Initiating a Wetland Inventory in the Ecoregion Puna of Peru

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Initiating A Wetland Inventory In The Ecoregion Puna Of Peru

Laura Wascher

Bachelor Thesis November 2010

Chair Of Climatology

Department Of Ecology

Technische Universität Berlin Bachelor Thesis

Declaration

With this statement I declare, that I have independently completed this bachelor thesis and only used literature cited in the included reference list.

Erklärung

Die selbständige und eigenhändige Anfertigung versichert an Eides statt

Reykjavik, den 30.11.2010 Title: Initiating a Wetland Inventory in the Ecoregion Puna of Peru

Author: Laura Wascher

Matriculation Number: 312441

Degree: B.Sc. Bachelor of Science

Credit Points: 11

Study Fields: Environmental Planning, Ecology and Landscape Archt.

Submitted to: Chair Of Climatology, Department Of Ecology, TU Berlin

First Examiner: Prof. Dr. Dieter Scherer, Chair of Climatology

Second Examiner: Dr. Jochen Richters, Ingenieurbüro Lohmeyer

Supervisor: Dipl.-Ing. Marco Otto, Chair of Climatology

Acknowledgements

I would like to express my gratitude to the following individuals for various encouragement.

M. Otto TU Berlin

C. Indolfo IAI

N.E. Lindh UMU

E. Wascher GETIDOS

U. Wascher A8 Print Abstract

This study concentrates on examining peatlands that exist above the timber line in the high Andes of Peru. The investigation focuses on the extent of the Puna ecoregion as dened by the WWF. More precisely referred to as high altitude wetlands HAW, they provide the means of existence for endemic and threatened plant and animal species. Besides that they constitute the livelihood of the indigenous people in a rather desertlike environment. Considering the various anthropogenic and natural pressures on HAW, like overgrazing by livestock, mining activities and ongoing climate change, the ecosystems face loss and degradation. In addition, the Ramsar Convention has considered them as fragile ecosystems. To estimate the particular impacts and future development of HAW, the ecosystems need to be studied more thoroughly. Initiating a wetland inventory is accordingly the basis for further assessment and monitoring of HAW. Knowledge about the actual spatial distribution and other ecologic and management attributes is a necessity for all involved in research and management of HAW.

Zusammenfassung

Diese Studie konzentriert sich auf die Erhebung von Torfmooren, die oberhalb der Baumgrenze in den Hochanden von Peru existieren. Die Untersuchung fokussiert sich auf den Umfang der Ökoregion Puna, wie sie vom WWF deniert ist. Genauer bezeichnet als Hochandine Feucht- gebiete (High Altitude Wetlands - HAW ), bieten diese die Grundlage zur Existenz für endemische und gefährdete Tier- und Panzenarten. Auÿer- dem stellen sie in der wüstenähnlichen Umgebung die Lebensgrundlage für die einheimische Bevölkerung dar. In Anbetracht der diversen anthro- pogenen und natürlichen Belastungen, wie Überweidung durch Viehbe- stand, Bergbau und fortschreitenden Klimawandel, veschwinden HAW zunehmend und werden zerstört. Überdies hat die Ramsar-Konvention diese Ökosysteme als fragil eingestuft. Um die spezischen Auswirkun- gen und die zukünftige Entwicklung von HAW zu beurteilen, müssen die Ökosysteme gründlicher erforscht werden. Ein Inventar für Feuchtge- biete zu initiieren ist demnach die Basis für weiterführende Bewertung und Monitoring von HAW. Das Wissen über die tatsächliche räumliche Verteilung und andere ökologische sowie management Eigenschaften, ist eine Notwendigkeit für alle Beteiligten in Forschung und Management von HAW. List of Abbreviations

CAN The Andean Community of Nations

CAT The Andean Development Corporation

CBD Convention on Biological Diversity

CONDESAN The Consortium for Sustainable Development in the Andean Ecoregion

CREHO The Ramsar Regional Center for Training and Research on Wetlands in the Western Hemisphere

CRS coordinate reference system

DU Ducks Unlimited

GCFA High Andes Flamingo Conservation Group

GIS geographic information system

GRoWI Global Review of Wetland Resources and Priorities for Wetland Inventory

GTZ German Technical Cooperation

HAW high altitude wetlands

IAI The Ibero-American Institute

IUCN International Union for Conservation of Nature

IWRB International Waterfowl & Wetlands Research Bureau (now WI) m a.s.l. meters above sea level

MEA Millennium Ecosystem Assessment

MINAG Ministry of Agriculture Peru

MINAM Ministry of the Environment Peru

MINEM Ministry of Energy and Mines Peru

OSM ordnance survey map

RSIS Ramsar Sites Information Service

SINANPE National System of Protected Areas of Peru

UTM Universal Transverse Mercator coordinate system

WI Wetlands International

WWF World Wildlife Fund

WWT Wildfowl and Wetlands Trust Contents

Abstract 4

List of Abbreviations 5

Contents 6

1 Introduction 9 1.1 Background ...... 9 1.1.1 Ecoregion Puna ...... 10 Central Andean Wet Puna ...... 11 Central Andean Puna ...... 13 Central Andean Dry Puna ...... 14 1.1.2 High Altitude Wetlands ...... 15 1.2 Aim of the Study ...... 17

2 Methods 19 2.1 Research on Wetland Inventories ...... 19 2.1.1 State of the Art ...... 19 A Directory of Neotropical Wetlands ...... 20 The Ramsar List of Wetlands of International Importance 23 High Andean Wetlands Inventory ...... 25 HumedAndes Initiative ...... 26 2.1.2 Creating a Wetland Inventory Template for the Puna . 27 2.2 Examination of High Altitude Wetlands ...... 31 2.2.1 Delineation of the Investigation Area in Peru ...... 31 Detailed Scanning of OSM ...... 32 2.2.2 Map Analysis and Data Recording ...... 33

6 Contents

3 Results 37 3.1 Wetland Inventory ...... 37 3.1.1 Template for a Wetland Inventory of the Puna . . . . . 37 3.2 Investigation Area ...... 39 3.2.1 Spatial Distribution of HAW in Peru ...... 40 3.2.2 Inventory Core Data ...... 41

4 Discussion 43

5 Conclusion 47

List of Figures 49

Bibliography 51

A Methods 57 A.1 List of variables from A Directory of Neotropical Wetlands . . 58 A.2 List of information via RSIS ...... 60 A.3 Stakeholder and Use of HAW ...... 61 A.4 Overview of Topographical Maps IAI ...... 63

B Results 65 B.1 Data Description ...... 65 B.2 OSM Per dl2 1:100.000 Carta Nacional del Peru ...... 68 B.3 Record of HAW Data from Ordnance Survey Maps ...... 71

Chapter 1

Introduction

1.1 Background

The Millennium Ecosystem Assessment from 2005 stated that wetlands provide ecosystem services to a large extent that contribute not only to human well-being. However the current estimates of wetland cover worldwide is known to under-represent many wetland types, and further data are required for some geographic regions. In addition, it is known that more than 50% of specic wetland types in North America, Europe, Australia, and New Zealand were destroyed during the twentieth century, and many others in various parts of the world degraded [Mil05]. The ability of wetlands to adapt to changing conditions, and to more rapid rates of change, will be crucial to human well-being and wildlife everywhere as the full impact of climate change on our ecosystem will be perceived in the present and near future [Ram09]. This thesis concerns particularly wetlands, or more precisely peatlands in the ecoregion Puna in the Andes. In the past, fragmented and oversimplied perception of these fragile Andean ecosystems resulted in mismanagement [Sto92]. Regarding sustainable development of this area, water resources are the most critical issue. Without much doubt the most likely limiting factor for future activities is the availability of water [MGV97]. Many cities and villages in the rural area depend on wetlands due to the essential services of water supply, but these resources are not unlimited and foremost the basis of life for wild plant and animal species. Therefore it is of great importance to focus on preserving them, and restrict- ing the utilization in such a way that no critical threshold, which would result in irreversible destruction, is crossed [RCH08]. Furthermore, The dynamics

9 1. Introduction

of peatlands and their connection with water sources is not well understood [SWAE06, 246]. And according to Earle et. al [2003] it is little known about these peatlands, that are locally known as bofedales, concerning their temporal and spatial development and their relationship to climate. Therefore it is vitally important to increase the reliability of groundwork data for decision making.

1.1.1 Ecoregion Puna

The Andean mountains contain various types of ecoregions that were determined by the World Wildlife Fund in 2001. We dene ecoregions as relatively large units of land containing a distinct assemblage of natural communities and species, with boundaries that approximate the original extent of natural communities prior to major land-use change [ODWB01, 933]. In South America the ecoregions Paramo, Jalca and Puna contain bofedales which in this case are referred to as high altitude wetlands (HAW) [WWF06]. The focus of this study is the ecoregion Puna as displayed in gure 1.1.1 on the facing page. It is located roughly between 8° to 30° S and 65° to 78° W. Based primarily on precipitation and moisture trends it is subdivided into Central Andean Puna, Central Andean Wet Puna and Central Andean Dry Puna [SWAE06, ODWB01]. The Puna ecoregion ranges from about 3200 m a.s.l. up to 6600 m a.s.l., and it consists of cold and arid grassland surrounded by mountain peaks and glaciers [Bro83, SWAE06, WWF01b]. The Puna can be found in Peru, Bolivia, Chile and Argentina and is often correlated to the extent of the Altiplano, which is one of the highest plateaus in the world [Bro83]. Along its central portion (15°- 22° S), the widening of the Andes produces distinctive meteorological conditions that we refer to as the climate of the Altiplano [GVC03, p.6]. The climate is characterized by hyper-aridity, intense solar radiation, high-velocity winds, hypoxia, daily frost, and a short growing season. Nevertheless bofedales exist under these conditions near the hydrological and altitudinal limits for plant life [SWAE06].

10 1.1. Background

Figure 1.1.1: Map of the Puna ecoregions in the Andes (own illustration based on [ODWB01] 2010)

Central Andean Wet Puna

This ecoregion stretches from central Peru to the north of Bolivia adjacent to the eastern cordillera of the Andes. In the north it borders on another high elevation grassland typical for the Andes, the Paramo, which diers by having no seasonal change in precipitation and temperature as well as having a relatively higher humidity [WB87]. Commencing above the timber line between 3500 and 3700 m a.s.l. the wet Puna reaches up to 4200 m a.s.l. [SWAE06, WWF01c]. In the Peruvian part it is fragmented due to complex mountain ridges of the Andes, there the ecoregion only includes the higher elevations of low mountain ranges. It is mainly characterized by mountainous landscape, with snow capped peaks, mountain pastures, salt

11 1. Introduction

lakes, lakes, wetlands, plateaus and valleys. The highest peak of the region is the Nevado Huascaran with 6745 m a.s.l. in Peru. Furthermore it also contains one of the highest lakes in the world, Lake Titicaca, with an elevation of about 3800 m a.s.l. at the border of Peru and Bolivia [WWF01c]. The grassland and steppe vegetation is mostly composed by small shrubs and grass, like Festuca and Stipa (see 1.1.2), which expand throughout the whole Puna ecoregion [SWAE06]. The vegetation cover of 22% between 3000 and 4000 m a.s.l. is decreasing with increasing elevation [SWAE06]. According to Wilcox & Bryant [1987] the mean annual tem- Figure 1.1.2: Peruvian Feather perature in the Puna is less than 10° C Grass Stipa ichu in August, Cen- and frost during night is very common. tral Andean Dry Puna above 4200 The daily uctuations can be around 20 m a.s.l. [Ord07] K which can be described as winter during night and summer during day time [WB87, WWF01c]. Precipitation occurs mostly during the summer or wet season between October and April. The average annual precipitation in the wet Puna is about 500 - 700 mm [SWAE06].

12 1.1. Background

Central Andean Puna

In contrast to the wet Puna, the central Puna only has a precipitation of about 250 - 500 mm per year, which also occurs mostly during summer season [SWAE06]. Part of this ecororegion stretches along the south west of Peru and borders in the north of Chile on the dry Puna. Adjacent to this on the east, the central Puna extends rather fragmented from 16° S in the western part of Bolivia to 30° S in the northwest of Argentina [ibid.]. The altitudinal range lies between 3200 and 6600 m a.s.l., and it functions as a transition between the wet and the dry Puna [ibid]. It is known that the alpine ora of South Amer- ica is the most species-rich of all high mountain regions in the tropics, and it contains the greatest proportion of endemic species [CWCV10]. The vegetation of the central Puna mainly consists of bunch grass, herbs, moss and lichens [WWF01b]. As in all of the Puna ecoregion, the development of life is generally limited by the harsh conditions due to aridity, low oxygen and fre- quent frost. Plant species have adapted by various means such as reduced, felty, and rolled up leaves plus larger root-systems and growing close to the surface [WB87]. Mammals Figure 1.1.3: Vicuña Vicugna vicugna in the on the other side are able to Central Andean Dry Puna of Chile [VJC08] feed on the hardest plants, and withstand low temperatures and winds through special fur [WWF01b]. The most obvious mam- malian inhabitants are Andean camelids, including the vicuña (Vicugna vicugna), llama (Lama glama), guanaco (Lama guanacoe), and alpaca (Lama pacos) [SWAE06]. The vicuña as seen in 1.1.3, was once endangered and since 2008 it is in the lower risk category of the IUCN red list, which also states that its habitat, correlating with the extent of the Puna, is threatened and the population might decline again unless conservation actions are in place [LBVH04].

13 1. Introduction

Central Andean Dry Puna

According to the IUCN red list an endemic bird species, the Phoenicoparrus jamesi or Puna Flamingo (see 1.1.4), is currently a near threatened species. It's habitat almost completely matches the dimensions of the dry Puna, and the population trend is decreasing [Bir04]. As one of the three Andean amingo species it is part of the rich avifauna of the Puna [MGV97]. According to Squeo et. al [2006] the dry Puna covers the largest area of all three ecoregions. It reaches from about 17° to 27° S in the southwest of Bolivia, to the northeast of Ar- gentina and northern Chile, located precisely east of the Atacama desert, one of the most arid deserts in the world [SWAE06]. The dry Puna is distinguished by the other types of Puna as it almost lacks rainfall completely. The northern part is in the summer rain region, divided in the middle by the Arid Diagonal around 24° - 25° S the southern part lies in the winter rain region. The annual precipitation very seldomly exceeds Figure 1.1.4: Phoenicoparrus jamesi 250 mm, and occurs solely as snow Puna Flamingo at Laguna Cañapa [ibid.]. The landscape at the eleva- above 4000 m a.s.l., Potosi, Bolivia tion of 3500 to 5000 m a.s.l. is char- [IS06] acterized by snow-capped peaks, vol- canoes, salt ats, lagoons and high plateaus [WWF01a]. At high elevations over 4,000 m above sea level, the vegetation in cushion bogs or bofedales includes oating submerged cushion plants [WWF01a, p. 7]

14 1.1. Background

Figure 1.1.5: Bofedal Vado de Putana at 22° S 68° W in February, Chile [Pri08]

1.1.2 High Altitude Wetlands

The typical peatlands in the Puna exist between 3200 to nearly 5000 m a.s.l. in the northern part and above 2800 m a.s.l. in the southern part. They are called bofedales and hence more precisely referred to as high altitude wetlands (HAW), representing the main focus of investigation concerning the wetland inventory. As Buttolph and Coppock [2004] specify them, they are spongy wetlands found along watercourses and in valley bottoms. Moreover they are described as heterogeneous, short and dense grasslands, crisscrossed by shallow streamlets on permanently watersaturated soil (except during the dry season). Thus they are the only native pasture resources available around the year, including during the dry winter season [MLT03]. An example can be seen in 1.1.5, which shows a bofedal above 4200 m a.s.l. in the dry Puna of Chile. According to Earle et al. [2003] they appear as green oases in this rather desertlike landscape. Individual wetland systems extend from less than one hectare to several square kilometers [BC04]. The water sources include fresh and slightly saline groundwater originating from glacial streams, snowmelt and rain [SWAE06]. Bofedales occur naturally but they can also be the result of traditional irrigation practices, on order to expand pasture land [BC04]. Never- theless it is obvious that these fragile ecosystems are highly sensitive towards any articial water transfers with the danger of immediate and irreversible habitat destruction [MGV97]. The peatlands play a critical role in sustaining a unique diversity of rare and endemic biota in the Cordillera de los Andes [SWAE06, p. 246]. Indeed,

15 1. Introduction

mammal and bird species, some of them threatened, rely on the bofedales in terms of grazing, nesting and water. In addition Squeo et al. [2006] state that the communities of natives, like the Aymara and Atacameños, directly depend on the peatlands, as the region features conditions which almost pre- clude human habitation. Their domestic herds of llamas and alpacas graze on the peatlands, and represent the basis of indigenous economy, as agriculture is considered not viable at these elevations [SWAE06]. According to Browman [1983] pastoralism was practiced for thousands of years with relatively little negative impact on the ecological base, but within the current century there has been a serious breakdown of the pastoral system. Nowadays the wetlands are threatened by overgrazing, due to lack of information on their dynamics [MBGB03]. Furthermore many HAW are lost rapidly, because of inappro- priate management and again lack of knowledge concerning their economic and ecologic importance [RCH08]. In addition previous research from northern Chile asserted that wetlands are severely degrading and even vanishing [SWAE06]. Other studies stated that a rapid rate of peat accumulation was common amongst high elevation tropical peatleands of South America, and may not indicate great antiquity [CWCV10]. What is more Earle et al. [2003] detected Chilean peatlands to be unusually young, dynamic and sensitive to environmental changes, as well as rapidly accumulating peat and carbon at rates that had never been ascertained before. They also indicate that autor- regulation processes of internal hydrology foster the development of peatland, which might be correlated with degradation at one side, and growth on the other. However, evidently HAW are threatened by ongoing decrease in precipitation and other impacts of climate change, increase of human impact like mining activities, uncontrolled burning, unregulated tourism, introduction of invasive species, livestock overgrazing and rising water demand of agriculture and urbanization in the lowlands [SWAE06, RCH08, Ram02]. Thus, due to the high level of fragility which is related to the former named natural and anthropogenic causes, the Ramsar Convention1 has considered High Andean wetlands as fragile ecosystems [RCH08].

1 1 on page 19

16 1.2. Aim of the Study

1.2 Aim of the Study

This work aims to deliver a contribution to landscape planning in South Amer- ica with regard to sustainable resource management and environmental conservation in the Puna ecoregion. To increase the reliability for decision making in particular conservation planning, it is important to know more about the actual spatial distribution and other ecological and management properties of high altitude wetlands. Consequently the rst task is to construct a template for an ideal inventory with a focus on the ecoregion Puna. There already exist some sources containing sparse information about particular wetlands in the general area, but none of them presents a complete and eective inventory of HAW in the ecoregion Puna. Initiating the investigation of the area with the help of ordnance survey maps shall be one measure of contributing information to the inventory. Subsequently geographic information systems will be applied to display and analyze the spatial distribution of HAW found through map research. A proper inventory shall be an essential foundation for further research concerning the natural development of HAW with regard to climate change, loss and degradation of HAW and adequate long term management and conservation planning. The result should contribute to the superordinate project entitled "Analysis of vegetation changes in high Andean wetlands in southern Peru - based on remotely sensed data sets" which will be conducted by the Chair of Climatology.

Chapter 2

Methods

2.1 Research on Wetland Inventories

2.1.1 State of the Art

The Global Review of Wetland Resources and Priorities for Wetland Inventory GRoWI [1999] (which was undertaken by Wetlands International on behalf of the Ramsar Convention1) estimated wetland extent from national inventories as approximately 1.2 million square kilometers, which is according to the Millennium Ecosystem Assessment [2005] considerably higher than previous estimates derived from remotely sensed information. Nevertheless the GRoWI number is still considered underestimate, in particular for the Neotropics (especially South America) and for certain wetland types such as peatlands [Mil05, RFN09]. The MEA [2005] stated further that the extent of wetland mapping an inventory was inadequate, being incomplete and inconsistent in many instances. Furthermore the estimates of wetland loss and degradation globally are considered incomplete or based on unsubstantiated assertions [Fin99]. That is why it is of great concern to the Ramsar Conven- tion, which has also contributed majorly to the MEA, to promote globally the

1The Convention on Wetlands is an intergovernmental treaty adopted on 2 February 1971 in the Iranian city of Ramsar, on the southern shore of the Caspian Sea. Thus, though nowadays the name of the Convention is usually written "Convention on Wetlands (Ramsar, Iran, 1971)", it has come to be known popularly as the "Ramsar Convention". The Ramsar Convention on Wetlands was developed as a means to call international attention to the rate at which wetland habitats were disappearing, in part due to a lack of understanding of their important functions, values, goods and services. Governments that join the Convention are expressing their willingness to make a commitment to helping to reverse that history of wetland loss and degradation. [Ram09, online: http://tinyurl.com/255szw3]

19 2. Methods

need and availability of comprehensive information on the status and trends of wetlands, their values and major drivers of change [RFN09]. According to Finlayson [2002] knowledge is still required about the location, distribution and character of wetlands, plus their values and uses as being essential for eective management. Moreover this information is necessary for various geographical scales, ranging from local site management, through development of regional and national policies, to global priority setting through international conventions and agreements [Fin02]. For the purpose of this study, literature and data research was focused on nding information on previous inventories for the Puna region on national scales. In consideration of 2.2.1, the research was concentrated on Peru. As a variety of sources was consulted through li- brary and internet research, the main aspect was to nd the most current, reliable and accessible data sources. As mentioned in Rebelo et al. [2009] there are gaps in global wetland inventory, especially for South America and peatlands. Consequently this was proven by the data and information that was found during research, which mostly referred to one and the same source - being A Directory of Neotropical Wetlands by Derek A. Scott and Montserrat Carbonell from 1986. This and other related sources of information on wetland inventory in the general region will be presented in the following part.

A Directory of Neotropical Wetlands

Scott & Carbonell based the compilation of their inventory in the Neotropics on the determination of wetlands as dened by the text of the Ramsar Convention Article 1.1 wetlands are areas of marsh, fen, peatland or water, whether natural or articial, permanent or temporary, with water that is static or owing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six meters [Ram71]. One main goal of the inventory was to include the entire biogeographic region to have a basic framework for sound conservation action for wetlands and waterfowl [Nar95].They compiled information from various dierent sources, building up networks of representatives of all countries of the Neotropics. These were instructed and given an information sheet containing 16 dierent variables that should be lled in for every wetland recorded (see Appendix A.1 on page 58). In the end the total of 368 wetlands of about 120 739 000 ha were recorded for South America distributed among 12 countries. The altitudinal range illustrated that over 96% of wetlands where detected under 1000 m a.s.l., whilst 2,93 % and there-

20 2.1. Research on Wetland Inventories

Figure 2.1.1: Wetlands compiled by Scott and Carbonell that are in accordance with the extent of the Puna ecoregion [own illustration based on [SC86, ODWB01, p. 213] 2010]

fore 3 031 731 ha where recorded as being above 3000 m a.s.l [ibid.]. Naranjo [1995] nevertheless stated the inconsistencies in recording wetlands, given the many participants gathering the information (e.g. Bolivia recorded the entire Amazonian basin as one wetland). The discrepancies where also quite obvious given that Bolivia designated 18% of total area to coverage of wetlands, whilst Peru had even less than 2%. Despite these inconveniences, the IWRB inventory has been a milestone for wetland conservation eorts throughout the continent[Nar95, p. 127]. As illustrated in gure 2.1.1, Peru had a total of 48 wetlands in the Directory of Neotropical Wetlands. 27 of those wetlands could be determined within or very close to the ecoregion Puna of the high Andes, some of them where on the outer range with elevations around 3200 m a.s.l..

21 2. Methods

They are listed in the Directory, beginning from wetland number 14 Laguna Pelagatos and the Conchu- cos Lakes continuously to wetland number 40 Laguna de Loriscota. These wetlands where however recorded solely as lakes, admit- tedly sometimes annotated as having bogs in the vicinity, and in certain cases even referred to directly as being bofedales [SC86]. Figure 2.1.3: Laguna Sibinacocha above To give an example, Laguna Sib- 4800 m a.s.l. in the Central Andean Wet inacocha is a high Andean lake of Puna, Cusco, Peru unknown salinity in the region of Cusco. The rather sparse documentation in Scott & Carbonell (which is number 24 on the list of wetlands in Peru) is seen in 2.1.2. In addition as the picture 2.1.3 shows, it is located close to the mountain range cordillera de Vilcanota with descending glaciers, whose melt water obviously feeds the lake.

Figure 2.1.2: Record of wetland number 24 of Peru: Laguna Sibinacocha [SC86, p. 227]

22 2.1. Research on Wetland Inventories

Figure 2.1.4: Map created by the Web-GIS of RSIS showing Ramsar sites in Peru [accessed 15.11.2010 via Web-GIS RSIS http://ramsar.wetlands.org]

The Ramsar List of Wetlands of International Importance

According to their webpage [http://www.ramsar.org accessed 15.11.2010] the Ramsar convention has : 160 Contracting Parties 1904 sites designated for the List of Wetlands of International Importance 186,584,279 hectares total surface area of designated sites The mission of the Ramsar Convention is the conservation and wise use of all wetlands through local, regional and national actions and international cooperation, as a contribution towards achieving sustainable development throughout the world[Ram07, p. 2]. This source represents the most consistent and up-to- date global inventory of wetlands. Data about all 1904 wetlands is accessible online, through a searchable site database and Web-GIS application showing spatial information. It is called the Ramsar Sites Information Service (RSIS) http://ramsar.wetlands.org and it is maintained in cooperation with Wet- lands International. All important information collected about the wetlands are provided. It also oers downloadable GIS data, but not for all regions, resulting in one point per wetland giving the location being displayed in the Web-GIS. Relating again to part 2.2.1 on page 31, information about Peru was the main focus. The database oers information about 13 wetlands of international importance in Peru, with a surface area of 6 784 042 hectares

23 2. Methods

Figure 2.1.5: English summary description of Ramsar Site No. 1313 [accessed 15.11.2010 via RSIS http://ramsar.wetlands.org]

[Ram09]. In March 1992 the Convention came into force in Peru [ibid]. As the Ramsar List also states, it includes data from the dataset compiled by Scott and Carbonell [1986]. Therefore, as comparing the wetland sites provided by RSIS, they are mostly congruent. Nevertheless one new wetland could be found in the list via RSIS, which occurred within the ecoregion Puna. A summary description from the online database was available in English, and can be reviewed in gure 2.1.5. The Ramsar information sheet for this site is only available as a thirteen-pages document in Spanish. However, a list of the information that can be acquired through RSIS in general is found in Appendix A.2 on page 60. In total there are 4 Ramsar sites that correlate with the extent of the Puna: Bofedales y Laguna de Salinas, Lago Titicaca (Peruvian sector), Reserva Nacional de Junín and Laguna del Indio - Dique de los Españoles as displayed in gure 2.1.4 on the previous page. Furthermore in the Resolution VIII.39 - High Andean wetlands as strategic ecosystems the Conference of the Contracting Parties: URGES the Contracting Parties concerned to identify additional High Andean wetlands in their countries for inclusion in the List of Wetlands of International Importance[Ram02, p. 3].

24 2.1. Research on Wetland Inventories

High Andean Wetlands Inventory

The Regional Strategy for the Conservation and Sustainable Use of High An- dean Wetlands [2008] was composed within the Ramsar Convention framework, with the active participation of all countries which include High Andean wetlands and related areas [RCH08]. It is a result of the work of the Ramsar Regional Center for Training and Research on Wetlands in the Western Hemi- sphere (CREHO for its initials in Spanish) and the derived Contact Group on High Andean Wetlands. During a ten year period, from 2005-2015, this strategy is supposed to operate as a guiding framework for regional cooperation between the participating countries. Its purpose is the conservation and sustainable use of wetlands and wetland complexes in páramos, jalca, puna, and other High Andean ecosystems that include glaciers, lakes, lagoons, wet meadows, bofedales, mallines, highland vegas, salt pans and peatlands, rivers, water streams and other water bodies, dened as wetlands within the Ramsar Convention classication, including catchments, located at the Andean Range and other mountain systems in Latin America [RCH08, p. 9]. The strategy points out the ecological, economical, social and cultural importance of High Andean wetlands, as well as their ecosystem services and threats and pressures they are exposed to. Concerning the condition of wetlands the strategy refers to preliminary data received from a High Andean wetland inventory that was undertaken as a part of the High Andean Wetlands project2 by the Grupo Páramo and a network of organizations in the seven Andean countries and Costa Rica [RCH08]. It further states that the project has obtained a number of 2103 wetlands and 191 wetland complexes, corresponding to more than 58 basins in the entire region. Unfortunately, despite sound research, no further information about the actual range or data of the investigation could be acquired.

2[...] there are initiatives underway related to the High Andean ecosystems and their associated wetlands, such as those of the International Working Group on Páramos (Grupo Páramo) involving governmental and non-governmental organizations, research centers, and representatives of the private sector in the countries with páramos and other countries with similar ecosystems, as well as the High Andes Flamingos Conservation Group (GCFA), an initiative of Argentina, Bolivia, Chile and Peru made up of governmental institutions, non-governmental organizations, the private sector and universities of the four countries, which carry out joint activities that incorporate the relevant aspects for the conservation of amingos, within the framework of the Ramsar Convention and the Convention on Migratory Species [Ram02, p. 2].

25 2. Methods

HumedAndes Initiative

HumedAndes is an initiative for institutional coordination and cooperation on Andean wetland inventories, as stated in the Ramsar handbook for the wise use of wetlands [Ram07]. The initiative was created in 2003 in Colombia with the aim of carrying out and promoting inventories on Andean wetlands. Regarding standardization and availability it was planned to develop a framework for the inventory and ecological characterization of the wetlands in the Andean region. Of special importance in this undertaking was the identication and location of those wetlands that, because of their size, geographical location and state of conservation, have not been assigned the degree of importance they deserve as biodiversity refuges and safety nets for the local communities that depend on them [Ram07, p. 14]. Many institutions3 contributed with developing inventories of their respective regions, and adding to the framework, which was also built on methodologies recommended by the Ramsar Convention. The conceptual framework advanced by HumedAn- des has a hierarchical structure of ve levels that assist in the location of the wetlands within their geographical range and provide additional information to identify potential threats and causes of degradation: Ecoregions; Biogeo- graphical units for highland aquatic ecosystems; Catchments Areas; Wetland Site; and Habitat [Ram07, p. 14]. One example of the many contributions of individual wetland inventories, is the collaboration of several participants under the Páramo Internacional project (Ecuador). Main focus were Andean wetlands above 2000 m.a.s.l in Colombia. [...] a total of 2,398 high An- dean wetlands were recorded using the available literature, 86% of them with precise geographical coordinates. However, it is likely that many of these no longer exist [Ram07, p. 15]. Unfortunately, no other further source of information or data regarding these inventory projects could be acquired.

As mentioned before, researching other sources (i.a. BirdLife International, WI, WWT, DU, IAI, GCFA, MINAM, SINANPE) brought no further result about wetland inventory in the Puna of Peru. Researching information online turned out to be either not accessible or detained by language barriers. Still it can be assumed that no major resource of information was neglected.

3Fundación Humedales, The Alexander von Humboldt Institute for Research on Biodi- versity and Biological Resources, the WWF- Colombia, Asociación Calidris, Fundación Fuer- achoga, the Environmental Studies School of Javeriana University, Fundación Ecotrópico, Fundación Ecopar[Ram07, p.14].

26 2.1. Research on Wetland Inventories

2.1.2 Creating a Wetland Inventory Template for the Puna

The Ramsar Convention has over the years built up a comprehensive collection of information material supporting the establishment and maintenance of wetland inventories worldwide. For the purpose of the initiation of a wetland inventory for the Puna, the diverse manuals and directives compiled by the Ramsar Convention where utilized. As seen below an important denition was itemized in the Ramsar handbook for the wise use of wetlands - Wetland Inventory [Ram07, p. 7].

Wetland inventory: The collection and/or collation of core information for wetland management, including the provision of an information base for specic assessment and monitoring activities.

Wetland assessment: The identication of the status of, and threats to, wetlands as a basis for the collection of more specic information through monitoring activities.

Wetland monitoring: Collection of specic information for management pur- poses in response to hypotheses derived from assessment activities, and the use of these monitoring results for implementing management. (Note that the collection of time-series information that is not hypothesis-driven from wetland assessment should be termed surveillance rather than monitoring, as outlined in Resolu- tion VI.1.)

Figure 2.1.6: Overview of steps for planning an inventory dened in A Ramsar framework for wetland inventory [Fin02, p. 27]

27 2. Methods

As this work is concentrating on part one - the actual inventory - further information on how to build up an inventory could be obtained, which is illustrated in the overview 2.1.6 on the preceding page. Regarding this overview point one to ve shall be further considered, as they are the main focus of the initiation of an inventory in this thesis. As step one is already discussed in chapter 1.1 on page 9, pointing out peatlands of higher elevations (HAW) to be the main focus, it is however important to take a more detailed look on the actual utilization and users of HAW in the Puna. It is required to know the purpose and objection of an inventory, by identifying the habitat and considering for whom the information might be useful [Ram07]. Hence illustrated in Appendix A.3 on page 61, the stakeholders of dierent levels are displayed, plus specications about HAW as a resource: The combination of wetland functions, products and attributes give the wetland benets and values that make it important to society [FS99, p. 5]. The stakeholders are collated to the civil society, the public sector and the private sector. The center states the subject/aim of this compilation of stakeholders.

Figure 2.1.7: Hierarchical framework for wetland inventory [Fin02, p. 25]

28 2.1. Research on Wetland Inventories

In addition these are divided regarding their direct or indirect inuence on HAW, into key stakeholders (rst circle), primary (second circle) & sec- ondary stakeholders (outside of circle). This gives a comprehensive overview of users and the utilization of HAW, which will be taken into account for setting up the attributes of the inventory later. Step two has been covered by 2.1.1 on page 19, stating the restriction of the inventory to the extent of the ecoregion Puna plus bofedales and oering a review of the examined information sources. Step three will be covered by part 2.2.1 on page 31, which leaves step four and ve to be considerate closely at this point. According to the suggestion of A Ramsar framework for wetland inventory [2007], wetland aggregations in regions should be analyzed with maps of a scale between 1:250,000 and 1:50,000. The choice of scale is of course also linked to the size of the geographic region, the required accuracy and the availability of resources [Ram07]. Figure 2.1.7 on the preceding page depicts the connection between scale and the amount of core data stored for wetland units. Besides it shows the hierarchical and multi-scalar approach for mapping with the help of a GIS and appropriate imagery or other data [Fin02]. Taking into account all previous information, step ve has a focus on establishing a core data set for the inventory. Having considered many attribute lists for wetland inventories, the core data illustrated in gure 2.1.8 on the following page represent the most consistent and appropriate example. As this is the suggestion made by the Ramsar Convention it represents an adequate basis for a template of an inventory for HAW.

29 2. Methods

Figure 2.1.8: Core data elds for biophysical and management features of wetlands [Ram07, p. 11]

30 2.2. Examination of High Altitude Wetlands

2.2 Examination of High Altitude Wetlands

2.2.1 Delineation of the Investigation Area in Peru

The objective now was to nd accessible data that could be utilized to identify HAW and add the location plus various other properties to the inventory. Research within libraries and the internet resulted in a very limited amount of valuable resources. Hence, it was focused on map archives in Berlin, to acquire available resources of topographical maps. It was decided to take a closer look at the map archives of the Ibero-American-Institute, being the only utile source. Topographical maps for the investigation area were only accessible as analog ordnance survey maps, unfortunately no digitalized data was available. However certain core data features, as seen 2.1.8, can be obtained using this viable method to initiate an inventory. Checking through a list of all stored maps, the various countries that include parts of the puna ecoregion where examined (see the list in Appendix A.4 on page 63). The aim was to nd the most complete set of topographical maps, with the appropriate scale. Thoroughly scanning through all map compilations in A.4, Peru was chosen primarily to be investigated in more detail. The topographical maps of Per dl 2 were the most appropriate choice as almost all ordnance survey maps (OSM) of interest were available, and the scale of 1:100.000 tted the guidelines discussed earlier. The OSM clearly displayed pantano (bog, mire) respec- tively marsh or swamp in the map and legend. Moreover the elevation was indicated well-dened by contour lines. Thus HAW could easily be detected, which was not the case with maps at a scale of 1:250.000. Given the time limits Figure 2.2.1: Overview of OSM in Per and the estimated capacious amount dl 2 [obtained via [II10] 2010] of data envisaged, the investigation

31 2. Methods

was narrowed down to the two Puna ecoregions that occur in Peru. This was also a result based on previous research and data collection that had been taken place by the Chair of Climatology, which made the decision of investigating Peru more valuable for further research. An overview of all OSM in Per dl 2 could be obtained (see 2.2.1 on the preceding page), which was thereafter georeferenced and further processed in GIS. Overlaying the borders of the ecoregions and the overview of OSM resulted in a better determination of maps of interest. With the help of this display a clear distinction between the three dierent puna regions could be made, and it showed that Peru has vast areas of the Central Andean Puna and the Cen- tral Andean Wet Puna, not including the Central Andean Dry Puna. Further request concerning the actual sources of data (aerial photography) that was used to create the maps, did unfortunately not yield any result. Therefore it is not sure whether the mapping was based on pictures form the summer or the winter season, leaving it unclear if the vegetation cover had reached its maximum or minimum extent.

Detailed Scanning of OSM

To get a general perception of the distribution of HAW around the Puna of Peru, all OSM that where completely within or on the border of the ecoregion where scanned. A list of the results can be found in Appendix B.2 on page 68. The system of designating OSM from the overview of Per dl 2 (letter plus number e.g. 23_i) was used to illustrate the result of overlaying the ecoregions and the ndings of the scanning process. Figure 2.2.2 on the facing page shows the OSM in central and south Peru that were investigated. 12 OSM were missing in the map archive, thus 109 OSM could be scanned. They were categorized regarding the occurrence of HAW, and in the case of striking features (such as glaciers, or mining activity), this information was registered in the list. Addi- tionally the code of the OSM, the year of production of the OSM and further annotations were recorded (see B.2 on page 68). On the illustration, gray elds suggest that no HAW were found in 15 OSM. The blue elds (22 OSM) indicate that there were many HAW found, which was dened by estimating 3/4 of the OSM where covered with HAW. Every OSM that had less than 3/4 covered with HAW was identied as few, which in total produced 72 green elds. The framed OSM in the illustration indicate the 17 OSM that were analyzed in more detail afterwards. The selection was based on the results of the scan-

32 2.2. Examination of High Altitude Wetlands

Figure 2.2.2: Overview Ordnance Survey Maps (OSM) Per dl 2 [own illustration based on [ODWB01] and gure A.4 [II10], 2010] ning process, choosing representatives for the wet and the central Puna, and OSM that comprised both Puna ecoregions. Moreover, further research aims were taken into account, resulting in OSM being chosen for north to south transects, and a larger case study area in the south (where ground truth data has already been collected in previous research).

2.2.2 Map Analysis and Data Recording

The selected 17 OSM where all analyzed in more detail, mapping HAW and collecting relevant data which was added to the initiated inventory list. The map legend named wetlands as marsh or swamp in the English version and pantano in the Spanish version indicated by this symbol . HAW could be determined by inspecting the contour lines, displaying the elevation. Ex- cept for one OSM (32-u), only HAW with the length of at least 1 km were recorded, as smaller ones are rather unstable and time and labor input were

33 2. Methods

limited. One exception was made for 32-u, as this area has been covered by previous research, it was tested to record all HAW, however this turned out to be too capacious given the amount of very small HAW. Moreover it proved more useful to form an own category to register if an HAW was surrounded by many small HAW (<1km length) within a radius of 5 km. First of all, each OSM provided a 1 km or 4 km grid of the respective UTM Zone, which made it possible to record the coordinates of the approximate center of each HAW. Consequently the exact easting and northing of the center coordinate could be recorded with the help of a ruler. Processing errors could have occurred during this procedure, such as recording transposed digits. The elevation of the center coordinate could be estimated using the contour lines. Additionally the approximate length and width was measured. This was not always very clearly distinguishable as the shape of HAW were rather heterogeneous - oval, stretched, following a river basin or even scattered and not denable. In certain cases the orientation could be determined, depending on the relevant shape of the HAW. The proximate waterbodies, mainly rivers, dry rivers, lakes and seldom glaciers, where identied. Sup- plementary the name of the relevant waterbody was recorded if possible. In case of striking features, such as roads, agricultural activity, mines, or in almost all cases detached houses in the vicinity, these were registered in the annotations. So called caminos de herradura livestock trails occurred prac- tically everywhere, and where therefore not mentioned extra in the annotations. A description of all data elds can be found in Appendix B.1 on page 65. Figure 2.2.3 on the next page shows an extract of OSM 30-x, with the 4 km grid for UTM Zone 19 (blue line) and the striking feature of a glacier, plus livestock trails (black lines) and detached houses (black cubes). Subsequently the now digitalized data, was imported to QuantumGIS (on Linux) for further processing. Unfortunately it was detected afterwards, that metadata is not editable and database support is still lacking in QuantumGIS. However HAW could be displayed as points in a shapele. Regarding the projection, one shapele for HAW in UTM Zone 18, and one for UTM Zone 19 had to be created in order to display the exact location of HAW. Overlaying and intersecting the ecoregions, country borders, the OSM investigated and the HAW shapeles permitted to determine exactly which HAW belonged to which ecoregion, how much area of wet Puna and central Puna was investigated and made error analysis possible (see 2.2.4 on page 36). Due to transposed

34 2.2. Examination of High Altitude Wetlands

Figure 2.2.3: Extract of OSM 30-x showing HAW around the Nevado Ñacaria, Apolobamba Cordillera, Puno, (blue UTM grid of 4 km) [own illustration via [II10] 2010]

digits, at least two HAW (32-t 17, 33-x 3) could not be displayed at the right location, i.e. they where left out from further considerations as it was not sure whether they actually lie outside or within either of the ecoregions. In addition ten other HAW were correctly found outside the ecoregion border, nevertheless mostly rather close and all above 3900 m a.s.l., which made it possible to guess fairly correct whether they belonged to wet or central Puna. Yet given the imprecision they were left without an entry in the attribute eld puna. Thus they were left out of further calculations, as these were referring precisely to the amount and size of HAW within the exact area of the ecoregions. Furthermore these calculations did not include HAW that did not meet the minimum length of 1 km, which was in total 15 HAW. Taking into account that 22 OSM of 109 were categorized as many and 72 as few, we have a ratio of roughly 1/3 . To estimate the average size of HAW in the whole ecoregion, random samples of OSM were taken. These were chosen nearly equally in both

35 2. Methods

ecoregions with the requirement of 2 many (30-x, 32-t) and 6 few (19-i, 24-m, 33-t, 33-u, 29-x, 31-u), keeping the ratio. The estimated amount of ecoregion area was obtained by intersection and union of the relevant OSM and ecoregion polygons as seen in 2.2.4. Therefore the approximate percentage share of HAW area of the total ecoregion in Peru could be estimated, and hence the percentage share of HAW area of the total area of Peru. To estimate the size of HAW in the two dierent Puna ecoregions, given the prerequisites mentioned earlier, the total amount of wp HAW (89) and of cp HAW (191) were applied.

Figure 2.2.4: Per dl 2 Overview with Intersection of OSM and Ecoregion - yellow highlighting some sample OSM [own illustration based on [II10, ODWB01] 2010]

36 Chapter 3

Results

3.1 Wetland Inventory

The Research on the State of the Art revealed rather few sources for information on wetlands, or particularly peatlands in the ecoregion Puna of Peru. The named sources referred to wetlands being mainly larger lakes, with additional lagoons, rivers etc. and sometime even associated with bogs. Therefore it was obvious that an inventory with the main focus on HAW was lacking.

3.1.1 Template for a Wetland Inventory of the Puna

The result of the literature research is a template for the wetland inventory of the ecoregion Puna. Several core data information and suggestions have been taken into account. As mentioned before, the main goal of an inventory is to collect data that is relevant for the management of a wetland. In Addition it should provide a basis for further assessement and monitoring acitivities. The recommendation is that sucient information should be collected in order to enable the major wetland habitats to be delineated and characterized for at least one point in time [Ram07]. The collection of the most relevant core data attributes for this purpose can be found in the list on the following page. The three main categories are general information, biophysical features and management features. They list the subcategories that were determined for a wetland inventory on the designated scale.

37 Core Data Attributes for a Wetland Inventory of the Puna Ecoregion

General Information Management features

• Site name (official name of site and catchment) • Current and former land utilization • Site number ◦ anthropogenic activities in the vicinity • Date of recording (local, and in the river basin) • Country, region, subregion, administrative region • Condition, trends and pressures on the wetland Biophysical features ◦ within the wetland and in the river basin

• Ecological region (cp - central, wp - wet, dp - dry) • Land tenure/ownership and administrative authority • Area and boundary ◦ for the wetland, and for critical parts of the river basin ◦ length, width, total size, range, number of separate units • Location • Conservation and management status of the wetland ◦ projection system, coordinates, elevation (max, min, average) ◦ national and/or international conservation status • Geomorphological setting ◦ including legal instruments and social or cultural traditions and ◦ linkage with water resources, landform, exposure, relief values that influence the management of the wetland • General description ◦ shape, cross-section and plan view • Ecosystem values and benefits (goods and services) • Climate derived from the wetland ◦ zone and major features (temperatures, precipitation) ◦ including products, functions and attributes (see Resolution VI.1) • Soil and, where possible, their services to human well-being ◦ structure and color, pH, depth, age, peat accumulation (see Resolutions VI.23 and VII.8) • Water Regime and Hydrology ◦ extent of flooding, surface water resource, connection to • Management plans and monitoring programs groundwater, surface stream, flow, reservoir size, ◦ land utilization and ecological changes ◦ salinity, pH, nutrients, metals ◦ in place and planned within the wetland • Fauna & Flora and in the river basin ◦ animal population and distribution, occurrence of livestock and (see Resolutions 5.7, VI.1, VII.17, and VIII.14) wild species, esp. endemic, threatened ◦ vegetation zones and structure, plant communities, species, esp. endemic, threatened 3.2. Investigation Area

3.2 Investigation Area

To sum up, the investigation area included the Central Andean Puna (~66 925,5 km²) and the Central Andean Wet Puna (~94 182,5 km²) of central and south Peru with a total size of ~161 108 km². All OSM with a scale of 1:100.000 included or bordering on this area were thouroughly scanned, and the result of this can be found in Appendix B.2 on page 68 with the data description in Appendix B.1 on page 65. One OSM has an estimated size of ~3000km², in conclusion 109 OSM and therefore the area of 327 000 km² has been investigated. Afterwards a more detailed investigation of 17 OSM added up to ~51 000 km².

Figure 3.2.1: 303 HAW recorded via map analysis [own illustration based on [ODWB01]2010 ]

39 3. Results

3.2.1 Spatial Distribution of HAW in Peru

Within these 51 000 km² the total amount of HAW found was 303 as displayed in gure 3.2.1 on the preceding page. As explained in 2.2.2 on page 33 23 of these were not included into calculations for various reasons. Hence 280 HAW were mapped correctly according to all prerequisites and could be used for calculations. 191 of them were determined in the Central Andean Puna, and 89 in the Central Andean Wet Puna. The area that was investigated in 2.2.2 on page 33 estimated as 51 000 km² could be divided into 19 421,7 km² of Central Andean Puna and 20 730,7 km² of Central Andean Wet Puna (neglecting the area outside of the ecoregion border). The amount of area investigated of each ecoregion can therefore be considered rather equal. Taking into account the 8 random sample OSM, the estimated average size of HAW in the ecoregion was 4,7 km². The ecoregion area of the sample OSM was 17 923,3 km². Consequently the estimated area covered by HAW was 3,25% of the sample OSM ecoregion area. Projecting this percentage on the total area of Peru (1 299 613.4 km²) the estimated area of HAW coverage would be roughly 0,4%. In addition, the average size of HAW was divided between the two Puna ecoregions, resulting in HAW of the wet Puna being 5,5 km² and the HAW of the central Puna being 5,2 km². Furthermore HAW occurred within the altitudinal range of 3800 m a.s.l. and 4900 m a.s.l., which is displayed in 3.2.2 on the next page.

40 3.2. Investigation Area

Figure 3.2.2: Detailed view of HAW elevation ranging from 3800 m a.s.l to 4900 m a.s.l., east of Lake Titicaca, Peru [own illustration based on [ODWB01] 2010] - plus shaded and colored SRTM elevation model [NASA/JPL/NIMA03]

3.2.2 Inventory Core Data

In addition to the coordinates of each HAW, a number of other attributes could be obtained via map analysis as described in 2.2.2 on page 33. In consideration of the template for wetland inventory for the Puna, the other attributes that were obtained included site number (osm code plus number of HAW), the ecoregion (cp or wp), area and boundary (length, width), location (coordinates, elevation), geomorphological setting (linkage with water resources), general description (shape), plus current and former land utilization (anthropogenic activities in the vicinity in annotations). The nal list with all information to the 303 HAW can be found in Ap- pendix B.3 on page 71 with a detailed data description in Appendix B.1 on page 65.

Chapter 4

Discussion

The estimated 0,4% extent of HAW in Peru challenges the estimation stated by Naranjo [1995] in the rst evaluation of the Directory of Neotropical wetlands [SC86]. There it was indicated that the estimated total amount of all wetlands was less than 2% of Peru's total area [Nar95]. Indeed the 0,4% can be considered rather underestimated, as there were many more HAW that have not been recorded due to their small size, however the amount was rather large and could contribute far more to the actual extent. Moreover it can be argued that HAW are probably the wetland type with the least expansion of all wetlands in Peru, as there are plenty of wetlands in the tropical areas, esp. under 1000 m a.s.l. that are provided with much more precipitation and longer vegetation periods, thus supposedly of greater dimensions. In addition, the average size of HAW in the wet Puna was slightly bigger than the average size of HAW of the central Puna. It can be argued that this could derive from the fact, that the annual precipitation is greater in the wet Puna, and average temperatures are assumed slightly higher. Therefore, the somewhat increased water availability and vegetation period provide the basis for a rather extended growth of HAW. Although, the dierence could simply be derived from diverse aerial photography as explained later in this part, which would render the dierence insignicant. However it is also an issue of the delineation of the ecoregion, as stated in 1.1.1 on page 11, 4200 m a.s.l. was dened as the upper limit of the wet Puna. Evidently, there is a contradiction with the results of the HAW map analysis, and the WWF ecoregion border. As the results show HAW were found in the wet Puna up to 4800 m a.s.l. (see 3.2.2 on page 41), so it is questionable, whether these HAW actually by denition belong to the

43 4. Discussion

central Puna instead of the wet Puna - implying the ecoregion determination by the WWF as rather rough, or the denitions concerning the upper limit as rather imprecise. Another point with the delineation of the ecoregion border is that there were 10 HAW recorded that could be determined outside of the ecoregion later on. As these were lying outside of the border within a range of a few hundred meters up to 13 km, all of them at elevations over 3900 m a.s.l., it is arguable, whether the border of the Puna ecoregion is rather imprecise on the regional level. Another option would be that these wetlands registered as pantano in the OSM are another type of wetland in fact assigned to one of the bordering ecoregions. On the north-eastern border of the Puna the adjacent ecoregion is dened as the Peruvian Yungas, which is tropical to subtropical moist forest at the eastern slopes of the Andes in Peru [WWF01d]. As the HAW found in that area had no special annotation to vast vegetation in the vicinity or alike, without any striking dierence to all proximate HAW inside the ecoregion border, it is questionable if they can be considered part of the Yungas. Nor does it seem evident that these HAW could be a form of agriculture, mistaken as pantano, although there are crops growing at these elevations like Quinoa, Bitter potato or the grain Cañihua that grow from 3800 up to 4300 m a.s.l. [Tap00]. It was rather obvious though that agricultural areas have been mapped precisely and have not been mistaken as swamps or marshes. The ecoregion on the south-western border is the Sechura desert with not more than 200 mm precipitation per year, rather similar to the Cen- tral Andean Dry Puna [WWF01e]. Thus HAW found in this proximity can rather surely be assumed to be HAW and not any other form of vegetation or wetland described as pantano in the OSM. As mentioned earlier, the exact date of the aerial photography that was used to create each individual OSM, could not be obtained. Thus it is speculative, whether the extent of wetland vegetation was at its peak after raining season, or at its low when the pantano were mapped. Meaning that the actual extent of the HAW during the dry winter season might be less, or the dimensions might be even greater for the time after the raining season. In addition most of the OSM were produced around 40 years ago. This makes them a rather ancient source, which is prof- itable when conducting change detection for wetlands over a longer period of time. However it can be assumed, just like in 2.1.1 on page 26, that many of the recorded wetlands might not exist anymore. This assumption can also be strengthened by taking a look at gure 3.2.2 on page 41, which shows cur-

44 rent populated areas and major highways. Already there it is visible, that many HAW are located close to highways and populated areas, and presum- ably much more infrastructural activity has inuenced many of the recorded HAW by today. It is evident that population growth and infrastructural activity have increased in the last decades. This development is also accompanied with growing needs, increased poverty and in many cases lack of sound planning [MGV97]. This of course promotes conict between all stakeholders and pressures the utilization of HAW. In fact, planning instruments, such as the environmental impact assessment (EIA) has been incorporated to the legisla- tion of all countries concerned. Though, in fact the implementation is weak and it is often merely reduced to an administrative formality [RCH08]. As mentioned in the annotations, some of the HAW were located very close to mining activities, and probably now expanded agricultural land, anticipating collateral increase in livestock grazing. It is to assess how signicant the anthropogenic impact is on each wetland, with regard to the additional impact by ongoing climate change, and the expected alteration of precipitation and glacier melting. Therefore the inventory as it is now, is a basis, for more research to be done. Utilizing satellite imagery remote sensing and ground truth data with ancillary data derived from OSM will improve classication of HAW in the Puna of Peru, and make it possible to detect and add more HAW to the inventory. Besides the biophysical core data elds of Area and boundary, Location, Geomorphological settings, General description and certain parts of Climate, Soil, Water regime and Fauna&Flora can be determined more precisely with remote sensing. Thus the inventory can become a more consistent baseline for further assessment and monitoring which can be supported by remote sensing and deliver reliable information. As mentioned earlier regarding assessment and monitoring, one important point is using multi-temporal data, which can be derived from subsequent OSM and remote sensing datasets, to assess the change in wetlands and their surroundings. It has been detected that wetlands have been accumulating peat and carbon at unprecedented rates just within the last 50 years, encouraging exceptional rapid development of peatland [EWA03]. Hence further research is needed to assess if peatlands are ancient ecosystems or if they can adapt to changed circumstances much faster than commonly believed. With data available from Landsat MSS (since 1972), AVHRR (since 1979) and Landsat TM (since 1982) repeat coverage of satellite remote sensing is possible to evaluate changes in the HAW [OB02].

Chapter 5

Conclusion

This work initiated the investigation of the larger area of the ecoregion Puna in Peru. By constructing a template for the wetland inventory of the Puna, data of 303 HAW was gathered. The spatial distribution of HAW was analyzed and ecological and management properties of each wetland were determined. Although there have been wetland inventory approaches in the general area, there has been none at this scale with the aim of collecting extensive data of the particular wetland type HAW in the Puna ecoregion. Depicting the estimated extent of this wetland type, arms the general underestimation and accentuates the overall need for more investigation of wetlands, particularly in Peru. Therefore it is proposed to apply remote sensing in order to extend the inventory, plus the successive steps of assessment and monitoring. Results could be implemented within existing organizations such as the HumedAndes initiative (see 2.1.1 on page 26) and it could contribute to the High Andean Wetlands Inventory (see 2.1.1 on page 25) mentioned earlier. In fact, further processing is necessary to produce scientically based proper management and conservation programs for the endemic and threatened species of animals and plants that depend on wetlands, which besides also ensure the livelihoods of indigenous people [SWAE06]. It is to emphasize that coordi- nated, exible and responsible participation of governments and non-government sectors, local communities, indigenous people, private and academic sector will promote wise use and conservation of the High Andean wetlands as a strategic ecosystem. Above all it is to consider that the local population and direct users of HAW should obtain economic benet from the utilized wetlands, since oth-

47 5. Conclusion

erwise it will be rather dicult to support wise use and preserve the wetlands [RCH08]. Thus sustainability should be fostered, such as by giving more attention to the support of the utilization of native crops and locally domesticated livestock, which has adapted to the specic and sometimes very harsh conditions of the assigned ecoregion [Tap00]. Eventually, the creation of new protected areas, would be a modest but e- cient measure for preserving these unique high elevation environments, which would provide water resources for the benet of both human development and nature conservation [MGV97].

48 List of Figures

1.1.1 Map of the Puna ecoregions in the Andes (own illustration based on [ODWB01] 2010) ...... 11 1.1.2 Peruvian Feather Grass Stipa ichu in August, Central Andean Dry Puna above 4200 m a.s.l., Bolivia (S 22.78564 W 67.84942), Or- denes, C., 2007: online on Wikimedia commons http://tinyurl.com/32gw8oo (accessed 10.11.2010) ...... 12 1.1.3 Vicuña Vicugna vicugna in July around 4200 m a.s.l., Central An- dean Dry Puna, Chile (S 23.73004 W 67.79526), V.,J.C., 2008: online on Wikimedia commons http://tinyurl.com/2ucqmhg (accessed 10.11.2010) ...... 13 1.1.4 Phoenicoparrus jamesi Puna Flamingo at Laguna Cañapa in De- cember above 4000 m a.s.l., Potosi, Bolivia (S 21.50870 W 68.01151), I.S., 2006: online on Wikimedia commons http://tinyurl.com/3y8crdt (accessed 10.11.2010) ...... 14 1.1.5 Bofedal Vado de Putana at 22° S 68° W in February above 4200 m a.s.l., Central Andean Dry Puna, Antofagasta, Chile (S 22.53587 W 68.03760), Prins, G., 2008: online on Wikimedia commons http://tinyurl.com/2uyakux (accessed 10.11.2010) ...... 15

2.1.1 Wetlands compiled by Scott and Carbonell that are in accordance with the extent of the Puna ecoregion [own illustration based on [SC86, ODWB01, p. 213] 2010] ...... 21 2.1.3 Laguna Sibinacocha in September above 4800 m a.s.l. in the Cen- tral Andean Wet Puna, Cusco, Peru (S 13.85671 W 71.02492), G., 2008: online on Wikimedia commons http://tiny.cc/gji6w (accessed 10.11.2010) ...... 22

49 List of Figures

2.1.2 Record of wetland number 24 of Peru: Laguna Sibinacocha [SC86, p. 227] ...... 22 2.1.4 Map created by the Web-GIS of RSIS showing Ramsar sites in Peru [accessed 15.11.2010 via Web-GIS RSIS http://ramsar.wetlands. org] ...... 23 2.1.5 English summary description of Ramsar Site No. 1313 [accessed 15.11.2010 via RSIS http://ramsar.wetlands.org] . . . 24 2.1.6 Overview of steps for planning an inventory dened in A Ramsar framework for wetland inventory [Fin02, p. 27] ...... 27 2.1.7 Hierarchical framework for wetland inventory [Fin02, p. 25] . . . . 28 2.1.8 Core data elds for biophysical and management features of wetlands [Ram07, p. 11] ...... 30 2.2.1 Overview of OSM in Per dl 2 [obtained via [II10] 2010] ...... 31 2.2.2 Overview Ordnance Survey Maps (OSM) Per dl 2 [own illustration based on [ODWB01] and gure A.4 [II10], 2010] ...... 33 2.2.3 Extract of OSM 30-x showing HAW around the Nevado Ñacaria, Apolobamba Cordillera, Puno, (blue UTM grid of 4 km) [own illustration via [II10] 2010] ...... 35 2.2.4 Per dl 2 Overview with Intersection of OSM and Ecoregion - yellow highlighting some sample OSM [own illustration based on [II10, ODWB01] 2010] ...... 36

3.2.1 303 HAW recorded via map analysis [own illustration based on [ODWB01]2010 ] ...... 39 3.2.2 Detailed view of HAW elevation ranging from 3800 m a.s.l to 4900 m a.s.l., Lake Titicaca, Peru [own illustration based on [ODWB01] and openstreetmap data peru.shapeles.zip obtained via http://tiny.cc/vdr8g 2010] - plus shaded and colored SRTM elevation model, NASA/JPL/NIMA, 2003: online http://tiny.cc/sbni7 (accessed 10.11.2010) ...... 41

50 Bibliography

[BC04] Buttolph, L.P. ; Coppock, D.L.: Inuence of deferred grazing on vegetation dynamics and livestock productivity in an Andean pastoral system. In: Journal of Applied Ecology 41 (2004), Nr. 4, S. 664674 15

[Bir04] BirdLifeInternational: Phoenicoparrus jamesi. In: IUCN 2010. IUCN Red List of Threatened Species. online. http: //tinyurl.com/385p22g. Version: 2010.4. 14

[Bro83] Browman, D. L.: Andean Arid Land Pastoralism and Develop- ment. In: Mountain Research and Development 3 (1983), Aug, Nr. 3, S. 241 252 10

[CWCV10] Cooper, D. J. ; Wolf, E. C. ; Colson, C. ; Vering, W.: Alpine Peatlands of the Andes, Cajamarca, Peru. In: ARCTIC ANTARCTIC AND ALPINE RESEARCH 42 (2010), feb, Nr. 1, S. 1933. ISSN 15230430 13, 16

[EWA03] Earle, L. R. ; Warner, B. G. ; Aravena, R.: Rapid development of an unusual peat-accumulating ecosystem in the Chilean Altiplano. In: Quaternary Research 59 (2003), Januar, Nr. 1, S. 211 45

[Fin99] Finlayson, C.M. ; Spiers, A.G. (Hrsg.): Global review of wetland resources and priorities for wetland inventory. Bd. Wet- lands International Publication 53. Supervising Scientist Re- port 144 / Wetlands International Publication 53, 1999. 524 S. http://tinyurl.com/23yaehe 19

[Fin02] Finlayson, C.M.: Integrated Inventory, Assessment and Moni- toring of Tropical Wetlands Conference on Environmental Moni-

51 Bibliography

toring of Tropical and Subtropical Wetlands. Maun, Botswana, 4-6 December 2002., GLOBAL WETLAND CONSORTIUM (GWC), 2002 20, 27, 28, 29, 50

[FS99] Kapitel 1 An introduction to wetland management Information needs for wetland management. In: Finlayson, C.M. ; Spiers, A.G.: A compendium of information for managing nd monitoring wetlands in tropical Australia. 1999, S. 17 28

[GVC03] Garreaud, R. ; Vuille, M. ; Clement, A. C.: The climate of the Altiplano: observed current conditions and mechanisms of past changes. In: Palaeogeography Palaeoclimatology Palaeoecology 194 (2003), Mai, Nr. 1-3, S. 522 10

[II10] IAI ; Indolfo, C.: Map Collection- The Ibero-American Institute. http://tiny.cc/9q3yi. Version: 2010 31, 33, 35, 36, 50, 63

[LBVH04] Lichtenstein, G. ; Baldi, R. ; Villalba, L. ; Hoces, D.: Vicugna vicugna. In: IUCN 2010. IUCN Red List of Threatened Species. online. http://tinyurl.com/36ocpnw. Version: 2010.4. 13

[MBGB03] Moreau, S. ; Bosseno, R. ; Gu, X. F. ; Baret, F.: Assessing the biomass dynamics of Andean bofedal and totora high-protein wetland grasses from NOAA/AVHRR. In: Remote Sensing Of Environment 85 (2003), Juni, Nr. 4, S. 516529 16

[MGV97] Messerli, B. ; Grosjean, M. ; Vuille, M.: Water Availability, Protected Areas, and Natural Resources in the Andean Desert Altiplano. In: Mountain Research and Development 17 (1997), S. 229238.. Managing Fragile Ecosystems in the Andes 9, 14, 15, 45, 48

[Mil05] MillenniumEcosystemAssessment: Ecosystems and Human Well-being: Wetlands and Water Synthesis. World Resources In- stitute, Washington, DC., 2005 9, 19

[MLT03] Moreau, Sophie ; Le Toan, Thuy: Biomass quantication of Andean wetland forages using ERS satellite SAR data for optimiz- ing livestock management. In: Remote Sensing of Environment 84 (2003), April, Nr. 4, S. 477492. ISSN 00344257 15

52 Bibliography

[Nar95] Naranjo, L.G.: An evaluation of the rst inventory of South American wetlands. In: Vegetatio (1995) 20, 21, 43, 58

[OB02] Ozesmi, S. L. ; Bauer, M.E.: Satellite remote sensing of wetlands. In: Wetlands Ecology and Management 10 (2002), S. 22 45

[ODWB01] Olson, D. ; Dinerstein, E. ; Wikramanayake, E. ; Burgess, N.D.: Terrestrial Ecoregions of the World - A New Map of Life on Earth. In: BioScience 51 (2001), 6. http://tiny.cc/ieysz 10, 11, 21, 33, 36, 39, 41, 49, 50

[Ram71] RamsarConvention: Convention on Wetlands of International Importance especially as Waterfowl Habitat. online (accessed 05.11.2010). http://tinyurl.com/2excxs5. Version: 1971 (UN Treaty Series No. 14583.). As amended by the Paris Protocol, 3 December 1982, and Regina Amendments, 28 May 1987 20

[Ram02] RamsarConvention: Resolution VIII.39 High Andean wetlands as strategic ecosystems. In: Wetlands: water, life and culture - 8th Meeting of the Conference of the Contracting Parties to the Convention on Wetlands, 2002 16, 24, 25

[Ram07] RamsarConventionSecretariat ; Ramsar Convention (Hrsg.): Wetland inventory: A Ramsar framework for wetland inventory. Ramsar handbooks for the wise use of wetlands, 3rd edition, vol. 12. Ramsar Convention Secretariat, Gland, Switzer- land.: Ramsar Convention, 2007 23, 26, 27, 28, 29, 30, 37, 50

[Ram09] RamsarConvention: Ramsar FAQs - Why conserve wetlands? Why an intergovernmental convention on wetlands? What is the Ramsar Convention on Wetlands? and The Annotated Ramsar List: Peru. online (accessed 10.11.2010). http://tinyurl.com/ 255szw3. Version: 2009. and http://tiny.cc/zv6zr 9, 19, 24

[RCH08] RCHAWSCG ; RamsarConvention, HAWS Contact- Group (Hrsg.): Regional Strategy for the Conservation and Sustainable Use of High Andean Wetlands. Ramsar Conven- tion, Governments of Ecuador and Chile, CONDESAN and

53 Bibliography

TNC-Chile., 2008 http://tinyurl.com/32qjwl6 9, 16, 25, 45, 48

[RFN09] Rebelo, L.-M. ; Finlayson, C.M. ; Nagabhatla, N.: Re- mote sensing and GIS for wetland inventory, mapping and change analysis. In: Journal of Environmental Management 90 (2009) 2144e2153 (2009) 19, 20

[SC86] Scott, DA ; Carbonell, M.: A Directory of Neotropical Wet- lands. 1986 http://tiny.cc/zwztw 21, 22, 43, 49, 50

[Sto92] Stone, P.B.: The state of the worlds mountains - a global report. Bd. XX. Zed Books, 1992. 391 S. 9

[SWAE06] Squeo, F. A. ; Warner, B. G. ; Aravena, R. ; Espinoza, D.: Bofedales- high altitude peatlands of the central Andes. In: Revista Chilena de Historia Natural 79(2) (2006), Jun, S. 245255 10, 11, 12, 13, 14, 15, 16, 47

[Tap00] Tapia, Mario E.: Mountain Agrobiodiversity in Peru - Seed Fairs, Seed Banks, and Mountain-to-Mountain Exchange. In: Mountain Research and Development 20(3):220-225. 2000 (2000) 44, 48

[WB87] Wilcox, B. P. ; Bryant, F. C.: An evaluation of range conditions in the Andes of central Peru. In: Journal of Range Management (1987), S. 41 45 11, 12, 13

[WWF01a] WWF: Ecoregions - Central Andean dry puna (NT1001). online (accessed 15.11.2010). http://tinyurl.com/2wl9fq4. Version: 2001 14

[WWF01b] WWF: Ecoregions - Central Andean puna (NT1002). online (accessed 15.11.2010). http://tinyurl.com/38v8pjf. Version: 2001 10, 13

[WWF01c] WWF: Ecoregions - Central Andean wet puna (NT1003). online (accessed 15.11.2010). http://tinyurl.com/33svexu. Version: 2001 11, 12

[WWF01d] WWF: Ecoregions - Peruvian Yungas (NT0153). online (accessed 15.11.2010). http://tiny.cc/d5tvh. Version: 2001 44

54 Bibliography

[WWF01e] WWF: Ecoregions - Sechura desert (NT1315). online (accessed 15.11.2010). http://tiny.cc/3bmc2. Version: 2001 44

[WWF06] WWF: High Andean Wetlands Regional Strategy. World Wildlife Fund Peru, 2006. 20 S. http://tinyurl.com/36xbkqj 10

[Zim09] Zimmermann, A. ; GTZ Deutsche Gesellschaft für Tech- nische Zusammenarbeit (Hrsg.): Instrumente zur Akteurs- Analyse 10 Bausteine für die partizipative Gestaltung von Koop- erationsystemen. Aus der Reihe: Förderung partizipativer En- twicklung in der deutschen Entwicklungszusammenarbeit. GTZ Deutsche Gesellschaft für Technische Zusammenarbeit, 2009 61

Appendix A

Methods

57 A. Methods

A.1 List of variables from A Directory of Neotropical Wetlands

Data sheet of Scott & Carbonell 1986 [Nar95, p. 129]

58 A.1. List of variables from A Directory of Neotropical Wetlands

59 A. Methods

A.2 List of information via RSIS

[http://ramsar.wetlands.org accessed 15.11.2010]

60 A.3. Stakeholder and Use of HAW

A.3 Stakeholder and Use of HAW

This stakeholder map is inspired by the visualisation of the manual Main- streaming Participation - Stakeholder Analysis by GTZ [Zim09, p. 15].

61 IUCN (International Union for Conservation of Nature) Convention on Biological Diversity (CBD) Civil society Ramsar Convention CREHO (Ramsar Regional Center) WWT (Wildfowl and Wetlands Trust) WWF (World Wide Fund For Nature) DU (Ducks Unlimited) GCFA (High Andes Flamingo Conservation Group) CONDESAN (The Consortium for Sustainable Development in the Andean Ecoregion) Attributes of a HAW: WI (Wetlands International) - biological diversity BirdLife International communidad campesina - gemorphic features Governmental (indigenous people) - unique cultural & heritage features development aid communities (e.g. GTZ - German These have value either because Technical Cooperation) citizens they include certain uses or because SINANPE Conservation they are valued themselves. [FS99 p.5] (National System of Protected Areas of Peru) and Sustainable Use MINEM Wetland of Tourism (Ministry of Energy and Mines) Managers High Altitude Wetlands in Farmers the Ecoregion Puna Products generated by HAW: MINAG region Proprietors - water supply (Ministry of Agriculture) of Mines - fisheries municipalities - wildlife resources Landowners - forage resources MINAM - agricultural resources (Ministry of the Environment) central government Stockbreeders Fishers These products are generated by the interactions between the biological, chemical and physical The Andean Community of Nations (CAN) components of a wetland. [FS99 p.5] The Andean Development Corporation (CAF) Functions performed by HAW: - water storage - storm protection, flood mitigation, erosion control - groundwater recharge, groundwater discharge Public sector - retention of nutrients, sediments and pollutants - stabilisation of local climate conditions, esp. rainfall and temperature Private sector The functions are the result of the interactions between the biological, chemical and physical components of a wetland, such as soils, water, plants and animals. [FS99 p.5] A.4. Overview of Topographical Maps IAI

A.4 Overview of Topographical Maps IAI

This is a list of maps that where scanned at the IAI map archive [II10]. The complete list can be obtained via the IAI website [http://tiny.cc/9q3yi accessed 15.11.2010]

Appendix B

Results

B.1 Data Description

65 Description of HAW_UTM_19 and HAW_UTM_18 Data Sets

November 2010

File name: UTM_19_HAW.shp & HAW_UTM_18.shp (components *.shp, *.shx, *.qpj *.prj, *.dbf, *.csv)

File format: Quantum GIS Point Shapele (ESRI Shapele)

Data format:

HAW_UTM_19: 262 points, 14 columns in attribute table HAW_UTM_18: 41 points, 14 columns in attribute table

Coordinate Reference System:

HAW_UTM_19: WGS 84 / UTM Zone 19 S HAW_UTM_18: WGS 84 / UTM Zone 18 S

Extent: Peru, South America

Map Sources: Ordnance Survey Maps of Per dl 2 1:100.000 Carta Nacional del Peru (for detailed list of OSM+year see .xls or .pdf OSM Per dl2 1:100.000 Carta Nacional del Peru )

Source: 1968-1985, IGM J631 Primera Edicion / Institutio Geograco Militar, Lima-Peru. 1971 pro metodo esteeofotogrametrico (A-8, B-8) De Fotograas Areas tomadas en 1955 control horizontal y vertical por el IGM en colaboracion con el IAGS clasicacion de campo 1964- 1967 escala de compliacion 1:25,000 Source: 1992 1999 J631 Edition 1-IGN / compiled in 1993 by stereophotogrammetric methods from aerial photography taken in 1976, 1989 and 1991. eld classication in 1993. map not eld checked Source: 1992 J632 Edition 1-DMA / Prepared and published by the Defense Mapping Agency Hy- drographic/Topographic Center, Bethesda, MD

File contents: Each point is characterized by a set of attributes as listed on the following page:

1 Column Description

osm code designated code for every ordnance survey map, consisting of a number and a letter nr of HAW series of numbers of high altitude wetlands that were found in one OSM easting coordinate for the eastward-measured distance (x-coordinate) of the approx. center of HAW northing coordinate for the northward-measured distance (y-coordinate) of the approx. center of HAW elevation elevation in m a.s.l. of the approx. center of HAW puna wp, cp indicates which puna ecoregion (wet puna, central puna) the HAW is part of shape oval, stretched, round, scattered, river basin, undened description of shape of HAW length measured length of HAW in km width measured width of HAW in km orient orientation of the HAW depending on shape (e.g stretched > north - south) waterbody river, dry river, lake, glacier identication of waterbodies close to HAW name water name of the relevant waterbody close to HAW (Q.=Quebrada L.=Laguna, R.=Rio) small HAW x indicates that smaller HAW (<1km²) exist in a radius of 5 km to HAW annotation indicates anthropogenic activity in the vicinity, by the following shortcuts

a armado = road, with two or more lanes (unpaved) b bosque= woodland ca casa aislada = detached buildings/houses f trocha ferrocarriles = railroad track h hacienda = estate m mina = mine n nevado = glacier t transitable en tiempo seco = road, loose surface tc terreno cultivado = cultivated land tel linea telegraca = telegraph line caminos de herradura = livestock trails (occur everywhere)

2 B. Results

B.2 OSM Per dl2 1:100.000 Carta Nacional del Peru

68 Ordnance Survey Maps Per dl2 1:100.000 Carta Nacional del Peru 1/2

OSM Year HAW Occurrence #HAW Name Puna annotations 18-g 1971 none 17-h 1971 few (tc) 18-h 1972 few (nevado, tc) 19-h 1982 few (nevado, tc) 20-h 1971 few (tc) 21-h 1971 none 18-i 1972 few (tc) outside of ecoregions border 19-i 1978 few (nevado, tc) 9 Huari wp 20-i 1976 many (nevado,t, mina) 21-i 1971 few (tc) 22-i 1969 few (tc) 19-j 1974 few (<20, tc) 20-j 1973 few (tc) 21-j 1971 few (nevado, tc) 22-j 1969 few (nevado, tc, mina!) 23-j 1968 few (tc, mina) 24-j 1973 few (5, tc) 20-k 1985 few (10, tc) 21-k 1969 few (tc) 22-k 1969 few (tc) 23-k 1968 many (nevado) 24-k 1973 few (nevado, tc, mina) 25-k 1972 few (tc) 21-l 1984 none 22-l 1975 few (tc) 23-l 1972 few (tc) 24-l 1972 few (nevado, tc) 25-l 1973 few (nevado, tc) 26-l 1973 few (nevado, tc) 27-l 1972 Few (4, tc) 23-m 1999 none (missing in legend) „marsh or svamp – none“ 24-m 1972 few (nevado, tc) 16 Jauja wp 25-m 1972 few (tc) 26-m 1973 many (tc) 27-m 1973 few 28-m 1971 few 24-n 1999 none (missing in legend) „marsh or svamp – none“ 26-n 1973 few (tc) 27-n 1972 many (tc) 28-n 1971 few 29-n 1968 few 30-n 1971 none 27-ñ 1970 few (tc) 28-ñ 1970 few (tc) 29-ñ 1969 few 30-ñ 1970 few (tc) 28-o 1970 few (tc) 29-o 1969 few (tc) 30-o 1998 many (tc) 26-p 27-p 28-p 1972 few (tc) 29-p 1973 few (tc) 30-p 1983 few (tc) 31-p 1968 few (tc) 26-q 1995 none (missing in legend) „marsh or svamp – none“ 27-q 2000 none (missing in legend) „marsh or svamp – none“ 28-q 1979 few (tc) 29-q 1973 many (tc) 16 Antabamba cp, wp 30-q 1973 many 31-q 1968 few (nevado, tc) Ordnance Survey Maps Per dl2 1:100.000 Carta Nacional del Peru 2/2

OSM Year HAW Occurrence #HAW Name Puna annotations 32-q 1968 few (nevado) 26-r 1999 none (missing in legend) „marsh or svamp – none“ 27-r 2000 none (missing in legend) „marsh or svamp – none“ 28-r 1977 few (tc) zona sin recubrimiento aerofotografico 29-r 1973 few (tc) 30-r 1973 many (nevados) 31-r 1968 few (nevados) 32-r 1967 few 26-s 1996 none 27-s 1977 few (tc) 28-s 1974 few (tc) Cuzco 29-s 1971 few (tc) 30-s 1969 many (tc) 31-s 1968 many (nevado) 32-s 1966 few (nevado, tc) Chivay 33-s 1966 none 27-t 28-t 1974 few (nevado, tc) 29-t 1971 few (nevado, tc, mina) 30-t 1969 few (tc) 31-t 1968 many 31 Condoroma cp, wp (1) 32-t 1966 many 29 Callalli cp 33-t 1966 few (nevado) 10 Characato cp Arequipa 34-t 1962 few (4) 27-u 1999 none 28-u 1984 few (nevado, tc) 29-u 1975 many (nevado, tc) 30-u 1973 many (nevado, tc) 31-u 1992 few (nevado) 37 Ocuviri cp, wp 32-u 1964 many 50 Lagunillas cp ½ of map recorded all HAW even under 1km² 33-u 1964 few 17 Ichuña cp Volcan Ubinas 34-u 1964 few (nevado) 35-u 28-v 1985 few (nevado) 29-v 1975 many (nevado, mina) 30-v 1992 many 31-v 1966 few (tc) 8 Juliaca wp Lampa 32-v 1965 few (tc) 12 Puno cp, wp Puno 33-v 1956 many (nevado) 25 Pichacane cp, wp 34-v 1964 many (nevado) 35-v 1961 few (nevado, mina) 28-x 1999 none 29-x 1977 few (tc) 8 Limbani wp 30-x 1972 many (nevado, tc) 18 Putina wp 31-x 1966 few (tc) 4 Huancane wp 32-x 1965 few (tc) 1 Acora wp 33-x 1965 many (tc) 12 Ilave cp, wp 34-x 1964 many 35-x 36-x 29-y 30-y 31-y 32-y 33-y 1992 no HAW found 34-y 35-y 33-z

Number of HAW in total: 303 B.3. Record of HAW Data from Ordnance Survey Maps

B.3 Record of HAW Data from Ordnance Survey Maps

71 1 Record of HAW Data from Ordnance Survey Maps

A B C D E F G H I J K L M N 1 osm code nr. of HAW easting northing elevation puna shape lenght width orientation waterbodies name waterbodies annotations smaller HAW around <5km 2 31_t 1 244150 8295000 4700 cp river basin 2.5 0.7 nw.se river. lake L. Smaccota Ca < 1km x 3 31_t 2 252320 8289000 4600 cp river basin. stretched 3.5 0.6 sw.ne river Q. Tacruma ca x 4 31_t 3 252230 8293040 4400 cp river basin. distorted 6 1 river R. Paranco t. ca 5 31_t 4 268100 8288000 4500 cp distorted 5 1 river Q. triguarata Ca. t < 1km x 6 31_t 5 272250 8294000 4600 cp river basin. distorted 7 1.5 river R.Canahuiri Ca. t < 1km x 7 31_t 6 276150 8293000 4600 cp river basin 2.5 1 lake. river L. Pane a. ca x 8 31_t 7 280250 8291050 4600 cp distorted 2.5 3 dry lakes Ca. t < 1km x 9 31_t 8 284000 8296000 4600 cp oval 5.5 2 river ca. t x 10 31_t 9 276100 8301000 4700 cp distorted 7 3 river Q. Rumihua a. ca x 11 31_t 10 268050 8297000 4800 cp distorted 4 1.5 dry river ca x 12 31_t 11 260200 8302000 4600 cp distorted 6 5 river dry river Q. Collpa Palca Mayo Ca x 13 31_t 12 244000 8304000 4500 cp river basin 3 1 river Q. Japocco Huaipo Ca x 14 31_t 13 280200 8304150 4700 cp distorted 8 2 river. lake Q. Sanuta Ca. t < 1km x 15 31_t 14 272000 8311000 4700 cp river basin 8 1.5 river R. Condorama a. ca < 1km x 16 31_t 15 260250 8311000 4800 cp oval 2 1 dry lake. river x 17 31_t 16 260150 8315000 4900 cp distorted 3 1 river Q. Marealla Ca < 1km x 18 31_t 17 252130 8320000 4500 cp oval 3 1 river Ca < 1km x 19 31_t 18 264050 8321000 4400 cp oval 2.5 1.2 river Q. Huayllumacahua x 20 31_t 19 256300 8326000 4500 cp river basin 3.5 0.7 river Q. Tambo Pata ca x 21 31_t 20 260100 8327000 4500 cp distorted 3.5 1.5 river Q. Ccaccarane Ca < 1km x 22 31_t 21 236230 8325050 4400 cp river basin 9 1 river Q. Chiluma Ca x 23 31_t 22 232200 8327000 4400 cp distorted 8 3 river R. Pirhuamayo ca x 24 31_t 23 240100 8331050 4500 cp river basin 6 1 sw. ne river R. Pirhuamayo Ca x 25 31_t 24 244150 8330000 4600 cp river basin 4 1 s.n river Q. Chuyu Pampamayo Ca < 1km x 26 31_t 25 276150 8329000 4200 cp river basin 5 0.7 s. nw river R. Chacamayoc t. ca x 27 31_t 26 276200 8331050 4200 cp oval 2 1 dry river t. ca < 1km x 28 31_t 27 276270 8335000 4200 cp river basin 4 0.7 se.nw river Q. Pucara Huayjo Ca x 29 31_t 28 280070 8331000 4200 cp river basin 4 1 river R. Jaruma t. ca x 30 31_t 29 284000 8329050 4200 cp distorted 4 2 dry river Ca x 31 31_t 30 280150 8333050 4200 cp river basin 5 0.7 nww.e river Q. Compuerta Ca x 32 31_t 31 284000 8339000 4300 wp distorted 5 2 river Ca x 33 32_t 1 235050 8233000 4600 cp river basin 6 0.7 s.n river. dry river Q. Calcha ca. t x 34 32_t 2 235050 8244000 4600 cp stretched 8 0.7 s.n dry river. nevado Nevado Calcha ca.t x 35 32_t 3 234000 8247000 4600 cp distorted 9 5 river. dry river R. Capillana ca. t. a x 36 32_t 4 240000 8248050 4400 cp distorted 9 1 river. dry river R. Capillana ca. t. a x 37 32_t 5 247050 8235050 4300 cp distorted 7 1 river ca. a (mina < 2km) 38 32_t 6 247050 8240050 4300 cp river basin 5 0.7 dry river Q. Sallaca ca. a x 39 32_t 7 267000 8234000 4400 cp distorted 5 2 river f. tel x

Record of HAW Data from Ordnance Survey Maps 1 2 Record of HAW Data from Ordnance Survey Maps

A B C D E F G H I J K L M N 1 osm code nr. of HAW easting northing elevation puna shape lenght width orientation waterbodies name waterbodies annotations smaller HAW around <5km 40 32_t 8 264000 8239020 4400 cp river basin 8 0.7 dry river Q. Rucarilla ca. f. tel x 41 32_t 9 271000 8238000 4600 cp river basin 5 0.7 s. nne river Q. Piscamayo ca x 42 32_t 10 281050 8236000 4400 cp stretched 5 0.7 s.n river R. Chuca a; ca < 1km x 43 32_t 11 280000 8240050 4400 cp river basin 6 1 dry river a. t ; ca < 1km x 44 32_t 12 280000 8246000 4400 cp oval 2 1.5 river R. Chili Ca < 1km x 45 32_t 13 275000 8251000 4400 cp oval 2 1 dry river ca. t. a < 1km x 46 32_t 14 284000 8252000 4400 cp distorted 4 1 dry river ca. tel. f < 1km x 47 32_t 15 281000 8256000 4400 cp distorted 6 5 river. lake R. Colca a. ca x 48 32_t 16 276000 8257050 4600 cp distorted 8 3 dry river ca x 49 32_t 17 236070 8357050 4600 river basin 2 0.7 dry river. lake L. Marecota ca x 50 32_t 18 244000 8262050 4300 cp distorted 4 2 river ca. a. t x 51 32_t 19 248000 8259000 4300 cp river basin 4 0.7 dry river Ca < 1km x 52 32_t 20 252050 8264000 4400 cp river basin. distorted 12 1 river. dry river R.Calhuanca ca. t x 53 32_t 21 236050 8272000 4400 cp stretched 3 0.7 dry river ca x 54 32_t 22 268000 8262020 4500 cp river basin 8 1 river R. Anchapara ca. t. mina x 55 32_t 23 243000 8282030 3900 cp river basin 3 0.7 river R. Llapa ca. t < 1 km x 56 32_t 24 278050 8265000 4400 cp oval 3 1 river Q. Yurac Cancha ca. t < 1km x 57 32_t 25 267000 8270050 4500 cp distorted 5 2 river R. Surage ca x 58 32_t 26 273000 8275000 4400 cp river basin 2.5 0.5 nw. se river Q. Junimata ca x 59 32_t 27 282050 8270050 4400 cp distorted 5 1 river R. Blanquillo t; ca < 1km x 60 32_t 28 281000 8276000 4400 cp distorted 3 1 dry river Q. Cajatambo ca. t x 61 32_t 29 285000 8282000 4500 cp oval 3 1 river Q. Pucacuncha Ca < 1km x 62 33_t 1 268220 8176350 4700 cp river basin. stretched 3 0.5 nw. se dry river. nevado x 63 33_t 2 280100 8176040 4600 cp distorted 3 0.8 river Rio Culine ca x 64 33_t 3 268300 8184200 4300 cp distorted. stretched 13 1.5 nww. see lake Laguna Salinas ca. t x 65 33_t 4 256270 8200300 4500 cp distorted 2 2 dry river Q. Chillihua Grande x 66 33_t 5 272000 8200350 4500 cp stretched 3 0.8 w.e river. dry river Rio Tari ca; t.a < 1km x 67 33_t 6 280130 8200280 4400 cp oval 2 0.6 river Rio Oco Grande ca. t.a < 1km x 68 33_t 7 264250 8208000 4100 cp stretched. river basin 4 0.3 s.n dry river Ca < 1km x 69 33_t 8 256330 8224050 4400 cp stretched. river basin 2 0.4 s.n dry river Q. Chapiocco x 70 33_t 9 280310 8220090 4200 cp oval 2 0.6 dry river t; ca < 1km 71 33_t 10 268050 8228000 4400 cp oval 2 0.6 river. dry river Rio Capimayo Ca < 1km x 72 31_u 1 300150 8286050 4600 cp oval 1.5 1 river x 73 31_u 2 318000 8288020 4500 cp oval 1.5 0.7 dry river Ca < 1km x 74 31_u 3 335070 8288060 4800 cp oval 1.2 0.7 x 75 31_u 4 287000 8297050 4700 cp oval 3 1 river ca. a x 76 31_u 5 291050 8294050 4800 cp river basin. distorted 3.5 2 river Ca x 77 31_u 6 303000 8296030 4900 cp river basin. distorted 3 1 dry river. river. lake Laguna Suito ca. a x

Record of HAW Data from Ordnance Survey Maps 2 3 Record of HAW Data from Ordnance Survey Maps

A B C D E F G H I J K L M N 1 osm code nr. of HAW easting northing elevation puna shape lenght width orientation waterbodies name waterbodies annotations smaller HAW around <5km 78 31_u 7 317050 8293000 4600 cp oval 1.5 0.7 river ca. a x 79 31_u 8 321020 8296070 4600 cp river basin 1.5 0.5 river. lake L. de Saitococha a x 80 31_u 9 331050 8296000 4600 cp oval 1.5 0.8 river a x 81 31_u 10 336030 8292030 4600 wp oval 1 0.6 river a x 82 31_u 11 286000 8301050 4700 cp round 1.5 1.5 river Ca < 1km x 83 31_u 12 299000 8303050 4800 cp stretched 2.5 0.5 s. n lake <1km L. Anata Ca < 1km x 84 31_u 13 307020 8300020 4800 cp oval 1.5 0.7 river a; ca < 1km x 85 31_u 14 306000 8305050 4700 cp river basin 3.5 1 river R. Pataquena a; ca < 1km x 86 31_u 15 312000 8299000 4600 cp river basin 2.5 1 river R. Quilisane a. ca < 1km x 87 31_u 16 315020 8306080 4900 cp round 1 1 nevado N. Quilca A < 1km 88 31_u 17 288000 8313000 4800 cp round 1.5 1.5 nevado Ca 89 31_u 18 292050 8312050 4700 cp river basin 3.5 1 river a; ca < 1km x 90 31_u 19 314050 8312000 4800 cp distorted 2 1.5 dry river. lakes a 91 31_u 20 336000 8318050 4600 wp round 1 1 river 92 31_u 21 290000 8318030 4800 cp round 1.5 1.5 river Ca < 1km 93 31_u 22 294000 8318000 4600 cp distorted 6 1.5 river a. ca 94 31_u 23 291050 8331000 4400 wp oval 2 1 lake L. Iniquilla a. ca x 95 31_u 24 300000 8323050 4500 cp distorted 4 1 dry river a. ca < 1km 96 31_u 25 306000 8320000 4900 cp oval 1.5 1 river Ca x 97 31_u 26 310080 8317080 4700 cp river basin 1.5 0.7 river. dry river Ca < 1km x 98 31_u 27 314050 8319050 4800 cp oval 2.5 1 river a 99 31_u 28 312050 8324050 4600 cp river basin 4 1 w.ne river Ca x 100 31_u 29 312070 8333000 4600 wp river basin 4 1 sw. nw river a x 101 31_u 30 314000 8335050 4700 wp oval 2.5 1 lake L. Challhuaneccocha A < 1km x 102 31_u 31 310050 8339000 4500 wp river basin 2 0.5 nw. se river a x 103 31_u 32 317040 8330000 4700 wp oval 2.5 1 ca. a x 104 31_u 33 318020 8333000 4600 wp oval 2 1 a x 105 31_u 34 319070 8337030 4500 wp oval 1.5 0.7 x 106 31_u 35 323050 8335050 4500 wp river basin 4 0.7 nw.se river x 107 31_u 36 334000 8332050 4500 wp oval 1.5 1 108 31_u 37 338000 8330000 4300 wp river basin 3.5 1 ne. sw river R. Sorapampa a x 109 32_u 1 296080 8232230 4600 cp stretched. river basin 2.5 0.5 w. ne river Q.Pucacancha Huaijo Ca < 1km 110 32_u 2 308100 8228140 4500 cp oval 1 0.6 river Ca < 1km 111 32_u 3 336120 8232030 4100 cp river basin 4 0.5 w.e river Q. Caballocota Ca < 1km 112 32_u 4 300390 8232040 4600 cp round 1 1 lake. river La. Coline ca 113 32_u 5 300220 8236000 4700 cp undefined 6 3 lakes. rivers La. Ajoyane Ca <2km 114 32_u 6 304100 8232160 4600 cp stretched. river basin 1.5 0.5 sw. ne river Rio Toledo Ca < 1km 115 32_u 7 304310 8232230 4600 cp round 0.5 0.5 river

Record of HAW Data from Ordnance Survey Maps 3 4 Record of HAW Data from Ordnance Survey Maps

A B C D E F G H I J K L M N 1 osm code nr. of HAW easting northing elevation puna shape lenght width orientation waterbodies name waterbodies annotations smaller HAW around <5km 116 32_u 8 332230 8232240 4100 cp river basin 0.7 0.3 river Rio Tarucani Ca < 2km 117 32_u 9 292160 8236200 4600 cp river basin 1 0.3 nww. see river Rio Colquiuta Ca < 1km 118 32_u 10 292330 8236150 4600 cp river basin 0.7 0.2 river Rio Colquiuta Ca < 1km 119 32_u 11 296120 8236290 4600 cp river basin 3 0.5 ssw.ne river Rio Colquiuta Ca < 1km 120 32_u 12 300080 8236340 4700 cp river basin 1.5 0.5 w.se dry river Rio Colquiuta Ca < 1km 121 32_u 13 300350 8236340 4800 cp oval 1 0.8 dry river. small glacier 122 32_u 14 304120 8236290 4600 cp oval 0.2 0.2 lake L. Ajuyani Ca < 2km 123 32_u 15 304220 8236380 4400 cp oval 0.5 2 river Rio Colloqueta ca 124 32_u 16 303090 8236110 4600 cp undefined 3 1 river. dry river Rio Colloqueta ca 125 32_u 17 308340 8236120 4200 cp undefined 3.5 2 river Toroya ca. t. h <1km 126 32_u 18 316000 8240140 4200 cp round 0.3 0.3 dry river Ca < 1km 127 32_u 19 316100 8240080 4300 cp round 0.2 0.2 dry river Ca < 1km 128 32_u 20 316290 8236320 4300 cp oval 0.4 0.2 dry river. river Q. Jollpa ca. t 129 32_u 21 316370 8236380 4400 cp river basin 0.9 0.2 river Q. Jollpa Ca < 1km 130 32_u 22 316330 8240050 4400 cp oval 0.5 0.2 river ca. t 131 32_u 23 316360 8240190 4500 cp round 0.2 0.2 t 132 32_u 24 320130 8236360 4400 cp oval 1 0.5 river Q. Jatunpuquio ca 133 32_u 25 320370 8236260 4400 cp round 0.2 0.2 dry river Q. Intipujo 134 32_u 26 320230 8236240 4400 cp river basin 2 0.5 sw.ne river Q. Limani Ca < 2km 135 32_u 27 332270 8236050 4100 cp river basin 1 0.5 n. s river Rio Tarucani ca 136 32_u 28 336150 8236030 4200 cp river basin 1.5 1.5 river Q. Quellocancha Ca < 2km 137 32_u 29 332200 8244000 4200 cp oval 1.5 1 lake Laguna Maquera a; h.ca < 2km 138 32_u 30 328290 8240240 4100 cp oval 1 0.4 river Rio Ojecancha t. ca 139 32_u 31 336100 8244010 4200 cp undefined 2.5 1.5 river Rio Sancayune a. ca <1km 140 32_u 32 292040 8244120 4700 cp undefined 8 1 river Q. Anashuata ca 141 32_u 33 296200 8240380 4700 cp oval 0.6 0.2 dry river Q. Mamaua Huachane 142 32_u 34 300190 8244060 4600 cp river basin 1.5 0.5 n.s river Q. Condore 143 32_u 35 328080 8248090 4200 cp undefined 6 5 rivers. lakes L. Huaicho ca. a x 144 32_u 36 332270 8244320 4200 cp oval 1 0.5 river ca 145 32_u 37 336150 8244040 4300 cp undefined 2.5 1.5 river Rio Sancayune a. ca <1km 146 32_u 38 292000 8252000 4500 cp undefined. river basin. scattere17 15 rivers Rio Chilamayo ca.t.h 147 32_u 39 300250 8248180 4400 cp river basin 1 0.5 sw.ne dry river Q. Huatalla Ca < 1km 148 32_u 40 304160 8248150 4300 cp river basin 2 0.5 sw.ne river Rio Acceuta Ca < 1km 149 32_u 41 304340 8248180 4300 cp oval 1 0.5 / t. ca < 1km 150 32_u 42 308250 8248230 4200 cp river basin 5 1 nw.se river Rio Tincopalca ca 151 32_u 43 316000 8248220 4200 cp undefined 5 1.5 river Q. Pasto Grande ca. t x 152 32_u 44 332170 8248120 4100 cp round 2 2 rivers Q. Palca ca x 153 32_u 45 336020 8248390 4400 cp river basin 3 0.5 ne.se river Q. Angostura Ca < 1km x

Record of HAW Data from Ordnance Survey Maps 4 5 Record of HAW Data from Ordnance Survey Maps

A B C D E F G H I J K L M N 1 osm code nr. of HAW easting northing elevation puna shape lenght width orientation waterbodies name waterbodies annotations smaller HAW around <5km 154 32_u 46 296100 8276000 4300 cp undefined. river basin. scattere10 3 rivers Rio Ichocollo Ca . t x 155 32_u 47 316120 8280100 4200 cp river basin 5 1 s. ne river Rio de Paratia Ca < 1km x 156 32_u 48 300370 8284000 4600 cp river basin 8 1 sw. se river. glacier Rio Jollpamayo ca x 157 32_u 49 284150 8280370 4300 cp oval 4 2.5 river Rio Aticata Ca < 1km x 158 32_u 50 308380 8264270 4200 cp river basin. undefined 5 2 river. lake L. Lagunillas. R. Lliccune ca; t <1km x 159 33_u 1 288280 8172370 4800 cp river basin 4 1 dry river. river Q. Saje x 160 33_u 2 320280 8176270 4000 river basin 9 3 river. dry river Rio Cocali ca; tc <1km 161 33_u 3 332180 8180270 4700 cp river basin 4 1.5 river Q. Jarajara x 162 33_u 4 292150 8184100 4500 cp river basin. distorted 5 3 dry river. river Q. Tambillo ca. t x 163 33_u 5 324100 8188100 4500 cp river basin. stretched 2 0.8 n.s river Q. Coteaca Ca < 1km x 164 33_u 6 336000 8192000 4700 cp river basin. stretched 3 0.8 nw. se river Ca < 1km x 165 33_u 7 328230 8192220 3900 cp river basin. stretched 9 0.6 s. ne river Rio de Curo Ca < 1km x 166 33_u 8 292000 8196150 4400 cp round 1.5 1.5 river Rio Chacalaque Ca < 1km x 167 33_u 9 300200 8196000 4200 cp river basin 4 1 river Rio del Para Ca < 1km. f x 168 33_u 10 332250 8204030 4800 cp distorted 2.5 2.5 rivers. lakes Rio Jayumayo x 169 33_u 11 284350 8204200 4200 cp oval 2 1.5 river Rio Cancusane ca. t x 170 33_u 12 300210 8204300 4700 cp distorted 2 1.5 dry river Ca < 1km x 171 33_u 13 288000 8216000 4200 cp oval 4 1.5 dry river Q. Yuracasa ca; t. a < 1km x 172 33_u 14 296000 8212250 4400 cp river basin. distorted 6 3 river Rio Chaclayo ca. t < 1km x 173 33_u 15 308000 8216030 4400 cp round 1.2 1.2 river Canal Ca < 1km x 174 33_u 16 296230 8220000 4600 cp distorted. river basin 9 1 river Q. Copecayoja x 175 33_u 17 304000 8228000 4700 cp river basin. distorted 3 2 river Q. Palca ca. a > 1km x 176 31_v 1 340150 8288060 4600 wp river basin 3 1 river Q. Sucuna ca x 177 31_v 2 352180 8295100 3800 wp oval 3 1 river Rio Pascorane ca. a x 178 31_v 3 348250 8304120 3800 wp oval 2.5 2 river. lake Rio Lampa ca.a .t . tc < 1km 179 31_v 4 340220 8316070 4300 wp distorted 2.5 1 dry river Rio Cachinane ca x 180 31_v 5 344150 8324080 3900 wp river basin 5 1 river Rio Colque ca. tc. t; b < 1km x 181 31_v 6 344200 8328170 3900 wp distorted 4 2 river. dry river Q. Ventilla ca; tc.b < 1km x 182 31_v 7 352100 8328120 3900 wp oval 2.5 1 dry river. river Rio Pucara ca. t. tc x 183 31_v 8 352300 8332300 3900 wp oval 2 1 river Rio Pucara ca; tc. a < 1km x 184 32_v 1 344000 8236250 4400 cp oval 3 1.5 dry river Q. Butlicacc ca; t< 1km x 185 32_v 2 348350 8232350 4500 cp river basin 2 1 river Q. Vilavilani Ca < 1km x 186 32_v 3 356170 8236220 4400 cp round 1.3 1.3 river Q. Pichu Ca < 1km x 187 32_v 4 376300 8240070 4200 wp oval 1.5 0.5 river Rio Sn Miguel Ca < 1km x 188 32_v 5 344000 8248150 4400 cp oval 1.5 0.6 dry river Ca < 1km x 189 32_v 6 372200 8248220 3900 wp distorted 3 3 river Rio Condorire ca. tc. t x 190 32_v 7 356150 8256240 3900 wp river basin. distorted 7 1 sw.ne river Rio Yanarico f. tc. ca. t. a x 191 32_v 8 360000 8256000 3800 wp river basin. distorted 8 2 sw.ne river Rio Cipache f. tc. ca. t. a x

Record of HAW Data from Ordnance Survey Maps 5 6 Record of HAW Data from Ordnance Survey Maps

A B C D E F G H I J K L M N 1 osm code nr. of HAW easting northing elevation puna shape lenght width orientation waterbodies name waterbodies annotations smaller HAW around <5km 192 32_v 9 364000 8252000 3900 wp river basin. distorted 8 1 s.n river Rio Vilque f. tc. ca. t. a x 193 32_v 10 344090 8256000 4400 cp river basin. stretched 2.5 0.5 ssw. nne dry river. lake Q. Coallaca ca.t < 1km x 194 32_v 11 344300 8260350 4200 cp distorted. 3.5 0.8 dry river. river Rio Tayataya ca; t < 1km x 195 32_v 12 352050 8280300 3900 wp round 1.3 1.3 dry river Q. Quishuarani ca. tc 196 33_v 1 349050 8177000 4400 cp distorted. river basin 6 1 river R. Callutane ca x 197 33_v 2 356000 8178000 4400 cp river basin 3.5 1 s. nw river R. Titire ca. a x 198 33_v 3 356000 8182000 4400 cp oval 2.5 1.5 river R. Titire ca. a < 1km x 199 33_v 4 380000 8178050 4400 cp oval 4 2 dry river. river R. Chapi ca x 200 33_v 5 392000 8177050 4200 cp river basin 5 1 river R. Blanco Ca < 1km x 201 33_v 6 372050 8183000 4500 cp oval 2 1 river Ca < 1km x 202 33_v 7 384000 8186050 4600 cp oval 2 1 river Q. Chojojote Ca < 1km x 203 33_v 8 372000 8188000 4400 cp distorted 2 1 river Q. Yiucollo Ca < 1km x 204 33_v 9 356000 8188000 4500 cp distorted 6 3 lake. river L. Asiruni ca. t. a x 205 33_v 10 347050 8192050 4400 cp distorted 3 1 river Q. Vizcalla ca x 206 33_v 11 359000 8192000 4600 cp distorted 3.5 2 river R. Jachouta Ca < 1km x 207 33_v 12 363000 8191000 4400 cp river basin 5 1 river ca x 208 33_v 13 362000 8195000 4600 cp river basin 5 1 river Q. Llaytapallane Ca < 1km x 209 33_v 14 369000 8197000 4500 cp distorted 7 3 river R. Pucara ca. t. a x 210 33_v 15 392000 8221000 4200 wp round 2 1.5 river R. Loripongo ca. t. a x 211 33_v 16 366000 8224000 4800 cp distorted 5 1.5 river R. Huancarane ca x 212 33_v 17 377000 8226050 4300 wp oval 2.5 1 river ca. mina < 2km x 213 33_v 18 358050 8201000 4800 cp distorted 5 3 river R. Huilacollco ca x 214 33_v 19 352000 8201050 4600 cp distorted 3.5 1.5 river R. Yanquiri ca x 215 33_v 20 353050 8208000 4600 cp distorted 4 2 river R. Liuchune x 216 33_v 21 356000 8211000 4800 cp distorted 4 1 river x 217 33_v 22 359000 8212000 4800 cp round 2 2 river R. Jancosire ca x 218 33_v 23 368000 8229000 4600 wp distorted 5 2 river . dry river Q. Cacahuarane Ca < 1km x 219 33_v 24 344000 8221050 4800 cp stretched 5 1 river. lake Ca < 1km x 220 33_v 25 344000 8229000 4800 cp distorted 4 2 river ca x 221 29_x 1 392340 8400200 4500 wp river basin 5 1 n/s river Rio Cullco ca x 222 29_x 2 424310 8400120 4600 wp strechted 4 1 no. sw lake laguna san bartolomä ca. tc< 4km x 223 29_x 3 416390 8404230 4600 wp oval 2.5 0.7 noo.sww dry river quebrado jollpa mayo a x 224 29_x 4 420300 8408230 4600 wp stretched 3 1 no. sw lake Laguna Chanjo Cocha N < 3km x 225 29_x 5 404200 8416020 4800 wp stretched 3 0.5 n. sw dry river ca x 226 29_x 6 404140 8420250 4800 wp river basin 3.5 1 nw.o river. lake Laguna Senja Cocha ca x 227 29_x 7 412105 8428310 4200 wp river basin 4 0.5 n.so river. Lakes Rio Cusqui ca. tc x 228 29_x 8 392350 8444100 4400 wp river basin 2.5 0.5 no. s dry river. lakes Quebrada Toltojere ca < 1km x 229 30_x 1 428000 8340250 3900 wp stretched 5 0.8 nww.o river ca. tc < 1km x

Record of HAW Data from Ordnance Survey Maps 6 7 Record of HAW Data from Ordnance Survey Maps

A B C D E F G H I J K L M N 1 osm code nr. of HAW easting northing elevation puna shape lenght width orientation waterbodies name waterbodies annotations smaller HAW around <5km 230 30_x 2 436220 8340380 4200 wp river basin 5 1.5 n.sw river Rio Humullo ca x 231 30_x 3 432130 8344040 4000 wp undefined. oval 6 3 river Rio Tisnahuyox ca. tc < 1km 232 30_x 4 440240 8352290 4400 wp undefined. oval 8 3 river. lake Laguna Pariacoto ca x 233 30_x 5 428140 8348240 4000 wp undefined. river basin 9 0.7 river Quebrada Quellouyo ca x 234 30_x 6 416320 8348300 3900 wp oval 2.5 1.7 river Rio Combuca ca tc < 1km. h.t x 235 30_x 7 432220 8360120 4200 wp river basin 3.5 2 river Quebrada Angosta ca x 236 30_x 8 432130 8356350 4300 wp oval 3 2.5 dry river ca x 237 30_x 9 408200 8356390 3900 wp oval 7 6 rivers Rio Tarucani ca. h.tc. t x 238 30_x 10 400300 8364000 3800 wp oval. undefined 6 6 rivers. lakes Rio Hilomayo. Rio Tarucani ca. tc ; t < 1km x 239 30_x 11 392230 8364340 4100 wp stretched 3 0.5 n. s lake. river Laguna Jearia a; ca.tc < 1km x 240 30_x 12 400050 8368080 3900 wp oval 2.3 1.7 river (canal) Acequia T < 1km x 241 30_x 13 420230 8368130 4400 wp river basin. stretched 8 0.5 n.s river Quebrada Yanaccacca ca x 242 30_x 14 436270 8376120 4500 wp river basin 3 0.5 nw.so river Rio Grande ca x 243 30_x 15 416180 8376180 4600 wp stretched. river basin 6.5 1 nw. so river. lake Laguna Chejuscocha ca x 244 30_x 16 440270 8380320 4600 wp river basin 4 0.7 no. sw glacier. river Nevado / Q. Nacaria Ca < 1km x 245 30_x 17 408220 8384030 4600 wp stretched 5 1 n. sw lake. river Laguna Ichuccota T < 1km x 246 30_x 18 428200 8388070 4400 wp oval 3 1.5 river Quebrada Nacaria ca x 247 31_x 1 432350 8324280 3800 wp oval 3 1 rivers. lake ca. tc; t <1km x 248 31_x 2 428300 8332100 3900 wp oval 2.5 2 dry lake ca; t. h. tc < 1km x 249 31_x 3 440270 8336310 4200 wp undefined. river basin 7 9 rivers Rio Ccarauta ca. tc. t x 250 31_x 4 428050 8336230 4000 wp river basin. undefined 9 4 rivers Rio Humullo ca. tc. t4 x 251 32_x 1 404040 8236020 4000 wp river basin 3.5 1.5 nw.s river Quebrada Lacacollo ca. tc < 1km x 252 33_x 1 396160 8176200 4400 cp river basin 4.5 1 n. so river Q. Jachaquepampa ca 253 33_x 2 400100 8176270 4400 cp river basin 7 0.5 nw.noo river Rio Jaquela ca 254 33_x 3 440350 8126280 4000 cp river basin 3 1 n.s river Q.Chincuma ca 255 33_x 4 408150 8180140 4500 cp river basin 4 0.7 no.sw river Rio Ccaccasuma ca 256 33_x 5 420000 8184280 4500 cp oval 2.5 2.3 dry river Q. Omaccata Ca < 1km 257 33_x 6 416300 8188220 4000 cp river basin 12 1 no. s river Q. Huajra ca; tc < 1km 258 33_x 7 400340 8200150 4000 wp river basin 20 2 no.sw rivers Rio Aguas Calientes ca. t; tc <1km 259 33_x 8 408000 8192000 4200 cp river basin 3.5 1 n. so rivers Rio Turnavi ca; tc < 1km 260 33_x 9 412100 8196200 4000 wp stretched 5 1 n.s rivers Rio Pacuta Ca < 1km 261 33_x 10 428300 8196150 3800 cp oval 3.5 2.5 rivers Rio Camellaque ca; a. tc < 1km 262 33_x 11 428250 8204270 3800 wp river basin 3.5 0.5 n.s river Rio Zapatilla ca; tc < 1km 263 33_x 12 404100 8220080 3800 wp undefined. river basin 17 7 rivers Rio Grande ca.t; tc.h < 1km 264 29_q 1 736190 8396300 4000 cp river basin 2 0.6 s.nee dry river Q. Teneriayoc Ca < 1km x 265 29_q 2 748020 8396240 4600 cp stretched 2.5 0.6 nw.se river Ca < 1km x 266 29_q 3 716110 8400210 4200 cp oval 3 1 rivers ca x 267 29_q 4 748320 8400050 4700 cp oval 2 1.5 river ca x

Record of HAW Data from Ordnance Survey Maps 7 8 Record of HAW Data from Ordnance Survey Maps

A B C D E F G H I J K L M N 1 osm code nr. of HAW easting northing elevation puna shape lenght width orientation waterbodies name waterbodies annotations smaller HAW around <5km 268 29_q 5 768160 8400350 4500 cp distorted 3 1 rivers.lake Ca < 1km x 269 29_q 6 748270 8404350 4600 cp river basin 2.5 0.6 river. dry river Ca < 1km x 270 29_q 7 756100 8480380 4600 wp distorted 2.7 2 rivers ca x 271 29_q 8 744190 8412210 4500 cp river basin 3 1 ssw.n rivers Q. Cullimayo ca x 272 29_q 9 752170 8412200 4600 cp distorted 4 2.5 rivers. lakes L. Cochajasa ca x 273 29_q 10 740120 8416100 4600 cp river basin 3 1 sw.ne river Q. Llavin ca x 274 29_q 11 728050 8420150 4200 oval 2 1 river. dry river Ca < 1km x 275 29_q 12 740320 8420210 4400 wp stretched 4.5 1 s.n rivers Q. Ocunca ca x 276 29_q 13 724380 8424310 4600 distorted 4 1 rivers. lakes L. Yanacocha Ca < 1km x 277 29_q 14 768000 8428230 4600 wp oval 2.5 1 river x 278 29_q 15 728040 8440000 4400 wp river basin 4.5 0.5 sw.ne river Q. Quinaquina Ca < 1km x 279 29_q 16 716060 8440050 4400 wp river basin 3 1 river. lake L. chamaca ca x 280 24_m 1 480200 8676050 4200 wp oval 1 0.3 river Liplispampa t x 281 24_m 2 488030 8676310 4700 wp distorted 2 2 river. lake L.s Quinsacocha x 282 24_m 3 488090 8684260 4500 wp river basin 3 0.5 s. ne river. lake (nevado) ca x 283 24_m 4 480180 8688220 4400 wp distorted 2.5 2 river Q. Mancocnacha Ca < 1km; tc <2km x 284 24_m 5 488380 8692170 4700 wp oval 1.2 0.6 river. nevado Q. Paucho x 285 24_m 6 476320 8692240 4400 wp river basin 3 0.6 river Q.Mituclo Ca < 1km x 286 24_m 7 472050 8696340 4500 wp river basin. distorted 2.5 1.5 river Q. Pirhuacocha Ca < 1km x 287 24_m 8 484240 8696210 4300 wp oval 1 0.5 river Q quispatuna m. t < 1km x 288 24_m 9 456120 8700080 4100 round 0.7 0.7 river Q. Sacomachay Ca < 1km x 289 24_m 10 476320 8704050 4300 wp river basin 2.5 0.8 s.n river. lake L. Luquina x 290 24_m 11 452200 8708350 4300 wp oval 1 0.6 river Rio Huala x 291 24_m 12 468300 8704330 4400 wp river basin 2 0.5 s.n river. lake L. Paccha x 292 24_m 13 476200 8712150 4400 river basin 5 1 river Q. Marairazo Nevado < 1km x 293 24_m 14 468130 8716070 4300 distorted 1.5 1.5 river. lake L.Utculazo x 294 24_m 15 452330 8724130 4300 wp river basin 2.5 0.5 w.e river Q. Marayrasha x 295 24_m 16 496360 8716350 4100 wp river basin 1.3 0.5 river 296 19_i 1 236150 8948350 4000 wp river basin. stretched 10 0.5 sw.ne river. nevado Q. Calcayhuanea ca x 297 19_i 2 272000 8952100 4200 wp oval 1.5 0.6 river. nevado Ca < 1km. tc < 2km x 298 19_i 3 228200 8960190 4600 wp oval 1.2 0.5 nevado Nevados Jatuncunca x 299 19_i 4 232060 8964390 4500 wp oval 1.3 0.6 river. lake. nevado Q. Aquilpo B < 1km 300 19_i 5 240120 8968180 4200 wp river basin 4 0.7 se. nw river. nevado Q. Minoyo Mina < 2km x 301 19_i 6 252110 8968350 3900 river basin 6 0.6 se.nw river. lakes Q. Cucharcas b x 302 19_i 7 264210 8976050 4200 round 0.7 0.7 river Q. Yanacolpa x 303 19_i 8 244250 8976000 4200 wp river basin 4 0.6 se.nw river Q. Ashnohuana b x 304 19_i 9 268260 8980310 4100 stretched 2 0.5 s.n river Q. Quisuarragra Ca. Mina < 1km (3) x

Record of HAW Data from Ordnance Survey Maps 8