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Species distribution models (SDMs) can be useful for different conservation purposes. We discuss the importance of fitting spatial scale and using current records and relevant predictors aiming conservation. We choose jaguar (Panthera onca) as a target species and Brazil and Atlantic Forest biome as study areas. We tested two different extents (continent and biome) and resolutions (~4 Km and ~1 Km) in Maxent with 186 records and 11 predictors (bioclimatic, elevation, land-use and landscape structure). All models presented satisfactory AUC values (>0.70) and low omission errors (<23%). SDMs were scale-sensitive as the use of reduced extent implied in significant gains to model performance generating more constrained and real predictive distribution maps. Continental-scale models performed poorly in predicting potential current jaguar distribution, but they reached the historic distribution. Specificity increased significantly from coarse to finer-scale models due to the reduction of overprediction. The variability of environmental space (E-space) differed for most of climatic variables between continental and biome-scale and the representation of the E-space by predictors differed significantly (t = 2.42, g.l.= 9, P < 0.05). Refining spatial scale, incorporating landscape variables and improving the quality of biological data are essential for improving model prediction for conservation purposes.

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Aim  The aim of this study was to understand the spatial distribution of capybara (Hydrochoerus hydrochaeris) according to habitat attributes, using a multiscale approach based on fine‐ and broad‐scale variables in agroecosystems. Location  Piracicaba river basin, south‐eastern Brazil (22°00′–23°30′ S; 45°45′–48°30′ W). Methods  Potential habitats for capybara were selected in order to evaluate species presence/absence from October 2001 to December 2002. In each site, habitat attributes were sampled in the field (fine scale) and from GIS maps (broad scale) in terms of their presence or absence close to water. The variability of land cover between study sites was described by principal components analysis. Chi‐square tests were calculated for capybara presence/absence and the presence of each habitat attribute. A linear discriminant function analysis was used to describe to what extent the species’ presence could be explained by habitat attributes. Results  The species presence was predominantly related to flat open areas (slope ranging from 0% to 6%) (χ2 = 37.054, d.f. = 4, P < 0.001), covered by sugar cane or cultivated pasture (χ2 = 84.814, d.f. = 9, P < 0.001). Terrain curvature, water meadows, aquatic vegetation, forest cover and open areas resulted in the best combination of variables, explaining 69.7% of capybara occurrence in the study sites in this river basin. Main conclusions  Capybaras are widespread in the Piracicaba river basin, except in elevated areas. The spatial distribution of capybara was associated with the main types of land cover in the river basin – sugar cane plantations or pasture – both key food sources for capybara. This probably explains the species’ recent abundance in the region, since an intensive process of landscape alteration has taken place in this region owing to the expansion of agriculture in recent decades. These results may be useful in understanding the relationship between recent landscape modifications and the species’ population expansion in agroecosystems.

RESUMO -Na bacia do rio Corumbataí, a vegetação natural ocupa menos de 3% de sua área total, e a ausência dessa vegetação florestal tem levado ao aumento dos processos erosivos e ao desequilíbrio do regime hídrico de seus rios, causando diversos problemas no abastecimento de água de várias cidades, como Piracicaba e Rio Claro. Desse modo, existe a necessidade de um reflorestamento criterioso em áreas dessa bacia. No entanto, devido à limitação de recursos, é necessário que sejam realizados estudos de seleção de áreas prioritárias para que, com os recursos disponíveis, o ganho ambiental das áreas restauradas seja máximo. O objetivo deste trabalho foi desenvolver um método de priorização de áreas para restauração florestal baseado no uso de indicadores de sustentabilidade em microbacias. Cinco indicadores foram utilizados: porcentagem de mata nativa na APP; descontinuidade da vegetação nativa na bacia; diversidade da paisagem; variação média do uso da terra; e suscetibilidade à erosão. A seleção das microbacias para restauração das áreas de APP foi realizada por meio da ponderação linear dos indicadores e ordenamento das microbacias. Simulação inicial foi realizada para a seleção de 1.000 ha para restauração, e os resultados indicaram que os indicadores representam diferentes aspectos de sustentabilidade das microbacias. O método foi considerado útil na seleção de microbacias em condições extremas, diferenciando aquelas que necessitam de ações de conservação daquelas que necessitam de ações de restauração.Palavras-chave: Ecologia da paisagem, reflorestamento e bacia hidrográfica. INCORPORATING SUSTAINABILITY INDICATORS ON SITE SELECTION FOR FOREST RESTORATION IN THE CORUMBATAÍ RIVER BASIN

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RESUMOApesar da reconhecida importância da Mata Atlântica, há uma escassez de estudos utilizando o sensoriamento remoto como ferramenta para identificação e classificação dos diferentes estágios sucessionais de seus remanescentes florestais. Neste estudo comparamos o desempenho de diferentes métodos para classificação de estágio sucessional e investigamos a existência de sazonalidade na resposta espectral de uma floresta tropical densa na Mata Atlântica. Usamos amostras de treinamento de três estágios sucessionais obtidas a partir de uma ortofoto de 2010 e selecionamos imagens Landsat 5 TM para os anos de 2009, 2010 e 2011, considerando os meses de maiores e menores médias históricas de temperatura e precipitação. Para avaliação da sazonalidade da resposta espectral usamos o teste de Mann-Whitney, comparando cada banda do espectro eletromagnético e estágios sucessionais entre as épocas de aquisição das imagens. Para classificação da cobertura vegetal usamos três Índices de vegetação (NDVI, EVI e NDMI) e Análise Discriminante Quadrática (QDA). Comparamos a acurácia dos classificadores a partir de matrizes de validação cruzada. Nossos resultados mostram diferenças significativas entre os estágios sucessionais para todas as bandas espectrais, com melhor distinção na época de menores temperaturas e precipitação. QDA foi o classificador com maior acerto global (92%), seguido por NDMI (68%), NDVI (67%) e EVI (59%). Concluímos que QDA é, dentre os classificadores avaliados, o mais eficiente para classificação sucessional da floresta e que imagens obtidas em época de menor precipitação e temperatura geram uma melhor distinção entre estágios sucessionais para essa fisionomia florestal. PALAVRAS-CHAVE: Análise discriminante quadrática, Floresta tropical, Índices de vegetação. ABSTRACTDespite the recognized importance of the Atlantic Forest, there is a shortage of studies using remote sensing as a tool to identify and classify the different successional stages of its forest remnants. In this study we compared the performance of different classifiers on the determination of successional stages and investigated the existence of seasonality in the spectral response of a dense tropical Atlantic Forest area. We used training samples of three successional stages gathered by an orthophoto from the year of 2010 and selected Landsat 5 TM images for the years of 2009, 2010 and 2011, considering the months of higher and lower historical averages of temperature and precipitation. To evaluate the seasonality in forest spectral response we used the Mann-Whitney test, comparing each band and successional stage between the two studied periods. To classify the vegetation cover we used three indices (NDVI, EVI and NDMI) and a Quadratic Discriminant Analysis (QDA). We compared classifiers accuracy using a cross validation matrix. We found significative differences between successional stages on all electromagnetic spectral zones, with finer definitions between stages at the samples of colder and drier periods. QDA was the classifier with high...

Forests provide several ecosystem services and its presence near streams can increase water quality and quantity. In human--dominated landscapes such as agricultural lands, the forests are usually limited to a few patches. To improve the protection of water ways in these areas, we propose a methodological framework to: (i) assess the contribution of water-related ecosystem services offered by the present forest vegetation in the landscape, and (ii) prioritize areas for recovery and restoration actions. The methodology is based on a balance between local demand (physical variables) and supply (forest characteristics) of water-related services. This balance has the advantage of showing the amount of forest that currently has potential to provide services and the areas with higher deficit of services. Although this method still needs to be validated, its simplicity and easy replicability makes our methodology a rapid assessment of forest potential to provide water-related ecosystem services within agricultural areas.