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The power, potential, and pitfalls of open access biodiversity data in range size assessments: Lessons from the fishes

Geographic rarity is a driver of a species’ intrinsic risk of extinction. It encompasses multiple key components including range size, which is one of the most commonly measured estimates of geographic rarity. Range size estimates are often used to prioritize conservation efforts when there are multiple candidate species, because data for other components of rarity such as population size are sparse, or do not exist for species of interest. Range size estimates can provide rankings of species vulnerability to changing environments or threats, identifying rare species for future study or conservation initiatives. However, range sizes can be estimated by several different metrics, and the degree of overlap in the identification of the rarest or most common species across methodologies is not well understood. This knowledge gap compromises our ability to prioritize correctly rare species, and presents a particularly difficult challenge for stream-dwelling organisms with distributions constrained to river networks. We evaluated the relationship of multiple range size estimates of a subset of freshwater fishes native to the United States to determine the degree of overlap in rarity rankings using different data sources and grain sizes. We used publicly available, open access data from the Global Biodiversity Information Facility (GBIF) to calculate extent of occurrence (minimum convex polygons) and area of occupancy (total area occupied, measured across various grain sizes). We compared range sizes estimated using GBIF data with the best available estimates of current distributions described by publicly available digital maps (NatureServe) to evaluate the efficacy of GBIF data in assessments of range size. We found strong correlations between range size estimates across analytical approaches and data sources with no detectable bias of taxonomy. We found that variation among rarity rankings was highest for species with intermediate range sizes indicating that the approaches considered here generally converge when used to identify the rarest or the most common species. Importantly, our results show that the rarest, and perhaps the most vulnerable, species are consistently identified across common methodological approaches. More broadly, our results support the use of open access biodiversity data that include opportunistically collated and collected point occurrence records as a complement to coarse-grain (e.g., whole range map) approaches, as we observed no systematic bias or deviation across data sources in our analyses. This indicates databases such as the GBIF may help fill important fundamental and applied knowledge gaps for many poorly understood species, particularly in a broad-scale, multispecies framework.

Ecological Indicators

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

Comparative phylogenomics reveal complex evolution of life history strategies in a clade of bivalves with parasitic larvae (Bivalvia: Unionoida: Ambleminae)

Freshwater mussels are a species‐rich group with biodiversity patterns strongly shaped by a life history strategy that includes an obligate parasitic larval stage. In this study, we set out to reconstruct the life history evolution and systematics in a clade of freshwater mussels adapted to parasitizing a molluscivorous host fish. Anchored hybrid enrichment and ancestral character reconstruction revealed a complex pattern of life history evolution with host switching and multiple instances of convergence, including reduction in size of larvae, increased fecundity, and growth during encapsulation. Our phylogenomic analyses also recovered non‐monophyly of taxa exhibiting multiple traits used as the basis for previous taxonomic hypotheses. Taxa with axe‐head shaped glochidia were resolved as paraphyletic, but our results strongly suggest the complex morphology is an adaptation to reduce larval size, with reduction in size further accentuated in taxa previously assigned to Leptodea . To more accurately reflect the evolutionary history of this group, we make multiple systematic changes, including the description of a new genus, Atlanticoncha gen. nov. , and the synonymy of the genus Leptodea under Potamilus . Our findings contribute to the growing body of literature showing that cladistic hypotheses based solely on morphological characters, including larval morphology, can be flawed in freshwater mussels.

Cladistics

Characterizing fish community diversity across Virginia landscapes: Prerequisite for conservation

The number of community types occurring within landscapes is an important, but often unprotected, component of biological diversity. Generally applicable protocols for characterizing community diversity need to be developed to facilitate conservation. We used several multivariate techniques to analyze geographic variation in the composition of fish communities in Virginia streams. We examined relationships between community composition and six landscape variables: drainage basin, physiography, stream order, elevation, channel slope, and map coordinates. We compared patterns at two scales (statewide and subdrainage-specific) to assess sensitivity of community classification to spatial scale. We also compared patterns based on characterizing communities by species composition vs. ecological composition. All landscape variables explained significant proportions of the variance in community composition. Statewide, they explained 32% of the variance in species composition and 48% of the variance in ecological composition. Typical communities in each drainage or physiography were statistically distinctive. Communities in different combinations of drainage, physiography, and stream size were even more distinctive, but composition was strongly spatially autocorrelated. Ecological similarity and species similarity of community pairs were strongly related, but replacement by ecologically similar species was common among drainage–physiography combinations. Landscape variables explained significant proportions of variance in community composition within selected subdrainages, but proportions were less than at the statewide scale, and the explanatory power of individual variables varied considerably among subdrainages. Community variation within subdrainages appeared to be much more closely related to environmental variation than to replacement among ecologically similar species. Our results suggest that taxonomic and ecological characterizations of community composition are complementary; both are useful in a conservation context. Landscape features such as drainage, physiography, and water body size generally may provide a basis for assessing aquatic community diversity, especially in regions where the biota is poorly known. Systematic conservation of community types would be a major advance relative to most current conservation programs, which typically focus narrowly on populations of imperiled species. More effective conservation of aquatic biodiversity will require new approaches that recognize the value of both species and assemblages, and that emphasize protection of key landscape-scale processes.

Ecological Applications

Biological responses to climate impacts with a focus on Regional Species of Greatest Conservation Need (RSGCN)

This chapter reviews the responses to climate change on the 367 Regional Species of Greatest Conservation Need (RSGCN) identified by the Northeast Fish and Wildlife Diversity Technical Committee (NEFWDTC), technical experts from states’ natural resource agencies (Appendix 3.1). These species were chosen based on their conservation status, listing in SWAPs, and the percentage of their range that occurs in the Northeast. The objectives of this chapter are to: summarize how regional biodiversity has already responded and is expected to respond to climate change; summarize information on specific RSGCN species responses to climate change to date and anticipated under future scenarios; characterize the greatest uncertainties about how biodiversity and RSGCN species will respond to climate change in the future; and highlight where other factors are expected to exacerbate the effects of climate change. This information was obtained through a systematic review of the peer-reviewed literature, primarily using the ISI Web of Knowledge to search for papers on each species related to “climate”, “temperature”, or “precipitation”. Although we undoubtedly missed some sources, the following allows us to review some of the ways climate change will affect regional species of conservation concern

Connecticut, Delaware, Massachusetts, Maryland, Ma

A metadata checklist and data formatting guidelines to make eDNA FAIR (Findable, Accessible, Interoperable and Reusable)

The success of environmental DNA (eDNA) approaches for species detection has revolutionized biodiversity monitoring and distribution mapping. Targeted eDNA amplification approaches, such as quantitative PCR, have improved our understanding of species distribution, and metabarcoding-based approaches have enabled biodiversity assessment at unprecedented scales and taxonomic resolution. eDNA datasets, however, are often scattered across repositories with inconsistent formats, varying access restrictions, and inadequate metadata; this limits their interoperation, reuse, and overall impact. Adopting FAIR (Findable, Accessible, Interoperable, and Reusable) data practices with eDNA data can transform the monitoring of biodiversity and individual species and support data-driven biodiversity management across broad scales. FAIR practices remain underdeveloped in the eDNA community, partly due to gaps in adapting existing vocabularies, such as Darwin Core (DwC) and Minimum Information about any (x) Sequence (MIxS), to eDNA-specific needs and workflows. To address these challenges, we propose a comprehensive FAIR eDNA (FAIRe) Metadata Checklist, which integrates existing data standards and introduces new terms tailored to eDNA workflows. Metadata are systematically linked to both raw data (e.g., metabarcoding sequences, Ct/Cq values of targeted qPCR assays) and derived biological observations (e.g., Amplicon Sequence Variant (ASV)/Operational Taxonomic Unit (OTU) tables, species presence/absence). Along with formatting guidelines, tools, templates, and example datasets, we introduce a standardized, ready-to-use approach for FAIR eDNA practices. Through broad collaboration, we seek to integrate these guidelines into established biodiversity and molecular data standards, promote journal data policies, and foster user-driven improvements and uptake of FAIR practices among eDNA data producers. In proposing this standardized approach and developing a long-term plan with key databases and data standard organizations, the goal is to enhance accessibility, maximize reuse, and elevate the scientific impact of these valuable biodiversity data resources.

Environmental DNA

Spatial partitioning of environmental correlates of avian biodiversity in the conterminous United States

Classification and regression tree (CART) analysis was used to create hierarchically organized models of the distribution of bird species richness across the conterminous United States. Species richness data were taken from the Breeding Bird Survey and were related to climatic and land use data. We used a systematic spatial grid of approximately 12,500 hexagons, each approximately 640 square kilometres in area. Within each hexagon land use was characterized by the Loveland et al. land cover classification based on Advanced Very High Resolution Radiometer (AVHRR) data from NOAA polar orbiting meteorological satellites. These data were aggregated to yield fourteen land classes equivalent to an Anderson level II coverage; urban areas were added from the Digital Chart of the World. Each hexagon was characterized by climate data and landscape pattern metrics calculated from the land cover. A CART model then related the variation in species richness across the 1162 hexagons for which bird species richness data were available to the independent variables, yielding an R2-type goodness of fit metric of 47.5% deviance explained. The resulting model recognized eleven groups of hexagons, with species richness within each group determined by unique sequences of hierarchically constrained independent variables. Within the hierarchy, climate data accounted for more variability in the bird data, followed by land cover proportion, and then pattern metrics. The model was then used to predict species richness in all 12,500 hexagons of the conterminous United States yielding a map of the distribution of these eleven classes of bird species richness as determined by the environmental correlates. The potential for using this technique to interface biogeographic theory with the hierarchy theory of ecology is discussed. ?? 1996 Blackwell Science Ltd.

Biodiversity Letters

Prioritizing river basins for nutrient studies

Increases in fluxes of nitrogen (N) and phosphorus (P) in the environment have led to negative impacts affecting drinking water, eutrophication, harmful algal blooms, climate change, and biodiversity loss. Because of the importance, scale, and complexity of these issues, it may be useful to consider methods for prioritizing nutrient research in representative drainage basins within a regional or national context. Two systematic, quantitative approaches were developed to (1) identify basins that geospatial data suggest are most impacted by nutrients and (2) identify basins that have the most variability in factors affecting nutrient sources and transport in order to prioritize basins for studies that seek to understand the key drivers of nutrient impacts. The “impact” approach relied on geospatial variables representing surface-water and groundwater nutrient concentrations, sources of N and P, and potential impacts on receptors (i.e., ecosystems and human health). The “variability” approach relied on geospatial variables representing surface-water nutrient concentrations, factors affecting sources and transport of nutrients, model accuracy, and potential receptor impacts. One hundred and sixty-three drainage basins throughout the contiguous United States were ranked nationally and within 18 hydrologic regions. Nationally, the top-ranked basins from the impact approach were concentrated in the Midwest, while those from the variability approach were dispersed across the nation. Regionally, the top-ranked basin selected by the two approaches differed in 15 of the 18 regions, with top-ranked basins selected by the variability approach having lower minimum concentrations and larger ranges in concentrations than top-ranked basins selected by the impact approach. The highest ranked basins identified using the variability approach may have advantages for exploring how landscape factors affect surface-water quality and how surface-water quality may affect ecosystems. In contrast, the impact approach prioritized basins in terms of human development and nutrient concentrations in both surface water and groundwater, thereby targeting areas where actions to reduce nutrient concentrations could have the largest effect on improving water availability and reducing ecosystem impacts.

Environmental Monitoring and Assessment

Pathology of tissue loss in three key gorgonian species in the Mediterranean Sea

The Mediterranean is known for its marine biodiversity, especially gorgonian forests. Unfortunately, these are experiencing rapid declines due to climate change, manifested by repeated marine heat waves resulting in mass mortality events since the early 1990 s. To better understand why gorgonians are declining, more systematic approaches to investigate the exact causes are needed, and pathology may aid in this goal. We described gross and microscopic pathology of tissue loss in three key gorgonian species in the Mediterranean region, Paramuricea clavata , Eunicella cavolini , and Leptogorgia sarmentosa , that were all experiencing various degrees of acute to subacute tissue loss characterized by exposed axial skeleton sometimes partly colonized by epibionts and thinning of adjacent tissues. The most significant variety of lesions was seen in P. clavata followed by L. sarmentosa and E. cavolini. For all species, dissociation of gastrodermal cells was the dominant microscopic lesion followed by necrosis of the gastrodermis. Ciliates invading gastrodermis and associated with necrosis of polyps were seen only in E. cavolini. Epidermal tissue loss was seen only in L. sarmentosa , while P. clavata was distinguished by a prominent inflammatory response and unidentified dark round structures within the tentacle epidermis and gastrodermis with no host response. Further work to understand the cause of death in gorgonians is needed, particularly to elucidate the role of ciliates and environmental co-factors or infectious agents not visible on light microscopy, as well as applications of additional tools such as cytology.

Journal of Invertebrate Pathology

Preserving reptiles for research

What are voucher specimens and why do we collect them? Voucher specimens are animals and/or their parts that are deposited in a research museum to document the occurrence of a taxon at a specific location in space and time (Pleijel et al., 2008; Reynolds and McDiarmid, 2012). For field biologists, vouchers are the repeatable element of a field study as they allow other biologists, now and in the future, to confirm the identity of species that were studied. The scientific importance of a voucher specimen or series of specimens is that other people are afforded the opportunity to examine the entire animal and confirm or correct identifications. A photographic record is somewhat useful for recording the occurrence of a species, but such records can be insufficient for reliable confirmation of specific identity. Even if a photo shows diagnostic characters of currently recognized taxa, it may not show characters that separate taxa that may be described in the future. Substantial cryptic biodiversity is being found in even relatively well-known herpetofaunas (Crawford et al., 2010), and specimens allow researchers to retroactively evaluate the true diversity in a study as understanding of taxonomy evolves. They enable biologists to study the systematic relationships of populations by quantifying variation in different traits. Specimens are also a source of biological data such as behaviour, ecology, epidemiology, and reproduction through examination of their anatomy, reproductive and digestive tracts, and parasites (Suarez and Tsutsui, 2004). Preserving reptiles as vouchers is not difficult, although doing it properly requires care, effort, and time. Poorly preserved vouchers can invalidate the results and conclusions of your study because of the inability to confirm the identity of your study animals. Good science requires repeatability of observations, and the absence of vouchers or poorly preserved ones prevents such confirmation. Due to space restrictions, we are unable to go into as much detail as we would like in this chapter. A number of publications give more details on some topics discussed in this chapter, such as Pisani (1973), Pisani and Villa (1974), Etheridge (1996), Karns (1986), McDiarmid (1994), Cortez et al. (2006), Foster (2012) (and subchapters therein), Reynolds and McDiarmid (2012), and Simmons (2015). Although some of these works focus on amphibians, they also apply to reptiles in many aspects.

Book chapter

A centroid model of species distribution with applications to the Carolina wren Thryothorus ludovicianus and house finch Haemorhous mexicanus in the United States

Drastic shifts in species distributions are a cause of concern for ecologists. Such shifts pose great threat to biodiversity especially under unprecedented anthropogenic and natural disturbances. Many studies have documented recent shifts in species distributions. However, most of these studies are limited to regional scales, and do not consider the abundance structure within species ranges. Developing methods to detect systematic changes in species distributions over their full ranges is critical for understanding the impact of changing environments and for successful conservation planning. Here, we demonstrate a centroid model for range-wide analysis of distribution shifts using the North American Breeding Bird Survey. The centroid model is based on a hierarchical Bayesian framework which models population change within physiographic strata while accounting for several factors affecting species detectability. Yearly abundance-weighted range centroids are estimated. As case studies, we derive annual centroids for the Carolina wren and house finch in their ranges in the U.S. We further evaluate the first-difference correlation between species’ centroid movement and changes in winter severity, total population abundance. We also examined associations of change in centroids from sub-ranges. Change in full-range centroid movements of Carolina wren significantly correlate with snow cover days (r = −0.58). For both species, the full-range centroid shifts also have strong correlation with total abundance (r = 0.65, and 0.51 respectively). The movements of the full-range centroids of the two species are correlated strongly (up to r = 0.76) with that of the sub-ranges with more drastic population changes. Our study demonstrates the usefulness of centroids for analyzing distribution changes in a two-dimensional spatial context. Particularly it highlights applications that associate the centroid with factors such as environmental stressors, population characteristics, and progression of invasive species. Routine monitoring of changes in centroid will provide useful insights into long-term avian responses to environmental changes.

Ecography

The conservation status of the world’s reptiles

Effective and targeted conservation action requires detailed information about species, their distribution, systematics and ecology as well as the distribution of threat processes which affect them. Knowledge of reptilian diversity remains surprisingly disparate, and innovative means of gaining rapid insight into the status of reptiles are needed in order to highlight urgent conservation cases and inform environmental policy with appropriate biodiversity information in a timely manner. We present the first ever global analysis of extinction risk in reptiles, based on a random representative sample of 1500 species (16% of all currently known species). To our knowledge, our results provide the first analysis of the global conservation status and distribution patterns of reptiles and the threats affecting them, highlighting conservation priorities and knowledge gaps which need to be addressed urgently to ensure the continued survival of the world’s reptiles. Nearly one in five reptilian species are threatened with extinction, with another one in five species classed as Data Deficient. The proportion of threatened reptile species is highest in freshwater environments, tropical regions and on oceanic islands, while data deficiency was highest in tropical areas, such as Central Africa and Southeast Asia, and among fossorial reptiles. Our results emphasise the need for research attention to be focussed on tropical areas which are experiencing the most dramatic rates of habitat loss, on fossorial reptiles for which there is a chronic lack of data, and on certain taxa such as snakes for which extinction risk may currently be underestimated due to lack of population information. Conservation actions specifically need to mitigate the effects of human-induced habitat loss and harvesting, which are the predominant threats to reptiles.

Biological Conservation

Using systematic conservation planning to recover climate resilient habitat for threatened and endangered species while retaining areas of cultural importance

The effective management of at-risk species often requires fine-scale actions by natural resource managers. However, balancing these actions with concurrent land uses is challenging, particularly when compounded by the interplay of climate shifts, and escalating wildland–urban interface conflicts. We used spatial prioritization tools designed for biodiversity conservation to help resource managers on the Island of Lānaʻi prioritize mutually exclusive land use objectives: endangered species recovery and subsistence and recreational hunting. We weighed the current and anticipated future distributions of threatened and endangered plant species against the distribution of non-native game mammals to plan for species recovery more effectively. Prioritization results identified multiple footprints that could support recovery of all endangered species targets in climate resilient areas while retaining the majority of existing hunting areas. However, very little native vegetation was retained in conservation footprints without deliberate inclusion, which increased footprint area by 268%. Scenarios which prioritized contiguous conservation areas also dramatically increased conservation footprint area, although these scenarios may reduce associated fencing costs. This work demonstrates how spatial prioritization may guide localized species recovery efforts by supporting long-term conservation planning that addresses anticipated climate-driven increases in conflict between conservation and other land uses, with clear applicability beyond Lānaʻi.

Conservation

GRA prospectus: optimizing design and management of protected areas

Protected areas comprise one major type of global conservation effort that has been in the form of parks, easements, or conservation concessions. Though protected areas are increasing in number and size throughout tropical ecosystems, there is no systematic method for optimally targeting specific local areas for protection, designing the protected area, and monitoring it, or for guiding follow-up actions to manage it or its surroundings over the long run. Without such a system, conservation projects often cost more than necessary and/or risk protecting ecosystems and biodiversity less efficiently than desired. Correcting these failures requires tools and strategies for improving the placement, design, and long-term management of protected areas. The objective of this project is to develop a set of spatially based analytical tools to improve the selection, design, and management of protected areas. In this project, several conservation concessions will be compared using an economic optimization technique. The forest land use portfolio model is an integrated assessment that measures investment in different land uses in a forest. The case studies of individual tropical ecosystems are developed as forest (land) use and preservation portfolios in a geographic information system (GIS). Conservation concessions involve a private organization purchasing development and resource access rights in a certain area and retiring them. Forests are put into conservation, and those people who would otherwise have benefited from extracting resources or selling the right to do so are compensated. Concessions are legal agreements wherein the exact amount and nature of the compensation result from a negotiated agreement between an agent of the conservation community and the local community. Funds are placed in a trust fund, and annual payments are made to local communities and regional/national governments. The payments are made pending third-party verification that the forest expanse and quality have been maintained.

Open-File Report

Establishing the foundation for the global observing system for marine life

Maintaining healthy, productive ecosystems in the face of pervasive and accelerating human impacts including climate change requires globally coordinated and sustained observations of marine biodiversity. Global coordination is predicated on an understanding of the scope and capacity of existing monitoring programs, and the extent to which they use standardized, interoperable practices for data management. Global coordination also requires identification of gaps in spatial and ecosystem coverage, and how these gaps correspond to management priorities and information needs. We undertook such an assessment by conducting an audit and gap analysis from global databases and structured surveys of experts. Of 371 survey respondents, 203 active, long-term (>5 years) observing programs systematically sampled marine life. These programs spanned about 7% of the ocean surface area, mostly concentrated in coastal regions of the United States, Canada, Europe, and Australia. Seagrasses, mangroves, hard corals, and macroalgae were sampled in 6% of the entire global coastal zone. Two-thirds of all observing programs offered accessible data, but methods and conditions for access were highly variable. Our assessment indicates that the global observing system is largely uncoordinated which results in a failure to deliver critical information required for informed decision-making such as, status and trends, for the conservation and sustainability of marine ecosystems and provision of ecosystem services. Based on our study, we suggest four key steps that can increase the sustainability, connectivity and spatial coverage of biological Essential Ocean Variables in the global ocean: (1) sustaining existing observing programs and encouraging coordination among these; (2) continuing to strive for data strategies that follow FAIR principles (findable, accessible, interoperable, and reusable); (3) utilizing existing ocean observing platforms and enhancing support to expand observing along coasts of developing countries, in deep ocean basins, and near the poles; and (4) targeting capacity building efforts. Following these suggestions could help create a coordinated marine biodiversity observing system enabling ecological forecasting and better planning for a sustainable use of ocean resources.

Frontiers in Marine Science

Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

Journal of Fish and Wildlife Management

An inventory and typology of permanent floodplain lakes in the Mississippi alluvial valley: A first step to conservation planning

The alluvial valley of the Mississippi River is an extensive area harboring hundreds of lakes created by fluvial dynamics. These floodplain lakes are scattered throughout the valley and carved over thousands of years by shifting river courses and other hydro-fluvial processes associated with contemporary and prehistoric rivers. These lakes have significant ecological importance as they support a large component of North American biodiversity. We used remote sensing to catalog lakes, to characterize morphology, and to construct a typology via cluster analysis. We identified over 1,300 permanent lakes totaling over 100,000 ha. The lakes were classified into 12 types according to lake size, shape, depth, connectivity, inundation frequency, and surrounding landcover. We anticipate that biotic characteristics differ among the 12 types, but large-scale systematic analyses of biotic assemblages of floodplain lakes in the region are mostly absent. Our typology can provide the framework essential for organizing research to define water dynamics, water quality, and ecological conditions such as forests, mussel, fish, and avian communities to construct conservation plans. The typology encourages a large-scale view of the properties of floodplain lakes in the alluvial valley. It is a functional tool that can be used to begin identifying conservation and research needs, adapt monitoring and management programs, customize environmental programs, and use conservation resources more effectively to achieve large-scale management objectives.

Mississippi River

A framework tool that applies weight-of-evidence integration to the analysis of existing datasets to guide freshwater conservation

The overarching issue we address here is how to extract clear and actionable ecological and management insights from real-world field data that often do not satisfy traditional statistical assumptions. Toward this goal, we developed a general 12+6 step adaptive management framework tool. We applied this framework tool to existing biodiversity monitoring data to create a proof-of-concept result that addresses the overarching question of “ why might a specific native stream fish taxon be present or absent at specific locations? ” Our multi-step framework tool links established steps and steps that are unique to our framework through weight-of evidence (WOE) integration, an approach that combines quantitative results from multiple visualization and statistical procedures. The systematic use of all steps in our framework can provide improved conservation outcomes compared to a single analysis. Advantages accrue from our approach because our framework tool refines the overarching goal into related sub-questions, applies a specific quantitative procedure to each sub-step, combines results from all sub-questions using a WOE integration, identifies testable questions that elucidate ambiguities and gaps revealed through WOE integration, and proposes practical field methods for obtaining this clarifying information through future research and data collections. The process of considering multiple visualizations and analyses as individual pieces of a shared puzzle offers a new way to approach the use of existing data. Our team-based approach transforms the collection and analysis of existing data into a series of field tests that can guide future actions (e.g., data collection-analysis events, restoration initiatives, research). Habitat and impact regressors will vary with taxa and system, but our structured process tool has broad generality for a range of conservation issues in which freshwater systems are threatened by human impacts.

Kansas