Community matrix

PressPurt - Network sensitivity to press perturbations under interaction uncertainty
While the use of networks to understand how complex systems respond to perturbations is pervasive across scientific disciplines, the …
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PressPurt - Network sensitivity to press perturbations under interaction uncertainty
The predictability of qualitative food web dynamics in response to extinction and invasion
Food webs are extraordinarily complex, containing myriad direct interactions and indirect effects. Determining how this network of …
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Exact probabilities for the indeterminacy of complex networks as perceived through press perturbations
We consider the goal of predicting how complex networks respond to chronic (press) perturbations when characterizations of their …
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Exact probabilities for the indeterminacy of complex networks as perceived through press perturbations
Rapid and direct recoveries of predators and prey through synchronized ecosystem management
One of the twenty-first century’s greatest environmental challenges is to recover and restore species, habitats and ecosystems. The …
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Characterizing species interactions to understand press perturbations: What is the community matrix?
The community matrix is among ecology’s most important mathematical abstractions, formally encapsulating the interconnected …
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Characterizing species interactions to understand press perturbations: What is the community matrix?
Complexity increases predictability in allometrically constrained food webs
All ecosystems are subjected to chronic disturbances, such as harvest, pollution, and climate change. The capacity to forecast how …
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Complexity increases predictability in allometrically constrained food webs
Predicting community responses to perturbations in the face of imperfect knowledge and network complexity
How best to predict the effects of perturbations to ecological communities has been a long‐standing goal for both applied and basic …
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Predicting community responses to perturbations in the face of imperfect knowledge and network complexity