Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.

Individual growth data are useful in assessing relative habitat quality, but this approach is less common when evaluating the efficacy of habitat restoration. Furthermore, available models describing growth are infrequently combined with computational approaches capable of handling large data sets....

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Main Authors: Carlos M Polivka, Joseph R Mihaljevic, Greg Dwyer
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0234072
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author Carlos M Polivka
Joseph R Mihaljevic
Greg Dwyer
author_facet Carlos M Polivka
Joseph R Mihaljevic
Greg Dwyer
author_sort Carlos M Polivka
collection DOAJ
description Individual growth data are useful in assessing relative habitat quality, but this approach is less common when evaluating the efficacy of habitat restoration. Furthermore, available models describing growth are infrequently combined with computational approaches capable of handling large data sets. We apply a mechanistic model to evaluate whether selection of restored habitat can affect individual growth. We used mark-recapture to collect size and growth data on sub-yearling Chinook salmon and steelhead in restored and unrestored habitat in five sampling years (2009, 2010, 2012, 2013, 2016). Modeling strategies differed for the two species: For Chinook, we compared growth patterns of individuals recaptured in restored habitat over 15-60 d with those not recaptured regardless of initial habitat at marking. For steelhead, we had enough recaptured fish in each habitat type to use the model to directly compare habitats. The model generated spatially explicit growth parameters describing size of fish over the growing season in restored vs. unrestored habitat. Model parameters showed benefits of restoration for both species, but that varied by year and time of season, consistent with known patterns of habitat partitioning among them. The model was also supported by direct measurement of growth rates in steelhead and by known patterns of spatio-temporal partitioning of habitat between these two species. Model parameters described not only the rate of growth, but the timing of size increases, and is spatially explicit, accounting for habitat differences, making it widely applicable across taxa. The model usually supported data on density differences among habitat types in Chinook, but only in a couple of cases in steelhead. Modeling growth can thus prevent overconfidence in distributional data, which are commonly used as the metric of restoration success.
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spelling doaj.art-a88f610a962c4897a48cb00d0998a5d12022-12-21T18:39:47ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01156e023407210.1371/journal.pone.0234072Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.Carlos M PolivkaJoseph R MihaljevicGreg DwyerIndividual growth data are useful in assessing relative habitat quality, but this approach is less common when evaluating the efficacy of habitat restoration. Furthermore, available models describing growth are infrequently combined with computational approaches capable of handling large data sets. We apply a mechanistic model to evaluate whether selection of restored habitat can affect individual growth. We used mark-recapture to collect size and growth data on sub-yearling Chinook salmon and steelhead in restored and unrestored habitat in five sampling years (2009, 2010, 2012, 2013, 2016). Modeling strategies differed for the two species: For Chinook, we compared growth patterns of individuals recaptured in restored habitat over 15-60 d with those not recaptured regardless of initial habitat at marking. For steelhead, we had enough recaptured fish in each habitat type to use the model to directly compare habitats. The model generated spatially explicit growth parameters describing size of fish over the growing season in restored vs. unrestored habitat. Model parameters showed benefits of restoration for both species, but that varied by year and time of season, consistent with known patterns of habitat partitioning among them. The model was also supported by direct measurement of growth rates in steelhead and by known patterns of spatio-temporal partitioning of habitat between these two species. Model parameters described not only the rate of growth, but the timing of size increases, and is spatially explicit, accounting for habitat differences, making it widely applicable across taxa. The model usually supported data on density differences among habitat types in Chinook, but only in a couple of cases in steelhead. Modeling growth can thus prevent overconfidence in distributional data, which are commonly used as the metric of restoration success.https://doi.org/10.1371/journal.pone.0234072
spellingShingle Carlos M Polivka
Joseph R Mihaljevic
Greg Dwyer
Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.
PLoS ONE
title Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.
title_full Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.
title_fullStr Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.
title_full_unstemmed Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.
title_short Use of a mechanistic growth model in evaluating post-restoration habitat quality for juvenile salmonids.
title_sort use of a mechanistic growth model in evaluating post restoration habitat quality for juvenile salmonids
url https://doi.org/10.1371/journal.pone.0234072
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