Fire-grazing interaction: An ecological process

The ecological interactions between fire and grazing are widespread throughout fire-prone ecosystems. It is an ecological process that drives ecosystem structure and function, influencing broad, landscape level events to fine, localized processes. The fire-grazing interaction occurs when spatially distinct fires are present across a landscape and move through time, forcing grazing animals to choose among burned and unburned areas. The mechanisms of this interaction occur at multiple levels. At broad, landscape level scales, animals are attracted to and focus their grazing on recently burned areas. This attraction decreases as the amount of time since fire progresses. For bison (Bison bison) and cattle (Bos taurus) in tallgrass prairie of North America, the influence of time since fire supersedes most landscape features (e.g., distance to water, topography, etc.), indicative of the overall strength of the fire-grazing interaction.Mechanisms of the fire-grazing interaction are also present at finer, patch level scales. Forage quality and quantity differences between burned areas are responsible for preferential grazing of burned areas. Forage quality is inversely related to time since fire, so that recently burned areas are greatest in quality, while areas with greater time since fire are significantly lower. The opposite relationship is present with forage quantity, with burned areas having small amounts of quantity compared to areas with greater time since fire. Tradeoffs between forage quality and quantity emerge and influence the attraction of grazing animals to burned areas.The light environment at finer, plot level scales is also determined by the amount of time since fire within the fire-grazing interaction. The preferential grazing of recently burned areas maintain high light environments throughout the growing season. These areas differ from that of fire alone, where light limitations quickly return after fire. The high light environment allows for increased photosynthetic rate of dominant prairie plants, but at the expense of low leaf area through continual preferential grazing by animals. As a result, total carbon gain by plants is reduced compared to areas with greater time since fire. These results feedback and affect forage quality and quantity

Ungulate preference for burned patches reveals strength of fire–grazing interaction

The interactions between fire and grazing are widespread throughout fire-dependent landscapes. The utilization of burned areas by grazing animals establishes the fire–grazing interaction, but the preference for recently burned areas relative to other influences (water, topography, etc.) is unknown. In this study, we determine the strength of the fire–grazing interaction by quantifying the influence of fire on ungulate site selection. We compare the preference for recently burned patches relative to the influence of other environmental factors that contribute to site selection; compare that preference between native and introduced ungulates; test relationships between area burned and herbivore preference; and determine forage quality and quantity as mechanisms of site selection. We used two large ungulate species at two grassland locations within the southern Great Plains, USA. At each location, spatially distinct patches were burned within larger areas through time, allowing animals to select among burned and unburned areas. Using fine scale ungulate location data, we estimated resource selection functions to examine environmental factors in site selection. Ungulates preferred recently burned areas and avoided areas with greater time since fire, regardless of the size of landscape, herbivore species, or proportion of area burned. Forage quality was inversely related to time since fire, while forage quantity was positively related. We show that fire is an important component of large ungulate behavior with a strong influence on site selection that drives the fire–grazing interaction. This interaction is an ecosystem process that supersedes fire and grazing as separate factors, shaping grassland landscapes. Inclusion of the fire–grazing interaction into ecological studies and conservation practices of fire-prone systems will aid in better understanding and managing these systems

Beyond Inventories: Emergence of a New Era in Rangeland Monitoring

In the absence of technology-driven monitoring platforms, US rangeland policies, management practices, and outcome assessments have been primarily informed by the extrapolation of local information from national-scale rangeland inventories. A persistent monitoring gap between plot-level inventories and the scale at which rangeland assessments are conducted has required decision makers to fill data gaps with statistical extrapolations or assumptions of homogeneity and equilibrium. This gap is now being bridged with spatially comprehensive, annual, rangeland monitoring data across all western US rangelands to as- sess vegetation conditions at a resolution appropriate to inform cross-scale assessments and decisions. In this paper, 20-yr trends in plant functional type cover are presented, confirming two widespread national rangeland resource concerns: widespread increases in annual grass cover and tree cover. Rangeland vegetation monitoring is now available to inform national to regional policies and provide essential data at the scales at which decisions are made and implemented

Challenges of Brush Management Treatment Effectiveness in Southern Great Plains, United States

Woodland expansion is a global challenge documented under varying degrees of disturbance, climate, and land ownership patterns. In North American rangelands, mechanical and chemical brush management practices and prescribed fire are frequently promoted by agencies and used by private landowners to reduce woody plant cover. We assess the distribution of agency-supported cost sharing of brush management (2000−2017) in the southern Great Plains, United States, and evaluate the longevity of treatment application. We test the general expectation that the current brush management paradigm in the southern Great Plains reduces woody plants and conserves rangeland resources at broad scales. This study represents the most comprehensive assessment of treatment longevity following brush management in the southern Great Plains by linking confidential private lands management data to a national inventory program (US Department of Agriculture Natural Resources Conservation Service National Resources Inventory). We observed regional differences in the types of brush management techniques used in cost-sharing programs throughout the study area. Mechanical brush management was the most common practice cost shared in Texas, while a mixture of mechanical and chemical application was most common in Oklahoma. Prescribed fire was most common in Kansas with some areas receiving chemical treatment. Our analysis showed brush management, as implemented, did not reduce tree cover long term and minimally reduced shrub cover. Evidence to support the current brush management paradigm only existed at local site-level scales of analysis (40- to 50-acre area), but treatment effectiveness was short-lived. At regional scales, observed changes in woody plant cover showed little to no overall net reduction from 2000 to 2017. These findings bring into question the philosophy of the current brush management paradigm, its implementation as the default rangeland conservation practice, and its prioritization over alternative practices that prevent new woody plant establishment and enhance resilience of rangelands in the southern Great Plains region

Spatial Imaging and Screening for Regime Shifts

Screening is a strategy for detecting undesirable change prior to manifestation of symptoms or adverse effects. Although the well-recognized utility of screening makes it commonplace in medicine, it has yet to be implemented in ecosystem management. Ecosystem management is in an era of diagnosis and treatment of undesirable change, and as a result, remains more reactive than proactive and unable to effectively deal with today’s plethora of non-stationary conditions. In this paper, we introduce spatial imaging-based screening to ecology. We link advancements in spatial resilience theory, data, and technological and computational capabilities and power to detect regime shifts (i.e., vegetation state transitions) that are known to be detrimental to human well-being and ecosystem service delivery. With a state-of-the-art landcover dataset and freely available, cloud-based, geospatial computing platform, we screen for spatial signals of the three most iconic vegetation transitions studied in western USA rangelands: (1) erosion and desertification; (2) woody encroachment; and (3) annual exotic grass invasion. For a series of locations that differ in ecological complexity and geographic extent, we answer the following questions: (1) Which regime shift is expected or of greatest concern? (2) Can we detect a signal associated with the expected regime shift? (3) If detected, is the signal transient or persistent over time? (4) If detected and persistent, is the transition signal stationary or non-stationary over time? (5) What other signals do we detect? Our approach reveals a powerful and flexible methodology, whereby professionals can use spatial imaging to verify the occurrence of alternative vegetation regimes, image the spatial boundaries separating regimes, track the magnitude and direction of regime shift signals, differentiate persistent and stationary transition signals that warrant continued screening from more concerning persistent and non-stationary transition signals, and leverage disciplinary strength and resources for more targeted diagnostic testing (e.g., inventory and monitoring) and treatment (e.g., management) of regime shifts. While the rapid screening approach used here can continue to be implemented and refined for rangelands, it has broader implications and can be adapted to other ecological systems to revolutionize the information space needed to better manage critical transitions in nature

Bison movements change with weather: Implications for their continued conservation in the Anthropocene

Animal movement patterns are affected by complex interactions between biotic and abiotic landscape conditions, and these patterns are being altered by weather variability associated with a changing climate. Some animals, like the American plains bison (Bison bison L.; hereafter, plains bison), are considered keystone species, thus their response to weather variability may alter ecosystem structure and biodiversity patterns. Many movement studies of plains bison and other ungulates have focused on point-pattern analyses (e.g., resource-selection) that have provided information about where these animals move, but information about when or why these animals move is limited. For example, information surrounding the influence of weather on plains bison movement in response to weather is limited but has important implications for their conservation in a changing climate. To explore how movement distance is affected by weather patterns and drought, we utilized 12-min GPS data from two of the largest plains bison herds in North America to model their response to weather and drought parameters using generalized additive mixed models. Distance moved was best predicted by air temperature, wind speed, and rainfall. However, air temperature best explained the variation in distance moved compared to any other single parameter we measured, predicting a 48% decrease in movement rates above 28°C. Moreover, severe drought (as indicated by 25-cm depth soil moisture) better predicted movement distance than moderate drought. The strong influence of weather and drought on plains bison movements observed in our study suggest that shifting climate and weather will likely affect plains bison movement patterns, further complicating conservation efforts for this wide-ranging keystone species. Moreover, changes in plains bison movement patterns may have cascading effects for grassland ecosystem structure, function, and biodiversity. Plains bison and grassland conservation efforts need to be proactive and adaptive when considering the implications of a changing climate on bison movement patterns

Herbaceous production lost to tree encroachment in United States rangelands

1. Rangelands of the United States provide ecosystem services that benefit society and rural economies. Native tree encroachment is often overlooked as a primary threat to rangelands due to the slow pace of tree cover expansion and the positive public perception of trees. Still, tree encroachment fragments these landscapes and reduces herbaceous production, thereby threatening habitat quality for grassland wildlife and the economic sustainability of animal agriculture. 2. Recent innovations in satellite remote sensing permit the tracking of tree encroachment and the corresponding impact on herbaceous production. We analysed tree cover change and herbaceous production across the western United States from 1990 to 2019. 3. We show that tree encroachment is widespread in US rangelands; absolute tree cover has increased by 50% (77,323 km2) over 30 years, with more than 25% (684,852 km2) of US rangeland area experiencing tree cover expansion. Since 1990, 302 ± 30 Tg of herbaceous biomass have been lost. Accounting for variability in livestock biomass utilization and forage value reveals that this lost production is valued at between $4.1–$ 5.6 billion US dollars. 4. Synthesis and applications. The magnitude of impact of tree encroachment on rangeland loss is similar to conversion to cropland, another well-known and primary mechanism of rangeland loss in the US Prioritizing conservation efforts to prevent tree encroachment can bolster ecosystem and economic sustainability, particularly among privately-owned lands threatened by land-use conversion

Terrestrial primary production for the conterminous United States derived from Landsat 30 m and MODIS 250 m

Terrestrial primary production is a fundamental ecological process and a crucial component in understanding the flow of energy through trophic levels. The global MODIS gross primary production (GPP) and net primary production (NPP) products (MOD17) are widely used for monitoring GPP and NPP at coarse resolutions across broad spatial extents. The coarse input datasets and global biome‐level parameters, however, are well‐known limitations to the applicability of the MOD17 product at finer scales. We addressed these limitations and created two improved products for the conterminous United States (CONUS) that capture the spatiotemporal variability in terrestrial production. The MOD17 algorithm was utilized with medium resolution land cover classifications and improved meteorological data specific to CONUS in order to produce: (a) Landsat derived 16‐day GPP and annual NPP at 30 m resolution from 1986 to 2016 (GPPL30 and NPPL30, respectively); and (b) MODIS derived 8‐day GPP and annual NPP at 250 m resolution from 2001 to 2016 (GPPM250 and NPPM250 respectively). Biome‐specific input parameters were optimized based on eddy covariance flux tower‐derived GPP data from the FLUXNET2015 database. We evaluated GPPL30 and GPPM250 products against the standard MODIS GPP product utilizing a select subset of representative flux tower sites, and found improvement across all land cover classes except croplands. We also found consistent interannual variability and trends across NPPL30, NPPM250, and the standard MODIS NPP product. We highlight the application potential of the production products, demonstrating their improved capacity for monitoring terrestrial production at higher levels of spatial detail across broad spatiotemporal scales

Low-Tech Riparian and Wet Meadow Restoration Increases Vegetation Productivity and Resilience Across Semiarid Rangelands

Restoration of riparian and wet meadow ecosystems in semiarid rangelands of the western United States is a high priority given their ecological and hydrological importance in the region. However, traditional restoration approaches are often intensive and costly, limiting the extent over which they can be applied. Practitioners are increasingly trying new restoration techniques that are more cost‐effective, less intensive, and can more practically scale up to the scope of degradation. Unfortunately, practitioners typically lack resources to undertake outcome‐based evaluations necessary to judge the efficacy of these techniques. In this study, we use freely available, satellite remote sensing to explore changes in vegetation productivity (normalized difference vegetation index) of three distinct, low‐tech, riparian and wet meadow restoration projects. Case studies are presented that range in geographic location (Colorado, Oregon, and Nevada), restoration practice (Zeedyk structures, beaver dam analogs, and grazing management), and time since implementation. Restoration practices resulted in increased vegetation productivity of up to 25% and increased annual persistence of productive vegetation. Improvements in productivity with time since restoration suggest that elevated resilience may further enhance wildlife habitat and increase forage production. Long‐term, documented outcomes of conservation are rare; we hope our findings empower practitioners to further monitor and explore the use of low‐tech methods for restoration of ecohydrologic processes at meaningful spatial scales

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes