birds; community ecology; functional traits; Bayesian statistics; biotic interactions; environmental niche; joint species distribution models; climate change; virtual ecologist approach
Rogers Haldre S, Beckman Noelle G, Hartig Florian, Johnson Jeremy S, Pufal Gesine, Shea Katriona, Zurell Damaris, Bullock James M, Cantrell Robert Stephen, Loiselle Bette, Pejchar Liba, Razafindratsima Onja H, Sandor Manette E, Schupp Eugene W, Strickland W Christopher, Zambrano Jenny (2019), The total dispersal kernel: a review and future directions, in AoB PLANTS
, 11(5), plz042.
Zurell Damaris, Zimmermann Niklaus E., Gross Helge, Baltensweiler Andri, Sattler Thomas, Wüest Rafael O. (2019), Testing species assemblage predictions from stacked and joint species distribution models, in Journal of Biogeography
, 47(1), 101-113.
Johnson Jeremy S, Cantrell Robert Stephen, Cosner Chris, Hartig Florian, Hastings Alan, Rogers Haldre S, Schupp Eugene W, Shea Katriona, Teller Brittany J, Yu Xiao, Zurell Damaris, Pufal Gesine (2019), Rapid changes in seed dispersal traits may modify plant responses to global change, in AoB PLANTS
, 11(3), plz020.
Aslan Clare, Beckman Noelle G, Rogers Haldre S, Bronstein Judie, Zurell Damaris, Hartig Florian, Shea Katriona, Pejchar Liba, Neubert Mike, Poulsen John, HilleRisLambers Janneke, Miriti Maria, Loiselle Bette, Effiom Edu, Zambrano Jenny, Schupp Geno, Pufal Gesine, Johnson Jeremy, Bullock James M, Brodie Jedediah, Bruna Emilio, Cantrell Robert Stephen, Decker Robin, Fricke Evan, et al. (2019), Employing plant functional groups to advance seed dispersal ecology and conservation, in AoB PLANTS
, 11(2), plz006.
Yates Katherine L., Bouchet Phil J., Caley M. Julian, Mengersen Kerrie, Randin Christophe F., Parnell Stephen, Fielding Alan H., Bamford Andrew J., Ban Stephen, Barbosa A. Márcia, Dormann Carsten F., Elith Jane, Embling Clare B., Ervin Gary N., Fisher Rebecca, Gould Susan, Graf Roland F., Gregr Edward J., Halpin Patrick N., Heikkinen Risto K., Heinänen Stefan, Jones Alice R., Krishnakumar Periyadan K., Lauria Valentina, et al. (2018), Outstanding Challenges in the Transferability of Ecological Models, in Trends in Ecology & Evolution
, 33(10), 790-802.
Zurell Damaris, Pollock Laura J., Thuiller Wilfried (2018), Do joint species distribution models reliably detect interspecific interactions from co-occurrence data in homogenous environments?, in Ecography
, 41(11), 1812-1819.
Zurell Damaris, Gallien Laure, Graham Catherine H, Zimmermann Niklaus E (2018), Do long-distance migratory birds track their niche through seasons?, in Journal of Biogeograpgy
, 45(7), 1459-1468.
Gallien Laure, Zurell Damaris, Zimmermann Niklaus E. (2018), Frequency and intensity of facilitation reveal opposing patterns along a stress gradient, in Ecology and Evolution
, 8(4), 2171-2181.
Zurell Damaris, Graham Catherine H., Gallien Laure, Thuiller Wilfried, Zimmermann Niklaus E. (2018), Long-distance migratory birds threatened by multiple independent risks from global change, in Nature Climate Change
, 8, 992-996.
Schäfer Merlin, Menz Stephan, Jeltsch Florian, Zurell Damaris (2018), sOAR: A tool for modelling optimal animal life-history strategies in cyclic environments, in Ecography
, 41(3), 551-557.
Zurell Damaris (2017), Integrating demography, dispersal and interspecific interactions into bird distribution models, in Journal of Avian Biology
, 48(12), 1505-1516.
Biodiversity loss due to global environmental change is expected to increase rapidly throughout the 21st century posing a major challenge to nature conservation and society. In order to anticipate and mitigate negative impacts on ecosystem functions and services, models are needed that reliably depict the abiotic and biotic drivers that determine species and community response to environmental change. Correlative species distribution models (SDMs) have been widely used in this context, but remain criticised for only implicitly accounting for interspecific interactions and for not being able to properly disentangle the fundamental and realised niche of a species. Recently, new tools have been introduced that integrate SDMs with community ecological methods of co-occurrence analyses. So-called joint species distribution models (JSDMs) simultaneously estimate the distribution of multiple species and allow partitioning species co-occurrence patterns into species-specific environmental responses and residual correlations between species, which may result from interspecific interactions but also from unmeasured environmental factors. JSDMs provide an exciting development in macroecology and community ecology, but are still in its infancy with few available applications and without rigorous evaluation. Important questions remain regarding, for example, the scale dependence and spatiotemporal variation in interspecific interaction mechanisms and their effect on JSDM performance, the specific data needed for reliably identifying these mechanisms, and the applicability of JSDMs for climate impact assessments.This project will focus on Swiss avian communities and aims at: (1) evaluating the ability of JSDMs to detect and reliably quantify different interspecific interaction mechanisms, and to predict avian communities under scenarios of climate change; (2) evaluating the scale dependence of interspecific interaction processes in avian assemblages and their relation to functional traits; (3) assessing the extent of spatial and temporal variation in interspecific interactions for selected bird assemblages; and (4) incorporating trait information into JSDMs to understand how behavioural syndromes mediate interspecific interactions in birds. To achieve these goals, the project will make use of the extensive bird monitoring programmes of Switzerland, supplemented by targeted simulation experiments that allow testing the models against specific underlying assumptions. The project is expected to provide both theoretical and conceptual advancements in model-based predictions of species range and community changes by explicitly studying the link between local scale biotic interactions and large-scale avian community patterns, and by combining extensive empirical and theoretical analyses to define practical requirements and guidelines for the implementation of community assemblage predictions. Moreover, it will help understanding the complexities of Swiss avian assemblages and help anticipating potential environmental change-induced changes to Swiss avian diversity.