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United States Department of Agriculture

Agricultural Research Service


Location: Range Management Research

2011 Annual Report

1a. Objectives (from AD-416)
The goal of the research unit based at the Jornada Experimental Range (JER) is to develop ecologically based technologies for monitoring, remediation, and grazing management in desert environments. In order to achieve this goal, our overall research objective is to determine how biological (plant, animal, microbial), soil, and geomorphological processes interact across multiple spatial and temporal scales to affect soil development, soil stability, nutrient and water retention and acquisition, plant establishment and survival, and animal foraging behavior. Our ecologically based management technologies will be built from a knowledge of these processes. We will accomplish this objective by integrating short- and long-term experiments with a suite of tools (simulation modeling, geographic information systems [GIS], and remote sensing) to extrapolate information across spatial scales from individual plants to landscapes. Such an approach will enable us to accomplish four specific objectives and associated products: 1. Develop an integrated assessment and monitoring approach for vegetation structure and composition, soil stability, watershed function, and biotic integrity of spatially and temporally heterogeneous rangelands at landscape, watershed, and regional scales. 2. Identify key plant and soil processes, and environmental factors, such as landscape position, land use history, and climate, that influence the potential for remediation success. 3. Develop adaptive strategies for livestock management across multiple scales based on animal foraging behavior. 4. Predict responses of ecosystem dynamics and livestock distribution across time and space to changes in climate and other management-dependent and -independent drivers, and develop an integrated management, monitoring, and knowledge toolbox that can be easily applied by individuals with a range of management experience, from minimal to extensive.

1b. Approach (from AD-416)
We will build upon information collected since 1912, complemented with ongoing and new research, to address our objectives. We will integrate short- and long-term data sets with simulation modeling, geographic information systems, and remote sensing tools. Our approach will combine short-term experiments to test specific hypotheses with synthetic experiments requiring a more complex integration of ecosystem components and drivers. Objective 1 is shared among numerous collaborators where we are evaluating ground-based and remotely sensed indicators of ecosystem properties for use at multiple-spatial scales for effectiveness in monitoring resource conditions. Objective 2 is addressed by studies to identify areas within landscapes where stimulation of key processes will generate recovery of desired functions or control of undesired species. Objective 3 is addressed by (a) developing techniques that control animal movements on rangelands, (b) rapidly identifying botanical composition of livestock diets, and (c) identifying cattle breeds adapted to nutritional forage and environmental conditions of deserts. Objective 4 is shared by the National Science Foundation Long-Term Ecological Research project at the Jornada. Experimentation involves long-term studies of the effects of disturbances on ecosystem properties. For example, we have well-established studies that quantify pattern and control of primary productivity.

3. Progress Report
We made significant progress in developing management and monitoring strategies that conserve natural resources. State and transition models, ground-based indicators, and remote sensing technologies were developed that are currently being used by land managers and federal agencies to monitor rangeland status and change. Protocols for application of state-and-transition models were improved by integrating several data sources to enhance description of states, resulting in increased evaluation specificity for ecological responses to conservation practices (Objective 1A). Progress was made in development of ground based indicators: a new low-cost system was developed for monitoring vegetation and soil change. This simple method involving only a yardstick and a datasheet is currently being used for rural development projects in East Africa (Objective 1B). Unmanned Aircraft technology for remotely sensing and monitoring vegetation change was modified to improve resolution (Objective 1C). We made progress in quantifying key factors involved in remediation success (Objective 2). Plant/endophyte relationships that influence remediation potential of disturbed landscapes were identified and factors that influence recovery of heavily grazed grasses on sandy soils were determined. Progress was also made in examining the importance of landscape context and spatial connectivity to plant establishment and remediation success. Progress in assessing animal productivity under alternative management strategies was achieved (Objective 3). Progress was made in determining the role of plant chemistry in use of shrubs by small ruminants, use of GPS data to distinguish and quantify livestock behaviors, and comparing travel and behavior of British breeds to those of an arid-adapted breed of cattle (criollo) on rangelands. Progress was also made in predicting responses of vegetation to environmental change (Objective 4A). Model simulation of grass establishment under varied soil and vegetation conditions was used to identify areas with highest probability of successful grass recruitment during remediation efforts. Progress was also made in developing a range management toolbox (Objective 4B). A landscape toolbox website was established with information and directions for development and application of monitoring systems that is currently being used by land managers in the US and globally.

4. Accomplishments
1. Data-based concepts for ecological states. Descriptions of ecological states in state-and-transition models (STMs) are important for understanding the potential of a given site, but are often of limited use in the field. We used inventory data and data from long-term experiments and monitoring to define key elements needed to describe states in STMs and applied these criteria to dominant ecological sites in the Chihuahuan Desert. These criteria and examples will help define protocols used to develop STMs nationwide and make STMs more useful for evaluation of conservation practices (e.g., Conservation Effects Assessment Program; CEAP) because they are more specific with regard to predicted relationships between conservation actions and ecological responses.

2. Development and calibration of ground-based indicators of ecosystem processes. Cost-effective vegetation and soil measures are needed that are simple but reflect properties of complex ecosystems. A new monitoring system was developed that requires only a yardstick and a single datasheet to document changes in four classes of ecosystem properties. Comparisons with currently applied standard monitoring methods showed that comparable data can be generated. These methods are already being applied to US-supported rural development projects in East Africa and will be further adapted for use in the US.

3. Improved remote sensing technologies for monitoring vegetation patterns. High resolution remote sensing technologies are needed to monitor, assess, and manage rangeland vegetation. We recently improved our Unmanned Aircraft System (UAS) by adding a six-band multispectral camera to a consumer-grade high resolution camera. This modificaton improved our ability to distinguish different vegetation types and vegetation change while retaining our high spatial resolution capability of 6 cm (less than about 3 inches). A new plant phenology study was established at five Jornada test sites using UAS in conjunction with large area monitoring via Landsat (30-cm resolution). Aerial and ground-collected data comparisons improved our ability to select the appropriate remote sensors for phenological monitoring.

4. Quantify processes that affect arid land ecosystem dynamics. Microbial endophytes may enhance the ability of plants to survive and adapt to harsh desert environments. Microbial endophytes (microbes that live in plants) were found to influence plant productivity differently under varied moisture regimes. The endophytes tested were most beneficial to plant growth under drought conditions. Soil microbial genetic and functional diversity were compared across disturbance gradients (natural vs grazed or natural gas well pad). Microbial CO2 emission increased and community organization decreased with disturbance. Understanding how microbes affect plant ecology will aid in development of microbial-based technologies for arid land restoration.

5. Experimental examination of grass recovery. Grassland recovery on sandy, erosion-prone soils is believed to be constrained by landscape processes such as grazing. We used an existing long-term experiment to evaluate recovery patterns nine years after cessation of heavy grazing disturbance. Effects of grazing on grass cover were exacerbated by the presence of shrubs, but recovery was unaffected by shrubs. There was evidence that when grass cover decreases below 2% foliar cover that recovery is very slow, possibly increasing the likelihood of local grass extinction. Results indicate that grass recovery in sandy soils is possible with reduced grazing pressure. Results may promote restoration attempts in desert grasslands because grasses may be more resilient than managers and scientists previously thought.

6. Importance of landscape linkages for remediation success. Role of landscape context and connections among different land units in remediation efforts needs to be better understood to increase success rate. A new experiment was established to test the hypothesis that vegetation recovery can be initiated through the strategic installation of small barriers. Analyses indicate these small barriers create conditions necessary for seedling establishment and survival. Land managers can use these findings to implement site-specific strategies to promote plant establishment and improve soil and water resource retention.

7. Biochemical principles of shrub use by livestock. Shrubs such as juniper are high in nutrients but contain aversive chemicals that suppress intake by livestock. Methods are needed to optimize juniper intake by livestock. Animal species and density may affect the amount of shrubs consumed. Effects of high vs low stocking density of goats alone or in combination with sheep were examined. Goats in the high density treatment ate more juniper and spent more time browsing juniper and less time grazing herbaceous vegetation than goats under low stocking density. The mixed species treatment ate more herbaceous vegetation than goats alone. The greatest frequency of heavy juniper defoliation and sapling debarking occurred with the mixed species/high density treatment. Animal density and species combinations can both affect behaviors that alter utilization of juniper saplings by goats.

8. Free-ranging cattle behavior. Spatial and temporal use of landscapes by foraging livestock is crucial information for producers to match animal location with areas of optimal nutrition. Foraging behavior and travel activity of cows fitted with GPS devices were recorded visually and integrated with GPS data collected during the same intervals. GPS data were successfully characterized with observational data and mean rate of travel was determined for different behaviors. Knowledge of animal activity can help managers predict spatial and temporal distribution of grazing livestock and facilitate proactive management by allowing producers to match timing of use with optimal forage conditions.

9. Arid adapted livestock breeds. Criollo cattle co-evolved with arid landscapes and our previous work indicated they require fewer external inputs and have lower supplementation costs than traditional breeds on southwestern rangelands. In addition to smaller frame size and lower forage requirements, criollo were found to spend less time grazing and to travel farther per day and farther from water than Angus-cross cattle. The larger home range and wider habitat range of criollo compared to traditional British breeds may give them a competitive advantage in harsh desert environments and reduce their impact on a given location within the landscape.

10. Simulation modeling of grass establishment under varied conditions. Tools are needed to integrate our knowledge base in order to predict grass recruitment and vegetation change. A model was used to simulate the probability of recruitment of perennial grasses into areas devoid of a particular grass species for selected vegetation-soil locations across the Jornada under different precipitation regimes. Recruitment was affected primarily by soil properties interacting with vegetation state (grassland or shrubland). Results can be used to strategically determine locations best suited for endophyte studies linked to grass remediation.

11. Integrated management, monitoring, and knowledge toolbox. An integrated suite of improved tools is needed to facilitate the synthesis, integration, and application of new and existing research. A "landscape toolbox" website was established that includes a "monitoring methods guide" and access to a broad array of information and knowledge necessary to design and implement effective monitoring systems. The toolbox is being regularly consulted by large numbers of individuals throughout the world, including many US land managers, increasing their ability to cost-effectively collect and interpret management-relevant data.

Review Publications
Davidson, A.D., Ponce, E., Lightfoot, D.C., Fredrickson, E.L., Brown, J.H., Cruzado, J., Toledo, D.N., Brantley, S.L., Sierra, R., Lisk, R., Ceballos, G. 2010. Rapid response of a grassland ecosystem to an experimental manipulation of a keystone rodent and domestic livestock. Ecology. 91(11):3189-3200.

Herrick, J.E., Lessard, V.C., Spaeth, K.E., Shaver, P.L., Dayton, R.S., Pyke, D.A., Jolley, L., Goebel, J. 2010. National ecosystem assessments supported by scientific and local knowledge. Frontiers in Ecology and the Environment. 8(8):403-408.

Peters, D.C. 2010. Accessible ecology: Synthesis of the long, deep, and broad. Trends in Ecology and Evolution. 25(10):592-601.

Herrick, J.E., Van Zee, J.W., Belnap, J., Johansen, J.R., Remmenga, M. 2010. Fine gravel controls hydrologic and erodibility responses to trampling disturbance for coarse-textured soils with weak cyanobacterial crusts. Catena. 83:119-126.

Anderson, D.M., Danielson, T.L., Obeidat, S.M., Rayson, G.D., Estell, R.E., Bai, B., Fredrickson, E.L. 2011. Differentiating among plant spectra by combining pH dependent photoluminescence spectroscopy with multi-way principal component analysis (MPCA). The Open Agriculture Journal. 5:1-9.

Laliberte, A.S., Rango, A. 2011. Image processing and classification procedures for analysis of sub-decimeter imagery acquired with an unmanned aircraft over arid rangelands. GIScience and Remote Sensing. 48(1):4-23.

Estell, R.E. 2010. Coping with shrub secondary metabolites by ruminants. Small Ruminant Research. 94:1-9.

Duniway, M.C., Herrick, J.E. 2011. Disentangling road network impacts: The need for a holistic approach. Journal of Soil and Water Conservation. 66(2):31A-36A.

Lucero, M.E., Unc, A., Cooke, P., Dowd, S., Sun, S. 2011. Endophyte microbiome diversity in micropropagated Atriplex canescens and Atriplex torreyi var griffithsii. PLoS One. 6(3):e17693.

Karl, J.W., Herrick, J.E. 2010. Monitoring and assessment based on ecological sites. Rangelands. 32(6):60-64.

Whitford, W.G., Steinberger, Y. 2010. Herbivore-plant interactions and desertification in arid lands. In: Seckback, J., Dubinsky, Z., editors. All Flesh is Grass. Springer-Verlag Publishing. p. 239-256.

Moseley, K., Shaver, P., Sanchez, H., Bestelmeyer, B.T. 2010. Ecological site development: A gentle introduction. Rangelands. 32(6):16-22.

Duniway, M.C., Bestelmeyer, B.T., Tugel, A.J. 2010. Soil processes and properties that distinguish ecological sites and states. Rangelands. 32(6):9-15.

Bestelmeyer, B.T., Moseley, K., Shaver, P., Sanchez, H., Briske, D., Fernandez-Gimenez, M. 2010. Practical guidance for developing state-and-transition models. Rangelands. 32(6):23-30.

Peinetti, H.R., Fredrickson, E.L., Peters, D.C., Cibils, A.F., Roacho-Estrada, J., Laliberte, A. 2011. Foraging behavior of heritage versus recently introduced herbivores on desert landscapes of the American Southwest. Ecosphere. 2(5):Article 57.

Rango, A., Laliberte, A., Herrick, J.E., Winters, C., Havstad, K.M., Steele, C., Browning, D.M. 2009. Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management. Journal of Applied Remote Sensing (JARS). 3(1):033542.

Rango, A., Laliberte, A. 2010. Impact of flight regulations on effective use of unmanned aircraft systems for natural resources pplications. Journal of Applied Remote Sensing (JARS). 4:043539.

Browning, D.M., Laliberte, A.S., Rango, A. 2011. Temporal dynamics of shrub proliferation: Linking patches to landscapes. International Journal of Geographical Information Science. 25(6):913-930.

Laliberte, A.S., Browning, D.M., Herrick, J.E., Gronemeyer, P. 2010. Hierarchical object-based classification of ultra-high-resolution digital mapping camera (DMC) imagery for rangeland mapping and assessment. Journal of Spatial Science. 55(1):101-115.

Bestelmeyer, B.T., Goolsby, D., Archer, S.R. 2011. Spatial perspectives in state-and-transition models: A missing link to land management? Journal of Applied Ecology. 48:746-757.

Duniway, M.C., Herrick, J.E., Pyke, D., Toledo, D.N. 2010. Assessing transportation infrastructure impacts on rangelands: Test of a standard rangeland assessment protocol. Rangeland Ecology and Management. 63:524-536.

Lujan, A.L., Utsumi, S.A., Smallidge, S.T., Baker, T.T., Estell, R.E., Cibils, A.F., Ivey, S.L. 2010. Manipulating sheep browsing levels on coyote willow (Salix exigua) with supplements. Sheep and Goat Research Journal. 25:32-38.

Bestelmeyer, B.T., Brown, J.R. 2010. An introduction to the special issue on ecological sites. Rangelands. 32(6):3-4.

Browning, D.M., Duniway, M.C. 2011. Digital soil mapping in the absence of field training data: A case study using terrain attributes and semiautomated soil signature derivation to distinguish ecological potential. Applied and Environmental Soil Science. 2011, Article ID 421904:1-12.

Whitford, W.G., Steinberger, Y. 2010. Pack rats (Neotoma spp.): Keystone ecological engineers? Journal of Arid Environments. 74:1450-1455.

Okin, G.S. 2010. The contribution of brown vegetation to vegetation dynamics. Ecology. 91(3):743-755.

Whitford, W.G., Steinberger, Y. 2011. Effects of simulated storm sizes and nitrogen on three Chihuahuan Desert perennial herbs and a grass. Journal of Arid Environments. 75:861-864.

Brown, J.R., Macleod, N. 2011. A site-based approach to delivering rangeland ecosystem services. The Rangeland Journal. 33:99-108.

Burkett, L.M., Bestelmeyer, B.T., Tugel, A. 2011. A field guide to pedoderm and pattern classes. Field Guide Handbook. Version 1.1. Jornada Experimental Range, Las Cruces, NM, 59 p.

Wang, Z., Jiao, S., Han, G., Zhao, M., Willms, W.D., Hao, X., Havstad, K.M. 2011. Impact of stocking rate and rainfall on sheep performance in a desert steppe. Rangeland Ecology and Management. 64(3):249-256.

Peters, D.C., Gosz, J., Collins, S. 2009. Boundary dynamics in landscapes. In: Levin, S.A., editor. The Princeton Guide to Ecology. Princeton, NJ:Princeton University Press. p. 458-463.

Brown, J.R., Bestelmeyer, B.T. 2008. Resolving critical issues for the development of ecological site descriptions: Summary of a symposium. Rangelands. 30(4):16-18.

Lucero, M.E., Estell, R.E., Tellez, M., Fredrickson, E.L. 2009. A retention index calculator simplifies identification of plant volatile organic compounds. Phytochemical Analysis. 20:378-384.

Kilgore, A., Jackson, E., Whitford, W. 2009. Fire in Chihuahuan Desert grassland: Short-term effects on vegetation, small mammal populations, and faunal pedoturbation. Journal of Arid Environments. 73:1029-1034.

Browning, D.M., Archer, S.R. 2011. Protection from livestock fails to deter shrub proliferation in a desert landscape with a history of heavy grazing. Ecological Applications. 21(5):1629-1642.

Laliberte, A.S., Winters, C.D., Rango, A. 2011. UAS remote sensing missions for rangeland applications. Geocarto International. 26(2):141-156.

Skaggs, R., Edwards, Z., Bestelmeyer, B.T., Wright, J.B., Williamson, J., Smith, P. 2011. Vegetation maps at the passage of the Taylor Grazing Act (1934): A baseline to evaluate rangeland change after a regime shift. Rangelands. 33(1):13-19.

Baddock, M.C., Zobeck, T.M., Van Pelt, R.S., Fredrickson, E.L. 2011. Dust emissions from undisturbed and disturbed, crusted playa surfaces: cattle trampling effects. Aeolian Research. 3(1):31-41.

Eldridge, D.J., Whitford, W.G., Duval, B.D. 2009. Animal disturbances promote shrub maintenance in a desertified grassland. Journal of Ecology. 97:1302-1310.

Peters, D.C. 2011. Globalization: Ecological consequences of global-scale connectivity in people, resources and information. In: Pachura, P., editor. The Systemic Dimension of Globalization. InTech Publisher. p. 211-232.

Peters, D.C., Lugo, A.E., Chapin, III, F., Pickett, S.T., Duniway, M.C., Rocha, A., Swanson, F., Laney, C., Jones, J. 2011. Cross-system comparisons elucidate disturbance complexities and generalities. Ecosphere. 2(7):Article 81.

Whitford, W.G., Barness, G., Steinberger, Y. 2008. Effects of three species of Chihuahuan Desert ants on annual plants and soil properties. Journal of Arid Environments. 72:392-400.

Karl, J.W., Colson, K., Swartz, H. 2011. Rangeland assessment and monitoring methods suide - an interactive tool for selecting methods for assessment and monitoring. Rangelands. 33(4):48-54.

Toevs, G., Karl, J.W., Taylor, J., Spurrier, C., Karl, M., Bobo, M., Herrick, J.E. 2011. Consistent indicators and methods and a scalable sample design to meet assessment, inventory, and monitoring information needs across scales. Rangelands. 33(4):14-20.

Karl, J.W. 2011. Turning information into knowledge for rangeland management. Rangelands. 33(4):3-5.

Courtright, E., Van Zee, J.W. 2011. The database for inventory, monitoring and assessment (DIMA). Rangelands. 33(4):21-26.

Riginos, C., Herrick, J.E., Sundaresan, S.R., Farley, C., Belnap, J. 2011. A simple graphical approach to quantitative monitoring of rangelands. Rangelands. 33(4):6-13.

Schrader, T.S., Duniway, M.C. 2011. Image interpreter tool: An ArcGIS tool for estimating vegetation cover from high-resolution imagery. Rangelands. 33(4):35-40.

Last Modified: 05/28/2017
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