Application of telemetry-based fish habitat models to predict spatial habitat availability and inform ecological restoration.

Conservation decisions surrounding which fish habitats managers choose to protect and restore are informed by fish habitat models. As acoustic telemetry has allowed for improvements in our ability to directly measure fish positions year-round, so too have there been opportunities to refine and apply fish habitat models. In an area with considerable anthropogenic disturbance, Hamilton Harbour in the Laurentian Great Lakes, we used telemetry-based fish habitat models to identify key habitat variables, compare habitat associations among seasons, and spatially identify the presence distribution of six fish species. Using environmental data and telemetry-based presence-absence from 2016 to 2022, random forest models were developed for each species across seasons. Habitat variables with the highest relative importance across species included fetch, water depth, and percentage cover of submerged aquatic vegetation. The presence probability of each species was spatially predicted for each season within Hamilton Harbour. Generally, species showed a spatial range expansion with greater presence probability in the fall and winter to include parts of the harbor further offshore, and a range contraction in the spring and summer toward the nearshore, sheltered areas, with summer having the most limited habitat availability. Greater habitat suitability was predicted in western Hamilton Harbour for the majority of species, whereas the east end was less suitable and may benefit from habitat restoration. These types of fish habitat models are highly flexible and can be used with a variety of data, not just telemetry, and should be considered as an additional tool for fish habitat and fisheries managers alike.

The importance of taxonomic resolution for additive beta diversity as revealed through DNA barcoding.

Additive diversity partitioning (α, ß, and γ) is commonly used to study the distribution of species-level diversity across spatial scales. Here, we first investigate whether published studies of additive diversity partitioning show signs of difficulty attaining species-level resolution due to inherent limitations with morphological identifications. Second, we present a DNA barcoding approach to delineate specimens of stream caddisfly larvae (order Trichoptera) and consider the importance of taxonomic resolution on classical (additive) measures of beta (ß) diversity. Caddisfly larvae were sampled using a hierarchical spatial design in two regions (subarctic Churchill, Manitoba, Canada; temperate Pennsylvania, USA) and then additively partitioned according to Barcode Index Numbers (molecular clusters that serve as a proxy for species), genus, and family levels; diversity components were expressed as proportional species turnover. We screened 114 articles of additive diversity partitioning and found that a third reported difficulties with achieving species-level identifications, with a clear taxonomic tendency towards challenges identifying invertebrate taxa. Regarding our own study, caddisfly BINs appeared to show greater subregional turnover (e.g., proportional additive ß) compared to genus or family levels. Diversity component studies failing to achieve species resolution due to morphological identifications may therefore be underestimating diversity turnover at larger spatial scales.

Freshwater zooplankton metapopulations and metacommunities respond differently to environmental and spatial variation.

Theory predicts that population genetic structure and metacommunity structure are linked by the common processes of drift and migration, but how population genetic structure and metacommunity structure are related in nature is still unknown. Deeper understanding of the processes influencing both genetic and community diversity is vital for better predicting how environmental change will impact biodiversity patterns. We examined how crustacean zooplankton and rotifer species' metapopulation genetic structure and metacommunities respond to environmental and spatial variation both within and across four regions of boreal Canada. Metapopulation and metacommunity variation partitioning results were compared within and across the four regions. Metapopulations and metacommunities responded differently to environmental variation and spatial structure both within and across regions, as metapopulations were influenced by different environmental variables compared to metacommunities. At larger spatial scales both metapopulations and metacommunities exhibited greater spatial and environmental structuring, again responding to a different subset of environmental variables. Our findings suggest that even though both genetic and species diversity are linked by the same processes, regional variation in environmental characteristics and spatial structure influence resulting biodiversity patterns differently. To date, no other empirical research has explored relationships between entire metapopulation and metacommunity assemblages at large regional spatial scales.

Conservation through the lens of (mal)adaptation: Concepts and meta-analysis.

Evolutionary approaches are gaining popularity in conservation science, with diverse strategies applied in efforts to support adaptive population outcomes. Yet conservation strategies differ in the type of adaptive outcomes they promote as conservation goals. For instance, strategies based on genetic or demographic rescue implicitly target adaptive population states whereas strategies utilizing transgenerational plasticity or evolutionary rescue implicitly target adaptive processes. These two goals are somewhat polar: adaptive state strategies optimize current population fitness, which should reduce phenotypic and/or genetic variance, reducing adaptability in changing or uncertain environments; adaptive process strategies increase genetic variance, causing maladaptation in the short term, but increase adaptability over the long term. Maladaptation refers to suboptimal population fitness, adaptation refers to optimal population fitness, and (mal)adaptation refers to the continuum of fitness variation from maladaptation to adaptation. Here, we present a conceptual classification for conservation that implicitly considers (mal)adaptation in the short-term and long-term outcomes of conservation strategies. We describe cases of how (mal)adaptation is implicated in traditional conservation strategies, as well as strategies that have potential as a conservation tool but are relatively underutilized. We use a meta-analysis of a small number of available studies to evaluate whether the different conservation strategies employed are better suited toward increasing population fitness across multiple generations. We found weakly increasing adaptation over time for transgenerational plasticity, genetic rescue, and evolutionary rescue. Demographic rescue was generally maladaptive, both immediately after conservation intervention and after several generations. Interspecific hybridization was adaptive only in the F1 generation, but then rapidly leads to maladaptation. Management decisions that are made to support the process of adaptation must adequately account for (mal)adaptation as a potential outcome and even as a tool to bolster adaptive capacity to changing conditions.