@article {JRN55414, title = {Cross-Site comparisons of dryland ecosystem response to climate change in the US Long-Term Ecological Research Network}, journal = {BioScience}, volume = {72}, year = {2022}, month = {8/16/2022}, pages = {889-907}, abstract = {Long-term observations and experiments in diverse drylands reveal how ecosystems and services are responding to climate change. To develop generalities about climate change impacts at dryland sites, we compared broadscale patterns in climate and synthesized primary production responses among the eight terrestrial, nonforested sites of the United States Long-Term Ecological Research (US LTER) Network located in temperate (Southwest and Midwest) and polar (Arctic and Antarctic) regions. All sites experienced warming in recent decades, whereas drought varied regionally with multidecadal phases. Multiple years of wet or dry conditions had larger effects than single years on primary production. Droughts, floods, and wildfires altered resource availability and restructured plant communities, with greater impacts on primary production than warming alone. During severe regional droughts, air pollution from wildfire and dust events peaked. Studies at US LTER drylands over more than 40 years demonstrate reciprocal links and feedbacks among dryland ecosystems, climate-driven disturbance events, and climate change.}, keywords = {ANPP, climate change, disturbance, drought, LTER, wildfire}, doi = {https://doi.org/10.1093/biosci/biab134}, url = {files/bibliography/22-023.pdf}, author = {Amy R Hudson and Debra P C Peters and John M Blair and Daniel L. Childers and Peter T Doran and Kerrie Geil and Micheal Gooseff and Katherine L Gross and Nick Haddad and Melissa A Pastore and Jennifer A Rudgers and Osvaldo Sala and Eric W Seabloom and Gaius Shaver} } @article {JRN54949, title = {Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U.S. rangelands, 1984{\textendash}2017}, journal = {Ecosphere}, volume = {9}, year = {2018}, month = {09/2018}, pages = {1-19}, chapter = {1}, abstract = {

Innovations in machine learning and cloud-based computing were merged with historical
remote sensing and field data to provide the first moderate resolution, annual, percent cover maps of plant
functional types across rangeland ecosystems to effectively and efficiently respond to pressing challenges
facing conservation of biodiversity and ecosystem services. We utilized the historical Landsat satellite
record, gridded meteorology, abiotic land surface data, and over 30,000 field plots within a Random
Forests model to predict per-pixel percent cover of annual forbs and grasses, perennial forbs and grasses,
shrubs, and bare ground over the western United States from 1984 to 2017. Results were validated using
three independent collections of plot-level measurements, and resulting maps display land cover variation
in response to changes in climate, disturbance, and management. The maps, which will be updated annually
at the end of each year, provide exciting opportunities to expand and improve rangeland conservation,
monitoring, and management. The data open new doors for scientific investigation at an unprecedented
blend of temporal fidelity, spatial resolution, and geographic scale.

}, keywords = {cloud computing, conservation, Google Earth Engine, grazing, land cover, landsat, machine learning, rangeland, remote sensing, Time series, wildfire}, doi = {doi.org/10.1002/ecs2.2430}, url = {files/bibliography/18-021.pdf}, author = {Matthew O. Jones and Brady W. Allred and David E. Naugle and J. Maestas and Donnelly, Patrick and Loretta Metz and Jason W. Karl and Smith, Rob and Brandon T Bestelmeyer and Chad S. Boyd and Kerby, Jay D. and McIver, James D.} } @article {JRN55005, title = {Digital soil mapping for predicting and managing fire in rangelands}, journal = {Fire Ecology}, year = {2018}, month = {12/2018}, pages = {1-12}, chapter = {1}, abstract = {

Background: Soil properties have important effects on fire occurrence and spread, but soils are often overlooked in
fire prediction models. Quantifying soil-fire linkages is limited by information in conventional soil maps, but digital
soil mapping products (e.g., detailed soil property maps) could improve both wildfire prediction models and post-fire
management decisions.
Results: Of our estimated 3.7 Mkm2 of rangeland in the continental US and Alaska, an average of 38 000 km2 burned
per year between 2008 and 2017. To highlight the role of soils in fire ecology, we present 1) a conceptual framework
explaining why soil information can be useful for fire models, 2) a comprehensive suite of literature examples that used
soil property information in traditional soil survey for predicting wildfire, and 3) specific examples of how more detailed
soil information can be applied for pre- and post-fire decisions.
Conclusions: Digital soil mapping can improve fire prediction models and inform post-fire management decisions

}, keywords = {digital soil mapping, fire effects, grasslands, shrublands, soil moisture, spatial modeling, wildfire}, doi = {doi.org/10.1186/s42408-018-0018-4}, url = {files/bibliography/19-006.pdf}, author = {Matthew Levi and Brandon T Bestelmeyer} } @article {49982, title = {Cross-system comparisons elucidate disturbance complexities and generalities}, journal = {Ecosphere}, volume = {2}, year = {2011}, month = {07/2011}, pages = {Article 81}, chapter = {1}, abstract = {Given that ecological effects of disturbance have been extensively studied in many ecosystems, it is surprising that few quantitative syntheses across diverse ecosystems have been conducted. Multi-system studies tend to be qualitative because they focus on disturbance types that are difficult to measure in an ecologically relevant way. In addition, synthesis of existing studies across systems or disturbance types is challenging because sufficient information needed for analysis is not easily available. Theoretical advances and improved predictions can be advanced by generalizations obtained from synthesis activities that include multiple sites, ecosystems, and disturbance events. Building on existing research, we present a conceptual framework and an operational analog to integrate this rich body of knowledge and to promote quantitative comparisons of disturbance effects across different types of ecosystems and disturbances. This framework recognizes individual disturbance events that consist of three quantifiable components: (1) environmental drivers, (2) initial system properties, and (3) physical and biological mechanisms of effect, such as deposition, compaction, and combustion. These components result in biotic and abiotic legacies that can interact with subsequent drivers and successional processes to influence system response. Through time, a coarse-scale quasi-equilibrial state can be reached where variation in drivers interacting with biotic processes and feedbacks internal to the system results in variability in dynamics. At any time, a driver of sufficient magnitude can push the system beyond its realm of natural variability to initiate a new kind of event. We use long-term data from diverse terrestrial ecosystems to illustrate how our approach can facilitate cross-system comparisons, and provide new insights to the role of disturbance in ecological systems. We also provide key disturbance characteristics and measurements needed to promote future quantitative comparisons across ecosystems.}, keywords = {disburbance event, disturbance type, drought, ecological theory, global change, hurricane legacies, overgrazing, thresholds, wildfire}, doi = {10.1890/es11-00115.1}, url = {/files/bibliography/11-015.pdf}, author = {Debra C. Peters and Ariel E. Lugo and F.S. Chapin III and Steward T.A. Pickett and Danielle Duni and Rocha, Adrian V. and F. J. Swanson and C. Laney and J. W. Jones (eds.)} }