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At least 361 records · Page 20Linked to original sources

Predicting disease spread from host movement data: Chronic wasting disease in North America as a case study

1. Rare long-distance movements can increase the spatial spread of invasive species and shifts in species ranges. However, in the context of wildlife disease spread, seasonal migrations only matter if they lead to transmission beyond an individual’s initial set of contacts, and the importance of juvenile dispersal depends on whether those juveniles become infected before they disperse. 2. High resolution animal movement data are increasing, but it is unclear how to leverage these data to improve predictions future disease spread particularly in regions without pre-existing movement data. 3. We predicted the speed of chronic wasting disease (CWD) spread based on movement metrics of mule deer ( Odocoileus hemionus ) and white-tailed deer ( Odocoileus virginianus ) and compared our predictions to observed spreading rates in North America from 2005 to 2022. We hypothesized that CWD should spread faster in regions with long-distance migratory mule deer, but this hypothesis was only partially supported. 4. Observed rates of CWD spread were faster in western epicenters with more mobile mule deer than in epicenters with only white-tailed deer (14-18 km/yr compared to 5-7 km/yr, respectively). However, the observed speed of CWD spread did not align well with migration distances. Deer movements in the Canadian Prairie Provinces (CPP) were far shorter than those in Colorado and Wyoming, yet had faster CWD spread much of which was open prairies where deer movements tend to be along riverine corridors rather than the longer elevational migrations in more montane regions. 5. Generally, our predicted rates of CWD spread from three different models were far slower than the observed rates regardless of whether the model included dispersal or migration. Understanding of these discrepancies is needed before high-resolution animal movement data can be used to predict broad-scale patterns of disease invasion. 6. Anthropogenic movements likely explain longer-distance movements of CWD across North America, but it remains unclear whether human-mediated movements or alternative analytical methods and deer movement metrics can explain the faster than predicted local CWD spread.

Journal of Animal Ecology

elfgen: A new instream flow framework for rapid generation and optimization of flow-ecology relations

Effective water resource management requires practical, data‐driven determination of instream flow needs. Newly developed, high‐resolution flow models and aquatic species databases provide enormous opportunity, but the volume of data can prove challenging to manage without automated tools. The objective of this study was to develop a framework of analytical methods and best practices to reduce costs of entry into flow–ecology analysis by integrating widely available hydrologic and ecological datasets. Ecological limit functions (ELFs) describing the relation between maximum species richness and stream size characteristics (streamflow or drainage area) were developed. Species richness is expected to increase with streamflow through a watershed up to a point where it either plateaus or transitions to a decreasing trend in larger streams. Our results show that identifying the location of this "breakpoint" is critical for producing optimal ELF model fit. We found that richness breakpoints can be estimated using automated low‐supervision methods, with high‐supervision providing negligible improvement in detection accuracy. Model fit (and predictive capability) was found to be superior in smaller hydrologic units. The ELF model ("elfgen" R package available on GitHub: https://github.com/HARPgroup/elfgen ) can be used to generate ELFs using built‐in datasets for the conterminous United States, or applied anywhere else streamflow and biodiversity data inputs are available.

Virginia

A multistate dynamic site occupancy model for spatially aggregated sessile communities

Estimation of transition probabilities of sessile communities seems easy in principle but may still be difficult in practice because resampling error (i.e. a failure to resample exactly the same location at fixed points) may cause significant estimation bias. Previous studies have developed novel analytical methods to correct for this estimation bias. However, they did not consider the local structure of community composition induced by the aggregated distribution of organisms that is typically observed in sessile assemblages and is very likely to affect observations. We developed a multistate dynamic site occupancy model to estimate transition probabilities that accounts for resampling errors associated with local community structure. The model applies a nonparametric multivariate kernel smoothing methodology to the latent occupancy component to estimate the local state composition near each observation point, which is assumed to determine the probability distribution of data conditional on the occurrence of resampling error. By using computer simulations, we confirmed that an observation process that depends on local community structure may bias inferences about transition probabilities. By applying the proposed model to a real data set of intertidal sessile communities, we also showed that estimates of transition probabilities and of the properties of community dynamics may differ considerably when spatial dependence is taken into account. Results suggest the importance of accounting for resampling error and local community structure for developing management plans that are based on Markovian models. Our approach provides a solution to this problem that is applicable to broad sessile communities. It can even accommodate an anisotropic spatial correlation of species composition, and may also serve as a basis for inferring complex nonlinear ecological dynamics.

Methods in Ecology and Evolution

Functional connectivity in a continuously distributed, migratory species as revealed by landscape genomics

Maintaining functional connectivity is critical for the long-term conservation of wildlife populations. Landscape genomics provides an opportunity to assess long-term functional connectivity by relating environmental variables to spatial patterns of genomic variation resulting from generations of movement, dispersal and mating behaviors. Identifying landscape features associated with gene flow at large geographic scales for highly mobile species is becoming increasingly possible due to more accessible genomic approaches, improved analytical methods and enhanced computational power. We characterized the genetic structure and diversity of migratory mule deer Odocoileus hemionus using 4051 single nucleotide polymorphisms in 406 individuals sampled across multiple habitats throughout Wyoming, USA. We then identified environmental variables associated with genomic variation within genetic groups and statewide using a stepwise approach to first evaluate nonlinear relationships of landscape resistance with genetic distances and then use mixed-effects modeling to choose top landscape genomic models. We identified three admixed genetic groups of mule deer and found that environmental variables associated with gene flow varied among genetic groups, revealing scale-dependent and regional variation in functional connectivity. At the statewide scale, more gene flow occurred in areas with low elevation and mixed habitat. In the southern genetic group, more gene flow occurred in areas with low elevation. In the northern genetic group, more gene flow occurred in grassland and forest habitats, while highways and energy infrastructure reduced gene flow. In the western genetic group, the null model of isolation by distance best represented genetic patterns. Overall, our findings highlight the role of different seasonal ranges on mule deer genetic connectivity, and show that anthropogenic features hinder connectivity. This study demonstrates the value of combining a large, genome-wide marker set with recent advances in landscape genomics to evaluate functional connectivity in a wide-ranging migratory species.

Wyoming

Modelling dendritic ecological networks in space: anintegrated network perspective

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2-D space can be used to explore the influence of multi-scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).

Ecology Letters

The ghosts of propagation past: Haplotype information clarifies the relative influence of stocking history and phylogeographic processes on contemporary population structure of walleye (Sander vitreus)

Stocking of fish is an important tool for maintaining fisheries but can also significantly alter population genetic structure and erode the portfolio of within-species diversity that is important for promoting resilience and adaptability. Walleye ( Sander vitreus ) are a highly valued sportfish in the midwestern United States, a region characterized by postglacial recolonization from multiple lineages and an extensive history of stocking. We leveraged genomic data and recently developed analytical approaches to explore the population structure of walleye from two midwestern states, Minnesota and Wisconsin. We genotyped 954 walleye from 23 populations at ~20,000 loci using genotyping by sequencing and tested for patterns of population structure with single-SNP and microhaplotype data. Populations from Minnesota and Wisconsin were highly differentiated from each other, with additional substructure found in each state. Population structure did not consistently adhere to drainage boundaries, as cases of high intra-drainage and low inter-drainage differentiation were observed. Low genetic structure was observed between populations from the upper Wisconsin and upper Chippewa river watersheds, which are found as few as 50 km apart and were likely homogenized through historical stocking. Nevertheless, we were able to differentiate these populations using microhaplotype-based co-ancestry analysis, providing increased resolution over previous microsatellite studies and our other single SNP-based analyses. Although our results illustrate that walleye population structure has been influenced by past stocking practices, native ancestry still exists in most populations and walleye populations may be able to purge non-native alleles and haplotypes in the absence of stocking. Our study is one of the first to use genomic tools to investigate the influence of stocking on population structure in a nonsalmonid fish and outlines a workflow leveraging recently developed analytical methods to improve resolution of complex population structure that will be highly applicable in many species and systems.

Minnesota, Wisconsin

Estimation of the water table position in unconfined aquifers with MODFLOW 6

The numerical estimation of the position of the water table in unconfined aquifers is important for many practical applications. Its determination through observations or analytical methods is restricted to a few cases. Therefore, it is often estimated through numerical simulations, which may be affected by numerical artifacts and/or poor stability. We use MODFLOW to estimate the position of the water table for a seemingly simple example problem and demonstrate difficulties that can be faced when performing this kind of numerical simulation. We explain the causes for the numerical challenges that originate from the properties of the mathematical equations that must be solved. Based on the results of more than 600 steady-state simulations, we show how the stability of the numerical solution can be affected by the values of physical parameters that define the problem (e.g., recharge rate, anisotropy ratio, and other parameters that control the numerical algorithm such as settings of the linear and nonlinear solution methods). Finally, we comment on some best practices to apply numerical simulations to estimate the water table position.

Groundwater

Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python

Regulatory agencies in humid temperate environments rely on timely evaluations of streamflow depletion and drawdown to protect aquatic ecosystems and existing water users. Numerical models offer detailed insights, but their complexity and time demands often preclude their practical use in rapid decision-making. We present pycap-dss, an open-source Python package that implements a suite of analytical solutions for estimating streamflow depletion and drawdown. The tool supports superposition of multiple wells and time-varying pumping, enabling cumulative impact assessments in situations with multiple wells and streams. The software is modular and extensible, allowing users to interchange solutions or add new analytical methods. A YAML-based configuration supports batch processing of multiple wells, and an optional AnalysisProject class facilitates integration with regulatory workflows. Rigorous unit and regression testing ensures computational reliability, and continuous integration supports ongoing development. We demonstrate deterministic examples of drawdown where multiple solutions are readily compared and streamflow depletion with multiple wells in the Central Sands region of Wisconsin. We also show the value of Monte Carlo analyses of streamflow depletion in the same Central Sands example, leveraging computational efficiency to evaluate the uncertainty of individual and cumulative streamflow depletion calculations from over 200 high-capacity wells.

Wisconsin

Change in field turbidity and trace element concentrations during well purging

Various physical and chemical properties were monitored sequentially in the field during well purging as indicators of stabilization of the composition of the water in the well. Turbidity was monitored on site during purging of oxic water from three wells with screened intervals open to an unconfined aquifer system in the Coastal Plain of southern New Jersey to determine if stabilization of turbidity is a reliable indicator of the optimum purge time required to collect unbiased trace element samples. Concurrent split (one filtered, one unfiltered) samples collected during purging of the wells were analyzed for concentrations of trace elements so that the relationships between trace element concentrations and turbidity could be compared. Turbidity correlated with the whole water recoverable (WWR) concentration of trace element species, such as iron (Fe), aluminum (Al), and manganese (Mn) in the oxic ground water. Turbidity appeared to be independent of other field-measured characteristics of water such as conductivity, pH, temperature, and dissolved oxygen. The WWR concentration of lead and copper, considered to be hydrophobic, correlated significantly with the sum of the WWR concentration of Fe, Al, and Mn. High values of field-measured turbidity were a key indicator of an overestimate of ambient hydrophobic trace element WWR concentrations. Stabilization of turbidity was a better indicator of stable, unfiltered trace element concentrations than were the other commonly measured field characteristics. At one well, turbidity was a better indicator of stable, filtered trace element concentrations than the other commonly measured field characteristics. As analytical methods for trace elements improve resulting in smaller MRLs (method reporting levels) and better precision, turbidity of ground water at values of less than 10 NTU (nepheiometric turbidity units) will become important in interpreting the significance of both unfiltered and filtered sample results.

New Jersey

Influences of Availability on Parameter Estimates from Site Occupancy Models with Application to Submersed Aquatic Vegetation

Site occupancy models are commonly used by ecologists to estimate the probabilities of species site occupancy and of species detection. This study addresses the influence on site occupancy and detection estimates of variation in species availability among surveys within sites. Such variation in availability may result from temporary emigration, nonavailability of the species for detection, and sampling sites spatially when species presence is not uniform within sites. We demonstrate, using Monte Carlo simulations and aquatic vegetation data, that variation in availability and heterogeneity in the probability of availability may yield biases in the expected values of the site occupancy and detection estimates that have traditionally been associated with low-detection probabilities and heterogeneity in those probabilities. These findings confirm that the effects of availability may be important for ecologists and managers, and that where such effects are expected, modification of sampling designs and/or analytical methods should be considered. Failure to limit the effects of availability may preclude reliable estimation of the probability of site occupancy.

Natural Resource Modeling

Optical characterization of two cyanobacteria genera, Aphanizomenon and Microcystis, with hyperspectral microscopy.

Cyanobacterial blooms are a nuisance and a potential hazard in freshwater systems worldwide. Remote sensing has been used to detect cyanobacterial blooms, but few studies have distinguished between genera of cyanobacteria. Because some genera are more likely to be toxic than others, this is a useful distinction.In this study, hyperspectral imaging reflectance microscopy was used to examine cyanobacteria from Upper Klamath Lake, Oregon, USA, at high spatial and spectral resolution to determine if two species found commonly in the lake, Aphanizomenon flos-aquae and Microcystis aeruginosa, can be separated spectrally. Of the analytical methods applied, a spectral shape algorithm applied to the derivative was found to be most successful in classifying these species in microscope scenes. Further work is required to determine if the spectral characterization of cyanobacterial genera can be scaled up to other remote sensing applications.

Oregon

Neutron activation analysis of fluid inclusions for copper, manganese, and zinc

Microgram quantities of copper, manganese, and zinc, corresponding to concentrations greater than 100 parts per million, were found in milligram quantities of primary inclusion fluid extracted from samples of quartz and fluorite from two types of ore deposits. The results indicate that neutron activation is a useful analytical method for studying the content of heavy metal in fluid inclusions.

Science

Functional response and capture timing in an individual-based model: predation by northern squawfish (Ptychocheilus oregonensis) on juvenile salmonids in the Columbia River

The behavior of individual northern squawfish ( Ptychocheilus oregonensis ) preying on juvenile salmonids was modeled to address questions about capture rate and the timing of prey captures (random versus contagious). Prey density, predator weight, prey weight, temperature, and diel feeding pattern were first incorporated into predation equations analogous to Holling Type 2 and Type 3 functional response models. Type 2 and Type 3 equations fit field data from the Columbia River equally well, and both models predicted predation rates on five of seven independent dates. Selecting a functional response type may be complicated by variable predation rates, analytical methods, and assumptions of the model equations. Using the Type 2 functional response, random versus contagious timing of prey capture was tested using two related models. ln the simpler model, salmon captures were assumed to be controlled by a Poisson renewal process; in the second model, several salmon captures were assumed to occur during brief "feeding bouts", modeled with a compound Poisson process. Salmon captures by individual northern squawfish were clustered through time, rather than random, based on comparison of model simulations and field data. The contagious-feeding result suggests that salmonids may be encountered as patches or schools in the river.

Canadian Journal of Fisheries and Aquatic Sciences

Relationship between deer mouse population parameters and dieldrin contamination in the Rocky Mountain Arsenal National Wildlife Refuge

A small-mammal capture-recapture study was conducted in the Rocky Mountain Arsenal National Wildlife Refuge to quantify the effects of soil contamination with dieldrin on demographic parameters of deer mouse (Peromyscus maniculatus) populations. Increased dieldrin concentrations were significantly associated with larger deer mouse populations, although the size of populations on contaminated sites decreased during the study. The most parsimonious model for estimating survival rates was one in which survival was a decreasing function of dieldrin concentration. A significantly higher proportion of female deer mice in the populations residing on the more highly contaminated sites exhibited signs of reproductive activity. Development of genetic resistance in P. maniculatus to chronic chemical exposure is suggested as a possible mechanism responsible for the species' observed dominance and relatively high densities on contaminated sites. Under the additional stress of unfavorable environmental conditions, however, these populations may suffer disproportionately greater mortality. The design and analytical methods presented offer a rigorous statistical approach to assessing the effects of environmental contamination on small mammals at the population level.

Canadian Journal of Zoology

Stream sediment geochemistry in mineral exploration: A review of fine-fraction, clay-fraction, bulk leach gold, heavy mineral concentrate and indicator mineral chemistry

Stream sediment surveys support early-stage reconnaissance mineral exploration and regional assessment programmes, enhanced by recent improvements in analytical method detection limits, continuously improving mineral chemistry, and new approaches to the interpretation of geochemical data. Sediment surveys may be used to predict catchment basin lithology, mineralization type based on pathfinder geochemistry, and geological features based on indicator mineral chemistry. Sediment surveys that target a finer-fraction sediment sample led to the discovery of the La Colosa gold deposit, Colombia. The Batu Hijau porphyry Cu–Au deposit in Indonesia was discovered based on an anomalous clay-sized fraction sample 12 km downstream. In an arid region with poorly developed drainages and minor topographic relief, the Ag-base-metal Navidad District in Argentina was discovered with clay-fraction sediment geochemistry. Heavy mineral concentrate (HMC) sediment surveys that include mineral chemistry determinations have led to global diamond discoveries. HMC surveys contributed to discovery of the Ring of Fire Ni–Cu–PGE and chromite district, Ontario, Canada. Discoveries and geochemical mapping can assist advancement of the application of stream sediment geochemistry in those global areas for which lithologies and deposits are exposed. Stream sediment surveys continue to be one of the most cost-effective geochemical methods for covering large areas for mineral exploration.

Geochemistry: Exploration, Environment, Analysis

Appendix 2: Tabulated analytical data

Details of analytical methods and errors are given in Appendix 1. bd means below detection and na not analysed. Samples numbers which begin with the letter S are from Druitt (1983) and those that begin with LS are from Edwards (1994). Sample numbers which begin with the number 8 are either from Mellors (1988) or Pyle (1990 b ). Subunits of each major tuff of the Thera pyroclastics are denoted by upper case letters (A to D). These are listed in Table 3.4. In the case of the minor sequences (Appendix 2.3), the sequence abbreviations (M6 to M8) are shown in Fig. 3.17 and the individual unit abbreviations (CD1 to CD10) are from Edwards (1994).

Geological Society, London, Memoirs

Modeling regional occupancy of fishes using acoustic telemetry: A model comparison framework applied to lake trout

Acoustic telemetry is a common tool used in fisheries management to estimate fish space use (i.e., occupancy) from a local habitat scale to entire systems. Numerous analytical models have been developed to estimate different aspects of fish movement from telemetry datasets, yet evaluations of model performance and comparisons among models are limited. Here, we develop a framework to evaluate model estimates of regional occupancy in large and fragmented systems using an acoustic receiver array in Lake Champlain. We simulated the tracks of 100 acoustically tagged fish using a random walk function and created detection events based on receiver positions and distance-based detection probability. Regional occupancy for the simulated data was estimated by six movement models that ranged in analytical complexity, and results were compared to the true distributions for each simulated track to evaluate model error. The six movement models included: (1) a basic residency index using detections alone; (2) a residency index using last-observation-carried-forward; (3) a centers of activity model; (4) linear and non-linear interpolations (i.e., least-cost paths); and (5 and 6) two dynamic Brownian bridge movement models generated using separate packages in R. We developed a model selection process to compare model performance and select the optimal analysis based on simulation error. This process showed significant differences in model performance among the six movement models based on model error. Overall, the model generating least-cost paths using linear and non-linear interpolations consistently provided the most accurate regional occupancy estimates. Based on these simulation results, we applied this model to a case study that evaluated patterns in the regional distribution of stocked lake trout ( Salvelinus namaycush ) in Lake Champlain, which demonstrated distinct regional occupancy of two stocked lake trout groups. These results demonstrate potential for large variability in interpretation of acoustic telemetry data for describing regional fish distribution dependent on the analytical method used.

New York, Vermont

Demographic outcomes of diverse migration strategies assessed in a metapopulation of tundra swans

Background Migration is a prominent aspect of the life history of many avian species, but the demographic consequences of variable migration strategies have only infrequently been investigated, and rarely when using modern technological and analytical methods for assessing survival, movement patterns, and long-term productivity in the context of life history theory. We monitored the fates of 50 satellite-implanted tundra swans (Cygnus columbianus) over 4 years from five disparate breeding areas in Alaska, and used known-fate analyses to estimate monthly survival probability relative to migration distance, breeding area, migratory flyway, breeding status, and age. We specifically tested whether migratory birds face a trade-off, whereby long-distance migrants realize higher survival rates at the cost of lower productivity because of reduced time on breeding areas relative to birds that migrate shorter distances and spend more time on breeding areas. Results Annual migration distances varied significantly among breeding areas (1020 to 12720 km), and were strongly negatively correlated with time spent on breeding areas (r = −0.986). Estimates of annual survival probability varied by wintering area (Pacific coast, Alaska Peninsula, and Eastern seaboard) and ranged from 0.79 (95%CI: 0.70–0.88) to 1.0, depending on criteria used to discern mortalities from radio failures. We did not find evidence for a linear relationship between migration distance and survival as swans from the breeding areas with the shortest and longest migration distances had the highest survival probabilities. Survival was lower in the first year post-marking than in subsequent years, but there was not support for seasonal differences in survival. Productivity varied among breeding populations and was generally inversely correlated to survival, but not migration distance or time spent on breeding areas. Conclusions Tundra swans conformed to a major tenet of life history theory, as populations with the highest survival generally had the lowest productivity. The lack of a uniform relationship between time spent on breeding areas and productivity, or time spent on wintering areas and survival, indicates that factors other than temporal investment dictate demographic outcomes in this species. The tremendous diversity of migration strategies we identify in Alaskan tundra swans, without clear impacts on survival, underscores the ability of this species to adapt to different environments and climatic regimes. Keywords: Cygnus columbianus, Known fate, Life history, Metapopulation, Migration distance, Productivity, Satellite telemetry, Survival, Transmitter effects, Tundra swan

Movement Ecology