Uncertainty in assessing the impacts of global change with coupled dynamic species distribution and population models. (31st December 2012)

• Record Type: Journal Article
• Authors: Conlisk, Erin; Syphard, Alexandra D.; Franklin, Janet; Flint, Lorraine; Flint, Alan; Regan, Helen
• Is Part Of: Global change biology. Volume 19:Number 3(2013:Mar.)
• Page Start: 858
• Page End: 869
• Publication Date: 2012-12-31
• Subjects: annual plant -- climate change -- conservation management -- coupled model -- habitat suitability -- invasive plants -- land‐use change -- uncertainty; Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.12090
• Languages: English
• ISSNs: 1354-1013

Abstract

Abstract: Concern over rapid global changes and the potential for interactions among multiple threats are prompting scientists to combine multiple modelling approaches to understand impacts on biodiversity. A relatively recent development is the combination of species distribution models, land‐use change predictions, and dynamic population models to predict the relative and combined impacts of climate change, land‐use change, and altered disturbance regimes on species' extinction risk. Each modelling component introduces its own source of uncertainty through different parameters and assumptions, which, when combined, can result in compounded uncertainty that can have major implications for management. Although some uncertainty analyses have been conducted separately on various model components – such as climate predictions, species distribution models, land‐use change predictions, and population models – a unified sensitivity analysis comparing various sources of uncertainty in combined modelling approaches is needed to identify the most influential and problematic assumptions. We estimated the sensitivities of long‐run population predictions to different ecological assumptions and parameter settings for a rare and endangered annual plant species ( Acanthomintha ilicifolia, or San Diego thornmint). Uncertainty about habitat suitability predictions, due to the choice of species distribution model, contributed most to variation in predictions about long‐run populations.