11039 VU 99 Thryothorus semibadius Riverside Wren LC 0 1200 12695 VU 11860 VU 7529 VU 3836 EN 98 Thryothorus thoracicus Stripe-breasted Wren LC 0 1100 73660 NT/LC 69677 NT/LC 46223 NT/LC 23709 NT/LC 99 Tinamus major Great Tinamou NT 0 1500 393741 NT/LC 369144 NT/LC 240109 NT/LC 135878 NT/LC 5 Touit costaricensis Red-fronted Parrotlet VU 500 3000 16744 VU 11861 VU 11618 VU 8342 VU 100 Troglodytes ochraceus Ochraceous Wren LC 900 2500 17458 VU 12146 VU 11183 VU 6286 VU 100 Troglodytes rufociliatus Rufous-browed Wren LC 1700 3500 99125 NT/LC 22201 NT/LC 14649 VU 6969 VU 100 Trogon bairdii Baird's Trogon NT 0 1250 12346 VU 10776 VU 7442 VU 3854 EN 98 Trogon clathratus Lattice-tailed Trogon LC 90 1360 16368 VU 12017 VU 10423 VU 6841 VU 100 Turdus nigrescens Sooty Thrush LC 2500 3500 2088 EN 1140 EN 1124 EN 1002 EN 100 Turdus rufitorques Rufous-collared Robin LC 1500 3500 61521 NT/LC 27492 NT/LC 17659 VU 8200 VU 100 Vireo carmioli Yellow-winged Vireo LC 1800 3300 4218 EN 3677 EN 3556 EN 2701 EN 100 Xenornis setifrons Spiny-faced Antshrike VU 120 800 8612 VU 6811 VU 6858 VU 2513 EN 49 Xenotriccus callizonus Belted Flycatcher NT 1200 1850 54267 NT/LC 23358 NT/LC 14999 VU 7671 VU 100 Zeledonia coronata Wrenthrush LC 1500 3300 5207 VU 4015 EN 3862 EN 2786 EN 100 Zentrygon chiriquensis Chiriqui Quail-dove LC 600 3100 16504 VU 15060 VU 12957 VU 6679 VU 100 Zentrygon costaricensis Buff-fronted Quail-dove LC 1000 3000 16645 VU 13044 VU 11810 VU 7031 VU 100

Zentrygon goldmani Russet-crowned Quail-dove NT 750 1600 2373 EN 947 EN 965 EN 146 EN 39 Zentrygon lawrencii Purplish-backed Quail-dove LC 400 1400 8027 VU 5538 VU 4961 EN 2777 EN 100

146

Appendix 9

Bird species used in maps of conservation priorities for Madagascar, including range size and threat category reassessment

during the range refining process.

BirdLife % Species Common name IUCN min max TC Ref_elev TC For_30m TC1 For_250m Range region2

Accipiter henstii Henst's Goshawk NT 0 1800 437328 NT/LC 434131 NT/LC 72378 NT/LC 52580 100 Accipiter madagascariensis Madagascar Sparrowhawk NT 0 1500 479481 NT/LC 468840 NT/LC 69995 NT/LC 50409 100 Artamella viridis White-headed Vanga LC 0 100 417883 NT/LC 113601 NT/LC 8093 VU 3634 100 Atelornis crossleyi Rufous-headed Ground-roller NT 800 2000 22561 NT/LC 20824 VU 16738 VU 16145 100 Atelornis pittoides Pitta-like Ground-roller LC 0 2000 46200 NT/LC 45728 NT/LC 36365 NT/LC 34620 100 Bernieria apperti Appert's Tetraka VU 600 1300 7852 VU 4687 EN 101 EN 63 100

147 Bernieria cinereiceps Grey-crowned Tetraka NT 900 2000 164831 NT/LC 100760 NT/LC 25384 NT/LC 21960 100

Bernieria madagascariensis Common Tetraka LC 0 100 448712 NT/LC 104241 NT/LC 8200 VU 3704 100 Bernieria tenebrosa Dusky Tetraka VU 200 950 16056 VU 13848 VU 11259 VU 10838 100 Bernieria zosterops Spectacled Tetraka LC 0 100 211699 NT/LC 34455 NT/LC 7378 VU 2353 100 Brachypteracias leptosomus Short-legged Ground-roller VU 0 1200 39314 NT/LC 37585 NT/LC 28411 NT/LC 26967 100 Calicalicus madagascariensis Red-tailed Vanga LC 0 100 343588 NT/LC 101159 NT/LC 8088 VU 3630 100 Copsychus albospecularis Madagascar Magpie-robin LC 0 100 594796 NT/LC 114283 NT/LC 8183 VU 3686 100 Coua serriana Red-breasted Coua LC 0 1000 63143 NT/LC 42584 NT/LC 23953 NT/LC 20040 100 Crossleyia xanthophrys Madagascar Yellowbrow NT 900 2300 22861 NT/LC 19269 VU 15550 VU 14999 100 Cryptosylvicola randrianasoloi Cryptic Warbler LC 900 2500 115908 NT/LC 65363 NT/LC 25398 NT/LC 22135 100 Cyanolanius madagascarinus Blue Vanga LC 0 100 448135 NT/LC 103950 NT/LC 8205 VU 3707 100 Dromaeocercus brunneus Brown Emu-tail LC 500 2500 52710 NT/LC 45964 NT/LC 34702 NT/LC 32534 100 Euryceros prevostii Helmet Vanga VU 0 1000 16348 VU 16000 VU 12992 VU 12246 100 Eutriorchis astur Madagascar Serpent-eagle EN 0 1500 34687 NT/LC 33209 NT/LC 26399 NT/LC 24783 100 Foudia madagascariensis Madagascar Red Fody LC 0 100 594444 NT/LC 114010 NT/LC 8094 VU 3634 99 Foudia omissa Forest Fody LC 0 2000 294139 NT/LC 291876 NT/LC 70251 NT/LC 49974 100 Gactornis enarratus Collared Nightjar LC 0 1880 227788 NT/LC 225409 NT/LC 69914 NT/LC 49582 100 Geobiastes squamiger Scaly Ground-roller VU 0 1000 21325 NT/LC 20696 VU 15676 VU 14698 100 Hypositta corallirostris Nuthatch Vanga LC 0 100 160572 NT/LC 22357 NT/LC 5859 VU 2105 100

Leptopterus chabert Chabert's Vanga LC 0 100 581476 NT/LC 114390 NT/LC 8204 VU 3705 100 Mesitornis unicolor Brown Mesite VU 0 1200 37398 NT/LC 35857 NT/LC 27494 NT/LC 26155 100 Mesitornis variegatus White-breasted Mesite VU 0 350 39785 NT/LC 32652 NT/LC 349 EN 842 100 Monias benschi Subdesert Mesite VU 0 100 12391 VU 5967 VU 3 CR 1 100 Monticola erythronotus Amber Mountain Rock-thrush EN 800 1300 380 NT/LC 189 EN 151 EN 164 100 Monticola sharpei Forest Rock-thrush LC 800 2050 244362 NT/LC 131844 NT/LC 30767 NT/LC 26401 100 Mystacornis crossleyi Crossley's Babbler LC 0 100 160911 NT/LC 33608 NT/LC 7300 VU 2336 100 Neodrepanis coruscans Sunbird Asity LC 400 1800 166382 NT/LC 120371 NT/LC 48155 NT/LC 39859 100 Neomixis flavoviridis Wedge-tailed Jery NT 600 1400 91686 NT/LC 50966 NT/LC 29206 NT/LC 26041 100 Neomixis striatigula Stripe-throated Jery LC 0 100 333371 NT/LC 59765 NT/LC 7475 VU 2729 100 Neomixis tenella Common Jery LC 0 100 589927 NT/LC 114165 NT/LC 8137 VU 3685 100 Neomixis viridis Green Jery LC 0 100 174250 NT/LC 34213 NT/LC 7347 VU 2347 100 Nesillas lantzii Lantz's Brush-warbler LC 0 500 70101 NT/LC 65802 NT/LC 92 CR 36 100 Newtonia amphichroa Dark Newtonia LC 0 100 243052 NT/LC 33868 NT/LC 7323 VU 2344 100 Newtonia archboldi Archbold's Newtonia LC 0 100 78262 NT/LC 15560 VU 12 CR 4 100 Newtonia brunneicauda Common Newtonia LC 0 100 554094 NT/LC 114445 NT/LC 8204 VU 3705 100 Newtonia fanovanae Red-tailed Newtonia VU 100 900 84637 NT/LC 50230 NT/LC 22519 NT/LC 16421 100 Oriolia bernieri Bernier's Vanga VU 0 900 20305 NT/LC 16818 VU 13209 VU 12359 100

148 Oxylabes madagascariensis White-throated Oxylabes LC 0 100 173812 NT/LC 33498 NT/LC 7199 VU 2292 100 Philepitta castanea Velvet Asity LC 600 1400 196754 NT/LC 89625 NT/LC 34684 NT/LC 29356 100 Philepitta schlegeli Schlegel's Asity NT 0 800 81186 NT/LC 79738 NT/LC 3394 EN 3215 100 Ploceus nelicourvi Nelicourvi Weaver LC 0 100 186973 NT/LC 33645 NT/LC 7256 VU 2286 100 Pseudobias wardi Ward's Flycatcher LC 0 1500 179692 NT/LC 172785 NT/LC 64113 NT/LC 45862 100 Randia pseudozosterops Rand's Warbler LC 0 1200 150587 NT/LC 133432 NT/LC 56123 NT/LC 39886 100 Saroglossa aurata Madagascar Starling LC 0 100 412232 NT/LC 103064 NT/LC 8193 VU 3699 100 Schetba rufa Rufous Vanga LC 0 100 410613 NT/LC 102897 NT/LC 8201 VU 3705 100 Tylas eduardi Tylas Vanga LC 0 1800 233291 NT/LC 231111 NT/LC 68676 NT/LC 48967 100 Tyto soumagnei Madagascar Red Owl VU 0 2000 61011 NT/LC 60576 NT/LC 41732 NT/LC 38298 100 Upupa marginata Madagascar Hoopoe LC 0 1500 533267 NT/LC 523296 NT/LC 40872 NT/LC 26278 100 Vanga curvirostris Hook-billed Vanga LC 0 100 502127 NT/LC 113985 NT/LC 8091 VU 3633 100 Xenopirostris damii Van Dam's Vanga EN 0 150 14214 VU 12074 VU 81 CR 288 100 Xenopirostris polleni Pollen's Vanga NT 400 2000 61695 NT/LC 50836 NT/LC 27740 NT/LC 23500 100

Appendix 10

Bird species used in maps of conservation priorities for Southeast Asia, including range size and threat category reassessment

during the range refining process.

BirdLife % Species Common name IUCN min max TC Ref_elev TC For_30m TC1 For_250m Range region2 Aceros nipalensis Rufous-necked Hornbill VU 150 2200 262808 NT/LC 235286 VU 184187 VU 171843 92 Aegithina lafresnayei Great Iora LC 0 100 1680724 NT/LC 547127 NT/LC 112945 NT/LC 168163 100 Alcippe castaneceps Rufous-winged Fulvetta LC 300 3600 1098657 NT/LC 924213 NT/LC 604033 NT/LC 584787 93 Alcippe cinerea Yellow-throated Fulvetta LC 600 2745 199192 NT/LC 155265 NT/LC 119758 NT/LC 80909 89 Alcippe grotei Black-browed Fulvetta LC 0 1200 232381 NT/LC 227551 NT/LC 126234 NT/LC 974 100 Alcippe klossi Black-crowned Fulvetta LC 50 2100 9481 VU 9438 VU 6317 VU 136434 100 Alcippe manipurensis Streak-throated Fuletta LC 1400 2800 122420 NT/LC 64139 NT/LC 38729 NT/LC 14392 100

149 Alcippe peracensis Mountain Fulvetta LC 760 2190 149004 NT/LC 44941 NT/LC 36725 NT/LC 915 100 Alcippe rufogularis Rufous-throated Fulvetta LC 0 1100 442459 NT/LC 386554 NT/LC 261766 NT/LC 34682 99 Alophoixus flaveolus White-throated Bulbul LC 0 100 535654 NT/LC 15712 VU 5827 VU 288554 95 Ampeliceps coronatus Golden-crested Myna LC 0 100 1381868 NT/LC 336724 NT/LC 50671 NT/LC 200164 100 Anorrhinus austeni Austen's Brown Hornbill NT 0 1800 778324 NT/LC 758911 NT/LC 464013 NT/LC 14288 100 Anorrhinus tickelli Tickell's Brown Hornbill NT 0 1500 160243 NT/LC 159666 NT/LC 89239 NT/LC 147928 99 Arborophila brunneopectus Bar-backed Partridge LC 0 1800 488823 NT/LC 481946 NT/LC 310440 NT/LC 32609 100 Arborophila cambodiana Chestnut-headed Partridge LC 200 1400 18036 VU 8668 VU 7430 VU 948 100 Arborophila campbelli Malay Partridge LC 50 2200 17196 VU 17181 VU 16460 VU 6062 100 Arborophila charltonii Chestnut-necklaced Partridge VU 0 500 90122 NT/LC 84170 VU 61517 VU 96680 80 Arborophila chloropus Green-legged Partridge LC 0 1400 710704 NT/LC 702641 NT/LC 375679 NT/LC 64 100 Arborophila davidi Orange-necked Partridge NT 140 400 4493 EN 1605 EN 1359 EN 101 100 Arborophila tonkinensis Tonkin Partridge LC 0 1400 22077 NT/LC 22043 NT/LC 12699 VU 39583 100 Certhia manipurensis Manipur Treecreeper LC 1300 3000 121891 NT/LC 71081 NT/LC 45946 NT/LC 32015 100 Cinclidium frontale Blue-fronted Robin LC 1850 2200 187034 NT/LC 2749 EN 2367 EN 55505 82 Cochoa purpurea Purple Cochoa LC 1000 3000 519699 NT/LC 370336 NT/LC 133898 NT/LC 418938 83 Cochoa viridis Green Cochoa LC 700 1800 1255145 NT/LC 551468 NT/LC 351998 NT/LC 8358 93 Coracina polioptera Indochinese Cuckooshrike LC 0 100 934531 NT/LC 313432 NT/LC 50580 NT/LC 19445 100 Crocias langbianis Grey-crowned Crocias EN 900 1700 348 EN 313 EN 182 EN 29423 100

Crypsirina temia Racket-tailed Treepie LC 0 100 1155754 NT/LC 334907 NT/LC 47317 NT/LC 75896 100 Cutia legalleni Vietnamese Cutia NT 0 100 28576 NT/LC 1479 EN 561 EN 183013 100 Dendrocitta frontalis Collared Treepie LC 0 100 187275 NT/LC 3233 EN 327 EN 512 93 Dendrocopos analis Freckle-breasted Woodpecker LC 0 2800 923410 NT/LC 912955 NT/LC 328426 NT/LC 1447 82 Dendrocopos atratus Stripe-breasted Woodpecker LC 800 2200 309565 NT/LC 236274 NT/LC 154415 NT/LC 50852 99 Dicrurus annectans Crow-billed Drongo LC 0 100 1926189 NT/LC 533987 NT/LC 102653 NT/LC 136392 73 Dinopium shorii Himalayan Flameback LC 0 1220 331610 NT/LC 327064 NT/LC 131866 NT/LC 4539 86 Gampsorhynchus rufulus Whit-hooded Babbler LC 0 1400 423154 NT/LC 356226 NT/LC 240180 NT/LC 7420 93 Gampsorhynchus torquatus Collared Babbler LC 500 1800 478797 NT/LC 337431 NT/LC 243037 NT/LC 211354 100 Garrulax annamensis Orange-breasted Laughingthrush LC 915 1510 8090 VU 5442 VU 3577 EN 2419 100 Garrulax austeni Brown-capped Laughingthrush LC 1800 3000 41605 NT/LC 8714 VU 7185 VU 13971 100 Garrulax bieti White-speckled Laughingthrush VU 2500 4270 20433 NT/LC 16283 VU 7669 VU 0 87 Garrulax castanotis Rufous-cheeked Laughingthrush LC 1800 3000 98991 NT/LC 736 EN 684 EN 332646 88 Garrulax chrysopterus Assam Laughingthrush LC 1280 3000 134953 NT/LC 45718 NT/LC 33270 NT/LC 42616 88 Garrulax ferrarius Cambodian Laughingthrush NT 800 1250 1259 EN 1013 EN 992 EN 275946 100 Garrulax gularis Rufous-vented Laughingthrush LC 0 100 357105 NT/LC 15002 VU 3103 EN 62713 95 Garrulax konkakinhensis Chestnut-eared Laughingthrush VU 1200 1750 652 EN 325 EN 321 EN 5755 100 Garrulax leucolophus White-crested Laughingthrush LC 0 2135 1582411 NT/LC 1549737 NT/LC 866443 NT/LC 149485 92

150 Garrulax melanostigma Silver-eared Laughingthrush LC 610 2565 479887 NT/LC 350155 NT/LC 222686 NT/LC 179984 100 Garrulax merulinus Spot-breastd Laughingthrush LC 800 2000 500923 NT/LC 343469 NT/LC 169401 NT/LC 26986 100 Garrulax milleti Black-hooded Laughingthrush NT 800 1650 24332 NT/LC 17418 VU 14194 VU 182 100 Garrulax ngoclinhensis Golden-winged Laughingthrush VU 1500 2200 155 EN 71 CR 68 CR 662 100 Garrulax peninsulae Malayan Laughingthrush LC 1065 1830 14937 VU 4087 EN 3982 EN 43509 100 Garrulax squamatus Blue-winged Laughingthruh LC 0 500 601270 NT/LC 54417 NT/LC 36103 NT/LC 179709 87 Garrulax strepitans White-necked laughingthrush LC 500 1800 248531 NT/LC 169758 NT/LC 117793 NT/LC 226955 100 Garrulax yersini Collared Laughingthrush EN 150 2440 724 EN 724 EN 643 EN 82687 100 Gecinulus grantia Pale-headed Woodpecker LC 0 1200 690029 NT/LC 627929 NT/LC 335100 NT/LC 150 92 Gecinulus viridis Bamboo Woodpecker LC 600 1400 188290 NT/LC 66453 NT/LC 53900 NT/LC 31714 100 Gypsophila crispifrons Limestone Wren-babbler LC 0 2135 206541 NT/LC 206226 NT/LC 132539 NT/LC 45730 100 Harpactes oreskios Orange-breasted Trogon LC 300 1500 1411968 NT/LC 671745 NT/LC 419828 NT/LC 44 86 Hemicircus canente Heart-spotted Woodpecker LC 0 1300 538436 NT/LC 532397 NT/LC 314886 NT/LC 115873 80 Hemixos flavala Ashy Bulbul LC 0 100 1019649 NT/LC 84229 NT/LC 39627 NT/LC 6456 77 Heterophasia annectens Rufous-backed Sibia LC 0 100 641718 NT/LC 8408 VU 2309 EN 145065 92 Heterophasia gracilis Grey Sibia LC 900 2800 207295 NT/LC 148506 NT/LC 109228 NT/LC 39590 86 Heterophasia melanoleuca Dark-backed Sibia LC 1000 2565 178674 NT/LC 67112 NT/LC 37566 NT/LC 282 100 Heterophasia picaoides Long-tailed Sibia LC 0 100 1231929 NT/LC 65796 NT/LC 28650 NT/LC 97601 81 Heterophasia pulchella Beautiful Sibia LC 1650 3200 168016 NT/LC 93699 NT/LC 57869 NT/LC 1133 93

Hypsipetes thompsoni White-headed Bulbul LC 0 100 197453 NT/LC 1647 EN 1008 EN 1080 100 Iole propinqua Grey-eyed Bulbul LC 0 100 1172762 NT/LC 171007 NT/LC 41896 NT/LC 175019 94 Iole virescens Olive Bulbul LC 0 100 237931 NT/LC 43535 NT/LC 9835 VU 2716 86 Jabouilleia danjoui Short-tailed Scimitar-babbler NT 50 2100 126741 NT/LC 97683 NT/LC 68236 NT/LC 54855 100 Liocichla phoenicea Red-faced Liocichla phoenicea LC 0 100 731756 NT/LC 14677 VU 2013 EN 38175 90 Lophura diardi Siamese Fireback LC 0 1150 513312 NT/LC 492811 NT/LC 259577 NT/LC 510739 100 Lophura edwardsi Edwards's Pheasant CR 0 300 8278 CR 6327 CR 3461 CR 534 100 Macronous kelleyi Grey-faced Tit-babbler LC 50 1165 178234 NT/LC 159529 NT/LC 107919 NT/LC 319 100 Meiglyptes jugularis Black-and-buff Woodpecker LC 0 900 582719 NT/LC 513622 NT/LC 273690 NT/LC 11519 100 Melanochlora sultanea Sultan Tit LC 0 100 1509386 NT/LC 228102 NT/LC 81245 NT/LC 742 91 Myophonus robinsoni Malaysian Whistling-thrush NT 750 1750 10888 VU 6855 VU 6677 VU 6221 100 Napothera brevicaudata Streaked Wren-babbler LC 0 100 1140316 NT/LC 110556 NT/LC 31120 NT/LC 13629 95 Niltava grandis Large Niltava LC 0 450 1398287 NT/LC 491561 NT/LC 210747 NT/LC 84906 86 Oriolus tenuirostris Slender-billed Oriole LC 0 100 1056903 NT/LC 78288 NT/LC 10367 VU 5083 93 Oriolus traillii Maroon Oriole LC 0 100 2148639 NT/LC 347040 NT/LC 37917 NT/LC 106085 88 Otus sagittatus White-ronted Scops-owl VU 0 700 148500 NT/LC 133733 VU 92655 VU 699 99 Paradoxornis atrosuperciliaris Pale-billed Parrotbill LC 215 2100 196782 NT/LC 178244 NT/LC 135730 NT/LC 1252 96 Paradoxornis margaritae Black-headed Parrotbill NT 850 1500 2954 EN 1863 EN 1568 EN 65901 100

151 Phylloscopus cantator Yellow-vented Warbler LC 300 2000 675718 NT/LC 495586 NT/LC 309749 NT/LC 410 85 Picus erythropygius Black-headed Woodpecker LC 0 1000 467058 NT/LC 444470 NT/LC 151084 NT/LC 3130 100 Picus rabieri Red-collared Woodpecker NT 0 700 229993 NT/LC 191071 NT/LC 105214 NT/LC 41933 93 Picus viridanus Streak-breasted Woodpecker LC 0 100 385229 NT/LC 173115 NT/LC 46578 NT/LC 109730 98 Picus vittatus Laced Woodpecker LC 0 1500 1136537 NT/LC 1112092 NT/LC 511349 NT/LC 1776 84 Pitta cyanea Blue Pitta LC 60 2000 1015104 NT/LC 981660 NT/LC 572664 NT/LC 137947 99 Pitta elliotii Bar-bellied Pitta LC 0 800 607570 NT/LC 521207 NT/LC 207401 NT/LC 20362 100 Pitta gurneyi Gurney's Pitta EN 0 150 2437 EN 1985 EN 1601 EN 10000 100 Pitta moluccensis Blue-winged Pitta LC 0 1800 1331295 NT/LC 1318339 NT/LC 598042 NT/LC 219574 51 Pitta nipalensis Blue-naped Pitta LC 0 1500 558973 NT/LC 469902 NT/LC 272707 NT/LC 385369 83 Pitta oatesi Rusty-naped Pitta LC 380 2600 546501 NT/LC 472955 NT/LC 321786 NT/LC 2457 99 Pitta phayrei Eared Pitta LC 0 1830 929340 NT/LC 924473 NT/LC 465532 NT/LC 51945 100 Polihierax insignis White-rumped Pygmy-falcon NT 0 700 534442 NT/LC 506689 NT/LC 146763 NT/LC 606 100 Polyplectron bicalcaratum Grey Peacock-pheasant LC 0 1800 1059686 NT/LC 1044723 NT/LC 676962 NT/LC 108512 96 Polyplectron germaini Germain's Peacock-pheasant NT 0 1400 38491 NT/LC 36572 NT/LC 15945 VU 76973 99 Polyplectron inopinatum Mountain Peacock-pheasant VU 820 1800 12772 VU 6542 VU 6378 VU 67914 100 Polyplectron malacense Malay Peacock-pheasant VU 0 300 116930 NT/LC 100869 VU 63337 VU 1679 99 Pomatorhinus ferruginosus Coral-billed Scimitar-babbler LC 0 100 569445 NT/LC 11397 VU 2994 EN 421643 88 Pomatorhinus hypoleucos Large Scimitar-babbler LC 0 100 748607 NT/LC 65645 NT/LC 17341 VU 350934 94

Pomatorhinus mcclellandi Spot-breasted Scimitar-babbler LC 750 1830 265857 NT/LC 103219 NT/LC 76238 NT/LC 55667 93 Pomatorhinus ochraceiceps Red-billed Scimitar-babbler LC 0 100 658797 NT/LC 21475 NT/LC 5923 VU 5588 99 Pomatorhinus schisticeps White-browed Scimitar-babbler LC 0 100 1087646 NT/LC 47367 NT/LC 21807 NT/LC 534 88 Prinia rufescens Rufescent Prinia LC 0 1800 2191041 NT/LC 2137813 NT/LC 1009944 NT/LC 11462 98 Psilopogon annamensis Annam Barbet LC 900 2000 239636 NT/LC 64476 NT/LC 51172 NT/LC 260399 100 Psilopogon auricularis Necklaced Barbet LC 900 2700 43094 NT/LC 19441 VU 15920 VU 14177 100 Psilopogon chersonesus Turquoise-throated Barbet LC 885 1520 852 EN 173 EN 172 EN 393345 100 Psilopogon cyanotis Blue-eared Barbet LC 0 1600 1456743 NT/LC 1414030 NT/LC 774794 NT/LC 58489 97 Psilopogon faiostrictus Green-eared Barbet LC 0 900 695062 NT/LC 628887 NT/LC 254158 NT/LC 8485 97 Psilopogon franklinii Golden-throated Barbet LC 900 2700 704158 NT/LC 443602 NT/LC 250110 NT/LC 63062 94 Psilopogon incognitus Moustached Barbet LC 400 1400 712182 NT/LC 302312 NT/LC 216675 NT/LC 92950 100 Psilopogon lagrandieri Red-vented Barbet LC 0 2100 353867 NT/LC 343688 NT/LC 161574 NT/LC 312 100 Psittacula roseata Blossom-headed Parakeet NT 0 1000 1589139 NT/LC 1352737 NT/LC 552345 NT/LC 40742 93 Pteruthius aenobarbus Chestnut-fronted Shrike-babbler LC 0 100 924946 NT/LC 31560 NT/LC 7799 VU 129 92 Pteruthius melanotis Black-eared Shrike-babbler LC 0 100 743501 NT/LC 1399 EN 351 EN 843 88 Pycnonotus flavescens Flavescent Bulbul LC 0 100 813554 NT/LC 7302 VU 2815 EN 1064 87 Pycnonotus hualon Bare-faced Bulbul LC 0 100 25358 NT/LC 0 CR 0 CR 156646 100 Pycnonotus striatus Striated Bulbul LC 300 3000 1034997 NT/LC 981924 NT/LC 553935 NT/LC 319094 95

152 Rheinardia ocellata Crested Argus NT 0 1900 55166 NT/LC 54916 NT/LC 46215 NT/LC 152703 100 Rhyticeros subruficollis Plain-pouched Hornbill VU 0 1000 72332 NT/LC 66786 VU 51140 VU 16030 99 Rimator malacoptilus Long-billed Wren-babbler LC 900 2700 161650 NT/LC 104541 NT/LC 85740 NT/LC 2622 84 Rimator pasquieri White-throated Wren-babbler EN 1220 2000 1841 EN 952 EN 646 EN 145799 100 Sasia ochracea White-browed Piculet LC 250 2600 1413167 NT/LC 1044281 NT/LC 672518 NT/LC 8278 93 Seicercus poliogenys Grey-cheeked Warbler LC 0 100 947361 NT/LC 21329 NT/LC 2574 EN 325598 90 Serilophus lunatus Silver-breasted Broadbill LC 250 2000 1123630 NT/LC 909349 NT/LC 544958 NT/LC 109216 92 Sitta formosa Beautiful Nuthatch VU 600 2400 357315 NT/LC 305156 VU 161002 VU 120214 95 Sitta magna Giant Nuthatch EN 1000 2500 414971 NT/LC 285209 EN 101865 EN 206197 96 Sitta solangiae Yellow-billed Nuthatch NT 700 2500 20587 NT/LC 18088 VU 14900 VU 2505 86 Sitta victoriae White-browed Nuthatch EN 2300 3000 817 EN EN 0 CR 49007 100 Spelaeornis chocolatinus Long-tailed Wren-babbler NT 1200 3100 11147 VU 2058 EN 1428 EN 93953 100 Spelaeornis formosus Spotted Wren-babbler LC 300 2400 535068 NT/LC 457998 NT/LC 262243 NT/LC 188889 80 Spelaeornis kinneari Pale-throated Wren-babbler VU 1400 2500 7247 VU 4318 EN 3201 EN 0 91 Spelaeornis longicaudatus Tawny-breasted Wren-babbler VU 1000 2000 15043 VU 6198 VU 3610 EN 21995 100 Spelaeornis oatesi Chin Hills Wren-babbler LC 1300 2800 29833 NT/LC 12655 VU 9009 VU 106827 100 Spelaeornis reptatus Grey-bellied Wren-babbler LC 1200 3000 213964 NT/LC 90546 NT/LC 52357 NT/LC 68141 95 Sphenocichla roberti Chevron-breasted Babbler NT 300 2010 184017 NT/LC 155603 NT/LC 100248 NT/LC 126554 100 Stachyris ambigua Buff-chested Babbler LC 0 100 781508 NT/LC 567 EN 103 EN 275632 92

Stachyris chrysaea Golden Babbler LC 0 100 909957 NT/LC 4096 EN 1270 EN 32121 89 Stachyris herberti Sooty Babbler LC 230 610 19244 VU 9822 VU 8065 VU 6351 100 Stachyris oglei Snowy-throated Babbler VU 450 1800 16533 VU 9373 VU 8933 VU 3955 100 Stachyris striolata Spot-necked Babbler LC 0 100 478264 NT/LC 21549 NT/LC 8581 VU 148850 80 Syrmaticus humiae Mrs Hume's Pheasant NT 700 2800 375847 NT/LC 334163 NT/LC 135704 NT/LC 452783 92 Temnurus temnurus Ratchet-tailed Treepie LC 0 100 226508 NT/LC 52807 NT/LC 4871 EN 8893 84 Tragopan blythii Blyth's Tragopan VU 1400 3300 112346 NT/LC 55643 VU 44909 VU 13453 93 Treron apicauda Pin-tailed Green-pigeon LC 0 1800 1431026 NT/LC 1192084 NT/LC 683198 NT/LC 12594 87 Treron phayrei Ashy-headed Green-pigeon NT 0 1500 1627423 NT/LC 1545076 NT/LC 761889 NT/LC 191206 94 Treron seimundi Yellow-vented Green-pigeon LC 0 100 220457 NT/LC 30721 NT/LC 4325 EN 92497 100 Trichastoma tickelli Buff-breasted babbler LC 0 1550 834216 NT/LC 763382 NT/LC 465041 NT/LC 2276 97 Turdinus macrodactylus Large Wren-babbler NT 0 1200 103365 NT/LC 102086 NT/LC 75040 NT/LC 282526 82 Turdus dissimilis Black-breasted Thrush LC 1200 2500 702957 NT/LC 345387 NT/LC 156254 NT/LC 6596 85 Urocissa whiteheadi White-winged Magpie LC 50 1400 314077 NT/LC 261853 NT/LC 165003 NT/LC 63115 84 Xiphirhynchus superciliaris Slender-billed Scimitar-babbler LC 600 3500 557551 NT/LC 381059 NT/LC 254068 NT/LC 40660 84 Yuhina bakeri White-naped Yuhina LC 300 2200 360056 NT/LC 296849 NT/LC 212498 NT/LC 1513 92 Yuhina castaniceps Striated Yuhina LC 180 1800 300530 NT/LC 247629 NT/LC 170752 NT/LC 396593 93 Yuhina humilis Burmese Yuhina LC 1075 2275 58096 NT/LC 31882 NT/LC 15911 VU 2219 100

153 Yuhina torqueola Indochinese Yuhina LC 350 2200 331159 NT/LC 262335 NT/LC 204221 NT/LC 268538 94 Zoothera marginata Dark-sided Thrush LC 750 2570 893928 NT/LC 522146 NT/LC 333225 NT/LC 1306 95

Appendix 11

Bird species used in maps of conservation priorities for Sumatra, including range size and threat category reassessment during

the range refining process.

BirdLife % Species Common name IUCN min max TC Ref_elev TC For_30m TC1 For_250m Range region2 Actenoides concretus Rufous-collared Kingfisher NT 0 1700 415258 NT/LC 393684 NT/LC 311711 NT/LC 230838 75 Aegithina viridissima Green Iora NT 0 100 447200 NT/LC 275722 NT/LC 185388 NT/LC 95497 72 Alcippe brunneicauda Brown Fulvetta NT 0 1000 152471 NT/LC 142551 NT/LC 135973 NT/LC 89782 35 Alophoixus finschii Finsch's Bulbul NT 0 100 306447 NT/LC 164780 NT/LC 109937 NT/LC 65215 73 Anthracoceros malayanus Black Hornbill NT 0 200 324509 NT/LC 239926 NT/LC 161181 NT/LC 98974 79 Anthreptes rhodolaemus Red-throated Sunbird NT 0 800 234215 NT/LC 210720 NT/LC 175434 NT/LC 105212 47 Arborophila charltonii Chestnut-necklaced Partridge VU 0 500 76784 NT/LC 66770 NT/LC 59998 NT/LC 37463 28

154 Arborophila rubrirostris Red-billed Partridge LC 900 2500 69941 NT/LC 46067 NT/LC 40569 NT/LC 36013 100 Argusianus argus Great Argus NT 0 1500 549508 NT/LC 516914 NT/LC 377275 NT/LC 268798 79 Batrachostomus auritus Large Frogmouth NT 0 100 205511 NT/LC 153517 NT/LC 91625 NT/LC 61150 91 Batrachostomus stellatus Gould's Frogmouth NT 0 500 254421 NT/LC 238760 NT/LC 176594 NT/LC 111549 68 Batrachostomus poliolophus Short-tailed Frogmouth NT 660 1400 94039 NT/LC 47377 NT/LC 40419 NT/LC 36216 100 Berenicornis comatus White-crowned Hornbill NT 0 900 456243 NT/LC 407341 NT/LC 303787 NT/LC 204960 72 Buceros bicornis Great Hornbill NT 0 2000 496377 NT/LC 477294 NT/LC 335740 NT/LC 250827 88 Buceros rhinoceros Rhinoceros Hornbill NT 0 1400 567676 NT/LC 529085 NT/LC 390766 NT/LC 270380 77 Caloperdix oculeus Ferruginous Partridge NT 0 1200 248982 NT/LC 212806 NT/LC 145963 NT/LC 122316 96 Caloramphus hayii Malay Brown Barbet NT 0 750 231566 NT/LC 208944 NT/LC 178894 NT/LC 108732 45 Calyptomena viridis Green Broadbill NT 0 1700 579174 NT/LC 552482 NT/LC 412286 NT/LC 288017 77 Carpimulgus pulchellus Salvadori's Nightjar NT 800 2100 15291 VU 12243 VU 11690 VU 10982 100 Carpococcyx viridis Sumatran Ground-cuckoo CR 300 1400 25351 NT/LC 18296 VU 16895 VU 14782 100 Chloropsis cyanopogon Lesser Green Leafbird NT 0 100 520949 NT/LC 332530 NT/LC 218039 NT/LC 119213 77 Chloropsis venusta Blue-masked Leafbird NT 600 1500 120779 NT/LC 66021 NT/LC 56658 NT/LC 49691 100 Cinclidium diana Sunda Robin LC 0 100 85682 NT/LC 264 EN 139 EN 55 100 Cochoa beccarii Sumatran Cochoa VU 1000 2200 64780 NT/LC 39942 NT/LC 35771 NT/LC 32251 100 Cyornis caerulatus Large-billed Blue-Flycatcher VU 0 500 358208 NT/LC 320510 NT/LC 195961 NT/LC 143209 100 Dicrurus sumatranus Sumatran Drongo LC 0 800 395377 NT/LC 358641 NT/LC 230468 NT/LC 172846 100

Dinopium rafflesii Olive-backed Woodpecker NT 0 1200 376876 NT/LC 362206 NT/LC 260310 NT/LC 159053 67 Eupetes macrocerus Rail-babbler NT 0 1060 431719 NT/LC 412123 NT/LC 309084 NT/LC 206874 71 Eurylaimus ochromalus Black-and-Yellow Broadbill NT 0 1220 397460 NT/LC 381127 NT/LC 283890 NT/LC 193831 73 Garrulax lugubris Black laughingthrush LC 0 100 41063 NT/LC 1211 EN 1196 EN 248 60 Garrulax palliatus Sunda Laughingthrush LC 0 100 49266 NT/LC 1927 EN 1003 EN 900 100 Hypsipetes virescens Green-winged Bulbul LC 0 100 63606 NT/LC 5 CR 4 CR 3 100 Indicator archipelagicus Malay Honeyguide NT 0 700 429542 NT/LC 390434 NT/LC 288754 NT/LC 189097 71 Iole olivacea Buff-vented Bulbul NT 0 825 449012 NT/LC 418031 NT/LC 309880 NT/LC 202630 72 Ixos malaccensis Streaked Bulbul NT 0 100 347017 NT/LC 195452 NT/LC 133451 NT/LC 73689 71 Kenopia striata Striped Wren-babbler NT 0 1000 69557 NT/LC 63474 NT/LC 47879 NT/LC 36106 65 Lophura erythrophthalma Malay Crestless Fireback VU 0 300 482234 NT/LC 403566 NT/LC 277923 NT/LC 169018 77 Lophura ignita Bornean Crested Fireback NT 0 1000 7281 VU 7045 VU 4401 EN 1864 100 Lophura rufa Malay Crested Fireback NT 0 1000 341896 NT/LC 322284 NT/LC 248014 NT/LC 176040 71 Macronous ptilosus Fluffy-backed Tit-babbler NT 0 700 233856 NT/LC 216257 NT/LC 148948 NT/LC 90129 80 Malacocincla malaccensis Short-tailed Babbler NT 0 1000 401305 NT/LC 377094 NT/LC 282261 NT/LC 197795 74 Malacopteron affine Sooty-capped Babbler NT 0 700 182703 NT/LC 170880 NT/LC 119198 NT/LC 69007 74 Malacopteron albogulare Grey-breasted Babbler NT 0 915 187326 NT/LC 171866 NT/LC 120455 NT/LC 88056 89 Malacopteron magnum Rufous-crowned Babbler NT 0 800 172706 NT/LC 153423 NT/LC 115436 NT/LC 86816 82

155 Meiglyptes tukki Buff-necked Woodpecker NT 0 600 311781 NT/LC 283941 NT/LC 212529 NT/LC 143399 71 Melanoperdix niger Black Partridge 0 1200 493857 NT/LC 477969 NT/LC 340985 NT/LC 223389 77 Mulleripicus pulverulentus Great Slaty Woodpecker VU 0 1830 148951 NT/LC 144331 NT/LC 138590 NT/LC 73064 12 Myophonus melanurus Shiny Whistling-thrush LC 0 1100 67360 NT/LC 29582 NT/LC 23818 NT/LC 20002 100 Niltava sumatrana Rufous-vented Niltava LC 1000 100 42743 NT/LC 35898 NT/LC 32320 NT/LC 28849 96 Oriolus xanthonotus Dark-throated Oriole NT 0 2000 436572 NT/LC 422947 NT/LC 321306 NT/LC 215020 72 Otus brookii Rajah Scops-owl LC 1200 100 29928 NT/LC 23784 NT/LC 21563 NT/LC 19675 100 Pericrocotus igneus Firey Minivet NT 0 100 532202 NT/LC 340384 NT/LC 224967 NT/LC 123628 77 Pericrocotus miniatus Sunda Minivet LC 0 100 112547 NT/LC 2442 EN 1413 EN 662 100 Philentoma velata Maroon-breasted Philentoma NT 0 100 433034 NT/LC 262782 NT/LC 177328 NT/LC 92176 71 Pitta caerulea Giant Pitta NT 0 1200 553762 NT/LC 502078 NT/LC 370786 NT/LC 256947 77 Pitta granatina Garnet Pitta NT 0 1200 327385 NT/LC 316605 NT/LC 226567 NT/LC 134227 68 Pitta irena Malayan Banded Pitta NT 0 500 516999 NT/LC 435592 NT/LC 307442 NT/LC 198898 76 Pitta schneideri Schneider's Pitta VU 900 1200 66281 NT/LC 18681 VU 15956 VU 14176 100 Pitta venusta Graceful Pitta VU 400 300 71646 NT/LC 49126 NT/LC 42066 NT/LC 36886 100 Platylophus galericulatus Crested Jay NT 0 1200 595793 NT/LC 542662 NT/LC 399173 NT/LC 273562 78 Platysmurus leucopterus Black Magpie NT 0 1500 506406 NT/LC 489988 NT/LC 354543 NT/LC 235141 76 Polyplectron chalcurum Bronze-tailed Peacock-pheasant LC 800 900 83765 NT/LC 6308 VU 5422 VU 4522 100 Psilopogon henricii Yellow-crowned Barbet NT 200 1387 299252 NT/LC 65949 NT/LC 62429 NT/LC 58755 71

Psilopogon mystacophanos Red-throated Barbet NT 0 750 491668 NT/LC 450145 NT/LC 322490 NT/LC 214985 74 Psilopogon pyrolophus Fire-tufted Barbet LC 400 1060 472681 NT/LC 81563 NT/LC 72870 NT/LC 64658 78 Psilopogon rafflesii Red-crowned Barbet NT 0 2020 253136 NT/LC 245078 NT/LC 183184 NT/LC 118360 65 Psittacula alexandri Red-breasted Parakeet NT 0 3100 5954 VU 5758 VU 5013 VU 3401 100 Psittacula longicauda Long-tailed parakeet NT 0 100 369521 NT/LC 286611 NT/LC 188639 NT/LC 106124 80 Pycnonotus bimaculatus Orange-spotted Bulbul LC 0 900 75534 NT/LC 23410 NT/LC 19849 VU 16902 100 Pycnonotus cyaniventris Grey-bellied Bulbul NT 0 100 350538 NT/LC 191397 NT/LC 130750 NT/LC 72825 71 Pycnonotus eutilotus Puff-backed Bulbul NT 0 100 355942 NT/LC 195234 NT/LC 133260 NT/LC 74749 72 Pycnonotus leucogrammicus Cream-striped Bulbul LC 0 100 63469 NT/LC 2 CR 2 CR 2 100 Pycnonotus melanoleucos Black-and-white Bulbul NT 493782 NT/LC 464734 NT/LC 353931 NT/LC 244782 74 Pycnonotus squamatus Scaly-breasted Bulbul NT 0 100 109629 NT/LC 1985 EN 1533 EN 507 85 Pycnonotus tympanistrigus Spot-necked Bulbul NT 300 100 97803 NT/LC 69092 NT/LC 60953 NT/LC 54918 100 Ramphiculus jambu Jambu Fruit-dove NT 0 1500 587716 NT/LC 553856 NT/LC 408783 NT/LC 281621 78 Rhabdotorrhinus corrugatus Wrinkled Hornbill NT 0 30 398934 NT/LC 163257 NT/LC 100191 NT/LC 46397 78 Rhinomyias umbratilis Grey-chested Jungle-Flycatcher NT 0 1160 464626 NT/LC 435949 NT/LC 328696 NT/LC 223110 73 Rhinoplax vigil Helmeted Hornbill NT 0 1500 494919 NT/LC 464292 NT/LC 356658 NT/LC 249383 74 Rhizothera longirostris Long-billed Partridge VU 0 1500 582904 NT/LC 549199 NT/LC 404680 NT/LC 279260 77 Rollulus rouloul Crested Partridge NT 0 1200 582906 NT/LC 530208 NT/LC 387859 NT/LC 264772 77

156 Seicercus grammiceps Sunda Warbler LC 1400 2200 23131 NT/LC 12437 VU 11540 VU 10792 100 Serinus estherae Mountain Serin LC 1900 3500 16099 VU 3295 EN 3361 EN 3312 100 Setornis criniger Hook-billed Bulbul VU 0 1000 170148 NT/LC 164675 NT/LC 100412 NT/LC 66512 100 Stachyris leucotis White-necked Babbler NT 0 100 188482 NT/LC 87621 NT/LC 80913 NT/LC 28960 30 Stachyris maculata Chestnut-rumped Babbler NT 0 800 203489 NT/LC 194331 NT/LC 138949 NT/LC 90125 70 Stachyris nigricollis Black-throated Babbler NT 0 100 108202 NT/LC 55406 NT/LC 46956 NT/LC 19379 37 Terpsiphone atrocaudata Japanese Paradise-flycatcher NT 1 1000 560745 NT/LC 490590 NT/LC 358822 NT/LC 243671 77 Treron oxyurus Sumatran Green-pigeon NT 350 3000 90159 NT/LC 81568 NT/LC 71642 NT/LC 65121 100 Trichastoma rostratum White-chested Babbler NT 0 500 149674 NT/LC 143841 NT/LC 105901 NT/LC 62887 70 Trichixos pyrropygus Rufous-tailed Shama NT 0 900 425627 NT/LC 400228 NT/LC 298621 NT/LC 197403 71 Turdinus macrodactylus Large Wren-Babbler NT 0 1200 96808 NT/LC 92073 NT/LC 85050 NT/LC 56936 24 Turdinus marmorata Marbled Wren-babbler LC 610 2000 87621 NT/LC 64947 NT/LC 57191 NT/LC 49672 78 Turdinus rufipectus Rusty-breasted Wren-babbler LC 900 2500 74094 NT/LC 46680 NT/LC 41045 NT/LC 36500 100 Zoothera interpres Chestnut-capped Thrush NT 200 1000 57973 NT/LC 16856 VU 17357 VU 15416 2 Zosterops atricapilla Black-capped White-eye LC 1500 3000 70540 NT/LC 14548 VU 14235 VU 13464 100

Appendix 12

Bird species used in maps of conservation priorities for the Western Andes in Colombia, including range size and threat category

reassessment during the range refining process.

BirdLife % Species Common name IUCN min max TC Ref_elev TC For_30m TC1 For_250m Range region2

Aglaiocercus coelestis Violet-tailed Sylph LC 900 2100 24505 NT/LC 11382 VU 8204 VU 1795 57 Amazilia grayi Gray's Hummingbird LC 500 2000 23846 NT/LC 17050 VU 3920 EN 1531 55 Amazilia rosenbergi Purple-chested Hummingbird LC 0 900 58734 NT/LC 54854 NT/LC 47360 NT/LC 19491 86 Andigena laminirostris Plate-billed Mountain-toucan NT 1200 3200 2319 EN 1588 EN 1212 EN 456 16 Anisognathus notabilis Black-chinned Mountain-tanager LC 900 2200 28630 NT/LC 14281 VU 9817 VU 2067 76 Atlapetes blancae Antioquia Brush-finch CR 2400 2800 43 CR 12 CR 5 CR 0 100

157 Bangsia aureocincta Gold-ringed Tanager EN 500 2200 3030 EN 2088 EN 1553 EN 180 100

Bangsia edwardsi Moss-backed Tanager LC 900 2100 13887 VU 5547 VU 4198 EN 1127 67 Bangsia melanochlamys Black-and-gold Tanager VU 1000 2300 8976 VU 6645 VU 3253 EN 1074 100 Bangsia rothschildi Golden-chested Tanager LC 0 1100 19826 VU 15482 VU 13003 VU 6901 88 Basileuterus ignotus Pirre Warbler VU 1200 1650 26 CR 8 CR 7 CR 1 12 Boissonneaua jardini Velvet-purple Coronet LC 350 2200 35140 NT/LC 27216 NT/LC 17175 VU 5240 87 Bucco noanamae Sooty-capped Puffbird NT 0 100 30981 NT/LC 21728 NT/LC 16624 VU 4985 100 Calliphlox mitchellii Purple-throated Woodstar LC 1000 2400 33992 NT/LC 15342 VU 8905 VU 2231 62 Capito hypoleucus White-mantled Barbet EN 400 1600 3656 EN 2454 EN 724 EN 524 23 Capito quinticolor Five-colored Barbet VU 0 575 39345 NT/LC 34759 NT/LC 29658 NT/LC 14904 97 Capito squamatus Orange-fronted Barbet NT 0 1500 8433 VU 7959 VU 4669 EN 2561 13 Cephalopterus penduliger Long-wattled Umbrellabird VU 80 1800 36988 NT/LC 21071 NT/LC 16874 VU 8586 39 Cercomacra parkeri Parker's Antbird LC 1130 1950 9151 VU 4121 EN 1133 EN 603 15 Chlorochrysa nitidissima Multicoloured Tanager VU 1300 2200 12705 VU 7860 VU 2144 EN 911 57 Chlorochrysa phoenicotis Glistening-green Tanager LC 700 2200 28231 NT/LC 17698 VU 11476 VU 2791 60

Chlorophonia flavirostris Yellow-collared Chlorophonia LC 100 1900 27037 NT/LC 20276 NT/LC 15026 VU 5734 72 Chlorospingus flavovirens Yellow-green Bush-tanager VU 450 1400 5440 VU 3748 EN 2959 EN 1082 55 Chlorospingus semifuscus Dusky Bush-tanager LC 1200 2500 31256 NT/LC 13167 VU 8134 VU 2162 75 Cinclodes excelsior Stout-billed Cinclodes LC 3200 5200 1367 EN 389 EN 31 CR 4 2 Clytoctantes alixii Recurve-billed Bushbird EN 185 1750 71561 NT/LC 11250 VU 5930 VU 3243 16 Coeligena orina Glittering Starfrontlet CR 3150 3500 1084 EN 55 CR 45 CR 18 100 Coeligena wilsoni Brown Inca LC 700 1900 28441 NT/LC 14253 VU 9778 VU 2164 54 Crax alberti Blue-billed Curassow CR 0 1200 56192 NT/LC 12638 VU 3547 EN 3004 24 Crypturellus berlepschi Berlepsch's Tinamou LC 0 1300 49472 NT/LC 48100 NT/LC 40557 NT/LC 15991 78 Cyanolyca pulchra Beautiful Jay NT 900 2300 23612 NT/LC 12543 VU 9245 VU 1993 81 Dacnis berlepschi Scarlet-breasted Dacnis VU 0 1300 2935 EN 2811 EN 1501 EN 747 13 Dacnis hartlaubi Turquoise Dacnis VU 1300 2200 2404 EN 1106 EN 253 EN 73 5 Diglossa gloriosissima Chestnut-bellied Flowerpiercer EN 2500 3800 3104 EN 1015 EN 793 EN 215 100 Diglossa indigotica Indigo Flowerpiercer LC 700 2400 31340 NT/LC 19829 VU 13062 VU 3244 87

158 Dysithamnus occidentalis Bicoloured Antvireo VU 900 2200 10675 VU 7125 VU 4862 EN 946 48

Entomodestes coracinus Black Solitaire LC 400 1900 29323 NT/LC 18703 VU 13058 VU 3919 72 Eriocnemis derbyi Black-thighed Puffleg NT 2500 3600 2310 EN 1413 EN 204 EN 82 1 Eriocnemis isabellae Gorgeted Puffleg CR 2600 2900 44 CR 8 CR 7 CR 6 100 Eriocnemis mirabilis Colorful Puffleg CR 2200 2800 40 CR 14 CR 8 CR 10 100 Eriocnemis mosquera Golden-breasted Puffleg LC 1200 4000 24435 NT/LC 20055 NT/LC 9871 VU 3813 4 Grallaria alleni Moustached Antpitta VU 1800 2500 6992 VU 539 EN 236 EN 89 7 Grallaria urraoensis Antioquia Antpitta CR 2500 3300 270 EN 117 EN 92 CR 29 100 Grallaria flavotincta Yellow-breasted Antpitta LC 1300 2350 22408 NT/LC 10011 VU 5941 VU 1497 87 Grallaria gigantea Giant Antpitta VU 1200 3000 11420 VU 297 EN 10 CR 9 1 Grallaria rufocinerea Bicoloured Antpitta VU 1950 3150 721 EN 640 EN 34 CR 33 0 Grallaricula cucullata Hooded Antpitta VU 1500 2700 2999 EN 575 EN 271 EN 107 13 Habia cristata Crested Ant-tanager LC 700 1800 21142 NT/LC 10880 VU 6137 VU 1238 100 Habia gutturalis Sooty Ant-tanager NT 100 1000 20495 NT/LC 10642 VU 5661 VU 4047 19 Haplophaedia lugens Hoary Puffleg NT 1100 2500 3116 EN 2110 EN 1088 EN 422 33

Heliangelus strophianus Gorgeted Sunangel LC 1200 2800 790 EN 382 EN 234 EN 200 8 Heliodoxa imperatrix Empress Brilliant LC 400 2000 26350 NT/LC 18458 VU 13021 VU 3688 79 Henicorhina negreti Munchique Wood-wren CR 2250 2640 6908 VU 874 EN 569 EN 264 100 Hypopyrrhus pyrohypogaster Red-bellied Grackle EN 1000 2400 16236 VU 12242 VU 2691 EN 1702 45 Iridosornis porphyrocephalus Purplish-mantled Tanager NT 1500 2700 27378 NT/LC 12594 VU 5555 VU 2275 73 Lipaugus weberi Chestnut-capped Piha CR 1500 1800 739 EN 366 EN 110 EN 76 60 Machaeropterus deliciosus Club-winged Manakin LC 100 1900 28091 NT/LC 20748 NT/LC 16326 VU 7448 52 Margarornis stellatus Fulvous-dotted Treerunner NT 1200 2200 27856 NT/LC 11463 VU 6244 VU 1701 85 Megascops colombianus Colombian Screech-owl NT 1250 2200 10602 VU 6522 VU 2645 EN 796 77 Melanerpes pulcher Picidae LC 170 1500 48462 NT/LC 669 EN 494 EN 394 2 Micrastur plumbeus Plumbeous Forest-falcon VU 500 1500 60599 NT/LC 15318 VU 11661 VU 2972 79 Myiarchus apicalis Apical Flycatcher LC 400 2500 14729 VU 13513 VU 2490 EN 1270 20 Myioborus ornatus Golden-fronted Redstart LC 2400 3400 35484 NT/LC 6292 VU 3296 EN 1656 23 Myrmeciza berlepschi Stub-tailed Antbird LC 0 650 47366 NT/LC 44725 NT/LC 38146 NT/LC 16819 84

159 Myrmeciza nigricauda Esmeraldas Antbird LC 150 1500 36926 NT/LC 10570 VU 9147 VU 4289 57

Neomorphus radiolosus Banded Ground-cuckoo EN 30 1525 9919 VU 8091 VU 6110 VU 2614 55 Nyctiphrynus rosenbergi Choco Poorwill NT 0 900 48965 NT/LC 46723 NT/LC 37859 NT/LC 18194 83 Odontophorus dialeucos Tacarcuna Wood-quai VU 1050 1500 46 CR 26 CR 23 CR 5 17 Odontophorus hyperythrus Chestnut Wood-quail NT 1300 2700 29696 NT/LC 17905 VU 6608 VU 2573 57 Odontophorus melanonotus Dark-backed Wood-quail VU 1100 1900 867 EN 531 EN 378 EN 116 16 Ognorhynchus icterotis Yellow-eared Parrot EN 1200 3400 20032 NT/LC 17673 VU 5914 VU 3116 11 Oreothraupis arremonops Tanager Finch VU 1200 2600 14833 VU 10220 VU 5769 VU 1812 62 Ortalis columbiana Colombian Chachalaca LC 0 2500 12008 VU 10733 VU 1276 EN 1082 9 Ortalis garrula Chestnut-winged Chachalaca LC 0 800 43379 NT/LC 32217 NT/LC 6057 VU 4413 33 Patagioenas goodsoni Dusky Pigeon LC 0 1000 59842 NT/LC 56896 NT/LC 48451 NT/LC 18749 66 Penelope ortoni Baudo Guan EN 70 3100 40979 NT/LC 30004 NT/LC 26186 NT/LC 10950 53 Penelope perspicax Cauca Guan EN 650 2200 15139 VU 7421 VU 627 EN 457 53 Phalcoboenus carunculatus Carunculated Caracara LC 3000 4000 12115 VU 949 EN 85 CR 33 6 Phylloscartes lanyoni Antioquia Bristle-tyrant EN 450 900 6389 VU 999 EN 208 EN 220 41

Picumnus granadensis Greyish Piculet LC 800 2200 27015 NT/LC 20355 NT/LC 4492 EN 2099 93 Pipreola jucunda Orange-breasted Fruiteater LC 600 2500 20490 NT/LC 14218 VU 10614 VU 2351 44 Pittasoma rufopileatum Rufous-crowned Antpitta NT 0 1100 58075 NT/LC 56106 NT/LC 47829 NT/LC 18676 77 Psarocolius cassini Baudo Oropendola EN 100 365 9108 VU 3902 EN 3603 EN 1620 100 Pyrilia pulchra Rose-faced Parrot LC 0 1200 58090 NT/LC 54723 NT/LC 47204 NT/LC 18663 57 Scytalopus canus Paramillo Tapaculo LC 2600 4000 946 EN 532 EN 430 EN 272 100 Scytalopus stilesi Stiles's Tapaculo LC 1420 2130 2832 EN 1641 EN 337 EN 300 15 Scytalopus vicinior Narino Tapaculo LC 1200 2800 24387 NT/LC 12770 VU 7719 VU 2116 72 Semnornis ramphastinus Toucan Barbet NT 1000 2400 35418 NT/LC 18331 VU 7934 VU 2464 58 Tangara fucosa Green-naped Tanager NT 1400 2000 1536 EN 8 CR 1 CR 0 49 Tangara johannae Blue-whiskered Tanager NT 0 1000 62579 NT/LC 60669 NT/LC 51262 NT/LC 20076 84 Tangara rufigula Rufous-throated Tanager LC 400 2100 27784 NT/LC 19570 VU 14880 VU 4240 77 Thripadectes ignobilis Uniform Treehunter LC 200 2500 35219 NT/LC 28490 NT/LC 22435 NT/LC 7687 60 Thryothorus spadix Sooty-headed Wren LC 400 1800 28936 NT/LC 13844 VU 9513 VU 2733 82

160 Tinamus osgoodi Black Tinamou VU 900 1400 1466 EN 160 EN 30 CR 29 3

Urosticte benjamini Purple-bibbed Whitetip LC 700 1600 22019 NT/LC 10206 VU 7328 VU 1621 81 Urothraupis stolzmanni Black-backed Bush-finch LC 3000 3600 1116 EN 337 EN 16 CR 1 2 Veniliornis chocoensis Choco Woodpecker NT 0 1000 68604 NT/LC 65608 NT/LC 55930 NT/LC 22830 86 Vireo masteri Choco Vireo EN 850 2400 5590 VU 3704 EN 2573 EN 454 55 Xenopipo flavicapilla Yellow-headed Manakin NT 1200 2400 14021 VU 9492 VU 2811 EN 1213 40 Zentrygon goldmani Russet-crowned Quail-dove NT 90 1600 3690 EN 2611 EN 2108 EN 1680 60

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Biography

I was born in Villavicencio, a small town in the llanos region of Colombia in

1987. Raised in Villavicencio, my family then moved to England for three years. We moved back to Colombia where I graduated from my Ecology bachelors in Bogota at the

Pontificia Universidad Javeriana in 2010. For my bachelors, I graduated with honors with the highest GPA of the cohort, and was also awarded a distinction from the university.

I started my PhD in Environmental Science and Policy at Duke in 2011 under a

Fulbright-Colciencias scholarship. My research focused on bird conservation in tropical 177 regions, specifically on assessing threats to birds in biodiversity hotspots, setting priorities for their conservation, and encouraging action to prevent extinction.

My publication list includes peer-reviewed articles and books:

Peer-reviewed publications

Ocampo-Peñuela, N., R.S. Winton, C. Wu, E. Zambello, T. Wittig & N. Cagle.

2015. Patterns of bird-window collisions inform mitigation on a university campus.

PeerJ 4:e1652; DOI 10.7717/peerj.1652.

Ocampo-Peñuela, N & S.L. Pimm. 2015. Elevational ranges of montane birds and deforestation in the Western Andes of Colombia. PLoS ONE 10(12):e0143311. doi:

10.1371/journal.pone.0143311

177

Ocampo-Peñuela, N & S.L. Pimm. 2015. Bird conservation would complement landslide prevention in the Central Andes of Colombia. PeerJ 3:e779; DOI

10.7717/peerj.779.

Ocampo-Peñuela, N & S.L. Pimm. 2014. Setting practical conservation priorities for birds in the Western Andes of Colombia. Conservation Biology 28(5): 1260-1270.

Ocampo-Peñuela, N & A. Etter. 2013. Contribution of different forest types to the bird community of a savanna landscape in Colombia. Neotropical Ornithology 24: 35-53.

Farji-Brener, A.G., N. Morueta-Holme, F. Chinchilla, B. Willink, N. Ocampo-

Peñuela & G. Bruner. 2012. Leaf-cutting ants as road engineers: the width of trails at

branching points in Atta cephalotes. Insectes Sociaux: International Journal for the Study 178 of Social Arthropods 59: 389-394.

Agudelo, L., J. Moreno, & N. Ocampo-Peñuela. 2010. Colisiones de aves contra

ventanales en un campus universitario de Bogotá, Colombia. Ornitología Colombiana

10: 3-10.

Ocampo-Peñuela, N. 2010. El fenómeno de la migración en aves: una mirada desde la Orinoquia. Orinoquia 14 (2):188-200.

Ocampo-Peñuela, N. 2010. Contribución de los elementos boscosos del paisaje a la avifauna de un bioma de sabana en San Martín (Meta, Colombia). Thesis Summary.

Ornitología Colombiana 9:79.

178

Castro-Lima, F. & N. Ocampo-Peñuela. 2010. Primer registro del Jilguero Cara

Amarilla (FRINGILLIDAE: Carduelis yarrellii) en Colombia. Ornitología Colombiana 10:

69-71.

Ocampo-Peñuela, N. 2006. Comparación de la avifauna de tres sistemas de producción en los Llanos Orientales de Colombia. Rev. Est. Investig. Ecotono Ecol. Bio.

Soc. 4: 6-14.

Books

Múnera, C., N. Ocampo-Peñuela, J. Castaño, D. Calderón, R. Schiele & I. Macías.

2011. Travel Guide for Birdwatching Places in Colombia. Proexport Colombia. 93p.

Peñuela, L., F. Castro & N. Ocampo-Peñuela. 2011. Las Reservas Naturales del 179

Nodo Orinoquia en su rol de conservación de la biodiversidad. Fundación Horizonte

Verde y Resnatur. Colombia. 104p.

Ocampo-Peñuela, N. 2010. Editor. Mecanismos de conservación privada: una opción viable en Colombia. Grupo Colombiano Interinstitucional de Herramientas de

Conservación Privada. Bogotá, Colombia. 112p.

Book chapters

Ocampo-Peñuela, N., G.H. Kattan, & G. Cadena. 2014. Grallaria alleni, in:

Renjifo, L.M., Gomez, M.F., Velasquez-Tibata, J., Amaya-Villareal, A.M., Kattan, G.H.,

Amaya-Espinel, J.D., & Burbano-Giron, J. 2014. Libro rojo de aves de Colombia,

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Volumen I: bosques húmedos de los Andes y la costa Pacífica. Editorial Pontifica

Universidad Javeriana e Instituto Alexander von Humboldt. Bogotá D.C., Colombia.

Kattan, G.H., G. Cadena, & N. Ocampo-Peñuela. 2014. Grallaria milleri, in:

Renjifo, L.M., Gomez, M.F., Velasquez-Tibata, J., Amaya-Villareal, A.M., Kattan, G.H.,

Amaya-Espinel, J.D., & Burbano-Giron, J. 2014. Libro rojo de aves de Colombia,

Volumen I: bosques húmedos de los Andes y la costa Pacífica. Editorial Pontifica

Universidad Javeriana e Instituto Alexander von Humboldt. Bogotá D.C., Colombia.

Castaño-Hernández, J. & Ocampo-Peñuela, N. 2014. Ampelion rufaxilla, in:

Renjifo, L.M., Gomez, M.F., Velasquez-Tibata, J., Amaya-Villareal, A.M., Kattan, G.H.,

Amaya-Espinel, J.D., & Burbano-Giron, J. 2014. Libro rojo de aves de Colombia, 180

Volumen I: bosques húmedos de los Andes y la costa Pacífica. Editorial Pontifica

Universidad Javeriana e Instituto Alexander von Humboldt. Bogotá D.C., Colombia.

Ocampo-Peñuela, N. 2014. Bucco noanamae, in: Renjifo, L.M., Gomez, M.F.,

Velasquez-Tibata, J., Amaya-Villareal, A.M., Kattan, G.H., Amaya-Espinel, J.D., &

Burbano-Giron, J. 2014. Libro rojo de aves de Colombia, Volumen I: bosques húmedos de los Andes y la costa Pacífica. Editorial Pontifica Universidad Javeriana e Instituto

Alexander von Humboldt. Bogotá D.C., Colombia.

Other publications

Ocampo-Peñuela, N. Book review: A walk in the forest. Trends in Ecology &

Evolution 30 (9): 512. http://dx.doi.org/10.1016/j.tree.2015.07.004.

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Scholarships and grants

For my various field seasons and research projects, I have been awarded grants from the following agencies:

- Fulbright-Colciencias PhD scholarship – 2011-2016

- National Science Foundation Dissertation Improvement Grant – 2014

- The Rufford Small Grants Programme – 2014

- Duke Graduate School – 2014

- Duke Center for Latin American and Caribbean Studies – 2014

- IDEAWILD – 2009 and 2014

- The Explorers Club Exploration Fund – 2014 181

- Park Flight Internship; 2009; Bird bander in PRBO Conservation Science

(Point Reyes Bird Observatory, California, USA.

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