Annualmeeting:2017 CSDMS meeting-124: Difference between revisions
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{{CSDMS meeting personal information template-2014 | {{CSDMS meeting personal information template-2014 | ||
|CSDMS meeting first name= | |CSDMS meeting first name=Brendan | ||
|CSDMS meeting last name= | |CSDMS meeting last name=Murphy | ||
|CSDMS meeting institute=University | |CSDMS meeting institute=Utah State University | ||
|CSDMS meeting city= | |CSDMS meeting city=Logan | ||
|CSDMS meeting country=United States | |CSDMS meeting country=United States | ||
|CSDMS meeting state= | |CSDMS meeting state=Utah | ||
|CSDMS meeting email address= | |CSDMS meeting email address=bpmurphy@aggiemail.usu.edu | ||
|CSDMS meeting phone= | |CSDMS meeting phone=512-799-8687 | ||
}} | }} | ||
{{CSDMS meeting scholar and pre-meeting | {{CSDMS meeting scholar and pre-meeting | ||
|CSDMS meeting pre-conference= | |CSDMS meeting pre-conference=Bootcamp | ||
|CSDMS meeting post-conference=No | |CSDMS meeting post-conference=No | ||
}} | }} | ||
{{CSDMS meeting select clinics1 | {{CSDMS meeting select clinics1 | ||
|CSDMS_meeting_select_clinics1= | |CSDMS_meeting_select_clinics1=4) Spatial agent-based models | ||
}} | }} | ||
{{CSDMS meeting select clinics2 | {{CSDMS meeting select clinics2 | ||
|CSDMS_meeting_select_clinics2= | |CSDMS_meeting_select_clinics2=2) Landlab I | ||
}} | }} | ||
{{CSDMS meeting select clinics3 | {{CSDMS meeting select clinics3 | ||
|CSDMS_meeting_select_clinics3= | |CSDMS_meeting_select_clinics3=4) LandLab and Dakota | ||
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{{CSDMS scholarships yes no | {{CSDMS scholarships yes no | ||
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{{CSDMS meeting abstract title temp | {{CSDMS meeting abstract title temp | ||
|CSDMS meeting abstract title= | |CSDMS meeting abstract title=Fish & Fire | ||
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{{CSDMS meeting authors template | |||
|CSDMS meeting coauthor first name abstract=Colton | |||
|CSDMS meeting coauthor last name abstract=Finch | |||
|CSDMS meeting coauthor institute / Organization=Utah State University | |||
|CSDMS meeting coauthor town-city=Logan | |||
|CSDMS meeting coauthor country=United States | |||
|State=Utah | |||
|CSDMS meeting coauthor email address=colton@aggiemail.usu.edu | |||
}} | |||
{{CSDMS meeting authors template | |||
|CSDMS meeting coauthor first name abstract=Patrick | |||
|CSDMS meeting coauthor last name abstract=Belmont | |||
|CSDMS meeting coauthor institute / Organization=Utah State University | |||
|CSDMS meeting coauthor town-city=Logan | |||
|CSDMS meeting coauthor country=United States | |||
|State=Utah | |||
|CSDMS meeting coauthor email address=patrick.belmont@usu.edu | |||
}} | |||
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|CSDMS meeting coauthor first name abstract=Phaedra | |||
|CSDMS meeting coauthor last name abstract=Budy | |||
|CSDMS meeting coauthor institute / Organization=Utah State University | |||
|CSDMS meeting coauthor town-city=Logan | |||
|CSDMS meeting coauthor country=United States | |||
|State=Utah | |||
|CSDMS meeting coauthor email address=phaedra.budy@usu.edu | |||
}} | }} | ||
{{CSDMS meeting abstract template | {{CSDMS meeting abstract template | ||
|CSDMS meeting abstract= | |CSDMS meeting abstract=Salmonine fishes (salmon and trout) are resilient and have evolved to survive environmental perturbations, including flood, drought, and wildfire. The effects of these perturbations are translated through the landscape by rivers, where aquatic communities can be severely impacted. For instance, after wildfire, rivers can experience increased frequency and magnitude of flash floods, ash and nutrient loading, increased sediment flux from runoff and debris flows, destabilization and physical alteration of fluvial habitat, stream temperature impairment, and either loss or gain of refuge (e.g. deep pools, woody debris, riparian vegetation). Depending on the severity, any one of these effects could drive the extirpation of fish populations, and the response and survival of fish gets increasingly complex when faced with multiple environmental perturbations. Historically, the extirpation of fish populations would not have been as significant a risk to the extinction of entire species or subspecies of salmonids, as unrestricted migration allowed for recolonization by neighboring populations. However, increasing river disconnectivity, due to the introduction of physical barriers, has put native fish species at greater risk of extinction after natural catastrophes. In order to evaluate the viability and recovery of fish populations after catastrophe, we have developed a multi-site structured population viability analysis (PVA) model that is designed to incorporate factors that are unique to the spatial distribution of catastrophe and migration in fluvial networks. Specifically, our multi-site PVA provides the flexibility to vary both the duration and severity (i.e., multi-year catastrophe and habitat recovery) of vital rate adjustment (survival and growth). Our model also allows for a multi-mechanistic approach to vital rate adjustment after catastrophe – this is a particularly important advancement, as fluvial habitats located within the fire perimeter often experience distinctly different impacts than those outside of but downstream of fire. Both of these improvements are necessary as the negative impacts of wildfire on fish habitat and vital rates can last for years or even decades, and commonly used PVA modeling software only allows for impairment to last for one year. Additionally, previous models allow for a “one, all or radial spreading” approach to the spatial distribution of catastrophe, which works for disease but is inconsistent with the flow routing of catastrophe in stream networks. Finally, we have also developed a new metapopulation migration model that accounts for bidirectional river connectivity, a characteristic of migration unique to fluvial environments. Migration behavior in this model is driven by simple probabilities of life-stage structured dispersal and migration distances, measures of habitat suitability (including post-catastrophe adjustment), and site population densities. To demonstrate the utility of our multi-site PVA, we apply it to a case study of Bonneville Cutthroat Trout after the Twitchell Canyon Fire in the Fish Lake National Forest, Utah. The impact on and recovery of trout populations after wildfire was monitored across 14 sites of variable hydrologic, temperature and physical impairment (both within and outside of the fire perimeter). Using these observations along with maps of stream connectivity barriers, we model trout population viability and recovery after wildfire in this site. We also compare our results to model simulations using single year impairment, more similar to that of previous PVAs. Finally, we demonstrate the potential improvements on population recovery through simulations removing individual fish barriers throughout the network. This model presents a new framework for directly linking parameters of landscape change that may vary in both spatial and temporal distribution to the viability of fish populations after natural catastrophe. Plans for future model development include linking the PVA with models of fish bioenergetrics and landscape evolution, which can provide spatially variable predictions of changes in discharge, stream temperature and sediment fluxes after fire. Ultimately, we hope to develop and provide a new management tool for evaluating the overall vulnerability of aquatic organisms to wildfire in watersheds throughout the Intermountain West. | ||
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Latest revision as of 15:40, 31 March 2017
Browse abstracts
Fish & Fire
[[Image:|300px|right|link=File:]]Salmonine fishes (salmon and trout) are resilient and have evolved to survive environmental perturbations, including flood, drought, and wildfire. The effects of these perturbations are translated through the landscape by rivers, where aquatic communities can be severely impacted. For instance, after wildfire, rivers can experience increased frequency and magnitude of flash floods, ash and nutrient loading, increased sediment flux from runoff and debris flows, destabilization and physical alteration of fluvial habitat, stream temperature impairment, and either loss or gain of refuge (e.g. deep pools, woody debris, riparian vegetation). Depending on the severity, any one of these effects could drive the extirpation of fish populations, and the response and survival of fish gets increasingly complex when faced with multiple environmental perturbations. Historically, the extirpation of fish populations would not have been as significant a risk to the extinction of entire species or subspecies of salmonids, as unrestricted migration allowed for recolonization by neighboring populations. However, increasing river disconnectivity, due to the introduction of physical barriers, has put native fish species at greater risk of extinction after natural catastrophes. In order to evaluate the viability and recovery of fish populations after catastrophe, we have developed a multi-site structured population viability analysis (PVA) model that is designed to incorporate factors that are unique to the spatial distribution of catastrophe and migration in fluvial networks. Specifically, our multi-site PVA provides the flexibility to vary both the duration and severity (i.e., multi-year catastrophe and habitat recovery) of vital rate adjustment (survival and growth). Our model also allows for a multi-mechanistic approach to vital rate adjustment after catastrophe – this is a particularly important advancement, as fluvial habitats located within the fire perimeter often experience distinctly different impacts than those outside of but downstream of fire. Both of these improvements are necessary as the negative impacts of wildfire on fish habitat and vital rates can last for years or even decades, and commonly used PVA modeling software only allows for impairment to last for one year. Additionally, previous models allow for a “one, all or radial spreading” approach to the spatial distribution of catastrophe, which works for disease but is inconsistent with the flow routing of catastrophe in stream networks. Finally, we have also developed a new metapopulation migration model that accounts for bidirectional river connectivity, a characteristic of migration unique to fluvial environments. Migration behavior in this model is driven by simple probabilities of life-stage structured dispersal and migration distances, measures of habitat suitability (including post-catastrophe adjustment), and site population densities. To demonstrate the utility of our multi-site PVA, we apply it to a case study of Bonneville Cutthroat Trout after the Twitchell Canyon Fire in the Fish Lake National Forest, Utah. The impact on and recovery of trout populations after wildfire was monitored across 14 sites of variable hydrologic, temperature and physical impairment (both within and outside of the fire perimeter). Using these observations along with maps of stream connectivity barriers, we model trout population viability and recovery after wildfire in this site. We also compare our results to model simulations using single year impairment, more similar to that of previous PVAs. Finally, we demonstrate the potential improvements on population recovery through simulations removing individual fish barriers throughout the network. This model presents a new framework for directly linking parameters of landscape change that may vary in both spatial and temporal distribution to the viability of fish populations after natural catastrophe. Plans for future model development include linking the PVA with models of fish bioenergetrics and landscape evolution, which can provide spatially variable predictions of changes in discharge, stream temperature and sediment fluxes after fire. Ultimately, we hope to develop and provide a new management tool for evaluating the overall vulnerability of aquatic organisms to wildfire in watersheds throughout the Intermountain West.
