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AimAssessing the distribution and persistence of species across their range is a crucial component of wildlife conservation. It demands data at adequate spatial scales and over extended periods of time, which may only be obtained through collaborative efforts, and the development of methods that integrate heterogeneous datasets. We aimed to combine existing data on large carnivores to evaluate population dynamics and improve knowledge on their distribution nationwide.LocationBotswana.MethodsBetween 2010 and 2016, we collated data on African wild dog, cheetah, leopard, brown and spotted hyaena and lion gathered with different survey methods by independent researchers across Botswana. We used a multi-species, multi-method dynamic occupancy model to analyse factors influencing occupancy, persistence and colonization, while accounting for imperfect detection. Lastly, we used the gained knowledge to predict the probability of occurrence of each species countrywide.ResultsWildlife areas and communal rangelands had similar occupancy probabilities for most species. Large carnivore occupancy was low in commercial farming areas and where livestock density was high, except for brown hyaena. Lion occupancy was negatively associated with human density; lion and spotted hyaena occupancy was high where rainfall was high, while the opposite applied to brown hyaena. Lion and leopard occupancy remained constant countrywide over the study period. African wild dog and cheetah occupancy declined over time in the south and north, respectively, whereas both hyaena species expanded their ranges. Countrywide predictions identified the highest occupancy for leopards and lowest for the two hyaena species.Main ConclusionsWe highlight the necessity of data sharing and propose a generalizable analytical method that addresses the challenges of heterogeneous data common in ecology. Our approach, which enables a comprehensive multi-species assessment at large spatial and temporal scales, supports the development of data-driven conservation guidelines and the implementation of evidence-based management strategies nationally and internationally. published

Spatial capture–recapture models have been widely used to estimate densities of species where individuals can be uniquely identified, but alternatives have been developed for estimation of densities for unmarked populations. In this study we used camera-trap records from 2018 to estimate densities of a species that does not always have individually identifiable marks, Baird's tapir Tapirus bairdii, in the Sierra Madre de Chiapas, southern Mexico. We compared the performance of the spatial capture–recapture model with spatial mark–resight and random encounter models. The density of Baird's tapir did not differ significantly between the three models. The estimate of density was highest using the random encounter model (26/100 km2, 95% CI 12–41) and lowest using the capture–recapture model (8/100 km2, 95% CI 4–16). The estimate from the spatial mark–resight model was 10/100 km2 (95% CI 8–14), which had the lowest coefficient of variation, indicating a higher precision than with the other models. Using a second set of camera-trap data, collected in 2015–2016, we created occupancy models and extrapolated density to areas with potential occupancy of Baird's tapir, to generate a population estimate for the whole Sierra Madre de Chiapas. Our findings indicate the need to strengthen, and possibly expand, the protected areas of southern Mexico and to develop an action plan to ensure the conservation of Baird's tapir.

Determining the density trends of a guild of species can help illuminate their interactions, and the impacts that humans might have on them. We estimated the density trends from 2013 to 2017 of the clouded leopard Neofelis nebulosa, leopard cat Prionailurus bengalensis and marbled cat Pardofelis marmorata in Nam Et—Phou Louey National Park (NEPL), Laos, using camera trap data and spatial capture-recapture models. Mean (± SD) density estimates (individuals/100 km2) for all years were 1.77 ± 0.30 for clouded leopard, 1.50 ± 0.30 for leopard cat, and 3.80 ± 0.70 for marbled cat. There was a declining trend in density across the study years for all three species, with a ≥ 90% probability of decline for clouded leopard and leopard cat and an 83% probability of decline for marbled cat. There was no evidence that mesopredator release occurred as a result of tiger (Panthera tigris) and leopard (P. pardus) extirpations. We believe that snaring, the factor that led to the extirpation of tiger and leopard in NEPL, is now contributing to the decline of smaller felids, to an extent that over-rides any potential effects of mesopredator release on their densities and interactions. We recommend that the NEPL managers implement a more systematic and intensified snare removal program, in concert with extensive community outreach and engagement of local people to prevent the setting of snares. These actions might be the only hope for saving the remaining members of the felid community in NEPL.

Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion‐activated trail cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy is poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best‐practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online: Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photograph was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answer for each photograph using a plurality algorithm. Subsequently, a subset of these images underwent expert review and were compared to the citizen scientist results. Classification errors were categorized by the nature of the error (e.g., false species or false empty), and reason for the false classification (e.g., misidentification). Our results show that Snapshot Serengeti had the highest accuracy (97.9%), followed by AmazonCam Tambopata (93.5%), then Wildwatch Kenya (83.4%). Error type was influenced by habitat, with false empty images more prevalent in open‐grassy habitat (27%) compared to woodlands (10%). For medium to large animal surveys across all habitat types, our results suggest that to significantly improve accuracy in crowdsourced projects, researchers should use a trail camera set up protocol with a burst of three consecutive photographs, a short field of view, and determine camera sensitivity settings based on in situ testing. Accuracy level comparisons such as this study can improve reliability of future citizen science projects, and subsequently encourage the increased use of such data., We show that the accuracy levels of trail‐camera image classification by citizen scientists are affected by habitat type and trail‐camera set up. By comparing the accuracy results from three camera trap citizen science projects, we found that setting trail cameras to capture 3 images per burst, testing the appropriate camera sensitivity, and a shorter field of view resulting from dense vegetation may significantly improve citizen scientist image classification accuracy when compared to classifications by experts.

Madagascar is a threatened global biodiversity hotspot and conservation priority, yet we lack broad-scale surveys to assess biodiversity across space and time. To fill this gap, we collated camera trap surveys, capturing species occurrences within Madagascar into a single standardized database. This data set includes nine distinct protected areas of Madagascar and encompasses 13 subprojects, 38 camera arrays, and 1156 sampling units (independent camera site per survey) within two important biodiversity eco-regions: western dry deciduous forest and eastern humid rainforest. Camera surveys were conducted from June 2007 to January 2021. The final data set includes 17 unique families of mammals (Bovidae, Canidae, Cheirogaleidae, Daubentoniidae, Equidae, Eupleridae, Felidae, Hominidae, Indriidae, Lemuridae, Lepilemuridae, Muridae, Nesomyidae, Pteropodidae, Soricidae, Suidae, Tenrecidae) comprising 45 species and 27 unique families of birds (Accipitridae, Acrocephalidae, Alcedinidae, Bernieridae, Brachypteraciidae, Caprimulgidae, Cisticolidae, Columbidae, Coraciidae, Corvidae, Cuculidae, Dicruridae, Mesitornithidae, Monarchidae, Motacillidae, Muscicapidae, Numididae, Phasianidae, Rallidae, Sarothruridae, Strigidae, Sturnidae, Sulidae, Threskiornithidae, Upupidae, Vangidae, Zosteropidae) comprising 58 species. Images were processed and verified by individual project data set creators and camera operation and species tables were then collated. The final product represents the first broad-scale freely available standardized formal faunal database for Madagascar. Data are available through this publication and at DOI: 10.5281/zenodo.5801806. These data will be useful for examining species-level and community-level trends in occurrence across space or time within Madagascar and globally, evaluating native and invasive species dynamics, and will aid in determining species conservation status and planning for at-risk species. There are no copyright restrictions; please cite this paper when using the data for publication.

The efficacy of translocation as a method for conserving species in peril has not been fully evaluated. Post‐release monitoring rarely involves long‐term assessments and initial success metrics may not translate to population viability. In particular, genetic factors may play a critical role in fitness following release as founder effect, genetic drift, inbreeding depression and outbreeding depression can influence extinction risk. As part of a multi‐year recovery effort, we translocated populations of the endangered Stephens' kangaroo rat (Dipodomys stephensi; SKR), in order to restore population connectivity. Here we evaluate the success of the translocation efforts through long‐term population estimation and genetic analyses. We conducted post‐release assessments for 9 years, and used Bayesian clustering analysis and principal components analysis (PCA) of 24 microsatellite markers developed for this species to assess genetic admixture between source and translocated populations. Demographic results indicate long‐term translocation success, as evidenced by founder survival and establishment, and population growth and regulation. Genetic results show admixture at the release site between genetically discrete source populations, provide definitive evidence that translocated individuals, not immigrants, produced offspring at the release site, that these offspring successfully reproduced and that even with moderate to great genetic differentiation of source populations, outbreeding depression was not detected. Despite the historical failure of heteromyid translocation efforts, our long‐term study illustrates how the development of species‐specific best practices led to an effective strategy for SKR recovery. More broadly, our results suggest efforts that use a systematic hypothesis‐testing framework alongside long‐term monitoring offer great promise in improving translocation outcomes.

Aim: Community‐level assessments of how biodiversity responds to disturbance within forest habitats are often biased towards terrestrial‐based surveys. However, recent research suggests that arboreal communities of several indicator groups (ants, amphibians, beetles and butterflies) are more susceptible to human disturbance than their terrestrial counterparts, but what about wildlife at higher trophic levels? We assess responses to disturbance, from forest floor to canopy, of a key conservation flagship group: medium to large rainforest mammals. Location: The Manu Biosphere Reserve, southeast Peru. Methods: We deploy both arboreal and terrestrial camera traps to directly compare the response of arboreal and terrestrial mammal communities to rainforest degradation and disturbance. Results: We show that the arboreal mammal community is more susceptible to habitat disturbance than the terrestrial community. Furthermore, the largest‐bodied arboreal species, which are major seed dispersers, showed the greatest negative response to forest disturbance. The strongest predictors of occupancy probability for arboreal communities were focal tree connectivity and canopy cover, whereas surrounding forest loss and canopy height were there strongest predictors of terrestrial community occupancy, although these also had effects similar in size and magnitude on the arboreal community. Main conclusions: Conservation conclusions drawn from camera‐based studies focused on the terrestrial realm likely underestimate the impact of rainforest degradation to arboreal communities and on arboreal rainforest biodiversity in general. We highlight the importance of implementing arboreal research methods, capable of investigating conservation implications of anthropogenic disturbance across all vertical strata, for accurate conservation assessments and improving rainforest management and restoration strategies.

1. Arboreal camera trapping is a burgeoning method providing a novel and effective technique to answer research questions across a variety of ecosystems, and it has the capacity to improve our understanding of a wide range of taxa. However, while terrestrial camera trapping has received much attention, there is little guidance for dealing with the unique challenges of working in the arboreal realm. 2. Our review draws on the expertise of researchers from six continents and the broader literature to investigate the advantages and disadvantages of arboreal camera trapping, and challenges to consider when using this technology. We also include mini-guides with detailed information on the current arboreal camera trap literature, mounts used to install arboreal cameras, tree climbing pointers and safety tips, methods for deploying cameras without climbing, and tips for managing interference with camera function. 3. We find that arboreal camera traps have been most commonly used in the study of mammals in forests, however there is potential for this method to be applied to a broad range of habitats including urban areas, and taxa such as birds, amphibians, invertebrates, and plants. Methods in arboreal camera trapping could be improved by developing a greater understanding of the factors affecting detection of species. The most common challenges of arboreal camera trapping are camera placement and camera site access. These can be overcome by understanding correct camera orientation, managing potential sources of interference in front of cameras, utilizing appropriate cameras mounts, and training researchers properly. 4. Given the benefits and opportunities presented by arboreal camera trapping, it is likely to become an ever-more popular method of studying arboreal species and systems. The information synthesized in this review provides guidance for future studies to help direct more reliable and robust ecological inferences from arboreal camera trapping.

Innovative techniques, such as environmental DNA (eDNA) metabarcoding, are now promoting broader biodiversity monitoring at unprecedented scales, because of the reduction in time, presumably lower cost, and methodological efficiency. Our goal was to assess the efficiency of established inventory techniques (live-trapping grids, pitfall traps, camera trapping, mist netting) as well as eDNA for detecting Amazonian mammals. For terrestrial small mammals, we used 32 live-trapping grids based on Sherman and Tomahawk traps (total effort of 10,368 trap-nights); in addition to 16 pitfall traps (1,408 trap-nights). For bats, we used mist nets at 8 sites (4,800 net hours). For medium and large mammals, we used 72 camera trap stations (5,208 camera-days). We identified vertebrate and mammal taxa based on eDNA analysis (12S region, with V05 and Mamm01 markers) from water samples, including a total of 11 3-km transects for stagnant water sampling and seven small streams for running water sampling. A total of 106 mammal species were recorded. Building on sample-based rarefaction and extrapolation curves, both trapping grids and pitfall were successful, recording 91.16% and 82.1% of the expected species for these techniques (~22 and ~9 species), and 16.98% and 6.60% of the total recorded mammal species, respectively. Mist nets recorded 83.2% of the expected bat species (~48), and 34.91% of the total recorded species. Camera trapping recorded 99.2% of the predicted large- and medium-sized species (~31), and 33.02% of the total recorded species. eDNA recorded 75.4% of the expected mammal species for this technique (~68), and 47.0% of the total recorded species. eDNA resulted in a useful tool that saves on effort and reduces sampling costs. This study is among the first to show the large potential of eDNA metabarcoding for assessing Amazonian mammal communities, providing, in combination with conventional techniques, a rapid overview of mammal diversity with broad applications to monitoring, management and conservation. By including appropriate genetic markers and updated reference databases, eDNA metabarcoding method can be extended to the whole vertebrate community.

Field photographs of plant species are crucial for research and conservation, but the lack of a centralized database makes them difficult to locate. We surveyed 25 online databases of field photographs and found that they harboured only about 53% of the approximately 125,000 vascular plant species of the Americas. These results reflect the urgent need for a centralized database that can both integrate and complete the photographic record of the world’s flora. Field photographs are essential for research and conservation, but are difficult to access since there is no central database or connection between archives. The 25 leading databases hold only 53% of the plant species of the Americas, illustrating the need for increased work on collecting and standardizing this valuable data.

Hunting for wild meat in the tropics provides subsistence and income for millions 29 of people. Methods have remained relatively unchanged since the introduction of 30 shotguns and battery-powered incandescent flashlights, but due to the short life of batteries in such flashlights, nocturnal hunting has been limited. However, brighter, 32 more efficient light-emitting diode (LED) flashlights, have recently been adopted by 33 hunters. Brighter spotlights increase the freezing response of many species, and 34 greater battery life allows hunters to pursue game for longer and more frequently. 35 Hunters interviewed in African and South American forests, disclosed that LEDs 36 increase the frequency and efficiency of nocturnal hunting, and the number of kills 37 made. These changes were reflected in harvest data in Brazil. The drastic change in 38 efficiency brought about by LEDs, well known to hunters around the world, poses a 39 significant threat to wildlife. We consider the implications for communities, governments, 40 wildlife managers and conservationists

Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion-activated trail-cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail-cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy are poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online: Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photo was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answer for each photo using a plurality algorithm. Subsequently, a subset of these images underwent expert review and were compared to the citizen scientist results. Classification errors were categorized by the nature of the error (e.g. false species or false empty), and reason for the false classification (e.g. misidentification). Our results show that Snapshot Serengeti had the highest accuracy (97.9%), followed by AmazonCam Tambopata (93.5%), then Wildwatch Kenya (83.4%). Error type was influenced by habitat, with false empty images more prevalent in open-grassy habitat (27%) compared to woodlands (10%). For medium to large animal surveys across all habitat types, our results suggest that to significantly improve accuracy in crowdsourced projects, researchers should use a trail-camera set up protocol with a burst of three consecutive photos, a short field of view, and consider appropriate camera sensitivity. Accuracy level comparisons such as this study can improve reliability of future citizen science projects, and subsequently encourage the increased use of such data.

Incluye contenido parcial de los autores Abstract.Mammalian carnivores are considered a key group in maintaining ecologicalhealth and can indicate potential ecological integrity in landscapes where they occur. Carni-vores also hold high conservation value and their habitat requirements can guide managementand conservation plans. The order Carnivora has 84 species from 8 families in the Neotropicalregion: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; andUrsidae. Herein, we include published and unpublished data on native terrestrial Neotropicalcarnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTRO-PICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data wereobtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organi-zations, and private consultants. Data were collected using several methods including cameratrapping, museum collections, roadkill, line transect, and opportunistic records. Literature(peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated inthis compilation. Most of the data set consists of detection data entries (n=79,343; 79.7%) butalso includes non-detection data (n=20,262; 20.3%). Of those, 43.3% also include count data(n=43,151). The information available in NEOTROPICAL CARNIVORES will contribute tomacroecological, ecological, and conservation questions in multiple spatio-temporal perspec-tives. As carnivores play key roles in trophic interactions, a better understanding of their distri-bution and habitat requirements are essential to establish conservation management plans andsafeguard the future ecological health of Neotropical ecosystems. Our data paper, combinedwith other large-scale data sets, has great potential to clarify species distribution and relatedecological processes within the Neotropics. There are no copyright restrictions and no restric-tion for using data from this data paper, as long as the data paper is cited as the source of theinformation used. We also request that users inform us of how they intend to use the data.

The harpy eagle (Harpia harpyja) is one of the main predators of arboreal mammals in the neotropics, affecting the ecology and behaviour these species. Knowledge of harpy eagle diets across their geographical range is patchy, the ability of harpy eagles to adapt to changing habitats is still open to question. The three main species in the diet of harpy eagles nesting at Tambopata were porcupines (Coendou sp.) (n = 7) howler monkeys (Alouatta sara) (n = 6) and two-toed sloths (Choloepus didactylus) (n = 4), all species that do well in disturbed forests. We conclude that harpy eagles can reproduce in secondary forests, feeding on abundant disturbance-tolerant species, if they themselves are not hunted and their nesting trees are conserved. Harpy eagle nests have a high value for tourism, and strategies that allow landowners to benefit from harpy eagles nesting on their property through revenues from tourism may be instrumental in incentivising the conservation of forests and emergent trees, and the regeneration of forests in anthropogenic landscapes.

Large areas of tropical forest have been designated for timber production but logging practices vary widely. Reduced-impact logging is considered best practice and third-party certification aims to ensure that strict standards are met. This includes minimizing the number of roads constructed, avoiding sensitive areas and strictly regulating hunting. Large scale camera trap grids were utilized in Guatemala and Peru to evaluate the impact of reduced-impact logging in certified concessions upon the large and medium-sized mammal fauna with special emphasis on jaguars (Panthera onca). Spatial capture-recapture models showed that jaguar density in Peru (4.54 ± 0.83 ind. 100 km−2) was significantly higher than in Guatemala (1.52 ± 0.34 ind. 100 km−2) but in both regions, densities were comparable to protected areas. Camera traps detected 22 species of large and medium sized mammals in Guatemala and 27 in Peru and a multi-species occupancy model revealed that logging had no negative impact on any of the species studied and actually had an initial positive impact on several herbivore species. We found no avoidance of logging roads; in fact, many species, especially carnivores, frequently used logging roads as movement corridors. Our results indicate that well-managed logging concessions can maintain important populations of large and medium-sized mammals including large herbivores and large carnivores as long as hunting is controlled and timber volumes extracted are low. Responsible forest management would therefore be an ideal activity in the buffer zones and multiple use zones of protected areas creating much less impact and conflict than alternatives such as agriculture or cattle ranching while still providing economic opportunities. Logging concessions can also play an important role in maintaining landscape connectivity between protected areas.

Made available in DSpace on 2022-05-01T07:58:51Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-08-09 Consejo Nacional de Investigaciones Científicas y Técnicas WWF International Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Large terrestrial carnivores have undergone some of the largest population declines and range reductions of any species, which is of concern as they can have large effects on ecosystem dynamics and function.1–4 The jaguar (Panthera onca) is the apex predator throughout the majority of the Neotropics; however, its distribution has been reduced by >50% and it survives in increasingly isolated populations.5 Consequently, the range-wide management of the jaguar depends upon maintaining core populations connected through multi-national, transboundary cooperation, which requires understanding the movement ecology and space use of jaguars throughout their range.6–8 Using GPS telemetry data for 111 jaguars from 13 ecoregions within the four biomes that constitute the majority of jaguar habitat, we examined the landscape-level environmental and anthropogenic factors related to jaguar home range size and movement parameters. Home range size decreased with increasing net productivity and forest cover and increased with increasing road density. Speed decreased with increasing forest cover with no sexual differences, while males had more directional movements, but tortuosity in movements was not related to any landscape factors. We demonstrated a synergistic relationship between landscape-scale environmental and anthropogenic factors and jaguars’ spatial needs, which has applications to the conservation strategy for the species throughout the Neotropics. Using large-scale collaboration, we overcame limitations from small sample sizes typical in large carnivore research to provide a mechanism to evaluate habitat quality for jaguars and an inferential modeling framework adaptable to the conservation of other large terrestrial carnivores. Asociación Guyra Paraguay and CONACYT Parque Ecológico Asunción Verde Insituto Saite Centro Nacional de Pesquisa e Conservação de Mamíferos Carnívoros Instituto Chico Mendes de Conservação da Biodiversidade Instituto de Biociências Universidade Estadual Paulista-UNESP Departamento de Biodiversidade Laboratório de Ecologia Espacial e Conservação LEEC Instituto Pró-Carnívoros Department of Animal Nutrition and Management Swedish University of Agricultural Sciences Instituto de Biociências Departamento de Ecologia Universidade de São Paulo Cidade Universitária, Rua do Matão, Trav. 14, no. 321 Instituto de Biología Subtropical Universidad Nacional de Misiones and CONICET Asociación Civil Centro de Investigaciones del Bosque Atlántico Programa Jaguares de la Selva Maya Bioconciencia A.C. School of Environmental and Geographical Sciences University of Nottingham Malaysia, Jalan Broga IPÊ-Instituto de Pesquisas Ecológicas Faro Moro Eco Research Estancia Faro Moro Departamento de Boquerón Instituto Onça Pintada Estacao Ecológica Taiamã Instituto Chico Mendes de Conservação da Biodiversidade Instituto de Desenvolvimento Sustentável Mamirauá Associação Onçafari Rua Ferreira de Araújo, 221, Cj.14, Sala 4, Pinheiros Panthera, 8 West 40th Street, 18th Floor Instituto SOS Pantanal, R. Gutemberg, 328 Centro Programa de Pós-graduação em Biologia Animal Instituto de Biociências Universidade Federal do Rio Grande do Sul (UFRGS) Instituto de Ecología Universidad Nacional Autónoma de México and CONACyT Ciudad Universitaria Instituto Internacional en Conservación y Manejo de Vida Silvestre Universidad Nacional de Costa Rica Department of Environmental Conservation University of Massachusetts, Amherst Centro de Investigación en Ciencias Biológicas Aplicadas Universidad Autónoma del Estado de México Instituto Literario 100 Col. Centro C.P. Instituto de Biologia Laboratório de Ecologia de Mamíferos LEMA Universidade Federal de Uberlândia Primero Conservation, Box 1588 Namá Conservation Rescate Animal Zooave Fundación Restauración de la Naturaleza, Apdo Projeto Carnívoros do Iguaçu Universidade Federal da Integração Latino-Americana Instituto Latino-Americano de Ciências da Vida e da Natureza Universidade Federal de Mato Grosso do Sul Faculdade de Medicina Veterinária e Zootecnia Instituto Onças do Rio Negro Fazenda Barranco Alto Departamento de Medicina Veterinária Universidade Federal de Viçosa Instituto de Defesa e Preservação dos Felídeos Brasileiros SUNY College of Environmental Science & Forestry Wildlife Biology Program W.A. Franke College of Forestry & Conservation University of Montana Universidade do Sul de Santa Catarina Wildlife Protection Solutions, 2501 Welton Street San Diego Zoo Global Institute for Conservation Research, 15600 San Pasqual Valley Road Universidade Federal de São João del Rei Departamento de Ciências Naturais Laboratório de Ecologia Manejo e Conservação de Fauna Silvestre Programa de Pós-Graduação Interunidades em Ecologia Aplicada Universidade de São Paulo ESALQ/CENA Universidad Nacional de Córdoba Facultad de Ciencias Exactas Físicas y Naturales Centro de Zoología Aplicada Consejo Nacional de Investigaciones Científicas y Técnicas CONICET Instituto de Diversidad y Ecología Animal IDEA Instituto Nacional de Medicina Tropical ANLIS Ministerio de Salud de la Nación Instituto de Pesquisa e Conservação de Tamanduás do Brasil Instituto de Biociências Universidade Estadual Paulista-UNESP Departamento de Biodiversidade Laboratório de Ecologia Espacial e Conservação LEEC FAPESP: 2014/24921-0 FAPESP: 2018/13037–3 FAPESP: 2018/24891-5

Non-motorized human recreation may displace animals from otherwise suitable habitat; in addition, animals may alter their activity patterns to reduce (or increase) interactions with recreationists. We investigated how hiking, mountain biking, equestrians, and recreationists with domestic dogs affected habitat use and diel activity patterns of ten species of medium and large-sized mammals in the San Francisco Bay ecoregion. We used camera traps to quantify habitat use and activity patterns of wild mammals and human recreationists at 241 locations in 87 protected areas. We modeled habitat use with a multi-species occupancy model. Species habitat use was most closely associated with environmental covariates such as landcover, precipitation, and elevation. Although recreation had less influence on habitat use, the presence of domestic dogs was negatively associated with habitat use of mountain lions and Virginia opossum. We also compared diel activity patterns of species at sites with no observed recreation to the activity patterns of species at sites with high (≥ eight per day) levels of non-motorized recreation. Coyotes were more active at night and less active during the day in areas with high levels of recreation. Striped skunks were slightly more active later into the morning in areas that allowed human recreation. Smaller carnivores with nocturnal activity patterns may not be directly affected by recreational activities that are limited to daylight hours. We suggest that by maintaining habitat free of domestic dogs, and creating trail-free buffers, land managers can manage recreation in a way that minimizes impacts to wildlife habitat and preserves the value of protected areas to people and wildlife.

Large and medium-bodied rainforest canopy mammals are typically surveyed using line transects, but these are labour intensive and usually ignore nocturnal species. Camera traps have become the preferred tool for assessing terrestrial mammal communities, but have rarely been used for arboreal species. Here, we compare the efficiency of arboreal camera trapping with line transects for inventorying medium and large-sized arboreal mammals, and assess the viability of using camera traps in trees to model habitat occupancy. We installed 42 camera traps, spaced 2 km apart, in the canopy of the Maijuna-Kichwa Regional Conservation Area, Peru and walked 2014 km of diurnal line transects on 22 trails at the same site. We compared the efficiency of each method using species accumulation curves. We applied a multi-species occupancy model, while examining the effect of camera height on detection probabilities, including the distance from a village and from a river as covariates to examine variability in habitat occupancy. In 3147 camera days, 18 species of arboreal medium and large-sized mammals were detected by cameras, while 11 species were recorded on line transects. Ten of these species were detected by both methods. Diurnal species were detected more quickly and with less effort using arboreal camera trapping than using diurnal line transects at the same site, although some species were more easily detected during line transects. Habitat occupancy was positively correlated with distance from the village for two species, and negatively correlated with distance from the river for one. Detection probabilities increased modestly with camera height. Practical limitations of arboreal camera trapping include the requirement for specialized climbing techniques, as well as increased potential for false triggers, requiring extended processing time. Arboreal camera trapping is an efficient method for inventorying arboreal mammals and a viable option for studying their distribution relative to environmental or anthropogenic variables when abundance or density estimates are not required.

Spatiotemporal patterns in biological communities are typically driven by environmental factors and species interactions. Spatial data from communities are naturally described by stacking models for all species in the community. Two important considerations in such multispecies or joint species distribution models (JSDMs) are measurement errors and correlations between species. Up to now, virtually all JSDMs have included either one or the other, but not both features simultaneously, even though both measurement errors and species correlations may be essential for achieving unbiased inferences about the distribution of communities and species co-occurrence patterns. We developed two presence-absence JSDMs for modeling pairwise species correlations while accommodating imperfect detection: one using a latent variable and the other using a multivariate probit approach. We conducted three simulation studies to assess the performance of our new models and to compare them to earlier latent variable JSDMs that did not consider imperfect detection. We illustrate our models with a large Atlas data set of 62 passerine bird species in Switzerland. Under a wide range of conditions, our new latent variable JSDM with imperfect detection and species correlations yielded estimates with little or no bias for occupancy, occupancy regression coefficients, and the species correlation matrix. In contrast, with the multivariate probit model we saw convergence issues with large data sets (many species and sites) resulting in very long run times and larger errors. A latent variable model that ignores imperfect detection produced correlation estimates that were consistently negatively biased, that is, underestimated. We found that the number of latent variables required to represent the species correlation matrix adequately may be much greater than previously suggested, namely around n/2, where n is community size. The analysis of the Swiss passerine data set exemplifies how not accounting for imperfect detection will lead to negative bias in occupancy estimates and to attenuation in the estimated covariate coefficients in a JSDM. Furthermore, spatial heterogeneity in detection may cause spurious patterns in the estimated species correlation matrix if not accounted for. Our new JSDMs represent an important extension of current approaches to community modeling to the common case where species presence-absence cannot be detected with certainty.

1. Monitoring the response of wild mammal populations to threatening processes is fundamental to effective conservation management. This is especially true for infectious diseases, which may have dynamic and therefore unpredictable interactions with their host. 2. We investigate the long-term impact of a transmissible cancer, devil facial tumour disease (DFTD), on the endemic Tasmanian devil. We analyse trends in devil spot-light counts and density across the area impacted by the disease. We investigate the demographic parameters which might be driving these trends, and use spatial capture-recapture models to examine whether DFTD has affected home range size. 3. We found that devils have declined by an average of 77% in areas affected by DFTD, and that there is a congruent trend of ongoing small decline in spotlight counts and density estimates. Despite this, devils have persisted to date within each of nine monitoring sites. One site is showing as yet unexplained small increases in density 8-10 years after the emergence of DFTD. 4. We also found the prevalence of DFTD has not abated despite large declines in density and that diseased sites continue to be dominated by young devils. The long-term impact of the disease has been partially offset by increased fecundity in the form of precocial breeding in 1-year-old females, and more pouch young per female in diseased sites. The lower densities resulting from DFTD did not affect home range size. 5. Synthesis and applications. Transmission of devil facial tumour disease continues despite large declines in devil density over multiple generations. Plasticity in life history traits has ameliorated the impact of devil facial tumour disease, however broad-scale trends in density show ongoing decline. In light of this, devil facial tumour disease and the impact of stochastic events on the reduced densities wrought by the disease, continue to threaten devils. In the absence of methods to manage disease in wild populations, we advocate managing the low population densities resulting from disease rather than disease per se.

The continuing development of improved capture–recapture (CR) modeling techniques used to study apex predators has also limited robust temporal and cross-site analyses due to different methods employed. We develop an approach to standardize older non-spatial CR and newer spatial CR density estimates and examine trends for critically endangered Sumatran tigers (Panthera tigris sumatrae) using a meta-regression of 17 existing densities and new estimates from our own fieldwork. We find that tiger densities were 47% higher in primary versus degraded forests and, unexpectedly, increased 4.9% per yr from 1996 to 2014, likely indicating a recovery from earlier poaching. However, while tiger numbers may have temporarily risen, the total potential island-wide population declined by 16.6% from 2000 to 2012 due to forest loss and degradation and subpopulations are significantly more fragmented. Thus, despite increasing densities in smaller parks, we conclude that there are only two robust populations left with >30 breeding females, indicating Sumatran tigers still face a high risk of extinction unless deforestation can be controlled., Determining the conservation status and populations trends for elusive predators has been impeded by discrepancies in how densities are calculated. Here, Luskin et al. introduce a means to standardize previous density estimates and assess the threats to the Sumatran tiger.

Within the United States (US), Peninsular bighorn sheep (Ovis canadensis nelsoni, PBS) are listed as federally endangered. Despite known metapopulation structure, little is known regarding functional connectivity across the international border with Mexico. Increasing threats to connectivity associated with highway expansion, renewable energy development, and completion of the US–Mexico border fence, led us to conduct a study of genetic variation and spatial structure. Blood and fecal samples were collected (n = 224) on both sides of the border from 1992 to 2013. Genetic data was obtained for 25 microsatellite loci and 515 base pairs of the mitochondrial DNA control region. Microsatellite diversity (observed heterozygosity = 0.56; allelic richness = 4.1; inbreeding coefficient = 0.01) was substantial despite past demographic declines. STRUCTURE analysis indicated the presence of three genetic populations, one of which spanned the international border. This pattern of genetic structure was supported by analysis of molecular variance for both microsatellites and mitochondrial DNA (P

Past temperature changes in tropical mountain regions are commonly inferred from vertical elevational shifts of montane indicator taxa in the palynological record. However temperature is one of several abiotic factors driving the low-elevational limits of species and many montane taxa can occur in warmer lowlands by tracking appropriate habitat types, especially highly flooded wetlands. In this paper we explore ways in which lowland habitat heterogeneity might introduce error into paleo-temperature reconstructions, based on field data of seven modern peatland vegetation communities in the southern Peruvian Amazon (~ 200 masl). Peat-rich substrates are common edaphic transitions in pollen cores and provide detailed records of past vegetation change. The data show that indicators of modern peatlands include genera with montane as well as lowland distributions, while indicators of surrounding forests on mineral substrates have predominantly lowland distributions. Based on family-level analyses we find that modern peatland vegetation communities have taxonomic compositions appearing to be 389 m to 1557 m (mean = 1050 ± 391 m) above their actual elevations due to a high abundance and number of families with high elevation optima. We interpret the relatively higher prevalence of montane elements in modern peatlands as habitat tracking of a conserved montane niche on heterogeneous lowland landscapes. We suggest that both high moisture availability and stressful edaphic conditions of peatland habitat may explain the montane bias observed. To the extent that fossilization provides a better record of past vegetation that occurred proximate to the site of deposition, we suggest that habitat tracking of montane elements may introduce a cool bias in lowland paleo-temperature reconstructions based on pollen proxies.

Summary Over the last two decades, a large number of camera trap surveys have been carried out around the world and camera traps have been proposed as an ideal tool for inventorying and monitoring medium to large-sized terrestrial vertebrates. However, few studies have analysed camera trap data at the community level. We developed a multi-session multi-species occupancy model that allows us to obtain estimates for species richness and occupancy combining data from multiple camera trap surveys (sessions). By estimating species presence at the session-level and modelling detection probability and occupancy for each species and sessions as nested random effects, we could improve parameter estimates for each session, especially for species with sparse data. We developed two variants of our model: one was a binary latent states model while the other used a Royle–Nichols formulation for the relationship between detection probability and abundance. We applied both models to data from eight camera trap surveys from south-eastern Peru including six study sites, 263 camera stations and 17 423 camera days. Sites covered protected areas, a logging concession and Brazil nut concessions. We included habitat (terra firme vs. floodplain) as a covariate for occupancy and trail vs. off-trail as a covariate for detection. Among-camera heterogeneity was a serious problem for our data and the Royle–Nichols variant of our model had a much better fit than the binary-state variant. Both models resulted in similar species richness estimates showing that most of the sites contained intact large mammal communities. Detection probabilities and occupancy values were more variable across species than across sessions within species. Three species showed a habitat preference and four species showed preference or avoidance of trails. Synthesis and applications. Our multi-session multi-species occupancy model provides improved estimates for species richness and occupancy for a large data set. Our model is ideally suited for integrating large numbers of camera trap data sets to investigate regional and/or temporal patterns in the distribution and composition of mammal communities in relation to natural or anthropogenic factors or to monitor mammal communities over time.

Camera traps are used by scientists and natural resource managers to acquire ecological data, and the rapidly increasing camera trapping literature highlights how popular this technique has become. Nevertheless, the methodological information reported in camera trap publications can vary widely, making replication of the study difficult. Here we propose a series of guiding principles for reporting methods and results obtained using camera traps. Attributes of camera trapping we cover include: (i) specifying the model(s) of camera traps(s) used, (ii) mode of deployment, (iii) camera settings, and (iv) study design. In addition to suggestions regarding best practice data coding and analysis, we present minimum principles for standardizing information that we believe should be reported in all peer-reviewed papers. Standardised reporting enables more robust comparisons among studies, facilitates national and global reviews, enables greater ease of study replication, and leads to improved wildlife research and management outcomes.

The Amazonian moist forest, which covers most of French Guiana, is one of the core habitats for the lowland tapirTapirus terrestris. Tapirs are hunted in French Guiana, although a law introduced in 2011 restricts hunting to one animal per person per hunting trip. We carried out camera-trap surveys in the Nouragues Nature Reserve for 4 years, with the goal of estimating tapir densities in undisturbed conditions and determining sustainable harvest levels for tapirs in French Guiana. We analysed our data with a Bayesian spatially explicit capture–recapture model, with parameter sharing across surveys to improve estimates, and used the model to calculate derived parameters such as maximum sustainable harvest levels. Density estimates for all four surveys were similar and the model indicated a difference in encounter rates for the two camera models used but no difference in encounter rates or home range sizes for males and females or between years. Based on the calculated density of 0.32 tapir km−2we estimated sustainable harvest levels at 0.009 tapir km−2. Comparing this value to hunting surveys from 11 sites between 1999 and 2006, we found that hunting levels were unsustainable in at least seven villages. We conclude that even the new restrictive hunting law will not prevent overhunting of tapirs in certain areas and thus stronger regulations are needed. However, because of the remoteness of tapir habitat in many parts of French Guiana tapirs are not immediately threatened in the country as a whole.

Over 80% of the currently occupied range of the jaguar ( Panthera onca ) lies in the Amazon. However, few density estimates exist for this habitat. Between 2005 and 2010 we carried out six camera trap surveys at three different sites in the department of Madre de Dios in the Peruvian Amazon. We analyzed our data using a Bayesian spatially explicit capture recapture model (SECR) with sex covariates to account for differences in home range size and detection probabilities of male and female jaguars. As several of our camera grids where too small for reliable density estimates, we used estimates for the σ parameter from the largest camera grid to correct for the bias. Density estimates for our surveys were similar with an average density of 4.4 ± 0.7 jaguar 100 km −2 . Both home range size and encounter rates varied significantly between sexes with males having a larger home range and higher encounter rate than females. Our estimated sex ratio was 1:1.5 compared to an observed ratio of 1.9:1. Not accounting for sex would have resulted in an underestimation of the true density. The densities found in this study are among the highest documented and show that the Amazon is indeed a core habitat for the jaguar. We estimate that three jaguar conservation units in our study region (areas defined by experts as having a high conservation priority) could harbor as many as 6000 jaguars (CI: 4278–8142).

Camera traps have become the main method for estimating jaguar (Panthera onca) densities. Over 74 studies have been carried out throughout the species range following standard design recommendations. We reviewed the study designs used by these studies and the results obtained. Using simulated data we evaluated the performance of different statistical methods for estimating density from camera trap data including the closed-population capture–recapture models Mo and Mh with a buffer of ½ and the full mean maximum distance moved (MMDM) and spatially explicit capture–recapture (SECR) models under different study designs and scenarios. We found that for the studies reviewed density estimates were negatively correlated with camera polygon size and MMDM estimates were positively correlated. The simulations showed that for camera polygons that were smaller than approximately one home range density estimates for all methods had a positive bias. For large polygons the Mh MMDM and SECR model produced the most accurate results and elongated polygons can improve estimates with the SECR model. When encounter rates and home range sizes varied by sex, estimates had a negative bias for models that did not include sex as a covariate. Based on the simulations we concluded that the majority of jaguar camera trap studies did not meet the requirements necessary to produce unbiased density estimates and likely overestimated true densities. We make clear recommendations for future study designs with respect to camera layout, number of cameras, study length, and camera placement. Our findings directly apply to camera trap studies of other large carnivores.

We present results of research concerning the distribution, depth, volume, geomorphology, and habitat diversity of peatlands in the southern Peruvian Amazon. We identified 295 peatlands covering 294 km2 and ranging in size from 10 to 3,500 ha. Individual peatlands were mostly restricted to the meander belt of the Madre de Dios River. Mean peat depth was 2.54 ± 1.84 m (n = 429), however we encountered depths to 9 m and 10% of the measurements exceeded 5 m. We developed a calibration factor to calculate peat volume across the study area, estimating total peat volume within 295 peatlands at 657 ± 119 Mm3. An interpolated depth map of subsurface morphology of a single peatland showed that fluvial features were well-conserved beneath several meters of peat and three distinct subsurface geomophological units defined by peat depth could be identified: the Primary Basin, Secondary Basin, and Intrabasin flats. Subsurface geomorphology resulted in increased within-habitat heterogeneity and explained 35% of the variation of pixel values extracted from Landsat™ imagery. Representing a hydrological link from elevated uplands to the lower floodplains, peatlands in Madre de Dios are especially threatened on local scales by habitat alteration in the uplands and gold mining in the floodplains.

The adult sphingid communities of three sites in southeastern Peru representative of the moist tropical forest of the lowland Amazon, the pluvial tropical forest of the upper Amazon and Andean foothills, and the montane cloud forest of the eastern slopes of the Andes were sampled during 2004–2006 by using mercury vapor light traps. In total, 119 species of Sphingidae were documented. Species diversity was highest in the upper Amazon and Andean foothills, with 94 species (21 genera), followed by 80 species (21 genera) in the Amazonian lowlands, and 43 species (17 genera) in the montane cloud forest. The greatest number of endemics (22) was registered at the upper AmazonAndean foothills site. The montane cloud forest site was characterized by the highest relative percentage of endemic species. The species assemblages of the lowland Amazon and the Andean foothills were more similar in composition to each other than to the montane assemblage. All three assemblages proved to be more distinctive than expected based on the proximity of the sampled sites and seemingly good flight capabilities of sphingid moths. This was reflected by the endemics accounting for nearly 40% of the total species pool. By contrast, cosmopolitans numbered only 26 species, or 22% of the total assemblage. We hypothesize that the composition and distribution of sphingid species along this elevational gradient may reflect floristic similarities and differences between the study sites and the extent to which different species are adapted to cope with certain environmental conditions, such as temperature and air humidity.

The lowland tapir Tapirus terrestris is the largest herbivore in the Neotropics and feeds on a large quantity of fruits, often ingesting the seeds and defecating them intact. Seed dispersal by the lowland tapir in the southwestern Amazon was studied by examining seeds from 135 dung samples collected between 2005 and 2007. Seeds of a total of 122 plant species were identified, representing 68 genera and 33 families. The species accumulation curve showed that more species can be expected with further sampling. Many species (45%) were only encountered once, and only 10 percent of all species were found in >10 samples, indicating that the lowland tapir is an opportunistic forager. Seed diversity showed a clear seasonal pattern and was highly correlated with fruit availability. Seed diameter ranged from

We studied the habitat use, activity patterns and use of mineral licks by five species of Amazonian ungulate using data from four 60-d camera trap surveys at two different sites in the lowland rain forest of Madre de Dios, Peru. Camera traps were set out in two regular grids with 40 and 43 camera stations covering an area of 50 and 65 km2, as well as at five mineral licks. Using occupancy analysis we tested the hypothesis that species are spatially separated. The results showed that the grey brocket deer (Mazama gouazoubira) occurred almost exclusively in terra firme forests, and that the white-lipped peccary (Tayassu pecari) used floodplain forest more frequently during some surveys. All other species showed no habitat preference and we did not find any spatial avoidance of species. The white-lipped peccary, the collared peccary (Pecari tajacu) as well as the grey brocket deer were strictly diurnal while the lowland tapir (Tapirus terrestris) was nocturnal. The red brocket deer (Mazama americana) was active day and night. The tapir was the species with the highest number of visits to mineral licks (average 52.8 visits per 100 d) followed by the white-lipped peccary (average 16.1 visits per 100 d) and the red brocket deer (average 17.1 visits per 100 d). The collared peccary was only recorded on three occasions and the grey brocket deer was never seen at a lick. Our results suggest that resource partitioning takes place mainly at the diet level and less at a spatial level; however, differences in small-scale habitat use are still possible.

There have been few telemetry studies on large and medium-sized mammals from Neotropical lowland forests. This can partly be explained by the difficulty of tracking animals with radio-telemetry in these forests, often in remote areas with poor access due to limited transportation infrastructure. Researchers have been forced to follow their collared animals by aeroplane (Crawshaw 1995, Fragoso 1998, Rabinowitz & Nottingham 1986), but aerial telemetry is dangerous and involves difficult logistics and high costs. GPS (Global Positioning System) collars that allow the collection of data automatically at long intervals would be a good alternative. The effect of canopy cover on GPS fix success and location accuracy was of concern from the beginning and has been widely investigated in temperate forests (D'Eon 2003, Di Orio et al. 2003, Dussault et al. 1999, Moen et al. 1996, Rempel et al. 1995). All studies found a significant decrease in fix success and a large increase in location errors under forest canopy. Tropical lowland rain forests have a much denser canopy than temperate forests, and up to now the performance of GPS collars in tropical forest has been very poor. Rumiz & Venegas (2006) showed that while GPS collars worked in the dry forest of the Bolivian Chaco, they only obtained a successful fix in 1–3% of all attempts in the lowland forest of the Madidi National Park, Bolivia.

Mammal inventories in tropical forests are often difficult to carry out, and many elusive species are missed or only reported from interviews with local people. Camera traps offer a new tool for conducting inventories of large- and medium-sized terrestrial mammals. We evaluated the efficiency of camera traps based on data from two surveys carried out at a single site during 2 consecutive years. The survey efforts were 1440 and 2340 camera days, and 75 and 86% of the 28 large- and medium-sized terrestrial mammal species known to occur at the site were recorded. Capture frequencies for different species were highly correlated between the surveys, and the capture probability for animals that passed in front of the cameras decreased with decreasing size of the species. Camera spacing and total survey area had little influence on the number of species recorded, with survey effort being the main factor determining the number of recorded species. Using a model we demonstrated the exponential increase in survey effort required to record the most elusive species. We evaluated the performance of different species richness estimators on this dataset and found the Jackknife estimators generally to perform best. We give recommendations on how to increase efficiency of camera trap surveys exclusively targeted at species inventories.

The complex floodplains of large rivers offer a striking example of how geomorphology, by dictating patterns in the frequency and duration of soil saturation and surface flooding, influences ecosystem structure and function. This study draws on multiple sources of data from remote sensing, together with ground observations and water sampling, to distinguish floodplain ecosystems in the Madre de Dios River, a tributary of the Amazon River in Peru. This remote tropical river meanders across sub-Andean alluvial deposits in a tectonically active region and creates floodplain surfaces of varying ages, including terraces that are above the reach of present-day river floods. Data from Landsat ETM+ (optical multispectral), JERS-1 (L-band radar), and the Shuttle Radar Topography Mission (C-band interferometric Digital Elevation Models) were integrated in an object-oriented image analysis approach to distinguish five classes of floodplain vegetation. Vegetation classes generally correspond with successional age and reflect the activity of the riverine meander belt. Stage data for the river show erratic fluctuations and an annual range exceeding 8 m, but the maximum depth of floodplain inundation varied from > 1 m close to the river to approximately 0.1 m on more elevated terraces. The major ion composition of standing waters on the floodplain during the dry season indicated the importance of emergence of local groundwater in maintaining saturated soils, particularly further from the river, where backswamp vegetation is distinct and includes palm swamps. Thus, a hydrological continuum exists from deep but sporadic river inundation near the river to constant soil saturation by groundwater emergence in distal backswamps, reflecting the geomorphological origin and age of the floodplain deposits. This hydrogeomorphic continuum results in fundamental ecological differences. The exceptionally rich biodiversity of the sub-Andean region may be ascribed in part to the enhanced biodiversity associated with fluvial geomorphological features, and, thus, conservation planning must account for the diverse landforms created by fluvial dynamics.

We evaluated the usefulness of herbarium collection databases for assessing patterns of species diversity and distribution based on a dataset from the flowering plant families Moraceae and Myristicaceae from the Peruvian Amazon. For Moraceae, a total of 3523 collections were used representing 134 species. The Myristicaceae were represented by 2113 collections of 46 species. We evaluated the distribution of collections based on 252 grid cells (0.5° size) covering all lowland rainforest in the Peruvian Amazon. We found that collections were concentrated in a few cells and that species diversity clearly increases in relation to collection density. Moraceae were collected in only 45% and Myristicaceae in only 31% of the 252 grid cells. Fifty percent of the collections came from just six and three cells, respectively. Most species were represented by only a small number of collections and collected only in a few grid cells, meaning a few widespread common species tend to dominate the collection records. Not surprisingly, most collections were made close to towns and transport routes. We evaluated the usefulness of rarefaction curves and diversity estimators for comparing diversity between regions. These techniques seem to be of little use for botanical collections due to violations of underlying assumptions. Problems such as accuracy of geographic and taxonomic data and strong bias in the spatial representation of the whole dataset are important to consider when basing conservation analysis, planning, and decision-making on seemingly large databases of biodiversity collections and are discussed in detail.

Summary 1The success of large-scale cattle ranching in African savanna vegetation has often been limited by problems of bush encroachment and disease (in particular trypanosomiasis spread by tsetse flies). Mkwaja Ranch, occupying an area of 462 km2 on the coast of Tanzania, is a recent example of a large ranching enterprise that failed within the savanna environment. It was closed in 2000 after 48 years of operation. In this paper we describe the main vegetation types of the area (excluding closed forest vegetation) and relate their patterns of distribution to the former use of the ranch for cattle. 2The study area comprised the former ranch and parts of the adjacent Saadani Game Reserve, which had not been grazed by cattle for many years and had never been used for large-scale ranching. Following field surveys, 15 distinct types of grassland and bush vegetation were defined and a vegetation map was created using a Landsat TM satellite image. A multispectral classification using the maximum likelihood algorithm gave good results and enabled all 15 vegetation types to be distinguished on the map. 3Two main spatial trends were detected in the vegetation. One was a large-scale decrease in the cover of bushland from the most intensively used parts of the ranch through more extensively used areas to the game reserve; this trend was attributed to differences in management history as well as to climatic and topographic factors. A second trend was a radial vegetation pattern associated with the enclosures where cattle were herded at night. High amounts of three bushland types [dominated by (i) Acacia zanzibarica, (ii) Dichrostachys cinerea, Acacia nilotica or Acacia mellifera and (iii) Terminalia spinosa] occurred in a zone between 300 and 2500 m from the paddocks, with a peak in bush density at about 900 m (mean value for 18 paddocks). In contrast, bushland dominated by Hyphaene compressa was scarce close to the paddocks and became more abundant with distance. There was also a radial trend in the grassland communities: close to the paddocks there was short grass vegetation containing many ruderals and invasive weedy species, while the tall grassland types with species such as Hyperthelia dissoluta and Cymbopogon caesius occurred further away in the areas less affected by cattle. 4Synthesis and applications. The intensive modern livestock ranching as practised on Mkwaja Ranch proved to be unsustainable both economically and ecologically. In the end, the biggest problem faced by the ranch managers was not controlling disease, as had originally been feared, but preventing the spread of bush on pasture land. The results of our study demonstrate just how severe the problem of bush encroachment was, especially in areas close to paddocks. An important lesson for management is that grazing patterns need to be taken into consideration when determining the sustainable stocking rate for an area. To reduce the risk of bush encroachment in grazing systems with focal points such as paddocks or watering points, stocking rates need to be lower than in systems with a more uniform grazing distribution.

During 2008–2009, ticks were opportunistically collected from free-living lowland tapirs (Tapirus terrestris) and white-lipped peccaries (Tayassu pecari) during two studies of the ecology of Amazonian ungulates near or within two conservation areas in Madre de Dios, Peru. From tapirs, adults of the following tick species were collected: Amblyomma coelebs, Amblyomma incisum, Amblyomma latepunctatum, Amblyomma oblongoguttatum, Amblyomma ovale, and Amblyomma scalpturatum. Ticks collected from peccaries included adults of Amblyomma naponense and A. oblongoguttatum, nymphs of A. coelebs and A. latepunctatum, and larvae of Amblyomma sp. The 7 Amblyomma species collected in the present study have been previously reported in Peru. Although it is a common parasite of tapirs and/or peccaries in the Neotropical Region, we provide the first report of A. oblongoguttatum on tapirs in Peru. In addition, we provide the first report of A. coelebs and A. latepunctatum nymphs on peccaries. For nymphs of the latter ...