Studies of eco‐evolutionary dynamics have integrated evolution with ecological processes at multiple scales (populations, communities and ecosystems) and with multiple interspecific interactions (antagonistic, mutualistic and competitive). However, evolution has often been conceptualised as a simple process: short‐term directional adaptation that increases population growth. Here we argue that diverse other evolutionary processes, well studied in population genetics and evolutionary ecology, should also be considered to explore the full spectrum of feedback between ecological and evolutionary processes. Relevant but underappreciated processes include (1) drift and mutation, (2) disruptive selection causing lineage diversification or speciation reversal and (3) evolution driven by relative fitness differences that may decrease population growth. Because eco‐evolutionary dynamics have often been studied by population and community ecologists, it will be important to incorporate a variety of concepts in population genetics and evolutionary ecology to better understand and predict eco‐evolutionary dynamics in nature.
more »
« less
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
-
more » « less
Abstract Matrix population models are frequently built and used by ecologists to analyse demography and elucidate the processes driving population growth or decline. Life Table Response Experiments (LTREs) are comparative analyses that decompose the realized difference or variance in population growth rate () into contributions from the differences or variances in the vital rates (i.e. the matrix elements). Since their introduction, LTREs have been based on approximations and have not included biologically relevant interaction terms.
We used the functional analysis of variance framework to derive an exact LTRE method, which calculates the exact response of to the difference or variance in a given vital rate, for all interactions among vital rates—including higher‐order interactions neglected by the classical methods. We used the publicly available COMADRE and COMPADRE databases to perform a meta‐analysis comparing the results of exact and classical LTRE methods. We analysed 186 and 1487 LTREs for animal and plant matrix population models, respectively.
We found that the classical methods often had small errors, but that very high errors were possible. Overall error was related to the difference or variance in the matrices being analysed, consistent with the Taylor series basis of the classical method. Neglected interaction terms accounted for most of the errors in fixed design LTRE, highlighting the importance of two‐way interaction terms. For random design LTRE, errors in the contribution terms present in both classical and exact methods were comparable to errors due to neglected interaction terms. In most examples we analysed, evaluating exact contributions up to three‐way interaction terms was sufficient for interpreting 90% or more of the difference or variance in .
Relative error, previously used to evaluate the accuracy of classical LTREs, is not a reliable metric of how closely the classical and exact methods agree. Error compensation between estimated contribution terms and neglected contribution terms can lead to low relative error despite faulty biological interpretation. Trade‐offs or negative covariances among matrix elements can lead to high relative error despite accurate biological interpretation. Exact LTRE provides reliable and accurate biological interpretation, and the R package
exactLTRE makes the exact method accessible to ecologists. -
Optimal dynamic spatial closures can improve fishery yield and reduce fishing-induced habitat damageBottom-towed fishing gears produce significant amounts of seafood globally but can result in seafloor habitat damage. Spatial closures provide an important option for mitigating benthic impacts, but their performance as a fisheries management policy depends on numerous factors, including how fish respond to habitat quality changes. Spatial fisheries management has largely focused on marine protected areas with static locations, overlooking dynamic spatial closures that change through time. To investigate the performance of dynamic closures, we develop a spatial fishery model with fishing-induced habitat damage, where habitat quality can affect both fish productivity and movement. We find that dynamic spatial closures often achieve greater harvest and habitat protection than fixed marine protected areas or conventional nonspatial maximum sustainable yield management, especially under strong habitat–stock interactions. Determining optimal dynamic spatial closures may require considerable information, but we find that simple policies of fixed-schedule rotating closures also perform well. Dynamic spatial closures have received less attention as fisheries management tools, and our results demonstrate their potential value for addressing both harvest and habitat impacts from fishing.more » « less
-
more » « less
Abstract Strategies to control ongoing biological invasions are often developed by modelling the invasive species' population and aiming to reduce its abundance. However, if the ultimate objective is to protect and restore native species, focussing solely on the invader may not be optimal because it does not account for (i) species interactions that can cause the invader's impacts to depend nonlinearly on its abundance, (ii) collateral damages to native species incurred due to nonspecific removal methods or (iii) native‐invader trait differences.
To identify an invader suppression strategy that maximizes average native population size, we applied optimal control theory to a two‐species model of a native species threatened by an invasive competitor. We examined trade‐offs between iterative physical removals that selectively target invaders and intensifiable chemical control that is nonselective but has higher efficacy.
We found that while iterative removals were capable of supporting large native populations when applied continuously, cost could be prohibitively high. In contrast, when favourable native‐invader trait differences enabled native species to re‐establish more quickly than invaders, intensifiable methods could achieve substantial restoration benefits at lower cost by focussing removal effort into periodic, high‐efficacy events.
In a metapopulation, removals that rotated among spatial patches were optimal when the native species had higher dispersal, whereas synchronous removals were preferred when native recovery was initiated locally and the invader could disperse.
For a case study in Hawaiian streams, we compared how effective two alternative methods of removing invasive live‐bearing fishes (poeciliids) might be at restoring the endemic freshwater goby
Sicyopterus stimpsoni . We found that rotenone (a piscicidal chemical) offered superior benefits when the control budget was small and efficacy was high, but that electrofishing (use of electricity to manually collect target fish) was better with larger budgets and in many lower‐efficacy scenarios.Synthesis and applications. Our findings demonstrate that, by accounting for species interactions and collateral damage, invasive species control strategies can be optimized in light of species traits. Choices about the timing, locations and types of removal events present opportunities to increase the efficiency with which invasive species suppression benefits native species. -
more » « less
Abstract Community assembly is often treated as deterministic, converging on one or at most a few possible stable endpoints. However, in nature, we typically observe continuous change in community composition, which is often ascribed to environmental change. But continuous changes in community composition can also arise in deterministic, time‐invariant community models, especially food web models. Our goal was to determine why some models produce continuous assembly and others do not. We investigated a simple two‐trophic‐level community model to show that continuous assembly is driven by the relative niche width of the trophic levels. If predators have a larger niche width than prey, community assembly converges to a stable equilibrium. Conversely, if predators have a smaller niche width than prey, then community composition never stabilizes. Evidence that food webs need not reach a stable equilibrium has important implications, as many ecological theories of community ecology based on equilibria may be difficult to apply to such food webs.
