Strength of Habitat and Landscape Metrics in Predicting Golden‐Headed Lion Tamarin Presence or Absence in Forest Patches in Southern Bahia, Brazil

Abstract

We investigated the effects of forest fragmentation on golden-headed lion tamarins (Leontopithecus chrysomelas) by qualitatively and quantitatively characterizing the landscape throughout the species range, conducting surveys, and exploring predictive models of presence and absence. We identified 784 forest patches that varied in size, shape, core area, habitat composition, elevation, and distance to neighboring patches and towns. We conducted 284 interviews with local residents and 133 playback experiments in 98 patches. Results indicated a reduction in the western portions of the former species range. We tested whether L. chrysomelas presence or absence was related to the aforementioned fragmentation indices using Monte Carlo logistic regression techniques. The analysis yielded a majority of iterations with a one-term final model of which Core Area Index (percent of total area that is core) was the only significant type. Model concordance ranged between 65 and 90 percent. Area was highlighted for its potential predictive ability. Although final models for area lacked significance, their failure to reach significance was marginal and we discuss potential confounding factors weakening the term's predictive ability. We conclude that lower Core Area Index scores are useful indicators of forest patches at risk for not supporting L. chrysomelas. Taken together, our analyses of the landscape, survey results, and logistic regression modeling indicated that the L. chrysomelas metapopulation is facing substantial threat. The limited vagility of lion tamarins in nonforest matrix may lead to increasingly smaller and inbred populations subject to significant impact from edge effects and small population size. Local extinction is imminent in many forest patches in the L. chrysomelas range.Abstract in Portuguese is available at

Occurrences of the Golden-Headed Lion Tamarin (Leontopithecuschrysomelas) Above 500 Meters in Southern Bahia, Brazil and Implications for Conservation Planning

“…The GHLT Connection surveyed forest patches 2005 and November 2007 using playback methods outlined in Raboy et al (2010). When L. chrysomelas were sighted, a GPS point was taken.…”

“…The golden-headed lion tamarin (Leontopithecus chrysomelas) inhabits wet coastal and inland semi-deciduous forests in the northern Atlantic forest, extending through southern Bahia and, in the past, northwest Minas Gerais (Pinto and Rylands 1997;Raboy et al 2010). It is classiloss and fragmentation resulting from conversion of forest and shade-cocoa agroforest to cattle pasture or other agricultural crops.…”

Identifying Important Forest Patches for the Long-Term Persistence of the Endangered Golden-Headed Lion Tamarin (Leontopithecus Chrysomelas)

“…However, a more recent survey suggests the possibility of a considerable population size and range reduction since then [25]. Forest cover in this region is characterized by highly deforested and fragmented seasonal semi-deciduous tropical rainforest in the west and more contiguous coastal evergreen tropical rainforest in the east.…”

“…We concluded our analyses by comparing the patches where we would expect to find GHLTs based on the modeling work presented here with the patches that are actually occupied by GHLTs. We overlaid 90 positive survey locations collected between 2005-2008 by the Conexão Mico Leão survey project [25,43] over the 2007 mosaic. "Positive survey locations" included confirmed sightings of and vocalizations from GHLTs by field teams in playback studies as well as recent sightings by local residents with high forest knowledge [25].…”

“…We overlaid 90 positive survey locations collected between 2005-2008 by the Conexão Mico Leão survey project [25,43] over the 2007 mosaic. "Positive survey locations" included confirmed sightings of and vocalizations from GHLTs by field teams in playback studies as well as recent sightings by local residents with high forest knowledge [25]. Some survey locations did not directly align with a forest patch in our classification (37 points), and we assigned these points to the nearest patch.…”