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Matthew J. Ashton

Publications and source records attributed to Matthew J. Ashton.

2 recordsLinked to original sources

Pit tag application in native freshwater mussels: Case studies across small, medium, and large rivers

Since their first use in the mid-1980s, external passive integrated transponder (PIT) tags have facilitated innovative investigations into multiple biological traits of animals. For native freshwater mussels, PIT tags are frequently used in capture-mark-recapture applications because they allow repeated, noninvasive sampling, are easy to apply, have high retention rates, and have negligible short-term effects on growth and survival. Because of these traits, resource managers and scientists are using PIT-tagged animals to estimate survival and movement of mussels associated with restoration efforts. However, consistency is limited in how PIT tags are affixed, monitored, and reported. Thus, our objectives were to (1) share our collective experiences in PIT tagging mussels across three case studies in small, medium, and large rivers and (2) propose guidelines for tagging and reporting data from PIT tag studies with native freshwater mussels to facilitate comparisons across future studies. The number of studies that have marked mussels with PIT tags has increased over the past 10 years. The ability to detect mussels using PIT tags has substantially advanced research in three areas of mussel ecology: (1) estimating vital rates (e.g., growth and survival), (2) tracking movements and behaviors of captively propagated, wild, and translocated individuals, and (3) improving our understanding of life history traits, such as reproductive timing. Each case study offers insights on tagging methods, tag loss, tag retention, and monitoring frequency across multiple species that range in conservation status from common to rare. We conclude with best-practice guidelines for placing PIT tags on freshwater mussels and a list of variables that could be reported in future studies to facilitate cross-system comparisons.

Freshwater Mollusk Biology and Conservation

Time marches on, but do the causal pathways driving instream habitat and biology remain consistent?

Stream ecosystems are complex networks of interacting terrestrial and aquatic drivers. To untangle these ecological networks, efforts evaluating the direct and indirect effects of landscape, climate, and instream predictors on biological condition through time are needed. We used structural equation modeling and leveraged a stream survey program to identify and compare important predictors driving condition of benthic macroinvertebrate and fish assemblages. We used data resampled 14 years apart at 252 locations across Maryland, USA. Sample locations covered a wide range of conditions that varied spatiotemporally. Overall, the relationship directions were consistent between sample periods, but their relative strength varied temporally. For benthic macroinvertebrates, we found that the total effect of natural landscape ( e.g ., elevation, longitude, latitude, geology) and land use ( i.e ., forest, development, agriculture) predictors was 1.4 and 1.5 times greater in the late 2010s compared to the 2000s. Moreover, the total effect of water quality ( e.g ., total nitrogen and conductivity) and habitat ( e.g ., embeddedness, riffle quality) was 1.2 and 4.8 times lower in the 2010s, respectively. For fish assemblage condition, the total effect of land use-land cover predictors was 2.3 times greater in the 2010s compared to the 2000s, while the total effect of local habitat was 1.4 times lower in the 2010s, respectively. As expected, we found biological assemblages in catchments with more agriculture and urban development were generally comprised of tolerant, generalist species, while assemblages in catchments with greater forest cover had more-specialized, less-tolerant species ( e.g., Ephemeroptera, Plecoptera, and Trichoptera taxa, clingers, benthic and lithophilic spawning fishes). Changes in the relative importance of landscape and land-use predictors suggest other correlated, yet unmeasured, proximal factors became more important over time. By untangling these ecological networks, stakeholders can gain a better understanding of the spatiotemporal relationships driving biological condition to implement management practices aimed at improving stream condition.

Maryland