Spatial variability in adult brook trout (<i>Salvelinus fontinalis</i>) survival within two intensively surveyed headwater stream networks

Kanno, Yoichiro; Letcher, Benjamin H.; Vokoun, Jason C.; Zipkin, Elise F.

doi:10.1139/cjfas-2013-0358

Cited by 11 publications

(7 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Captured fish were measured for total length (±1 mm) and mass (±0.1 g) and returned to the stream after all passes were completed. YOY individuals can be distinguished from older individuals (‘adults’ hereafter) based on length–frequency distributions (Xu et al ., ; Kanno et al ., ). A length–frequency histogram was plotted for each site × year combination, and the cutoff size between the two stages was determined individually (see Appendix S1 for example histograms).…”

Section: Methodsmentioning

confidence: 97%

“…() who demonstrated that demographic heterogeneity among individuals (e.g., age, size, and sex) can be estimated with this framework. This structured population model provides a flexible method for incorporating temporal and spatial heterogeneity in the environment as well as density‐dependent processes into the analysis of count data, but its applications to empirical data have been limited to date (Kanno et al ., ; Zipkin et al ., ).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Seasonal weather patterns drive population vital rates and persistence in a stream fish

Kanno

Letcher

Hitt

et al. 2015

Global Change Biology

Self Cite

View full text Add to dashboard Cite

Climate change affects seasonal weather patterns, but little is known about the relative importance of seasonal weather patterns on animal population vital rates. Even when such information exists, data are typically only available from intensive fieldwork (e.g., mark-recapture studies) at a limited spatial extent. Here, we investigated effects of seasonal air temperature and precipitation (fall, winter, and spring) on survival and recruitment of brook trout (Salvelinus fontinalis) at a broad spatial scale using a novel stage-structured population model. The data were a 15-year record of brook trout abundance from 72 sites distributed across a 170-km-long mountain range in Shenandoah National Park, Virginia, USA. Population vital rates responded differently to weather and site-specific conditions. Specifically, young-of-year survival was most strongly affected by spring temperature, adult survival by elevation and per-capita recruitment by winter precipitation. Low fall precipitation and high winter precipitation, the latter of which is predicted to increase under climate change for the study region, had the strongest negative effects on trout populations. Simulations show that trout abundance could be greatly reduced under constant high winter precipitation, consistent with the expected effects of gravel-scouring flows on eggs and newly hatched individuals. However, high-elevation sites would be less vulnerable to local extinction because they supported higher adult survival. Furthermore, the majority of brook trout populations are projected to persist if high winter precipitation occurs only intermittently (≤3 of 5 years) due to density-dependent recruitment. Variable drivers of vital rates should be commonly found in animal populations characterized by ontogenetic changes in habitat, and such stage-structured effects may increase population persistence to changing climate by not affecting all life stages simultaneously. Yet, our results also demonstrate that weather patterns during seemingly less consequential seasons (e.g., winter precipitation) can have major impacts on animal population dynamics.

show abstract

Section: Methodsmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Seasonal weather patterns drive population vital rates and persistence in a stream fish

Kanno

Letcher

Hitt

et al. 2015

Global Change Biology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Furthermore, extensions of this model across seasons allow for explicit estimation of population trend (Kéry et al , Dail and Madsen ). To date, N ‐mixture models have been applied to a variety of species, including birds (Kéry et al , Kéry and Royle , Deluca and King , Jakob et al ), reptiles (Kéry et al ), fish (Kanno et al ), mammals (Priol et al ), and amphibians (Dodd and Dorazio ) to answer a variety of questions in basic and applied population ecology.…”

mentioning

confidence: 99%

Improved analysis of lek count data using N‐mixture models

2016

View full text Add to dashboard Cite

The greater sage-grouse (Centrocercus urophasianus) is a species of conservation concern in western North America that is experiencing ongoing population declines due to habitat loss, energy development, disease, and other factors. It is therefore imperative to have robust estimates of population size and trends in this species across its range as part of monitoring, management, and conservation efforts. Greater sage-grouse are typically monitored by conducting counts of males at breeding leks, but the relationship between this index and true population size is unknown. In an attempt to improve the analyses of this population index, we examined the potential of N-mixture models to evaluate population size, detection probability, and trend in greater sage-grouse using lek count data collected over space and time. We used simulations to test how well the models recovered abundance and growth rate parameters with increasingly sparse count data. We found that the models correctly recovered parameters for scenarios with both constant and variable detection probability, even with up to 90% of the data missing, where 95% of simulations contained the true population growth rate parameter value within the 95% credible interval. We then applied the model to 13 years of lek count data from Montana, USA, collected at 2 spatial scales. Statewide, we determined that the population was decreasing by 7% per year on average over this time period, and that mean annual detection probability ranged from 0.20 to 0.76. In contrast, regressions of na€ ıve counts over time showed a 9% annual decrease in population size with a confidence interval spanning 0. High interannual variability in detection probability demonstrates that na€ ıve counts do not accurately measure interannual variability in population size, and may lead to misleading trends in population size over time. Although N-mixture models still have limitations, they are a promising approach for conducting robust analyses of population trends for species that aggregate at discrete breeding sites, even when datasets are sparse or uneven. Ó

show abstract

“…Stream temperature is one of the ultimate determinants of the geographic distribution of trout species (MacCrimmon and Marshall 1968;MacCrimmon and Campbell 1969;Wehrly et al 2003) and affects longitudinal positions within watersheds ; de la Hoz Franco and Budy 2005) as well as influence reproductive success (Hokanson et al 1973;Bell 2006;Kanno et al 2016b). Along with thermal requirements, macrohabitat, substratum, and riparian conditions can also affect trout distribution , habitat suitability (Raleigh 1982;Boets et al 2018), and demography rates (Öhlund et al 2008;Kanno et al 2014). Trout species compete for resting and feeding positions in pool habitats under or near cover that allow them to minimize their energy output (Slaney and Northcote 1974;.…”

Section: Department Of Natural Resources 2015a) and Illinois (Illinoimentioning

confidence: 99%

Spatial distribution and ecological relationships of stream fishes in Iowa's Driftless Area

Kelly¹

View full text Add to dashboard Cite

I want to thank my committee chair, Michael Weber, and my committee members, Clay Pierce, and Stephen Dinsmore, for their guidance and mentorship during my studies here at Iowa State University. I would also like to thank Michael Siepker, with the Iowa Department of Natural Resources, for his assistance with the project design and implementation. None of this project would have been possible without partial funding from the U.S. Fish and Wildlife Service and Iowa Department of Natural Resources. Others within Trout Unlimited and the University of Wisconsin at Stevens Point, are deserving of recognition for their assistance with various aspects of project completion.

show abstract

Spatial variability in adult brook trout (Salvelinus fontinalis) survival within two intensively surveyed headwater stream networks

Cited by 11 publications

References 50 publications

Seasonal weather patterns drive population vital rates and persistence in a stream fish

Seasonal weather patterns drive population vital rates and persistence in a stream fish

Improved analysis of lek count data using N‐mixture models

Spatial distribution and ecological relationships of stream fishes in Iowa's Driftless Area

Contact Info

Product

Resources

About