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Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Habitat loss represents the greatest threat to freshwater biodiversity. The potential for life history attributes to correlate with the risks associated with habitat loss represents a possible mechanism for more effective and rapid assessments, especially in data-limited situations. Body size correlates with many other life history attributes and is a good starting point for investigating correlates with habitat loss. Here, we use a generic stage-based matrix population model, parameterized using length-based allometries, to investigate if such a mechanism exists. Our analysis revealed that small species (shorter maximum body length) were initially more sensitive to the loss of habitat. Moreover, distinct stage-based patterns exist showing an increased sensitivity of population growth rate for small species to both habitat loss and vital rate perturbations of pre-adult stages. This indicates that the pre-adult period represents a critical stage for the continued production of small species and increased importance of the conservation of habitat used by young-of-the-year and juvenile fishes. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Numerous researchers have attempted to find suitable proxies for the lipid content of fishes. Owing to the high carbon content of lipids, C:N ratios have been used as a predictor of lipid content both for the purposes of quantifying condition and for stable isotope analyses. Here we examine the utility of C:N ratios for predicting the lipid content within and among populations, and to validate commonly used published percent lipid - C:N ratio models. No common percent lipid - C:N ratio model was found to apply; instead, population-specific influences on lipid content were observed. Published lipid prediction models significantly underestimated lipid content, and often had worse prediction error than the error obtained by using measured mean lipids as the prediction for all samples. Maximum prediction error by population ranged from a low of 50.7% to a high of 65.0%. Our results provide no support for the idea that there is a predictable relationship between bulk C:N ratios and lipid content. We recommend that sample-specific relationships be developed in situations where lipid prediction is needed, rather than relying on published models. De nombreux chercheurs ont essayé de trouver des variables de remplacement adéquates pour le contenu lipidique des poissons. À cause du fort contenu en carbone des lipides, les rapports C :N ont servi à prédire le contenu lipidique, tant pour la mesure de la condition que pour les analyses d'isotopes stables. Nous examinons ici l'utilité des rapports C :N pour la prédiction du contenu lipidique au sein des populations et entre les populations afin de valider les modèles % de lipides - rapport C :N les plus communément utilisés dans la littérature. Aucun des modèles communs % de lipides - rapport C :N n'est applicable; au contraire, on observe des influences spécifiques aux populations sur le contenu lipidique. Les modèles de prédiction des lipides dans la littérature sous-estiment significativement le contenu lipidique et souvent ils ont une erreur de prédiction plus importante que celle obtenue en utilisant la mesure des lipides moyens comme base de prédiction pour tous les échantillons. L'erreur de prédiction maximale par population varie d'un minimum de 50,7 % à un maximum de 65,0 %. Nos résultats n'appuient en aucune façon la proposition qu'il existe une relation prédictive entre les rapports globaux de C :N et le contenu lipidique. Nous recommandons d'établir des relations spécifiques aux échantillons pour obtenir des prédictions des lipides plutôt que de se fier aux modèles publiés. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In data-poor regions, modeled river temperatures are essential for predicting potential stressors for species at risk. With limited data from the Grand, Thames, and Sydenham rivers in southern Ontario, Canada, we evaluated simple mixed-effect regression models to predict water temperature using air temperature from nearby weather stations. Model performance was assessed for periods relevant to the fitness of the black redhorse (Moxostoma duquesni): June to August, when heat events may be likely; and May, when spawning occurs. All of the models performed better when trained on data from these periods, compared with using data from the entire growing season. The best model was a linear regression using 5 days of lagged air temperature. This model had a root mean square error for summer means of 1.5 °C. The differences in prediction error at different times of year highlight the importance of considering species ecology in model interpretation. However, the improvement in model fit when using only data from the relevant time of year suggests that relatively simple models can be used effectively in a management arena when applied appropriately. [ABSTRACT FROM AUTHOR]

Effective conservation requires that species recovery measures are informed by rigorous scientific research. For imperilled freshwater fishes and mussels in Canada, numerous research gaps exist, in part owing to the need for specialized research methods. The Canadian Freshwater Species at Risk Research Network (SARNET) was formed and identified or implemented approaches to address current research gaps, including (1) captive experimental research populations, (2) nonlethal methods for estimating abundance and distribution, (3) nonlethal field methods to measure life-history parameters, (4) species distribution models informed by co-occurring species, (5) conservation physiology to inform habitat and threat science, (6) evidence syntheses to evaluate threats and recovery measures, (7) disease-transmission models to understand mussel–host relationships, (8) experimental mesocosms and manipulative experiments to evaluate key habitat stressors, (9) threat and hazard models for predictive applications, and (10) rigorous evaluation of surrogate species. Over a dozen threat- and recovery-focused SARNET research applications are summarized, demonstrating the value of a coordinated research program between academics and government to advance scientific research on, and to support the recovery of, imperilled freshwater species. [ABSTRACT FROM AUTHOR]

More than 15 years have passed since Canada's Species at Risk Act was enacted. To evaluate scientific progress in support of the Act, we identified research accomplishments up to 2017 for imperilled aquatic species in the Great Lakes – St. Lawrence River basin based on recovery documents and an expert survey, spanning 1182 activities across 68 research topics for 45 fish and mussel species. Greatest progress was observed for population ecology (38% of activities with major progress) and habitat science (28%), with comparably less progress on threats (mechanisms and impacts; 19%) and recovery (threat mitigation and reintroduction; 21%). As a result of lagging progress, threat and reintroduction topics were prioritized for a Canadian Freshwater Species at Risk Research Network (SARNET; 2017–2020), which focused on addressing key knowledge gaps with novel applications. This special issue outlines the SARNET projects, which span novel field, laboratory, and analytical activities. Continued research investment into novel and existing approaches is necessary to advance scientific achievements for fishes and mussels in support of the Species at Risk Act in Canada. [ABSTRACT FROM AUTHOR]

The use of translocations to recover populations requires a sufficiently large number of individuals from source populations, but removing too many individuals could lead to source population collapse. To understand the trade-off between the probabilities of source population extirpation and translocation success, matrix population models that incorporate Allee effects, density dependence, and demographic and environmental stochasticity were combined with a model that simulates removals from source populations. We apply these models to eastern sand darter (Ammocrypta pellucida; Species at Risk Act status: Threatened) translocation scenarios in Canada. The results suggest that translocations most often require source populations >20 000 individuals, as source population extirpation probability increased with the number and frequency of removals. Transport mortality or losses immediately following introduction further affected translocation success. Uncertainty around life-history parameters and the strength of Allee effects led to additional uncertainty about the required source population size. Although stochastic processes affected the probability of translocation success, factors such as stocking density and frequency can be controlled, and translocation may therefore be a viable strategy for eastern sand darter recovery, even when applying cautious thresholds to guard against uncertainty. [ABSTRACT FROM AUTHOR]