On the use of 10-minute point counts and 10-species lists for surveying birds in lowland Atlantic Forests in southeastern Brazil

Due to rapid and continuous deforestation, recent bird surveys in the Atlantic Forest are following rapid assessment programs to accumulate significant amounts of data during short periods of time. During this study, two surveying methods were used to evaluate which technique rapidly accumulated most species (> 90% of the estimated empirical value) at lowland Atlantic Forests in the state of São Paulo, southeastern Brazil. Birds were counted during the 2008-2010 breeding seasons using 10-minute point counts and 10-species lists. Overall, point counting detected as many species as lists (79 vs. 83, respectively), and 88 points (14.7 h) detected 90% of the estimated species richness. Forty-one lists were insufficient to detect 90% of all species. However, lists accumulated species faster in a shorter time period, probably due to the nature of the point count method in which species detected while moving between points are not considered. Rapid assessment programs in these forests will rapidly detect more species using 10-species lists. Both methods shared 63% of all forest species, but this may be due to spatial and temporal mismatch between samplings of each method.

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.