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Julian Olden

Climate change remains a primary threat to inland fishes and fisheries. Using topic modeling to examine trends and relationships across 36 years of scientific literature on documented and projected climate impacts to inland fish, we identify ten representative topics within this body of literature: assemblages, climate scenarios, distribution, climate drivers, population growth, invasive species, populations, phenology, physiology, and reproduction. These topics are largely similar to the output from artificial intelligence application (i.e., ChatGPT) search prompts, but with some key differences. The field of climate impacts on fish has seen dramatic growth since the mid-2000s with increasing popularity of topics...
Categories: Publication; Types: Citation
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A Landscape Approach for Fisheries Database Compilation and Predictive Modeling (Not listed in the LCC Science Catalog due to Desert LCC co-funding and catalog administering)
The Arizona Game and Fish Department (AGFD) recognizes the need for a strong data foundation to inform science-based decisions for fisheries management at a watershed level. In preparation for a shift towards comprehensive watershed-scale planning, AGFD is developing a fisheries data management system with an initial focus on compiling and formatting several hundred thousand fish survey and stocking records. Fish data will be integrated within a Geographic Information System (GIS) by georeferencing observations to an existing national spatial framework (National Hydrography Dataset), which will allow for broader transferability to watersheds shared with neighboring states, creating a seamless layer not limited by...
Fisheries data compilation efforts for this project fell within two large watersheds in Arizona; the Verde River watershed (Desert LCC) and the Little Colorado River watershed (Southern Rockies LCC). We divided the project into two phases; 1) data compilation for the Arizona Game and Fish Fisheries Information Systems (FINS) and 2) a demonstration of FINS through model development and species distribution data. During phase 1, we compiled, cleaned, assigned National Hydrography Dataset (NHD) reachcodes to historical data for 113,230 fish records in the Verde River watershed and 43,828 fish records from the Little Colorado River watershed. These records were standardized to meet the Arizona Game and Fish Department...
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Evaluating Species’ Adaptive Capacity in a Changing Climate: Applications to Natural-Resource Management in the Northwestern U.S.
Natural resource managers are confronted with the pressing challenge to develop conservation plans that address complex ecological and societal needs against the backdrop of a rapidly changing climate. Climate change vulnerability assessments (CCVAs) provide valuable information that helps guide management and conservation actions in this regard. An essential component to CCVAs is understanding adaptive capacity, or the ability of a species to cope with or adjust to climate change. However, adaptive capacity is the least understood and evaluated component of CCVAs. This is largely due to a fundamental need for guidance on how to assess adaptive capacity and incorporate this information into conservation planning...
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Anticipating Climate-Driven Spread and Impact of Multiple Interacting Invasive Species in the Columbia River Basin
A persistent management question is whether current climate adaptation planning will remain robust when facing a growing number of invasive species. The concern is that current management strategies that focus exclusively on single invasive species and overlook climate-driven biological interactions, may lead to poor decisions. By delivering actionable science, this project directly informs specific planning, management and decision needs of tribal and governmental partners working in the Columbia River Basin. First, we assess the information needs for, and barriers to, effective aquatic invasive species management in the face of climate change in the Columbia River Basin. This helps synthesize knowledge and build...
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