Range-wide declines of a key Neotropical ecosystem architect, the Near Threatened white-lipped peccary Tayassu pecari M a r i a n a A l t r i c h t e r , A n d r e w T a b e r , H a r a l d B e c k , R a f a e l R e y n a -H u r t a d o L e o n i d a s L i z a r r a g a , A l e x i n e K e u r o g h l i a n and E r i c W . S a n d e r s o n Abstract We report a range-wide status assessment of a key Neotropical ecosystem architect, the white-lipped peccary Tayassu pecari, categorized as Near Threatened on the IUCN Red List, using published information and unpublished data from 41 scientists in 15 range countries. We estimate that the white-lipped peccary has been extirpated in 21% of its historical range over the last 100 years, with reduced abundance and a low to medium probability of long-term survival in another 48% of its current range. We found major range declines in Argentina, Paraguay, southern Brazil, Colombia, Venezuela, north-east Brazil, Mexico and Costa Rica. This species is particularly at risk in more xeric ecosystems, especially the caatinga, cerrado and pampas. Hunting and habitat destruction are the most severe threats, although there are also unexplained sudden die-offs suggestive of disease. We evaluate our results in light of this species' important interspecific interactions and its role as an ecosystem architect. One of our recommendations is that conservation efforts should focus on landscape conservation of large, continuous and ecologically intact areas containing a mosaic of different habitat types.This paper contains supplementary material that can be found online at
Forest biodiversity conservation and species distribution modeling greatly benefit from broad-scale forest maps depicting tree species or forest types rather than just presence and absence of forest, or coarse classifications. Ideally, such maps would stem from satellite image classification based on abundant field data for both model training and accuracy assessments, but such field data do not exist in many parts of the globe. However, different forest types and tree species differ in their vegetation phenology, offering an opportunity to map and characterize forests based on the seasonal dynamic of vegetation indices and auxiliary data. Our goal was to map and characterize forests based on both land surface phenology and climate patterns, defined here as forest phenoclusters. We applied our methodology in Argentina (2.8 million km 2 ), which has a wide variety of forests, from rainforests to cold-temperate forests. We calculated phenology measures after fitting a harmonic curve of the enhanced vegetation index (EVI) time series derived from 30-m Sentinel 2 and Landsat 8 data from 2018-2019. For climate, we calculated land surface temperature (LST) from Band 10 of the thermal infrared sensor (TIRS) of Landsat 8, and precipitation from Worldclim (BIO12). We performed stratified X-means cluster classifications followed by hierarchical clustering. The resulting clusters separated well into 54 forest phenoclusters with unique combinations of vegetation phenology and climate characteristics. The EVI 90th percentile was more important than our climate and other phenology measures in providing separability among different forest phenoclusters. Our results highlight the potential of combining remotely sensed phenology measures and climate data to improve broad-scale forest mapping for different management and conservation goals, capturing functional rather than structural or compositional characteristics between and within tree species. Our approach results in classifications that go beyond simple forest-nonforest in areas where the lack of detailed ecological field data precludes tree species-level classifications, yet
SUMMARYIn many developing countries, high rates of deforestation and biodiversity loss make conservation efforts urgent. Improving existing land-use plans can be an option for enhancing biodiversity conservation. We showcase an approach to enhancing an existing forest land-use plan using widely available data and spatial tools, focusing on Argentina's Southern Yungas ecoregion. We mapped the distribution of wilderness areas and species and habitats of conservation concern, assessed their representation in the land-use plan and quantified potential changes in habitat availability and forest connectivity. Wilderness comprised 48% of the study area, and the highest concentrations of elements of conservation concern were in the north. In the current land-use plan, wilderness areas often occur in regions where logging and grazing are allowed, and a large proportion of the forest with the highest conservation value (43%) is under some level of human influence. Furthermore, we found that deforestation being legally allowed in the land-use plan could reduce forest connectivity and habitat availability substantially. We recommend updating the current land-use plan by considering human influence and elements of conservation concern. More broadly, we demonstrate that widely available spatial datasets and straightforward approaches can improve the usefulness of existing land-use plans so that they more fully incorporate conservation goals.
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