How to not inflate population estimates? Spatial density distribution of white-lipped peccaries in a continuous Atlantic forest
D. Norris1, F. Rocha-Mendes1,2, S. Frosini de Barros Ferraz3, J. P. Villani4 & M. Galetti1
´ 1 Laboratorio de Biologia da Conservacao, Departamento de Ecologia, Universidade Estadual Paulista (UNESP), Rio Claro, SP, Brazil¸˜ 2 Neotropical Institute: Research and Conservation, Curitiba, PR, Brazil ˆ 3 Departamento de Ciencias Florestais, Escola Superior de Agricultura ‘Luiz de Queiroz’, Universidade de Sa Paulo, Piracicaba, SP, Brazil ˜o ´ 4 Parque Estadual da Serra do Mar – Nucleo Santa Virg´nia, Sa Luiz de Paraitinga, SP, Brazil ı ˜o
Keywords Atlantic forest; ENFA; MAXENT; presence only; protected area management;spatial prediction; species distribution monitoring; Tayassu pecari. Correspondence ´ Darren Norris, Laboratorio de Biologia da Conservacao, Departamento de Ecologia, ¸˜ Universidade Estadual Paulista (UNESP), Caixa Postal 199, Rio Claro, 13506-900 SP, Brazil. Tel/Fax: +55 51 3332 0762 Email: email@example.com Editor: Res Altwegg Received 13 November 2010; accepted 10 February 2011doi:10.1111/j.1469-1795.2011.00450.x
In a world with poor biological inventorying and rapid land-use change, predicting the spatial distribution of species is fundamental for the effective management and conservation of threatened taxa. However, on a regional scale, predicting the distribution of rare terrestrial mammals is often unreliable and/or impractical, especially in tropical forests. Weapply a recently developed analytic process that integrates density estimation (kernel smoothing), niche-analysis and geostatistics (regression-kriging) to model the occupancy and density distribution of a threatened population of white-lipped peccaries Tayassu pecari in a Brazilian Atlantic forest. Locations (n = 45) within a protected area of the Serra-do-Mar state park were obtained from diurnalline transect census (233 km), camera-trapping (751 camera-trap days) and surveys (4626 km) conducted by park rangers. Niche modelling (environmental niche-factor analysis and MAXENT) revealed a restricted niche compared with the available habitat as deﬁned by seven environmental variables. From the occupancy model obtained from regression-kriging, we found that 72% of a 170 km2 protected area islikely to be used by peccaries. We demonstrate that the distribution of large mammals can be restricted within continuous areas of Atlantic forest and therefore population estimates based on the size of protected areas can be overestimated. Our ﬁndings suggest that the generation of realized density distributions should become the norm rather than the exception to enable conservation managers andresearchers to extrapolate abundance and density estimates across continuous habitats and protected areas.
On a broad scale, the distribution of mammal species is largely predictable, making them appropriate subjects for landscape-scale analysis (Soares-Filho et al., 2006; Galetti et al., 2009). Yet, such broad-scale assessments overlook inherent and induced habitatheterogeneity, which can have a signiﬁcant impact on faunal communities. For example, Galetti et al. (2009) found that the abundance and biomass of mid- and large-bodied mammals varied by orders of magnitude among continuous areas of Atlantic forest, a variation equal to or greater than that recorded between forest fragments of different sizes (Chiarello, 2000; Cullen, Bodmer & Valladares-Pauda, 2000). On aregional scale, the cryptic nature, low abundances and heterogeneous distribution of mammalian species mean that predicting their distribution is often unreliable and or impractical, with some authors reporting that it is not possible to establish conservation priorities as it is not possible to detect patterns
in species occurrence throughout the remaining areas of Atlantic forest...