Species persistence in changing seasonal environments: A new holistic framework integrating demography and biotic interactions

Project Information

SEASON

Grant agreement ID: 894223

DOI

10.3030/894223

Project closed

EC signature date 25 March 2020

Start date 1 July 2020

End date 30 June 2022

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 172 932,48

EU contribution

€ 172 932,48

Coordinated by

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
Spain

Periodic Reporting for period 1 - SEASON (Species persistence in changing seasonal environments: A new holistic framework integrating demography and biotic interactions)

Reporting period: 2020-07-01 to 2022-06-30

Summary of the context and overall objectives of the project

Most species show seasonal variation in survival and reproduction, which determines and is affected by biotic (intra- and interspecific) interactions. Such demography-biotic-interaction feedbacks, in turn, mediate community responses to seasonal patterns in environmental factors. Changing these seasonal patterns, which then results in adverse effects on the demography of interacting species, is one important way in which global environmental change alters biodiversity. However, as population and community responses to changes in seasonality are typically studied separately, we lack a mechanistic understanding of the processes that threaten the persistence of interacting species, posing a major challenge to biodiversity conservation. Robustly capturing some of the pathways through which global change affects populations may allow us to design robust alternative forecasting scenarios of outcomes under global change.

The main aim of the MSCA project SEASON was to derive general principles of how feedbacks between demography and biotic interactions mediate species persistence and community dynamics under changes in the seasonality of environmental factors. To achieve this aim, SEASON consisted of two objectives:

Objective 1: Develop a unified framework of species interactions under seasonality change – advance theoretical ecology through simulations and projections of multiple demography-biotic-interaction feedbacks

Objective 2: Synthesize empirical patterns of species interactions under seasonality change – improve biodiversity conservation by evaluating/refining framework on empirical data to guide assessment of feedbacks

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

I developed a flexible analytical comparative framework that simulates natural communities differing in (a) how similar species are in allocating resources to reproduction vs. survival, (b) how strongly they interact with other species vs. conspecifics, and (c) how much survival varies across seasons. I successfully developed this framework by working with experts in community ecology, and we integrated the theoretical simulations into an existing R package on community dynamics to make them widely accessible to a wide range of researchers. The results have advanced our understanding of the species most vulnerable to directional environmental change and the key role seasonal demographic responses play in mediating population responses to environmental change. Simulations showed that species at higher trophic levels can be substantially threatened by changes in seasonal weather patterns through the combined direct effects of these changes and indirect ones, altering species interactions.

Parallel to the development of theoretical simulations, SEASON had a strong empirical component, where I used multi-species demographic and abundance data from four systems to develop mechanistic multispecies forecasts of seasonal climate-change effects. These empirical study cases supported predictions from the theoretical simulations and produced evidence that accounting for seasonal biotic interactions is key in forecasting population dynamics. I used the results from the empirical studies to develop a guide for future biodiversity research highlighting that ecological forecasting must assess how changes in abiotic factors (such as climate) affects species’ demographic rates directly or indirectly by altering species interactions. A key output of the empirical analyses has also been to demonstrate how demographic models can be parameterized and projected from abundance data for data-limited systems – which promises a broader applications of mechanistic forecasting approaches that account for demography-biotic-interactions feedbacks.

Outputs from the theoretical and empirical analyses have been published or submitted to scientific journals. Publications are accompanied by press releases, and project updates, including communication activities, are published on the project website and on social media. I also presented the simulations and empirical applications at three international conferences and have used them extensively as teaching material.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Both the theoretical and empirical analyses have synthesized novel insights into population responses to climate change. I was able to disentangle under what biotic and abiotic conditions higher trophic levels are under risk of extinction in a changing seasonal climate. Current forecasts of climate-change effects on species rely on linking raw climatic projections to abundances or demography. SEASON provided key evidence that forecasting applications must consider the biotic mechanisms through which climate change affects persistence of species embedded in natural communities. By asserting that we must place a stronger focus on whole lifecycle analyses and species interactions in our assessments of global-change effects on species, the work carried out is directly relevant to goal 15 of the EU 2030 Agenda for Sustainable Development: halting biodiversity loss.

Freely available demographic multispecies models that can be used to forecast the effect of seasonality change on communities are currently not available; and the simulations I developed in SEASON are an important step towards creating easily applicable tools to understand the demographic mechanisms that allow populations and communities respond to a key aspect of global change. The results of SEASON can be exploited by researchers and practitioners to assess how seasonal individual, age- or stage-specific demographic responses to biotic and abiotic drivers for several species in a community affect fates of populations and communities under environmental change.

Assessing population dynamics under climate change must account for species interactions