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Conservation and management of Mediterranean freshwaters under climate change: An eco-evolutionary and socio-economic modelling framework

Final Report Summary - ECOEVOLCLIM (Conservation and management of Mediterranean freshwaters under climate change: An eco-evolutionary and socio-economic modelling framework)

The main scientific and technical objective of the EcoEvolClim research project was to develop an eco-evolutionary and socio-economic modelling framework to simulate the long-term dynamics of biological reference conditions, ecological thresholds and targets, and system recovery trajectories of Mediterranean trout rivers under different climate change and river basin management scenarios. Specific objectives were articulated in five research tasks (RTs):

1. To develop a simulation model (RT1) designed with an individual-based demo-genetic structure and parameterized and calibrated through a pattern-oriented modelling framework using specific data from Mediterranean brown trout populations at low-latitude range margins.
2. To simulate the evolution of demographics, life-history and genetic traits of Mediterranean trout populations under different scenarios of climate change (RT2).
3. To simulate the evolution of demographics, life-history and genetic traits of Mediterranean trout populations under different climate change and river basin management scenarios (RT3).
4. To define population demographic, life-history and genetic metrics (RT4) sensitive to climatic variation and anthropogenic disturbances.
5. To simulate the evolution of biological reference conditions, ecological thresholds, approaching targets and system recovery trajectories (RT5) of Mediterranean trout rivers under the defined climate change and river basin management scenarios.

The researcher designed, implemented in the free software platform NetLogo 5.0.4 tested and validated a spatially explicit eco-genetic individual-based model called inSTREAM-Gen (RT1). The whole process of model development including planning, design, testing, parameterization, evaluation and validation was reported in a 110 page TRACE (TRAnsparent and Comprehensive Ecological modelling documentation) document. The description of the model and its potential applications is currently under review in the Ecological Modelling research journal.

In RT2, the model was calibrated on five resident Mediterranean brown trout populations living along a steep temperature gradient, based on 12-year population data. Since inSTREAM-Gen is spatially explicit, the researcher developed site-specific environmental time series for years 1993-2100 based on the regional projections under the B2 and A1B1 SRES emission scenarios derived by the Spanish State Meteorological Agency through statistical downscaling techniques from data of four Global Climate Models. In RT3, the researcher assessed the interactive effects of climate change and two anthropogenic drivers of change (land use change and fishing) on the eco-evolutionary dynamics of populations. Scenarios of moderate (climate change plus single stressor) and high (climate change plus multiple stressors) rates of environmental change were simulated.

In RT4, the researcher statistically modelled the spatio-temporal trends of 31 demographic, life-history, phenological and genetic population traits, assessing their rate of change under the scenarios of change compared to the baseline conditions. The most sensitive ecological and genetic metrics were identified and linked to their biological and environmental drivers. Probability of extinction functions were modelled, so that tipping points beyond which population collapse is almost certain, were identified. In RT5, the researcher compared the evolution of the new biological reference conditions set by climate change to the trajectories of change resulting from simulated management actions to assess future population conservation status. Evolutionary impact graphs were develop to forecast outcomes from different management practises and thus to set ecological thresholds and restoration targets, and quantify the economic costs of their implementation.

The researcher successfully developed a running version of inSTREAM-Gen, which will be freely available from the internet. The researcher plans to promote its use as a management tool through a website and short workshops oriented to environmental managers. Researchers from environmental agencies from USA (US Forest Service), Canada (Ministry of the Environment) and France (EDF), and research institutions (Karlstad University and University of Applied Sciences Western Switzerland) have shown interest in applying the model to different trout river typologies.

The evolutionary impact assessment performed in EcoEvolClim showed that climate warming alone would not necessarily drive healthy populations to extinction because of both evolutionary and plastic rescue. InSTREAM-Gen predicted severe declines in density and biomass and a shift in the populations' age structure towards dominance of juveniles. Nevertheless, strong evolutionary responses towards smaller size-at-emergence and earlier maturation compared to baseline dynamics buffer the decline in population numbers and stabilize the number of breeders over time. However, probability of evolutionary rescue is contingent on initial state of the environment and the population, and on the rates of environmental change. Evolutionary responses cannot prevent extinction in populations already experiencing limiting water temperatures (over 19.5 ºC) that involve initial low population numbers and disrupted age-structures. Simulations showed that evolutionary responses are either not rapid enough or maladaptive when driven by genetic drift.

When environmental change involves changes in both temperature and flow (climate and land use change scenario), rapid evolutionary adaptation cannot prevent extinction of healthy populations in contemporary time frames. Under this context, recreational fishing is not possible, even at low pressures, as it would lead to certain rapid extinction. Under warming alone, environmental stochasticity would threaten populations only under fishing scenarios imposing strong selection pressure (low legal minimum size and high exploitation rates). Evolutionary impact graphs illustrate indeed that under most management options, fishing would not lead to extinction, but evolutionary responses would result in strong shifts in population age structure, which would entail a devaluation of the socio-economic value of the fishing stock. Statistical models showed that the rate of environmental change had stronger effects on population demographics while exploitation rate and minimum legal size were the main drivers of genetic and reproductive traits.

Statistical models developed in EcoEvolClim allow to forecast future trajectories of change and final conservation status of populations under different management options, which help prioritize conservation and restoration targets. Statistical analyses showed that metrics measuring population biomass or skewness of age structure are more sensitive to environmental change, and thus better indicators of ecological change, than metrics classically used in management, such as total population numbers, breeding stock, or recruitment. Results from EcoEvolClim highlight that management strategies should focus on minimizing concomitant impacts of climate change on such metrics to increase probability of persistence while maintaining the socio-economic value of managed populations. EcoEvolClim provides then an adaptive framework to anticipate system's threshold changes and thus help managers prioritize settings where management can influence the trajectory of ecosystem shifts toward new stable states that supply valued ecosystem services.