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Confronting dynamics and uncertainty in optimal decision making for conservation

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making--a careful consideration of values, actions, and outcomes.

Environmental Research Letters↗

Reorganization of vegetation, hydrology and soil carbon after permafrost degradation across heterogeneous boreal landscapes

The diversity of ecosystems across boreal landscapes, successional changes after disturbance and complicated permafrost histories, present enormous challenges for assessing how vegetation, water and soil carbon may respond to climate change in boreal regions. To address this complexity, we used a chronosequence approach to assess changes in vegetation composition, water storage and soil organic carbon (SOC) stocks along successional gradients within four landscapes: (1) rocky uplands on ice-poor hillside colluvium, (2) silty uplands on extremely ice-rich loess, (3) gravelly–sandy lowlands on ice-poor eolian sand and (4) peaty–silty lowlands on thick ice-rich peat deposits over reworked lowland loess. In rocky uplands, after fire permafrost thawed rapidly due to low ice contents, soils became well drained and SOC stocks decreased slightly. In silty uplands, after fire permafrost persisted, soils remained saturated and SOC decreased slightly. In gravelly–sandy lowlands where permafrost persisted in drier forest soils, loss of deeper permafrost around lakes has allowed recent widespread drainage of lakes that has exposed limnic material with high SOC to aerobic decomposition. In peaty–silty lowlands, 2–4 m of thaw settlement led to fragmented drainage patterns in isolated thermokarst bogs and flooding of soils, and surface soils accumulated new bog peat. We were not able to detect SOC changes in deeper soils, however, due to high variability. Complicated soil stratigraphy revealed that permafrost has repeatedly aggraded and degraded in all landscapes during the Holocene, although in silty uplands only the upper permafrost was affected. Overall, permafrost thaw has led to the reorganization of vegetation, water storage and flow paths, and patterns of SOC accumulation. However, changes have occurred over different timescales among landscapes: over decades in rocky uplands and gravelly–sandy lowlands in response to fire and lake drainage, over decades to centuries in peaty–silty lowlands with a legacy of complicated Holocene changes, and over centuries in silty uplands where ice-rich soil and ecological recovery protect permafrost.

Alaska↗

Consumption of baits containing raccoon pox-based plague vaccines protects black-tailed prairie dogs (Cynomys ludovicianus)

Baits containing recombinant raccoon poxvirus (RCN) expressing plague antigens (fraction 1 [F1] and a truncated form of the V protein-V307) were offered for voluntary consumption several times over the course of several months to a group of 16 black-tailed prairie dogs ( Cynomys ludovicianus ). For comparison, another group of prairie dogs ( n = 12) was injected subcutaneously (SC) (prime and boost) with 40 μg of F1-V fusion protein absorbed to alum, a vaccine-adjuvant combination demonstrated to elicit immunity to plague in mice and other mammals. Control animals received baits containing RCN without the inserted antigen ( n = 8) or injected diluent ( n = 7), and as there was no difference in their survival rates by Kaplan–Meier analysis, all of them were combined into one group in the final analysis. Mean antibody titers to Yersinia pestis F1 and V antigen increased ( p < 0.05) in the vaccinated groups compared to controls, but titers were significantly higher ( p < 0.0001) in those receiving injections of F1-V fusion protein than in those orally vaccinated with RCN-based vaccine. Interestingly, upon challenge with approximately 70,000 cfu of virulent Y. pestis , oral vaccination resulted in survival rates that were significantly higher ( p = 0.025) than the group vaccinated by injection with F1-V fusion protein and substantially higher ( p < 0.0001) than the control group. These results demonstrate that oral vaccination of prairie dogs using RCN-based plague vaccines provides significant protection against challenge at dosages that simulate simultaneous delivery of the plague bacterium by numerous flea bites.

Vector-Borne and Zoonotic Diseases↗

Navigating ecological transformation: Resist-accept-direct as a path to a new resource management paradigm

Natural resource managers worldwide face a growing challenge: Intensifying global change increasingly propels ecosystems toward irreversible ecological transformations. This nonstationarity challenges traditional conservation goals and human well-being. It also confounds a longstanding management paradigm that assumes a future that reflects the past. As once-familiar ecological conditions disappear, managers need a new approach to guide decision-making. The resist–accept–direct (RAD) framework, designed for and by managers, identifies the options managers have for responding and helps them make informed, purposeful, and strategic choices in this context. Moving beyond the diversity and complexity of myriad emerging frameworks, RAD is a simple, flexible, decision-making tool that encompasses the entire decision space for stewarding transforming ecosystems. Through shared application of a common approach, the RAD framework can help the wider natural resource management and research community build the robust, shared habits of mind necessary for a new, twenty-first-century natural resource management paradigm.

BioScience↗

At the leading edge: Advancing and bridging the science and management of range-shifting species

Climate-mediated shifts in species distributions are reshaping ecosystems worldwide, creating major challenges for conservation and resource management. These range shifts have far-reaching ecological and socio-economic consequences, requiring managers to address complex ecological dynamics while navigating diverse regulatory and value systems. Despite growing attention, key gaps remain in supporting management, from improved understanding of the mechanisms of range shifts, to evaluating the effectiveness of climate adaptation strategies, and tailoring science to the institutional and social contexts of decision-making. Central challenges include scaling processes across space, time, and organizational levels, and reconciling mismatches between biogeographical and management scales. Progress will depend on more comprehensive datasets to assess outcomes across taxa and regions, stronger cross-jurisdictional cooperation, and decision frameworks that integrate uncertainty alongside multiple value systems. Addressing these gaps is essential to make research more actionable and to enable successful management of species redistribution.

BioScience↗

Synthesis centers as critical research infrastructure

Demand for the opportunity to participate in a synthesis-center activity has increased in the years since the US National Science Foundation (NSF)–funded National Center for Ecological Analysis and Synthesis (NCEAS) opened its doors in 1995 and as more scientists across a diversity of scientific disciplines have become aware of what synthesis centers provide. The NSF has funded four synthesis centers, and more than a dozen new synthesis centers have been established around the world, some following the NSF model and others following different models suited to their national funding environment ( http://synthesis-consortium.org ). Scientific synthesis integrates diverse data and knowledge to increase the scope and applicability of results and yield novel insights or explanations within and across disciplines (Pickett et al. 2007 , Carpenter et al. 2009 ). The demand for synthesis comes from the pressing societal need to address grand challenges related to global change and other issues that cut across multiple societal sectors and disciplines and from recognition that substantial added scientific value can be achieved through the synthesis-based analysis of existing data. Demand also comes from groups of scientists who see exciting opportunities to generate new knowledge from interdisciplinary and transdisciplinary collaboration, often capitalizing on the increasingly large volume and variety of available data (Kelling et al. 2009 , Bishop et al. 2014 , Specht et al. 2015b ). The ever-changing nature of societal challenges and the availability of data with which to address them suggest there will be an expanding need for synthesis. However, we are now entering a phase in which government support for some existing synthesis centers has ended or will be ending soon, forcing those centers to close or develop new operational models, approaches, and funding streams. We argue here that synthesis centers play such a unique role in science that continued long-term public investment to maximize benefits to science and society is justified. In particular, we argue that synthesis centers represent community infrastructure more akin to research vessels than to term-funded centers of science and technology (e.g., NSF Science and Technology Centers). Through our experience running synthesis centers and, in some cases, developing postfederal funding models, we offer our perspective on the purpose and value of synthesis centers. We present case studies of different outcomes of transition plans and argue for a fundamental shift in the conception of synthesis science and the strategic funding of these centers by government funding agencies.

BioScience↗

Hawaii as a microcosm: Advancing the science and practice of managing introduced and invasive species

Invasive species are a leading driver of global change, with consequences for biodiversity and society. Because of extraordinary rates of endemism, introduction, and extinction, Hawaii offers a rich platform for exploring the cross-disciplinary challenges of managing invasive species in a dynamic world. We highlight key successes and shortcomings to share lessons learned and inspire innovation and action in and beyond the archipelago. We then discuss thematic challenges and opportunities of broad relevance to invaded ecosystems and human communities. Important research needs and possible actions include eradicating mammals from “mainland island” sanctuaries, assessing hidden threats from poorly known introduced species, harnessing genomic tools to eradicate disease vectors, structured decision making to achieve common objectives among diverse stakeholders, and enhancing capacity through nontraditional funding streams and progressive legislation. By shining a spotlight on invasive species at the front lines in Hawaii, we hope to catalyze strategic research and practice to help inform scientists and policymakers.

Hawaii↗

Transcriptomic response to elevated water temperatures in adult migrating Yukon River Chinook salmon (Oncorhynchus tshawytscha)

Chinook salmon ( Oncorhynchus tshawytscha ) declines are widespread and may be attributed, at least in part, to warming river temperatures. Water temperatures in the Yukon River and tributaries often exceed 18°C, a threshold commonly associated with heat stress and elevated mortality in Pacific salmon. Untangling the complex web of direct and indirect physiological effects of heat stress on salmon is difficult in a natural setting with innumerable system challenges but is necessary to increase our understanding of both lethal and sublethal impacts of heat stress on populations. The goal of this study was to characterize the cellular stress response in multiple Chinook salmon tissues after acute elevated temperature challenges. We conducted a controlled 4-hour temperature exposure (control, 18°C and 21°C) experiment on the bank of the Yukon River followed by gene expression (GE) profiling using a 3′-Tag-RNA-Seq protocol. The full transcriptome was analysed for 22 Chinook salmon in muscle, gill and liver tissue. Both the 21°C and 18°C treatments induced greater activity in genes associated with protein folding (e.g. HSP70, HSP90 mRNA) processes in all tissues. Global GE patterns indicate that transcriptomic responses to heat stress were highly tissue-specific, underscoring the importance of analyzing multiple tissues for determination of physiological effect. Primary superclusters (i.e. groupings of loosely related terms) of altered biological processes were identified in each tissue type, including regulation of DNA damage response (gill), regulation by host of viral transcription (liver) and regulation of the force of heart contraction (muscle) in the 21°C treatment. This study provides insight into mechanisms potentially affecting adult Chinook salmon as they encounter warm water during their spawning migration in the Yukon River and suggests that both basic and more specialized cellular functions may be disrupted.

Alaska↗

Inter-population differences in salinity tolerance of adult wild Sacramento splittail: osmoregulatory and metabolic responses to salinity

The Sacramento splittail ( Pogonichthys macrolepidotus ) is composed of two genetically distinct populations endemic to the San Francisco Estuary (SFE). The allopatric upstream spawning habitat of the Central Valley (CV) population connects with the sympatric rearing grounds via relatively low salinity waters, whereas the San Pablo (SP) population must pass through the relatively high-salinity Upper SFE to reach its allopatric downstream spawning habitat. We hypothesize that if migration through SFE salinities to SP spawning grounds is more challenging for adult CV than SP splittail, then salinity tolerance, osmoregulatory capacity, and metabolic responses to salinity will differ between populations. Osmoregulatory disturbances, assessed by measuring plasma osmolality and ions, muscle moisture and Na + -K + -ATPase activity after 168 to 336 h at 11‰ salinity, showed evidence for a more robust osmoregulatory capacity in adult SP relative to CV splittail. While both resting and maximum metabolic rates were elevated in SP splittail in response to increased salinity, CV splittail metabolic rates were unaffected by salinity. Further, the calculated difference between resting and maximum metabolic values, aerobic scope, did not differ significantly between populations. Therefore, improved osmoregulation came at a metabolic cost for SP splittail but was not associated with negative impacts on scope for aerobic metabolism. These results suggest that SP splittail may be physiologically adjusted to allow for migration through higher-salinity waters. The trends in interpopulation variation in osmoregulatory and metabolic responses to salinity exposures support our hypothesis of greater salinity-related challenges to adult CV than SP splittail migration and are consistent with our previous findings for juvenile splittail populations, further supporting our recommendation of population-specific management.

California↗

Subsurface structure across the Tacoma Basin, Washington State, using trans-dimensional Bayesian inversion of fundamental mode spatial autocorrelation data

Spatial autocorrelation (SPAC), the azimuthal average of the normalized cross-correlation between equidistant station pairs deployed in a 2-D array, is widely used to image the subsurface structure. However, the rigorous estimate of subsurface structure and its uncertainties as a function of depth using SPAC data is challenging due to the nonlinear relation between the SPAC data and Earth structure as well as the trade-off between depth and velocity. Additionally, data noise is strongly correlated due to data processing (e.g. filtering, stacking from multiple time segments and azimuthal averaging). Most studies do not account for the correlated noise and fix the ratio of compressional-wave velocity ( V P ) to shear-wave velocity ( V s ) (i.e. V P / V s ratio) and the number of layers, both of which are typically unknown. To address these challenges, we develop a hierarchical trans-dimensional Bayesian inversion of fundamental mode of SPAC data that properly accounts for the correlated data noise, samples the V P / V s ratio and relaxes the number of layers (i.e. model parametrization) to be unknown in the inversion. We further examine the limitation of using only fundamental modes in the inversion. Our synthetic experiments show that the inversion recovers an incorrect model unless we sample the correlated noise and V P / V s ratio in the inversion. The inversion is then applied to SPAC data acquired at 19 sites across the Tacoma basin in Washington State to characterize the V s and the time-averaged V s over 30-m depth ( V s 30 ). Our results show that the V s 30 varies from ∼200 to 800 m s −1 . The V s 30 within the basin is higher in the middle and lower on the east and west sides. We find that these V s 30 values vary with geologic unit. The uncertainties for V s 30 are within 20 m s −1 in average except for the most eastern site TB28. Additionally, the uncertainties are greater for deeper depths beneath most of the sites as the sensitivity decreases as a function of depth. The Vs structure as a function of depth is also complex beneath some sites, possibly because the SPAC curves are affected by higher order Rayleigh modes that are not considered in the inversion. To better constrain the deeper V s structure, V s 30 and/or other average measures of V s over depth, additional constraints from complementary data, such as ellipticity or geologic data are needed. Moreover, our synthetic experiments show that higher order modes can have significant effect in the inversion results, particularly when there is a low-velocity layer.

Washington↗

Comparative endocrinology in the 21st century

Hormones coordinate developmental, physiological, and behavioral processes within and between all living organisms. They orchestrate and shape organogenesis from early in development, regulate the acquisition, assimilation, and utilization of nutrients to support growth and metabolism, control gamete production and sexual behavior, mediate organismal responses to environmental change, and allow for communication of information between organisms. Genes that code for hormones; the enzymes that synthesize, metabolize, and transport hormones; and hormone receptors are important targets for natural selection, and variation in their expression and function is a major driving force for the evolution of morphology and life history. Hormones coordinate physiology and behavior of populations of organisms, and thus play key roles in determining the structure of populations, communities, and ecosystems. The field of endocrinology is concerned with the study of hormones and their actions. This field is rooted in the comparative study of hormones in diverse species, which has provided the foundation for the modern fields of evolutionary, environmental, and biomedical endocrinology. Comparative endocrinologists work at the cutting edge of the life sciences. They identify new hormones, hormone receptors and mechanisms of hormone action applicable to diverse species, including humans; study the impact of habitat destruction, pollution, and climatic change on populations of organisms; establish novel model systems for studying hormones and their functions; and develop new genetic strains and husbandry practices for efficient production of animal protein. While the model system approach has dominated biomedical research in recent years, and has provided extraordinary insight into many basic cellular and molecular processes, this approach is limited to investigating a small minority of organisms. Animals exhibit tremendous diversity in form and function, life-history strategies, and responses to the environment. A major challenge for life scientists in the 21st century is to understand how a changing environment impacts all life on earth. A full understanding of the capabilities of organisms to respond to environmental variation, and the resilience of organisms challenged by environmental changes and extremes, is necessary for understanding the impact of pollution and climatic change on the viability of populations. Comparative endocrinologists have a key role to play in these efforts.

Integrative and Comparative Biology↗

Identical sequence types of Yersinia ruckeri associated with lethal disease in wild-caught invasive Blue Catfish and cultured hybrid catfish (Channel Catfish ♀ × Blue Catfish ♂) from disparate aquatic ecosystems

Objective The Blue Catfish Ictalurus furcatus is commonly raised in warmwater aquaculture in the United States to produce Channel Catfish I. punctatus × Blue Catfish hybrids. It is also a prominent aquatic invasive species of concern in the mid-Atlantic region of the United States. Here, Yersina ruckeri was isolated from moribund Blue Catfish and hybrid catfish from disparate regions of the USA. The goal of the research here was to compare these Y. ruckeri strains to each other and other known strains for which adequate sequence data was available. In addition, we sought to determine if the strain from Blue Catfish was pathogenic to Rainbow Trout Oncorhynchus mykiss . Methods Moribund hybrid catfish from culture ponds in Mississippi were processed for diagnostic evaluation in March 2016. In April 2022, a moribund Blue Catfish specimen was collected from a tributary of the Nanticoke River in Maryland. Bacterial isolates were identified and characterized using biochemical tests, antimicrobial sensitivity screening, serotyping, and complete or partial genome sequencing. Disease pathology was described via histology. The isolate from Blue Catfish was used in challenge experiments to determine if it was pathogenic to Rainbow Trout. Multilocus sequencing typing was conducted using the PubMLST database. Results Biochemical testing was consistent with Y. ruckeri . A draft genome of the Y. ruckeri isolate was assembled based on Oxford Nanopore Technology sequencing and identified a single genomic replicon (3,791,418 bp) consistent in size to other Y. ruckeri genomes and a pLT plasmid (60, 933 bp). The challenge study demonstrated no significant virulence of this isolate for Rainbow Trout ( Y. ruckeri ). This isolate was most similar to other strains isolated from ictalurids. Notably, the gyrase B gene from this isolate was identical to that of archived strains isolated from moribund Mississippi hybrid catfish aquaculture during 2016 and these isolates share identical PubMLST sequence type profiles. Similarly, they shared a pLT plasmid that differed by only 6 bp. This plasmid has never been reported from trout isolates and appears to be unique to ictalurids. Conclusions Analyses here provide preliminary genetic evidence that geographically distant (Maryland and Mississippi, USA) isolates of Y. ruckeri from ictalurids are genetically similar to each other and Y. ruckeri (strain SC09) that infects ictalurids in China. This strain is not a biothreat to Rainbow Trout at typical culture temperatures.

Journal of Aquatic Animal Health↗

Bridging the research-implementation gap in avian conservation with translational ecology

The recognized gap between research and implementation in avian conservation can be overcome with translational ecology, an intentional approach in which science producers and users from multiple disciplines work collaboratively to co-develop and deliver ecological research that addresses management and conservation issues. Avian conservation naturally lends itself to translational ecology because birds are well studied, typically widespread, often exhibit migratory behaviors transcending geopolitical boundaries, and necessitate coordinated conservation efforts to accommodate resource and habitat needs across the full annual cycle. In this perspective, we highlight several case studies from bird conservation practitioners and the ornithological and conservation social sciences exemplifying the 6 core translational ecology principles introduced in previous studies: collaboration, engagement, commitment, communication, process, and decision-framing. We demonstrate that following translational approaches can lead to improved conservation decision-making and delivery of outcomes via co-development of research and products that are accessible to broader audiences and applicable to specific management decisions (e.g., policy briefs and decision-support tools). We also identify key challenges faced during scientific producer–user engagement, potential tactics for overcoming these challenges, and lessons learned for overcoming the research-implementation gap. Finally, we recommend strategies for building a stronger translational ecology culture to further improve the integration of these principles into avian conservation decisions. By embracing translational ecology, avian conservationists and ornithologists can be well positioned to ensure that future management decisions are scientifically informed and that scientific research is sufficiently relevant to managers. Ultimately, such teamwork can help close the research-implementation gap in the conservation sciences during a time when environmental issues are threatening avian communities and their habitats at exceptional rates and at broadening spatial scales worldwide.

Ornithological Applications↗

Satellite imagery can predict bird species occupancy and inform multispecies management in pine savannas

Multispecies management can contribute to meeting growing challenges of preserving biodiversity, yet current game and threatened species management often focuses on individual species. Satellite imagery available at high spatial and temporal resolution provides a potential tool to overcome the challenge posed by multispecies management of linking patterns of habitat use among species. We sought to determine whether satellite imagery could be used to describe patterns of species occupancy and inform multispecies management in pine savannas in Georgia, USA. We conducted point-count surveys at 7 sites in 2022 for 3 bird species: Colinus virginianus (Northern Bobwhite), Dryobates borealis (Red-cockaded Woodpecker), and Peucaea aestivalis (Bachman’s Sparrow). We built single-season occupancy models comparing a set of models using covariates collected from field vegetation surveys and another set using covariates extracted from Sentinel-2 satellite imagery. We then used a multi-objective optimization algorithm to identify quasi-optimal management solutions (i.e., sets of covariate values from top satellite imagery metric models). We found that models created using satellite imagery performed well at predicting occupancy of all 3 species as measured by the area under the receiver operating characteristic curve (AUC > 0.8) and had higher AUC scores than field-derived habitat covariate-based models. We found combinations of metrics that could result in high rates of predicted probability of occupancy for all species (within 86% of highest possible occupancy probability), but these combinations did not exist at any of the sites. Our results demonstrate that (1) satellite imagery can allow users to build reliable occupancy models without intensive field-based vegetation surveys; and (2) C. virginianus , D. borealis, and P. aestivalis in pine savanna ecosystems could be simultaneously managed through more frequent burning, changes in canopy cover or by producing suitable heterogeneity of habitats after identifying an appropriate scale of management.

Georgia↗

Fungal biology and agriculture: revisiting the field

Plant pathology has made significant progress over the years, a process that involved overcoming a variety of conceptual and technological hurdles. Descriptive mycology and the advent of chemical plant-disease management have been followed by biochemical and physiological studies of fungi and their hosts. The later establishment of biochemical genetics along with the introduction of DNA-mediated transformation have set the stage for dissection of gene function and advances in our understanding of fungal cell biology and plant-fungus interactions. Currently, with the advent of high-throughput technologies, we have the capacity to acquire vast data sets that have direct relevance to the numerous subdisciplines within fungal biology and pathology. These data provide unique opportunities for basic research and for engineering solutions to important agricultural problems. However, we also are faced with the challenge of data organization and mining to analyze the relationships between fungal and plant genomes and to elucidate the physiological function of pertinent DNA sequences. We present our perspective of fungal biology and agriculture, including administrative and political challenges to plant protection research.

Molecular Plant-Microbe Interactions↗

Differential virulence mechanisms of infectious hematopoietic necrosis virus in rainbow trout (Oncorhynchus mykiss) include host entry and virus replication kinetics

Host specificity is a phenomenon exhibited by all viruses. For the fish rhabdovirus infectious hematopoietic necrosis virus (IHNV), differential specificity of virus strains from the U and M genogroups has been established both in the field and in experimental challenges. In rainbow trout (Oncorhynchus mykiss), M IHNV strains are consistently more prevalent and more virulent than U IHNV. The basis of the differential ability of these two IHNV genogroups to cause disease in rainbow trout was investigated in live infection challenges with representative U and M IHNV strains. When IHNV was delivered by intraperitoneal injection, the mortality caused by U IHNV increased, indicating that the low virulence of U IHNV is partly due to inefficiency in entering the trout host. Analyses of in vivo replication showed that U IHNV consistently had lower prevalence and lower viral load than M IHNV during the course of infection. In analyses of the host immune response, M IHNV-infected fish consistently had higher and longer expression of innate immune-related genes such as Mx-1. This suggests that the higher virulence of M IHNV is not due to suppression of the immune response in rainbow trout. Taken together, the results support a kinetics hypothesis wherein faster replication enables M IHNV to rapidly achieve a threshold level of virus necessary to override the strong host innate immune response. ?? 2009 SGM.

Journal of General Virology↗

A system dynamics model to understand the integrated ecological and human dimension aspects of wildlife health and disease management

Chronic wasting disease (CWD) presents an ongoing challenge for the management of deer populations and sustaining harvest opportunities across North America. Existing disease models often fail to fully capture the complex interplay between disease dynamics, host ecology, and socio-economic factors. We developed a comprehensive system dynamics (SD) model that integrates demographic, epidemiological, ecological, and socio-economic processes within a single model to more fully characterize the complex network of causal feedbacks throughout the system. The model was calibrated using a Bayesian approach that incorporates prior knowledge to generate biologically interpretable outcomes, even with sparse data. For estimating the joint posterior distribution of model parameters, we leveraged time series of deer abundance, harvest composition, genetic profiles, CWD surveillance, and hunter demographics and behavior. Model outputs reproduced key system behaviors, including observed CWD prevalence trends, deer population dynamics, and hunter license purchasing patterns. Model predictions were most sensitive to parameters governing initial deer population size and recruitment. While model predictions generally aligned with observed data, discrepancies in early CWD detection and overestimation of the reactivation of long-inactive hunters reflect data limitations and modeling challenges. Key results suggest that indirect transmission is necessary to explain observed prevalence, that transmission is moderately density-dependent, and that observed population-level genetic shifts driven by CWD may play a role in transmission and progression. The SD modelling approach enabled estimation of difficult-to-measure parameters and identified potential leverage points for management—such as prioritizing increasing participation in antlerless harvest of existing hunters over the recruitment of new hunters. This integrated modeling approach offers a flexible foundation for adaptive wildlife disease management and emphasizes the value of unifying biological and human dimension processes to better inform effective, evidence-based policy.

BioRxiv↗

A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters

Occurrences of harmful algal blooms (HABs) in rivers challenge the belief that rivers are not susceptible to HABs because of their short residence times and fluctuating hydrology. Here we present a systematic literature review of predictive and forecasting models for HABs in flowing waters, including rivers, flowing in-stream reservoirs (e.g., run-of-river reservoirs and lock-and-dam systems) and tidal or estuarine systems with riverine processes. The review aimed to understand current and historical modeling approaches for predicting and forecasting river HABs, without restricting to specific taxa, such as cyanobacteria, or modeling endpoints. The review included 162 articles published over nearly 50 years, covering more than 80 rivers worldwide. Eutrophic, non-wadable rivers with in-stream obstruction were commonly modeled, though diverse environmental characteristics were reported. Most articles used algal biomass or chlorophyll as modeling endpoints, with a quarter using novel or unique endpoints. Algal toxins motivated model development in 23% of the articles, however just 5% used algal toxins as an endpoint. Only 6% of the articles modeled benthic HABs; the rest focused on pelagic HABs. There was no standard model used for modeling river HABs. Process-based models were more common (59%) than data-driven approaches (37%), with model formulations ranging from simple to complex, which contrasts with a lake-focused literature review of HAB models that found data-driven models were more common. Models in river settings shared similar input variables as those previously identified for lakes, such as water temperature, nutrients, and light availability. However, streamflow and other transport metrics took prominence in river models compared to lake models. Algal cell physiology (such as growth, predation, and motility) was routinely included as input data or as mathematical formulations in process-based models and these processes were frequently identified as an important predictor by the articles’ authors. Conversely, data-driven models rarely included these processes, instead using predictors related to environmental conditions, such as nutrients, water quality, water temperature, and streamflow. These important proxy predictors have apparent success with modeling overall algal biomass (irrespective of taxa) whereas other factors, such as those related to algal physiology and other biological processes, are likely responsible for more subtle shifts in community composition. These differences highlight the influence of data availability, especially for processes that are difficult, time-consuming, or expensive to measure, on model development and model outcomes, raising questions about the selection of modeling inputs and endpoints. Challenges to advancing river HAB modeling include the lack of site-specific model inputs representing key processes (e.g., photosynthetic parameters and predation rates), overlooked riverine environments like the benthos and side/back-channel areas, lack of information on environmental settings, and poorly reported model performance metrics. This review emphasizes opportunities for advancing river HAB modeling by learning from well-honed estuarine models, supporting current forecasting and operationalization efforts, and developing common datasets for river HAB model development and evaluation.

BioRxiv↗