Geology topics

Ryan P. Boyles

Publications and source records attributed to Ryan P. Boyles.

8 recordsLinked to original sources

USGS2024

U.S. Geological Survey climate science plan—Future research directions

Executive Summary Climate is the primary driver of environmental change and is a key consideration in defining science priorities conducted across all mission areas in the U.S. Geological Survey (USGS). Recognizing the importance of climate change to its future research agenda, the USGS’s Climate Science Steering Committee requested the development of a Climate Science Plan to identify future research directions. Subject matter experts from across the Bureau formed the USGS Climate Science Plan Writing Team, which convened in September 2022 to identify and outline the major climate science topics of future concern and develop an integrated approach to conducting climate science in support of the USGS and U.S. Department of the Interior missions. The resulting USGS Climate Science Plan identifies three major priorities under which USGS climate science proceeds: (1) characterize climate change and associated impacts, (2) assess climate change risks and develop approaches to mitigate climate change, and (3) provide climate science tools and support. The Climate Science Plan identifies 12 specific goals to achieve the outcomes of the three priorities. Conduct long-term, broad-scale, and multidisciplinary measurements and monitoring and research activities to define, quantify, and predict the impacts of climate change on natural and human systems; Provide leadership to standardize measuring, monitoring, reporting, and verifying greenhouse gas emissions, lateral carbon fluxes, and carbon sinks across lands managed by the U.S. Department of the Interior (DOI); Provide science capacity, training, tools, and infrastructure to Tribal partners; support Tribal-led science initiatives; Conduct climate change research in partnership with the broader climate science community; Develop improved data synthesis methods through collaborative and open science across mission areas and between the USGS and agency partners; Translate climate change impacts into risk assessments in support of risk management strategies; Develop new and improved risk assessments, models, and approaches for mitigating climate change, adapting to its impacts, and reducing uncertainties; design early warning systems for risk mitigation; Investigate climate change mitigation strategies and create decision science support tools to inform climate change mitigation and adaptation; Provide a framework that facilitates knowledge co-production needed to inform policy decisions; Provide access to USGS data and information through novel integration and visualization approaches; Build capacity within USGS and DOI through development of scientific training curricula; and Coordinate science and capacity building efforts broadly across the Federal Government. To achieve these goals, the USGS Climate Science Plan also outlines climate science guidelines—key elements for conducting climate-based research—as well as emerging opportunities to support successful climate science. The USGS Climate Science Plan provided in this circular will guide future research priorities and science-support investments, as well as continued development of the climate workforce for decades to come, ensuring that the USGS continues to serve as one of the Nation’s leading climate science agencies.

Circular↗

USGS2024

Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making

The purpose of this document is to provide technical guidance, practical application examples, and resource lists for those who conduct, manage, and/or interpret technical workflows within the Department of the Interior. This document is intended to support implementation of Department of the Interior policy 526 DM 1 and establish best practices for using climate change science to inform analysis, consultation, and decision making. The Earth’s climate is an interconnected system that distributes energy, heat, and water around the planet. Due to human-driven increases in long-lived greenhouse gases, the Earth’s climate is now changing. For Departmental decision-making purposes, assuming a static, unchanging baseline climate is no longer consistent with current knowledge about the climate system. There are uncertainties about future climate and how resources or assets (RoAs) will respond to new conditions. To depict the possibilities, the global climate science community develops scenarios and models to explore how future climate may respond to socioeconomic and technological development in the world. Principles for informing policy development, planning and decisions, and regulatory processes using climate change science must: 1) consider the effects of future climate change, 2) characterize the risks, and 3) characterize the uncertainties. Best practices include: Use multiple scenarios to assess risks from a range of plausible societal pathways. When constraints prevent the use of multiple scenarios or if decision makers are risk averse, ensure that the chosen scenario considers higher risk outcomes. This is particularly important for large investments or irreversible decisions and reduces the chances of overconfident decision making. Use multiple climate models within each scenario to account for the range of outcomes due to model uncertainty. Do not rely solely on a single model or an ensemble average. Use relevant climate data . Use a time-period for model projections of the future climate change consistent with the relevant timeframe of the policy, action, or decision being considered. Historical observations are useful for understanding past conditions and climate trends for the next several years, but not beyond the next decade. Consult with climate data and modeling experts to assess which data and model resources are most appropriate for any given application. Clearly describe key analysis uncertainties (including with any climate observations, models, and scenarios used), and how they were addressed in the analysis and/or decision process. This ensures transparency and learning among analysts and decision makers.

Report↗

USGS2023

Potential effects of climate change on Emydoidea blandingii (Blanding’s turtle)

Emydoidea blandingii (Holbrook, 1838; Blanding’s turtles) are a species of medium-sized, long-lived, semiaquatic, freshwater turtles with a wide distribution across the northern and eastern United States and southern Canada. They have an annual activity cycle consisting of late autumn and winter overwintering and spring emergence, spring movement and foraging, spring and summer nesting, and summer and autumn foraging and nonnesting movement. In response to changes in average and extreme temperatures, Blanding’s turtles are likely to experience increased physiological stress and reduced reproductive success. Variability in precipitation may affect the availability of freshwater habitats for overwintering, shelter, and feeding; however, projected changes in precipitation vary widely. This analysis presents anticipated climate conditions and effects on the species; the complex life history and expansive geographic range of this species require additional analysis at local scales.

Open-File Report↗

USGS2023

Potential effects of climate change on Ambystoma barbouri (streamside salamander)

Ambystoma barbouri (streamside salamanders) are stream-breeding mole salamanders that rely on seasonally intermittent, fishless streams for egg and larval development but are primarily fossorial as adults. Climate-driven changes are likely to alter streamflow duration, peak, and seasonality within the range of A. barbouri , reducing reproductive habitat and larval survival. Although future changes in precipitation volume within the geographic range of A. barbouri are uncertain, in the next 90 years, increasing temperatures will likely increase potential evapotranspiration. Decreasing ratio of precipitation to potential evapotranspiration will likely shorten flow duration for intermittent streams, potentially causing earlier stream dry downs before larval metamorphosis. Increased temperatures may also shorten developmental periods buffering A. barbouri larvae from the effects of increased stream no-flow days. Additionally, precipitation in the future will increasingly fall in heavy rainfall events. Heavy rain and subsequent flooding during early larval stages may displace A. barbouri larvae from fishless pools into downstream reaches with vertebrate predators that can reduce survival. Finally, agriculture and urban land cover may amplify the stresses of climate change on A. barbouri , altering reproductive habitat and reducing survival of larval, juvenile, and adult life stages.

Illinois, Indiana, Kentucky, Ohio, Tennessee, West↗

USGS2023

Potential effects of climate change on Appalachian stoneflies ( Remenus kirchneri , Acroneuria kosztarabi , and Tallaperla lobata )

Plecoptera (stoneflies) are an order of insects where most species rely on clean, fast-moving freshwater for an aquatic larval stage followed by a short terrestrial adult stage. Most species of Plecoptera seem to be restricted to specific stream types and thermal regimes. Climate-driven changes are likely to alter stream temperatures and flow, resulting in physiological stress, reduced reproductive success, and possibly latitudinal or elevational distribution shifts. This report focuses on climate projections and the resulting ecological effect for three species of Appalachian stoneflies: Remenus kirchneri , Acroneuria kosztarabi , and Tallaperla lobata . Although species-specific information is sparse for these three species, climate studies for other Plecoptera spp. are applicable. In the focal region, temperature is increasing and likely leading to increased stream temperatures. In response, Plecoptera spp. will likely experience physiological stress from increasing metabolic rates and energy demands concurrent with changing food quality and access. Warming temperatures and decreased larval energy stores are likely to contribute to lower adult body size and longevity, thus decreasing reproductive success. Whereas projected changes to precipitation and runoff are less certain, under drier future climate projections, decreased streamflow may further stress larval Plecoptera. Remenus kirchneri , A. kosztarabi , and T. lobata will likely retain stable permanent stream habitats for the analyzed future (2006–99). Changing climate is of particular concern for mountaintop species R. kirchneri and T. lobata because they may be unable to track shifts in suitable climate and habitat.

North Carolina, Tennessee, Virginia↗

USGS2021

Science needs of southeastern grassland species of conservation concern: A framework for species status assessments

The unglaciated southeastern United States is a biodiversity hotspot, with a disproportionate amount of this biodiversity concentrated in grasslands. Like most hotspots, the Southeast is also threatened by human activities, with the total reduction of southeastern grasslands estimated as 90 percent (upwards to 100 percent for some types) and with many threats escalating today. This report summarizes the results of a multistakeholder workshop organized by the Southeastern Grasslands Initiative and the U.S. Geological Survey, held in January 2020 to provide a scientific needs assessment to help inform the Species Status Assessment (SSA) process under the U.S. Endangered Species Act, with a focus on grassland species and communities of conservation concern in the southeastern United States. This report reviews the ecology of southeastern grasslands, including influences on their origin, maintenance, and high species richness and endemism; presents findings from the workshop; and discusses science questions, hypotheses, and possibilities for future research projects to help fill key knowledge gaps. Participants in the January 2020 workshop, representing diverse expertise in various topics in southeastern grassland ecology, were tasked with identifying major threats to grassland species in the Southeast as well as potential ways to make the SSA process more efficient and effective. An underlying assumption and starting place for workshop discussion was that an ecosystem-based approach to the SSA process is more cost-efficient than a species-by-species approach, in large part because many species with similar biological requirements can be addressed by the same actions. Nevertheless, one partner in this effort, the U.S. Fish and Wildlife Service, does require specific attention be given to taxa that have been petitioned for Federal listing, though as often as possible these taxa are considered alongside a larger group of priority taxa with an ecosystem approach. For group discussions, workshop participants followed a modified “World Café” method, a structured conversational approach for knowledge sharing. Group discussions focused on five categories of threats to grassland communities and species: (1) habitat loss, fragmentation, and disruption of functional population connectivity; (2) climate change, especially changes in temperature and precipitation, including intensity and seasonality, and impacts on soil moisture, groundwater levels, and other ecosystem parameters; (3) changes to disturbance regimes, as influenced by climate and land-use change, extinctions, and human attitudes and behaviors; (4) invasive species (not limited to nonnative species); and (5) localized or subregional impacts such as sea-level rise. In addition to group discussions, workshop participants—as well as other grassland experts who were unable to attend the workshop—completed a preworkshop survey concerning challenges and opportunities for grassland conservation. Findings reported here under each of these topics represent ideas, problems, hypotheses, and questions identified by a diverse community of grassland managers and researchers which may be addressed by future research and monitoring in southeastern grassland ecosystems to help guide science-based conservation of grassland-dependent species.

Alabama, Arkansas, Florida, Georgia, Kentucky, Lou↗

USGS2018

Downscaling future climate change projections over Puerto Rico using a non-hydrostatic atmospheric model

We present results from 20-year “high-resolution” regional climate model simulations of precipitation change for the sub-tropical island of Puerto Rico. The Japanese Meteorological Agency Non-Hydrostatic Model (NHM) operating at a 2-km grid resolution is nested inside the Regional Spectral Model (RSM) at 10-km grid resolution, which in turn is forced at the lateral boundaries by the Community Climate System Model (CCSM4). At this resolution, the climate change experiment allows for deep convection in model integrations, which is an important consideration for sub-tropical regions in general, and on islands with steep precipitation gradients in particular that strongly influence local ecological processes and the provision of ecosystem services. Projected precipitation change for this region of the Caribbean is simulated for the mid-twenty-first century (2041–2060) under the RCP8.5 climate-forcing scenario relative to the late twentieth century (1986–2005). The results show that by the mid-twenty-first century, there is an overall rainfall reduction over the island for all seasons compared to the recent climate but with diminished mid-summer drought (MSD) in the northwestern parts of the island. Importantly, extreme rainfall events on sub-daily and daily time scales also become slightly less frequent in the projected mid-twenty-first-century climate over most regions of the island.

Puerto Rico↗

USGS2017

Characterizing sources of uncertainty from global climate models and downscaling techniques

In recent years climate model experiments have been increasingly oriented towards providing information that can support local and regional adaptation to the expected impacts of anthropogenic climate change. This shift has magnified the importance of downscaling as a means to translate coarse-scale global climate model (GCM) output to a finer scale that more closely matches the scale of interest. Applying this technique, however, introduces a new source of uncertainty into any resulting climate model ensemble. Here we present a method, based on a previously established variance decomposition method, to partition and quantify the uncertainty in climate model ensembles that is attributable to downscaling. We apply the method to the Southeast U.S. using five downscaled datasets that represent both statistical and dynamical downscaling techniques. The combined ensemble is highly fragmented, in that only a small portion of the complete set of downscaled GCMs and emission scenarios are typically available. The results indicate that the uncertainty attributable to downscaling approaches ~20% for large areas of the Southeast U.S. for precipitation and ~30% for extreme heat days (> 35°C) in the Appalachian Mountains. However, attributable quantities are significantly lower for time periods when the full ensemble is considered but only a sub-sample of all models are available, suggesting that overconfidence could be a serious problem in studies that employ a single set of downscaled GCMs. We conclude with recommendations to advance the design of climate model experiments so that the uncertainty that accrues when downscaling is employed is more fully and systematically considered.

Journal of Applied Meteorology and Climatology↗