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Harvesting has been implicated in destabilizing the abundances of exploited populations. Because selective harvesting often targets large individuals, some studies have proposed that exploited populations often experience demographic shifts toward younger, smaller individuals and become more sensitive to environmental fluctuations. The theory of consumer–resource dynamics has been applied to address the impacts of harvesting in simple modular food webs, but harvested populations are embedded in a complex food web in nature. In addition, exploited populations have been shown to undergo trait evolution or phenotypic changes toward early maturation at smaller sizes. Using an empirically derived complex food web model, Kuparinen et al. (2016. Fishing-induced life-history changes degrade and destabilize harvested ecosystems. Scientific Reports: 6, 22,245) demonstrated that exploited fish populations and other ecosystem properties increased variability due to harvesting and harvesting-induced life-history evolution in the absence of environmental fluctuations. In the present study, we examined a large set of simulated complex food webs to attest the generality of the findings in Kuparinen et al. (2016). We found that harvesting both increased and decreased temporal variability of fish biomass dynamics, especially in food webs with intrinsically oscillating dynamics, while the vast majority of the food webs did not experience destabilization. We also elucidated the large impacts of the shape of functional responses on food web structure, energy flow, and changes in temporal variability caused by harvesting. Our results suggest that the destabilizing or stabilizing effects of harvesting and harvesting-induced evolution importantly depend on the shape of functional responses in dynamical models of complex food webs and that food webs with intrinsically oscillating dynamics are more prone to changes in temporal variability caused by harvesting and harvesting-induced evolution. peerReviewed

Ecosystems face both local hazards, such as over-exploitation, and global hazards, such as climate change. Since the impact of local hazards attenuates with distance from humans, local extinction risk should decrease with remoteness, making faraway areas safe havens for biodiversity. However, isolation and reduced anthropogenic disturbance may increase ecological specialization in remote communities, and hence their vulnerability to secondary effects of diversity loss propagating through networks of interacting species. We show this to be true for reef fish communities across the globe. An increase in fish-coral dependency with the distance of coral reefs from human settlements, paired with the far-reaching impacts of global hazards, increases the risk of fish species loss, counteracting the benefits of remoteness. Hotspots of fish risk from fish-coral dependency are distinct from those caused by direct human impacts, increasing the number of risk hotspots by ~30% globally. These findings might apply to other ecosystems on Earth and depict a world where no place, no matter how remote, is safe for biodiversity, calling for a reconsideration of global conservation priorities., Coral reefs face both local and global stressors. Here, the authors show how a positive relationship between distance from human settlements and ecological specialisation makes remote coral reef fish communities more vulnerable to coral loss.

Facing the loss of biodiversity caused by landscape fragmentation, implementation of ecological networks to connect habitats is an important biodiversity conservation issue. It is necessary to develop easily reproducible methods to identify and prioritize actions to maintain or restore ecological corridors. To date, several competing methods are used with recurrent debate on which is best and if expert-based approaches can replace data-driven models. We compared three methods: knowledge-driven (expert based), data-driven (based on species distribution model), and a mixed approach. We quantified their differences in habitat and corridor mapping, and prioritizations of landscape elements in terms of importance for connectivity. Key parameters generating these differences were identified. To put this into practice, the case study of the wildcat (Felis silvestris Schreber, 1777) was chosen. The results highlighted differences and similarities between approaches used. The data-driven approach was more successful in identifying the suitable habitat with regard to wildcat ecology, while the knowledge-driven approach was better able to account for obstacles to wildcat movements in the landscape matrix. However, these two methods converged for the identification of patterns of habitat patches and corridors that are important for global landscape connectivity. For both methods, we identified adjustments that can improve the outcome. The mixed approach largely differed in that it required more inputs to be performed. In the end, conservation actions were identified and could guide nature conservation practitioners in their efforts to restore landscape connectivity. peerReviewed