Geology topics

Krishna Pacifici

Publications and source records attributed to Krishna Pacifici.

At least 19 recordsLinked to original sources

USGS2025

Spatiotemporal dynamics and habitat use of red snapper (Lutjanus campechanus) on the southeastern United States Atlantic continental shelf

Red snapper ( Lutjanus campechanus ) is an iconic marine fish species along the southeast United States coast. Despite its ecological and economic importance, surprisingly little is known about red snapper biology and habitat use on the southeast United States Atlantic continental shelf (SEUS). We used data from a long-term baited trap and video survey (2011–2022), as well as from remotely operated vehicle (ROV) sampling (2021–2023), to quantify temporal changes in relative abundance, patterns of spatial distribution, and habitat use of red snapper in the SEUS. Using generalized additive models, we showed that red snapper increased in relative abundance from 2011 to 2022 by 960% in traps and 1,141% in video samples. Red snapper relative abundance was highest in mid-shelf waters off the east coast of Florida, Georgia, and, to a lesser extent, off the Outer Banks of North Carolina; red snapper were less common off southern North Carolina and South Carolina. Highest relative abundance of red snapper occurred in locations with a moderate amount of natural structured habitat and high seafloor complexity and were never observed at randomly selected ROV stations (n = 197) lacking structured habitat. These results increase our understanding of the spatial and temporal distribution of red snapper, improve our knowledge of red snapper habitat use, and can be used when scaling local density estimates to the entire SEUS.

Florida, Georgia, North Carolina, South Carolina↗

USGS2024

Applying mark-resight, count, and telemetry data to estimate effective sampling area and fish density with stationary underwater cameras

Accurate estimates of abundance and density for geographically open populations must account for the effective sampling area (ESA) of sampling gears. We describe a Marked N-Mixture model to estimate ESA and density (number of individuals/unit area) from repeated counts of unmarked and marked individuals, integrating mark-resight, camera counts, and telemetry data of red snapper ( Lutjanus campechanus ) at a 1.6 km 2 reef off North Carolina, USA. Cameras recorded observations of unmarked and marked individuals, whereas telemetry data indicated the number of tagged fish present on the reef. We estimated density (95 individuals/km 2 , 95%CI: 58–149), ESA (which was lower when current direction was towards the camera), detection probability (0.06, 95%CI: 0.03–0.09), and covariate relationships. Simulation studies under different scenarios of data quality and space use identified positive bias in density estimates from N-mixture models due to fish movement. In contrast, the Marked N-Mixture model returned unbiased estimates of density, ESA, and detection parameters, and appears to be a more robust method for modeling density given the data available for this analysis. This approach can be applied to other populations where count and telemetry data overlap in space and time.

North Carolina↗

USGS2023

Minimal shift of eastern wild turkey nesting phenology associated with projected climate change

Climate change may induce mismatches between wildlife reproductive phenology and temporal occurrence of resources necessary for reproductive success. Verifying and elucidating the causal mechanisms behind potential mismatches requires large-scale, longer-duration data. We used eastern wild turkey ( Meleagris gallopavo silvestris ) nesting data collected across the southeastern U.S. over eight years to investigate potential climatic drivers of variation in nest initiation dates. We investigated climactic relationships with two datasets, one inclusive of successful and unsuccessful nests (full dataset) and another of just successful nests (successfully hatched dataset), to determine whether successfully hatched nests responded differently to weather changes than all nests did. In the full dataset, each 10 cm increase in January precipitation was associated with nesting occurring 0.46-0.66 days earlier, and each 10 cm increase in precipitation during the 30 days preceding nesting was associated with nesting occurring 0.17-0.21 days later. In the successfully hatched dataset, a 10 cm increase in March precipitation was associated with nesting occurring 0.67-0.74 days earlier, and an increase of one unit of variation in February maximum temperature was associated with nesting occurring 0.02 days later. We combined the results of these modeled relationships with multiple climate scenarios to understand potential implications of future climate change on wild turkey nesting phenology; results indicated that mean nest initiation date is projected to change by <0.1 day by 2040-2060. Wild turkey nesting phenology did not track changes in spring green-up timing, which could result in phenological mismatch between the timing of nesting and the availability of resources critical for successful reproduction.

Climate Change Ecology↗

USGS2022

Modeling and estimating co-occurrence between the invasive Shiny Cowbird and its Puerto Rican hosts

Invasive species threaten island biodiversity globally. For example, the Shiny Cowbird ( Molothrus bonariensis ) parasitizes many of Puerto Rico’s endemic species, particularly in the open forests in the island’s southwest. Less is known, however, about cowbird parasitism in the agro-ecological highlands, which contain a patchwork of forests, shaded-coffee plantations, and coffee farms without shade. In this paper, we estimated co-occurrence rates, a potential indicator of parasitism rates, between the cowbird and four host species across these three land uses, hypothesizing that cowbirds would most likely co-occur with their hosts in shaded-coffee farms. We also hypothesized that the presence of host species would increase the probability of cowbird occurrence. To investigate these hypotheses, we developed three Bayesian hierarchical occupancy models: one where the hosts and parasite occurred independently, one that used the latent host species richness as a predictor of cowbird occurrence, and one that used each latent host occurrence state as predictors. These methods addressed observation errors and appropriately propagated error to our predictions of co-occurrence rates. We selected the best performing model using WAIC, then used it to predict co-occurrence rates. While there was some evidence that host species richness increased the probability of cowbirds, the parsimonious model assumed no interaction. With this model, we found that cowbirds were more likely to overlap with certain hosts in shaded-coffee plantations. This may suggest increased parasitism at these plantations, potentially presenting challenges for managers who advocate for shade restoration to gain ecological services such as biodiversity conservation.

Biological Invasions↗

USGS2021

Climate change implications for the conservation of amphibians in tropical environments.

The U.S. Fish and Wildlife Service and the Puerto Rico Department of Natural and Environmental Resources want to develop a plan of actions to protect 12 species of coqui frogs (Eleutherodactylus spp.) that are currently considered at risk of being considered threatened or endangered, requiring additional protections under the Endangered Species Act. Actions center on two possible adaptation strategies: a) translocations to suitable, unoccupied habitat, and b) identifying climate-resilient habitats to ensure the persistence of species. Knowledge required to implement these strategies includes understanding how microhabitat and microclimatic factors – the local environmental conditions around individual frogs influence their occupancy (distribution), abundance, and reproduction; these were estimated by focusing on four representative species (E. wightmanae, E. brittoni, E. antillensis, and E. coqui). The abundance of all species but E. antillensis was positively and strongly influenced by moisture levels. As expected, E. antillensis exhibited an opposite relationship. Similarly, the reproductive activity of E. coqui was influenced by higher relative humidity and the presence of a chorus of other individuals. We found that our four focal species were not affected (e.g., abundance, reproduction) by the passing of hurricane Maria in September 2017, possibly because fallen debris creates conditions of increased food and shelter. Our findings help to assess habitat suitability, potential climate refuges, and inform timing for managed translocations.

Final Report↗

USGS2021

Linking demographic rates to local environmental conditions: Empirical data to support climate adaptation strategies for Eleutherodactylus frogs

Conducting managed species translocations and establishing climate change refugia are adaptation strategies to cope with projected consequences of global warming, but successful implementation requires on-the-ground validation of demographic responses to transient climate conditions. Here we estimated the effect of nine abiotic and biotic factors on local occupancy and an index of abundance (few or chorus) for four amphibian species ( Eleutherodactylus wightmanae , E. brittoni , E. antillensis, and E. coqui ) in Puerto Rico, USA. We also assessed how the same factors influenced reproductive activity of E. coqui and how species responded to hurricane María (20 September 2017). As predicted, occupancy and abundance of E. wightmanae , E. brittoni and E. coqui were positively and strongly influenced by abiotic covariates (e.g., relative humidity) that characterize high elevation, mesic habitats. E. antillensis exhibited the opposite pattern, with highest probabilities (≥0.6) recorded at ≤300 m and with average relative humidity<75%. Biotic covariates (e.g., canopy cover) had a weak influence on both parameters, regardless of species. High probabilities (≥0.9) of detecting an E. coqui chorus and active nests occurred at sites experiencing average relative humidity of>80% and temperature of ≤26 °C. Moderate to high probabilities of detecting a chorus (0.4–0.7) were recorded at sites with average temperatures>26 °C, but no reproductive activity was detected, implying that monitoring abundance alone could misrepresent the capacity of a local population to sustain itself. The possibility underscores the importance of understanding the interplay between local demographic and environmental parameters in the advent of global warming to help guide monitoring and management decisions, especially for high elevation specialists. Hurricanes can inflict marked reductions in population numbers, but impacts vary by location and species. We found that the abundance (chorus) of E. antillensis and E. brittoni increased after the hurricane, but the abundance of the other two species did not differ between years. Lack of impacts was probably mediated by low structural damage to forest tracts (e.g., 9% canopy loss). Our findings help assess habitat suitability in terms of parameters that foster local population growth, which provides a basis for testing spatio-temporal predictions about demographic rates in potential climate refugia and for designing criteria to help guide managed translocations.

Puerto Rico↗

USGS2021

Survey design optimization for monitoring wildlife communities in areas managed for federally endangered species

In wildlife communities composed of federally endangered species, there are often several species of conservation concern that have not yet warranted federally mandated protection. These species often need continued monitoring to inform the direction of future management. While recovering endangered species is an important conservation goal, practitioners are challenged by balancing federally mandated protocols with actions that promote non-listed priority species. Practitioners need an understanding of how focused, single-species management actions may affect non-listed priority species, but developing a monitoring protocol that can detect such effects with limited resources is a challenge. Here we use constrained optimization as a path to identifying a sampling scheme that overcomes these logistical challenges and then illustrate its potential in the Sandhills region of North Carolina, USA. Using empirical results from multi-year avian community monitoring, we parameterized simulations to understand how varying the number of sampling locations and site visits affected the optimal monitoring protocol across three different avian community composition scenarios: a community with (1) 10 percent, (2) 25 percent, or (3) 50 percent non-listed priority species. We found the greatest rate of change in precision of community-level metrics such as species richness by increasing sampling replicates when surveying up to 50 sites. Importantly, this trend was apparent across all three community scenarios, indicating relatively predictable changes in uncertainty regardless of community composition. In contrast, increasing the sampling frequency did not consistently reduce uncertainty in species-level parameters such as occupancy probability. Concerningly, we saw the greatest variation when communities were comprised of 50 percent non-listed species suggesting increasingly complex monitoring protocols may be required if the number of non-listed priority species continues to increase. Practitioners could consider reducing detection error of priority species through increasing sampling frequency, as this can strongly affect optimization study designs.

North Carolina↗

USGS2020

Estimating the drivers of species distributions with opportunistic data using mediation analysis

Ecological occupancy modeling has historically relied on high-quality, low-quantity designed-survey data for estimation and prediction. In recent years, there has been a large increase in the amount of high-quantity, unknown-quality opportunistic data. This has motivated research on how best to combine these two data sources in order to optimize inference. Existing methods can be infeasible for large datasets or require opportunistic data to be located where designed-survey data exist. These methods map species occupancies, motivating a need to properly evaluate covariate effects (e.g., land cover proportion) on their distributions. We describe a spatial estimation method for supplementarily including additional opportunistic data using mediation analysis concepts. The opportunistic data mediate the effect of the covariate on the designed-survey data response, decomposing it into a direct and indirect effect. A component of the indirect effect can then be quickly estimated via regressing the mediator on the covariate, while the other components are estimated through a spatial occupancy model. The regression step allows for use of large quantities of opportunistic data that can be collected in locations with no designed-survey data available. Simulation results suggest that the mediated method produces an improvement in relative MSE when the data are of reasonable quality. However, when the simulated opportunistic data are poorly correlated with the true spatial process, the standard, unmediated method is still preferable. A spatiotemporal extension of the method is also developed for analyzing the effect of deciduous forest land cover on red-eyed vireo distribution in the southeastern United States and find that including the opportunistic data do not lead to a substantial improvement. Opportunistic data quality remains an important consideration when employing this method, as with other data integration methods.

eastern United States↗

USGS2020

Using biodiversity metrics to guide conservation planning in altered tropical landscapes

Biodiversity metrics are frequently used to guide conservation planning because they can summarize biogeographical attributes of plant and animal communities quickly and at multiple scales. Attributes include habitat features of high conservation value, representativeness, and redundancy of biological communities. We conducted a rapid ecological assessment of resident avian species in the west-central mountainous region of Puerto Rico in 2015, a landscape dominated by coffee cultivation. We focused on this landscape because shade-grown and restored shade-grown coffee plantations offer an opportunity to complement protected habitat (e.g., reserves) to enhance species persistence. We used species richness, which tallies the number of unique species, and a quadratic entropy index of diversity, which incorporates interspecific taxonomic differentiation to evaluate species representativeness and redundancy across sun- and shade-grown coffee plantations and secondary forest. We surveyed 120 sites, calculating both metrics using species-specific occupancy probabilities estimated from community-level occupancy models. Species representativeness and redundancy were high as neither metric was able to discriminate among habitat types, possibly because plant communities were redundant, and the avian community was dominated by species adept at exploiting altered habitats. Similarly, we could not discriminate among avian communities modeling each biodiversity metric as a function of site-specific habitat covariates. Our findings and available knowledge on avian community demographics suggest that conservation strategies could couple protected habitat (e.g., reserves) and restored habitat (e.g., coffee plantations) to enhance species diversity and persistence across human-modified landscapes.

Caribbean Naturalist↗

USGS2019

Evaluation of artificial cover units as a sampling technique and habitat enhancement for madtoms in rivers

Instream habitat degradation and loss are major threats to freshwater fishes and critical conservation issues among nongame species, due to a lack of research and knowledge concerning their habitat requirements. Instream physical cover is an important component of fish habitat, especially for benthic species that require cover for reproduction and shelter from predators. One such species is the Carolina Madtom Noturus furiosus, a small, imperiled, nongame catfish endemic to the Neuse and Tar river basins of North Carolina. To enhance understanding of instream cover dynamics, we constructed artificial cover units from terra cotta materials and deployed them in rivers to (1) evaluate if they could be an effective passive sampling technique to estimate detection and occupancy of the Carolina Madtom, and (2) determine their potential to enhance habitat in systems where instream cover has been lost. Artificial cover units were deployed at 8 sites in the Neuse and Tar river basins, and collected 30 Carolina Madtoms at 2 sites in the Tar River basin. Occupancy modeling estimated Carolina Madtom detection probability using artificial cover units at 0.92. Compared to other standardized sampling methods, artificial cover units were an efficient, passive sampling technique for detecting Carolina Madtoms. Observations also revealed that artificial cover units were occupied by Carolina Madtoms for reproduction. These findings provide natural resource managers an additional means to assess the status of this imperiled species using an inexpensive, passive sampling device that can provide spawning habitat, protection from predators, and help mitigate effects of instream habitat degradation.

North Carolina↗

USGS2018

Optimal treatment allocations in space and time for online control of anemerging infectious disease

A key component in controlling the spread of an epidemic is deciding where, when and to whom to apply an intervention. We develop a framework for using data to inform these decisions in realtime. We formalize a treatment allocation strategy as a sequence of functions, one per treatment period, that map up‐to‐date information on the spread of an infectious disease to a subset of locations where treatment should be allocated. An optimal allocation strategy optimizes some cumulative outcome, e.g. the number of uninfected locations, the geographic footprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategy for an emerging infectious disease is challenging because spatial proximity induces interference between locations, the number of possible allocations is exponential in the number of locations, and because disease dynamics and intervention effectiveness are unknown at outbreak. We derive a Bayesian on‐line estimator of the optimal allocation strategy that combines simulation–optimization with Thompson sampling. The estimator proposed performs favourably in simulation experiments. This work is motivated by and illustrated using data on the spread of white nose syndrome, which is a highly fatal infectious disease devastating bat populations in North America.

Journal of the Royal Statistical Society. Series C↗

USGS2018

Avian response to shade‐layer restoration in coffee plantations in Puerto Rico

Documenting the evolving processes associated with habitat restoration and how long it takes to detect avian demographic responses is crucial to evaluate the success of restoration initiatives and to identify ways to improve their effectiveness. The importance of this endeavor prompted the U.S. Fish and Wildlife Service and the USDA Natural Resources Conservation Service to evaluate their sun‐to‐shade coffee restoration program in Puerto Rico initiated in 2003. We quantified the responses of 12 resident avian species using estimates of local occupancy and extinction probabilities based on surveys conducted in 2015–2017 at 65 restored farms grouped according to time‐since‐initial‐restoration (TSIR): new (2011–2014), intermediate (2007–2010), and old (2003–2006). We also surveyed 40 forest sites, which served as reference sites. Vegetation complexity increased with TSIR, ranging between 35 and 40% forest cover in farms 6–9 years TSIR. Forest specialists (e.g. Loxigilla portoricencis ) exhibited highest average occupancy in farms initially classified as intermediate (6–9 years) and old (>10 years), paralleling occupancy in secondary forests. Occupancy of open‐habitat specialists (e.g. Tiaris olivaceus ) was more variable, but higher in recently restored farms. Restoring the shade layer has the potential to heighten ecological services derived from forest specialists (e.g. frugivores) without losing the services of many open‐habitat specialists (e.g. insectivores). Annual local extinction probability for forest specialists decreased with increasing habitat complexity, strengthening the potential value of shade restoration as a tool to enhance habitat for avifauna that evolved in forested landscapes.

Restoration Ecology↗

USGS2017

Integrating multiple data sources in species distribution modeling: A framework for data fusion

The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeoff between data quality and quantity. Recently several authors have developed approaches for jointly modeling two sources of data (one of high quality and one of lesser quality). We extend their work by allowing for explicit spatial autocorrelation in occurrence and detection error using a Multivariate Conditional Autoregressive (MVCAR) model and develop three models that share information in a less direct manner resulting in more robust performance when the auxiliary data is of lesser quality. We describe these three new approaches (“Shared,” “Correlation,” “Covariates”) for combining data sources and show their use in a case study of the Brown-headed Nuthatch in the Southeastern U.S. and through simulations. All three of the approaches which used the second data source improved out-of-sample predictions relative to a single data source (“Single”). When information in the second data source is of high quality, the Shared model performs the best, but the Correlation and Covariates model also perform well. When the information quality in the second data source is of lesser quality, the Correlation and Covariates model performed better suggesting they are robust alternatives when little is known about auxiliary data collected opportunistically or through citizen scientists. Methods that allow for both data types to be used will maximize the useful information available for estimating species distributions.

Ecology↗

USGS2017

Occupancy and abundance of Eleutherodactylus frogs in coffee plantations in Puerto Rico

Shaded coffee plantations are of conservation value for many taxa, particularly for resident avifauna in the face of extensive landscape changes. Yet, little is known about the value of coffee plantations for amphibians because there are scant demographic data to index their value among species with different habitat preferences. We estimated the probability of occupancy of three frog species: Eleutherodactylus wightmanae, a forest species; E. brittoni, a grassland species; and E. antillensis, an open habitat species. Occupancy was estimated in sun and shaded plantations, and in secondary forest, in the west-central mountains of Puerto Rico. We also estimated the probability that a survey station was occupied by no individuals, one, or >1 individual, as a proxy of abundance. The aforementioned parameters, and local colonization and extinction probability, were modeled as a function of weather conditions (temperature, humidity) and vegetation cover at the sampling station (5 m) and contextual (100 m) scales. Encounter histories were obtained with passive acoustic recorders between February and July in 2015. Consistent with known habitat preferences, the highest occupancies were associated with secondary forests for E. wightmanae and sun plantations for E. brittoni . Occupancy probability for E. antillensis was similar across habitat types, indicating no aversion to shaded–forested habitats. Shaded plantations harbored moderate levels of occupancy for all species, indicating their potential value for multispecies conservation. Local colonization rates increased with forest cover for E. wightmanae, and with open habitats for E. brittoni and E. antillensis . Open habitats harbored a higher abundance of E. brittoni and E antillensis, but lower values for E. wightmanae . Sun and shaded plantations could provide quality habitat for Eleutherodactylus spp. if managed for features that promote local colonization and abundance.

Puerto Rico↗

USGS2017

Declining occurrence and low colonization probability in freshwater mussel assemblages: A dynamic occurrence modeling approach

Mussel monitoring data are abundant, but methods for analyzing long-term trends in these data are often uninformative or have low power to detect changes. We used a dynamic occurrence model, which accounted for imperfect species detection in surveys, to assess changes in species occurrence in a longterm data set (1986–2011) for the Tar River basin of North Carolina, USA. Occurrence of all species decreased steadily over the time period studied. Occurrence in 1986 ranged from 0.19 for Utterbackia imbecillis to 0.60 for Fusconaia masoni . Occurrence in 2010–2011 ranged from 0.10 for Lampsilis radiata to 0.40 for F. masoni . The maximum difference between occurrence in 1986 and 2011 was a decline of 0.30 for Alasmidonta undulata . Mean persistence for all species was high (0.97, 95% CI ¼ 0.95–0.99); however, mean colonization probability was very low (,0.01, 95% CI ¼ ,0.01–0.01). These results indicate that mussels persisted at sites already occupied but that they have not colonized sites where they had not occurred previously. Our findings highlight the importance of modeling approaches that incorporate imperfect detection in estimating species occurrence and revealing temporal trends to inform conservation planning.

North Carolina↗

USGS2017

Occupancy and abundance of Eleutherodactylus wightmanae and E. brittoni along elevational gradients in west-central Puerto Rico

Populations of Eleutherodactylus species in Puerto Rico have declined in recent decades due to habitat loss and long-term climatic changes. The conservation of these habitat specialists requires an understanding of factors influencing their abundance and distribution, which at present is scant. We estimated occupancy probability and the probability of encountering ≥2 individuals of E. wightmanae (Melodius Coqui or Wightman's Robber Frog) and E. brittoni (Grass Coqui), species with contrasting habitat affinities, using multi-season, multi-state occupancy models. These parameters also served as an index of abundance (non-presence, 1, and ≥2 individuals). We modeled parameters as a function of seasonal temperature and humidity, long-term average monthly precipitation, and habitat covariates measured at survey sites along 2 elevation gradients in the southern slopes of west-central Puerto Rico. We collected survey data using passive acoustic recorders during 3 seasonal periods between February and July 2015. Occupancy patterns of both species was unimodal, containing higher probabilities (e.g., ≥0.5) at elevations between 400 m and 700 m, where long-term monthly precipitation varied between 120 mm and 160 mm. Chances of encountering ≥2 individuals increased with ground cover for E. brittoni , and decreased with increasing canopy cover for E. wightmanae . Seasonal temperature and relative humidity did not influence occupancy or the probability of encountering ≥2 individuals, likely because covariates varied within known tolerance levels for Eleutherodactylus . Our findings help reduce local extinction probability through management of habitat conditions that increase the likelihood of encountering ≥2 individuals. We also detailed an analytical framework suitable to test hypotheses aimed at predicting potential impacts from land use and climatic changes, and species responses to conservation actions.

Puerto Rico↗

USGS2016

Uncertainty quantification and propagation for projections of extremes in monthly area burned under climate change: A case study in the coastal plain of Georgia, USA

Human‐caused climate change is predicted to affect the frequency of hazard‐linked extremes. Unusually large wildfires are a type of extreme event that is constrained by climate and can be a hazard to society but also an important ecological disturbance. This chapter focuses on changes in the frequency of extreme monthly area burned by wildfires for the end of the 21st century for a wildfire‐prone region in the southeast United States. Predicting changes in area burned is complicated by the large and varied uncertainties in how the climate will change and in the models used to predict those changes. The chapter characterizes and quantifies multiple sources of uncertainty and propagate the expanded prediction intervals of future area burned. It illustrates that while accounting for multiple sources of uncertainty in global change science problems is a difficult task, it will be necessary in order to properly assess the risk of increased exposure to these society‐relevant events.

Georgia↗

USGS2016

Species traits and catchment-scale habitat factors influence the occurrence of freshwater mussel populations and assemblages

Conservation of freshwater unionid mussels presents unique challenges due to their distinctive life cycle, cryptic occurrence and imperilled status. Relevant ecological information is urgently needed to guide their management and conservation. We adopted a modelling approach, which is a novel application to freshwater mussels to enhance inference on rare species, by borrowing data among species in a hierarchical framework to conduct the most comprehensive occurrence analysis for freshwater mussels to date. We incorporated imperfect detection to more accurately examine effects of biotic and abiotic factors at multiple scales on the occurrence of 14 mussel species and the entire assemblage of the Tar River Basin of North Carolina, U.S.A. The single assemblage estimate of detection probability for all species was 0.42 (95% CI, 0.36–0.47) with no species- or site-specific detection effects identified. We empirically observed 15 mussel species in the basin but estimated total species richness at 21 (95% CI, 16–24) when accounting for imperfect detection. Mean occurrence probability among species ranged from 0.04 (95% CI, 0.01–0.16) for Alasmidonta undulata, an undescribed Lampsilis sp. , and Strophitus undulatus to 0.67 (95% CI, 0.42–0.86) for Elliptio icterina . Median occurrence probability among sites was <0.30 for all species with the exception of E. icterina . Site occurrence probability generally related to mussel conservation status, with reduced occurrence for endangered and threatened species. Catchment-scale abiotic variables (stream power, agricultural land use) and species traits (brood time, host specificity, tribe) influenced the occurrence of mussel assemblages more than reach- or microhabitat-scale features. Our findings reflect the complexity of mussel ecology and indicate that habitat restoration alone may not be adequate for mussel conservation. Catchment-scale management can benefit an entire assemblage, but species-specific strategies may be necessary for successful conservation. The hierarchical multispecies modelling approach revealed findings that could not be elucidated by other means, and the approach may be applied more broadly to other river basins and regions. Accurate measures of assemblage dynamics, such as occurrence and species richness, are required to create management plans for effective conservation.

Freshwater Biology↗