Geology topics

Daniel Hocking

Publications and source records attributed to Daniel Hocking.

3 recordsLinked to original sources

USGS2016

A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags

Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade −1 ) and a widening of the synchronized period (29 d decade −1 ). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.

PeerJ↗

USGS2015

Seasonal temperature and precipitation regulate brook trout young-of-the-year abundance and population dynamics

Abundance of the young‐of‐the‐year (YOY) fish can vary greatly among years and it may be driven by several key biological processes (i.e. adult spawning, egg survival and fry survival) that span several months. However, the relative influence of seasonal weather patterns on YOY abundance is poorly understood. We assessed the importance of seasonal air temperature (a surrogate for stream temperature) and precipitation (a surrogate for stream flow) on brook trout ( Salvelinus fontinalis ) YOY summer abundance using a 29‐year data set from 115 sites in Shenandoah National Park, Virginia, U.S.A. We used a Bayesian hierarchical model that allowed the effect of seasonal weather covariates to vary among sites and accounted for imperfect detection of individuals. Summer YOY abundance was affected by preceding seasonal air temperature and precipitation, and these regional‐scale drivers led to spatial synchrony in YOY abundance dynamics across the 170‐km‐long study area. Mean winter precipitation had the greatest effect on YOY abundance and the relationship was negative. Mean autumn precipitation, and winter and spring temperature had significantly positive effects on YOY abundance, and mean autumn temperature had a significant negative effect. In addition, the effect of summer precipitation differed along a latitudinal gradient, with YOY abundance at more northern sites being more responsive to inter‐annual variation in summer precipitation. Strong YOY years resulted in high abundance of adults (>age 1 + fish) in the subsequent year at more than half of sites. However, higher adult abundance did not result in higher YOY abundance in the subsequent year at any of the study sites (i.e. no positive stock–recruitment relationship). Our results indicate that YOY abundance is a key driver of brook trout population dynamics that is mediated by seasonal weather patterns. A reliable assessment of climate change impacts on brook trout needs to account for how alternations in seasonal weather patterns impact YOY abundance and how such relationships may differ across the range of brook trout distribution.

Virginia↗

USGS2014

Making decisions in complex landscapes: Headwater stream management across multiple federal agencies

Headwater stream ecosystems are vulnerable to numerous threats associated with climate and land use change. In the northeastern US, many headwater stream species (e.g., brook trout and stream salamanders) are of special conservation concern and may be vulnerable to climate change influences, such as changes in stream temperature and streamflow. Federal land management agencies (e.g., US Fish and Wildlife Service, National Park Service, USDA Forest Service, Bureau of Land Management and Department of Defense) are required to adopt policies that respond to climate change and may have longer-term institutional support to enforce such policies compared to state, local, non-governmental, or private land managers. However, federal agencies largely make management decisions in regards to headwater stream ecosystems independently. This fragmentation of management resources and responsibilities across the landscape may significantly impede the efficiency and effectiveness of conservation actions, and higher degrees of collaboration may be required to achieve conservation goals. This project seeks to provide an example of cooperative landscape decision-making to address the conservation of headwater stream ecosystems. We identified shared and contrasting objectives of each federal agency and potential collaboration opportunities that may increase efficient and effective management of headwater stream ecosystems in two northeastern US watersheds. These workshops provided useful insights into the adaptive capacity of federal institutions to address threats to headwater stream ecosystems. Our ultimate goal is to provide a decision-making framework and analysis that addresses large-scale conservation threats across multiple stakeholders, as a demonstration of cooperative landscape conservation for aquatic ecosystems. Additionally, we aim to provide new scientific knowledge and a regional perspective to resource managers to help inform local management decisions.

Maine, New Hampshire, Virginia, West Virginia↗