Adaptation and Resilience of Spatial Ecological Networks to human-Induced Changes

Informations

Funding country

France

Acronym

ARSENIC

URL

-

Start date

11/1/2014

End date

-

Budget

498,682 EUR

Fundings

Abstract

Anthropogenic environmental changes increasingly threaten biodiversity and ecosystem services, thus kindling a societal demand for predictions that ecology as a science has yet to answer. Available models are poorly suited to predicting the ecological effects of such changes because they ignore variation in species’ niche due to ecological interactions and evolution. Without understanding the functioning of ecological networks and how they are shaped by evolution, it is indeed difficult to predict how changes of the environment will cascade through ecosystems and make species traits evolve. Understanding the dynamics of ecological networks is a dual goal, both for fundamental research and for building informed programs on sustainable ecosystem services and species conservation. Accounting for species interactions and evolution to understand the consequences of global changes is the critical question we want to tackle through an integrative approach that combines coevolutionary models and analyses of empirical datasets, existing or to be obtained through the project actions. We will tackle these challenges by capitalizing on the strengths of a pluridisciplinary consortium with highly complementary skills, from theoretical modelling to expert field work and taxonomical identification. First, we will build evolutionary models of spatially structured antagonistic and mutualistic networks to understand how evolution affects (i) the association of traits in interacting species, (ii) the dynamical properties of ecological networks, and (iii) the dynamics of species’ ranges when embedded in a network of interactions. These models will help understand how climate change, eutrophication and pollution affect the properties of interaction networks through the evolution of interaction strengths and species dispersal abilities. These models will hint at how and why some specialization traits can be evolutionarily associated with higher dispersal, and thus will suggest trait associations within and across networks that can then be tested. Effects of natural selection on the stability of feasible ecological equilibria will also be studied in the context of May’s diversity-stability paradox. Finally, studying the dynamics of species’ ranges in networks will allow us to make predictions of how trait evolution shapes the geographical distribution of mutualistic or trophic partners. Second, we will test these models (i) on existing databases on traits and interactions and (ii) using new observations. Existing databases on food web and plant-pollinator networks, on species traits and on geographical distributions will be tapped to uncover correlations between species traits and their position within networks, and among traits in species with different trophic niches or different degrees of specialization. We will also perform field surveys to test predictions of our models. The first survey will assess plant-pollinator interactions and their associated traits along a thousand-kilometre long latitudinal gradient of calcareous grasslands. Focusing on a few entomophilous, widely distributed plant species, we will identify and measure relevant traits of their associated pollinating fauna. Plant traits will be measured along the gradient to uncover associations between trait values and breadths of the pollinator spectrum. The second survey will compare herbivore and pollinator communities associated with metallicolous vs. non-metallicolous genotypes of the plant species Noccaea caerulescens. We will assess the links between the abundances of pollinators and herbivores, differences in heavy metal accumulation abilities and variation in self-fertilization rates in plants.