Do species evenness and plant density influence the magnitude of selection and complementarity effects in annual plant species mixtures?

Plant species richness influences primary productivity via mechanisms that (1) favour species with particular traits (selection effect) and (2) promote niche differentiation between species (complementarity). Influences of species evenness, plant density and other properties of plant communities on productivity are poorly defined, but may depend on whether selection or complementarity prevails in species mixtures. We predicted that selection effects are insensitive to species evenness but increase with plant density, and that the converse is true for complementarity. To test predictions, we grew three species of annuals in monocultures and in three-species mixtures in which evenness of established plants was varied at each of three plant densities in a cultivated field in Texas, USA. Above-ground biomass was smaller in mixtures than expected from monocultures because of negative \u27complementarity\u27 and a negative selection effect. Neither selection nor complementarity varied with species evenness, but selection effects increased at the greatest plant density as predicted

Adaptive, Multi-Paddock, Rotational Grazing Management: An Experimental, Ranch-Scale Assessment of Effects on Multiple Ecosystem Services

Decisions on how to move livestock in space and time are central to rangeland management. Despite decades of small-scale research, substantial uncertainty exists regarding the relative importance of cattle stocking rates per se, versus the movement of cattle in both space and time, in achieving desired vegetation and livestock outcomes at scales relevant to livestock producers. We report on a ranch-scale experiment comparing effects of collaborative, adaptive, multi-paddock, rotational management (CARM) versus more traditional, season-long, continuous rangeland management (TRM) on perennial grass density and production, cattle performance, and wildlife habitat, while holding the annual stocking rate the same in both systems. We collaborated with stakeholders to develop an adaptive grazing management plan, collected pre-treatment data in 2013, and implemented treatments during 2014 – 2020. Results for 2014 – 2018 were reported by Augustine et al. (2020); here we report on two additional years of results, covering a 7-year period of treatments from 2014 – 2020. With two additional years of measurements, we found no significant difference in total forage production in CARM vs. TRM treatments, averaged across all soil types in the experiment. In one year, we found that CARM increased forage production on loamy soils and decreased forage production on alkaline soils, but these differences were minor and in opposite directions, resulting in no net overall effect. Furthermore, we found that adaptive, rotational grazing management substantially reduced livestock weight gains in each of the first 6 years of the experiment, when cattle were managed as a single, large herd occupying each paddock sequentially. Across the 6 years, cattle weight gain averaged 15% lower in CARM vs. TRM. In the 7th year, stocking density in CARM was reduced 50% by giving cattle access to two paddocks at a time. This year also coincided with a drought. Under these conditions, cattle weight gains were identical in both treatments. Results emphasize the importance of replicated controls in assessing grazing management effects. Even in heterogeneous landscapes where livestock are moved adaptively among paddocks to match seasonal patterns of forage growth, such management may not lead to desired outcomes for vegetation and livestock

Biophysical, Grazing-Season Management, and Animal Traits Effects on Individual Animal Performance of Cow-Calf Systems: Insights from a Long-Term Experiment in the US Western Great Plains

Beef grazing systems require information on management, biophysical, and individual animal influences on performance metrics. However, long-term controlled experiments are lacking to comprehensively ascertain these individual and likely interacting influences. We used a legacy data set from the USDA Agricultural Research Service where individual weight gains were determined from on and off weights of Hereford cows and calves grazing native northern mixed-grass prairie, during the June through September season, from 1975-2001 near Cheyenne, Wyoming, USA. The herd size varied from a minimum of 10 to a maximum of 48 pairs across years. Management (on and off grazing dates and stocking rate, kg BW/ha), biophysical (forage production estimated through NDVI LANDSAT time series, temperature, and precipitation variability), and individual animal (cow age, cow body weight at beginning of grazing season, and calf gender) influences were evaluated for effects on calf weight gain (WG, kg/head). Linear mixed models were used for analyses where the above mentioned were fixed factors, and year and individual cow were random ones. Calf performance was influenced by three animal traits: gender with steer WG 4 kg more than heifer, cow body weight with calf WG increased 2kg for each 100kg of cow body weight, and cow age as optimum calf WG occurred with 5-year-old cows. Management influenced calf WG through the on and off dates. Delaying the start of a grazing season decreased calf WG by 0.80 kg per delayed day. On the contrary, extending the grazing season increased calf WG by about the same amount. Biophysical effects on calf WG were not significant suggesting that the cow performance was mitigating these effects of variability. Results suggest that calf individual performance in this resilient rangeland ecosystem relies on cows’ body weight at beginning of the grazing, their age, and the timing to enter and remove animals from pastures

Adaptive Rotational Grazing and the Story of the Regrazed Grass Plant

Livestock stocking rates and decisions about how to move animals in time and space impact plant responses to livestock grazing. We report on a ranch-scale collaborative experiment comparing adaptive rotational grazing management to season-long continuous grazing during a 4.5-month grazing period during the growing season. As part of this project, stakeholders and scientists worked together to articulate their hypotheses about the mechanisms linking rotational grazing with expected vegetation outcomes. Several stakeholders expected rotational grazing to enhance the production and diversity of grazing-sensitive perennial grass species. The main hypothesized mechanism underlying this expectation was that rotation grazing should reduce regrazing of these grass plants. To test this hypothesis, we monitored patterns of grazing and regrazing on individual tillers (ramets) of a grazing-sensitive grass species, Pascopyrum smithii (western wheatgrass) for three consecutive years. We measured regrazing rates in paddocks managed using moderate stocking and adaptive rotational grazing as well as paddocks grazed continuously, season-long at light, moderate, or heavy stocking rates. Tillers in heavily grazed paddocks were regrazed more than three times as frequently as tillers in moderately grazed pastures, reinforcing the importance of stocking rate as a driver of vegetation impact. At the ranch-scale, tillers were regrazed equally often under adaptive rotational and season-long continuous grazing management, and this result did not vary across years. Adaptive rotational grazing greatly increased heterogeneity among paddocks in patterns of regrazing, with some paddocks experiencing high utilization and others experiencing low utilization. In this semi-arid rangeland, tiller defoliation data do not support the hypothesis that adaptive rotational grazing leads to less regrazing at the ranch-scale. In line with these mechanistic results, the production and diversity of grazing-sensitive perennial grasses also failed to respond to adaptive rotational grazing after five years. However, adaptive rotational grazing may enhance management flexibility and provide opportunities to work towards other objectives, such as wildlife habitat

Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage

In the Great Plains of central North America, sustainable livestock production is dependent on matching the timing of forage availability and quality with animal intake demands. Advances in remote sensing technology provide accurate information for forage quantity. However, similar efforts for forage quality are lacking. Crude protein (CP) content is one of the most relevant forage quality determinants of individual animal intake, especially below an 8% threshold for growing animals. In a set of shortgrass steppe paddocks with contrasting botanical composition, we (1) modeled the spatiotemporal variation in field estimates of CP content against seven spectral MODIS bands, and (2) used the model to assess the risk of reaching the 8% CP content threshold during the grazing season for paddocks with light, moderate, or heavy grazing intensities for the last 22 years (2000–2021). Our calibrated model explained up to 69% of the spatiotemporal variation in CP content. Different from previous investigations, our model was partially independent of NDVI, as it included the green and red portions of the spectrum as direct predictors of CP content. From 2000 to 2021, the model predicted that CP content was a limiting factor for growth of yearling cattle in 80% of the years for about 60% of the mid-May to October grazing season. The risk of forage quality being below the CP content threshold increases as the grazing season progresses, suggesting that ranchers across this rangeland region could benefit from remotely sensed CP content to proactively remove yearling cattle earlier than the traditional October date or to strategically provide supplemental protein sources to grazing cattle.EEA Concepción del UruguayFil: Irisarri, Jorge Gonzalo Nicolás. Rothamsted Research. Sustainable Agriculture Sciences; Reino UnidoFil: Durante, Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; ArgentinaFil: Durante, Martin. Instituto Nacional de Investigación Agropecuaria (INIA). Estación Experimental INIA Tacuarembó. Programa Pasturas y Forrajes; UruguayFil: Derner, Justin D. United States Department of Agriculture-Agricultural Research Service. Rangeland Resources Research Unit; Estados UnidosFil: Oesterheld, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Oesterheld, Martin. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Augustine, David J.. United States Department of Agriculture–Agricultural Research Service. Rangeland Resources and Systems Research Unit; Estados Unido

Predicting spatial-temporal patterns of diet quality and large herbivore performance using satellite time series

Adaptive management of large herbivores requires an understanding of how spatial-temporal fluctuations in forage biomass and quality influence animal performance. Advances in remote sensing have yielded information about the spatial-temporal dynamics of forage biomass, which in turn have informed rangeland management decisions such as stocking rate and paddock selection for free-ranging cattle. However, less is known about the spatial-temporal patterns of diet quality and their influence on large herbivore performance. This is due to infrequent concurrent ground observations of forage conditions with performance (e.g., mass gain), and previously limited satellite data at fine spatial and temporal scales. We combined multi-temporal field observations of diet quality (weekly) and mass gain (monthly) with satellite-derived phenological metrics (pseudo-daily, using data fusion and interpolation) to model daily mass gains of free-ranging yearling cattle in shortgrass steppe. We used this model to predict grazing season (mid-May to October) mass gains, a key management indicator, across 40 different paddocks grazed over a 10-year period (n = 138). We found strong relationships between diet quality and the satellite-derived phenological metrics, especially metrics related to the timing and rate of green-up and senescence. Satellite-derived diet quality estimates were strong predictors of monthly mass gains (R2 = 0.68) across a wide range of aboveground net herbaceous production. Season-long predictions of average daily gain and cattle off-mass had mean absolute errors of 8.9% and 2.9%, respectively. The model performed better temporally (across repeated observations in the same paddock) than spatially (across all paddocks within a given year), highlighting the need for accurate vegetation maps and robust field data collection across both space and time. This study demonstrates that freeranging cattle performance in rangelands is strongly affected by diet quality, which is related to the timing of vegetation green-up and senescence. Senescing vegetation suppressed mass gains, even if adequate forage was available. The satellite-based pseudo-daily approach presented here offers new opportunities for adaptive management of large herbivores, such as identifying withinseason triggers to move livestock among paddocks, predicting wildlife herd health, or timing the grazing season to better match earlier spring green-up caused by climate change and plant species invasion

Integration of Crop-Livestock Systems: An Opportunity toProtect Grasslands from Conversion to Cropland in the US Great Plains

The Great Plains is a mixture of cropland and grassland mainly used for agricultural purposes, with grasslands under continual threat of conversion to cropland. Agriculturists are advocating for the integration of crop-livestock systems (ICLS) to recouple nutrient cycles, improve biodiversity, and increase resilience of agricultural operations. We address the benefits of ICLS in the Great Plains, contending that focus on improving soil health and financial stability of agricultural operations should reduce the conversion of grasslands to cropland. Using US Department of Agriculture National Agricultural Statistics Service Census of Agriculture survey data from the 1925 to 2017 category “cropland used only for pasture or grazing,” which represents land that had been cropped but converted to annual/perennial pasture and grazed, we showcase that the number of farms and the land area in this category is a reasonable proxy of ICLS. As expected, ICLS dramatically decreased in the entire United States from 1925 to 1945, but from 1945 to 2002 in the Great Plains ICLS remained relatively constant, providing evidence of sustained crop-livestock integration. Consistent high numbers of beef cows during this period and the wide availability of forages and crop residues for ruminants facilitated opportunities for producers to use ICLS on their individual operations (within farm) or among operations where row crop farmers and forage-based producers integrated beef cattle use across the landscape (among farms). This integration, however, was decoupled from 2006 to 2013, a period of high grain prices. As a result, economic value of grasslands was decreased and conversion to cropland was increased. Thus, conservation efforts in the Great Plains for grasslands should focus on keeping grasslands intact for provision of multiple ecosystem goods and services by emphasizing incorporation of ICLS within and among farms to reduce the risk of converting grassland to cropland

How to Talk With Ranchers About Drought and Climate Resilience: Lessons From Knowledge Exchange Workshops in Montana

This article offers the Extension community a pathway to drought resilience and climate-related conversations through knowledge exchange workshops. In 2017, a flash drought affected eastern Montana, and ranchers in the region faced numerous challenges. Moreover, drought-favorable climate conditions are predicted to increase for the region. We held five workshops to facilitate an exchange of adaptive drought management strategies, focusing on key themes for drought resilience: (a) drought planning and adaptive management, (b) use of local knowledge networks, (c) flexible stocking and grazing, and (d) adaptation to shifting baselines. Extension can use this approach to foster multidirectional knowledge sharing to strengthen ranching resilience to drought conditions

Using APAR to Predict Aboveground Plant Productivity in Semi-Arid Rangelands: Spatial and Temporal Relationships Differ

Monitoring of aboveground net primary production (ANPP) is critical for effective management of rangeland ecosystems but is problematic due to the vast extent of rangelands globally, and the high costs of ground-based measurements. Remote sensing of absorbed photosynthetically active radiation (APAR) can be used to predict ANPP, potentially offering an alternative means of quantifying ANPP at both high temporal and spatial resolution across broad spatial extents. The relationship between ANPP and APAR has often been quantified based on either spatial variation across a broad region or temporal variation at a location over time, but rarely both. Here we assess: (i) if the relationship between ANPP and APAR is consistent when evaluated across time and space; (ii) potential factors driving differences between temporal versus spatial models, and (iii) the magnitude of potential errors relating to space for time transformations in quantifying productivity. Using two complimentary ANPP datasets and remotely sensed data derived from MODIS and a Landsat/MODIS fusion data product, we find that slopes of spatial models are generally greater than slopes of temporal models. The abundance of plant species with different structural attributes, specifically the abundance of C4 shortgrasses with prostrate canopies versus taller, more productive C3 species with more vertically complex canopies, tended to vary more dramatically in space than over time. This difference in spatial versus temporal variation in these key plant functional groups appears to be the primary driver of differences in slopes among regression models. While the individual models revealed strong relationships between ANPP to APAR, the use of temporal models to predict variation in space (or vice versa) can increase error in remotely sensed predictions of ANPPEEA Concepción del UruguayFil: Gaffney, Rowan. United States Department of Agriculture–Agricultural Research Service. Rangeland Resources and Systems Research Unit; Estados UnidosFil: Porensky, Lauren M. United States Department of Agriculture–Agricultural Research Service. Rangeland Resources and Systems Research Unit; Estados UnidosFil: Feng, Gao. United States Department of Agriculture–Agricultural Research Service. Hydrology and Remote Sensing Laboratory; Estados UnidosFil: Irisarri, Jorge Gonzalo Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Durante, Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; ArgentinaFil: Derner, Justin D. United States Department of Agriculture-Agricultural Research Service. Rangeland Resources Research Unit; Estados UnidosFil: Augustine, David J.. United States Department of Agriculture–Agricultural Research Service. Rangeland Resources and Systems Research Unit; Estados Unido