Predicting the Viability of Fish Populations in a Modified Riverine Environment

Riverine fishes evolved to life in a highly variable, flow-driven environment. During the two past centuries, large rivers have been substantially altered by human activities. This has resulted in declines of fish populations that depend on the large river environment. The research described here uses models to evaluate the effects of human activities on the viability of fish populations in rivers. I focused on five modifications of the river environment associated with impoundment: (1) seasonal allocation of river flow; (2) diversion of river flow; (3) fragmentation of the river habitat by dams; (4) conversion of free-flowing river to reservoir habitat; and (5) alteration of migration patterns. To understand the role of flow regulation on chinook salmon (Oncorhynchus tshawytscha) recruitment, I developed an individual-based model to predict recruitment as a function of seasonal flow patterns in the Tuolumne River, California. I used simulated annealing to find flow patterns that maximize chinook recruitment under wet and dry hydrologic conditions. As water availability increased, I found that the optimal flow pattern shifted from allocating low flows uniformly across seasons to a pattern with high spring flows. When I considered a new objective: maximizing the variance of spawning times among recruits, the optimal flow regime called for a winter pulse in flow just before the peak spawning date for the minority (late-fall) run. To evaluate the recovery options for chinook salmon in the Tuolumne River, Ideveloped an age-based model to conduct a population viability analysis (PVA). I developed a flow-dependent spawner-recruitment relationship from the recruitment model. Its shape depended on the flow regime, suggesting that such relationships are not fixed properties of species, but depend on environmental conditions. The PVA model suggested that recovery, in the absence of straying, would be enhanced most by significantly reducing ocean harvest, followed by reduced diversion of water from the river. For white sturgeon (Acipenser transmontanus) populations in the Snake River, Idaho a main concern is habitat fragmentation by dams resulting in smaller, isolated populations. Simulation experiments to evaluate the effects of fragmentation suggested that population viability was higher when dams were spaced widely enough apart to retain free-flowing habitat. A simulation experiment to evaluate the effects of altered migration patterns associated with impoundment showed that both the likelihood of persistence and the genetic diversity among white sturgeon populations were enhanced by balanced upstream and downstream migration rates. Models that simulate the responses of fish populations to modified river habitat do not consider the potential for an evolutionary response. I designed a PVA model simulating the genetic basis of age at maturity for individual fish. Simulated individual variation in this trait lead to increased population viability only when the variation was heritable and subjected to an altered selective regime. The results support the idea that predicting population viability depends on estimating the potential for evolution in fitness-related traits for populations exposed to anthropogenic changes in the environment that impose strong, directional selective forces

Empirical Geographic Modeling of Switchgrass Yields in the United States

Switchgrass (Panicum virgatum L.) is a perennial grass native to the United States that has been studied as a sustainable source of biomass fuel. Although many field‐scale studies have examined the potential of this grass as a bioenergy crop, these studies have not been integrated. In this study, we present an empirical model for switchgrass yield and use this model to predict yield for the conterminous United States. We added environmental covariates to assembled yield data from field trials based on geographic location. We developed empirical models based on these data. The resulting empirical models, which account for spatial autocorrelation in the field data, provide the ability to estimate yield from factors associated with climate, soils, and management for both lowland and upland varieties of switchgrass. Yields of both ecotypes showed quadratic responses to temperature, increased with precipitation and minimum winter temperature, and decreased with stand age. Only the upland ecotype showed a positive response to our index of soil wetness and only the lowland ecotype showed a positive response to fertilizer. We view this empirical modeling effort, not as an alternative to mechanistic plant‐growth modeling, but rather as a first step in the process of functional validation that will compare patterns produced by the models with those found in data. For the upland variety, the correlation between measured yields and yields predicted by empirical models was 0.62 for the training subset and 0.58 for the test subset. For the lowland variety, the correlation was 0.46 for the training subset and 0.19 for the test subset. Because considerable variation in yield remains unexplained, it will be important in the future to characterize spatial and local sources of uncertainty associated with empirical yield estimates

Predicting impacts of chemicals from organisms to ecosystem service delivery: A case study of endocrine disruptor effects on trout

We demonstrate how mechanistic modeling can be used to predict whether and how biological responses to chemicals at (sub)organismal levels in model species (i.e., what we typically measure) translate into impacts on ecosystem service delivery (i.e., what we care about). We consider a hypothetical case study of two species of trout, brown trout (Salmo trutta; BT) and greenback cutthroat trout (Oncorhynchus clarkii stomias; GCT). These hypothetical populations live in a high-altitude river system and are exposed to human-derived estrogen (17α‑ethinyl estradiol, EE2), which is the bioactive estrogen in many contraceptives. We use the individual based model in STREAM to explore how seasonally varying concentrations of EE2 could influence male spawning and sperm quality. Resulting impacts on trout recruitment and the consequences of such for anglers and for the continued viability of populations of GCT (the state fish of Colorado) are explored. in STREAM incorporates seasonally varying river flow and temperature, fishing pressure, the influence of EE2 on species-specific demography, and inter-specific competition. The model facilitates quantitative exploration of the relative importance of endocrine disruption and inter-species competition on trout population dynamics. Simulations predicted constant EE2 loading to have more impacts on GCT than BT. However, increasing removal of BT by anglers can enhance the persistence of GCT and offset some of the negative effects of EE2. We demonstrate how models that quantitatively link impacts of chemicals and other stressors on individual survival, growth, and reproduction to consequences for populations and ecosystem service delivery, can be coupled with ecosystem service valuation. The approach facilitates interpretation of toxicity data in an ecological context and gives beneficiaries of ecosystem services amore explicit role in management decisions. Although challenges remain, this type of approach may be particularly helpful for site-specific risk assessments and those in which trade offs and synergies among ecosystem services need to be considered

Hair Cortisol in Twins : Heritability and Genetic Overlap with Psychological Variables and Stress-System Genes

A. Palotie on työryhmän jäsen.Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.Peer reviewe

Finding middle ground: Flow regimes designed for salmon and energy value

In regulated rivers, shaping seasonal flows to recover species at risk depends on understanding when to expect conflicts with competing water users and when their interests are aligned. Multi-objective optimization can be used to reveal such conflicts and commonalities. When species are involved, multi-objective optimization is challenged by the need to simulate complex species responses to flow regimes. Previously, we addressed that challenge by developing a simplified salmon model (Quantus) that defines cohorts of salmon by the river section and time in which they were spawned. Salmon in these space-time cohorts are tracked from the time redds (nests) are constructed until the cohort exits the tributary en route to the ocean. In this study, we modeled seasonal patterns in energy value and developed a Pareto-optimal frontier of seasonal flow patterns to maximize in-river salmon survival and hydropower value. Candidate flow regimes were characterized by two pulse flows varying in magnitude, timing, and duration and constrained by a total annual flow near the historical median. Our analysis revealed times when economic and salmon objectives were aligned and times when they differed. Pulse flows that favored higher energy value were timed to meet demand during extreme temperatures. Both salmon and hydropower objectives produced optimal flow regimes with pulse flows in early summer, but only solutions favoring hydropower value included high flows in mid-winter. Solutions favoring higher age-0 salmon survival provided an extended pulse flow in late winter/early spring, which suggests that access to productive floodplain habitat allowed faster growth and earlier out-migration and reduced the need for higher temperature-moderating flows later in spring. Minimum flows were also higher among solutions favoring salmon over energy. The tools used to produce these results can help to design simplified seasonal flow regimes by revealing compromise solutions that satisfy both fish and energy producers and highlighting when potential conflicts are likely

Avoiding Conflicts between Future Freshwater Algae Production and Water Scarcity in the United States at the Energy-Water Nexus

Sustainable production of algae will depend on understanding trade-offs at the energy-water nexus. Algal biofuels promise to improve the environmental sustainability profile of renewable energy along most dimensions. In this assessment of potential US freshwater production, we assumed sustainable production along the carbon dimension by simulating placement of open ponds away from high-carbon-stock lands (forest, grassland, and wetland) and near sources of waste CO 2 . Along the water dimension, we quantified trade-offs between water scarcity and production for an ‘upstream’ indicator (measuring minimum water supply) and a ‘downstream’ indicator (measuring impacts on rivers). For the upstream indicator, we developed a visualization tool to evaluate algae production for different thresholds for water surplus. We hypothesized that maintaining a minimum seasonal water surplus would also protect river habitat for aquatic biota. Our study confirmed that ensuring surplus water also reduced the duration of low-flow events, but only above a threshold. We also observed a trade-off between algal production and the duration of low-flow events in streams. These results can help to guide the choice of basin-specific sustainability targets to avoid conflicts with competing water users at this energy-water nexus. Where conflicts emerge, alternative water sources or enclosed photobioreactors may be needed for algae cultivation

Predicting impacts of chemicals from organisms to ecosystem service delivery: A case study of insecticide impacts on a freshwater lake

Assessing and managing risks of anthropogenic activities to ecological systems is necessary to ensure sustained delivery of ecosystem services for future generations. Ecological models provide a means of quantitatively linking measured risk assessment end points with protection goals, by integrating potential chemical effects with species life history, ecological interactions, environmental drivers and other potential stressors. Here we demonstrate how an ecosystem modeling approach can be used to quantify insecticide-induced impacts on ecosystem services provided by a lake from toxicity data for organism-level endpoints. We used a publicly available aquatic ecosystem model AQUATOX that integrates environmental fate of chemicals and their impacts on food webs in aquatic environments. By simulating a range of exposure patterns,we illustrated how exposure to a hypothetical insecticide could affect aquatic species populations (e.g., recreational fish abundance) and environmental properties (e.g., water clarity) that would in turn affect delivery of ecosystem services. Different results were observed for different species of fish, thus the decision to manage the use of the insecticide for ecosystem services derived by anglers depends upon the favored species of fish. In our hypothetical shallow reservoir, water clarity was mostly driven by changes in foodweb dynamics, specifically the presence of zooplankton. In contrast to the complex response by fishing value,water clarity increasedwith reduced insecticide use,which produced amonotonic increase in value by waders and swimmers. Our study clearly showed the importance of considering nonlinear ecosystem feed backs where the presence of insecticide changed the modeled food-web dynamics in unexpected ways. Our study highlights one of the main advantages of using ecological models for risk assessment, namely the ability to generalize to meaningful levels of organization and to facilitate quantitative comparisons among alternative scenarios and associated trade-offs among them while explicitly accounting for different groups of beneficiaries