Geology topics

Taylor Woods

Publications and source records attributed to Taylor Woods.

8 recordsLinked to original sources

USGS2025

Diverging fish biodiversity trends in cold and warm rivers and streams

Worldwide, freshwater systems contain more than 18,000 fish species 1,2,3 , which are critical to the functioning of these ecosystems 4 and are vital cultural and economic resources to humans 5,6,7 ; despite this value, fish biodiversity is at risk globally 8,9 . In the USA, leading threats to fish communities in rivers and streams include climate change and invasive fish introductions and game fish stocking by humans 10,11,12,13,14 . Here we harmonized US federal biomonitoring datasets with 389 species spanning 27 years (1993–2019) and 2,992 sites to analyse trends in fish biodiversity. In cold streams (past summer stream temperatures below 15.4 °C), fish abundance and richness declined by 53.4% and 32% over 27 years, respectively, and uniqueness increased. Periodic (large-bodied, late-maturing) fishes increased, and opportunists (small-bodied, short generation time, ‘r-selected’) decreased, possibly due to proliferation of native or introduced game fishes. In warm streams (stream temperatures greater than 23.8 °C), fish abundance and richness increased by 70.5% and 15.6% over 27 years, respectively, and communities homogenized. Small opportunistic fishes replaced large periodic fishes. Intermediate streams (stream temperatures 15.4–23.8 °C), representing the average stream, had minimal changes in fish biodiversity through time. Interactions between warming and introduced fish were associated with increased rates of degradation to local fish biodiversity. Given the magnitude of these changes in a relatively short time span, there is an urgent need to curb degradation of fish biodiversity caused by fish introductions and warming water temperatures.

continental United States↗

USGS2025

Stressor-driven changes in freshwater biological indicators inform spatial management strategies using expert knowledge, observational data, and hierarchical models

Stream ecosystems face continuous pressures from multiple anthropogenic stressors that reshape biological communities and impact ecosystem health and services. Managers can encounter challenges in stewarding ecosystems threatened by multiple stressors, in part because most multiple stressor studies are experimental and, while valuable, offer limited management relevance in targeting these stressors on the landscape. Recent advances in causal inference coupled with large biomonitoring data sets could further understanding of observational stressor-response relationships, aiding management. In this study, we use bioassessment data in the Chesapeake Bay watershed in the mid-Atlantic region of the United States to identify how water quality and physical habitat stressors influence key benthic macroinvertebrate response metrics, considering hierarchical relationships using Bayesian networks. Results suggest water temperature and specific conductivity were prevalent stressors in a mountainous region (northern Appalachians), whereas in an agriculturally dominated region (southern Appalachians) physical habitat alterations were the predominant stressor. In mixed-land use regions (Piedmont & Coastal Plains), specific conductivity was a key stressor, but habitat heterogeneity was important for macroinvertebrate metrics. To illustrate how these stressor-response relationships can be used to guide management decisions, we applied the resist-accept-direct (RAD) framework to develop a portfolio of management options based on predicted changes in macroinvertebrate metrics in response to physical habitat and water quality stressors. For example, accepting changes in areas with co-occurring stressors may be the most feasible option, whereas directing changes through stream restoration or water quality improvements may be effective in areas with single stressor groups. By leveraging observational bioassessment data and causal inference to identify key stressor-response relationships, this research supports decision making by building a simple, strategic management portfolio.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2025

Integrating theory and empirical patterns: Fish body size distributions, life history traits, and environmental flows in streams

Individual size distributions (ISDs) are prominent in ecological research and may support resource managers with ecosystem-scale objectives. We use a database of individual size measurements for US stream fishes to test for direct and indirect effects of traits, flow regimes, and land use on the interspecific ISD exponent. Path analysis indicates that traits have strong, direct effects on ISD. Flow and land use effects on the exponent are largely indirectly mediated by their influences on species traits. ISD exponents increase (abundances of larger-bodied individuals increase, relative to smaller-bodied) when environments favor higher trophic levels, warmer thermal tolerances, and periodic life histories. Alternatively, ISD exponents decrease in systems that favor opportunistic life histories. Our flexible modeling framework that includes direct and indirect effects of traits, flow regimes, and land use on ISD could be expanded to incorporate additional variables that interact with flow (e.g., temperature and physical habitat) to assess of effects of multiple stressors on aquatic ecosystem functioning.

Science Advances↗

USGS2024

Causal inference approaches reveal both positive and negative unintended effects of agricultural and urban management practices on instream biological condition

Agricultural and urban management practices (MPs) are primarily designed and implemented to reduce nutrient and sediment concentrations in streams. However, there is growing interest in determining if MPs produce any unintended positive effects, or co-benefits, to instream biological and habitat conditions. Identifying co-benefits is challenging though because of confounding variables (i.e., those that affect both where MPs are applied and stream biota), which can be accounted for in novel causal inference approaches. Here, we used two causal inference approaches, propensity score matching (PSM) and Bayesian network learning (BNL), to identify potential MP co-benefits in the Chesapeake Bay watershed portion of Maryland, USA. Specifically, we examined how MPs may modify instream conditions that impact fish and macroinvertebrate indices of biotic integrity (IBI) and functional and taxonomic endpoints. We found evidence of positive unintended effects of MPs for both benthic macroinvertebrates and fish indicated by higher IBI scores and specific endpoints like the number of scraper macroinvertebrate taxa and lithophilic spawning fish taxa in a subset of regions. However, our results also suggest MPs have negative unintended effects, especially on sensitive benthic macroinvertebrate taxa and key instream habitat and water quality metrics like specific conductivity. Overall, our results suggest MPs offer co-benefits in some regions and catchments with largely degraded conditions but can have negative unintended effects in some regions, especially in catchments with good biological conditions. We suggest the number and types of MPs drove these mixed results and highlight carefully designed MP implementation that incorporates instream biological data at the catchment scale could facilitate co-benefits to instream biological conditions. Our study underscores the need for more research on identifying effects of individual MP types on instream biological and habitat conditions.

Maryland↗

USGS2024

Assessing the added value of antecedent streamflow alteration information in modeling stream biological condition

In stream systems, disentangling relationships between biology and flow and subsequent prediction of these relationships to unsampled streams is a common objective of large-scale ecological modeling. Often, streamflow metrics are derived from aggregating continuous streamflow records available at a subset of stream gages into long-term flow regime descriptors. Despite demonstrated value, shortcomings of these long-term approaches include spatial restriction to locations with long-term continuous flow records (commonly, biased toward larger systems) and omission of potentially ecologically important short-term (i.e., ≤1 year) antecedent streamflow information. We used long-term flow regime and short-term antecedent streamflow alteration information to evaluate relative performance in modeling stream fish biological condition. We compared results to understand whether short-term antecedent streamflow information improved models of fish biological condition. Results indicated that models incorporating short-term antecedent data performed better than those relying solely on long-term flow regime data (kappa statistic = 0.29 and 0.23, respectively) and improved prediction accuracy among stream sizes and in six of nine ecoregions. Additionally, models relying solely on short-term streamflow information performed similarly to those with only long-term streamflow information (kappa = 0.23). Incorporating short-term antecedent streamflow metrics may provide added ecological information not fully captured by long-term flow regime summaries in macroscale modeling efforts or perform similarly to long-term streamflow data when long-term data are not available.

Science of the Total Environment↗

USGS2024

Evaluating the effectiveness of joint species distribution modeling for fresh water fish communities within large watersheds

Accurately predicting species’ distributions is critical for the management and conservation of fish and wildlife populations. Joint Species Distribution Models (JSDMs) account for dependencies between species often ignored by traditional species distribution models. We evaluated how a JSDM approach could improve predictive strength for stream fish communities within large watersheds (the Chesapeake Bay Watershed, USA), using a cross-validation study of JSDMs fit to data from over 50 species. Our results suggest that conditional predictions from JSDMs have the potential to make large improvements in predictive accuracy for many species, particularly for more generalist species where single species models may not perform well. For some species there was no added explanatory effect from conditional information, most of which already exhibited strong marginal predictive ability. For several rare species there were significant improvements in occurrence predictions, while the results for two invasive species considered did not show the same improvements. Overall, the optimal number of species to condition upon, as well as the effects of conditioning upon an increasing number of species, varied widely among species.

Chesapeake Bay watershed↗

USGS2023

Observed and projected functional reorganization of riverine fish assemblages from global change

Climate and land-use/land-cover change (‘global change’) are restructuring biodiversity, globally. Broadly, environmental conditions are expected to become warmer, potentially drier (particularly in arid regions), and more anthropogenically developed in the future, with spatiotemporally complex effects on ecological communities. We used functional traits to inform Chesapeake Bay Watershed fish responses to future climate and land-use scenarios (2030, 2060, and 2090). We modelled the future habitat suitability of focal species representative of key trait axes (substrate, flow, temperature, reproduction, and trophic) and used functional and phylogenetic metrics to assess variable assemblage responses across physiographic regions and habitat sizes (headwaters through large rivers). Our focal species analysis projected future habitat suitability gains for carnivorous species with preferences for warm water, pool habitats, and fine or vegetated substrates. At the assemblage level, models projected decreasing habitat suitability for cold-water, rheophilic, and lithophilic individuals but increasing suitability for carnivores in the future across all regions. Projected responses of functional and phylogenetic diversity and redundancy differed among regions. Lowland regions were projected to become less functionally and phylogenetically diverse and more redundant while upland regions (and smaller habitat sizes) were projected to become more diverse and less redundant. Next, we assessed how this model projected assemblage changes 2005-2030 related to observed time-series trends (1999–2016). Halfway through the initial projecting period (2005–2030), we found observed trends broadly followed modelled patterns of increasing proportions of carnivorous and lithophilic individuals in lowland regions but showed opposing patterns for functional and phylogenetic metrics. Leveraging observed and predicted analyses simultaneously helps elucidate the instances and causes of discrepancies between model predictions and ongoing observed changes. Collectively, results highlight the complexity of global change impacts across broad landscapes that likely relate to differences in assemblages’ intrinsic sensitivities and external exposure to stressors.

Global Change Biology↗

USGS2020

Influence of grain size and shape on volcanic ash electrical conductivity

Few studies have examined the electrical properties of volcanic ash or considered the effects of physical characteristics, such as grain size and shape on its electrification. This study measures the resistivity of eight volcanic ash samples, three milled-samples and five natural ashfall samples from Alaska, U.S.A., using a current amplifier and examines the influence of particle size and particle shape on calculated grain conductivity. Grain conductivities are calculated by applying spherical, oblate, and prolate ellipsoidal shape parameters within a general effective media equation. Volcanic ash is an electrically insulating material with average resistivity values ranging from 1.732E 7 to 1.606E 12 Ωm. Results show that grain size has a limited impact on resistivity. Calculated grain conductivities remained within the same order of magnitude between the three different shape calculations ranging between 1.367E − 7 and 2.196E − 12 S/m using the spherical shape parameter. Electrical measurements of heterogeneous powders are complex and challenging. This study aims to expand the community's dataset and understanding of the electrical properties of volcanic ash and the impact of different physical characteristics. This has implication for understanding ash hazards to electrical infrastructure and volcanic lightning.

Journal of Volcanology and Geothermal Research↗