Botanical richness and endemicity patterns of Borneo derived from species distribution models

Abstract

This study provides a Borneo-wide, quantitative assessment of botanical richness and endemicity at a high spatial resolution, and based on actual collection data. To overcome the bias in collection effort, and to be able to predict the presence and absence of species, even for areas where no collections have been made, we constructed species distribution models (SDMs) for all species taxonomically revised in Flora Malesiana. Species richness and endemicity maps were based on 1439 significant SDMs. Mapping of the residuals of the richness-endemicity relationship identified areas with higher levels of endemicity than can be expected on the basis of species richness, the endemicity hotspots. We were able to identify one previously unknown region of high diversity, the high mountain peaks of East Kalimantan; and two additional endemicity hotspots, the Müller Mountains and the Sangkulirang peninsula. The areas of high diversity and endemicity were characterized by a relatively small range in annual temperature, but with seasonality in temperatures within that range. Furthermore, these areas were least affected by El Niño Southern Oscillation drought events. The endemicity hotspots were found in areas, which were ecologically distinct in altitude, edaphic conditions, annual precipitation, or a combination of these factors. These results can be used to guide conservation efforts of the highly threatened forests of Borneo.

Ecology and Evolution of Melanism in Big Cats: Case Study with Black Leopards and Jaguars

“…Since correlation among explanatory predictors can lead to model overfitting, we computed Pearson's correlation coefficient (r) between each pair of variables [31][32][33]. The correlation was assessed by extracting predictor information from 10,000 unique and randomly generated points within the present geographic distribution layer of both species (obtained from IUCN and complemented with our own database records).…”

Partial versus Full Species Distribution Models

“…To date, this has resulted in two textbooks on the principles and applications of SDMs by Franklin (2009) and Peterson et al (2011), and in numerous review and perspectives papers. The popularity can be ascribed to the application of SDMs in the fields of species discovery (Raxworthy et al 2003), mapping biodiversity (Raes et al 2009;van Welzen et al 2011), conservation planning (Zhang et al 2012), climate change effects (Hsu et al 2011), species' invasions (Broennimann & Guisan 2008), evolution of niches (Yesson & Culham 2006;Evans et al 2009), to list but a few (see Araújo & Peterson (2012) for an extensive list).…”

New insights on phylogeography and distribution of painted frogs (Discoglossus) in northern Africa and the Iberian Peninsula

“…The final models were reclassified in ArcGIS 10 (ESRI) into binary presenceabsence maps based on the assumption that ten percent of the records were either wrongly identified or georeferenced, meaning, that the 10% of model outputs with the lowest predicted probabilities fall into the 'absence' region of the threshold model, and 'presence' regions include the 90% of distribution records with the highest model values (Raes et al, 2009). All models were tested with receiver operating characteristics (ROC) curve plots, and the area under the curve (AUC) of the ROC plot of ten models was taken as a measure of the overall fit of each model.…”