Geology topics

Alexander J. Jensen

Publications and source records attributed to Alexander J. Jensen.

5 recordsLinked to original sources

USGS2024

The value of information is context dependent: A demonstration of decision tools to address multispecies river temperature management under uncertainty

Trade-offs among objectives in natural resource management can be exacerbated in altered ecosystems and when there is uncertainty in predicted management outcomes. Multi-criteria decision analysis and value of information (VOI) are underutilized decision tools that can assist fisheries managers in handling trade-offs and evaluating the importance of uncertainty. We demonstrate the use of these tools using a case study in the Sacramento River, California, USA, where two imperiled species with different temperature requirements, winter-run Chinook Salmon Oncorhynchus tshawytscha and Green Sturgeon Acipenser medirostris , spawn and rear in the artificially cold Shasta Dam tailwater. A temperature-control device installed on Shasta Dam maintains cool water for Chinook Salmon; however, uncertainties exist related to the effects of temperatures on the spawning and rearing of both species. We consider four alternative hypotheses in models of early life-stage dynamics to evaluate the effects of alternative temperature management strategies on Chinook Salmon and Green Sturgeon management objectives. We used VOI to quantify the increase in management performance that can be expected by resolving hypothesis-based uncertainties as a function of the weight assigned to species-specific objectives. We found the decision was hindered by uncertainty; the best performing alternative depends on which hypothesis is true, with warmer or cooler alternative management strategies recommended when weights favor Green Sturgeon or Chinook Salmon objectives, respectively. The value of reducing uncertainty was highest when Green Sturgeon was slightly favored, highlighting the interaction between scientific uncertainty and decision makers' values. Our demonstration features multi-criteria decision analysis and VOI as transparent, deliberative tools that can assist fisheries managers in confronting value conflicts, prioritizing resolution of uncertainty, and optimally managing aquatic ecosystems.

Fisheries↗

USGS2022

Phenomenological and mechanistic modeling of recreational angling behavior using creel data

Improved understanding of angling behavior in recreational fisheries can help managers account for partial controllability in systems in which angling effort is not directly regulated. Relevant aspects of angling behavior include fishing participation, site choice, and catch-and-release actions and can be considered at scales of both aggregate fishing effort and individual-decision-making. Using creel survey data collected across eight fishery seasons, we predicted aggregate angling effort (e.g., daily number of boating trips engaged in fishing) and characterized influences of individual trip-based site choice for recreational fisheries acting on fall-run Chinook salmon and coho salmon near the mouth of the Columbia River, United States of America. We applied an overdispersed Poisson likelihood-based generalized linear model with an autoregressive structure to aggregate boating effort and a multinomial logit model to trip-based site choice decisions among separate ocean and estuary fishing zones. Predictive models explained 71% and 79% of out-of-sample and in-sample variability in aggregate effort, respectively, and included the covariates weekend status, Chinook salmon catch rate, tidal range, and pre-season expectations of fish abundance. In addition to reinforcing the importance of Chinook salmon catch rate and tidal range, site choice model selection revealed influences of weather, fishery restrictions, expected fishery season lengths, and the individual-specific characteristics of boat length and guide status on decision-making. Model results provide predictive models for short-term fishery planning, highlight heterogeneity in individual decision-making, and illustrate the value of standardized creel data for evaluating angling behavior.

Oregon↗

USGS2021

Mechanistic invasive species management models and their application in conservation

Management strategies to address the challenges associated with invasive species are critical for effective conservation. An increasing variety of mathematical models offer insight into invasive populations, and can help managers identify cost effective prevention, control, and eradication actions. Despite this, as model complexity grows, so does the inaccessibility of these tools to conservation practitioners making decisions about management. Here, we seek to narrow the science-practice gap by reviewing invasive species management models (ISMMs). We define ISMMs as mechanistic models used to explore invasive species management strategies, and include reaction-advection–diffusion models, integrodifference equations, gravity models, particle transport models, nonspatial and spatial discrete-time population growth models, cellular automata, and individual-based models. For each approach, we describe the model framework and its implementation, discuss strengths and weaknesses, and give examples of conservation applications. We conclude by discussing how ISMMs can be used in concert with adaptive management to address scientific uncertainties impeding action and with multiple objective decision processes to evaluate tradeoffs among management objectives. We undertook this review to support more effective decision-making involving invasive species by providing conservation practitioners with the information they need to identify tools most useful for their applications.

Conservation Science and Practice↗

USGS2021

Rapid phenotypic stock identification of Chinook Salmon in recreational fishery management

Rapid phenotypic stock identification in mixed-stock fisheries can provide a useful alternative to more time-intensive methods (e.g., coded wire tags, genetics) in assessing harvest and informing management decisions. We leveraged local ecological knowledge, existing stock identification methods, and understanding of life history differences to develop rapid stock identification tools for fall-run Chinook Salmon Oncorhynchus tshawytscha encountered in the Buoy 10 recreational fishery at the mouth of the Columbia River. Specifically, we sought to differentiate between the fishery’s two dominant genetic lineages: lower river tules and upriver brights. We sampled recreationally landed Chinook Salmon in 2017, 2018, and 2019, assigned sampled individuals to functional reporting groups using a single-nucleotide-polymorphism-based genetic baseline, and collected measurements on phenotypic traits. Using traits including pigmentation patterns (e.g., spotting), fin morphology, characteristics indicative of sexual maturity, and muscle lipid content, random forest classification models provided consistently high classification success across and within genetic groups (i.e., up to 90%). Classification success remained consistent over time within fishery seasons and between years but showed meaningful bias between sexes. Based on observed classification success, we developed and evaluated a categorical visual identification guide capable of facilitating more rapid trait observations and on-site stock identification. The resulting classification key, built using classification trees and visual guide observations from 2019, achieved slightly lower classification success across and within genetic groups and had variable success among samplers. Compared with the existing use of coded wire tags in harvest assessment, phenotypic stock identification methods can provide more rapid and more numerous assignments, albeit with a greater degree of individual assignment error. Applied as a complement to standard methods like coded wire tags, the use of rapid phenotypic stock identification methods offers the potential for increased overall precision and timeliness in harvest assessments.

Oregon, Washington↗

USGS2020

Application of genetic stock identification and parentage-based tagging in a mixed-stock recreational chinook salmon fishery

Genetic methods can guide and improve the management of recreational mixed-stock fisheries by informing stock-specific estimates of harvest. We applied genetic stock identification and parentage-based tagging to a recreational Chinook Salmon Oncorhynchus tshawytscha fishery in the Columbia River to illustrate the value of genetic analysis in management. We sampled landed catch in 2017 and 2018, assigned the fish to genetic reporting groups, explored temporal trends in harvest composition within and between seasons, and assessed the accuracy and precision of genetic methods against estimates from conventional tagging methodology. The genetic stock identification and parentage-based tagging produced concordant stock assignments, and the harvest composition estimates were validated with independent data. High assignment rates, relative to expended sampling effort, and precise harvest composition estimates with adequate sample sizes demonstrate that both genetic methods can be complementary, effective tools in advancing harvest assessment and recreational fisheries management. The success of genetic stock identification and parentage-based tagging supports the expanded application of genetics to similar fisheries, potentially alongside existing or emerging assessment methods, and guides future improvements in data collection and analysis.

Oregon, Washington↗