Species distribution modeling in the tropics: problems, potentialities, and the role of biological data for effective species conservation

In this paper we aim to investigate the problems and potentialities of species distribution modeling (SDM) as a tool for conservation planning and policy development and implementation in tropical regions. We reviewed 123 studies published between 1995 and 2007 in five of the leading journals in ecology and conservation, and examined two tropical case studies in which distribution modeling is currently being applied to support conservation planning. We also analyzed the characteristics of data typically used for fitting models within the specific context of modeling tree species distribution in Central America. The results showed that methodological papers outnumbered reports of SDMs being used in an applied context for setting conservation priorities, particularly in the tropics. Most applications of SDMs were in temperate regions and biased towards certain organisms such as mammals and birds. Studies from tropical regions were less likely to be validated than those from temperate regions. Unpublished data from two major tropical case studies showed that those species that are most in need of conservation actions, namely those that are the rarest or most threatened, are those for which SDM is least likely to be useful. We found that only 15% of the tree species of conservation concern in Central America could be reliably modelled using data from a substantial source (Missouri Botanical Garden VAST database). Lack of data limits model validation in tropical areas, further restricting the value of SDMs. We concluded that SDMs have a great potential to support biodiversity conservation in the tropics, by supporting the development of conservation strategies and plans, identifying knowledge gaps, and providing a tool to examine the potential impacts of environmental change. However, for this potential to be fully realized, problems of data quality and availability need to be overcome. Weaknesses in current biological datasets need to be systematically addressed, by increasing collection of field survey data, improving data sharing and increasing structural integration of data sources. This should include use of distributed databases with common standards, referential integrity, and rigorous quality control. Integration of data management with SDMs could significantly add value to existing data resources by improving data quality control and enabling knowledge gaps to be identified

Applying Climatically Associated Species Pools to modelling compositional change in tropical montane forests

Aim Predictive species distribution modelling is a useful tool for extracting the maximum amount of information from biological collections and floristic inventories. However, in many tropical regions records are only available from a small number of sites. This can limit the application of predictive modelling, particularly in the case of rare and endangered species. We aim to address this problem by developing a methodology for defining and mapping species pools associated with climatic variables in order to investigate potential species turnover and regional species loss under climate change scenarios combined with anthropogenic disturbance. Location The study covered an area of 6800 km(2) in the highlands of Chiapas, southern Mexico. Methods We derived climatically associated species pools from floristic inventory data using multivariate analysis combined with spatially explicit discriminant analysis. We then produced predictive maps of the distribution of tree species pools using data derived from 451 inventory plots. After validating the predictive power of potential distributions against an independent historical data set consisting of 3105 botanical collections, we investigated potential changes in the distribution of tree species resulting from forest disturbance and climate change. Results Two species pools, associated with moist and cool climatic conditions, were identified as being particularly threatened by both climate change and ongoing anthropogenic disturbance. A change in climate consistent with low-emission scenarios of general circulation models was shown to be sufficient to cause major changes in equilibrium forest composition within 50 years. The same species pools were also found to be suffering the fastest current rates of deforestation and internal forest disturbance. Disturbance and deforestation, in combination with climate change, threaten the regional distributions of five tree species listed as endangered by the IUCN. These include the endemic species Magnolia sharpii Miranda and Wimmeria montana Lundell. Eleven vulnerable species and 34 species requiring late successional conditions for their regeneration could also be threatened. Main conclusions Climatically associated species pools can be derived from floristic inventory data available for tropical regions using methods based on multivariate analysis even when data limitations prevent effective application of individual species modelling. Potential consequences of climate change and anthropogenic disturbance on the species diversity of montane tropical forests in our study region are clearly demonstrated by the method

Remote sensing and the future of landscape ecology

Landscape ecology focuses on the analysis of spatial pattern and its relationship to ecological processes. As a scientifi c discipline, landscape ecology has grown rapidly in recent years, supported by developments in GIS and spatial analysis techniques. Although remote sensing data are widely employed in landscape ecology research, their current and potential roles have not been evaluated critically. To provide an overview of current practice, 438 research papers published in the journal Landscape Ecology for the years 2004–2008 were examined for information about use of remote sensing. Results indicated that only 36% of studies explicitly mentioned remote sensing. Of those that did so, aerial photographs and Landsat satellite sensor images were most commonly used, accounting for 46% and 42% of studies, respectively. The predominant application of remote sensing data across these studies was for thematic mapping purposes. This suggests that landscape ecologists have been relatively slow to recognize the potential value of recent developments in remote sensing technologies and methods. The review also provided evidence of a frequent lack of key detail in studies recently published in Landscape Ecology, with 75% failing to provide any assessment of uncertainty or error relating to image classifi cation and mapping. It is suggested that the role of remote sensing in landscape ecology might be strengthened by closer collaboration between researchers in the two disciplines, by greater integration of diverse remote sensing data with ecological data, and by increased recognition of the value of remote sensing beyond land-cover mapping and pattern description. This is illustrated by case studies drawn from Latin America (focusing on forest loss and fragmentation) and the UK (focusing on habitat quality for woodland birds). Such approaches might improve the analytical and theoretical rigour of landscape ecology, and be applied usefully to issues of outstanding societal interest, such as the impacts of environmental change on biodiversity and ecosystem services