Rangeland Productivity Research Articles

Global rangeland production systems and livelihoods at threat under climate change and variability

Rangelands are one of the Earth’s major ice-free land cover types. They provide food and support livelihoods for millions of people in addition to delivering important ecosystems services. However, rangelands are at threat from climate change, although the extent and magnitude of the potential impacts are poorly understood. Any declines in vegetation biomass and fluctuations in grazing availability would be of concern for food production and ecosystem integrity and functionality. In this study, we use a global rangeland model in combination with livestock and socio-economic datasets to identify where and to what extent rangeland systems may be at climatic risk. Overall, mean herbaceous biomass is projected to decrease across global rangelands between 2000 and 2050 under RCP 8.5 (−4.7%), while inter- (year-to-year) and intra- (month-to-month) annual variabilities are projected to increase (+21.3% and +8.2%, respectively). These averaged global estimates mask large spatial heterogeneities, with 74% of global rangeland area projected to experience a decline in mean biomass, 64% an increase in inter-annual variability and 54% an increase in intra-annual variability. Half of global rangeland areas are projected to experience simultaneously a decrease in mean biomass and an increase in inter-annual variability—vegetation trends both potentially harmful for livestock production. These regions include notably the Sahel, Australia, Mongolia, China, Uzbekistan and Turkmenistan and support 376 million people and 174 million ruminant Tropical Livestock Units. Additionally, the rangeland communities currently the most vulnerable (here, with the lowest livestock productivities and economic development levels and with the highest projected increases in human population densities) are projected to also experience the most damaging vegetation trends for livestock production. Although the capacity of rangeland systems to adapt is highly complex, analyses such as these generate some of the information required to inform options to facilitate pastoral system mitigation and adaptation strategies under climate change.

Modeling Climate Change Impacts on Rangeland Productivity and Livestock Population Dynamics in Nkayi District, Zimbabwe

Smallholder farmers in semi-arid areas depend on both cropping and livestock as the main sources of livelihoods. Rangeland productivity varies on both spatial and temporal scales and provides the major source of feed for livestock. Rangeland productivity is expected to decline with climate change thereby reducing livestock feed availability and consequently livelihoods that depend on livestock. This study was carried out to assess the impacts of climate change on rangeland productivity and consequently livestock population dynamics using a 30-year simulation modeling approach. The climate scenarios used in the simulations are built from the localized predictions by General Circulation Models (GCMs). The primary climate variables under consideration are rainfall (+/−7% change), carbon dioxide (CO2 up to 650 ppm) and temperature (+4 °C change). This was done by applying the SAVANNA ecosystem model which simulates rangeland processes and demographic responses of herbivores on a temporal and spatial scale using a weekly internal time step and monthly spatial and temporal outputs. The results show that rainfall levels of less than 600 mm/year have the largest negative effect on herbaceous biomass production. The amount of biomass from the woody layer does not change much during the year. The carbon dioxide (CO2) effects are more influential on the tree and shrub layers (C3 plants) than the herbaceous layer (C4 grasses). The CO2 effect was more dominant than the effects of rainfall and temperature. In the baseline simulations, the shrub plant layer increased significantly over 30 years while there is a three-fold increase in the woody plant layer (trees and shrubs) where biomass increased from a 1980 production to that of 2010. The biomass of the herbaceous layer was stable over the historical period (1980 to 2010) with values fluctuating between 200 and 400 g/m2. Grass green biomass has a variable distribution where most production occurred in the fields and cleared areas while lower levels of production were found in the forested areas. The spatial distribution of shrub green biomass was less directly linked to yearly rainfall. Shrub biomass was mostly found in forested areas, and it showed a steady increase in production. Cattle, donkey, and goat populations rose slowly from 1980 but the rise was disrupted by a dry period during the late 1980s to the early 1990s causing a decline in all populations primarily due to grass unavailability. The populations of cattle goats and donkeys started to rise again from 1995 onwards due to improvements in rainfall. Cattle and donkey populations were rising faster than that of goats while sheep population was not changing much for most of the simulation period, otherwise they declined significantly during the drought of 2002. Similar changes in simulated grass biomass (g/m2) were observed in almost all climate scenarios, except for the peak and low years. The livestock population simulation showed few variations in livestock population under all scenarios. The main conclusion from the study is that CO2 effects on rangeland productivity are much more dominant than the localized effects of rainfall and temperature. This has implications of favoring the growth of the tree and shrub layers over herbaceous layer, which meant that in the long run, the species that are able to use tree and shrub layers may be kept as a livelihood source as they will have a feed source.

Comparing stability in random forest models to map Northern Great Plains plant communities in pastures occupied by prairie dogs using Pleiades imagery

Abstract. Black-tailed prairie dogs (Cynomys ludovicianus) have been described as a keystone species and are important for grassland conservation, yet many concerns exist over the impact of prairie dogs on plant biomass production and consequently livestock production. The ability to map plant communities in pastures colonized by prairie dogs can provide land managers with an opportunity to optimize rangeland production while balancing conservation goals. The aim of this study was to test the ability of random forest (RF) models to classify five plant communities located on and off prairie dog towns in mixed-grass prairie landscapes of north central South Dakota, assess the stability of RF models among different years, and determine the utility of utilizing remote sensing techniques to identify prairie dog colony extent. During 2015 and 2016, Pleiades satellites were tasked to image the study site for a total of five monthly collections each summer (June–October). Training polygons were mapped in 2016 for the five plant communities and used to train RF models. Both the 2015 and 2016 RF models had low (1 %) out-of-bag error rates. However, comparisons between the predicted plant community maps using the 2015 imagery and one created with the 2016 imagery indicate over 32.9 % of pixels changed plant community class between 2015 and 2016. The results show that while RF models may predict with a high degree of accuracy, overlap of plant communities and interannual differences in rainfall may cause instability in fitted models. A final RF model combining both 2015 and 2016 data yielded the lowest error rates and was also highly accurate in determining prairie dog colony boundaries.

An Assessment of Production Trends on the Great Plains from 1984 to 2017

Throughout the Great Plains, aboveground annual net primary productivity (ANPP) is a critical ecosystem service supporting billions of dollars of commerce and countless stakeholders. Managers and producers struggle with high interannual change in ANPP, which often varies 40% between years due to fluctuating precipitation and drought. To quantify ANPP trends and evaluate interannual and spatial variation, we created the Rangeland Production Monitoring Service (RPMS), a spatially explicit database with automatic annual updates of ANPP for all rangelands in the conterminous United States. The RPMS establishes relationships between normalized difference vegetation index (NDVI) from remote sensing data and ANPP from soil ecological site descriptions. These relationships were applied to NDVI data in each year from 1984 to present, although the present assessment focuses on the period from 1984 to 2017. Validation metrics include an r2 of 89% between predicted and observed ANPP at three locations in the Great Plains. For this special issue, we assess data from the RPMS to quantify trends and variation of ANPP in the Great Plains region for four major grassland types, smaller-scale ecological subsections, and national grassland units. Significant (α ≤ 0.05) increases in ANPP since 1984 were observed across all major grassland types in the Great Plains, particularly the northern mixed-grass prairie, which also had the greatest interannual variation (21%) from 1984 to 2017. Corresponding significant increases (P < 0.1) in growing season precipitation were found in all grassland types except the shortgrass steppe. Spatial variation decreases from west to east and tallgrass prairie exhibited the lowest temporal and spatial variation of 8% and 21%, respectively, from 1984 to 2017. Grazing allotments in the National Grasslands exhibit differential recovery after drought ranging from about 15% to 350%.

Soil hydraulic model parameters and methodology as affected by sodium salt solutions

AbstractSoil salinization from shallow ground waters is problematic in numerous regions of the world. These ground waters can degrade soil physical properties and require special land management to maintain soil salinity levels ideal for crop and rangeland production. The objectives of this study were to evaluate how saline and sodic solutions changed soil hydrologic properties and how hydrologic parameters change with solution composition. Four soils ranging in texture from sandy loam to silty clay, were saturated with solutions ranging in electrical conductivities (EC) of 0.5 to 8 dS m−1 and sodium adsorption ratios (SAR) of 0 to 20. The hydraulic conductivity and water retention were measured using pressure plates, HYPROP evaporation method, and a dewpoint potentiometer. Data was fit with the van Genuchten and dual porosity models and the model parameters were evaluated. There was an increase in water retention and decrease in hydraulic conductivity when soils were near saturation as solution SAR increased and EC decreased at potentials near saturation. Water retention method combinations agreed well for low salinity treatments, but fitting parameters did not agree well for the higher salinity treatments. The coarser textured soil had a stronger disagreement in fitting parameters for the different water retention method combinations and greater salt build up near soil surface. Capillary rise of salt bearing waters of low EC and high SAR increases soil water retention and decreases hydraulic conductivity near saturation which will slow rates of downward water movement and salt leaching.

Application of Landsat-derived vegetation trends over South Africa: Potential for monitoring land degradation and restoration

Abstract Monitoring vegetation change is important because the nature, extent and rate of change in key measures, such as plant biomass, cover and species composition, provides critical insight into broader environmental and land use drivers and leads to the development of appropriate policy. We used Landsat data between 1984 and 2018 to produce a map of Enhanced Vegetation Index (EVI) change over South Africa at 30 m resolution and an interactive web application to make the analysis both globally applicable and locally meaningful. We found an increase in EVI of 0.37 ± 0.59% yr−1 (mean ± standard deviation), confirming global vegetation greening trends observed with lower-resolution satellites. Mesic, productive biomes including the Albany Thicket and Savanna, exhibited the largest greening trends while browning trends were dominant in more arid biomes, such as the Succulent Karoo and Desert. Although overall EVI trends correspond to vegetation index trends derived from the Advanced Very-High-Resolution Radiometer (8 km resolution), the relative scarcity of Landsat data availability during the 1980 s is a potential source of error. Using repeat very-high-resolution satellite (ca. 3 m resolution) imagery and ground-based photography as reference, we found good correspondence with EVI trends, revealing patterns of degradation (e.g. woody plant encroachment, desertification), and restoration (e.g. increased rangeland productivity, alien clearing) over selected landscapes. The utility of the EVI trend layer to government and industry for monitoring ecosystem changes will be enhanced by the ability to distinguish climatic from anthropogenic drivers of change. This may be partially achieved though interactive exploration of the EVI trends using the application found here: http://evitrend.zsv.co.za

Goats nutrient the body needs covered, depending on the productivity of rangeland and instead added opportunities

Goats nutrient the body needs covered, depending on the productivity of rangeland and instead added opportunities

The Effect of Land-Use on Herbaceous Production and Grazing Capacity in the Molopo District of the North West Province, South Africa

There are three main types of rangeland management systems in South Africa, namely commercial livestock farming, communal livestock farming and game farming. In commercial farming you normally find one manager/owner with a specific management plan, whilst communal farming is characterized by numerous land users with no specific management plan. The communal areas are also normally overstocked and this overstocking leads to rangeland degradation. In this study the effect of two land-uses (commercial and communal) on herbaceous production and grazing capacity were studied. It was clear from the results that the herbaceous production of the communal rangelands was lower than that of the commercial rangelands. The grazing capacity figures showed that sustainable farming practices were also not possible if the communal rangeland is in a poor condition – this was not even possible in good rainfall years.

Management of phosphorus nutrition of beef cattle grazing seasonally dry rangelands: a review

This review examines the effects of phosphorus (P) deficiency as a major constraint to productivity of cattle grazing rangelands with low-P soils. Nutritional deficiency of P may severely reduce liveweight (LW) gain of growing cattle (e.g. by 20–60 kg/annum) and the productivity of breeder cow herds as weaning rate, mortality and calf growth. In seasonally dry tropical environments, the production responses to supplementary P occur primarily during the rainy season when the nutritional quality of pasture as metabolisable energy (ME) and protein is high and pasture P concentration is limiting, even though the P concentrations are higher than during dry season. When ME and nitrogen of rainy-season pasture are adequate, then P-deficient cattle typically continue to gain LW slowly, but with reduced bone mineralisation (i.e. osteomalacia). In beef breeder herds when diet P is insufficient, cows with high bone P reserves can mobilise bone P reserves during late pregnancy and early lactation. Mobilisation may contribute up to the equivalent of ~7 g diet P/day (one-third of the P requirements) in early lactation, and, thus, allow acutely P-deficient breeders to maintain calf growth for at least several months until depletion of cow body P reserves. However, severe P deficiency in cattle is usually associated with reduced voluntary intake (e.g. by 20–30% per kg LW), severe LW loss and poor reconception rates. When P intake is greater than immediate requirements, breeders can replenish bone P. Replenishment in mature cows occurs slowly when ME intake is sufficient only for slow LW gain, but rapidly at ME intakes sufficient for rapid LW gain. Bone P replenishment also occurs in late-pregnant heifers even when losing maternal LW. Intervals of mobilisation and replenishment of body P reserves will often be important for P nutrition of beef breeder cows through annual cycles. Diagnosis of P deficiency in grazing cattle is difficult and must encompass estimation of both diet P intake and availability of P from body reserves. Cattle behaviour (e.g. pica, osteophagea), low soil P concentrations and low herd productivity provide valuable indicators. Some constituents of blood (plasma inorganic P, calcium, plasma inorganic P:calcium ratios and endocrine markers) are valuable indicators, but the threshold values indicative of P deficiency at various ME intakes are not well established. It is evident that knowledge of both the nutritional physiology and requirements for P provide opportunities to better manage P nutrition to alleviate production losses in low-input systems with beef cattle grazing rangelands.

INVESTIGATION OF THE TiO2 NANOPARTICLES EFFECT ON SEED GERMINATION CHARACTERISTICS OF ZIZIPHORA CLINOPODIOIDES LAM.

Improvement in the rate and amount of germination of seeds has a very important effect on the establish-ment of primary seedlings and the increase of rangeland production. The rapid and uniform germination of seeds leads to the successful establishment of plants. The use of nanoscale materials can help germinate faster seeds. Therefore, in this study, the effects of TiO2 nanoparticles in concentrations of 0, 10, 20, 30, 40, 60 and 80 mg / l on the rate and speed of seed germination of Ziziphora clinopodioides Lam. paid. This design was carried out in a completely randomized design with four replications for 20 days at a constant temperature of 20°C under 12 hours of light and 12 hours of darkness at the Germinator of Natural Resources Faculty of the Ferdowsi University of Mashhad. The results showed that germination percentage of treated seeds with TiO2 nanoparticles increased to 23% ppm compared to control treatment. Also, in other concentrations of other nanoparticles, there was a positive effect on speed and germination percentage, so that the effect of different concentrations of nanoparticles on germination characteristics of Ziziphora clinopodioides Lam. seeds was significant. The highest germination percentage was observed in the concentration of 30 ppm and the lowest germination rate at 30 and 20 ppm concentrations. In high concentrations of TiO2 nanoparticles, no positive effects were observed on the germination characteristics of seed Ziziphora clinopodioides Lam. To conclude the use of TiO2 nanoparticles can be improved by improving the seed germination properties of the medicinal plant Ziziphora clinopodioides Lam. that cause increases plant’s establishment in natural areas.

A coupled forage-grazer model predicts viability of livestock production and wildlife habitat at the regional scale

Informed management of livestock on rangelands underpins both the livelihoods of communities that depend on livestock for sustenance, and the conservation of wildlife that often depend on livestock-dominated landscapes for habitat. Understanding spatial patterns of rangeland productivity is therefore crucial to designing global development strategies that balance social and environmental benefits. Here we introduce a new rangeland production model that dynamically links the Century ecosystem model with a basic ruminant diet selection and physiology model. With lightweight input data requirements that can be met with global sources, the model estimates the viability of broad livestock management decisions, and suggests possible implications of these management decisions for grazing wildlife. Using minimal field data, the new rangeland production model enables the reliable estimation of cattle stocking density; this is an important predictor of the viability of livestock production and forage available for grazing wildlife.

Preweaning performance of lambs sired by Suffolk, Siremax composite, and USSES paternal composite rams in an extensive rangeland production system.

Preweaning performance of lambs sired by Suffolk, Siremax composite, and USSES paternal composite rams in an extensive rangeland production system.

Coping with drought: diapause plasticity in katydid eggs at high, mid‐, and low elevations

1. Semi‐arid rangeland productivity is limited by precipitation, and yet droughts are projected to increase in frequency and duration with unknown impacts on insect populations. As some katydids prolong diapause and remain in an egg bank as a blastoderm for multiple growing seasons, is it possible that drought could prolong diapause and promote outbreaks by synchronising embryonic development and hatching of Mormon crickets, Anabrus simplex, after moisture is restored?2. In this study, a high‐elevation Wyoming population (WY) was compared with a mid‐elevation Idaho (ID) and a low‐elevation Oregon population (OR). It was predicted that eggs from the drier ID and OR habitats would be more tolerant of desiccation. Developmental state and water loss of eggs were measured after drought treatments, and when moisture was restored.3. The two drier treatments had significantly more WY eggs prolonging diapause until after drought ended compared with the two wetter treatments. Whether WY eggs developed in the second or subsequent warm periods was independent of drought treatments. Significantly fewer OR embryos developed in the driest treatment compared with the others, whereas almost all ID eggs developed irrespective of the drought treatment.4. In conclusion, Mormon crickets can delay embryonic development to improve drought tolerance. Although drought did not synchronise development and hatching, diapause plasticity allowed insects to cope and await more favourable conditions.5. Unexpectedly, eggs from WY (the highest, wettest site) were more tolerant, because postponing development resulted in less water loss than in developed embryos. OR egg loss was also reduced by prolonging diapause, relative to ID, which developed in even the driest conditions.

Jointed cactus Opuntia aurantiaca modifies soil nutrient concentrations, grass species assemblage and biomass yield in a savanna rangeland

Biological invasions are currently recognized as a major threat to biodiversity and ecosystem function worldwide, but invasion studies in savanna rangelands are limited. Therefore, we studied the soil properties and grass species abundance, diversity and biomass yield in Opuntia aurantiaca uninvaded, recently-invaded (<30 years ago) and historically-invaded (>30 years) sites in a savanna rangeland, Zimbabwe. Soil nutrient concentrations significantly differed between sites, with nutrient-rich soils in Opuntia-invaded sites. The soil nutrient content in invaded sites was greater by a factor of up to 7 for N, 44 for P and 3.4 for Ca. However, soil pH did not differ between sites (p > 0.05), with slightly acidic soils in all sites. Grass species abundance declined while species evenness increased with time since Opuntia invasion. Further, grass species height and biomass yield in the uninvaded sites were greater than those in the recently-invaded and historically-invaded sites. We also observed a shift in above and belowground biomass allocation in grass species suggesting shifts in plastic allocations with invasion. Overall, redundancy analysis showed a significant negative effect of O. aurantiaca density on the abundance, species richness, species diversity and biomass yield of grass species. In contrast, species evenness and dominance were positively correlated with O. aurantiaca density. In conclusion, despite the positive effects of invasion on soil nutrient concentrations, the findings are worrisome as grass abundance, height and biomass yield are negatively affected. Consequently, rangeland productivity might also be curtailed, indicating the need to manage and eradicate O. aurantiaca given a considerable amount of comparable rangeland that can be affected.

Effects of Livestock Grazing Management on Grassland Birds in a Northern Mixed-Grass Prairie Ecosystem

Grassland birds have undergone substantial population declines throughout much of their historic ranges in North America. Most of the remaining grassland bird habitat is restricted to rangelands managed for livestock production, so grazing management has strong implications for grassland bird conservation efforts. We conducted 1 830 point-count surveys at 305 sites during 2016–2017 to evaluate the relative effects of three livestock grazing systems on the abundance and community composition of grassland birds in a northern mixed-grass prairie ecosystem of eastern Montana, United States. Our objectives were to 1) evaluate effects of grazing management on abundance and community composition of grassland obligate birds, focusing specifically on grazing systems, stocking rates, and interactions with rangeland productivity; 2) evaluate the importance of local vegetation characteristics for grassland birds within grazing systems; and 3) assess the effectiveness of rest-rotation grazing to create patch-heterogeneity in rangeland vegetation through the alteration of structural components and the response of grassland birds to these treatments. Overall, we found inconsistent responses in abundances of grassland birds relative to livestock grazing systems and no discernable differences among grazing systems relative to community composition. However, local abundances were often driven by interactions between grazing system and rangeland production potential, suggesting the effects of livestock grazing management were generally mediated by rangeland productivity. In addition, associations between avian abundance and grazing management parameters (e.g., stocking rate) were species specific. Ubiquitous guidelines for livestock grazing systems may be inappropriate for grassland bird conservation efforts in the northern mixed-grass prairie, and high stocking rates may negatively impact populations of dense-grass obligate grassland birds in this region.

Existing Accessible Modeling Tools Offer Limited Support to Evaluation of Impact Investment in Rangeland Ecosystem Services

Privately owned rangelands in the western US support many ecosystem services and are threatened by financial incentives favoring conversion to housing development and more intensive forms of agriculture. Recognizing this threat, the impact investment community has identified rangeland management as a potential investing strategy to produce financial returns while preserving or enhancing the ecosystem services provided by intact rangelands. This strategy is based primarily on the notion that a capital-intensive conversion from continuous to rotational grazing can financially sustain rangelands through a combination of increased productivity and potentially monetized ecosystem service flows. The potential for these gains is supported by compelling anecdotal evidence, yet a robust body of scientific literature based on rigorous field experiments has not supported those claims, nor produced transferable estimates of the benefits provided by rotational grazing of livestock (particularly cattle in the western US). Therefore, to demonstrate investment viability and measure investment success, impact investors will likely need to address these well-documented disconnects through some combination of monitoring and process-based modeling. This study examines the extent to which existing modeling tools are up to this task, by assessing the ability of two process-based models to represent four specific rotational grazing benefits put forth by impact investors, using a ranch in northeastern Wyoming as a case study. Using the Soil Water Assessment Tool, we simulated high magnitude changes in the water balance from surface runoff to evapotranspiration, which may be a benefit or negative impact depending on context (Benefit 1). We simulated a decrease in soil water storage under rotational grazing, which directly contradicts the outcome assumed in investment literature (Benefit 2). Using the InVEST beta Rangeland Production Model (based on the Century ecosystem model), we simulated increased biomass productivity (Benefit 3) under rotational grazing, which enhanced animal performance under some management parameters but negatively impacted it in others (Benefit 4). We conclude that the impact investing community will likely find greater success through a shift to objective-oriented ranch management, rather than a specific focus on rotation, and will also need additional investment in science and monitoring to demonstrate benefits.

Monitoring Drought Impact on Annual Forage Production in Semi-Arid Grasslands: A Case Study of Nebraska Sandhills

Land management practices and disturbances (e.g. overgrazing, fire) have substantial effects on grassland forage production. When using satellite remote sensing to monitor climate impacts, such as drought stress on annual forage production, minimizing land management practices and disturbance effects sends a clear climate signal to the productivity data. This study investigates the effect of this climate signal by: (1) providing spatial estimates of expected biomass under specific climate conditions, (2) determining which drought indices explain the majority of interannual variability in this biomass, and (3) developing a predictive model that estimates the annual biomass early in the growing season. To address objective 1, this study uses an established methodology to determine Expected Ecosystem Performance (EEP) in the Nebraska Sandhills, US, representing annual forage levels after accounting for non-climatic influences. Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) data were used to approximate actual ecosystem performance. Seventeen years (2000–2016) of annual EEP was calculated using piecewise regression tree models of site potential and climate data. Expected biomass (EB), EEP converted to biomass in kg*ha−1*yr−1, was then used to examine the predictive capacity of several drought indices and the onset date of the growing season. Subsets of these indices were used to monitor and predict annual expected grassland biomass. Independent field-based biomass production data available from two Sandhills locations were used for validation of the EEP model. The EB was related to field-based biomass production (R2 = 0.66 and 0.57) and regional rangeland productivity statistics of the Soil Survey Geographic Database (SSURGO) dataset. The Evaporative Stress Index (ESI), the 3- and 6-month Standardized Precipitation Index (SPI), and the U.S. Drought Monitor (USDM), which represented moisture conditions during May, June and July, explained the majority of the interannual biomass variability in this grassland system (three-month ESI explained roughly 72% of the interannual biomass variability). A new model was developed to use drought indices from early in the growing season to predict the total EB for the whole growing season. This unique approach considers only climate-related drought signal on productivity. The capability to estimate annual EB by the end of May will potentially enable land managers to make informed decisions about stocking rates, hay purchase needs, and other management issues early in the season, minimizing their potential drought losses.

Rapid assessment of juniper distribution in prairie landscapes of the northern Great Plains

Woody plant species including eastern redcedar (Juniperus virginiana) and Rocky Mountain juniper (Juniperus scopulorum) are expanding throughout the prairie ecosystems of the Great Plains because of fire suppression, land management practices, and climate change. Juniper encroachment threatens native grasslands by altering soil characteristics, limiting herbaceous biomass, hindering native plant regeneration, and reducing rangeland productivity. Existing land cover products do not effectively characterize the distribution of juniper over a range of densities, making it difficult to assess the scale of the problem. We evaluated a method for rapid classification and mapping of juniper using matched filtering with Landsat 8 snow-covered and snow-free winter imagery (January-March), and snow-free spring imagery (April–June) for 2015–2016. We used data from two path/rows (29/30 and 30/30) in southeastern South Dakota and northeastern Nebraska (approximately 23,000 km2). In both path/rows, we found that snow-covered winter images increased contrast between juniper and the image background and resulted in the highest overall classification accuracies of 94.5% and 88.9% for juniper densities above 15%, compared to 91.4% and 85.7% for snow-free winter imagery and 57.8% and 74.1% for growing season imagery. Using winter imagery, we successfully captured pixels containing juniper density above 50% with ≥90% detection probability. However, the true positive rate dropped to less than 50% once juniper density fell below 20%. We identified 84 791 ha within the study area occupied by juniper (3.6% of the total area), including 27 504 ha in deciduous forests (33% of deciduous forest area) and 38 738 ha in grasslands (6% of grassland area).

Effects of herd management and the use of ivermectin on dung arthropod communities in grasslands

Agroecosystems represent a large geographical footprint in most terrestrial landscapes, and management decisions within these systems affect their function in species conservation. We evaluated the effects that rangeland management systems (based on stocking density, rotation frequency, and the number of avermectin applications) have on conserving the dung arthropod community in the Northern Great Plains of North America. Comprehensive bioinventories of arthropods were collected from 16 rangelands using core samples of dung pats. Ivermectin was quantified in pats from each ranch using enzyme-linked immunosorbant assay (ELISA). Arthropods in dung were abundant (116,244 specimens) and diverse in eastern South Dakota (172 morphospecies). Rangelands managed with more regenerative practices (frequent rotation at high stocking densities and lack of ivermectin applications) had greater species richness, diversity, predator species abundance, and dung beetle abundance than more conventionally managed rangelands. Ivermectin quantity in cattle pats was negatively correlated with dung beetle abundance and diversity. This work shows that herd management (specifically high-intensity, frequent rotational grazing and eliminating prophylactic ivermectin use) that aims to mimic intensive grazing of large migrating herds of ruminants can foster dung arthropod community structure, a key trait correlated with nutrient cycling, pest suppression, and productivity of cattle-grazed rangelands.

Estimation of spatial and temporal changes in net primary production based on Carnegie Ames Stanford Approach (CASA) model in semi-arid rangelands of Semirom County, Iran

Net primary production (NPP) is an indicator of rangeland ecosystem function. This research assessed the potential of the Carnegie Ames Stanford Approach (CASA) model for estimating NPP and its spatial and temporal changes in semi-arid rangelands of Semirom County, Iran. Using CASA model, we estimated the NPP values based on monthly climate data and the normalized difference vegetation index (NDVI) obtained from the MODIS sensor. Regression analysis was then applied to compare the estimated production data with observed production data. The spatial and temporal changes in NPP and light utilization efficiency (LUE) were investigated in different rangeland vegetation types. The standardized precipitation index (SPI) was also calculated at different time scales and the correlation of SPI with NPP changes was determined. The results indicated that the estimated NPP values varied from 0.00 to 74.48 g C/(m2·a). The observed and estimated NPP values had different correlations, depending on rangeland conditions and vegetation types. The highest and lowest correlations were respectively observed in Astragalus spp.-Agropyron spp. rangeland (R2=0.75) with good condition and Gundelia spp.-Cousinia spp. rangeland (R2=0.36) with poor and very poor conditions. The maximum and minimum LUE values were found in Astragalus spp.-Agropyron spp. rangeland (0.117 g C/MJ) with good condition and annual grasses-annual forbs rangeland (0.010 g C/MJ), respectively. According to the correlations between SPI and NPP changes, the effects of drought periods on NPP depended on vegetation types and rangeland conditions. Annual plants had the highest drought sensitivity while shrubs exhibited the lowest drought sensitivity. The positive effects of wet periods on NPP were less evident in degraded areas where the destructive effects of drought were more prominent. Therefore, determining vegetation types and rangeland conditions is essential in NPP estimation. The findings of this study confirmed the potential of the CASA for estimating rangeland production. Therefore, the model output maps can be used to evaluate, monitor and optimize rangeland management in semi-arid rangelands of Iran where MODIS NPP products are not available.