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Brandon T. Bestelmeyer

Publications and source records attributed to Brandon T. Bestelmeyer.

16 recordsLinked to original sources
USGS2025

Sentinel-2 based estimates of rangeland fractional cover and canopy gap class for the western United States

Rangelands are extensive ecosystems, providing important ecosystem services while undergoing continuous change. As a result, improved monitoring technologies can help better characterize vegetation change. Satellite remote sensing has proven effective in this regard, tracking vegetation dynamics at broad and fine scales. We leveraged the spatial, spectral, and temporal resolution of Sentinel-2 satellites to estimate fractional cover and canopy gap across rangelands of the western United States. We produced annual, 10 m spatial resolution estimates of fractional cover and canopy gap size class for years 2018 to 2024. Fractional cover estimates include that of common plant functional types (annual forb and grass, bareground, littler, perennial forb and grass, shrub, tree) and select genera (including invasive annual grass species, pinyon-juniper species, and sagebrush species); canopy gap size classes include gap sizes 25 to 50, 51 to 100, 101 to 200, and greater than 200 cm. We make these data available as Cloud Optimized GeoTIFFs, organized as 75 × 75 km tiles covering the 17 western states of the United States.

western United States↗
USGS2025

Sentinel-2 based estimates of rangeland fractional cover and canopy gap class for the western United States

Rangelands are extensive ecosystems, providing important ecosystem services while undergoing continuous change. As a result, improved monitoring technologies can help better characterize vegetation change. Satellite remote sensing has proven effective in this regard, tracking vegetation dynamics at broad and fine scales. We leveraged the spatial, spectral, and temporal resolution of Sentinel-2 satellites to estimate fractional cover and canopy gap across rangelands of the western United States. We produced annual, 10 m spatial resolution estimates of fractional cover and canopy gap size class for years 2018 to 2024. Fractional cover estimates include that of common plant functional types (annual forb and grass, bareground, littler, perennial forb and grass, shrub, tree) and select genera (including invasive annual grass species, pinyon-juniper species, and sagebrush species); canopy gap size classes include gap sizes 25 to 50, 51 to 100, 101 to 200, and greater than 200 cm. We make these data available as Cloud Optimized GeoTIFFs, organized as 75×75 km tiles covering the 17 western states of the United States.

BioRxiv↗
USGS2024

The LTAR Grazing Land Common Experiment at the Jornada Experimental Range: Old genetics, new precision technologies, and adaptive value chains

Rangelands and the supply chains connected to them are central to the agrifood systems of the Southwestern United States. Local ranchers are simultaneously arid lands managers, herd managers, and marketing managers. To stay in business, they must constantly adapt to unpredictable forage resources and markets while conserving soils and vegetation resources for the long term. As climate warming and drying exacerbate the complexity and difficulty of day-to-day production, producers and policy-makers are seeking alternatives to “business as usual”. To meet this need, the LTAR-Jornada team has developed a package of strategies to help producers adapt to the local and inter-regional challenges. The package includes heritage cattle, precision ranching systems, and adaptive value chains. Five ranches across the Southwest have adopted different combinations of the strategies and are partnering to measure their benefits and drawbacks in real-world conditions. Opportunities for controlled experimentation differ among the ranches, so we use LTAR’s indicator system to assess and compare results. Even as we invest in co-producing knowledge about these three strategies, we recognize that progressive aridification and urbanization of Southwestern rangelands create challenges for which a single “silver bullet” agricultural innovation is unlikely to provide durable solutions. We are learning from our customers and stakeholders about ways to adjust the development of new options.

New Mexico↗
USGS2023

The Landscape Data Commons: A system for standardizing, accessing, and applying large environmental datasets for agroecosystem research and management

Understanding where, when, and why agroecosystems are changing requires quality information about ecosystems that span land tenure, ecological processes, and spatial scales. Over the past two decades, land management agencies and research groups have adopted a suite of standardized methods for monitoring rangelands, which have been implemented at over 85,000 monitoring locations globally. However, the ability to use these data to understand agroecosystem dynamics and change across scales and across land ownership has been limited because, until now, these data have not been available in a harmonized, accessible format for analyses, modeling, and decision-support tools. We present the Landscape Data Commons, a cyberinfrastructure platform that harmonizes and aggregates standardized agroecosystem data, enables linkages to models, and facilitates analysis and interpretation of data within decision-support tools. The Landscape Data Commons provides a community platform for users to contribute data and develop next-generation tools to support agroecosystem management through the 21st century.

Agricultural & Environmental Letters↗
USGS2022

The consequences of climate change for dryland biogeochemistry

Drylands, which cover more than 40% of Earth’s terrestrial surface, are dominant drivers of global biogeochemical cycling and home to more than one third of the human population. Climate projections predict warming, drought frequency and severity, and evaporative demand will increase in drylands at faster rates than global means. Due to extreme temperatures and high biological dependency on limited water availability, drylands are predicted to be exceptionally sensitive to climate change and, indeed, significant climate impacts are already being observed. Yet our understanding and ability to forecast climate change effects on dryland biogeochemistry and ecosystem functions lag behind many mesic systems. To improve our capacity to forecast ecosystem change, we propose focusing on the controls and consequences of two key characteristics affecting dryland biogeochemistry: i) high spatial and temporal heterogeneity in environmental conditions and ii) generalized resource scarcity. In addition to climate change, drylands are experiencing accelerating land use change. Building our understanding of dryland biogeochemistry in both intact and disturbed systems will better equip us to address the interacting effects of climate change and landscape degradation. Responding to these challenges will require a diverse, globally distributed, and interdisciplinary community of dryland experts united towards better understanding these vast and important ecosystems.

New Phytologist Foundation↗
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↗
USGS2019

Traversing the wasteland: A framework for assessing ecological threats to drylands

Drylands cover 41% of the Earth's terrestrial surface, play a critical role in global ecosystem function, and are home to over two billion people. Like other biomes, drylands face increasing pressure from global change, but many of these ecosystems are close to tipping points, which, if crossed, can lead to abrupt transitions and persistent degraded states. Their limited but variable precipitation, low soil fertility, and low productivity have given rise to a perception that drylands are wastelands, needing societal intervention to bring value to them. Negative perceptions of drylands synergistically combine with conflicting sociocultural values regarding what constitutes a threat to these ecosystems. In the present article, we propose a framework for assessing threats to dryland ecosystems and suggest we must also combat the negative perceptions of drylands in order to preserve the ecosystem services that they offer.

Arizona, Colorado, New Mexico, Utah↗
USGS2019

Digital mapping of ecological land units using a nationally scalable modeling framework

Ecological site descriptions (ESDs) and associated state-and-transition models (STMs) provide a nationally consistent classification and information system for defining ecological land units for management applications in the United States. Current spatial representations of ESDs, however, occur via soil mapping and are therefore confined to the spatial resolution used to map soils within a survey area. Land management decisions occur across a range of spatial scales and therefore require ecological information that spans similar scales. Digital mapping provides an approach for optimizing the spatial scale of modeling products to best serve decision makers and have the greatest impact in addressing land management concerns. Here, we present a spatial modeling framework for mapping ecological sites using machine learning algorithms, soil survey field observations, soil survey geographic databases, ecological site data, and a suite of remote sensing-based spatial covariates (e.g., hyper-temporal remote sensing, terrain attributes, climate data, land-cover, lithology). Based on the theoretical association between ecological sites and landscape biophysical properties, we hypothesized that the spatial distribution of ecological sites could be predicted using readily available geospatial data. This modeling approach was tested at two study areas within the western United States, representing 6.1 million ha on the Colorado Plateau and 7.5 million ha within the Chihuahuan Desert. Results show our approach was effective in mapping grouped ecological site classes (ESGs), with 10-fold cross-validation accuracies of 70% in the Colorado Plateau based on 1405 point observations across eight expertly-defined ESG classes and 79% in the Chihuahuan Desert based on 2589 point observations across nine expertly-defined ESG classes. Model accuracies were also evaluated using external-validation datasets; resulting in 56 and 44% correct classification for the Colorado Plateau and Chihuahuan Desert, respectively. National coverage of the training and covariate data used in this study provides opportunities for a consistent national-scale mapping effort of ecological sites.

Chihuahuan Desert, Colorado Plateau↗
USGS2016

Improving the effectiveness of ecological site descriptions: General state-and-transition models and the Ecosystem Dynamics Interpretive Tool (EDIT)

State-and-transition models (STMs) are useful tools for management, but they can be difficult to use and have limited content. STMs created for groups of related ecological sites could simplify and improve their utility. The amount of information linked to models can be increased using tables that communicate management interpretations and important within-group variability. We created a new web-based information system (the Ecosystem Dynamics Interpretive Tool) to house STMs, associated tabular information, and other ecological site data and descriptors. Fewer, more informative, better organized, and easily accessible STMs should increase the accessibility of science information.

Rangelands↗
USGS2016

Generalizing ecological site concepts of the Colorado Plateau for landscape-level applications

Numerous ecological site descriptions in the southern Utah portion of the Colorado Plateau can be difficult to navigate, so we held a workshop aimed at adding value and functionality to the current ecological site system. We created new groups of ecological sites and drafted state-and-transition models for these new groups. We were able to distill the current large number of ecological sites in the study area (ca. 150) into eight ecological site groups that capture important variability in ecosystem dynamics. Several inventory and monitoring programs and landscape scale planning actions will likely benefit from more generalized ecological site group concepts.

Rangelands↗
USGS2015

Desertification, land use, and the transformation of global drylands

Desertification is an escalating concern in global drylands, yet assessments to guide management and policy responses are limited by ambiguity concerning the definition of “desertification” and what processes are involved. To improve clarity, we propose that assessments of desertification and land transformation be placed within a state change–land-use change (SC–LUC) framework. This framework considers desertification as state changes occurring within the context of particular land uses (eg rangeland, cropland) that interact with land-use change. State changes that can be readily reversed are distinguished from regime shifts, which are state changes involving persistent alterations to vegetation or soil properties. Pressures driving the transformation of rangelands to other types of land uses may be low, fluctuating, or high, and may influence and be influenced by state change. We discuss how the SC–LUC perspective can guide more effective assessment of desertification and management of drylands.

Frontiers in Ecology and the Environment↗
USGS2014

Scale-dependent feedbacks between patch size and plant reproduction in desert grassland

Theoretical models suggest that scale-dependent feedbacks between plant reproductive success and plant patch size govern transitions from highly to sparsely vegetated states in drylands, yet there is scant empirical evidence for these mechanisms. Scale-dependent feedback models suggest that an optimal patch size exists for growth and reproduction of plants and that a threshold patch organization exists below which positive feedbacks between vegetation and resources can break down, leading to critical transitions. We examined the relationship between patch size and plant reproduction using an experiment in a Chihuahuan Desert grassland. We tested the hypothesis that reproductive effort and success of a dominant grass ( Bouteloua eriopoda ) would vary predictably with patch size. We found that focal plants in medium-sized patches featured higher rates of grass reproductive success than when plants occupied either large patch interiors or small patches. These patterns support the existence of scale-dependent feedbacks in Chihuahuan Desert grasslands and indicate an optimal patch size for reproductive effort and success in B. eriopoda . We discuss the implications of these results for detecting ecological thresholds in desert grasslands.

New Mexico↗
USGS2012

A test of critical thresholds and their indicators in a desertification-prone ecosystem: more resilience than we thought

Theoretical models predict that drylands can cross critical thresholds, but experimental manipulations to evaluate them are non-existent. We used a long-term (13-year) pulse-perturbation experiment featuring heavy grazing and shrub removal to determine if critical thresholds and their determinants can be demonstrated in Chihuahuan Desert grasslands. We asked if cover values or patch-size metrics could predict vegetation recovery, supporting their use as early-warning indicators. We found that season of grazing, but not the presence of competing shrubs, mediated the severity of grazing impacts on dominant grasses. Recovery occurred at the same rate irrespective of grazing history, suggesting that critical thresholds were not crossed, even at low cover levels. Grass cover, but not patch size metrics, predicted variation in recovery rates. Some transition-prone ecosystems are surprisingly resilient; management of grazing impacts and simple cover measurements can be used to avert undesired transitions and initiate restoration.

Ecology Letters↗
USGS2012

A holistic strategy for adaptive land management

Adaptive management is widely applied to natural resources management (Holling 1973; Walters and Holling 1990). Adaptive management can be generally defined as an iterative decision-making process that incorporates formulation of management objectives, actions designed to address these objectives, monitoring of results, and repeated adaptation of management until desired results are achieved (Brown and MacLeod 1996; Savory and Butterfield 1999). However, adaptive management is often criticized because very few projects ever complete more than one cycle, resulting in little adaptation and little knowledge gain (Lee 1999; Walters 2007). One significant criticism is that adaptive management is often used as a justification for undertaking actions with uncertain outcomes or as a surrogate for the development of specific, measurable indicators and monitoring programs (Lee 1999; Ruhl 2007).

Journal of Soil and Water Conservation↗
USGS2009

Historical and modern disturbance regimes, stand structures, and landscape dynamics in piñon-juniper vegetation of the western United States

Piñon–juniper is a major vegetation type in western North America. Effective management of these ecosystems has been hindered by inadequate understanding of 1) the variability in ecosystem structure and ecological processes that exists among the diverse combinations of piñons, junipers, and associated shrubs, herbs, and soil organisms; 2) the prehistoric and historic disturbance regimes; and 3) the mechanisms driving changes in vegetation structure and composition during the past 150 yr. This article summarizes what we know (and don't know) about three fundamentally different kinds of piñon–juniper vegetation. Persistent woodlands are found where local soils, climate, and disturbance regimes are favorable for piñon, juniper, or a mix of both; fires have always been infrequent in these woodlands. Piñon–juniper savannas are found where local soils and climate are suitable for both trees and grasses; it is logical that low-severity fires may have maintained low tree densities before disruption of fire regimes following Euro-American settlement, but information is insufficient to support any confident statements about historical disturbance regimes in these savannas. Wooded shrublands are found where local soils and climate support a shrub community, but trees can increase during moist climatic conditions and periods without disturbance and decrease during droughts and following disturbance. Dramatic increases in tree density have occurred in portions of all three types of piñon–juniper vegetation, although equally dramatic mortality events have also occurred in some areas. The potential mechanisms driving increases in tree density—such as recovery from past disturbance, natural range expansion, livestock grazing, fire exclusion, climatic variability, and CO 2 fertilization—generally have not received enough empirical or experimental investigation to predict which is most important in any given location. The intent of this synthesis is 1) to provide a source of information for managers and policy makers; and 2) to stimulate researchers to address the most important unanswered questions.

Rangeland Ecology and Management↗