840 R. Costa‐Araújo et al.


FIG. 2 Geographical distribution and potential habitat of Plecturocebus vieirai in the Tapajós–Xingu interfluve: (a) records of P. vieirai and Plecturocebus moloch, and habitat suitability modelled using environmental variables; (b) suitable forest habitat area in 2020; (c) modelled potentially suitable habitat area in 2044. AOH, area of habitat (based on environmental suitability and forest availability).


vary from 0 to 1 based on the specificity and sensitivity of the species’ response to environmental variables.We selected models with AUC .0.7 and TSS .0.4 (Buisson et al., 2010) using the mean suitability value of each grid (2.5-min scale) and the minimum omission method (Silva et al., 2017, 2020). To identify the environmental variables that best explain the occurrence of the species we used the jackknife test (Phillips et al., 2006). Using ArcGIS 10.1 (Esri, Redlands,USA),we delimited the geographical distribution of P. vieirai from the occurrence records, the ensemble model, knowledge of the distribu- tion of congeneric, neighbouring species and considering that rivers restrict the occurrence of primate species in Amazonia (Mourthé et al., 2022). Finally, we overlaid the species distribution with raster layers of vegetation classes (Souza et al., 2020), elevation (which is a constraint for species occurrence; Jarvis et al., 2008) and forest cover (Soares-Filho et al., 2006), to extract the area of suitable habitat available for P. vieirai in the present (2020) and in the future (2044). We used a threshold of 24 years, repre- senting three P. vieirai generations (Veiga et al., 2011; Defler&García, 2012), as a baseline to estimate the availabil- ity of suitable habitat in the future and to assess the species’ conservation status. We calculated the extent of occurrence and the area of suitable habitat (Brooks et al., 2019)in 2020


and in 2044 using the R package red (Cardoso, 2017, 2018). We validated the area of suitable habitat using our dataset of location records overlain on a binary map of presence or absence predicted from the environmental variables. We used the data from our linear transect surveys to es-


timate population density and sighting rates with Distance 7.1 (Thomas et al., 2010). We carried out this analysis by pooling all sightings from the four survey areas using the hazard-rate model, a simple polynomial adjustment and 45 m as the effective sighting distance (χ2 = 0.80;df = 3; P=0.84); the final model was selected using the Akaike information criterion. We used the oldest available satellite data of forest cover over the species range (1985; Souza et al., 2020) as a conservative baseline to extract an approxi- mate estimate of the original habitat area of P. vieirai.


Results


We gathered 96 occurrence records of P. vieirai in addition to the three records available from the species description: 90 from fieldwork, four from the literature (Miranda et al., 2014; Vendramel, 2016) and two from specimens stored in the Museu Paraense Emílio Goeldi (MPEG 246, 21837; Supplementary Table 2). All records are from


Oryx, 2022, 56(6), 837–845 © The Author(s), 2022. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S003060532100171X


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