BIOLOGICAL CONSERVATION 133 (2006) 198– 211
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Rapid avifaunal collapse along the Amazonian deforestation frontier
Alexander C. Lees, Carlos A. Peres*
Centre for Ecology Evolution and Conservation, School of Environmental Sciences, University of East Anglia, Norwich, Norfolk NR4 7TJ, United Kingdom
ARTICLE INFO ABSTRACT
Article history: The combined effects of rapid habitat loss, fragmentation and disturbance on tropical for- Received 16 February 2006 est avifaunas have not been examined to date. The southern Amazonian ‘arc of deforesta- Received in revised form tion’ marks the boundary of the most aggressive agricultural frontier in tropical forests 15 May 2006 worldwide. We sampled 21 disturbed and undisturbed primary forest patches, ranging in Accepted 8 June 2006 size from 1.2 to 14,476 ha, to elucidate the synergistic effects of both forest disturbance and fragmentation on bird community structure, and pinpoint which species were the ‘‘winners’’ and ‘‘losers’’ from this process. A number of forest patch metrics, derived from Keywords: an independent remote sensing approach, explained much of the resulting presence/ Birds absence matrix. The bird community exhibited a highly nested structure, with small Brazil patches being most dissimilar from one another. Bird species differed in their response Habitat quality to both forest patch size and forest canopy perforation according to their dependence on Remote sensing closed-canopy primary forest. Forest patch geometry, which clearly modulated the shape Rainforest of species–area relationships accounted for 83–96% of the variation in species richness, Species–area relationships but forest habitat quality resulting from logging and surface-fire disturbance was also a sig- nificant predictor of species richness for the most forest-dependent taxa. 2006 Elsevier Ltd. All rights reserved.
1. Introduction mentation. Setting aside a major network of sufficiently large protected areas that can retain viable populations of all forest The current absolute rate of tropical deforestation is unprec- taxa is critical to ensure a reduced chance of future extinction edented, and nowhere is this loss more acute than in Brazil- events (Peres, 2005). ian Amazonia (INPE, 2005). By 2003, the total area of forest Virtually all studies of habitat fragmentation have demon- cleared had reached 64 Mha, with annual deforestation rates strated that patch size is a powerful predictor of species rich- in 2002 and 2003 climbing to nearly 2.4 Mha per year (Lau- ness; indeed this species–area relationship (SAR) is one of the rance et al., 2004; Fearnside, 2005). Of the 902 forest birds that few ‘‘Newtonian’’ rules in ecology (Lawton, 1999; Ginzburg and are threatened on a global scale, 82% are restricted to tropical Colyvan, 2004). The relationship between habitat area and forest and 41% to lowland forest (Birdlife International, 2000). number of species approximates to S = cAz where S is number The Brazilian Amazon retains at least 1300 resident bird spe- of species, A is area, and c and z are constants (Preston, 1962). cies, of which 263 species are endemic and 20 are threatened z-Values are known to increase as a result of land-class frag- (Mittermeier et al., 1999; Marini and Garcia, 2005). The major mentation (Rosenzweig, 1995) and true archipelagos typically threats to forest birds (and indeed most other forest wildlife) have higher z-values than mainland areas. This is generally of the region are the twin processes of habitat loss and frag- ascribed to different rates of immigration, extinction, and
* Corresponding author: Tel.: +44 1603 592549; fax: +44 1603 591327. E-mail address: [email protected] (C.A. Peres). 0006-3207/$ - see front matter 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2006.06.005 BIOLOGICAL CONSERVATION 133 (2006) 198– 211 199
speciation that occur in either insular or naturally fragmented est remnants are highly variable in size, degree of connectiv- biotas (Diamond and May, 1976; Brown and Dinsmore, 1988; ity, and levels of anthropogenic disturbance, including Bond et al., 1988; Rosenzweig, 1995). Higher values should logging, surface fires and hunting (Peres and Michalski, equate to more species encountered per area encompassed 2006), all of which can compound the effects of fragmentation and, by analogy, more species becoming locally extinct per (Nepstad et al., 1999; Peres, 2001; Cochrane and Laurance, area lost. Preston (1962) and MacArthur and Wilson (1967) pre- 2002; Martı´nez-Morales, 2005). Nowhere are these effects dicted that most z-values would fall within the range 0.15–0.35 more keenly felt than across the Amazonian ‘Arc of Defores- for the power form of species–area curves. z-Values obtained tation’ which encompasses over 60 municipal counties in from forest fragmentation experiments vary greatly, for exam- the states of Rondoˆ nia, Mato Grosso and Para´. Here we exam- ple from 0.177 to 0.250 for relict temperate forest patches in ine the effects of both forest fragmentation and forest canopy Chile (Cornelius et al., 2000) to 0.62 for isolated forest patches perturbation within remaining forest patches on the structure in New South Wales, Australia (Howe, 1984). Some authors of bird assemblages in a highly fragmented forest landscape have even attempted to derive estimates of species loss by in the deforestation arc of the southern Amazon. rearranging the species–area equation S = cAz with an esti- mate of the constant z (e.g. Brooks et al., 1997). 2. Methods In both temperate and tropical regions, there is a vast liter- ature on the effects of habitat fragmentation on wildlife and 2.1. Study area birds in particular (e.g. see reviews in: Saunders et al., 1991; Andre´n, 1994; Debinski and Holt, 2000; Fahrig, 2003). Aside The countryside around the town of Alta Floresta, State of from the ground-breaking work conducted north of Manaus Mato Grosso (09 530 S; 56 280 W), lies along the center of the under the auspices of the Biological Dynamics of Forest Frag- southern arc of Amazonian deforestation. Having experi- ments Project (e.g. Bierregaard et al., 1992), there has been no enced a very rapid expansion of its agricultural frontier since other published studies on the effects of forest fragmentation 1976, this represents a near-ideal region to study the effects of on the birds of the Amazon basin. The combination of road relatively recent fragmentation on flora and fauna in a ‘‘real paving and the creation of a number of large, central-govern- world’’ hyper-fragmented landscape retaining an inequitable ment sponsored agricultural resettlement programs during size distribution of forest patches (Fig. 1). The regional climate the 1970s and 1980s acted as a catalyst for massive forest is humid tropical with a mean annual rainfall of 2350 mm, clearance in southern Amazonia (Hecht, 1993). Subsidized including a pronounced dry season between May and Sep- by generous fiscal incentives for large-scale cattle ranching, tember (Young, 1976; RADAMBRASIL, 1983). The annual mean these programs have created several types of landscape struc- temperature is 26.5 C and the relative humidity is 76% (Barb- ture, ranging from the typical fish-bone pattern, dominated osa and Neves, 1985). The region is part of the Central Brazil- by small forest remnants in small landholdings, to those ian Crystalline Plateau, formed by Proterozoic terrain (1800– dominated by sizeable remnants within large cattle ranches 1100 Ma) comprising intermediate-acid volcanic bedrock and (Oliveira-Filho and Metzger, in press). Consequently, such for- scattered granite stocks. Local soils consist primarily of red-
Fig. 1 – Location of the study region around Alta Floresta, northern State of Mato Grosso, Brazil, showing the 21 surveyed sites (black), and surrounding forest (grey) and non-forest matrix (white). 200 BIOLOGICAL CONSERVATION 133 (2006) 198– 211
yellow latosols ca. 3 m deep, with scattered flooded areas con- area constraints. An equal amount of sampling time (10 point taining highly leached hydromorphic soils of the same origin counts per day) was allocated to fragments of all size classes (RADAMBRASIL, 1983). The town of Alta Floresta was founded and the control site. A total of 15 min were spent at each in 1976 by southern Brazilian immigrants, with the objective point count, systematically logging all bird species seen or of colonizing the upper Tapajo´ s river basin. Prior to 1976 the heard within the boundaries of the fragment, which may in- region had been entirely covered by undisturbed Amazonian clude typical ‘‘matrix taxa’’ if they occurred within the edge forest of similar physiognomy (Oliveira-Filho and Metzger, boundaries of the patch. Records of bird species detected in in press). Subsequently the region has experienced extremely the surrounding open-habitat matrix were excluded from high deforestation rates: by 2003 only 37% of the pre-frontier the analysis. forest cover remained in the Alta Floresta region south of the Sampled forest fragments ranged in size across five orders Teles Pires river (Michalski and Peres, 2005). Despite the of magnitude, from 1.2 to 14,476 ha. As a consequence, more nearly 30-year process of deforestation in Alta Floresta, most time per unit area was spent within small fragments and the forest isolates are much younger. For example, the forest frag- data may be biased against rare species occurring in larger ments examined in this study had a post-isolation ecological fragments. In addition, the total area sampled in small ‘relaxation’ history of only 3–24 years (mean ± SD = 9.75 ± 7.67 patches was proportionately larger than that in large patches. years, N = 20), equating to the time since the last significant Our results should therefore be considered conservative with reduction in patch size. Remaining forest remnants were also respect to habitat area effects owing to this potential Type II widely variable in size, shape and degree of connectivity, but error. Effects of seasonality (presence/absence of austral mi- otherwise were surrounded by a similar matrix of managed grants and peaks and troughs in vocalisation activity) were cattle pastures, the dominant land-use in Alta Floresta. controlled for by systematically rotating surveys in fragments of different size classes across the entire sampling period. 2.2. Sampling methods Point counts from each site were not treated as independent samples and were pooled producing a single binary pres- Prior to the study, one observer (A.C.L.) spent an intensive ence/absence matrix. The sampling period began a few min- training period of three months in the field at one of the con- utes pre-dawn and ended when all 10 counts had been trol forest sites (Rio Cristalino) and subsequently five months completed, invariably within a 3 h 30 min interval (0530– in the laboratory in order to recognise all the region’s avian 0900 h). Surveys were not carried out on days with rain and/ taxa by sight and sound. This relied on both commercially or strong winds. If a species’ identification was ever in doubt, available recordings (e.g. Mayer, 2000) and private recordings playbacks were used to lure the singer within sighting range by professional ornithologists. Because the Rio Cristalino to establish its identity, but playbacks were not used system- has become the premier ecotourism destination in Brazilian atically to increase the detectablity of any given species. In Amazonia for amateur ornithologists, this training period the present analysis we consider all species that were re- also benefited from the direct assistance of the leading neo- corded within the fragments. This therefore included some tropical ornithologists and at least 15 years of intensive orni- non-forest taxa, but we excluded all obligate water birds; noc- thological observations at this site (e.g. Zimmer et al., 1997). turnal species and aerial insectivores all of which were From June to September 2004, 630 unlimited radius point incompletely sampled. Although the control site was located counts (Blondel et al., 1970, 1981) were completed in 21 forest on the opposite bank of the Teles Pires river, from the per- sites, including 20 fragments and one continuous, undis- spective of traditional morphology-based taxonomy, this river turbed control site. Two large forest fragments were, however, does not represent an avifaunal barrier (Bates et al., 2004). larger than 10,000 ha and may be treated as pseudo-controls. We also assigned a primary forest dependence score to Most of the fragments included in the study were isolated each bird species including: (1) all strict forest interior un- from the wider skeletal forest matrix surrounding Alta Flor- der/mid-storey species; e.g. Variegated Antpitta (Grallaria var- esta with the exception of some of the larger (>1000 ha) rem- ia); (2) all remaining primary forest dependent species; e.g. nants. Finding true isolates for these largest size classes was Red-billed Pied-tanager (Lamprospiza melanoleuca); (3) forest impossible, as most remained nominally connected by ripar- species that are able to tolerate secondary or more degraded ian forest corridors along perennial streams as required by forest; e.g. Lineated Woodpecker (Drycopus lineatus); and (4) Brazilian environmental legislation (IBDF, 1965). Nineteen of primarily non-forest, scrub and open-country species e.g. the 21 sites surveyed had already been inventoried as part Ruddy Ground-dove (Columbina talpacoti). The score for each of a separate study (Michalski and Peres, 2005), these having species was independently based on published classifications been initially selected using a georeferenced 2001 Landsat of habitat use, including Stotz et al. (1996) and Wunderle et al. ETM image (scene 227/67), on the basis of their size, degree (2005), with the exception of recently described or poorly of isolation, and nature of the surrounding habitat matrix. known taxa such as Cryptic Forest-falcon (Micrastur mintoni) All sites were located within a 50-km radius of the town of (Whittaker, 2002) for which the classification was based on Alta Floresta and were accessible by river, paved or unpaved our own observations. roads, or both. GPS coordinates were obtained in situ to plot the location of all sampled forest patches. 2.3. Forest patch metrics Thirty point counts were completed within each site over three consecutive mornings at points along transects spaced Following a two-stage unsupervised classification of a 2004 200 m apart wherever possible, but this distance was inevita- Landsat image (ETM 227/067), it was possible to unambigu- bly reduced to 50 m in the smallest fragments owing to severe ously resolve eight mutually exclusive land cover classes BIOLOGICAL CONSERVATION 133 (2006) 198– 211 201
including closed-canopy forest, open-canopy forest, disturbed a general linear model (GLM). We performed the GLMs using forest, highly disturbed forest, managed and unmanaged the R statistical package (Ihaka and Gentleman, 1996: http:// pasture, bare ground, and open water. The image was geore- www.r-project.org). Specifically, we examined the effects of ferenced using a 1996 satellite image as a base which has an our composite patch metrics variable, the forest habitat qual- accuracy of 0.33 pixels, each of which with a spatial resolution ity index, the percentage of closed-canopy forest within the of 15 m. Landscape variables were then extracted from the im- patch, two landscape variables (the percentage forest cover age using Fragstats v. 3.3 (McGarigal et al., 2002) and ArcView within a 1-km buffer of the patch boundary and the straight- 3.2. For forest patches surveyed that were not completely iso- line distance to the nearest patch >1000 ha), and patch age lated (3 of 20 patches), we artificially eroded the narrowest on the total number of all bird species and the number of bird connections – usually consisting of riparian corridors to other species in each habitat sensitivity class. Patch age (years, sqrt- forest patches – in order to calculate the total patch area. Ero- transformed) was calculated from the time since a given patch sion of connections was always carried out across the narrow- had last succumbed to significant forest loss, when the sur- est groups of pixels representing the most degraded class of rounding pasture matrix was formed by extensive clearcut- forest cover such as young second-growth. The history of for- ting of adjacent primary forest areas. This information was est patch isolation was reconstructed from structured inter- obtained during focal, semi-structured interviews in estab- views at local households, and these data were then lished households in the proximity of each patch (Michalski independently verified using an annual Landsat image time and Peres, 2005), and then verified on the basis of an annual series dating back to 1978 (Michalski and Peres, 2005). To ob- Landsat image time-series (1980–2004). A supervised stepwise tain patch metrics data for our largest site located in vast model selection procedure based on the Akaike’s information tracts of continuous forest north of the Teles Pires River, we criterion (AIC) (Akaike, 1974) was then used to select the most allocated it an arbitrary area equivalent to one order of magni- significant predictor variables. We investigated the variation tude larger than the largest fragment. Subsequently we used among sites in the structure of the bird community using non- linear regression models based on all other patches to derive metric multidimensional scaling ordinations (NMDS; Clarke hypothetical shape and size patch metrics to facilitate com- and Green, 1988), with the Bray–Curtis dissimilarity measure, parison with this continuous patch. We used Fragstats to ex- using the PRIMER statistical package (Carr, 1996). tract metrics for patch area (AREA), core-area (where fixed Species assemblage nestedness is a common response to edge depth = 200 m), perimeter (PERIM), perimeter-edge ratio faunal relaxation so we used the nestedness calculator (Atmar (PARA) and shape index (SHAPE). Forest patch quality was and Patterson, 1993) to determine whether patterns of avian quantified on the basis of the number of 15 · 15 m pixels rep- occurrence within forest remnants created nested species dis- resenting each of the eight land cover classes. A forest habitat tributions among the surveyed sites. The nestedness calculator quality index (HQI) was then calculated using a weighted measures the extent of the ‘‘order’’ present in nested presence– mean value for all pixels within the patch. Closed-canopy for- absence matrices, as well as providing a risk assessment of the est was assigned the highest score, whereas bare ground was extinction probability of the populations isolated on islands of assigned the lowest, with six intermediate classes for dis- fragmented habitat. This procedure maximally packs the pres- turbed forest and pasture subtypes. ence–absence species matrix by ranking all sites according to their richness, by manipulating the number and position of 2.4. Data analysis unexpected presence ‘‘holes’’ and absence ‘‘oultliers’’ (Cutler, 1991). A matrix-wide value of heat disorder – the ‘‘nestedness We constructed expected species accumulation curves using temperature’’ – is then calculated. This may vary between 0 first-order Jackknife estimators (based on the numbers of for a perfectly nested system and 100 for a perfectly random duplicates and singletons and the number of samples) with system. Nestedness tests were performed on total richness of 95% confidence intervals, with the analytical formulas of species in habitat sensitivity classes 1, 2, 3 and 4 using 500 per- Colwell et al. (2004), using EstimateS 7.5 (Colwell, 2004). To mutations. The program does have some shortcomings (Fischer assess the species–area relationships between forest patch and Lindenmayer, 2002) and some absences within the matrix area (log10 ha) and number of bird species in each of the may be an artefact of undersampling (Cam et al., 2000) but this four habitat sensitivity classes, we performed linear regres- was only likely to be the case in the largest forest sites. sion models considering all 21 forest sites. The R2 value that we report is always the adjusted R2. To assess the ef- 3. Results fects of patch metrics, and to avoid problems associated with multicolinearity we combined the shape and size The size of the 21 forest sites surveyed ranged from 1.2 to patch metrics into independent linear combinations of the >100,000 ha (largest true patch = 14,476 ha; mean ± SD = original variables using principal component analysis 1489.3 ± 3917.7 ha). Forest patch quality was also highly vari-
(PCA). We used the first axis of a PCA (PC1) incorporating able with the pixel-scale percentage of closed-canopy forest the metrics derived using Fragstats for patch area, core ranging from 17.4% to 72.7% (mean ± SD = 49.5 ± 15.9%). Like- area, perimeter, and shape, which accounted for 96.6% of wise, the landscape context in which these patches were the cumulative variation. embedded was highly variable; the proportion of closed-can- Based on the PCA factor scores of the grid cells, we pre-se- opy primary forest within a 1-km circular buffer varied be- lected relatively uncorrelated and representative landscape tween 4.8% and 81.2% (mean ± SD = 24.4 ± 27.2%), and the indices and used these variables as predictors of species rich- distance to the nearest source patch >1000 ha ranged from 0 ness (based on total number of species recorded per patch) in to 10,301 m (mean ± SD = 3383 ± 2967 m). 202 BIOLOGICAL CONSERVATION 133 (2006) 198– 211
We recorded 328 bird species (excluding nocturnal species, random could be identical or ‘‘colder’’ than that observed in aerial insectivores and waterbirds); species occupancy per the Alta Floresta region is infinitesimally small (P = patch varied between 31 and 224 species (Table 1). Based on 1.24 · 10 48). The same measures calculated for forest habitat the jackknife index, completeness of the inventories at single sensitivity classes 2, 3 and 4 species were as follows: 30.2%, sites ranged between 66% and 94% for all birds (77.6 ± 6.8%; 11.3 , 68.9 (SD = 2.5 ), (P = 1.56 · 10 75); 35.0%, 19.6 , 68.5 Fig. 2). Near-exhaustive inventories (>85% completeness) (SD = 2.8 ), (P = 2.18 · 10 54); and 30.2%, 32.3 , 59.8 (SD = were only obtained in fragments smaller than 10 ha (N =5) 5.0 ), (P = 1.78 · 10 8). These results suggest that local extinc- (Fig. 2). Consequently, the species totals for large fragments tion events, from the most species-rich to the most species- should be regarded as conservative, in that some low-density poor site, are relatively predictable across different species and rare forest interior species were almost certainly missed in differing habitat sensitivity classes, with the most sensitive during sampling and it should be noted that new bird species group exhibiting the highest degree of nestedness. are recorded in the Alta Floresta region every year despite the Species richness per fragment increased over the entire intensive previous observer effort (Zimmer et al., 1997). range of observed fragment sizes in the Alta Floresta region, The species occupancy data for the most sensitive taxa (67 generating highly significant semi-log or double-log species– species in class 1) for all 21 sites (fragments and continuous area relationships (r2 = 0.957, P < 0.001, N = 21). Species–area forest) filled 31.8% of the cells in the overall species-by-site curves were markedly different when bird species were split matrix. The nestedness analysis calculated a temperature of into four different habitat sensitivity classes (Table 1). These 5.93 C for the observed matrix and we obtained a mean tem- relationships were significant despite expected differences perature of 65.24 C (SD = 3.65 ) on the basis of 500 randomly in these species responses to fragmentation (Fig. 3). When drawn matrices. Thus the probability that a matrix drawn at all other patch and landscape variables were considered
Table 1 – Linear species–area relationships and degree of assemblage nestedness for all species and those within different classes of habitat sensitivitya Total Range Nestedness R2-value R2-value z-Value number of per patch matrix (semi-log linear (log–log linear species temperatureb regression) regression)
Sensitivity 1 66 0–58 5.93 0.918 0.751 0.359 Sensitivity 2 139 6–104 11.3 0.960 0.818 0.257 Sensitivity 3 93 13–68 19.67 0.834 0.797 0.137 Sensitivity 4 30 5–12 32.36 0.13 0.122 0.039 All species 328 31–224 – 0.957 0.887 0.188
a (1) all strict forest interior under/mid-storey species; (2) all remaining primary forest dependent species; (3) forest species that are able to tolerate secondary or more degraded forest; (4) non-forest, scrub and open-country species. b Sensu Atmar and Patterson (1993).
Fig. 2 – Individual-based rarefaction curves of bird species richness on the basis of unlimited-radius point count stations estimated for all surveyed forest patches using the first-order jackknife method. BIOLOGICAL CONSERVATION 133 (2006) 198– 211 203
Fig. 3 – Species–area relationships for four functional groups of bird species with varying degrees of habitat requirements
(S1 = habitat sensitivity class 1; S2 = sensitivity class 2; S3 = sensitivity class 3; S4 = sensitivity class 4).
simultaneously for all species, our composite measure of predictor of species richness. For forest birds in sensitivity patch size and geometry (PC1) was the only significant predic- classes 2 and 3, PC1 was again the only significant predictor tor of bird species richness, whereas all other variables (patch of species richness. However, none of the predictor variables age, distance to the nearest patch >1000 ha, proportion of for- could account for the variation in species richness of non-for- est cover within 1-km buffers) were repeatedly excluded from est species (sensitivity 4). the model (Table 2). Replacing PC1 for patch size alone (log10 Small patches not only retained far fewer species than forest patch area) produced the same results in the final min- large patches, but NMDS scores indicate that they were also imum GLM. However, if only the most forest-dependent group more dissimilar from one another in assemblage composition (sensitivity 1) are considered, the habitat quality index (HQI) (Fig. 4). Similarity between large patches was highest for spe- (or alternatively the proportion of 15 m · 15 m pixels repre- cies in the most sensitive forest dependent class, with less senting closed-canopy primary forest) was also a significant sensitive classes becoming increasingly more dissimilar so
Table 2 – Minimum general linear models (GLMs) listing the most important forest patch and landscape variables (see text and footnotea) predicting the number of bird species within different classes of habitat sensitivity persisting in a forest patch Effect Estimate SE tP
All species (327 taxa) PC1b 26.613 1.456 18.282 0.000 Good forest 8.039 4.831 1.664 0.113 Akaike’s information criterion (AIC) model = 170.69
Sensitivity class 1 species (67 taxa) PC1 6.9422 0.4582 15.151 0.000 Good forest 5.2889 1.5205 3.478 0.003 Akaike’s information criterion (AIC) model = 122.14
Sensitivity class 2 species (138 taxa) PC1 13.1479 0.7083 18.563 0.000 Good forest 3.6457 2.3503 1.551 0.138 Akaike’s information criterion (AIC) model = 140.44
Sensitivity class 3 species (91 taxa) PC1 6.7596 0.6827 9.901 0.000 Akaike’s information criterion (AIC) model = 143.44
Sensitivity class 4 species (31 taxa) Fragment age 0.6817 0.5174 1.318 0.203 Akaike’s information criterion (AIC) model = 106.27
Stepwise model selection was performed using the Akaike’s information criterion (AIC). a Explanatory variables used in the analysis were as follows: PC1, fragment age, percentage of closed canopy forest pixels (good forest), percentage forest cover within 1 km of the patch boundary and straight-line distance to the nearest patch larger than 1000 ha. b PC1 is a composite measure of patch size and geometry. 204 BIOLOGICAL CONSERVATION 133 (2006) 198– 211
Fig. 4 – Bird assemblage composition as a function of forest patch size for four species groupings according to habitat sensitivity: (a) class 1 [stress = 0.11]; (b) class 2 [stress = 0.09]; (c) class 3 [stress = 0.12]; (d) class 4 [stress = 0.18]. Each point is a global, two-dimensional nonmetric multidimensional scaling (NMDS) representation of bird species composition. Distances between points reflect a dissimilarity matrix created using the Bray–Curtis coefficient. Bubble size is proportional to forest patch size, which predicted most of the variation in NMDS dimension 1 (e.g. for sensitivity class 1: R2 = 0.877, N = 21, P = <0.000).
that no obvious relationship could be detected for class 4 spe- environmental gradients, including forest types, soil types, cies. This suggests that core primary forest interior species and tree species composition as quantified within quarter- were more strongly affected by patch area than were sec- hectare forest plots sampled in all but two of our sites ond-growth and/or edge species. In fact, small fragments (F. Michalski and C. Peres, unpublished data). Most, if not (>50 ha) were dominated by edge effects and often retained all, differences in avian alpha-diversity between sites are no core forest habitat, rendering the entire patch susceptible therefore assumed to be the result of differences in patch to invasion by second-growth taxa. and landscape characteristics. Our estimates of z = 0.359 (sen- sitivity 1) to 0.137 (sensitivity 3) span the entire ‘‘null’’ range of 4. Discussion z-value estimates and suggest that more species extinctions should be expected for the most forest-dependent taxa. How- This study clearly shows that primary forest bird assemblages ever, Connor and McCoy (1979) observed that z-values in the in southern Amazonia are severely eroded following a rela- range 0.2–0.4 are ‘‘characteristic of any regression system tively brief post-fragmentation history marked by both the with a high r-value and a small range in the dependent vari- isolation and internal disturbance of remaining forest able [species] relative to that in the independent variable patches. Although habitat area predicted most of the varia- [area]’’, questioning the legitimacy of making too many infer- tion in species persistence, the SAR for primary forest special- ences based on z-values. Furthermore, experimental work ists was also mediated by habitat quality, defined in terms of based on bryophyte microlandscapes suggest that predicting pixel-scale forest canopy fracture and perforation, which in future species loss by increasing z with respect to a single turn is affected by the extent of selective logging and surface estimate of fluctuating continuous z-values may result in wildfire disturbance, and edge effects. We found no evidence unreliable predictions of future species loss (Gonzalez, to suggest that differences in bird species composition be- 2000). Nevertheless, the fact that observed z-values for differ- tween sites were due to pre-existing baseline differences in ent functional groups of species were consistent with our BIOLOGICAL CONSERVATION 133 (2006) 198– 211 205
hypotheses – that more sensitive species should be lost at a (e.g. Stratford and Stouffer, 1999) are all inextricably linked faster rate – does suggest that analysis of z-values is a worth- to patch size. while exercise. Fundamentally, however, for the most sensitive group of Nestedness is most prevalent in habitat patches derived forest specialists we found internal habitat patch quality to from a once continuous system with a common species pool be a highly significant determinant of species richness, that that has subsequently become isolated (Atmar and Patterson, can interact if not supersede the effects of patch size and 1993). Following local extinction events, the nestedness of the geometry. Habitat quality was highly variable between first three species-by-site matrices was highly non-random in patches because of differing gradients of anthropogenic im- terms of the order in which different species were lost from pacts, such as logging and surface wildfires, which kill a large the most species-rich to the most species-poor patch. The proportion of canopy trees (Barlow and Peres, 2004; Barlow high degree of nestedness observed in the forest patches et al., 2006). For instance, sympathetic landowners were able around Alta Floresta suggests that fragmentation dispropor- to conserve more forest-dependent species in a relatively tionately influences species based on their ecological traits. pristine 80-ha patch than a 200-ha patch that had been heav- The neutral theory (Hubbell, 2001) suggests that functional ily disturbed, but the total number of species in the two sites differences among species need not play an important role might be quite similar, due to the propensity to invasion of in generating SARs. Our results would appear to contradict the larger patch by ‘‘weedy’’ second-growth or scrub species this assumption, suggesting that this ecological neutrality such as Smooth-billed Ani (Crotophaga ani), Great Antshrike may break-down given a history of disturbance, certainly an (Taraba major) and Palm Tanager (Thraupis palmarum). Distance area worthy of future research. Even so, for functionally sim- and isolation metrics are widely regarded as important pre- ilar species, such as various obligate mixed-species flock-fol- dictors of species richness when habitat fragments are spaced lowing taxa, the species remaining within any given small by 100–10,000 m (e.g. Newmark, 1991; Bierregaard et al., 1992). fragment of a similar size class may be due to chance differ- That we could not find community-level evidence for such an ences in extinction, persistence, and colonisation events, effect in our study may be an artefact of sample size and the rather than their inherent ecological characteristics. Results recent relaxation history of the fragmented landscape. Many from the nestedness simulations are reinforced by those of patches may owe an extinction debt (Tilman et al., 1994) if the ordinations that show the structuring of the community their isolation precludes any rescue effect (Brown and Kod- gradually disintegrating, as less forest-dependent species ric-Brown, 1977). Brooks et al. (1999) reported that most are included. Second-growth tolerant and edge species were extinctions in tropical forest fragment systems occurred much less fragmentation-sensitive and their patch occupancy within 120 years of habitat loss. This is at odds with the rela- probability did not rise as steeply with increasing patch area. tively unimportant effects of time-since-isolation so far, as The relationship between patch size and fragmentation detected in the GLMs (Table 2), in the relatively young forest may be ambiguous because both habitat loss and habitat frag- patches we surveyed. The ecological consequences of the mentation per se (i.e. the subdivision of habitat, controlling landscape fragmentation process around Alta Floresta could for the remaining habitat area) result in smaller patches (Fah- therefore be considered incipient, and even large fragments rig, 2003). Usage of patch size as a measure of habitat frag- may continue to haemorrhage bird species for up to 100 years, mentation per se assumes that patch size is independent of even without further reduction in patch area, which is unli- habitat availability at the landscape scale (e.g. Niemela¨, kely in this region. Moreover, a landscape-scale projection of 2001). Realistically, this is not the case in many landscapes, avian assemblage impoverishment in Alta Floresta would re- where large patches are more common in regions retaining sult in a far worse scenario than that suggested by the size more habitat (McCoy and Mushinsky, 1999). The Alta Floresta distribution of the patches we sampled because most remain- landscape is such an example in that forest patch sizes tend ing forest patches in this region and other Amazonian defor- to increase with greater radial distances from the town in estation frontiers (Peres, 2001) are considerably smaller near concentric rings. The relative importance of habitat loss (Fig. 1). Future local extinctions seem to be a certainty, but alone, patch size, and patch isolation is scale-dependent with the fact that newly isolated patches already conform to strong the latter two variables likely to have more of an effect in species–area relationships emphasises how rapidly tropical smaller patches (Andre´n, 1994). Classic ‘‘area effects’’ there- forest fragmentation affects community structuring. fore not only relate to the amount of available space for spe- A simple remote sensing approach based on readily avail- cies packing but other factors that interact synergistically able satellite images, such as used here, is an efficient and with area – many of these fall under the edge effects umbrella objective tool for large-scale monitoring of the quality of for- – specifically for birds: microclimatic changes causing edge- est cover. Observed levels of bird species diversity on the implosion and consequent habitat alteration (Ferreira and ground were predicted remarkably well based on both habitat Laurance, 1997; Cochrane and Laurance, 2002), increased patch area and pixel-scale patch quality data gleaned from nest-predation rates following meso-predator release in small space, which paves the way to relatively accurate predictive fragments (e.g. Batari and Baldi, 2004; Stephens et al., 2004) models of species persistence based on patch metrics, land- and increased rates of parasitism (Brash, 1987). Furthermore scape configuration, and the quality of both habitat patch density-dependent scramble competition (Poethke et al., and the surrounding matrix. Finally, we suggest that the 1996), food availability (Didham et al., 1996; Didham, 1997; importance of habitat quality in species–area relationships Zanette et al., 2000, but see Sekercioglu et al., 2002) and oppor- can be even more important than area per se for the most for- tunities for dispersal (Stouffer and Bierregaard, 1995; Seker- est dependent species, which are in steep decline in most cioglu et al., 2002) and subsequent genetic bottlenecking tropical deforestation frontiers. 206 BIOLOGICAL CONSERVATION 133 (2006) 198– 211
Acknowledgements iod; Fernanda Michalski for logistical support and counsel; Geraldo Arau´ jo, Kim Barbieri, Luiz Crestani and the staff This study was funded by a small grant from the Center at the Fundac¸a˜o Ecolo´ gica Cristalino for help with logisti- of Applied Conservation Sciences at Conservation Interna- cal and transport problems; Joe Tobias and Sjoerd tional. We thank Vitoria da Riva Carvalho and her staff at Mayer for help with bird sound identification and all the both the Floresta Amazonica Hotel and Cristalino Jungle landowners and people of Alta Floresta for their co-opera- Lodge for providing accommodation during the study per- tion.
Appendix A
Classification and nomenclature follows Remsen et al. (2006)
Latin binomial English name Sens Latin binomial English name Sens
Tinamus tao Gray Tinamou 2 Geotrygon violacea Violaceous Quail-Dove 3 Tinamus major Great Tinamou 3 Geotrygon montana Ruddy Quail-Dove 2 Crypturellus cinereus Cinereous Tinamou 2 Ara ararauna Blue-and-yellow Macaw 3 Crypturellus soui Little Tinamou 3 Ara macao Scarlet Macaw 2 Crypturellus obsoletus Brown Tinamou 2 Ara chloropterus Red-and-green Macaw 2 Crypturellus undulatus Undulated Tinamou 2 Ara severus Chestnut-fronted Macaw 3 Crypturellus strigulosus Brazilian Tinamou 2 Orthopsittaca manilata Red-bellied Macaw 4 Crypturellus variegatus Variegated Tinamou 2 Aratinga leucophthalma White-eyed Parakeet 3 Crypturellus tataupa Tataupa Tinamou 4 Pyrrhura perlata Crimson-bellied Parakeet 2 Penelope jacquacu Spix’s Guan 2 Pyrrhura picta Painted Parakeet 2 Pipile cujubi Red-throated Piping-Guan 2 Forpus sclateri Dusky-billed Parrotlet 2 Mitu tuberosum Razor-billed Curassow 2 Brotogeris chrysoptera Golden-winged Parakeet 3 Crax fasciolata Bare-faced Curassow 2 Touit huetii Scarlet-shouldered Parrotlet 2 Pionites leucogaster White-bellied Parrot 2 Odontophorus gujanensis Marbled Wood-Quail 2 Pionus menstruus Blue-headed Parrot 3 Cathartes melambrotus Greater Yellow-headed 2 Amazona ochrocephala Yellow-crowned Parrot 3 Vulture Amazona kawalli Kawall’s Parrot 2 Coragyps atratus Black Vulture 4 Amazona amazonica Orange-winged Parrot 2 Amazona farinosa Mealy Parrot 2 Harpagus bidentatus Double-toothed Kite 2 Deroptyus accipitrinus Red-fan Parrot 2 Ictinia plumbea Plumbeous Kite 3 Accipiter superciliosus Tiny Hawk 2 Piaya cayana Squirrel Cuckoo 3 Geranospiza caerulescens Crane Hawk 2 Piaya melanogaster Black-bellied Cuckoo 2 Leucopternis kuhli White-browed Hawk 2 Piaya minuta Little Cuckoo 4 Asturina nitida Gray Hawk 4 Crotophaga ani Smooth-billed Ani 4 Buteo magnirostris Roadside Hawk 4 Buteo brachyurus Short-tailed Hawk 3 Dromococcyx phasianellus Pheasant Cuckoo 2 Spizaetus tyrannus Black Hawk-Eagle 2 Dromococcyx pavoninus Pavonine Cuckoo 2 Spizaetus ornatus Ornate Hawk-Eagle 2 Glaucis hirsutus Rufous-breasted Hermit 3 Daptrius ater Black Caracara 3 Threnetes leucurus Pale-tailed Barbthroat 3 Ibycter americanus Red-throated Caracara 2 Phaethornis ruber Reddish Hermit 2 Caracara plancus Southern Caracara 4 Phaethornis bourcieri Straight-billed Hermit 2 Herpetotheres cachinnans Laughing Falcon 4 Phaethornis superciliosus Eastern Long-tailed Hermit 2 Micrastur ruficollis Barred Forest-Falcon 2 Campylopterus largipennis Gray-breasted Sabrewing 3 Micrastur mintoni Cryptic Forest-Falcon 2 Florisuga mellivora White-necked Jacobin 3 Micrastur mirandollei Slaty-backed Forest-Falcon 2 Anthracothorax nigricollis Black-throated Mango 4 Micrastur semitorquatus Collared Forest-Falcon 2 Discosura langsdorffi Black-bellied Thorntail 3 Falco sparverius American Kestrel 4 Thalurania furcata Fork-tailed Woodnymph 3 Falco rufigularis Bat Falcon 3 Hylocharis cyanus White-chinned Sapphire 3 Psophia viridis Dark-winged Trumpeter 1 Amazilia versicolor Versicolored Emerald 3 Heliothryx auritus Black-eared Fairy 2 Columbina talpacoti Ruddy Ground-Dove 4 Heliomaster longirostris Long-billed Starthroat 3 Claravis pretiosa Blue Ground-Dove 3 Calliphlox amethystina Amethyst Woodstar 3 Patagioenas speciosa Scaled Pigeon 2 Patagioenas picazuro Picazuro Pigeon 4 Trogon viridis White-tailed Trogon 2 Patagioenas cayennensis Pale-vented Pigeon 4 Trogon curucui Blue-crowned Trogon 2 Patagioenas plumbea Plumbeous Pigeon 2 Trogon violaceus Violaceous Trogon 3 Patagioenas subvinacea Ruddy Pigeon 2 Trogon collaris Collared Trogon 2 Leptotila verreauxi White-tipped Dove 3 Trogon rufus Black-throated Trogon 3 Leptotila rufaxilla Gray-fronted Dove 3 Trogon melanurus Black-tailed Trogon 2 BIOLOGICAL CONSERVATION 133 (2006) 198– 211 207
Appendix A – continued
Latin binomial English name Sens Latin binomial English name Sens
Electron platyrhynchum Broad-billed Motmot 2 Sclerurus caudacutus Black-tailed Leaftosser 1 Momotus momota Blue-crowned Motmot 3 Sclerurus albigularis Gray-throated Leaftosser 1
Galbula cyanicollis Blue-cheeked Jacamar 2 Xenops tenuirostris Slender-billed Xenops 2 Galbula ruficauda Rufous-tailed Jacamar 3 Xenops minutus Plain Xenops 2 Galbula dea Paradise Jacamar 2 Dendrocincla fuliginosa Plain-brown Woodcreeper 1 Jacamerops aureus Great Jacamar 1 Dendrocincla merula White-chinned Woodcreeper 1 Notharchus hyperrhynchus White-necked Puffbird 3 Deconychura longicauda Long-tailed Woodcreeper 1 Notharchus ordii Brown-banded Puffbird 2 Deconychura stictolaema Spot-throated Woodcreeper 1 Notharchus tectus Pied Puffbird 3 Sittasomus griseicapillus Olivaceous Woodcreeper 3 Bucco capensis Collared Puffbird 1 Glyphorynchus spirurus Wedge-billed Woodcreeper 3 Nystalus striolatus Striolated Puffbird 3 Dendrexetastes rufigula Cinnamon-throated 2 Malacoptila rufa Rufous-necked Puffbird 2 Woodcreeper Nonnula frontalis Gray-cheeked Nunlet 2 Hylexetastes perrotii Red-billed Woodcreeper 2 Monasa nigrifrons Black-fronted Nunbird 3 Xiphocolaptes promeropirhynchus Strong-billed Woodcreeper 2 Monasa morphoeus White-fronted Nunbird 2 Dendrocolaptes certhia Amazonian Barred- 1 Chelidoptera tenebrosa Swallow-winged Puffbird 3 Woodcreeper Dendrocolaptes picumnus Black-banded 1 Capito dayi Black-girdled Barbet 2 Woodcreeper Ramphastos tucanus White-throated Toucan 2 Xiphorhynchus picus Straight-billed 3 Ramphastos vitellinus Channel-billed Toucan 2 Woodcreeper Selenidera gouldii Gould’s Toucanet 2 Xiphorhynchus obsoletus Striped Woodcreeper 2 Pteroglossus inscriptus Lettered Aracari 3 Xiphorhynchus elegans/spixii Elegant/Spix’s 2 Pteroglossus bitorquatus Red-necked Aracari 3 Woodcreeper Pteroglossus castanotis Chestnut-eared Aracari 3 Xiphorhynchus guttatus Buff-throated Woodcreeper 2 Pteroglossus beauharnaesii Curl-crested Aracari 2 Lepidocolaptes albolineatus Lineated Woodcreeper 2 Campylorhamphus procurvoides Curve-billed Scythebill 2 Picumnus aurifrons Bar-breasted Piculet 3 Cymbilaimus lineatus Fasciated Antshrike 2 Melanerpes cruentatus Yellow-tufted Woodpecker 3 Taraba major Great Antshrike 3 Veniliornis affinis Red-stained Woodpecker 2 Sakesphorus luctuosus Glossy Antshrike 2 Piculus flavigula Yellow-throated 2 Thamnophilus palliatus Chestnut-backed Antshrike 2 Woodpecker Thamnophilus aethiops White-shouldered Antshrike 1 Piculus chrysochloros Golden-green Woodpecker 2 Thamnophilus schistaceus Plain-winged Antshrike 1 Celeus grammicus Scale-breasted Woodpecker 2 Thamnophilus stictocephalus Natterer’s Slaty-Antshrike 2 Celeus elegans Chestnut Woodpecker 2 Thamnophilus amazonicus Amazonian Antshrike 1 Celeus torquatus Ringed Woodpecker 2 Thamnomanes saturninus Saturnine Antshrike 1 Dryocopus lineatus Lineated Woodpecker 3 Thamnomanes caesius Cinereous Antshrike 1 Campephilus rubricollis Red-necked Woodpecker 2 Pygiptila stellaris Spot-winged Antshrike 2 Campephilus melanoleucos Crimson-crested 3 Woodpecker Myrmotherula leucophthalma White-eyed Antwren 1 Myrmotherula ornata Ornate Antwren 2 Synallaxis rutilans Ruddy Spinetail 2 Myrmotherula brachyura Pygmy Antwren 3 Synallaxis cherriei Chestnut-throated Spinetail 2 Myrmotherula sclateri Sclater’s Antwren 2 Cranioleuca gutturata Speckled Spinetail 2 Myrmotherula hauxwelli Plain-throated Antwren 1 Simoxenops ucayalae Peruvian Recurvebill 2 Myrmotherula axillaris White-flanked Antwren 3 Ancistrops strigilatus Chestnut-winged Hookbill 2 Myrmotherula longipennis Long-winged Antwren 1 Hyloctistes subulatus Striped Woodhaunter 1 Myrmotherula menetriesii Gray Antwren 1 Philydor ruficaudatum Rufous-tailed Foliage- 2 Herpsilochmus rufimarginatus Rufous-winged Antwren 2 gleaner Microrhopias quixensis Dot-winged Antwren 2 Philydor erythrocercum Rufous-rumped Foliage- 2 Drymophila devillei Striated Antbird 2 gleaner Cercomacra cinerascens Gray Antbird 1 Philydor erythropterum Chestnut-winged Foliage- 2 Cercomacra nigrescens Blackish Antbird 3 gleaner Cercomacra manu Manu Antbird 2 Philydor pyrrhodes Cinnamon-rumped Foliage- 1 Pyriglena leuconota White-backed Fire-eye 1 gleaner Myrmoborus leucophrys White-browed Antbird 2 Anabazenops dorsalis Dusky-cheeked Foliage- 1 Myrmoborus myotherinus Black-faced Antbird 1 gleaner Hypocnemis cantator Warbling Antbird 1 Automolus ochrolaemus Buff-throated Foliage- 1 Myrmeciza hemimelaena Chestnut-tailed Antbird 2 gleaner Myrmeciza atrothorax Black-throated Antbird 3 Automolus paraensis Para Foliage-gleaner 1 Rhegmatorhina gymnops Bare-eyed Antbird 1 Automolus rufipileatus Chestnut-crowned Foliage- 2 Hylophylax naevius Spot-backed Antbird 1 gleaner Hylophylax poecilinotus Scale-backed Antbird 1 Sclerurus mexicanus Tawny-throated Leaftosser 1 Phlegopsis nigromaculata Black-spotted Bare-eye 1 Sclerurus rufigularis Short-billed Leaftosser 1 (continued on next page) 208 BIOLOGICAL CONSERVATION 133 (2006) 198– 211
Appendix A – continued
Latin binomial English name Sens Latin binomial English name Sens
Formicarius colma Rufous-capped Antthrush 1 Chiroxiphia pareola Blue-backed Manakin 1 Formicarius analis Black-faced Antthrush 1 Pipra fasciicauda Band-tailed Manakin 2 Grallaria varia Variegated Antpitta 1 Pipra rubrocapilla Red-headed Manakin 1 Hylopezus macularius Spotted Antpitta 1 Tityra inquisitor Black-crowned Tityra 3 Hylopezus berlepschi Amazonian Antpitta 3 Tityra semifasciata Masked Tityra 3 Myrmothera campanisona Thrush-like Antpitta 1 Schiffornis turdina Thrush-like Schiffornis 1 Conopophaga aurita Chestnut-belted Gnateater 1 Laniocera hypopyrra Cinereous Mourner 1 Pachyramphus castaneus Chestnut-crowned Becard 3 Tyrannulus elatus Yellow-crowned Tyrannulet 3 Pachyramphus polychopterus White-winged Becard 3 Myiopagis gaimardii Forest Elaenia 3 Pachyramphus marginatus Black-capped Becard 2 Myiopagis caniceps Gray Elaenia 2 Pachyramphus minor Pink-throated Becard 2 Ornithion inerme White-lored Tyrannulet 2 Piprites chloris Wing-barred Piprites 1 Corythopis torquatus Ringed Antpipit 1 Capsiempis flaveola Yellow Tyrannulet 3 Cyclarhis gujanensis Rufous-browed 3 Zimmerius gracilipes Slender-footed Tyrannulet 2 Peppershrike Mionectes oleagineus Ochre-bellied Flycatcher 3 Vireolanius leucotis Slaty-capped Shrike-Vireo 2 Leptopogon amaurocephalus Sepia-capped Flycatcher 3 Vireo olivaceus Red-eyed Vireo 3 Sublegatus modestus Southern Scrub-Flycatcher 4 Hylophilus semicinereus Gray-chested Greenlet 3 Myiornis ecaudatus Short-tailed Pygmy-Tyrant 2 Hylophilus hypoxanthus Dusky-capped Greenlet 2 Lophotriccus galeatus Helmeted Pygmy-Tyrant 3 Hylophilus ochraceiceps Tawny-crowned Greenlet 1 Hemitriccus minor Snethlage’s Tody-Tyrant 1 Microcerculus marginatus Scaly-breasted Wren 1 Hemitriccus griseipectus White-bellied Tody-Tyrant 1 Odontorchilus cinereus Tooth-billed Wren 2 Poecilotriccus latirostris Rusty-fronted Tody- 3 Troglodytes aedon House Wren 4 Flycatcher Campylorhynchus turdinus Thrush-like Wren 3 Todirostrum chrysocrotaphum Yellow-browed Tody- 3 Thryothorus genibarbis Moustached Wren 2 Flycatcher Thryothorus leucotis Buff-breasted Wren 2 Tolmomyias assimilis Yellow-margined Flycatcher 1 Cyphorhinus arada Musician Wren 1 Tolmomyias flaviventris Yellow-breasted Flycatcher 2 Platyrinchus saturatus Cinnamon-crested 1 Ramphocaenus melanurus Long-billed Gnatwren 2 Spadebill Turdus lawrencii Lawrence’s Thrush 1 Platyrinchus platyrhynchos White-crested Spadebill 1 Turdus fumigatus Cocoa Thrush 1 Onychorhynchus coronatus Royal Flycatcher 1 Turdus albicollis White-necked Robin 1 Terenotriccus erythrurus Ruddy-tailed Flycatcher 1 Lathrotriccus euleri Euler’s Flycatcher 3 Cissopis leverianus Magpie Tanager 3 Colonia colonus Long-tailed Tyrant 3 Lamprospiza melanoleuca Red-billed Pied Tanager 2 Legatus leucophaius Piratic Flycatcher 3 Tachyphonus cristatus Flame-crested Tanager 2 Myiozetetes cayanensis Rusty-margined Flycatcher 4 Tachyphonus luctuosus White-shouldered Tanager 3 Myiozetetes luteiventris Dusky-chested Flycatcher 2 Lanio versicolor White-winged Shrike- 2 Pitangus sulphuratus Great Kiskadee 4 Tanager Pitangus lictor Lesser Kiskadee 4 Ramphocelus carbo Silver-beaked Tanager 4 Megarynchus pitangua Boat-billed Flycatcher 3 Thraupis episcopus Blue-gray Tanager 4 Empidonomus varius Variegated Flycatcher 3 Thraupis palmarum Palm Tanager 4 Tyrannus albogularis White-throated Kingbird 4 Tangara chilensis Paradise Tanager 3 Tyrannus melancholicus Tropical Kingbird 4 Tangara schrankii Green-and-gold Tanager 2 Tyrannus savana Fork-tailed Flycatcher 4 Tangara gyrola Bay-headed Tanager 2 Rhytipterna simplex Grayish Mourner 2 Tangara cyanicollis Blue-necked Tanager 3 Myiarchus tuberculifer Dusky-capped 3 Tangara nigrocincta Masked Tanager 3 Flycatcher Tangara velia Opal-rumped Tanager 2 Myiarchus ferox Short-crested Flycatcher 3 Dacnis lineata Black-faced Dacnis 3 Myiarchus tyrannulus Brown-crested Flycatcher 4 Dacnis flaviventer Yellow-bellied Dacnis 2 Ramphotrigon megacephalum Large-headed Flatbill 2 Dacnis cayana Blue Dacnis 3 Ramphotrigon ruficauda Rufous-tailed Flatbill 2 Cyanerpes nitidus Short-billed Honeycreeper 2 Ramphotrigon fuscicauda Dusky-tailed Flatbill 2 Cyanerpes caeruleus Purple Honeycreeper 3 Attila cinnamomeus Cinnamon Attila 2 Chlorophanes spiza Green Honeycreeper 2 Attila spadiceus Bright-rumped Attila 2 Hemithraupis flavicollis Yellow-backed Tanager 3 Cotinga cayana Spangled Cotinga 2 Habia rubica Red-crowned Ant-Tanager 1 Lipaugus vociferans Screaming Piha 2 Coereba flaveola Bananaquit 4 Xipholena punicea Pompadour Cotinga 2 Gymnoderus foetidus Bare-necked Fruitcrow 2 Volatinia jacarina Blue-black Grassquit 4 Arremon taciturnus Pectoral Sparrow 1 Tyranneutes stolzmanni Dwarf Tyrant-Manakin 1 Machaeropterus pyrocephalus Fiery-capped Manakin 1 Parkerthraustes humeralis Yellow-shouldered Grosbeak 2 Lepidothrix nattereri Snow-capped Manakin 1 Saltator grossus Slate-colored Grosbeak 1 Manacus manacus White-bearded Manakin 3 Saltator maximus Buff-throated Saltator 3 BIOLOGICAL CONSERVATION 133 (2006) 198– 211 209
Appendix A – continued
Latin binomial English name Sens Latin binomial English name Sens
Saltator coerulescens Grayish Saltator 4 Cacicus haemorrhous Red-rumped Cacique 3 Cyanocompsa cyanoides Blue-black Grosbeak 3 Icterus cayanensis Epaulet Oriole 3 Molothrus oryzivorus Giant Cowbird 4 Granatellus pelzelni Rose-breasted Chat 2 Euphonia chlorotica Purple-throated Euphonia 3 Psarocolius decumanus Crested Oropendola 3 Euphonia minuta White-vented Euphonia 2 Psarocolius bifasciatus Olive Oropendola 3 Euphonia chrysopasta Golden-bellied Euphonia 2 Cacicus cela Yellow-rumped Cacique 3 Euphonia rufiventris Rufous-bellied Euphonia 2
*Remsen, J.V., Jr., Jaramillo, A., Nores, M., Pacheco, J.F., Robbins, M.B., Schulenberg, T.S., Stiles, F.G., da Silva, J.M.C., Stotz, D.F., Zimmer, K.J., 2006. A classification of the bird species of South America. American Ornithologists’ Union. http://www.museum.lsu.edu/~Remsen/ SACCBaseline.html.
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