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Current rates of environmental change are exceeding the capacity of many populations to adapt to new conditions and thus avoid demographic collapse and ultimate extinction. In particular, cold-water freshwater fish species are predicted to experience strong selective pressure from climate change and a wide range of interacting anthropogenic stressors in the near future. To implement effective management and conservation measures, it is crucial to quantify the maximum rate of change that cold-water freshwater fish populations can withstand. Here, we present a spatially explicit eco-genetic individual-based model, inSTREAM-Gen, to predict the eco-evolutionary dynamics of stream-dwelling trout under anthropogenic environmental change. The model builds on a well-tested demographic model, which includes submodels of river dynamics, bioenergetics, and adaptive habitat selection, with a new genetic module that allows exploration of genetic and life-history adaptations to new environments. The genetic module models the transmission of two key traits, size at emergence and maturity size threshold. We parameterized the model for a brown trout (Salmo trutta L.) population at the warmest edge of its range to validate it and analyze its sensitivity to parameters under contrasting thermal profiles. To illustrate potential applications of the model, we analyzed the population's demographic and evolutionary dynamics under scenarios of (1) climate change-induced warming, and (2) warming plus flow reduction resulting from climate and land use change, compared to (3) a baseline of no environmental change. The model predicted severe declines in density and biomass under climate warming. These declines were lower than expected at range margins because of evolution towards smaller size at both emergence and maturation compared to the natural evolution under the baseline conditions. Despite stronger evolutionary responses, declining rates were substantially larger under the combined warming and flow reduction scenario, leading to a high probability of population extinction over contemporary time frames. Therefore, adaptive responses could not prevent extinction under high rates of environmental change. Our model demonstrates critical elements of next generation ecological modelling aiming at predictions in a changing world as it accounts for spatial and temporal resource heterogeneity, while merging individual behaviour and bioenergetics with microevolutionary adaptations.
Intraspecific trait variability plays an important role in species adaptation to climate change. However, it still remains unclear how plants in semi-arid environments respond to increasing aridity. We investigated the intraspecific trait variability of two common Mediterranean annuals (Geropogon hybridus and Crupina crupinastrum) with similar habitat preferences. They were studied along a steep precipitation gradient in Israel similar to the maximum predicted precipitation changes in the eastern Mediterranean basin (i.e. -30% until 2100). We expected a shift from competitive ability to stress tolerance with decreasing precipitation and tested this expectation by measuring key functional traits (canopy and seed release height, specific leaf area, N-and P-leaf content, seed mass). Further, we evaluated generative bet-hedging strategies by different seed traits. Both species showed different responses along the precipitation gradient. C. crupinastrum exhibited only decreased plant height toward saridity, while G. hybridus showed strong trends of generative adaptation to aridity. Different seed trait indices suggest increased bet-hedging of G. hybridus in arid environments. However, no clear trends along the precipitation gradient were observed in leaf traits (specific leaf area and leaf N-/P-content) in both species. Moreover, variance decomposition revealed that most of the observed trait variation (>> 50%) is found within populations. The findings of our study suggest that responses to increased aridity are highly species-specific and local environmental factors may have a stronger effect on intraspecific trait variation than shifts in annual precipitation. We therefore argue that trait-based analyses should focus on precipitation gradients that are comparable to predicted precipitation changes and compare precipitation effects to effects of local environmental factors. (C) 2017 Gesellschaft fur Okologie. Published by Elsevier GmbH. All rights reserved.
Gene flow is an important factor determining the evolution of a species, since it directly affects population structure and species’ adaptation. Here, we investigated population structure, population history, and migration among populations covering the entire distribution of the geographically isolated South-West European common lizard (Zootoca vivipara louislantzi) using 34 newly developed polymorphic microsatellite markers. The analyses unravelled the presence of isolation by distance, inbreeding, recent bottlenecks, genetic differentiation, and low levels of migration among most populations, suggesting that Z. vivipara louislantzi is threatened. The results point to discontinuous populations and are in line with physical barriers hindering longitudinal migration south to the central Pyrenean cordillera and latitudinal migration in the central Pyrenees. In contrast, evidence for longitudinal migration exists from the lowlands north to the central Pyrenean cordillera and the Cantabrian Mountains. The locations of the populations south to the central Pyrenean cordillera were identified as the first to be affected by global warming; thus, management actions aimed at avoiding population declines should start in this area.
Both climate change and land use regimes affect the viability of populations, but they are often studied separately. Moreover, population viability analyses (PVAs) often ignore the effects of large environmental gradients and use temporal resolutions that are too coarse to take into account that different stages of a population's life cycle may be affected differently by climate change. Here, we present the High-resolution Large Environmental Gradient (HiLEG) model and apply it in a PVA with daily resolution based on daily climate projections for Northwest Germany. We used the large marsh grasshopper (LMG) as the target species and investigated (1) the effects of climate change on the viability and spatial distribution of the species, (2) the influence of the timing of grassland mowing on the species and (3) the interaction between the effects of climate change and grassland mowing. The stageand cohort-based model was run for the spatially differentiated environmental conditions temperature and soil moisture across the whole study region. We implemented three climate change scenarios and analyzed the population dynamics for four consecutive 20-year periods. Climate change alone would lead to an expansion of the regions suitable for the LMG, as warming accelerates development and due to reduced drought stress. However, in combination with land use, the timing of mowing was crucial, as this disturbance causes a high mortality rate in the aboveground life stages. Assuming the same date of mowing throughout the region, the impact on viability varied greatly between regions due to the different climate conditions. The regional negative effects of the mowing date can be divided into five phases: (1) In early spring, the populations were largely unaffected in all the regions; (2) between late spring and early summer, they were severely affected only in warm regions; (3) in summer, all the populations were severely affected so that they could hardly survive; (4) between late summer and early autumn, they were severely affected in cold regions; and (5) in autumn, the populations were equally affected across all regions. The duration and start of each phase differed slightly depending on the climate change scenario and simulation period, but overall, they showed the same pattern. Our model can be used to identify regions of concern and devise management recommendations. The model can be adapted to the life cycle of different target species, climate projections and disturbance regimes. We show with our adaption of the HiLEG model that high-resolution PVAs and applications on large environmental gradients can be reconciled to develop conservation strategies capable of dealing with multiple stressors.