Geology topics

Bill Davidson

Publications and source records attributed to Bill Davidson.

4 recordsLinked to original sources

USGS2020

Spatial grain of adaptation is much finer than ecoregional-scale common gardens reveal

Adaptive variation among plant populations must be known for effective conservation and restoration of imperiled species and predicting their responses to a changing climate. Common‐garden experiments, in which plants sourced from geographically distant populations are grown together such that genetic differences may be expressed, have provided much insight on adaptive variation. Common‐garden experiments also form the foundation for climate‐based seed‐transfer guidelines. However, the spatial scale at which population differentiation occurs is rarely addressed, leaving a critical information gap for parameterizing seed‐transfer guidelines and assessing species’ climate vulnerability. We asked whether adaptation was evident among populations of a foundational perennial within a single “empirical” seed‐transfer zone (based on previous common‐garden findings evaluating very distant populations) but different “provisional” seed zones (groupings of areas of similar climate and are not parameterized from common‐garden data). Seedlings from three populations originating from similar conditions within an intermediate elevation were planted into gardens nearby at the same elevation, or 250–450 m higher or lower in elevation and 0.4–25 km away. Substantial variation was observed between gardens in survival (ranging 2%–99%), foliar crown volume (7.8–22.6 dm 3 ), and reproductive effort (0%–65%), but not among the three transplanted populations. The between garden variation was inversely related to climatic differences between the gardens and seed‐source populations, specifically the site differences in maximum–minimum annual temperatures. Results suggest that substantial site‐specificity in adaptation can occur at finer scales than is accounted for in empirical seed‐transfer guidance when the guidance is derived from broadscale common‐garden studies. Being within the same empirical seed zone, geographic unit, and even within 10 km distance may not qualify as “local” in the context of seed transfer. Moving forward, designing common‐garden experiments so that they allow for testing the scale of adaptation will help in translating the resulting seed‐transfer guidance to restoration projects.

Idaho↗

USGS2019

Can’t see the random forest for the decision trees: Selecting predictive models for restoration ecology

Improving predictions of restoration outcomes is increasingly important to resource managers for accountability and adaptive management, yet there is limited guidance for selecting a predictive model from the multitude available. The goal of this paper was to identify an optimal predictive framework for restoration ecology using eleven modeling frameworks (including, machine learning, inferential, and ensemble approaches), and three data groups (field data, geographic data [GIS], and a combination thereof). We test this approach with a dataset from a large post-fire sagebrush reestablishment project in the Great Basin, USA. Predictive power varied among models and data groups, ranging from 58-79% accuracy. Finer scale field data generally had the greatest predictive power, although GIS data were present in the best models overall. An ensemble prediction computed from the ten models parameterized to field data was well above average for accuracy but was outperformed by others that prioritized model parsimony by selecting predictor variables based on rankings of their importance among all candidate models. The variation in predictive power among a suite of modeling frameworks underscores the importance of a model comparison and refinement approach that evaluates multiple models and data groups, and selects variables based on their contribution to predictive power. The enhanced understanding of factors influencing restoration outcomes accomplished by this framework has the potential to aid the adaptive management process for improving future restoration outcomes.

Restoration Ecology↗

USGS2019

Landscape and organismal factors affecting sagebrush-seedling transplant survival after megafire restoration

Larger and more frequent disturbances are motivating efforts to accelerate recovery of foundational perennial species by focusing efforts into establishing island patches to sustain keystone species and facilitate recovery of the surrounding plant community. Evaluating the variability in abiotic and biotic factors that contribute to differences in survival and establishment can provide useful insight into the relative importance of these factors. In the western United States, severe degradation of the sagebrush steppe has motivated substantial efforts to restore native perennial cover, but success has been mixed. In this study, we evaluated survival of >3000 sagebrush seedlings transplanted on 12 patches totaling of 650 ha within a 113,000 ha burn area, and related the survival to organismal and sub‐taxonomic traits, and to landscape variables. Big sagebrush has high intraspecific diversity attributed to subspecies and cytotypes identifiable through UV‐induced fluorescence, length:width of leaves, or genome size (ploidy). Of these organismal traits, survival was related only to UV fluorescence, and then only so when landscape variables were excluded from analyses. The most significant landscape variable affecting survival was soil taxonomic subgroup, with much lower survival where buried restrictive layers reduce deep water infiltration. Survival also decreased with greater slope steepness, exotic annual grass cover, and burn severity. Survival was optimal where perennial bunchgrasses comprised 8‐14% of total cover. These soil, topographic, and community condition factors revealed through monitoring of landscape‐level treatments can be used to explain the success of plantings and to strategically plan future restoration projects.

Restoration Ecology↗

USGS2018

Thresholds and hotspots for shrub restoration following a heterogeneous megafire

Context Reestablishing foundational plant species through aerial seeding is an essential yet challenging step for restoring the vast semiarid landscapes impacted by plant invasions and wildfire-regime shifts. A key component of the challenge stems from landscape variability and its effects on plant recovery. Objectives We assessed landscape correlates, thresholds, and tipping points for sagebrush presence from fine-scale sampling across a large, heterogeneous area burned the previous year, where we were able to quantify soil surface features that are typically occluded yet can strongly affect recovery patterns. Methods Hypothesis testing and binary-decision trees were used to evaluate factors affecting initial sagebrush establishment, using 2171 field plots (totaling ~ 2,000,000 m 2 sampled) over a 113,000-ha region. Results Sagebrush established in 50% of plots where it was seeded, a > 12-fold greater establishment frequency than in unseeded areas. Sagebrush establishment was enhanced in threshold-like ways by elevation (> 1200 m ASL), topographic features that alter heatload and soil water, and by soil-surface features such as “fertile islands” that bore the imprint of pre-fire sagebrush. Sagebrush occupancy had a negative, linear relationship with exotic-annual grass cover and parabolic relationship with perennial bunchgrasses (optimal at 40% cover). Conclusions Our approach revealed interactive, ecological relationships such as novel soil-surface effects on first year establishment of sagebrush across the burned landscape, and identified “hot spots” for recovery. The approach could be expanded across sites and years to provide the information needed to explain past seeding successes or failures, and in designing treatments at the landscape scale.

Idaho↗