Geology topics

Kirk W. Davies

Publications and source records attributed to Kirk W. Davies.

7 recordsLinked to original sources

USGS2024

Cross-scale analysis reveals interacting predictors of annual and perennial cover in Northern Great Basin rangelands

Exotic annual grass invasion is a widespread threat to the integrity of sagebrush ecosystems in Western North America. Although many predictors of annual grass prevalence and native perennial vegetation have been identified, there remains substantial uncertainty about how regional-scale and local-scale predictors interact to determine vegetation heterogeneity, and how associations between vegetation and cattle grazing vary with environmental context. Here, we conducted a regionally extensive, one-season field survey across burned and unburned, grazed, public lands in Oregon and Idaho, with plots stratified by aspect and distance to water within pastures to capture variation in environmental context and grazing intensity. We analyzed regional-scale and local-scale patterns of annual grass, perennial grass, and shrub cover, and examined to what extent plot-level variation was contingent on pasture-level predictions of site favorability. Annual grasses were widespread at burned and unburned sites alike, contrary to assumptions of annual grasses depending on fire, and more common at lower elevations and higher temperatures regionally, as well as on warmer slopes locally. Pasture-level grazing pressure interacted with temperature such that annual grass cover was associated positively with grazing pressure at higher temperatures but associated negatively with grazing pressure at lower temperatures. This suggests that pasture-level temperature and grazing relationships with annual grass abundance are complex and context dependent, although the causality of this relationship deserves further examination. At the plot-level within pastures, annual grass cover did not vary with grazing metrics, but perennial cover did; perennial grasses, for example, had lower cover closer to water sources, but higher cover at higher dung counts within a pasture, suggesting contrasting interpretations of these two grazing proxies. Importantly for predictions of ecosystem response to temperature change, we found that pasture-level and plot-level favorability interacted: perennial grasses had a higher plot-level cover on cooler slopes, and this difference across topography was starkest in pastures that were less favorable for perennial grasses regionally. Understanding the mechanisms behind cross-scale interactions and contingent responses of vegetation to grazing in these increasingly invaded ecosystems will be critical to land management in a changing world.

Ecological Applications↗

USGS2023

Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity

Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this “hierarchy of predictability” hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.

Continental United States↗

USGS2023

Sage-grouse

In this chapter, we summarize the ecology and conservation issues affecting greater ( Centrocercus urophasianus ) and Gunnison ( C . minimus ) sage-grouse, iconic and obligate species of rangelands in the sagebrush ( Artemisia spp.) biome in western North America. Greater sage-grouse are noted for their ability to migrate, whereas Gunnison sage-grouse localize near leks year-round. Seasonal habitats include breeding habitat where males display at communal leks, nesting habitat composed of dense sagebrush and herbaceous plants to conceal nests, mesic summer habitats where broods are reared, and winter habitat, characterized by access to sagebrush for cover and forage. While two-thirds of sage-grouse habitat occurs on public lands, private land conservation is the focus of national groups including the USDA-NRCS Sage-Grouse Initiative. Sage-grouse are a species of great conservation concern due to population declines associated with loss and fragmentation of more than half of the sagebrush biome. Wildlife and land management agencies have been increasingly proactive in monitoring trends in sage-grouse populations (e.g., lek count index), adapting regulations to reduce harvest on declining populations, and in designing and implementing conservation policies such as core areas to conserve sage-grouse habitats and populations. Much of the remaining sagebrush habitat is threatened by altered fire regimes, invasive annual grasses and noxious weeds, encroaching piñon ( Pinus edulis and monophylla )-juniper ( Juniperus spp.) woodlands, sagebrush conversion, anthropogenic development, and climate change. Several diseases affect sage-grouse, but to date, disease has not been a widespread cause of declines. Proper livestock grazing and limited hunting appear to be sustainable with sage-grouse, whereas improper grazing, increasing free-roaming equid populations, and sagebrush conversion are primary concerns for future conservation. Research has identified additional concerns for sage-grouse including effects from fence collisions, predation from common ravens ( Corvus corax ), and reduced habitat effectiveness resulting from grouse avoidance of anthropogenic infrastructure. There is a need for future research evaluating sage-grouse habitat restoration practices following improper rangeland management, habitat alteration from invasive species and fire, effects on small and isolated populations, and effects from diseases.

Book chapter↗

USGS2023

Variable effects of long-term livestock grazing across the western United States suggest diverse approaches are needed to meet global change challenges

Aims Livestock production is the most widespread land use globally and occurs across a diverse set of ecosystems. Variability in long-term livestock grazing impacts across ecosystems is poorly characterized, particularly at larger spatial scales, despite strong relationships with various ecosystem services related to soil fertility and stabilization and vegetation productivity. Here we examine the effects of grazing on vegetation and the implications for resistance and resilience to global change. Methods We use six long-term research stations in the western United States, spanning two ecoregions, multiple ecosystems, and 311 total site-years of research. Across these sites we evaluate convergence and divergence of vegetation response to grazing vs grazing removal, focusing on interactions with drivers of global change. Results We found that at long time scales (multiple decades), grazing has numerous convergent and divergent effects across ecoregions and ecosystems. Similarity among precipitation patterns and plant traits linked to grazing and production timing were key elements explaining convergence or divergence in long-term patterns of livestock grazing response. Ecosystem differences across western US rangelands are also associated with variable effects of grazing on resistance and resilience to invasive species and climate change. Conclusions These results suggest that unique ecosystem or ecoregion responses to future global change may result from complex interactions between grazing and environmental factors, such as precipitation timing and plant traits. Adapting livestock and grazing management to specific ecosystem vegetation and climate variability is needed to manage for the myriad global changes affecting rangeland production and diversity.

Applied Vegetation Science↗

USGS2023

Trends, impacts, and cost of catastrophic and frequent wildfires in the sagebrush biome

Fire regimes in sagebrush ( Artemisia spp.) ecosystems have been greatly altered across the western United States. Broad-scale invasion of non-native annual grasses, climate change, and human activities have accelerated wildfire cycles, increased fire size and severity, and lengthened fire seasons in many sagebrush ecosystems to the point that current wildfire-management practices and postfire restoration efforts cannot keep pace to ameliorate the ecological consequences of sagebrush ecosystem loss. The greatest impact of uncharacteristically frequent fire is the transition from native sagebrush-perennial grass communities to invasive, non-native, annual grasslands that are highly flammable. These community transitions are often permanent, owing to the low probability of reestablishing native perennial plants in non-native annual grass−dominated communities. Moreover, these grasses can form extensive and continuous fine fuel loads that promote more frequent fire and the continued expansion of invasive, non-native annuals. More frequent, larger, and severe wildfires necessitate greater resources for fire-prevention, fire-suppression, and postfire restoration activities, while decreasing critical ecosystem services, economic and recreational opportunities, and cultural traditions. Increased flexibility and better prioritization of management activities based on ecological needs, including commitment to long-term prefire and postfire management, are needed to achieve notable reductions in uncharacteristic wildfire activity and associated negative impacts. Collaboration and partnerships across jurisdictional boundaries, agencies, and disciplines can improve consistency in sagebrush-management approaches and thereby contribute to this effort. Here, we provide a synthesis on sagebrush wildfire trends and the impacts of uncharacteristic fire regimes on sagebrush plant communities, dependent wildlife species, fire-suppression costs, and ecosystem services. We also provide an overview of wildland fire coordination efforts among federal, state, and tribal entities.

Rangeland Ecology and Management↗

USGS2021

Drivers of seedling establishment success in dryland restoration efforts

Restoration of degraded drylands is urgently needed to mitigate climate change, reverse desertification and secure livelihoods for the two billion people who live in these areas. Bold global targets have been set for dryland restoration to restore millions of hectares of degraded land. These targets have been questioned as overly ambitious, but without a global evaluation of successes and failures it is impossible to gauge feasibility. Here we examine restoration seeding outcomes across 174 sites on six continents, encompassing 594,065 observations of 671 plant species. Our findings suggest reasons for optimism. Seeding had a positive impact on species presence: in almost a third of all treatments, 100% of species seeded were growing at first monitoring. However, dryland restoration is risky: 17% of projects failed, with no establishment of any seeded species, and consistent declines were found in seeded species as projects matured. Across projects, higher seeding rates and larger seed sizes resulted in a greater probability of recruitment, with further influences on species success including site aridity, taxonomic identity and species life form. Our findings suggest that investigations examining these predictive factors will yield more effective and informed restoration decision-making.

Nature Ecology and Evolution↗

USGS2021

Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty

Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales. We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data. Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product. The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform (https://rangelands.app/), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.

Methods in Ecology and Evolution↗