Environmental suitability of a highly fragmented and heterogeneous landscape for forest bird species in south-eastern Brazil

Assessment of the suitability of anthropogenic landscapes for wildlife species is crucial for setting priorities for biodiversity conservation. This study aimed to analyse the environmental suitability of a highly fragmented region of the Brazilian Atlantic Forest, one of the world's 25 recognized biodiversity hotspots, for forest bird species. Eight forest bird species were selected for the analyses, based on point counts (n = 122) conducted in April-September 2006 and January-March 2009. Six additional variables (landscape diversity, distance from forest and streams, aspect, elevation and slope) were modelled in Maxent for (1) actual and (2) simulated land cover, based on the forest expansion required by existing Brazilian forest legislation. Models were evaluated by bootstrap or jackknife methods and their performance was assessed by AUC, omission error, binomial probability or p value. All predictive models were statistically significant, with high AUC values and low omission errors. A small proportion of the actual landscape (24.41 +/- 6.31%) was suitable for forest bird species. The simulated landscapes lead to an increase of c. 30% in total suitable areas. In average, models predicted a small increase (23.69 +/- 6.95%) in the area of suitable native forest for bird species. Being close to forest increased the environmental suitability of landscapes for all bird species; landscape diversity was also a significant factor for some species. In conclusion, this study demonstrates that species distribution modelling (SDM) successfully predicted bird distribution across a heterogeneous landscape at fine spatial resolution, as all models were biologically relevant and statistically significant. The use of landscape variables as predictors contributed significantly to the results, particularly for species distributions over small extents and at fine scales. This is the first study to evaluate the environmental suitability of the remaining Brazilian Atlantic Forest for bird species in an agricultural landscape, and provides important additional data for regional environmental planning.

Modeling the Potential Geographic Distribution of Black Pepper (Piper nigrum) in Asia Using GIS Tools

Known as the "king of spices", black pepper (Piper nigrum), a perennial crop of the tropics, is economically the most important and the most widely used spice crop in the world. To understand its suitable bioclimatic distribution, maximum entropy based on ecological niche modeling was used to model the bioclimatic niches of the species in its Asian range. Based on known occurrences, bioclimatic areas with higher probabilities are mainly located in the eastern and western coasts of the Indian Peninsula, the east of Sumatra Island, some areas in the Malay Archipelago, and the southeast coastal areas of China. Some undocumented places were also predicted as suitable areas. According to the jackknife procedure, the minimum temperature of the coldest month, the mean monthly temperature range, and the precipitation of the wettest month were identified as highly effective factors in the distribution of black pepper and could possibly account for the crop's distribution pattern. Such climatic requirements inhibited this species from dispersing and gaining a larger geographical range.

Species Distribution Modeling for Conservation Purposes

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 (similar to 4 Km and similar to 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.I. = 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.

Pollination services at risk: Bee habitats will decrease owing to climate change in Brazil

Native bees are important providers of pollination services, but there are cumulative evidences of their decline. Global changes such as habitat losses, invasions of exotic species and climate change have been suggested as the main causes of the decline of pollinators. In this study, the influence of climate change on the distribution of 10 species of Brazilian bees was estimated with species distribution modelling. We used Maxent algorithm (maximum entropy) and two different scenarios, an optimistic and a pessimistic, to the years 2050 and 2080. We also evaluated the percentage reduction of species habitat based on the future scenarios of climate change through Geographic Information System (GIS). Results showed that the total area of suitable habitats decreased for all species but one under the different future scenarios. The greatest reductions in habitat area were found for Melipona bicolor bicolor and Melipona scutellaris, which occur predominantly in areas related originally to Atlantic Moist Forest. The species analysed have been reported to be pollinators of some regional crops and the consequence of their decrease for these crops needs further clarification. (C) 2012 Elsevier B.V. All rights reserved.