Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.
نویسندگان
چکیده
Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.
منابع مشابه
The Influence of Climate Change on distribution of an Endangered Medicinal Plant (Fritillaria Imperialis L.) in Central Zagros
Climate change has a great impact on the species distribution range and many endangered plant species. Fritillaria imperialis as a species that is native to Central Zagros, Iran is a medicinal plant with great ecological and commercial profits. Its population has decreased considerably and the species would be endangered in later decades. Understanding the habitat needs of this species, evaluat...
متن کاملPredicting the geographical distribution of Alopecurus textilis Boiss rangeland species on basis Consensus approach of climate change in Mazandaran province
The climate changes have an important role in distribution of plant species. Statistical species distribution models (SDMs) are widely used to predict the changes in species distribution under climate change scenarios. In the peresent study, the distribution of Alopecurus textilis in the current and future climate condition (2050) under the influence of climate change and two scenarios of RCP 4...
متن کاملCorrelative and mechanistic models of species distribution provide congruent forecasts under climate change
Good forecasts of climate change impacts on extinction risks are critical for effective conservation management responses. Species distribution models (SDMs) are central to extinction risk analyses. The reliability of predictions of SDMs has been questioned because models often lack a mechanistic underpinning and rely on assumptions that are untenable under climate change. We show how integrati...
متن کاملModeling the current and future suitable habitat distribution of Fritillaria imperialis under climate change scenarios and using three general circulation model in Iran
Climate change may pose challenges to the conservation of plant species such as the Fritillaria imperialis that have narrow geographical distribution. In this study, the modeling suitable habitats of F.imperialis in Iran was done in the current condition and under climate change (2050). For this purpose, 78 species presence data along with 12 environmental variables including bioclimatic, physi...
متن کاملModelling the responses of Andean and Amazonian plant species to climate change: the effects of georeferencing errors and the importance of data filtering
Aim Species distribution models are a potentially powerful tool for predicting the effects of global change on species distributions and the resulting extinction risks. Distribution models rely on relationships between species occurrences and climate and may thus be highly sensitive to georeferencing errors in collection records. Most errors will not be caught using standard data filters. Here ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Biology letters
دوره 4 5 شماره
صفحات -
تاریخ انتشار 2008