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Woody plant encroachment into rangeland ecosystems is a widespread and often unwelcomed circumstance affecting rangeland management decisions worldwide. In the rangeland management profession, varying philosophies have been employed in the management of woody plant encroachment. Following World War II, total eradication of woody plant cover was commonly practiced, eventually giving way to a mosaic approach that benefits livestock, wildlife, and recreational objectives, with cover increasing or even stabilizing in many areas. Cultural practices such as land fragmentation, lifestyles not dependent on agricultural income, and shifts in herbivory from predominately browsers to grazers may also be contributing factors. Modern image analysis technologies, such as object-oriented feature extraction and patch metric analyses, can shed light on past paradigm shifts through spectral and textural assessment of modern and historical aerial photography. In this study, woody plant cover and patch metrics were analyzed for a period spanning from 1938 to 1940 through 2018 in the Bennett and Sulphur Creek watersheds of the Lampasas Cut Plain of Central Texas. Object-based feature extraction was used to calculate woody plant cover, and Fragstats was used for landscape patch metrics. Total woody cover was compared with past stewardship paradigms. There was a net decrease of total woody plant cover from 1938 to 1940 through 2018, with variation in between as management paradigms shifted. A pattern of decline, regrowth, and stabilization, like that observed in other research, was noticed for the Bennett Creek watersheds but was not apparent in Sulfur Creek. Patch size/shape varied as well, but fractal patch complexity was relatively stable through time. Raster algebra analysis showed that

Large wildfires have increased in western US rangelands over the last three decades. There is limited information on the impacts of wildfires with different severities on the vegetation in these rangelands. This study assessed the impacts of large wildfires on rangeland fractional cover including annual forbs and grasses (AFG), perennial forbs and grasses (PFG), shrubs (SHR) and trees (TREE) across the western US, and explored relationships between changes in fractional cover and prefire soil moisture conditions. The Expectation Maximization (EM) algorithm was used to group wildfires into nine clusters based on the prefire rangeland fractional cover extracted from the Rangeland Analysis Platform. The Standardized Precipitation Evapotranspiration Index (SPEI) with various lag scales from the Gridded Surface Meteorological (GRIDMET) dataset was used to represent antecedent soil moisture conditions. The results showed generally that fractional cover decreased most for AFG and PFG during the fire year, one year postfire for SHR, and two years postfire for TREE. High severity wildfires led to the greatest decrease in cover for all plant functional types, while low severity wildfires caused the least decrease in the functional type cover in most cases, though some variations existed. Furthermore, the impacts of wildfires on vegetation cover were greater in woody (SHR and TREE) types than in herbaceous (AFG and PFG) types. Significant negative correlation existed between percent changes in AFG and PFG cover and SPEI indicating higher prefire soil moisture conditions likely increased fine fuel loads and led to a larger decrease in AFG and PFG cover following wildfires. Significant positive correlation existed between percent changes in SHR and TREE cover and SPEI indicating drier prefire conditions resulted in larger decreases in SHR and TREE cover following wildfires. These findings help better understand the impacts of wildfires on rangelands and provide insights for rangeland management.

Terrain can influence vegetation composition, diversity, and biogeochemical cycling in grassland ecosystems. Solar radiation, soil temperature, and moisture distribution are dependent on terrain, which, in turn, can affect plant community structure, rate of litter mass decomposition, and carbon, nitrogen, and phosphorus release. A litter decomposition experiment was conducted over 12 mo at a site representing typical steppe grasslands to better understand the effects of terrain on biogeochemical cycling. The study site had both northeast (shaded) and southwest (sunny) facing aspects with each aspect having three slopes: 15°, 30°, 45°. Litterbags were used for collection of plant community litter from each location. The results indicated that slope and aspect both have significant effects on decomposition rate of litter mass and release rate of C, N, and P. The most rapid decomposition rate of litter mass was on 45° sunny slopes (k value 1.82 × 10‒3 d−1). The most rapid release of C was on 30° shaded slopes with release rate of 4.54 g C yr‒1. The release rate of N decreased with increasing slope steepness but was more rapid on shaded compared with sunny slopes. The most rapid release of P (10.51 mg P yr‒1) occurred on 45° shaded slopes. The total effects of solar radiation and soil temperature on litter mass decomposition were larger, with 0.91 and 0.93, respectively. Soil temperature, litter functional diversity, and initial C/N had positive effects on the litter C release. The release of litter N was mainly promoted by soil temperature. Soil moisture appeared to promote the release of litter P. Overall, terrain influenced litter mass decomposition and C, N, and P release by its effect on the distribution of solar radiation, soil temperature and moisture, and through modification of functional diversity, initial C/N ratios, and water content of litter in typical steppe.

The daily nutritional balance of free-ranging cattle is the net result of intake from available forage biomass and nutritive value weighed against the nutritional requirements of the animal. Plant phenology influences nutritive value. Plant phenology is dictated by time of year and an accumulation of photosynthetically active days. Growing degree day (GDD) is a concept that quantifies this relationship and has been used to predict nutritive value in perennial range grasses. GDD could be substituted for chemical analysis to inform grazing animal nutritional monitoring efforts. We hypothesized that in C4 grass-dominated rangelands, a cumulative GDD calculation would correlate with diet crude protein (CP) predictions obtained by fecal near infrared spectroscopy (FNIRS) from free-ranging cattle. Therefore, the objectives of our research were to evaluate the effectiveness of GDD to predict FNIRS-derived determinations of grazing cattle diet CP in 1) two groups of three individual animals grazing a small native pasture and 2) large commercial-scale herds grazing expansive rangelands. For the first objective, cumulative GDD and FNIRS-predicted diet CP were strongly correlated (r2 = 0.76; P

On the Ground • Knowledge derived from grazing lands assessment programs provides the foundation for the development of conservation policy and informs local, regional, and national entities on benefits associated with investments in conservation and land management. • Conservation Effects Assessment Project – Grazing Lands provides a baseline for informing decision-makers at all levels of the impacts and potential values of conservation practice application. • Comprehensive assessment at multiple scales provides opportunities for understanding the impacts of land management and conservation programs on approximately 600 million acres of grazing lands in the United States.

On the Ground • Ashe juniper invasion is a widespread issue on Texas and Oklahoma rangelands. Increased densities of Ashe juniper trees increase the risk of wildfire and decrease herbaceous forage production. • Browsing animals, such as goats, are one tool that can be used to effectively reduce juniper fuel. • In order to estimate the available biomass, allometric measurements were compared against three-dimensional Light Detection and Ranging (LiDAR) scans of whole juniper plants. • Accurate measurements of standing juniper browse and fuel load can be vital information for decision support of grazing management and wildland fire mitigation, especially in the ever-growing wildland-urban interface.

We modified the grazing module of the APEX simulation model to allow for selective grazing of plant species and dietary-specific excretion of urine and feces. To determine the sensitivity of these changes on nutrient flows, vegetation responses, and grazer diet, we simulated the conditions of a 20-year historic grazing treatment conducted in Kansas, United States of America. Simulated scenarios were a factorial of 2 grazer types (naive and selective) and 3 stocking densities (high, medium, low). Naive grazers represented model behavior before our modifications. Selective grazers selected forage species based on crude protein content, digestibility, and anti-quality factors. We found that the new selective grazing algorithm resulted in a change in grazer diet quality, nutrient excretion, and standing vegetation residue. The difference between selective and naive grazers varied over the course of the grazing season, with greatest differences occurring early in the year. C3 grasses were generally preferred in the spring, after which time C4 grasses were preferred until autumn. Simulated diet quality was relatively insensitive to stocking density, although stocking density did impact standing vegetation residue. Urinary and fecal N excretion varied seasonally and interacted with weather-induced plant water stress. The revised model’s ability to simulate differences in vegetation residue, diet quality, and nutrient excretion provide necessary building blocks to use or improve the model for the simulation of animal production, sediment erosion, water runoff, N and P runoff, and soil C accretion. The model’s performance might be improved by tracking individual plant components (e.g. leaves, stems, seeds, mast), albeit at the cost of greater input requirements.

We used a fecal near infrared spectroscopy (FNIRS) calibration for cattle diet crude protein (CP) to evaluate the efficacy of growing degree day (GDD) as a remotely-sensed method to monitor grazing animal nutrition. Composite fecal samples representing a herd of 24 cross bred beef cows grazing native range pastures in southwest Texas were collected along with GDD and precipitation data from April 2018 to September 2019. Regression analyses were performed to determine relationships between FNIRS-predicted diet CP and GDD within year and growing season. In 2018, FNIRS-predicted diet CP ranged from a minimum of 7.05% in August to a maximum of 9.69% in July. 2018 cumulative precipitation was 28% and 94% of the 20-year average for January-April and May-August, respectively. In 2019, FNIRS-predicted diet CP ranged from a minimum of 6.85% in September to a maximum of 12.01% in May. 2019 cumulative precipitation was 74% and 102% of the 20-year average for January-April and May-August, respectively. There were no significant (P > 0.1) simple linear relationships identified between FNIRS-predicted diet CP and GDD. There were, however, cubic exponential relationships identified in both 2018 (y = 7E-10x3 - 5E-06x2 + 0.0106x + 2.9603; R² = 0.7261; P = 0.1271) and 2019 (y = 1E-09x3 - 6E-06x2 + 0.0062x + 9.2923; R² = 0.7659; P = 0.0493). As expected, perennial range grass phenology/nutritive value (i.e. cattle diet CP) was influenced by accumulation of heat units (i.e. GDD) and precipitation. Although FNIRS is an established non-invasive method to monitor grazing animal nutrition, a remotely-sensed method to accomplish this task, such as GDD, has the potential to facilitate large-scale monitoring of grazing animal nutritional status. Our results indicate that complementary research using data from multiple locations and for more than 2 years is needed to fully evaluate these techniques.

Under the combined effect of stocking rate and grazing season, it is very significant to ascertain whether there is a quantitative relationship between plant community characteristics, chemical composition of forage, and grazing behaviors of Tibetan sheep to better utilize native pasture in the northeast region of the Qinghai&ndash, Tibetan Plateau (QTP). The two consecutive year observation experiments on Tibetan sheep&rsquo, s grazing behavior were conducted to evaluate the above-stated relationships between stocking rates of 8 sheep/ha and 16 sheep/ha stocking rates in the both the warm and cold seasons. The results demonstrated that at 8 sheep/ha or in the warm season, due to better forage quality, Tibetan sheep had higher herbage mass, forage crude protein (CP) concentration, CP intake, dry matter intake (DMI), and interval between feed boluses and total number of steps, as well as lower fiber concentration than that at 16 sheep/ha or in the cold season. Diurnal intake rate and walking velocity while intaking increased as both average daylight ambient temperature and relative humidity rose. Using the CP concentration, acid detergent fiber (ADF) concentration, neutral detergent fiber (NDF) concentration, and forage metabolic energy (ME) to predict grazing behavior yielded the best fit equation for Tibetan sheep. For local herdsmen to sustainably use the alpine meadow, 8 sheep/ha in the warm season should be considered as the better grazing condition for preventing grassland degradation.

The conservation and management of military training lands has long evolved around the unique criteria for maintaining a viable fighting force. In lieu of this primary mission, landscapes have often experienced accelerated degradation and loss of structural and functional capabilities for providing desired ecosystem services (including the basic training mission). In an effort to aid military land managers as well as anyone who makes and implements decisions for natural resource management; we support an innovative approach towards the integration of evidence and the application of diagnosis and prognosis for the decision-making process through the use of Bayesian Networks. Illustrated below is an example for utilizing Bayesian Networks in the decision support process. We utilized data and experience from ongoing efforts at the Fort Hood Military Installation to build the initial network; then integrate expert input from authors and engineers in propagating the node relationships. Through this approach, we demonstrate how military land managers can integrate varying streams of evidence, including empirical, model generated or expert opinion, into a network for decision support. The example below is developed based upon land management issues within the U.S. Army, but the process can be adapted and implemented across most all ecosystems under some form of land management.

When field research is cost- or time-prohibitive, models can inform decision-makers regarding the impact of agricultural policy on production and the environment, but process-based models that simulate animal-plant-soil interaction and ecosystem services in grazing lands are rare. In the U.S.A., APEX (Agricultural Policy/Environmental eXtender) is a model commonly used to inform policy on cropland, but its ability to simulate grazinglands was less robust. Therefore, we enhanced the APEX model’s plant growth module to improve its utility on grazing lands. Improvements addressed allocation of new biomass, response to water stress, competition for soil water, and regrowth of herbaceous perennials. Sensitivity analysis demonstrated that simulated biomass responded to changes in precipitation through adjustments to both total biomass and distribution of biomass aboveground and belowground. A deep-rooted species generally outperformed a shallow-rooted species but the relative advantage was greatest when precipitation was historically low. A 10-year dataset of peak biomass collected in central Kansas, U.S.A., was divided among 5 species and species groups and was used for calibration and validation. When the mass of all species was combined in the validation dataset, the percent bias was −2%, Willmott’s Dr was 0.79, and r2 was 0.84. When biomass production of individual species was analyzed, the model did not perform as well, with the percent bias ranging from −36 to 29%, Willmott’s Dr ranging from 0.58 to 0.71, and r2 from 0.25 to 0.67. Because grazing lands often have a rich species diversity, the improvements made APEX better-suited to modeling such heterogeneous landscapes. However, simulating biomass of individual species, rather than the sum of all species, is an area that still needs improvement. Further testing at additional sites to calibrate single- and multiple-species growth and identify any spatial trends in model performance will also be beneficial.

On the Ground • Opportunities for rangeland inventory and monitoring have been transformed by innovations in both indicator and methods standardization and new technologies. • These technologies make it easier to collect, store, access, and interpret inventory and monitoring data. • The Land-Potential Knowledge System (LandPKS) platform and apps help users with little or no soils knowledge to describe their soil, and for those with little botanical knowledge to monitor key shifts in the relative dominance of plant structural groups. • The system also allows users to easily share and compare their data with others.

We review evidence of Holocene climate, vegetation, and cultural changes in Mongolia and critically examine evidence that Mongolia’s steppes are at the brink of ecological and cultural tipping points in the Anthropocene. Until 5,000 YBP there is no evidence of lasting human influences on ecosystems, but after this time, changes in vegetation and soil physical properties signal domestic livestock grazing impacts on steppe ecosystems. Contemporary (1991–2015) literature and region by region analysis of climate, livestock, remote-sensing and human population data reveal two potential tipping points. Temperatures warmed across the 5 regions. Since 1991, livestock densities and forage use increased in most regions, the spatial distribution of grazing pressure is more heterogeneous, and variability increased in stocking densities, forage use and forage production in all or most regions. Substantial plant species shifts and losses occurred in the mountain and forest steppe regions. Although a large proportion of Mongolia’s rangelands are altered from their ecological potential, few have crossed an irreversible threshold of ecological change. Rangelands in Mongolia’s Khangai, northern and central regions may be approaching an ecological tipping point if grazing pressure is not reduced. After 1991, herder populations initially rose and then decreased significantly across most regions. If demographic and social trends contribute to loss of herding knowledge and identity, a cultural tipping point could occur. We describe four potential future scenarios that could unfold if these tipping points are reached, hypothesize feedbacks between ecological and cultural thresholds, and discuss implications for policy and management.

Bovine babesiosis, a highly fatal tick-borne disease of cattle, was eliminated from the United States in the last century through tick eradication programs against 2 species of cattle fever ticks. The threat to the U.S. cattle industry continues through tick introductions from Mexico. The standard method of detecting Cattle Fever Ticks [Rhipicephalus (B.) annulatus and R. (B.) microplus] in the state-federal tick eradication program is physical examination of restrained cattle to find attached ticks. New methods of detecting tick-infested cattle could improve reliability and reduce animal stress. The objective of this study was to determine whether changes in fecal chemistry induced by tick infestation was detectable using near-infrared reflectance spectroscopy (NIRS). Fecal samples were collected daily from 6 stanchioned Bos taurus yearling heifers (initial mean weight 163.3 kg +/- 4.7 kg) at the USDA Cattle Fever Tick Research Laboratory, Edinburg, TX, before, during, and after an infestation of 5000 R. (B.) microplus larvae. Cluster analyses were conducted using GRAMS IQ for NIR spectra in the 576–1126 nm range to test for fecal chemistry changes different from pre-infestation condition, and coincident with the biological phases of the tick infestation. The first three factors of spectral variation accounted for 87.87% of spectral variation among all samples. Factors 1, 2, and 3 had F-Ratios for the Reduced Eigenvalues of 941.59, 387.44, and 221.79, respectively. Three-dimensional analysis for these 3 factors shows shifts in sample clusters away from pre-infestation and coincident with progressive tick blood-feeding and post-infestation recovery. We conclude that fecal NIRS may provide a tool for detection of tick-infested cattle; however, further testing is needed to determine the sensitivity of detection on cattle with varying levels of tick burden, and a protocol developed and evaluated for fecal sampling under field conditions

The Mongolian Rangelands and Resilience (MOR2) Project sought to understand how climate and socio-economic changes affect social-ecological systems in rural Mongolia, and how herder responses feedback to influence ecological-social conditions. Led by Colorado State University, the interdisciplinary team included collaborating scientists from one US and nine Mongolian research institutions and NGOs. As such, MOR2 spanned boundaries among disciplines, cultures, and sectors of society. Conceptual and analytical integration across disciplines proved challenging. However, unforeseen and novel interdisciplinary and cross-sectoral collaborations emerged focused on herder observations of environmental changes, participatory scenario building, science capacity building, and community and policymaker engagement. The MOR2 team’s commitment to continual reflection and adaptation built trust and sustained collaborative relationships that led to important scientific results and a wide variety of broader impacts.

Woody plant encroachment—the conversion of grasslands to woodlands—is among the greatest challenges faced by rangelands worldwide. Yet this phenomenon is poorly understood, and complex land use dynamics make interpreting the timing and extent of land cover changes a global challenge. For many regions, the true degree and rate of historical change in woody cover and cropland remain unknown. We quantify these processes and explore the effects of prior cultivation on woody plant distribution. In the Lampasas Cut Plain, USA, we measured rangeland transformation using digital classification of aerial imagery 1937–2012. Our study is the first to use data of such high spatial and temporal resolution to address this question at this scale. We also provide some of the first documentation of dramatic regional cropland abandonment. Although total woody cover remained almost unchanged (1937: 28%, 2012: 27 %), woody cover underwent a major redistribution across the landscape. Formerly open areas attained much greater levels of woody cover, and previously wooded areas lost woody cover. As cropland area declined by 78 %, woody plants invaded former croplands more slowly than the rangeland portions of the area (0.1 % year−1 vs. 0.3 % year−1, respectively). These findings conflict with widely held assumptions and suggest that woody plant encroachment is more nuanced than often recognized. Multiple dynamics and past conditions interact in complex ways to produce landscape change. Because perceptions of encroachment determine how we respond to this challenge, great care should be taken in interpreting observed woody plant encroachment of the world’s rangelands.

Despite their size, small farm ponds are important features in many landscapes. Yet hydrographical databases often fail to capture these ponds, and their impacts on watershed processes remain unclear. For a 230-km2 portion of central Texas, United States (U.S.), we created a historical inventory of ponds and quantified the accuracy of automated detection methods under varying drought conditions. In addition, we documented pond dredging/enlargement events and identified sites that had been abandoned. We also analyzed sediment cores from downstream reservoirs to track changes in watershed sediment transport. Over 75 years, pond densities increased more than 350% — to among the highest documented in the U.S. — and the ability of automated methods to detect these ponds was highly dependent on drought severity (R2 = 0.96). Approximately 5% of ponds present in the 1950s were no longer present in 2012, while 33% were dredged between 1937 and 2012. Downstream reservoir sedimentation has decreased by an average of 55% as ponds have increased in number. These findings suggest that small ponds and the maintenance of trapping efficiency have large-scale impacts on sediment dynamics. Accurately accounting for these storage effects is vital to water resource planning efforts.

Weather and climate extremes have impacted forage conditions and lead to loss of animal production and livelihood of livestock-dependent communities in Kenya. Monitoring of forage conditions and developing a reliable early warning system can reduce the loss of livestock and improve the resilience. In order to enhance resilience of affected populations, through a collaboration of multiple agencies in Kenya and beyond, a dynamic web-based Predictive Livestock Early Warning System (PLEWS) decision support tool was developed. The system combines the water balance, PHYGROW (Phytomass Growth Model) simulation model and spatial analysis tools to generate current and a 6-monthly forecast of forage conditions. Although in its pilot phase, the tool holds potentials to provide decision support with anticipatory actions by communities, regional and national governments. By utilizing the output and engaging such pre-emptive interventions, emergencies can be prevented by promoting proactive decision-making conditioned on advance information of forage conditions. Timely actions based on advanced information can reduce potential impacts of extreme weather and climate events on livestock. The pro-active actions can reduce the losses and response costs associated with the impacts of weather, climate extremes and can improve food security of most vulnerable populations. Keywords: Early warning, Livestock, Community resilience, Drought, Livelihoods

Terracette landscapes are common on hilly rangelands in arid and semiarid regions. Terracette structure significantly modifies the hydrological and biogeochemical processes, resulting in striking spatial patterns in soil moisture, nutrient, and vegetation distribution. However, there is still no efficient and precise method for monitoring and analyzing terracettes formation and maintenance processes. Therefore, we investigated spatial patterns and vegetation cover of these landscapes via field sampling and unmanned aerial vehicle (UAV) methods on the Loess Plateau, China. The parameters considered included land-use patterns (grazed vs. un-grazed) and topography (aspect: north and south, slope: 0°, 15°, 30°, and 45°). We revealed structural characteristics of terracettes, evaluated the differences between two sampling methods and explored the potential formation and maintenance mechanisms of these landscapes. The results showed that: 1) terracettes only existed in the north-30°, north-45°, and south-45° areas of grazed plots, 2) terracettes density (terracettes basic unit number/m, TBU/m) and vegetation cover differed significantly among the land-use patterns and topographies, 3) vegetation cover increased and then decreased with increasing terracettes density, with an inflection point of ~0.78 TBU/m, up to a vegetation cover of ~70%. These results could have major implications on land-use policies and environmental conservation and socioecological sustainability practices of the Loess Plateau. Finally, UAV can be used to effectively and accurately monitor and analyze terracette landscapes, and have great potential for monitoring terracettes in future studies.

Near infrared spectroscopy (NIRS) was applied to determine faecal nitrogen and phosphorus using a temporo-spatially diverse dataset derived from multiple ruminant herbivore species (i.e. cattle, bison, deer, elk, goats, and sheep). Single-species NIRS calibrations have previously been developed to predict faecal constituents. Multi-species NIRS calibrations have previously been developed for herbivore faecal nitrogen but not for faecal phosphorus. Faecal samples representing a herd or flock composite were analysed via NIRS (400–2498nm). Calibration sets for faecal nitrogen and phosphorus were developed from: (1) all samples from all six species, (2) all cattle samples only, (3) all samples except those from bison, (4) all samples except those from deer, (5) all samples except those from elk, (6) all samples except those from goats, and (7) all samples except those from sheep. Validation sample sets included: (1) each of the individual species (predicted with a cattle only-derived calibration), and (2) each of the individual species (other than cattle) predicted with a multi-species calibration constructed from all cattle samples plus those samples from the remaining four species (i.e. ‘leave-one-out’). All multiple coefficient of determination (R2) values for faecal nitrogen calibrations were ≥0.97. Corresponding standard error of cross validation (SECV) values were ≤0.13. Validation simple coefficient of determination (r2) and standard error of prediction (SEP) of each alternate species using the cattle-derived calibration ranged from 0.76 to 0.84, and 0.28 to 0.5 respectively. Similar values for the sequential species leave-one-out validation for faecal nitrogen were 0.67 to 0.89, and 0.17 to 0.47 respectively. All R2 values for faecal phosphorus calibrations were ≥0.79; corresponding SECV were ≤0.14. Validation r2 and SEP of each alternate species using the cattle-derived phosphorus calibration were ≤0.63 and ≥0.13 respectively. Similar values for the sequential species leave-one-out validation were ≤0.66 and ≥0.22 respectively for faecal phosphorus. Multi-species faecal NIRS calibrations can be developed for monitoring applications in which determination of faecal nitrogen is appropriate, e.g. free-ranging herbivore nutrition, nitrogen deposition from animal faeces on rangelands with declining forage quality, or runoff from confined animal feeding operations. Similar calibrations for faecal phosphorus require additional research to ascertain their applicability.

Woody plant encroachment—the conversion of grasslands to woodlands—continues to transform rangelands worldwide, yet its causes and consequences remain poorly understood. Despite this being a coupled human–ecological phenomenon, research to date has tended toward ecological aspects of the issue. In this paper, we provide new insight into the long-term relationships between human demographics and woody plant cover at the landscape scale. We used time-series aerial imagery and historical census data to quantify changes in population, land ownership patterns, and woody cover between 1937 and 2012 in three different settings in central Texas, USA. Woody cover closely paralleled population in a semi-urban watershed (R2 = 0.81) and two separate clusters of rural watersheds (R2 = 0.88 and 0.93), despite exhibiting very different directional trends over time in each setting. Woody cover also closely tracked average farm size in each rural watershed cluster (R2 = 0.57 and 0.90). These results highlight a tight coupling between demographic trends and the extent of woody plant cover. Such human factors may explain a great deal of woody plant cover patterns in other global rangeland systems with similar historical contexts and serve as a predictive proxy of landscape trends. Accordingly, policy recommendations should consider these demographic factors, and future woody plant encroachment research should explicitly include human dimensions.

Mongolian rangelands have experienced warming temperatures and increasing livestock densities over the past 20 years. Remote sensing studies report widespread degradation, but there are no long-term field studies of vegetation responses to shifts in climate and stocking densities. In 2013, we resampled plots originally sampled in 1994–1995 in the desert-steppe, steppe and mountain-steppe, and analyzed changes in vegetation in relation to changes in climate, stocking densities and forage use. Summer temperatures significantly increased and stocking densities fluctuated in response to droughts followed by harsh winters. Total herbaceous biomass in 2013 was similar to (desert-steppe and steppe) or greater than (mountain-steppe) in 1995, and total foliar and herbaceous cover were unchanged since 1995 in all zones. In the mountain-steppe, functional type and species cover shifts were consistent with warming temperatures and increasing grazing pressure. All species richness and diversity indicators declined significantly in the mountain-steppe since 1995, as did richness in the steppe. Some Mongolian rangelands may be losing resilience due to interacting climate and grazing pressures, but our data suggest degradation observed at our study sites is reversible. Mountain-steppe systems appear more vulnerable to grazing- and climate-induced vegetation change than steppe and desert-steppe.

This article analyses the level of integration in 10 cattle markets in Mali. The results indicate a limited interdependence among markets where, in majority of cases, more than 70 per cent of price variation is due to own-price shocks. However, the Segou market exhibited a high level of interaction with other markets, behaving mostly as a price information receiver. Some markets behaved as sources of price information, however, without taking a clear price leadership role. This low level of market integration may be attributed to limited access to livestock markets and timely price information.

Despite tremendous advancements in the livestock sector, additional opportunities exist to improve even further livestock production around the globe. Forecasting is not an exact science and it relies heavily on past and current knowledge. Improvements in the nutritional sciences (both human and animal) include a better understanding of agents that cause deterioration of human health, improving the quality of animal products, applying effective fetal programming, developing new feeds and feeding strategies, and revisiting longstanding technologies. Improvements in the understanding of the rumen microbiome will enable scientists to increase the fermentation efficiency and, hopefully, select microbial species of greater interest. Improvements in remote sensing and ground-based instrumentation, telecommunications, and weather forecasting technologies will aid in the continued improvements of early warning systems to assist livestock producers in reducing risk and adapting to the changing environment. Broad utilization of sensor technologies will allow scientists to collect real-time data and, when combined with mathematical modeling, decision support systems will become an indispensable managerial tool for livestock production with the possibility to automate low-level decisions on the farm, such as supplementation schedules, sorting of animals, and early detection of disease and outbreaks. The identification of feed efficient animals may be the single most impactful advancement towards long-term livestock sustainability and the promise of feeding the world animal products. We contend that education across societal levels is the first step to solve current and future challenges of the livestock industry. The dilemma has been who will take the first step forward.

While fire and rangeland managers frequently have different land management roles and objectives, their data needs with regards to herbaceous biomass (fuel loads and forage) often overlap, and can be served with a single sampling protocol for both rangeland and fuels management. In this study, we examined how two herbaceous sampling methods compare in measuring species richness, ground cover, and standing herbaceous biomass for range and forestry management using the Phytomass Growth Simulator (Phygrow). Phygrow is an herbaceous vegetation growth model used to simulate rangeland plant production for herbivory, drought, and wildfire severity early warning systems. The Point-frequency protocol has been used for 10 years to collect plant community parameters for Phygrow. The Common Non-Forested Vegetation Sampling Protocol (CNVSP) is a commonly used rangeland assessment protocol in the southwestern United States. Data from both methods were used to parameterize the Phygrow model to examine their similarities and differences, and to see if data collected from the CNVSP methodology could be used to model herbaceous fuel loads. We determined that the data collected in the CNVSP protocol met the needs for Phygrow model validation of standing herbaceous fuels, but data was insufficient for modeling surface dead fuel loads.

In many developing countries where rangelands are a dominant land type and critically important in livelihoods of a significant portion of the population, severe rangeland degradation and/or conflicts over rangeland use can create significant social, economic, and environmental problems. In this paper, we review rangeland degradation in the developing world, its impacts and causes, discuss problems in applying rangeland science to improve rangeland conditions, discuss the role of rangeland scientists, and discuss our approach for enhancing rangeland science in international development. We suggest range scientists can provide valuable input and direction on issues of rangeland degradation (including state changes and impacts on ecosystem goods and services), provide guidance in methods and realistic opportunities for rangeland improvement to local users, government, and development organizations, and work to provide pastoralists with adaptive management in variable ecosystems. Conflict and poverty can create situations where a long-term goal of sustainable rangeland use is overwhelmed by short-term needs of safety and food security; however, providing science and training on sustainable management can make a difference where conflicts are not too severe and can help promote societal stability. Negative perceptions about aid are widespread, but the needs for improved conditions associated with multiple values of rangelands, and the needs of people utilizing these areas, are great. Conducting planning and projects with transparency and accountability will help promote more inclusive participation and successful projects. To be effective, a project needs to consider the needs of the people utilizing the project area but also provide to these communities information on values of the rangelands to other stakeholders (ecosystem services). Sustainable projects will require accountability and enhance self-reliance to allow community empowerment and adaptability to changes.

In North America, it has been shown that cattle in warmer, drier grasslands have lower quality diets than those cattle grazing cooler, wetter grasslands, which suggests warming will increase nutritional stress and reduce weight gain. Yet, little is known about how the plant species that comprise cattle diets change across these gradients and whether these shifts in dietary quality coincide with shifts in dietary composition, i.e. the relative abundance of different plant species consumed by cattle. To quantify geographic patterns in dietary composition, we analyzed the dietary composition and dietary quality of unsupplemented cattle from 289 sites across the central US by sequence-based analyses of plant DNA isolated from cattle fecal samples. Overall, assuming that the percentage of reads for a species in a sample corresponds to the percentage of protein derived from the species, only 45% of the protein intake for cattle was derived from grasses. Within the Great Plains, northern cattle relied more on grasses than southern cattle, which derived a greater proportion of their protein from herbaceous and woody eudicots. Eastern cattle were also more likely to consume a unique assemblage of plant species than western cattle. High dietary protein was not strongly tied to consumption of any specific plant species, which suggests that efforts to promote individual plant species may not easily remedy protein deficiencies. A few plant species were consistently associated with lower quality diets. For example, the diets of cattle with high amounts of Elymus or Hesperostipa were more likely to have lower crude protein concentrations than diets with less of these grasses. Overall, our analyses suggest that climatic warming will increase the reliance of cattle on eudicots as protein concentrations of grasses decline. Monitoring cattle diet with this DNA-based sequencing approach can be an effective tool for quantifying cattle diet to better increase animal performance and guide mitigation strategies to changing climates.

Rangelands provide an array of ecosystem services such as food, fiber, water, recreation, minerals, and are important to the livelihoods of people across the globe, especially in developing countries. Competing land uses, overgrazing, extreme climate events, and socioeconomic changes are resulting in rangeland degradation in many parts of the world. Given our reliance on rangelands, degradation of this resource can have far-reaching effects. In this chapter, causes of rangeland degradation are examined. Indicators that can be used to identify degradation and methods for assessing the degree of degradation in rangeland ecosystems are discussed. Options and considerations for restoring disturbed rangeland are presented, in addition to future directions in rangeland degradation monitoring and assessment.

Stocking density, both current and past, is a major determinant of the nature and condition of rangelands. Despite this fact, there have been few detailed examinations of historical trends in stocking density. We used data from the U.S. Census of Agriculture to track the density of domestic livestock from the early 1900s to the present, for six rangeland regions in the State of Texas: (1) the Edwards Plateau; (2) the Trans-Pecos; (3) the Lampasas Cut Plain; (4) the South Texas Plains; (5) the Rolling Plains; and (6) the High Plains. We find that stocking densities have declined across the state—ranging from a decline of about 40% in some regions to as much as 75% in the Trans-Pecos and Edwards Plateau regions. The period of sharpest decline, which began in the middle of the last century, reflects important, but not fully understood, socioeconomic changes. These most likely include changing land ownership, fragmentation of land holdings, and increasing emphasis on wildlife conservation. Other factors potentially contributing to the destocking of Texas rangelands include woody plant encroachment and a rise in predation. We argue that the dramatic reduction in stocking densities documented here has profound socioeconomic, ecological, and hydrological implications that need to be better understood.

Rangelands make an important contribution to carbon dynamics of terrestrial ecosystems. We used a readily accessible interface (COMET VR) to a simulation model (CENTURY) to predict changes in soil carbon in response to management changes commonly associated with conservation programs. We also used a subroutine of the model to calculate an estimate of uncertainty of the model output based on the similarity between climate, soil, and management history inputs and those used previously to parameterize the model for common land use (cropland to perennial grassland) and management (stocking rate reductions and legume addition) changes to test the validity of the approach across the southwestern United States. The conversion of small grain cropland to perennial cover was simulated acceptably (, 20% uncertainty) by the model for soil, climate, and management history attributes representative of 32% of land area currently in small grain production, while the simulation of small grain cropland to perennial cover + legumes was acceptable on 73% of current small grain production area. The model performed poorly on arid and semiarid rangelands for both management (reduced stocking) and restoration (legume addition) practices. Only 66% of land area currently used as rangeland had climate, soil, and management attributes that resulted in acceptable uncertainty. Based on our results, it will be difficult to credibly predict changes to soil carbon resulting from common land use and management practices, both at fine and coarse scales. To overcome these limitations, we propose an integrated system of spatially explicit direct measurement of soil carbon at locations with well-documented management histories and climatic records to better parameterize the model for rangeland applications. Further, because the drivers of soil carbon fluxes on rangelands are dominated by climate rather than management, the interface should be redesigned to simulate soil carbon changes based on ecological state rather than practice application. Resumen

The feasibility of using Normalized Differential Vegetation Index (NDVI) and geostatistical techniques in the mapping of livestock diet quality was investigated using the northern Ghana savanna zone as a test bed. Near infrared reflectance spectroscopy (NIRS), crude protein (CP) and digestible organic matter (DOM) calibration equations developed for Sub-Saharan African cattle were used for the analysis of faecal samples collected between February and August 2000 from selected households located within the northern Ghana savanna. The predicted CP and DOM values (%) were used with Normalized Differential Vegetation Index (NDVI) data and cokriging procedures to create maps describing diet quality for March and July 2000, representing the dry and wet seasons respectively. Cross-validation results indicated an above average capability of cokriging to estimate the predicted CP% for March (r2 = 0.687, SEp = 1.736), but average for July (r2 = 0.513, SEp = 1.558). The cokriged-estimated DOM value for July was above average (r2 = 0.584, SEp = 3.611); however, March DOM% estimation was rather poor (r2 = 0.132, SEp = 3.891). The results suggested that a reasonable level of success was achieved in using NDVI and geostatistics techniques in cattle diet quality mapping; however, further research is required in this field.

With over 1 billion cattle in the world as well as over 2 billion sheep, goats and buffalo, these animals contribute approximately 15% of the global human protein supply while producing a significant proportion of anthropogenic emissions of greenhouse gases and global nutrient fluxes. Despite increasing reliance on grazers for protein production globally, the future of grazers in a changing world is uncertain. Factors such as increased prevalence of drought, rising atmospheric CO2 concentrations, and sustained nutrient export all have the potential to reduce cattle performance by reducing the nutritional quality of forage. However, there are no analyses to quantify changes in diet quality, subsequent impact on cattle performance and cost of supplementation necessary to mitigate any predicted protein deficiency. To quantify the trajectory of nutritional stress in cattle, we examined more than 36 000 measurements of dietary quality taken over 22 yr for US cattle. Here, we show that standardizing for spatial and temporal variation in drought and its effects on forage quality, cattle have been becoming increasingly stressed for protein over the past two decades, likely reducing cattle weight gain. In economic terms, the replacement costs of reduced protein provision to US cattle are estimated to be the equivalent of $1.9 billion annually. Given these trends, nitrogen enrichment of grasslands might be necessary if further reduction in protein content of forages is to be prevented.

Near-infrared reflectance spectroscopy of fecal samples from crossbred beef cows grazing native range forage was performed to determine whether supplemental feeding would alter the prediction of forage quality. In one trial, 2.27 kg.cow-1 x d-1 of supplemental feed with 20% CP and 3.3 Mcal of DE/kg had a detectable, but unimportant, effect on the predicted forage digestibility of OM, whereas the predicted forage content of CP was increased from 5.6 to 6.4% (P < .01). In a second trial at another location, supplemental feeding of isonitrogenous (700 g.cow-1 x feeding-1) feeds that provided low, medium, or high levels of DE three times weekly caused detectable, but unimportant, changes in the predicted digestibility of forage OM, whereas important changes were noted in the predicted CP content of grazed forages. Although forage quality could not be evaluated from spectra developed with unsupplemented cows, a change in the plane of nutrition was detectable. In the first trial, apparent effects of supplemental feeding on predicted diet quality were not detected if fecal sampling occurred 36 or 56 h after the supplemental feeding ceased for CP and OM digestibility, respectively. Whether supplemental feeding altered the grazing behavior of cows and quality of forage grazed, or merely altered composition of fecal samples, was not determined.

Grazing strategies, consisting of grazing systems and stocking rate adjustments, have evolved from the need to sustain efficient use of the forage resources by livestock, increase animal performance and sustain forage production. A 3-year study was conducted with Tibetan sheep on the Eastern Qinghai-Tibetan Plateau, China to compare: (1) two grazing systems [season-long continuous (SLC; July to December) versus short duration with seasonal rotation (SDSR; July to September in growing-season pasture and October to December in cold-season pasture) with a stocking rate of 24 sheep months ha–1(SM ha–1)]; (2) SDSR system with 24, 36 and 48 SM ha–1; and (3) seasonal aspects of stocking rate under the SDSR system by comparing strategies of heavy stocking rate in the growing season and light stocking rate in the cold season (SDSR-HL) versus light stocking rate in the growing season and heavy stocking rate in the cold season (SDSR-LH). No differences were found between grazing systems in liveweight gain per head or per ha and in residual herbage mass. Liveweight gain per head for treatment SDSR24 was greater than for treatments SDSR36 and SDRS48, whereas liveweight gain per ha showed the opposite tendency. No differences were found between the SDSR-HL and SDSR-LH treatments in liveweight gain per head or per ha, whereas the ratio of residual herbage mass at the end of grazing the growing-season pasture to the cold pasture of treatment SDSR-LH was more than twice that of treatment SDSR-HL. Daily liveweight gain of Tibetan sheep decreased linearly with increasing grazing pressure in both growing and cold seasons. It was estimated that, at a grazing pressure index of 310 sheep days t–1 DM peak herbage mass, liveweight gain per head and ha appears to be optimised over the whole grazing period. Liveweight loss by Tibetan sheep during the cold season was apparent regardless of grazing pressure indicating that temperature had a stronger influence on sheep performance in the cold season than herbage availability.

Rangelands in Africa (i.e., grasslands, savannas, and woodlands, which contain both grasses and woody plants) cover approximately 2.1 × 109 ha. Africa’s livestock population of about 184 million cattle, 3.72 million small ruminants (sheep and goats), and 17 million camels extract about 80% of their nutrition from these vast rangelands (IPCC, 1996). Rangelands have a long history of human use and are noted for great variability in climate and frequent drought events. The combination of climatic variability, low ecological resilience, and human land use make rangeland ecosystems more susceptible to rapid degeneration of ecosystems. From a land-use perspective, there are differences between West Africa and East Africa in rangelands use. In arid and semiarid areas of West Africa (rainfall 5–600 mm), millet (or another crop) is planted over a unimodal (one peak in rainfall per year) rainy season (three to four months); then fields remain fallow during the dry season, ranging from eight to nine months. Livestock eat crop residues. Land use is dominated by cultivation, with livestock playing a subsidiary role in the village economy. In East Africa, by contrast, areas with higher rainfall (up to 600 mm) are inhabited by pastoralists rather than farmers. In dry parts, cultivation occurs mainly where irrigation is possible or where water can otherwise be sequestered and stored for cropping. Rainfall is bimodal (two peaks in rainfall per year) in most rangelands, resulting in two growing seasons. As much as 85% of the population live and depend on rangelands in a number of countries in Africa. With emerging problems associated with the increasing population, the changes in key production areas, and the prevalence of episodic droughts and insecurity due to climatic change and ecological degradation and expansion of grazing territories, the traditional coping strategies of farmers, ranchers, and pastoralists have become inappropriate. More uncertainties require new innovations in characterizing, monitoring, analyzing, and communicating the emergence of drought to allow pastoral communities to cope with a rapidly changing environment. To this end, the United States Agency for International Development (USAID) awarded the Texas A&M University System an assessment grant to develop a Livestock Early Warning System (LEWS) as part of the Global Livestock Collaborative Research Support Program.

Timely information on the availability of water and forage is important for the sustainable development of pastoral regions. The lack of such information increases the dependence of pastoral communities on perennial sources, which often leads to competition and conflicts. The provision of timely information is a challenging task, especially due to the scarcity or non-existence of conventional station-based hydrometeorological networks in the remote pastoral regions. A multi-source water balance modelling approach driven by satellite data was used to operationally monitor daily water level fluctuations across the pastoral regions of northern Kenya and southern Ethiopia. Advanced Spaceborne Thermal Emission and Reflection Radiometer data were used for mapping and estimating the surface area of the waterholes. Satellite-based rainfall, modelled run-off and evapotranspiration data were used to model daily water level fluctuations. Mapping of waterholes was achieved with 97% accuracy. Validation of modelled water levels with field-installed gauge data demonstrated the ability of the model to capture the seasonal patterns and variations. Validation results indicate that the model explained 60% of the observed variability in water levels, with an average root-mean-squared error of 22%. Up-to-date information on rainfall, evaporation, scaled water depth and condition of the waterholes is made available daily in near-real time via the Internet (http://watermon.tamu.edu). Such information can be used by non-governmental organizations, governmental organizations and other stakeholders for early warning and decision making. This study demonstrated an integrated approach for establishing an operational waterhole monitoring system using multi-source satellite data and hydrologic modelling.