African Journal of Range & Forage Science 2017: 1–10 Printed in South Africa — All rights reserved This is the final version of the article that is published ahead of the print and online issue
Copyright © NISC (Pty) Ltd
AFRICAN JOURNAL OF RANGE & FORAGE SCIENCE ISSN 1022-0119 EISSN 1727-9380 http://dx.doi.org/10.2989/10220119.2017.1334706
Review Paper
Grazing management that regenerates ecosystem function and grazingland livelihoods Richard Teague1* and Matt Barnes2 Department of Ecosystem Science and Management, Texas A&M University and Texas A&M AgriLife Research Center, Vernon, Texas, USA 2 Shining Horizons Land Management LLC, Bozeman, Montana, USA * Corresponding author, email: rteague@ag.tamu.edu 1
Adopting a systems view and regenerative philosophy can indicate how to regenerate ecosystem function on commercial-scale agro-ecological landscapes. Adaptive multi-paddock grazing management is an example of an approach for grazinglands. Leading conservation farmers have achieved superior results in ecosystem improvement, productivity, soil carbon and fertility, water-holding capacity and profitability. Their method is to use multiple paddocks per herd with short grazing periods, long recovery periods, and adaptively changing recovery periods, residual biomass, animal numbers and other management elements as conditions change. In contrast, much research on grazing management has not followed adaptive research protocols to account for spatial effects, for sufficient time to produce resource improvement, sound animal production, and socio-economic goals under constantly varying conditions on rangelands. We briefly review what management has achieved best outcomes and show how previous reviews of grazing studies were limited in scope and applicability to larger, more complex landscapes. We argue that future research can provide better understanding of how multi-paddock grazing management can improve socio-ecological resilience in grazing ecosystems, while avoiding unintended consequences of possible management options, by involving realistic scale and context, partnering with innovative land managers on real operations, applying adaptive treatments, and combining field studies with modelling approaches. Keywords: ecosystem services, management research, regenerative agriculture, simulation modelling, systems research
Introduction For humans to live sustainably, land must be stewarded to enhance its potential for self-regeneration and the provision of essential ecosystem services such as stable and productive soils, air quality, clean water and biological integrity (Daily 1997; Grice and Hodgkinson 2002; MEA 2005). However, on most of the world’s grazinglands, continuous or relatively unmanaged grazing in excess of carrying capacity (Vetter et al. 2006; Moreno García et al. 2014), often exacerbated by supplementary feeding (Müller et al. 2015), has resulted in degraded vegetation and soils (Milchunas and Lauenroth 1993; Teague et al. 2011), declines in productivity and biodiversity, and a reduction in ecosystem resilience (Knopf 1994; Frank et al. 1998; Peterson et al. 1998). Grazing managers and scientists have tried various forms of grazing management for sustainability or regeneration, with mixed results. The approach with the most promise (and debate about its effectiveness) is one that combines complexity or systems thinking with creative, adaptive management to manage the distribution of grazing over time, across landscapes and plant communities, using planned movement of livestock through a series of paddocks: strategic or adaptive multipaddock (AMP) grazing management.
Results from single-discipline, small-scale, short-term component scientific research are useful for mechanistic understanding, but are problematic for complex adaptive systems such as agro-ecosystems as they often overlook interactions among different elements, and do not seek to identify unintended consequences of options they promote, and thus have limited applicability to managed landscapes such as grazinglands (van der Ploeg et al. 2006; Barnes and Hild 2013; Teague et al. 2013). To bridge the gap between single-discipline, component research and adaptive practices for effective resource management, research must have a realistic, relevant scale and context; thus, scientists would do well to partner with financially successful, environmentally conscious farm managers to conduct research (Herrero and Thornton 2013; Provenza et al. 2013). Skepticism and inquisitiveness are necessary to push forward the frontiers of knowledge, sometimes bringing apparent consensus into question, until a higher synthesis is achieved. The scientific method requires constantly looking for deviations from existing hypotheses, and constantly checking for consistency among field research, modelling and practitioner experiences (Popper 1959; Kuhn 1970).
African Journal of Range & Forage Science is co-published by NISC (Pty) Ltd and Informa UK Limited (trading as Taylor & Francis Group)
2
In this paper we present (1) what has been published on the advantages and disadvantages of multi-paddock grazing, (2) how multi-paddock grazing needs to be managed to achieve best outcomes, and (3) hypothesise what research will provide a better understanding of how multi-paddock grazing management can improve the delivery of ecosystem services and socio-ecological resilience in grazing ecosystems while avoiding unintended consequences. We build on a previous paper that comprehensively reviewed the dichotomy between results from research on rotational grazing and the contradictory results that have been obtained by farmers using AMP grazing (Teague et al. 2013). Our current paper builds on the points discussed in this previous review and includes AMP grazing results that have been published subsequently. Managing to regenerate ecosystem function Although simple forms of grazing management (e.g. rotational deferment, rotational rest and rotational grazing) have been recommended for over a century as an important tool to sustain grazingland productivity and improve animal management (Tainton et al. 1999), they have often been applied rigidly rather than adaptively, and with mixed results. Most, but not all, grazing studies in the scientific literature have concluded that rotational grazing is no better than light continuous (season-long) grazing (Gammon and Roberts 1978; Gammon 1984; Briske et al. 2008, 2011), in apparent contrast to the experience of many AMP practitioners. These criticisms of multi-paddock grazing are based on a subset of rotational grazing management studies that were generally designed and conducted in reductionist ways, and not in ways likely to have been applied by successful exponents of AMP grazing, and thus did not reflect the successes achieved with AMP on commercial ranches. The design and management of experiments profoundly impacts the results obtained, a point not often taken into account (Teague et al. 2013). Desired outcomes are achieved by managing for specific goals. Most rotational grazing treatments in experiments (as cited by Briske et al. 2008) have not been conducted under management protocols demonstrated to provide desired outcomes, and underestimate the potential of multi-paddock grazing to improve ecosystem function (Teague et al. 2013). Specifically, the studies have been short term and have not included the critical factor of scale. Paddocks have been grazed for too long and not enough time has been allowed for plants to recover from grazing. As conditions change, research management has not adapted to the changes but used fixed, predetermined protocols. By not adapting under constantly varying conditions, good animal production and resource improvement have not been achieved (Teague et al. 2013). Researchers have also concentrated on differences in productivity without considering negative impacts on key elements of ecosystem function or the long-term accumulating negative impacts of continuous grazing. Wolf and Horney (2017) conducted a quantitative meta-analysis of the studies previously reviewed by Briske et al. (2008), accounted for influential variables within the studies such as local climate and management factors, and
Teague and Barnes
found that (despite the aforementioned limitations of the studies) as experimental scale increased, animal production increased under rotational grazing compared with continuous grazing – consistent with Norton (1998, 2003), Norton et al. (2013) and Teague et al. (2013). Studies from Argentina, Australia, Germany, southern Africa and the USA have arrived at very different conclusions to the above reviews when the research (1) was conducted at the scale of ranching operations, (2) was adaptively managed to achieve desired ecosystem and production goals as conditions changed, (3) used management protocols that have achieved best outcomes on commercial ranches and (4) measured parameters indicating change of hypothesised causal mechanisms in ecosystem function (Teague et al. 2011, 2013; Barnes and Hild 2013). It is becoming increasingly clear that the key to sustainable use and recovery from degradation involves grazing for short periods, grazing moderately in the growing season, leaving adequate plant cover followed by adequate, planned recovery that is facilitated by effective multipaddock grazing management protocols, and adjusting stock numbers to match forage biomass (Earl and Jones 1996; Murphy 1998; Gerrish 2004; Butterfield et al. 2006; Jacobo et al. 2006; Müller et al. 2007; Provenza 2008; Teague et al. 2011, 2013; Barnes and Hild 2013; Jakoby et al. 2014; Martin et al. 2014; Jakoby et al. 2015; Müller et al. 2015; Flack 2016; Wang et al. 2016). Stocking rate has a great impact on plant production, species composition and animal performance; consequently, it has been extensively investigated and is believed by most scientists to be a key management factor needed to sustain long-term profits while maintaining ecosystem function (Huffaker and Wilen 1991; Torell et al. 1991; Huffaker and Cooper 1995; Kobayashi et al. 2007; Briske et al. 2008; Ritten et al. 2010; Briske et al. 2011). However, appropriate stocking rate alone does not avoid rangeland degradation, because livestock in large paddocks exhibit repetitive use of preferred plants and patches (Norton 1998, 2003; Barnes et al. 2008; Teague et al. 2013). This repeated preferential consumption of preferred plants and patches results in uneven impact, such that even at low stocking rates localised undesired changes in plants and soil take place, with these patches persisting and expanding, progressively degrading the landscape (Fuls 1992; O’Connor 1992; Bullock et al. 1994; Bailey et al. 1998; Teague et al. 2004). Well-planned AMP grazing can mitigate these negative grazing impacts and improve species composition and ecosystem function (DeRamus et al. 2003; Gerrish 2004; Teague et al. 2013). Many farmers around the world have used AMP grazing management to restore ecosystem services and productivity on degraded rangelands in areas with less than 250 to 1 500 mm of annual precipitation (Earl and Jones 1996; Butterfield et al. 2006; Jacobo et al. 2006; Müller et al. 2007; Teague et al. 2011, 2013; Barnes and Hild 2013; Jakoby et al. 2014). Many of these ranches in drier areas were initially so bare of vegetation that they would have been classified as desertified. Improved management has been shown to reverse the causal mechanisms of degradation by decreasing bare ground, increasing water infiltration rates, enhancing soil carbon, enhancing soil fertility,
African Journal of Range & Forage Science 2017: 1–10
increasing soil and ecosystem community biodiversity, and restoring the dominance of the most productive plant species. These functions are all strongly linked to shifts in soil microbial and biological community composition, carbon cycling and nitrogen cycling (Altieri 1999; van der Heijden et al. 2008; Neilsen et al. 2011; de Vries et al. 2012). In addition to soil microbes, key organisms such as dung beetles and earthworms have a strong influence on ecological function and farm management can be adjusted to optimise the benefits they provide (Herrick and Lal 1995; Richardson and Richardson 2000; Wardle and Bardgett 2004; Blouin et al. 2013. Farmers using AMP grazing on rangelands have won many conservation awards. These farmers operate in extensive, heterogeneous landscapes, where they are confronted with the adverse effects of uneven grazing distribution, and use their collective ecological and management knowledge to achieve superior outcomes by practicing adaptive, multi-paddock grazing management. Superior results in terms of range ecosystem improvement, productivity, soil carbon and fertility, water-holding capacity and profitability have been regularly obtained by farmers using AMP with short periods of grazing, long recovery periods and adaptively changing recovery periods and other management elements as conditions change (Teague et al. 2011, 2013; Barnes and Hild 2013). Many rangeland conservationists (agency personnel and consultants) are in constant contact with farmers, both the best and the rest, and they appreciate the positive resource and economic value of using well-managed AMP grazing management. For example, the US Department of Agriculture – Natural Resource Conservation Service (USDA-NRCS) policies and advice to farmers is centred on using AMP grazing management. Focusing grazing research on ecosystem function The best management is based on good science conducted at appropriate and multiple scales (Carroll 2016). Research in all agricultural endeavours, including rangeland and forage ecosystems, needs to have an ecosystem perspective and a complex systems framework, incorporating adaptability and creativity, and it is this higher synthesis that resolves the long-standing debate over AMP and rotational grazing (Barnes and Hild 2013). Control of all variables is impossible in field research, especially when studying processes rather than events, and is at odds with realistic scale and context (Provenza et al. 2013). Single-discipline research on small plots and in pots does not include the complexity and interactions that occur in managed landscapes, but these are the functional elements that we need to understand and explore because they determine responses to different management at the scale that land is managed. We need to understand more fully how we can modify management in grazing systems to use the positive ecosystem services provided by soil biota, insects, birds and mammals that influence soil function, and minimise management practices that cause negative consequences. Most research on grazingland has been conducted on above-ground biota, but as soil biota are responsible for more than 90% of how the soil–plant system and
3
ecosystem function we need to build on the large base of science that has developed an understanding of the function of soil organisms (Lehman et al. 2015). Soil biology and biological diversity govern the essential ecosystem functions that need to be operating well for delivery of essential services, so research of grazing ecosystems should include key biological drivers and test hypothesised causal mechanisms. These include soil organic matter accumulation, solar energy capture, water infiltration and retention, nutrient cycling, and maintaining the requisite ecosystem biodiversity that provides these services. The responses of entire landscapes and water catchments to different grazing management strategies need to be understood to regenerate ecological function that improves the delivery of essential ecological services. An excellent example of the need to understand the connectivity and response of ecosystems to changes in key driving factors, but also of the inability of large-scale, uncontrollable and unreplicable research to determine causality, is the landscape and water-catchment impacts after the reintroduction of the grey wolf to Yellowstone National Park in North America in 1995 (Wolf et al. 2007; Ripple and Beschta 2011). Prior to this, elk had free reign to the whole park, and the population soared; they became a dominating influence, overgrazed and overbrowsed along lower catenal positions, and degraded the vegetation in the areas they preferred. This had cascading negative consequences on key plant and dependent mammal species such as beavers, and on water-catchment function. The reintroduction of wolves and subsequent decline of the elk population reduced consumption of vegetation in lower catenal parts of the landscape, facilitating recovery of key species such as willows and beavers in these degraded parts of the landscape, in turn contributing to improved water-catchment function (Morell 2015). There is debate about the extent of these changes and the exact causal mechanisms. The decline in the elk population may have occurred even without wolf recovery, and the bison population increased as the elk population decreased, which may have masked effects. Nevertheless, this example suggests that restoring grazingland ecosystem function can potentially be accomplished by changing grazing patterns with AMP grazing such that stocking rates do not exceed forage supply on the landscape. The factor limiting ecosystem function most in grazingland ecosystems is not the amount of rainfall received but the amount of water that infiltrates into the soil. Normal soil function and ecosystem health is possible only if adequate plant and litter cover is present to provide protection from soil loss and to allow soil microorganisms to perform optimally. Hydrological function is greatest under mid and tall bunch grasses and woody plant canopies, followed by short grasses, and least under bare ground (Thurow 1991; Pluhar et al. 1987). Plant and litter cover enhances infiltration, buffers temperatures and decreases evaporation so that soil moisture is retained for longer after each precipitation event. This enhances soil microbial activity, which promotes soil aggregation and aggregate stability, sustains plant nutrient status and availability, improves plant growing conditions and results in the incorporation of more organic matter in the soil. Management that increases the
4
rate of photosynthesis and the number of days that leaf is photosynthesising in the management area increases the amount of energy driving the system and the productivity of the soil biota and plants (Thurow 1991; Rietkerk et al. 2000; Bardgett 2005). Consequently, how grazing is managed has a substantial impact on infiltration, runoff and erosion (Mathews et al. 1994; Haan et al. 2006; Webber et al. 2010; Schwarte et al. 2011), plant species composition and soil cover, which further influences soil hydrological properties (Wright and Bailey 1982; Herrick and Jones 2002). Grasslands need periodic perturbation to maintain ecological function and biodiversity but it must not be too frequent. Tall- and mid-grass ecosystems deteriorate in the absence of disturbance in the form of fire, mowing or periodic grazing, but thrive and remain competitive under infrequent and light to moderate defoliation (Knapp 1985). Light is the primary limiting factor in undefoliated or lightly defoliated prairie, and competition for light quickly favours the tallest herbaceous plants. This results in domination by just a few tall grass species, and plant and ecosystem diversity decline. Self-shading by these taller plants also reduces photosynthesis (Seastedt 1995). Collectively, these changes result in reduced soil fungal presence, curtail nutrient cycling, and increase water and nitrogen accumulation, with leaching reducing ecosystem productivity and impairing water quality downstream. Grazing removes light as a limiting factor and enhances nutrient cycling, nutrient uptake by plants and biodiversity while other plants increase uptake of soil nutrients and nitrogen becomes the limiting factor (Seastedt and Knapp 1993; Blair 1997). In tall- and mixed-grass grazing ecosystems, this can result in compensatory growth under a light to moderate defoliation regime or pulsed grazing (Dyer et al. 1993; Turner et al. 1993) afforded by AMP grazing management. Fieldwork in this ecosystem indicates soil organic matter and cation exchange capacity were higher with AMP grazing and no-grazing than both light and heavy continuous grazing. In addition, the fungal/bacterial ratio was highest with AMP grazing, indicating superior waterholding capacity and nutrient availability and retention (Teague et al. 2011). As the tall grass species are obligate mycotrophs (Hartnett and Wilson 1999), the higher fungal/ bacterial ratio under AMP likely also contributed to the higher productivity of AMP grazing measured in the field by Teague et al. (2011), as discussed by Bardgett and McAlister (1999) and de Vries et al. (2012). Compared with unmanaged or continuous grazing, AMP grazing can have a very different impact on plant and soil parameters that influence hydrological function in managed grazing landscapes (Thurow 1991; Teague et al. 2011). Continuous grazing leads to much higher effective grazing pressure on preferred patches, causing resource deterioration in those preferred areas of the landscape (Thurow 1991; Fuls 1992; O’Connor 1992; Teague et al. 2004). In continuous grazing, heavier stocking increases the impacts of area- and patch-selective grazing in both severity and extent. Appropriately managed AMP grazing may result in better grass species composition, greater primary and secondary production, greater economic returns, and lower biological and economic risk (Teague et al. 2011; Sherren et al. 2012; Teague et al. 2013; Jakoby et al. 2014). The
Teague and Barnes
most beneficial management includes short periods of moderate defoliation during the growing season, leaving relatively high biomass levels upon exiting paddocks, and allowing sufficient growing-season recovery before grazing again (Steffens et al. 2013). The potential results include less bare ground, greater litter and plant cover, increased soil carbon, greater infiltration and water-holding capacity, and improved soil microbial species composition. Partnering with outstanding managers and consultants Superior outcomes for land and people are achieved by accepting novel concepts, using different techniques, allocating resources appropriately, and adaptively changing these elements. Introduction of innovative ideas requires skill, judgement and developing strategies with people such as consultants and other farmers. Farmers manage complex, interacting, diverse and variable landscapes, very unlike small plots with all or most variability removed. Unlike most researchers, innovative farmers try different approaches within their whole-ranch systems because they are less constrained by convention. Positive, neutral or negative results discovered by farmers drive progress (van der Ploeg et al. 2006; Teague et al. 2016). Mindsets from institutionalised research protocols and non-systems training preclude many research scientists from being able to fully understand, represent or manage research projects to achieve the best possible outcomes of innovative, promising management options (van der Ploeg et al. 2006; Provenza et al. 2013; Teague et al. 2016). When those researchers try different ideas, they usually conduct non-systems experiments that limit inclusion of critical elements of socio-ecological systems, as illustrated by van der Ploeg et al. (2006). There are many studies claiming that the management elements studied can improve the impact of agriculture on soil, climate, productivity, etc. If the research has been conducted for short periods at a small scale, in isolation of interacting elements, and with variability purposely reduced, there is no guarantee that they would deliver this promise in a commercial setting or not cause unintended impacts. While small-scale component scientific methods have generated considerable mechanistic knowledge about soils, water, plants and herbivores, and their interactions, very few managementrelated factors have been incorporated in each experiment, thus limiting the discovery of positive or negative interactive effects important for flexibility in successful farm management. Consequently, they have a much-reduced utility for farmers managing complex landscapes. The regenerative way of thinking and conducting research is foreign to many farmers and agricultural scientists. Consequently, it will take very obvious examples of farmers successfully using regenerative principles and practices in functional whole-farm systems to educate others on how to manage regeneratively, and on the advantages that accrue from using these principles. These studies need to be complemented by whole-farm-systems enquiries with farmers to identify synergisms in different combinations and methods of management. Conducting research on regenerative farm businesses in every major agro-ecological region is necessary to provide these platforms.
African Journal of Range & Forage Science 2017: 1–10
Working on commercial ranches is probably the only way of studying interactions of the whole management unit at the commercial scale and incorporating the required level of management expertise with appropriate adjustments in response to changing circumstances. Classical, replicated research protocols generally are too rigid to allow the flexibility to apply the necessary adaptive protocols that farmers use to achieve their resource and economic goals in highly variable environments and markets. To meet predetermined goals, the short- and long-term responses of the whole ecosystems of the farm landscapes must be taken into account. With changing circumstances, management must proactively adjust to minimise negative impacts. For short- and long-term success, successful farmers aiming for regenerative and sustainable economic goals manage for the best soil and vegetation function, animal performance and profit, and do so within the constraints of their unique landscapes, weather and market variability. The effective study of farm management requires understanding farm landscape responses to alternative management actions and comparison of the ways in which they interact with biophysical processes and evolve over time. As noted by van der Ploeg et al. (2006) and Teague et al. (2016), the temporal and spatial variation in biophysical processes and their interaction with different management decisions cannot be determined using classical, replicated experiments that reduce variability and scale of enquiry to understand limited situations. Small-scale component research rarely incorporates management-related factors, thus limiting the discovery of positive or negative interacting effects important for the adaptive flexibility required for best outcomes in the farm business (Teague et al. 2016). A whole-systems approach facilitates discovering emergent properties as illustrated by van der Ploeg et al. (2006) and Teague et al. (2013). Evaluating management requires assessing systems level, multi-year responses. Management research should be designed to investigate what combinations of systems level decisions are most successful. Following implementation of different management treatments, many ecosystem variables are affected simultaneously, including soils, vegetation and livestock. These changes carry over to following years, and are influenced by spatial scale, with the impacts of weather and previous management compounding over time. Consequently, management-related treatments need to be conducted for sufficient time to account for lag effects following implementation of that treatment. Treatments applied non-adaptively in response to changing weather events diminish the likelihood of discovering the most desirable outcomes. However, simulation models are useful in detecting desirable outcomes from management strategies. This can be done by measuring the impact of different management on commercial farms and then using the field data to challenge simulation models to test if the models corroborate the data. When corroboration is deemed acceptable, the validated models are used to determine sensitivity to different management inputs and interventions and which are the primary determinants governing the outcomes from these field results (Teague et al. 2013). In this manner, using a selection of alternative management algorithms to test
5
different management hypotheses provides a sound theoretical base to understand how changing combinations of management strategies and actions can provide superior biological and economic outcomes. Thus, outcomes from different management combinations can be evaluated beyond the site and circumstances of the original experiments while ensuring simulation results are within the bounds of relevant field data (Soler et al. 2011; Lugato et al. 2014; Teague et al. 2015; Park et al. 2017). What we have learnt from simulation modelling Understanding complex systems requires development of a sound theoretical base for studying biophysical processes and management hypotheses at the landscape scale, and testing them against observed results (Starfield and Bleloch 1985; Woodward 2005). Simulation modelling at the systems level provides the theoretical base and complements both small-plot and farm-based field research as treatments can be explored without the variability, space, time and cost limitations of traditional grazing research. Through model simulations the consequences of different site physical properties, levels of inputs, and climate or management actions for different land management units can be assessed. Such simulations can address these issues at the whole-farm level and be extended to include assessment of production and economic consequences of adopting different combinations of management options (Coughenour 1991; Teague et al. 2013) providing model output is corroborated with field data (Chiang et al. 2010). Use of models can enhance our understanding of field experiments by accounting for the wide spatial and temporal variability of rangelands, accounting for the necessary decades-long time-frame assessments to improve understanding and facilitate the transfer of information from research areas (Teague et al. 2013; Owen et al. 2015; Wang et al. 2016). Edaphic and topographic variability among rangeland management units is usually high due to low productivity and large land area, which complicates the interpretation of research obtained from similar (never identical) areas. In addition, because the amount of land area for research is often limited, many field grazing studies are not replicated, further complicating interpretation. To date, grazing systems modelling efforts have been used to investigate the outcomes of unreplicated field experiments, the influence of spatial scale, relevance of adequate recovery in rangelands, stock number management strategies, risk assessment, water catchments and ecological economics (Beukes et al. 2002; Teague et al. 2013; Park et al. 2017). Modelling is very effective in assessing the complex issues involved with evaluating how to adapt management to spatial heterogeneity in managed landscapes and constantly varying climate and markets. Management decisions are generally a trade-off between production and economic benefits and maintaining or improving the resource base. Although there is much conflicting evidence from many studies based on field data, simulation modelling offers an assessment of why different research projects have offered very different management recommendations.
6
Corroborated models can effectively test a greater range of management choices and weather sequences than is possible with field studies (Jakoby et al. 2015). Using spatial models has shown that adaptive stocking is less sensitive to overstocking than constant stocking, and that advantages of AMP over continuous grazing are less important at low levels of stocking but become increasingly important as stock numbers increase, improving net economic returns (Jakoby et al. 2015). Norton (1998) hypothesised that on small areas of land with no difference between defoliation rates across different grazing methods, the performance of rotational grazing (MP) grazing is no better than continuous grazing; this was corroborated by the simulation study of Wang et al (2016). These authors also concluded that, at the scale of commercial ranches, MP grazing with improved defoliation management improves grass composition and productivity, as well as livestock consumption relative to continuous grazing, especially with heavier stocking rates and unfavourable initial biomass composition. The advantages of MP grazing, however, are less evident with favourable rainfall conditions, light stocking, low levels of undesirable plants and inadequate recovery periods. Modelling has also indicated that the grazing management strategy of using short periods of grazing with long periods of recovery afforded by using a greater number of paddocks per herd allowed higher stocking rates (Barnes et al. 2011), resulting in higher net returns, lower income variability, protection of the resource base and facilitated resource restoration over a wide range of possible management scenarios (Jakoby et al. 2014). However, adapting management to changing circumstances is required. This involves adjusting stock numbers and grazing period and length of recovery after grazing to balance the ongoing needs of both the livestock and resource condition requirements. Too long a period of grazing or recovery resulted in poorer animal performance or plant recovery, with negative economic consequences (Teague et al. 2015), as acknowledged by experienced consultants working with farmers (Walt Davis, Davis Consulting, Calera, OK, USA, and Dave Pratt, Ranch Management Consultants, Fairfield, CA, USA, pers. comm.). The model assessments of Jakoby et al. (2015) using a comprehensive spatial model indicated that appropriate AMP grazing with a large number of paddocks and short grazing periods facilitated resource improvement and gave the best economic results. However, AMP grazing decreased economic risk only when management adjustments accounted for paddock forage quality and seasonality over the managed landscape. Jakoby et al. (2015) also examined the influence of different farmer objectives on management choices and outcomes. They compared ‘low risk’ and ‘high risk – high profitability’ strategies. Under the low risk strategy there were several viable management choices, all under relatively low stocking rates. In contrast, under both strategies, MP grazing with short grazing periods and long rest periods afforded by a large paddock number and a reasonably high stocking rate gave superior economic outcomes, lower income variability and greater attainment of a minimum income goal while maintaining resource condition.
Teague and Barnes
Numerous modelling papers have reported that MP management resulted in soil and plant conditions that improved hydrological function compared with continuous grazing, even with fewer than six paddocks (Gilley et al. 1996; Sanjari et al. 2009; Schwarte et al. 2011). At the ranch scale, Park et al. (2017) compared the hydrological function of light and heavy continuous grazing with AMP grazing and found annual surface runoff was the major contributor to stream flow with heavy continuous grazing, whereas with AMP grazing, base flow from water entering the soil was the major source of streamflow. At the watercatchment scale, relative to heavy continuous grazing, AMP grazing decreased surface runoff by 47%, increased infiltration by 5%, and decreased streamflow by 29.5%. Improvements using AMP grazing decreased the simulated highest annual streamflow from 8.3 m3 s−1 (baseline scenario) to 6.2 m3 s−1 (MP grazing), reducing the risk of flooding downstream (Park et al. 2017). Necessary components to include in grazing studies Based on published research results we have studied, our published research and reconnaissance sampling in numerous grazingland ecosystems in North America (Bardgett and McAlister 1990; Carroll 2016; Fynn et al 2003; van der Ploeg et al. 2006; Teague et al. 2011, 2013; Barnes and Hild 2013; Jakoby et al. 2014; Martin et al. 2014; Jakoby et al. 2015), we find that only studies at the commercial-ranch scale and on appropriately managed ranches can include the impacts of scale, management quality and adaptive management protocols to achieve desired outcomes. We recommend that the following elements be included in research on the biological components of grazing management: • the increasing heterogeneity of livestock impact with increasing scale • adequate time for treatments to affect biology and soil carbon, ranging from 5 years in areas with high annual rainfall and a long growing season (e.g. the south-eastern USA), to 15 years in areas with rainfall < 900 mm and shorter growing seasons • adaptive management to achieve the best possible results • parameters relating to ecosystem functions as well as production • multiple trophic levels and disciplines: soil, fungi, bacteria, plants, insects, wildlife, spatial hydrology and socio-economics • adequate soil depth and spatial sampling • detailed CO2 flux and 13CO2 static chamber assessments of GHG dynamics within the context of each treatment to determine current carbon sequestration; this must be done within the context of the management being investigated and only once that treatment has been in place for long enough to have equilibrated with that specific management • routine life-cycle analysis and costing to calculate the full costs to society of farm grazing practices and inputs such as fertilisers, pesticides and pharmaceuticals • simulation modelling corroborated with field data, to provide mathematical hypotheses to underpin our
African Journal of Range & Forage Science 2017: 1–10
scientific understanding, and to assess what combinations of management decisions achieve best results in different places and contexts. Conclusions Multiple-paddock grazing does indeed provide tangible and substantive advantages over continuous grazing, if it is well planned and adaptively managed. However, the core is complexity and creativity, not paddocks per se: more paddocks facilitate adaptive management. It is a key to sustaining resources and regenerating ecosystem services from grazing lands to improve farmer incomes. To promote light continuous grazing in the hope it will minimise negative impacts will at best only sustain or slightly improve a degraded state of the grazingland resource while limiting the ability of farmers to earn a decent and sustainable living. Why do so many studies seem to contradict logic and experience? When evaluating the conclusions of research, it is imperative to consider how implementation contributed to the results obtained, and whether the results can be generalised beyond the terms of reference of the study. There are two core problems with almost all of the ‘classical’ grazing studies, both of which are variations of choosing simplicity over complexity, control and replication over realistic context. Most grazing studies, for the sake of scientific rigour, examined rigidly applied treatments, precluding adaptive management, and what they collectively show is that without goal-oriented, creative and adaptive management, all forms of grazing management (‘systems’) are limited in their effectiveness. The overwhelming majority of those studies also were conducted at scales too small to incorporate diversity and unevenness of grazing (the process by which degradation occurs), collectively showing that small paddocks tend to be more evenly grazed. This kind of study represents a larger landscape, but one that has been divided into many tiny paddocks – subsuming a signature benefit of MP grazing (reduced paddock size) even in continuous-grazing treatments. The problem, then, is not that the studies were poorly conducted, but that their design precluded realistic context and the result (usually no apparent difference between treatments) cannot be extrapolated to a large, complex landscape. In contrast, the relatively few studies that have the realistic context of scale and complexity, coupled with well-planned adaptive application of treatment, showed numerous benefits of MP grazing. The approach to agricultural production should be guided by regenerative management protocols to ensure long-term economic sustainability and ecological resilience of agro-ecosystems. Ecologically sensitive management in grazingland ecosystems can contribute positively to critical ecosystem services, in contrast to the deficiencies of many current agricultural production systems. A regenerative philosophy can be adopted by exploring how to restore delivery of ecosystem services on commercialscale landscapes. Ecosystem function, productivity, soil carbon and fertility, water-holding capacity and profitability have been improved by many farmers using AMP grazing principles.
7
Their method is to use multiple paddocks per herd with short periods of grazing, adequate recovery periods and adaptively changing recovery periods, residual biomass, animal numbers and other management elements as growing conditions change. In contrast, much research on grazing management has not (1) accounted for spatial effects, (2) followed adaptive research protocols, (3) provided adequate recovery periods after grazing, (4) allowed sufficient years to measure resource improvement following grazing treatment application, and (5) managed for sound animal production to increase net economic returns under constantly varying conditions on rangelands. An ecosystem perspective and systems framework can be accomplished by combining small-scale component research within a whole-farm and landscape systems framework. Multiple disciplines need to focus on identifying how different management strategies impact causal mechanisms that drive biological function at local and landscape scales. It will be important to complement such research with simulation model experiments to provide a sound theoretical base that can be applied more widely than merely at research sites. Simulation models can not only address these complex, interacting issues at the whole-farm level but also be extended to include assessment of production, resource and economic consequences of adopting different management strategies. Acknowledgements — We are indebted to the support and funding provided by the Dixon Water Foundation and Texas A&M AgriLife Research under project H8179.
References Altieri MA. 1999. The ecological role of biodiversity in agroecosystems. Agriculture, Ecosystems and Environment 74: 19–31. Bailey DW, Dumont B, Devries MF. 1998. Utilization of heterogeneous grasslands by domestic herbivores: theory to management. Annals of Zootechnology 47: 321–333. Bardgett RD. 2005. The biology of soil: a community and ecosystem approach. New York: Oxford University Press. Bardgett RD, McAlister E. 1999. The measurement of soil fungal: bacterial biomass ratios as an indicator of ecosystem selfregulation in temperate meadow grasslands. Biology and Fertility of Soils 29: 282–290. Barnes M, Hild A (eds). 2013. Strategic grazing management for complex creative systems (sponsored issue). Rangelands 35: 1–66. Barnes MK, Norton BE, Maeno M, Malechek JC. 2008. Paddock size and stocking density affect spatial heterogeneity of grazing. Rangeland Ecology and Management 61: 380–388. Barnes MK, Steffens TJ, Rittenhouse LR. 2011. Grazing period stocking rate drives livestock performance in rotational stocking. In: Feldman SR, Oliva GE, Sacido MB (eds), Diverse Rangelands for a Sustainable Society: proceedings of the IX International Rangeland Congress, 2–8 April 2011, Rosario, Santa Fe, Argentina. Rosario: International Rangeland Congress. p 633. Beukes PC, Cowling RM, Higgins SI. 2002. An ecological economic simulation model of a non-selective grazing system in the Nama Karoo, South Africa. Ecological Economics 42: 221–242. Blair JM. 1997. Fire, N availability, and plant response in grasslands: a test of the transient maxima hypothesis. Ecology 78: 2359–2368. Blouin M, Hodson ME, Delgado EA, Bakerd G, Brussaard L, Butt
8
KR, Daig J, Dendooven L, Peres G, Tondoh JE, Cluzeau D, Brun J-J. 2013. A review of earthworm impact on soil function and ecosystem services. European Journal of Soil Science 64: 161–182. Briske D, Derner J, Brown J, Fuhlendorf S, Teague R, Gillen B, Ash A, Havstad K, Willms W, 2008. Benefits of rotational grazing on rangelands: an evaluation of the experimental evidence. Rangeland Ecology and Management 61: 3–17. Briske DD, Sayre NF, Huntsinger L, Fernandez-Gimenez M, Budd B, Derner JD. 2011. Origin, persistence, and resolution of the rotational grazing debate: integrating human dimensions into rangeland research. Rangeland Ecology and Management 64: 325–334. Bullock JM, Hill BC, Dale MP, Silvertown J. 1994. An experimental study of vegetation change due to sheep grazing in a speciespoor grassland and the role of seedling recruitment into gaps. Journal of Applied Ecology 31: 493–507. Butterfield J, Bingham S, Savory A. 2006. Holistic management: a new framework for decision making. Washington, DC: Island Press. Carroll SB. 2016. The Serengeti rules: the quest to discover how life works and why it matters. Princeton: Princeton University Press. Chiang L, Chaubey I, Gitau MW, Arnold JG. 2010. Differentiating impacts of land use changes from pasture management in a CEAP watershed using the SWAT model. Transactions of the ASABE 53: 1569–1584. Coughenour M B. 1991. Spatial components of plant-herbivore interactions in pastoral, farming and native ungulate ecosystems. Journal of Range Management 44: 530–542. Daily GC. 1997. Introduction: What are ecosystem services? In: Daily GC (ed.), Nature’s services: societal dependence on natural ecosystems. Island Press, Washington, pp 1–10. DeRamus HA, Clement TC, Giampola DD, Dickison PC. 2003. Methane emissions of beef cattle on forages: efficiency of grazing management systems. Journal of Environmental Quality 32: 269–277. de Vries FT, Bloem J, Quirk H, Stevens CJ, Bol R, Bardgett RD. 2012. Extensive management promotes plant and microbial nitrogen retention in temperate grassland. PLoS ONE 7: e51201. Dyer MI, Turner CL, Seastedt TR. 1993. Herbivory and its consequences. Ecological Applications 3: 10–16. Earl JM, Jones CE. 1996. The need for a new approach to grazing management - is cell grazing the answer? Rangeland Journal 18: 327–350. Flack S. 2016. The art and science of grazing: how grass farmers can create sustainable systems for healthy animals and farm ecosystems. White River Junction: Chelsea Green Publishing. Frank DA, McNaughton SJ, Tracy BF. 1998. The ecology of the earth’s grazing ecosystems. BioScience 48: 513–521. Fuls ER. 1992. Semi-arid and arid rangelands: a resource under siege due to patch selective grazing. Journal of Arid Environments 22: 191–193. Fynn RWS, Haynes RJ, O’Connor TG. 2003. Burning causes long-term changes in soil organic matter content of a South African grassland. Soil Biology and Biochemistry 35: 677–687. Gammon DM. 1984. An appraisal of short duration grazing as a method of veld management. Zimbabwe Agricultural Journal 82: 59–64. Gammon DM, Roberts BR. 1978. Patterns of defoliation during continuous and rotational grazing of the Matopos Sandveld of Rhodesia. 1. Selectivity of grazing. Rhodesia Journal of Agricultural Research 16: 117–131. Gerrish J. 2004. Management-intensive grazing: the grassroots of grass farming. Ridgeland: Green Park Press. Gilley JE, Patton BD, Nyren PE, Simanton JR. 1996. Grazing and haying effects on runoff and erosion from a former conservation
Teague and Barnes
reserve program site. Applied Engineering in Agriculture 12: 681–684. Grice AC, Hodgkinson KC. 2002. Challenges for rangeland people. In: Grice AC, Hodgkinson KC (eds), Global rangelands: progress and prospects. Wallingford: CABI Publishing. pp 1–9. Haan MM, Russell JR, Powers WJ, Kovar JL, Benning JL. 2006. Grazing management effects on sediment and phosphorus in surface runoff. Rangeland Ecology and Management 59: 607–615. Hartnett DC, Wilson GWT. 1999. Mycorrhizae influence plant community structure and diversity in tallgrass prairie. Ecology 80: 1187–1195. Herrero M, Thornton PK. 2013. Livestock and global change: emerging issues for sustainable food systems. Proceedings of the National Academy of Sciences of the USA 110: 20878–20881. Herrick JE, Jones TL. 2002. A dynamic cone penetrometer for measuring soil penetration resistance. Soil Science Society of America Journal 66: 1320–1324. Herrick JE, Lal R. 1995. Soil physical property changes during dung decomposition in a tropical pasture. Soil Science Society of America Journal 59: 908–912. Huffaker R, Cooper K. 1995. Plant succession as a natural range restoration factor in private livestock enterprises. American Journal of Agricultural Economics 77: 901–913. Huffaker RG, Wilen JE. 1991. Animal stocking under conditions of declining forage nutrients. American Journal of Agricultural Economics 73: 1213–1223. Jacobo EJ, Rodríguez AM, Bartoloni N, Deregibus VA. 2006. Rotational grazing effects on rangeland vegetation at a farm scale. Rangeland Ecology and Management 59: 249–257. Jakoby O, Quaas MF, Baumgärtner S, Frank K. 2015. Adapting livestock management to spatio-temporal heterogeneity in semi-arid rangelands. Journal of Environmental Management 162: 179–189. Jakoby O, Quaas MF, Müller B, Baumgärtner S, Frank K. 2014. How do individual farmers’ objectives influence the evaluation of rangeland management strategies under a variable climate? Journal of Applied Ecology 51: 483–493. Knapp AK. 1985. Effect of fire and drought on the ecophysiology of Andropogon gerardii and Panicum virgatum in a tallgrass prairie. Ecology 66: 1309–1320. Knopf FL. 1994. Avian assemblages on altered grasslands. Studies in Avian Biology 15: 247–257. Kobayashi M, Howitt RE, Jarvis LS, Emilio AL. 2007. Stochastic rangeland use under capital constraints. American Journal of Agricultural Economics 89: 805–817. Kuhn TS. 1970. The structure of scientific revolutions. Chicago: University of Chicago Press. Lehman RM, Cambardella CA, Stott DE, Acosta-Martinez V, Manter DK, Buyer JS, Maul JE, Smith JL, Collins HP, Halvorson JJ, Kremer RJ, Lundgren JG, Ducey TF, Jin VL, Karlen DL. 2015. Understanding and enhancing soil biological health: the solution for reversing soil degradation. Sustainability 7: 988–1027. Lugato E, Panagos P, Bampa F, Jones A, Montanarella L. 2014. A new baseline of organic carbon stock in European agricultural soils using a modelling approach. Global Change Biology 20: 313–26. Martin R, Müller B, Linstädter A, Frank K. 2014. How much climate change can pastoral livelihoods tolerate? Modelling rangeland use and evaluating risk. Global Environmental Change 24: 183–192. Mathews BW, Sollenberger LE, Nair VD, Staples CR. 1994. Impact of grazing on soil nitrogen, phosphorus, potassium, and sulfur distribution. Journal of Environmental Quality 23: 1006–1013. Milchunas DG, Lauenroth WK. 1993. Quantitative effects of grazing on vegetation and soils over a global range of environments.
African Journal of Range & Forage Science 2017: 1–10
Ecological Monographs 63: 327–366. MEA (Millennium Ecosystem Assessment). 2005. Ecosystems and human well-being: synthesis. Washington, DC: Island Press. Moreno García CA, Schellberg J, Ewert F, Brüser K, Canales-Prati P, Linstädter A, Oomen RJ, Ruppert JC, Perelman SB. 2014. Response of community-aggregated plant functional traits along grazing gradients: insights from African semi-arid grasslands. Applied Vegetation Science 17: 470–481. Morell V. 2015. Lessons from the wild lab: Yellowstone Park is a real-world laboratory of predator-prey relations. Science 347: 1302–1307. Müller B, Frank K, Wissel C. 2007. Relevance of rest periods in non-equilibrium rangeland systems: a modelling analysis. Agricultural Systems 92: 295–317. Müller B, Schulze J, Kreuer D, Linstädter A, Frank K. 2015. How to avoid unsustainable side effects of managing climate risk in drylands – the supplementary feeding controversy. Agricultural Systems 139: 153–165. Murphy B. 1998. Greener pasture on your side of the fence: better farming with Voisin management-intensive grazing (4th edn). Colchester, VT: Arriba Publishers. Nielsen UN, Ayres E, Wall DH, Bardgett RD. 2011. Soil biodiversity and carbon cycling: a review and synthesis of studies examining diversity-function relationships. European Journal of Soil Science 62: 105–116. Norton BE. 1998. The application of grazing management to increase sustainable livestock production. Animal Production in Australia 22: 15–26. Norton BE. 2003. Spatial management of grazing to enhance livestock production and resource condition: a scientific argument. In: Allsopp N, Palmer AR, Milton SJ, Kirkman KP, Kerley GIH, Hurt CR, Brown CJ (eds), Proceedings of the 7th International Rangeland Congress, Durban, South Africa. Irene: Document Transfer Technologies. pp 810–820. Norton B, Barnes M, Teague R. 2013. Grazing management can improve livestock distribution. Rangelands 35: 45–51. O’Connor TG. 1992. Patterns of plant selection by grazing cattle in two savanna grasslands: a plant’s eye view. Journal of the Grassland Society of Southern Africa 9: 97–104. Owen JJ, Parton WJ, Silver WL. 2015, Long-term impacts of manure amendments on carbon and greenhouse gas dynamics of rangelands. Global Change Biology 21: 4533–4547. Park Y, Ale S, Teague WR, Dowhower SL. 2017. Simulating hydrologic responses to alternate grazing management practices at the ranch and watershed scales. Journal of Soil and Water Conservation 72: 102–121. Peterson G, Allen GR, Holling CS. 1998. Ecological resilience, biodiversity and scale. Ecosystems 1: 6–18. Pluhar JJ, Knight RW, Heitschmidt RK. 1987. Infiltration rates and sediment production as influenced by grazing systems in the Texas rolling plains. Journal of Range Management 40: 240–243. Popper KR. 1959. The logic of scientific discovery. London: Routledge. Provenza FD. 2008. What does it mean to be locally adapted and who cares anyway? Journal of Animal Science 86: 271–284. Provenza F, Pringle H, Revell D, Bray N, Hines C, Teague R, Steffens T, Barnes M. 2013. Complex creative systems. Rangelands 35: 6–13. Richardson PQ, Richardson RH. 2000. Dung beetles improve the soil community in Texas and Oklahoma. Ecological Restoration 18: 116−117. Rietkerk M, Ketner P, Burger J, Hoorens B, Olff H. 2000. Multiscale soil and vegetation patchiness along a gradient of herbivore impact in a semi-arid grazing system in West Africa. Plant Ecology 148: 207–224. Ripple WJ, Beschta RL. 2011. Trophic cascades in Yellowstone:
9
the first 15 years after wolf reintroduction. Biological Conservation 145: 205–213. Ritten JP, Frasier WM, Bastian CT, Gray ST. 2010. Optimal rangeland stocking decisions under stochastic and climate impacted weather. American Journal of Agricultural Economics 92: 1242–1255. Sanjari G, Yu B, Ghadiri H, Ciesiolka CAA, Rose CW. 2009. Effects of time-controlled grazing on runoff and sediment loss. Soil Research 47: 796–808. Schwarte KA, Russell JR, Kovar JL, Morrical DG, Ensley SM, Yoon KJ, Cornick NA, Cho YI. 2011. Grazing management effects on sediment, phosphorus, and pathogen loading of streams in cool-season grass pastures. Journal of Environmental Quality 40: 1303–1313. Seastedt TR. 1995. Soil systems and nutrient cycles of the North American prairie. In: Joern A, Keeler KH (eds), The changing prairie: North American grasslands. New York: Oxford University Press. pp 157–176. Seastedt TR, Knapp AK. 1993. Consequences of nonequilibrium resource availability across multiple time scales: the transient maxima hypothesis. American Naturalist 141: 621–633. Sherren K, Fischer J, Fazey I. 2012. Managing the grazing landscape: Insights for agricultural adaptation from a mid-drought photo-elicitation study in the Australian sheep-wheat belt. Agricultural Systems 106: 72–83. Soler CM, Bado VB, Traore K, Bostick WM, Jones JW, Hoogenboom G. 2011. Soil organic carbon dynamics and crop yield for different crop rotations in a degraded ferruginous tropical soil in a semi-arid region: a simulation approach. Journal of Agricultural Science 149: 579–593. Starfield AM, Bleloch AL. 1985. Building models for conservation and wildlife management. New York: MacMillan. Steffens T, Grissom G, Barnes M, Provenza F, Roath R. 2013. Adaptive grazing management for recovery. Rangelands 35: 28–34. Tainton NM, Aucamp AJ, Danckwerts JE. 1999. Principles of managing veld. In: Tainton NM (ed.), Veld management in South Africa. Pietermaritzburg: University of Natal Press. pp 169–193. Teague WR, Apfelbaum S, Lal R, Kreuter UP, Rowntree J, Davies CA, Conser R, Rasmussen M, Hatfield J, Wang T, Wang F, Byck P. 2016. The role of ruminants in reducing agriculture’s carbon footprint in North America. Journal of Soil and Water Conservation 71: 156–164. Teague WR, Dowhower SL, Baker SA, Haile N, DeLaune PB, Conover DM. 2011. Grazing management impacts on vegetation, soil biota and soil chemical, physical and hydrological properties in tall grass prairie. Agriculture, Ecosystems and Environment 141: 310–322. Teague WR, Dowhower SL, Waggoner JA. 2004. Drought and grazing patch dynamics under different grazing management. Journal of Arid Environments 58: 97–117. Teague R, Grant B, Wang H. 2015. Assessing optimal configurations of multi-paddock grazing strategies in tallgrass prairie using a simulation model. Journal of Environmental Management 150: 262–273. Teague R, Provenza F, Kreuter U, Steffens T, Barnes M. 2013. Multi-paddock grazing on rangelands: why the perceptual dichotomy between research results and rancher experience? Journal of Environmental Management 128: 699–717. Thurow T. 1991. Hydrology and erosion. In: Heitschmidt RK, Stuth JW (eds), Grazing management: an ecological perspective. Portland: Timberland Press. pp 141–159. Torell LA, Lyon KS, Godfrey EB. 1991. Long run versus short-run planning horizons and the rangeland stocking rate decision. American Journal of Agricultural Economics 73: 795–807. Turner CL, Seastedt TR, Dyer MI. 1993. Maximization of aboveground grassland production: the role of defoliation
10
Teague and Barnes
frequency, intensity and history. Ecological Applications 3: 175–186. van der Heijden MGA, Bardgett RD, van Straalen NM. 2008. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecological Letters 11: 296–310. van der Ploeg JD, Verschuren P, Verhoeven F, Pepels J. 2006. Dealing with novelties: a grassland experiment reconsidered. Journal of Environmental Policy and Planning. 8: 199–218. Vetter S, Goqwana WM, Bond WJ, Trollope WSW. 2006. Effects of land tenure, geology and topography on vegetation and soils of two grassland types in South Africa. African Journal of Range and Forage Science 23: 13–27. Wardle DA, Bardgett RD. 2004. Human-induced changes in large herbivorous mammal density: the consequences for decomposers. Frontiers in Ecology 2: 145–153. Wang T, Teague WR, Park SC. 2016. Evaluation of continuous and multipaddock grazing on vegetation and livestock performance – a modelling approach. Rangeland Ecology and Management 69:
457–464. Webber DF, Mickelson SK, Ahmed SI, Russell JR, Powers WJ, Schultz RC, Kovar JL. 2010. Livestock grazing and vegetative filter strip buffer effects on runoff sediment, nitrate, and phosphorus losses. Journal of Soil and Water Conservation 65: 34–41. Wolf EC, Cooper DJ, Hobbs NT. 2007. Hydrologic regime and herbivory stabilize an alternative state in Yellowstone National Park. Ecological Applications 17: 1572–1587. Wolf KM, Horney MR. 2016. Revisiting the rotational and continuous grazing system debate via meta-analysis. In: Wolf KM. Examinations of the ecology, management, and restoration of rangeland ecosystems. PhD thesis, University of California Davis, USA. pp 20–146. Woodward I. 2005. Modelling and theory. New Phytologist 165: 337–338. Wright HA, Bailey AW. 1982. Fire ecology. New York: John Wiley and Sons.
Received 28 January 2017, revised 30 April 2017, accepted 18 May 2017 Associate Editor: Kevin Kirkman
View publication stats