Geology topics

E. Ashley Steel

Publications and source records attributed to E. Ashley Steel.

9 recordsLinked to original sources

USGS2024

Life on land needs fresh water (SDG 15)

Terrestrial ecosystems, such as forests, and the inland waters within them, such as bogs, floodplains, lakes, rivers, springs, and wetlands, are foundational for life on earth. They provide critical ecosystem services such as carbon storage and sequestration, clean water, primary production, pollination, soil fertility, and erosion control. The human footprint on terrestrial and freshwater ecosystems continues to expand, imposing pressures from deforestation, invasive species, climate change, overexploitation of species, and land conversion for agricultural production. The United Nations’ Sustainable Development Goal (SDG) 15 (Life on Land) aims to address these changes by promoting the protection, restoration, and sustainable use of terrestrial ecosystems globally. Freshwater ecosystem services and freshwater biological diversity are inherently part of, and critical to, achieving SDG 15; yet they remain absent from the goal and largely hidden within the targets and indicators. Here, we aim to highlight the role and importance of freshwater ecosystems in achieving SDG 15. We identify the six major themes of SDG 15 in which freshwater ecosystems have a preeminent role: (1) increasing protected areas, (2) sustainably managing forests, (3) reducing land degradation, (4) protecting threatened and trafficked species, (5) reducing invasive species, and (6) mobilizing resources. For each theme, we detail (a) freshwater connections to the topic, (b) key opportunities in addressing freshwater components, and (c) a relevant case study highlighting cobenefits for terrestrial ecosystems from actions targeting freshwater ecosystems. We conclude with opportunities for integrative terrestrial–aquatic monitoring, management, and policy actions. Ultimately, achieving the targets of SDG 15 requires recognition of terrestrial–aquatic interdependencies and prioritization of freshwater ecosystems and biodiversity.

Book chapter↗

USGS2023

Future-proofing the Emergency Recovery Plan for freshwater biodiversity

Freshwater biodiversity loss is accelerating globally, but humanity can change this trajectory through actions that enable recovery. To be successful, these actions require coordination and planning at a global scale. The Emergency Recovery Plan for global freshwater biodiversity aims to reduce the risk for freshwater biodiversity loss through six priority actions: (1) accelerate implementation of environmental flows; (2) improve water quality to sustain aquatic life; (3) protect and restore critical habitats; (4) manage exploitation of freshwater species and riverine aggregates; (5) prevent and control nonnative species invasions in freshwater habitats; and (6) safeguard and restore freshwater connectivity. These actions can be implemented using future-proofing approaches that anticipate future risks (e.g., emerging pollutants, new invaders, and synergistic effects) and minimize likely stressors to make conservation of freshwater biodiversity more resilient to climate change and other global environmental challenges. While uncertainty with respect to past observations is not a new concern for freshwater biodiversity, future-proofing has the distinction of accounting for the uncertainty of future conditions that have no historical baseline. The level of uncertainty with respect to future conditions is unprecedented. Future-proofing of the Emergency Recovery Plan for freshwater biodiversity will require anticipating future changes and developing and implementing actions to address those future changes. Here, we showcase future-proofing approaches likely to be successful using local case studies and examples. Ensuring that response options within the Emergency Recovery Plan are future-proofed will provide decision makers with science-informed choices, even in the face of uncertain and potentially new future conditions. We are at an inflection point for global freshwater biodiversity loss; learning from defeats and successes can support improved actions toward a sustainable future.

Environmental Reviews↗

USGS2022

A future for the inland fish and fisheries hidden within the sustainable development goals

The United Nations Sustainable Development Goals (SDGs) are a unifying call for change - guiding global actions at multiple levels of governance for a better planet and better lives. Consequently, achieving the “future we want” may be hindered by overlooking valuable natural resources and services that are not explicitly included in the SDGs. Not recognizing the direct, intrinsic value of some natural resources may threaten the sustainability of the services they provide and their contributions to the SDGs. Here, we use inland aquatic ecosystems, and the fish and fisheries therein, as an example to explore opportunities for recognition and inclusion of other natural resources that are missing from the SDGs. Key resources absent from the SDGs are less likely to be incorporated in global, national, and regional objectives, dialogues, and policies. We outline multiple potential pathways for better inclusion and capitalization of contributions from these overlooked natural resources during the operationalization of the SDGs and other global instruments.

Frontiers in Environmental Science↗

USGS2020

Inland fish and fisheries integral to achieving the Sustainable Development Goals

Inland fish provide food for billions and livelihoods for millions of people worldwide and are integral to effective freshwater ecosystem function, yet the recognition of these services is notably absent in development discussions and policies, such as the United Nations Sustainable Development Goals (SDGs). How might the SDGs be enhanced if inland fishery services were integrated into policies and development schemes? Here, we examine the relationships between inland fish, sustainable fisheries, and functioning freshwater systems and the targets of the SDGs. Our goal is to highlight synergies across the SDGs, particularly No Poverty (SDG 1), Zero Hunger (SDG 2), Clean Water and Sanitation (SDG 6), Responsible Consumption and Production (SDG 12) and Life on Land (SDG 15), that can be achieved with the inclusion of these overlooked inland fishery services.

Nature Sustainability↗

USGS2017

Envisioning, quantifying, and managing thermal regimes on river networks

Water temperatures fluctuate in time and space, creating diverse thermal regimes on river networks. Temporal variability in these thermal landscapes has important biological and ecological consequences because of nonlinearities in physiological reactions; spatial diversity in thermal landscapes provides aquatic organisms with options to maximize growth and survival. However, human activities and climate change threaten to alter the dynamics of riverine thermal regimes. New data and tools can identify particular facets of the thermal landscape that describe ecological and management concerns and that are linked to human actions. The emerging complexity of thermal landscapes demands innovations in communication, opens the door to exciting research opportunities on the human impacts to and biological consequences of thermal variability, suggests improvements in monitoring programs to better capture empirical patterns, provides a framework for suites of actions to restore and protect the natural processes that drive thermal complexity, and indicates opportunities for better managing thermal landscapes.

Washington↗

USGS2017

Estimating inbreeding rates in natural populations: Addressing the problem of incomplete pedigrees

Understanding and estimating inbreeding is essential for managing threatened and endangered wildlife populations. However, determination of inbreeding rates in natural populations is confounded by incomplete parentage information. We present an approach for quantifying inbreeding rates for populations with incomplete parentage information. The approach exploits knowledge of pedigree configurations that lead to inbreeding coefficients of F = 0.25 and F = 0.125, allowing for quantification of Pr( I | k ): the probability of observing pedigree I given the fraction of known parents ( k ). We developed analytical expressions under simplifying assumptions that define properties and behavior of inbreeding rate estimators for varying values of k . We demonstrated that inbreeding is overestimated if Pr( I | k ) is not taken into consideration and that bias is primarily influenced by k . By contrast, our new estimator, incorporating Pr( I | k ), is unbiased over a wide range of values of k that may be observed in empirical studies. Stochastic computer simulations that allowed complex inter- and intragenerational inbreeding produced similar results. We illustrate the effects that accounting for Pr( I | k ) can have in empirical data by revisiting published analyses of Arabian oryx ( Oryx leucoryx ) and Red deer ( Cervus elaphus ). Our results demonstrate that incomplete pedigrees are not barriers for quantifying inbreeding in wild populations. Application of our approach will permit a better understanding of the role that inbreeding plays in the dynamics of populations of threatened and endangered species and may help refine our understanding of inbreeding avoidance mechanisms in the wild.

Journal of Heredity↗

USGS2015

Rethinking the longitudinal stream temperature paradigm: region-wide comparison of thermal infrared imagery reveals unexpected complexity of river temperatures

Prevailing theory suggests that stream temperature warms asymptotically in a downstream direction, beginning at the temperature of the source in the headwaters and leveling off downstream as it converges to match meteorological conditions. However, there have been few empirical examples of longitudinal patterns of temperature in large rivers due to a paucity of data. We constructed longitudinal thermal profiles (temperature versus distance) for 53 rivers in the Pacific Northwest (USA) using an extensive dataset of remotely sensed summertime river temperatures and classified each profile into one of five patterns of downstream warming: asymptotic (increasing then flattening), linear (increasing steadily), uniform (not changing), parabolic (increasing then decreasing), or complex (not fitting other classes). We evaluated (1) how frequently profiles warmed asymptotically downstream as expected, and (2) whether relationships between river temperature and common hydroclimatic variables differed by profile class. We found considerable diversity in profile shape, with 47% of rivers warming asymptotically, and 53% having alternative profile shapes. Water temperature did not warm substantially over the course of the river for coastal parabolic and uniform profiles, and for some linear and complex profiles. Profile classes showed no clear geographical trends. The degree of correlation between river temperature and hydroclimatic variables differed among profile classes, but there was overlap among classes. Water temperature in rivers with asymptotic or parabolic profiles was positively correlated with August air temperature, tributary temperature and velocity, and negatively correlated with elevation, August precipitation, gradient, and distance upstream. Conversely, associations were less apparent in rivers with linear, uniform, or complex profiles. Factors contributing to the unique shape of parabolic profiles differed for coastal and inland rivers, where downstream cooling was influenced locally by climate or cool water inputs, respectively. Potential drivers of shape for complex profiles were specific to each river. These thermal patterns indicate diverse thermal habitats that may promote resilience of aquatic biota to climate change. Without this spatial context, climate change models may incorrectly estimate loss of thermally suitable habitat.

California, Idaho, Oregon, Washington↗

USGS2014

Applications of spatial statistical network models to stream data

Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., nonindependence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.

WIREs Water↗

USGS2013

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↗