Including species interactions in risk assessments for global change

Abstract

Most ecological risk assessments for global change are restricted to the effects of trends in climate or atmospheric carbon dioxide. In order to move beyond investigation of the effects of climate alone, the CLIMEXt model was extended to investigate the effects of species interactions, in the same or different trophic levels, along environmental gradients on a geographical scale. Specific needs that were revealed during the investigations include: better treatment of the effects of temporal and spatial climatic variation; elucidation of the nature of boundaries of species ranges; data to quantify the role of species traits in interspecies interactions; integrated observational, experimental, and modelling studies on mechanisms of species interactions along environmental gradients; and high-resolution global environmental datasets. Greater acknowledgement of the shared limitations of simplified models and experimental studies is also needed. Above all, use of the scientific method to understand representative species ranges is essential. This requires the use of mechanistic approaches capable of progressive enhancement.

The change of the potential occurence of Colorado Potato Beetle (Leptinotarsa decemlineata, Say 1824) in the Czech Republic till 2050

“…Výstupem simulace vývoje mandelinky bramborové v závislosti na teplotách prostředí je ekoklimatický index (EI) vyjadřující vhodnost klimatických podmínek pro etablování a dlouhodobý výskyt populace škůdce na dané lokalitě. EI obecně dosahuje hodnot 0-100, kde hodnota 0 indikuje lokalitu nevhodnou pro dlouhodobý výskyt modelovaného druhu a EI větší než 30 reprezentuje velmi příznivé klima pro výskyt (SU-THERST, MYAWALD, 1985SUTHERST et al, 2001. HODDLE (2003) považuje lokality již s hodnotou EI vyšší než 25 za velmi vhodné pro populační růst a výskyt druhu, hodnota EI 10-25 za vhodné a hodnota EI nižší než 10 indikuje mezní lokality pro vý-skyt.…”

Predicted decrease in global climate suitability masks regional complexity of invasive fruit fly species response to climate change

“…hot/cold and wet/dry) to calculate an Ecoclimatic Index (EI) (Sutherst et al 2007;Macfadyen and Kriticos 2012). The EI can then be determined across spatially explicit climate data to estimate the suitability of each grid cell (ranging from completely unsuitable to optimal) (see methods; Sutherst et al 2007). CLIMEX is thus able to avoid some of the issues involved with transferability associated with ENMs, as the model is rebuilt de novo for climate change scenarios rather than being extrapolated from current distributional estimates (Webber et al 2011).…”

“…This GI is then combined with stress indices (e.g. hot/cold and wet/dry) to calculate an Ecoclimatic Index (EI) (Sutherst et al 2007;Macfadyen and Kriticos 2012). The EI can then be determined across spatially explicit climate data to estimate the suitability of each grid cell (ranging from completely unsuitable to optimal) (see methods; Sutherst et al 2007).…”

“…Thus, SDMs that rely on at least a partial mechanistic understanding of the species-environment relationship are perhaps more appropriate tools in predicting distributions under climate change and biological invasion scenarios. One such SDM is CLIMEX (Hearne Scientific Software Pty Ltd, Australia) (Sutherst & Maywald 1985;Sutherst et al 2007) which employs a semi-mechanistic approach to examine the relationship between climate, species distributions and patterns of growth (Macfadyen and Kriticos, 2012). CLIMEX models are typically fitted using a combination of empirically measured life history parameters (e.g.…”

For switchgrass cultivated as biofuel in California, invasiveness limited by several steps

“…There are numerous methods for estimating the bioclimatic envelope, including CLIMEX, Maxent, GARP, BIOCLIM, classification and regression tree, and simple logistic regression. CLIMEX has been used to model the distribution of biocontrol agents (Poutsma et al 2008), poikilothermic (cold-blooded) animals (Sutherst et al 2007) and many invasive plant species (Holt and Boose 2000;Kriticos et al 2005;Pattison and Mack 2008). The strength of CLIMEX for invasive species applications is that the model can be based on the historical range (e.g., from herbarium data) and supplemented with empirically derived biological and physiological data (Sutherst et al 1999).…”