Predicted insect diversity declines under climate change in an already impoverished region

Maes, Dirk; Titeux, Nicolas; Hortal, Joaquín; Anselin, Anny; Decleer, Kris; Knijf, Geert De; Fichefet, Violaine; Luoto, Miska

doi:10.1007/s10841-010-9277-3

Cited by 52 publications

(24 citation statements)

References 63 publications

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“…Forward‐looking approaches that explore future changes in species distributions and richness in a range of species groups are essential anticipatory tools in conservation planning (Franklin, ; Titeux et al., ). Apart from being useful at large scales, there is a growing interest in applying such tools in geographically restricted areas of conservation relevance and at fine spatial resolutions that closely match the scale of decision‐making processes for local conservation practitioners (Maes et al., ). Although our results in Spain indicate that local models may produce estimates of future changes in species richness that are similar to the outcomes of continental models, projections based on local models in Finland and Belgium/Netherlands deviate strongly from those derived from the continental models.…”

Section: Discussionmentioning

confidence: 99%

The need for large‐scale distribution data to estimate regional changes in species richness under future climate change

Titeux

Maes

Daele

et al. 2017

Diversity and Distributions

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Aim: Species distribution models built with geographically restricted data often fail to capture the full range of conditions experienced by species across their entire distribution area. Using such models to predict distribution shifts under future environmental change may, therefore, produce biased projections. However, restricted-scale models have the potential to include a larger sample of taxa for which distribution data are available and to provide finer-resolution projections that are better applied to conservation planning than the forecasts of broad-scale models. We examine the circumstances under which the projected shifts in species richness patterns derived from restricted-scale and broad-scale models are most likely to be similar. Location: Europe.Methods: The distribution of butterflies in Finland, Belgium/Netherlands and Spain was modelled based on restricted-scale (local) and broad-scale (continental) distribution and climate data. Both types of models were projected under future climate change scenarios to assess potential changes in species richness.Results: In Finland, species richness was projected to increase strongly based on restricted-scale models and to decrease slightly with broad-scale models. In Belgium/ Netherlands, restricted-scale models projected a larger decrease in richness than Settele et al.

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Section: Discussionmentioning

confidence: 99%

The need for large‐scale distribution data to estimate regional changes in species richness under future climate change

Titeux

Maes

Daele

et al. 2017

Diversity and Distributions

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“…We used General Linear Models (GLM; McCullagh & Nelder 1989) for both modelling processes, as the ability of these methods to capture species responses to environmental gradients is rooted in a strong theoretical background (Austin et al 1990;Austin 2002;Maes et al 2010). Presence/absence data were modelled using logistic regression (logit regression with logarithmic link function), and common multinomial regression was used to model the dominance (assuming normal distribution for the variable and identity as the link function with the predictors).…”

Section: Discussionmentioning

confidence: 99%

Assessing the areas under risk of invasion within islands through potential distribution modelling: The case of Pittosporum undulatum in São Miguel, Azores

Hortal

Borges

Jiménez‐Valverde

et al. 2010

Journal for Nature Conservation

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a b s t r a c tNon-indigenous plant species have been frequently reported as successful invaders in island environments, changing plant community composition and structure. This is the case of the sweet pittosporum (Pittosporum undulatum), native from Australia, which is one of the most successful plant invaders in the Azores archipelago. Data extracted from recent forestry inventories were used to model and map the potential distribution of P. undulatum in São Miguel, the larger island of the Azores. Current distribution of P. undulatum is related to climate, altitude and some human activity effects. Further analysis of the areas under risk of invasion showed that protected areas are under potential threat, although only a few native forest remnants seem to be threatened due to future expansion of P. undulatum, since the current distribution of these native communities has been reduced due to clearing and competition with invasive plants. We discuss the threats that any further expansion of the species will represent for low-altitude native forests, as well as the utility of species distribution models in the assessment of the areas under risk of invasion.

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“…Many studies have predicted the consequences of expected climate change on biodiversity (Bellard et al, 2012;Staudinger et al, 2013;Pacifici et al, 2015). For instance, future climate change is predicted to induce latitudinal or altitudinal shifts in species ranges with important effects on ecological communities (Maes et al, 2010;Barbet-Massin & Jetz, 2015), to increase the risks of species extinction (Thomas et al, 2004;Urban, 2015) or to reduce the effectiveness of conservation areas (Ara ujo et al, 2011). Projections of land-use/cover change have been used to predict future changes in suitable habitats for a number of species (Martinuzzi et al, 2015;Newbold et al, 2015), to predict future plant invasions (Chytr y et al, 2012), to estimate potential future extinctions in biodiversity hotspots (Jantz et al, 2015) or to highlight the restricted potential for future expansion of protected areas worldwide (Pouzols et al, 2014).…”

Section: Emphasis On Climate Change Impacts In Biodiversity Scenariosmentioning

confidence: 99%

Biodiversity scenarios neglect future land‐use changes

Titeux

Henle

Mihoub

et al. 2016

Global Change Biology

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Efficient management of biodiversity requires a forward-looking approach based on scenarios that explore biodiversity changes under future environmental conditions. A number of ecological models have been proposed over the last decades to develop these biodiversity scenarios. Novel modelling approaches with strong theoretical foundation now offer the possibility to integrate key ecological and evolutionary processes that shape species distribution and community structure. Although biodiversity is affected by multiple threats, most studies addressing the effects of future environmental changes on biodiversity focus on a single threat only. We examined the studies published during the last 25 years that developed scenarios to predict future biodiversity changes based on climate, land-use and land-cover change projections. We found that biodiversity scenarios mostly focus on the future impacts of climate change and largely neglect changes in land use and land cover. The emphasis on climate change impacts has increased over time and has now reached a maximum. Yet, the direct destruction and degradation of habitats through land-use and land-cover changes are among the most significant and immediate threats to biodiversity. We argue that the current state of integration between ecological and land system sciences is leading to biased estimation of actual risks and therefore constrains the implementation of forward-looking policy responses to biodiversity decline. We suggest research directions at the crossroads between ecological and environmental sciences to face the challenge of developing interoperable and plausible projections of future environmental changes and to anticipate the full range of their potential impacts on biodiversity. An intergovernmental platform is needed to stimulate such collaborative research efforts and to emphasize the societal and political relevance of taking up this challenge.

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Predicted insect diversity declines under climate change in an already impoverished region

Cited by 52 publications

References 63 publications

The need for large‐scale distribution data to estimate regional changes in species richness under future climate change

The need for large‐scale distribution data to estimate regional changes in species richness under future climate change

Assessing the areas under risk of invasion within islands through potential distribution modelling: The case of Pittosporum undulatum in São Miguel, Azores

Biodiversity scenarios neglect future land‐use changes

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