@conference {JRN55399, title = {An evaluation of soil heterogeneity and representativeness within and across sites in the NEON network}, booktitle = {ESA - August 2021 meeting -Virtual}, year = {2021}, month = {3/1/2021}, abstract = {Background/Question/Methods The National Ecological Observatory Network (NEON) provides coincident hierarchical and ecologically meaningful measurements made at diverse U.S. ecosystems designed to answer key ecological questions at the national scale. Comprehensive soil properties are critical to characterize the geomorphic template at NEON sites from which the multi-scale and -taxa ecological observations arise. Physical and chemical soil properties play an important role in ecosystem function; spatial variation in soil physical and chemical properties is expected to influence ecosystem dynamics, nutrient cycling and myriad ecological processes. We report on a standardized, nationwide soil characterization effort at NEON terrestrial sites designed to describe how soils vary within and among NEON sites and to provide contextual information to support the long-term biodiversity sampling program. Sampling for the NEON soils characterization project was done at distributed plots at 46 of 47 terrestrial NEON sites via a modified stratified sampling design. In addition to broadly describing these soils data for the ecological community, we posed the following questions: How representative are NEON distributed soil pedons of soils in the surrounding landscapes?; and how does variability in soil properties within NEON sites range across the network? Results/Conclusions~ NRCS soil scientists collected and processed samples for 715 pedons constituting 3,246 horizons across the NEON network. Eleven of twelve soil orders were identified from the described pedons, with only Oxisols (a tropical soil) absent from the network. A total of 560 pedons were described from soil pits with the remaining 155 described from soil cores. Of the 3,246 horizons, 10.4\% were classified as organic horizons, with the remaining mineral horizons comprising top soil (A, 26.8\%), eluviated horizons (E, 6.8\%), subsoil (B, 48.7\%), parent material (C, 18\%), and bedrock (R, 2.1\%). The distributed pedons vary in how closely the descriptions correspond with existing Soil Survey data. Similarity in soils beyond NEON site boundaries ranged from highest coincidence in the Mid-Atlantic, Central and Northern Plains domains to lower correspondence in the western U.S. and Tundra and Taiga domains in Alaska. Alaska{\textquoteright}s low correspondence is due to missing data where soils have not been mapped. High agreement areas have either more similarly described NEON soils (as in the mid-Atlantic region) or more homogenous mapped soils (as in the Great Plains). Regions of low correspondence between NEON soils and the surrounding area represent an opportunity for future exploration through NEON{\textquoteright}s relocatable sites or collaborative projects with outside researchers. }, author = {Dawn M. Browning and Stanish, Lee F. and S. W. Salley and Dave Kinsbury and David L. Hoover} } @article {JRN55316, title = {Monitoring agroecosystem productivity and phenology at a national scale: A metric assessment framework}, journal = { Ecological Indicators}, volume = {131}, year = {2021}, month = {8/27/2021}, chapter = {108147}, abstract = {Effective measurement of seasonal variations in the timing and amount of production is critical to managing spatially heterogeneous agroecosystems in a changing climate. Although numerous technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) network and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in croplands, grazing lands, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat satellite, Landsat NDVI, and vegetation greenness (Green Chromatic Coordinate, GCC) from tower-mounted PhenoCams for 2017 and 2018. Overall, our analysis compared production dynamics estimated from three independent ground and remote platforms using data for 34 agricultural sites constituting 51 site-years of co-located time series. Pairwise sensor comparisons across all four metrics revealed stronger correlation and lower root mean square error (RMSE) between end of season (EOS) dates (Pearson R ranged from 0.6 to 0.7 and RMSE from 32.5 to 67.8) than start of season (SOS) dates (0.46 to 0.69 and 40.4 to 66.2). Overall, moderate to high correlations between SOS and EOS metrics complemented one another except at some lower productivity grazing land sites where estimating SOS can be challenging. Growing season length estimates derived from 16-day satellite GPP (179.1 days) were significantly longer than those from PhenoCam GCC (70.4 days, padj < 0.0001) and EC GPP (79.6 days, padj < 0.0001). Landscape heterogeneity did not explain differences in SOS and EOS estimates. Annual integrated estimates of productivity from EC GPP and PhenoCam GCC diverged from those estimated by Landsat GPP and NDVI at sites where annual production exceeds 1000 gC/m-2 yr-1. Based on our results, we developed a {\textquotedblleft}metric assessment framework{\textquotedblright} that articulates where and how metrics from satellite, eddy covariance and PhenoCams complement, diverge from, or are redundant with one another. The framework was designed to optimize instrumentation selection for monitoring, modeling, and forecasting ecosystem functioning with the ultimate goal of informing decision-making by land managers, policy-makers, and industry leaders working at multiple scales.}, keywords = {Agricultural management, eddy covariance, GPP, Growing season length, indicators, LandsatPhenoCam, Long-Term Agroecosystem Research (LTAR) network, Sustainable agriculture}, doi = {10.1016/j.ecolind.2021.108147}, url = {files/bibliography/21-031.pdf}, author = {Dawn M. Browning and Eric S. Russell and Guillermo E. Ponce-Campos and N. E. Kaplan and Andrew D. Richardson and Bijan Seyednasrollah and S. Spiegal and Nicanor Z. Saliendra and Joseph G. Alfieri and J. M. Baker and Carl Bernacchi and Brandon T Bestelmeyer and David D. Bosch and Elizabeth H. Boughton and Raoul K. Boughton and Patrick E. Clark and Gerald N. Flerchinger and Nuria Gomez-Casanovas and Sarah Goslee and Nick Haddad and David L. Hoover and Abdullah Jaradat and Marguerite Mauritz and Gregory McCarty and Gretchen R. Miller and John Sadler and Amartya Saha and R.L. Scott and Andrew Suyker and Craig Tweedie and Jeffrey D. Wood and Xukai Zhang and Shawn D. Taylor} } @conference {JRN55400, title = {Where management and climate variability matter most: An evaluation of metrics for monitoring agroecosystem production and phenology}, booktitle = {2021 Fall Meeting of the American Geophysical Union}, year = {2021}, month = {8/5/2021}, abstract = {Effective measurement of seasonal variations in the timing and amount of production are critical to managing spatially heterogeneous agroecosystems in a changing climate. Although many technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in 34 cropland, grazingland, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat satellite, Landsat NDVI, and vegetation greenness (Green Chromatic Coordinate, GCC) from tower-mounted PhenoCams for 2017 and 2018. We analyzed production dynamics estimated from three independent ground and remote platforms for 51 site-years of co-located time series. We found that when similar methods were applied across the four metrics, pairwise sensor comparisons revealed stronger correlation and lower root mean square error (RMSE) between end of season (EOS) dates (Pearson R ranged from 0.6 to 0.7 and RMSE from 32.5 to 67.8) than start of season (SOS) dates (0.46 to 0.69 and 40.4 to 66.2). Overall, moderate to high correlations between SOS and EOS metrics complemented one another except at some lower productivity grazingland sites where estimating SOS can be challenging and inter-annual variability in production is high. Growing season length estimates derived from 16-day Satellite GPP (179.1 days) were significantly longer than those from PhenoCam GCC (70.4 days, padj < 0.0001) and EC GPP (79.6 days, padj < 0.0001). Landscape heterogeneity did not explain differences in SOS and EOS estimates. Annual integrated estimates of productivity from EC GPP and PhenoCam GCC diverged from those estimated by Landsat GPP and NDVI at sites where annual production exceeds 1000 gC m-2 yr-1. We identified production systems where management and climate variability mattered most and offered ideas we feel can advance our capacity to better integrate management decision-making into long- and short-term forecasting for drought and climate scenarios at multiple spatial scales.}, author = {Dawn M. Browning and Eric S. Russell and Guillermo E. Ponce-Campos and N. E. Kaplan and Andrew D. Richardson and Bijan Seyednasrollah and S. Spiegal and Nicanor Z. Saliendra and Joseph G. Alfieri and J. M. Baker and Carl Bernacchi and Brandon T Bestelmeyer and David D. Bosch and Elizabeth H. Boughton and Raoul K. Boughton and Patrick E. Clark and Gerald N. Flerchinger and Nuria Gomez-Casanovas and Sarah Goslee and Nick Haddad and David L. Hoover and Marguerite Mauritz and Gretchen R. Miller and John Sadler and Amartya Saha and Russell L. Scott and Andrew Suyker and Craig Tweedie and Jeffrey D. Wood and Xukai Zhang and Shawn D. Taylor} } @conference {JRN55244, title = {Climate and phenology network synergies for sustainable agriculture}, booktitle = {Ecological Society of America}, year = {2020}, month = {08/2020}, address = {Virtual Conference}, abstract = {Agricultural producers face multiple challenges in a consistently changing climate and managed agroecosystems pose a challenge for broad-scale forecasts for yield given myriad cropping and management scenarios. There is a pressing need for integrative frameworks to support and inform management strategies that adapt to climate change for a diverse set of stakeholders. We use phenology {\textendash} the study of seasonal patterns in plant productivity {\textendash} to examine historical and current responses to regional climate in the continental U.S. We identify opportunities and knowledge gaps through case studies that involve data products from multiple research and observational networks. Poster $\#$ 82205.}, author = {Dawn M. Browning and Shawn D. Taylor} } @article {JRN55095, title = {Plant phenology: Taking the pulse of rangelands}, journal = {Rangelands}, volume = {41}, year = {2019}, month = {06/2019}, pages = {129-134}, chapter = {129}, abstract = {Plant phenology{\textemdash}the timing of seasonal life cycle events{\textemdash}is a primary control on ecosystem productivity and an integrative indicator of species{\textquoteright} responses to the environment. Plant phenology data can be used to design better management systems by adjusting the timing of grazing, fire and other disturbances relative to the growth stage of key species and in planning restoration activities such as herbicide applications or targeted grazing. Repeated observations needed to understand phenology can be collected at various spatial scales with a variety of methods from field-based observations of individual plants to broad-scale observations of landscape {\textquotedblleft}greenness{\textquotedblright} from satellite imagery. Digital cameras mounted on towers (phenocams) provide a more cost-effective way to collect data to capture vegetation {\textquotedblleft}greenness.{\textquotedblright} Phenocam greenness values are used to generate plant canopy- and community-level metrics in real-time for a fraction of the cost of on-the-ground field observations. Phenocam greenness metrics also serve to link plant- or community-scale phenology observations collected in the field with those from satellite remote sensing and can reveal the plant species or functional groups contributing to satellite NDVI. Phenocam image time series also help interpret rangeland monitoring data by placing data in the context of inter- and intra-annual variability.}, keywords = {grasslands, invasive species, management tools, monitoring, phenocams, plant phenology}, doi = {doi.org/10.1016/j.rala.2019.02.001}, url = {files/bibliography/19-011.pdf}, author = {Dawn M. Browning and K. A. Snyder and Jeffrey E. Herrick} } @article {JRN54890, title = {Integrating space and time: A case for phenological context in grazing studies and management}, journal = {Frontiers of Agricultural Science and Engineering}, volume = {5}, year = {2018}, month = {03/2018}, pages = {44-56}, chapter = {44}, abstract = {

In water-limited landscapes, patterns in primary production are highly variable across space and time. Livestock grazing is a common agricultural practice worldwide and a concern is localized overuse of specific pasture resources that can exacerbate grass losses and soil erosion. On a research ranch in New Mexico (MAP = 217 mm), we demonstrate with a quantitative approach that annual seasons vary greatly and examine foraging patterns in Angus-Hereford (Bos taurus) cows. We define five seasonal stages based on MODIS NDVI: Pre-Greenup, Greenup, Peak Green, Drydown, and Dormant and examine livestock movements in 2008. Daily distance traveled by cows was greater and foraging area expanded during periods with higher precipitation. A regression model including minimum NDVI, rainfall, and NDVI*rainfall explained 81\% of the seasonal variation in distance traveled by cows (P \< 0.01). Cows explored a daily average 81.1 ha while foraging but tended to explore smaller areas as the pasture became greener (Greenup, Peak Green). Cows foraged an average 9.7 hours daily and spent more time foraging as pastures became greener. Our findings suggest that phenological context can expand the capacity to compare and integrate findings and facilitate meta-analyses of grazing studies conducted at different locations and times of year.

}, keywords = {GPS collars, Jornada Experimental Range, land-surface phnology, livestock movement, LTAR, MODIS NDVI, rangeland}, doi = {10.15302/j-FASE-2017193}, url = {files/bibliography/18-006.pdf}, author = {Dawn M. Browning and S. Spiegal and Richard E. Estell and Andr{\'e}s F. Cibils and H. Raul Peinetti} } @conference {JRN54941, title = {Phenocams bridge the gap between field and satellite observations: Applications from agroecosystems}, booktitle = {US-International Association for Landscape Ecology}, year = {2018}, month = {04/2018}, address = {Chicago, Illinois}, abstract = {

Agro-ecosystems represent a gap in national research networks established to address ecological questions that site-level research cannot address. The Long-Term Agroecosystem Research (LTAR) network established by the U.S.D.A. Agriculture Research Service is intended to fill this gap. In this study, we combine data from two LTAR network sites in the arid southwestern U.S. spanning 18 site-years to evaluate relationships between greenness index values derived from near-surface phenocams (GCC) and MODIS satellite imagery (NDVI) with measures of ecosystem productivity. Two core data sets for sites in the LTAR network are aboveground net primary production (ANPP) estimated in the field and gross primary production (GPP) modeled from eddy covariance flux towers. We explore relationships between remotely-derived greenness using camera GCC and MODIS NDVI indices and ANPP and GPP from 2013 to 2016. We used ANPP at three camera sites on the Jornada Experimental Range (JER) in southern New Mexico and GPP at two camera sites at the Walnut Gulch Experimental Watershed (WGEW) in southern Arizona. We calculated pairwise Pearson correlations between growing season integrals of GPP derived from CO2 flux measurements and remotely-sensed indicators (camera GCC and NDVI) at the two WGEW sites. At JER, we calculated correlations between ANPP and growing season integrals of GCC and NDVI. Our analysis showcases methods for comparing ANPP computed annually and GPP estimated daily with time series GCC and NDVI. As LTAR site locations accumulate phenocam imagery, analyses will be expanded across the network to quantitatively evaluate the role of growing season dynamics and climate on primary productivity in agro-ecosystems.

}, author = {Dawn M. Browning and Ponce Campos, Guillermo and R.L. Scott and Debra C. Peters} } @article {JRN54924, title = {Synchronous species responses reveal phenological guilds: implications for management}, journal = {Ecosphere}, volume = {9}, year = {2018}, month = {09/2018}, pages = {1-23}, chapter = {1}, abstract = {

Phenological studies are critical for understanding the ability of terrestrial ecosystems to respond to changes in climate. Monitoring seasonal transitions at the species or community level across large areas is challenging and expensive. One approach for lowering costs is to identify phenological guilds{\textemdash}groups of species that exhibit similar timing of seasonal transitions{\textemdash}and limit monitoring to a smaller number of species within a guild. In this study, we evaluated 23 consecutive years of monthly observations of individual species at 15 long-term study sites at the Jornada Basin USDA-Long-Term Ecological Research site to identify patterns in the onset of three phenophases{\textemdash}leaf-out, flower, and fruit{\textemdash}of 16 widely occurring species in the arid southwestern United States and to investigate the existence of phenological guilds. We conducted univariate analyses of distributions in the timing of leaf, flower, and fruit production across time and space and multivariate cluster analysis of the time series to identify coherent groups of species{\textendash}site instances that exhibit coherence in timing of phenophase onsets (i.e., guilds). The six species of C3 shrubs demonstrated greater consistency in timing of all phenophases relative to C4 grasses. Further, we found that in all species, leaf-out occurred prior to the onset of the summer monsoon rains. Cluster analysis revealed six groups of species{\textendash}site observations demonstrating high within-year concordance in timing of leaf-out and first fruit across variable site conditions and rainfall years. The six groups for timing of first fruit differed from those for first leaf in that they exhibited greater multi-species membership and within-year variability in timing. We propose that use of phenological guilds can improve the efficiency of ecosystem monitoring, predictive models of ecosystem cues driving phenological events, and land management outcomes.

}, keywords = {Chihuahuan Desert, drylands, first fruit, first leaf, long-term ecological research, pattern recognition, phenological functional group, plant phenology, Special Feature: Dynamic Deserts, start of season}, doi = {doi.org/10.1002/ecs2.2395}, url = {files/bibliography/18-017.pdf}, author = {Dawn M. Browning and Theresa Crimmins and D. K. James and S. Spiegal and Matthew Levi and John P. Anderson and Debra C. Peters} } @article {JRN54808, title = {Breaks in MODIS time series portend vegetation change: verification using long-term data in an arid grassland ecosystem}, journal = {Ecological Applications}, volume = {27}, year = {2017}, month = {07/2017}, pages = {1677-1693}, chapter = {1677}, abstract = {

Frequency and severity of extreme climatic events are forecast to increase in the 21st century. Predicting how managed ecosystems may respond to climatic extremes is intensified by uncertainty associated with knowing when, where, and how long effects of the extreme events will be manifest in the ecosystem. In water-limited ecosystems with high inter-annual variability in rainfall, it is important to be able to distinguish responses that result from seasonal fluctuations from long-term increases or decreases in rainfall. A tool that successfully distinguishes seasonal from directional biomass responses in the long-term trend would allow land managers to make informed decisions during extreme climatic events. We leveraged long-term observations (2000-2013) of quadrat-level plant biomass at multiple locations across a semi-arid landscape in southern New Mexico to verify the use of NDVI time-series derived from 250-m MODIS data as a proxy for changes in above-ground productivity. This time period encompassed years of sustained drought (2000-2003) and record-breaking high rainfall (2006 and 2008) followed by subsequent drought years (2011 through 2013) that resulted in a restructuring of plant community composition in some locations. Our objective was to decompose vegetation patterns derived from MODIS NDVI over this period into contributions from: (1) the long-term trend, (2) seasonal cycle, and (3) unexplained variance using the Breaks For Additive Season and Trend (BFAST) model. BFAST breakpoints in NDVI trend and seasonal components were verified with field-estimated biomass at 15 sites ranging in species diversity, vegetation cover, and soil properties. We found that 42 of 45 breaks in NDVI trend reflected large changes in mean biomass and 16 of 19 seasonal breaks accompanied changes in the contribution to biomass by perennial and/or annual grasses. The BFAST method using satellite imagery proved useful for detecting previously reported ground-based changes in vegetation in this arid ecosystem. We demonstrate that time-series analysis of NDVI data holds potential for monitoring landscape condition in arid ecosystems at the large spatial scales needed to differentiate responses to a changing climate from responses to seasonal variability.

}, doi = {10.1002/eap.1561}, url = {files/bibliography/17-026_0.pdf}, author = {Dawn M. Browning and Jonathan Maynard and Jason W. Karl and Debra C. Peters} } @article {JRN54829, title = {Phenocams bridge the gap between field and satellite observations in an arid grassland ecosystem}, journal = {Remote Sensing of Environment}, volume = {9, 1071}, year = {2017}, month = {10/2017}, abstract = {

Near surface (i.e., camera) and satellite remote sensing metrics have become widely used indicators of plant growing seasons. While robust linkages have been established between field metrics and ecosystem exchange in many land cover types, assessment of how well remotely-derived season start and end dates depict field conditions in arid ecosystems remain unknown. We evaluated the correspondence between field measures of start (SOS; leaves unfolded and canopy greenness \> 0) and end of season (EOS) and canopy greenness for two widespread species in southwestern U.S. ecosystems with those metrics estimated from near-surface cameras and MODIS NDVI for five years (2012-2016). Using the Timesat software to estimate SOS and EOS from the phenocam green chromatic coordinate (GCC) greenness index resulted in good agreement with ground observations for honey mesquite but not black grama. Despite differences in the detectability of SOS and EOS for the two species, GCC was significantly correlated with field estimates of canopy greenness for both species throughout the growing season. MODIS NDVI for this arid grassland site was driven by the black grama signal although a mesquite signal is discernable in average rainfall years. Our findings suggest phenocams could help meet myriad needs in natural resource management.

}, doi = {doi:10.3390/rs9101071}, url = {files/bibliography/17-027.pdf}, author = {Dawn M. Browning and Jason W. Karl and Moran, David and Andrew D. Richardson and Craig Tweedie} } @conference {JRN54798, title = {Watching grass grow: Successes and limitations of image-based methods for monitoring grassland phenology}, booktitle = {12th International Congress of Ecology INTECOL 2017}, year = {2017}, month = {08/2017}, publisher = {International Congress of Ecology INTECOL }, organization = {International Congress of Ecology INTECOL }, address = {Beijing, China}, abstract = {

Seasonal changes in aboveground primary production (i.e. phenology) are influenced by environmental conditions with implications for land-atmosphere interactions, carbon cycling, and agricultural production. Monitoring phenology and quantifying seasonal patterns across spatially extensive grasslands and savannas require cost-effective, consistent, and accurate approaches for detecting changes in the growing season. Remotely sensed imagery offers capabilities to quantify growing season metrics via vegetation indices that have been linked to biomass and forage and net primary production. However, in many water-limited ecosystems contributions of exposed soil due to modest vegetation cover and susceptibility of vegetation to drought challenge these biophysical retrievals using moderate- and coarse-resolution satellite imagery. This challenge emphasizes the importance of verifying seasonal metrics derived from remotely sensed imagery (e.g., start, end, and length of growing season and timing of peak greenness) to identify limitations and uncertainty of said metrics used to forecast plant responses to climate and estimate biomass accrual and crop yields. We collected and evaluated data at multiple spatial and temporal scales from 2012 through 2016 to quantify the degree of correspondence between field and remotely sensed growing season metrics. This study was conducted at an ungrazed desert grassland site in southern New Mexico. Weekly field observations of plant phenology and canopy greenness were compared with metrics derived from MODIS satellite imagery and near-surface digital cameras (hereafter {\textquotedblleft}phenocams{\textquotedblright}). MODIS 250-m NDVI vegetation index data are acquired every 16 days while color images are acquired daily from phenocams mounted at a height of ca 6 meters providing data at finer spatial and temporal scales that those from satellite. In addition, phenocams offer the opportunity to identify individual plants in the image to extract species-specific patterns in greenness. Growing season metrics from both types of imagery were derived using Timesat software (v3.2).
Phenocam greenness curves for individual species indicated rapid canopy development for the widespread deciduous mesquite shrub (Prosopis glandulosa) over 14 to 16 d in the spring (April to May) whereas peaks in greenness for the dominant perennial black grama grass (Bouteloua eriopoda) occur with warm season rainfall in July. Weekly field estimates of canopy development were significantly correlated with greenness index values from phenocams for mesquite (r = 0.735) and black grama (r = 0.609). Start and end dates for growing season derived from MODIS NDVI corresponded well with phenocam greenness representing the landscape (R2 = 0.691) with better fit for end of season. These data demonstrate the utility of phenocams for reliably depicting species-specific patterns in phenology in this arid grassland although uncertainty with start of season for black grama was less than that for mesquite. The ability to distinguish contributions to landscape greenness between C3 shrubs and C4 grasses can dramatically enhance landscape monitoring efforts over spatially extensive grasslands and savannas where field monitoring is not feasible large areas. Future research will include additional grassland sites using image data from the Phenocam Network and online analytical tools that are in development to bolster opportunities to bridge satellite, camera, and field data to quantify and predict ecosystem productivity.

}, author = {Dawn M. Browning} } @article {JRN54146, title = {Emerging technological and cultural shifts advancing drylands research and management}, journal = {Frontiers in Ecology and the Environment}, volume = {13}, year = {2015}, month = {02/2015}, pages = {52-60}, chapter = {52}, abstract = {

Sustainable management of arid landscapes is complicated by extreme conditions that constrain biological responses to perturbation, great spatial complexity, and uncertain degrees of ecosystem resilience to climate change. Traditional approaches to the collection, management, and analysis of data from dryland monitoring efforts should consider these complications. Over the past century, research on drylands has gradually transitioned from short-term, plot-scale studies to long-term, regional- and biome-scale efforts. Two thresholds are imminent: a technological tipping point that will facilitate performing novel science using new techniques to collect, manage, and analyze data, and a cultural tipping point, where various research products are shared more freely and through different communication pathways. A new framework could be developed by promoting interdisciplinary collaboration and implementing standardized practices regarding data collection, curation, and sharing.

}, keywords = {cultural tipping point, dryland management, emerging technology, ryland research, sustainable management, technological tipping point}, doi = {10.1890/140161}, url = {/files/bibliography/15-007.pdf}, author = {Dawn M. Browning and A. Rango and Jason W. Karl and C. Laney and Enrique Vivoni and Craig Tweedie} } @article {JRN54096, title = {Spatial patterns of grassland-shrubland state transitions: a 74-year record on grazed and protected areas}, journal = {Ecological}, volume = {24}, year = {2014}, month = {09/2014}, pages = {1421-1433}, chapter = {1421}, abstract = {

Tree and shrub abundance has increased in many grasslands, causing changes in ecosystem carbon and nitrogen pools that are related to patterns of woody plant distribution. However, with regard to spatial patterns, little is known about (i) how they develop; (ii) how they are influenced by grazing; or (iii) the extent to which intraspecific interactions dictate them. We addressed these questions by quantifying changes in the spatial distribution of Prosopis velutina (mesquite) shrubs over 74 years on grazed and protected grasslands. Livestock are effective agents of mesquite dispersal and mesquite has lateral roots extending well beyond its canopy. We therefore hypothesized that mesquite distributions would be (a) random on grazed areas and clustered on protected areas; and (b) that clustered or random distributions at early stages of encroachment would give way to regular distributions as stands matured and density-dependent interactions intensified. Assessments in 1932, 1948 and 2006 supported the first hypothesis, but we found no support for the second. In fact, clustering intensified with time on the protected area and the pattern remained random on the grazed site. Although shrub density increased on both areas between 1932 and 2006, we saw no progression toward a regular distribution indicative of density-dependent interactions. We propose that processes related to seed dispersal, grass-shrub seedling interactions, and hydrological constraints on shrub size interact to determine vegetation structure in grassland-to-shrubland state changes with implications for ecosystem function and management.

}, keywords = {LISA, livestock exclusion, mesquite, Moran{\textquoteright}s I, pair correlation function, point pattern analysis, Prosopis velutine, Ripley{\textquoteright}s K, Sonoran Desert, spatial autocorrelation, spatial ecology}, url = {/files/bibliography/14-029.pdf}, author = {Dawn M. Browning and Janet Franklin and Steven R. Archer and Jeffrey K. Gillan and Guertin, D. Phillip} } @article {49840, title = {Vegetation index differencing for broad-scale assessment of productivity under prolonged drought and sequential high rainfall conditions}, journal = {Remote Sensing}, volume = {5}, year = {2013}, month = {01/2013}, pages = {327-341}, chapter = {327}, abstract = {

Spatially-explicit depictions of plant productivity over large areas are critical to monitoring landscapes in highly heterogeneous arid ecosystems. Applying radiometric change detection techniques we sought to determine whether: (1) differences between pre- and post-growing season spectral vegetation index values effectively identify areas of significant change in vegetation; and (2) areas of significant change coincide with altered ecological states. We differenced NDVI values, standardized difference values to Z-scores to identify areas of significant increase and decrease in NDVI, and examined the ecological states associated with these areas. The vegetation index differencing method and translation of growing season NDVI to Z-scores permit examination of change over large areas and can be applied by non-experts. This method identified areas with potential for vegetation/ecological state transition and serves to guide field reconnaissance efforts that may ultimately inform land management decisions for millions of acres of federal lands.\ 

}, keywords = {change detection; rangeland monitoring; Landsat; ecological state mapping; state-and-transition models; phenology}, doi = {10.3390/rs5010327 }, url = {/files/bibliography/13-001.pdf}, author = {Dawn M. Browning and Caitriana Steele} } @proceedings {JRN54526, title = {Comparing phenology of Chihuahuan desert perennial grasses and shrubs between normal and below-average precipitation years}, volume = {PS 92-59}, year = {2012}, month = {08/2012}, publisher = {Ecological Society of America}, address = {Portland, Oregon}, abstract = {Arid and semi-arid regions of the southwestern USA are especially sensitive to changes in temperature, drought frequency and intensity. Observations of plant phenology in these water-limited environments serve as salient indicators of plant responses to changing climate. Repeated consistent phenology observations in conjunction with local climatological (e.g., precipitation, temperature) and soil (e.g., moisture, temperature) measurements are key to elucidating the role of abiotic drivers in the timing of lifecycle events. Weekly observations of plant phenology were initiated in Mar 2010 at a Soil Climate Analysis Network (SCAN) site on the Jornada Experimental Range in southern New Mexico. Weekly observations for 20 individuals across three functional groups - perennial grasses (Aristida purpurea, Sporobolus spp., and Pleuraphis mutica), the deciduous shrub honey mesquite (Prosopis glandulosa) and the evergreen shrub creosote (Larrea tridentata) {\textendash} were conducted using National Phenology Network (NPN) protocols. Phenology patterns by functional group were compared and examined in the context of precipitation. We determined dates of first production of leaves (initial growth), open flowers and fruits; in addition, we calculated the time from initial growth to full canopy and from flower to fruit production for 2010 and 2011 growing seasons. Rainfall in the 2010 rain year (213.4-mm) was near the long-term average (245-mm). Aristida and Sporobolus grasses initiated growth prior to 17 Mar 2010. Mesquite initiated growth later (19 Apr 2010), but achieved full canopy within an average of 4.5 weeks. In contrast, canopy development for grasses in 2010 occurred over 22 weeks. Time from first flower to fruit for grasses in 2010 ranged from 2.0 (for Sporobolus and Pleuraphis) to 2.7 weeks (for Aristida). Rainfall in the 2011 was far below average (89.4-mm) and encapsulated 242 consecutive dry days. Initial growth for all grasses was delayed until 11 Jul 2011, presumably due to deficit rainfall conditions. In contrast, mesquite and creosote shrubs initiated growth prior to the first rain event after 08 Oct 2010 (06 Jun 2011). We hypothesize that changes in soil temperature at depth trigger initial growth for deep-rooted shrubs. No grasses produced flowers or fruit in 2011. Next steps are to evaluate the soil temperature hypothesis with soil measurements at the SCAN site and examine relationships between environmental variables and phenophase transitions using a proportional hazards model.}, author = {Dawn M. Browning and M. Mattocks} } @proceedings {JRN54525, title = {Evaluating plant community responses to rainfall extremes in southwest U.S. ecosystems using radiometric change detection}, volume = {COS 174-3}, year = {2012}, month = {08/2012}, publisher = {Ecological Society of America}, address = {Portland, Oregon}, abstract = {Spatially-explicit depictions of plant productivity and biomass over large areas are critical to monitoring landscapes in highly heterogeneous arid and semi-arid ecosystems. Radiometric change detection techniques applied to Landsat Thematic Mapper (TM) imagery provide an opportunity to characterize changes in land surface conditions that are relevant to land managers. Importantly, these techniques are straightforward and readily transferable to those without expertise in remote sensing. We sought to answer three questions: (1) can we use differences between pre- and post-growing season spectral vegetation index values (i.e., normalized difference vegetation index (NDVI)) to locate areas of extreme change in vegetation? (2) in what ecological sites do these areas of extreme change occur? and (3) can extreme changes in vegetation be related to vegetation dynamics conceptualized in state-and-transition models. We calculated the difference between NDVI values representing pre- (May) and post- (September/October) growing season conditions, standardized NDVI difference values to Z-scores to identify areas of extreme high and low change over the growing season, and determined the plant and soil features associated with significantly high or low NDVI difference values. Calculations were made for two years selected to represent below- (2003) and above-(2009) average rainfall conditions. Two percent of the 5696 km2 study area experienced significant reduction in NDVI values in 2003. The extreme reductions in NDVI values in 2003 were most commonly observed in Rockland and Hills ecological sites in a Historical Savanna state, but were also observed on an area of Clay Loam Upland in a Historical Grassland state. Interestingly, part of this Clay Loam Upland area also demonstrated an extreme increase in NDVI over the wet 2009 growing season. Such responses to wet and dry years detected by NDVI could portend community phase changes within the Historical Grassland state or a transition to an alternative state. The NDVI difference in 2009 following above-average rainfall in 2006 and 2008 resulted in 3.7\% of the area experiencing a significant increase between May and Sep. The largest most contiguous patches of significant increase in NDVI occurred on the Clay Loam Upland ecological site and correspond to the Historical Grassland state. The vegetation index differencing method and translation of growing season differences to Z-scores permit examination of changes over large areas and can be applied by non-experts. Use of additional image dates could enhance interpretations of vegetation dynamics, focus field reconnaissance efforts, and become a routine operational work flow for natural resource managers.}, author = {Dawn M. Browning and Caitriana Steele} } @article {49876, title = {Hierarchial analysis of vegetation dynamics over 71 years: soil-rainfall interactions in a Chihuahuan Desert ecosystem}, journal = {Ecological Applications}, volume = {22}, year = {2012}, month = {04/2012}, pages = {909-926}, chapter = {909}, abstract = {

Proliferation of woody plants in grasslands and savannas is a persistent problem globally. This widely observed shift from grass to shrub dominance in rangelands worldwide has been heterogeneous in space and time largely due to cross-scale interactions among soils, climate, and land-use history. Our objective was to use a hierarchical framework to evaluate the relationship between spatial patterns in soil properties and long-term shrub dynamics in the northern Chihuahuan Desert of New Mexico, USA. To meet this objective, shrub patch dynamics from 1937 to 2008 were characterized at patch and landscape scales using historical imagery and a recent digital soils map. Effects of annual precipitation on patch dynamics on two soils revealed strong correlations between shrub growth on deep sandy soils and above-average rainfall years (r = 0.671, P = 0.034) and shrub colonization and below-average rainfall years on shallow sandy soils (r = 0.705, P = 0.023). Patch-level analysis of demographic patterns revealed significant differences between shrub patches on deep and shallow sandy soils during periods of above- and below-average rainfall. Both deep and shallow sandy soils exhibited low shrub cover in 1937 (1.0\% {\textpm} 2.3\% and 0.3\% {\textpm} 1.3\%, respectively [mean {\textpm} SD]) and were characterized by colonization or appearance of new patches until 1960. However, different demographic responses to the cessation of severe drought on the two soils and increased frequency of wet years after 1960 have resulted in very different endpoints. In 2008 a shrubland occupied the deep sandy soils with cover at 19.8\% {\textpm} 9.1\%, while a shrub-dominated grassland occurred on the shallow sandy soils with cover at 9.3\% {\textpm} 7.2\%. Present-day shrub vegetation constitutes a shifting mosaic marked by the coexistence of patches at different stages of development. Management implications of this long-term multi-scale assessment of vegetation dynamics support the notion that soil properties may constrain grassland remediation. Such efforts on sandy soils should be focused on sites characterized by near-surface water-holding capacity, as those lacking available water-holding capacity in the shallow root zone pose challenges to grass recovery and survival.

}, keywords = {aerial photography, Chihuahuan Desert, cross-scale linkages, ecological-state mapping, hierarchy theory, Jornada Basin LTER, New Mexico USA, object-based change detection, petrocalcic soil, prosopis glandulosa, shrub patch dynamics, shrub proliferation, soil depth}, doi = {10.1890/11-1193.1}, url = {/files/bibliography/12-026.pdf}, author = {Dawn M. Browning and Danielle Duni and Andrea S. Laliberte and A. Rango} } @proceedings {JRN54527, title = {Phenological patterns of Chihuahuan desert perennial grasses and shrubs in normal and below-average precipitation years}, volume = {Poster}, year = {2012}, month = {03/2012}, publisher = {Phenology Research and Observations of Southwest Ecosystems}, address = {Tucson, Arizona}, abstract = {Observations of plant phenology in Arid and semi-arid regions of the southwestern USA serve as salient indicators of plant responses to changing climate. Repeated consistent phenology observations in conjunction with local climatological (e.g., precipitation, temperature) and soil (e.g., moisture, temperature) measurements are key to elucidating the role of abiotic drivers in the timing of lifecycle events. We initiated weekly observations of plant phenology in March 2010 at a Soil Climate Analysis Network (SCAN) site on the Jornada Experimental Range in southern New Mexico. Weekly observations for 20 individuals across three functional groups - perennial grasses (Aristida purpurea, Sporobolus spp., and Pleuraphis mutica), the deciduous shrub honey mesquite (Prosopis glandulosa) and the evergreen shrub creosote (Larrea tridentata) {\textendash} were conducted using National Phenology Network (NPN) protocols. We compare and contrast phenology patterns by functional group in the context of precipitation for 2010 and 2011 rain years. Dates of first leaf (initial growth), open flowers and fruit production are noted; in addition, the time from initial growth to full canopy and from flower to fruit production were calculated for both growing seasons. Rainfall in the 2010 rain year (213.4-mm) was near the long-term average (245-mm). Aristida and Sporobolus grasses initiated growth prior to 17 Mar 2010. Mesquite initiated growth later (19 Apr 2010), but achieved full canopy within 4.5 weeks. In contrast, canopy development for grasses in 2010 occurred over 22 weeks. Time from first flower to fruit for grasses in 2010 ranged from 2 (for Sporobolus and Pleuraphis) to 2.7 weeks (for Aristida). Rainfall in the 2011 was far below average (89.4-mm) and encapsulated 242 consecutive dry days. Initial growth for all grasses was delayed until 11 Jul 2011, presumably due to deficit rainfall conditions. No grasses produced flowers or fruit in 2011. In contrast, mesquite and creosote shrubs initiated growth prior to the first rain event after 08 Oct 2010 (06 Jun 2011). We hypothesize that changes in soil temperature at depth trigger initial growth for deep-rooted shrubs. Next steps are to evaluate the soil temperature hypothesis with soil measurements and examine relationships between environmental variables and phenophase transitions using a proportional hazards model.}, author = {Dawn M. Browning and M. Mattocks} } @article {49935, title = {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}, journal = {Applied and Environmental Soil Science}, volume = {2001}, year = {2011}, month = {04/2011}, pages = {421904}, chapter = {421904}, abstract = {Spatially-explicit data for soil properties governing plant water availability are needed to understand mechanisms influencing plant species distributions and predict plant responses to changing climate. This is especially important for arid and semi-arid regions. Spatial data representing surrogates for soil forming factors are becoming widely available (e.g. spectral and terrain layers). However, field-based training data remain a limiting factor, particularly across remote and extensive drylands. We present a method to map soils with Landsat ETM+ imagery and high resolution (5 m) terrain (IFSAR) data based on statistical properties of the input data layers that do not rely on field training data. We then characterize soil classes mapped using this semi-automated technique. The method distinguished spectrally distinct soil classes that differed in subsurface rather than surface properties. Field evaluations of the soil classification in conjunction with analysis of long-term vegetation dynamics indicate the approach was successful in mapping areas with similar soil properties and ecological potential.}, doi = {10.1155/2011/421904}, url = {/files/bibliography/11-006.pdf}, author = {Dawn M. Browning and Danielle Duni} } @conference {49937, title = {Patterns in reproductive phenology for dryland grasses and shrubs from 1993 to 2010 in the Chihuahuan Desert}, booktitle = {96th ESA Annual Meeting, Earth Stewardship: Preserving and enhancing earth{\textquoteright}s life-support systems}, year = {2011}, month = {08/2011}, publisher = {ESA}, organization = {ESA}, address = {Austin, TX}, abstract = {Arid and semi-arid regions of the southwestern USA are especially sensitive to changes in temperature as well as drought frequency and intensity. Timing of periodic life cycle events (i.e., phenology) is an integrated and salient indicator of plant responses to climate change. Spatially extensive phenology observations in these environments are uncommon and with few exceptions, there is a paucity of long-term records collected using standardized protocols. We examine an 18-year dataset of monthly observations of reproductive phenology for two species of perennial grasses and a deciduous shrub distributed across three upland grassland sites and three mesquite-dominated sites on the Jornada Basin LTER in southern New Mexico, USA. Our objective was to compare and contrast timing and duration of flower and fruit production for two perennial grass species (Bouteloua eriopoda [black grama], \ Sporobolus flexuosus [mesa dropseed]) with one co-existing shrub that has historically displaced grasses in this system (Prosopis glandulosa [honey mesquite]). Field observations are made monthly along two 75-m x 1-m belt transects at each site and constitute a count of individual plants in each of five phenophases: (1) dormant, (2) leaf-out with no reproductive structures, and producing (3) flowers, (4) seeds, or (5) fruits. The protocol simultaneously yields estimates of status and abundance. The appearance of first fruit for grasses (i.e., grains) occurred consistently in August or September, although the number of plants producing fruit was highly variable from year to year. Mesquite demonstrated remarkable synchrony in the production of first leaves (in April), flowers (in May), and fruit (in June) across four sites. The appearance of first fruit and peak fruit production was most often in the same month for mesquite and mesa dropseed. The time from first to peak fruit production in black grama was one month at two sites and in the same month at a third, suggesting local variability in rainfall or soil moisture dynamics may play a role in peak fruit production. Future analyses will examine relationships between the amount and seasonal distribution of rainfall with timing and abundance of fruit production. Understanding the role of abiotic factors in influencing the timing and success of reproductive events is especially relevant to the conservation and restoration of species of concern as well as in predicting plant responses to changes in climate.}, author = {Dawn M. Browning and John P. Anderson and Debra C. Peters} } @article {49934, title = {Protection from livestock fails to deter shrub proliferation in a desert landscape with a history of heavy grazing}, journal = {Ecological Applications}, volume = {21}, year = {2011}, month = {07/2011}, pages = {1629-1642}, chapter = {1629}, abstract = {Desertification is often characterized by the replacement of mesophytic grasses with xerophytic shrubs. Livestock grazing is considered a key driver of shrub encroachment, although most evidence is anecdotal or confounded by other factors. Mapping of velvet mesquite (Prosopis velutina) shrubs in and out of exclosures in 1932, 1948, and 2006 in semiarid grasslands of southeastern Arizona, USA, afforded the opportunity to quantify livestock grazing effects on mesquite proliferation over 74 years in the absence of fire to test the widespread assumption that livestock grazing promotes shrub proliferation. In 1932, shrub cover, density, and aboveground biomass were compared on grazed (12\%, 173 plants/ha, 4182 kg/ha) and newly protected areas (8\%, 203 plants/ha, 3119 kg/ha). By 1948, cover on both areas increased to 18\%; yet, density on the protected area increased 300\% (to 620 plants/ha), nearly twice that of the grazed area (325 plants/ha). From 1932 to 1948, differences in recruitment of new plants and growth of existing plants were reflected in biomass, which was higher on the protected area (415 plants/ha, 8788 kg/ha) relative to the grazed area (155 plants/ha, 7085 kg/ha), although mortality was equally low (0.06\%). In 2006, 42 years after an herbicide application reset mesquite cover to 10\% on both areas, aboveground mesquite mass was comparable on both areas (4700 kg/ha), but cover and density on the protected area (22\%, 960 plants/ha) exceeded that on the grazed area (15\%, 433 plants/ha). Mesquite mass in 2006 was substantially below 1948 levels, so continued accrual is likely. That shrub recovery from herbicides on a biomass basis was much less than recovery on a cover basis suggests that remotely sensed biomass estimates should integrate land management history. Contrary to widely held assumptions, protection from livestock since 1932 not only failed to deter woody-plant proliferation, but actually promoted it relative to grazed areas. Results suggest (1) that thresholds for grassland resistance to shrub encroachment had been crossed by the 1930s, and (2) fire management rather than grazing management may be key to maintaining grassland physiognomy in this bioclimatic region.}, keywords = {arid rangelands, land use legacy, landcover change, livestock grazing, mesquite, Prosopis velutina, shrub encroachment, shrub proliferation, Sonoran Desert, woody biomass}, doi = {10.1890/10-0542.1}, url = {/files/bibliography/11-014.pdf}, author = {Dawn M. Browning and Steven R. Archer} } @article {49936, title = {Temporal dynamics of shrub proliferation: Linking patches to landscapes}, journal = {International Journal of Geographical Information Science}, volume = {25}, year = {2011}, month = {08/2011}, pages = {913-930}, chapter = {913}, abstract = {Shifts in vegetation composition and cover are generally characterized by processes acting at different levels such as landscapes, hill slopes, or plant interspaces. Object-oriented analytical approaches are based upon the inherently hierarchical nature of complex systems and are well-suited to research applications conducted at a range of spatial scales. We quantified long-term vegetation dynamics from two perspectives (i.e., landscape and vegetation patches) in a Chihuahuan Desert ecosystem in southern New Mexico, U.S.A. from 1937 to 2008. Our multi-scale approach comprised object-based analysis of time series aerial photography with automated image analysis at the landscape scale and manual delineation of shrub image objects at the patch scale. We sought to identify mechanisms associated with changes in shrub patch density and percent cover by classifying the fate of individual shrub patches from one image to the next in the time series. The classification scheme captured colonization by new shrub patches, growth or decline in patch area, and patch stability (i.e., change in size of less than 15\%). Patch growth was categorized as growth by coalescence with neighboring patches or canopy expansion. Similarly, patch decline was distinguished as either loss of patch area due to fragmentation of conglomerate patches or canopy die-back. Interpretations of change in patch density based solely on shrub establishment and mortality can be too simplistic. Increases in patch density can result from an influx of new patches or fragmentation of patches into its constituent patches; conversely, decreases in density may be due to mortality of patches or coalescence of existing patches. We illustrate that patches grew in size at the beginning of the study period in conjunction with increases in shrub cover (0.5\% in 1937 to 11\% in 1960) and patch density (4 patches ha-1 in 1937 to 80 patches ha-1 in 1960) increased during the initial encroachment phase of shrub proliferation. Shrub cover remained stable at 7\% from 1967 to 1989 and over this period, patch dynamics were broadly characterized by maintenance of patch area with roughly equal proportions of mortality and establishment. Shrub cover increased linearly from 8\% in 1989 to 14\% in 2008, approaching a maximum projected shrub cover of 18\% based on mean annual precipitation of 230 mm from Sankaran et al. (2005). Shrub patch fate over this period constituted growth and maintenance of patch area whereas appearance of new patches remained relatively stable. Patch dynamics signify a shifting mosaic in which shrub patch establishment, growth, and mortality wax and wane. Monitoring patch dynamics will become increasingly important in these actively managed ecosystems as broad-scale measures of percent cover approach and fluctuate about a dynamic equilibrium.}, keywords = {cross-scale analysis, hill slopes, landscapes, object-oriented classification, patches dynamics, plant interspaces, proliferation, shrub encroachment}, doi = {10.1080/13658816.2010.498789}, url = {/files/bibliography/11-020.pdf}, author = {Dawn M. Browning and Andrea S. Laliberte and A. Rango} } @conference {JRN54479, title = {Bridging field observations and remotely sensed assessments of land surface phenology in the arid southwestern U.S.}, booktitle = {95th Ecological Society of America}, year = {2010}, month = {08/2010}, publisher = {Ecological Society of America}, organization = {Ecological Society of America}, address = {Pittsburgh, PA}, abstract = {

Strong seasonal patterns in vegetation greenness from TM reflected dynamics in aboveground plant biomass. TM-based responses in fall 2008 production to 2006 and 2008 above-average rainfall were consistent across all sites. The cumulative effect of 2006 and 2008 rainfall was most prominently reflected in biomass at mesquite-dominated sites. Biomass ranged widely over time and across sites (0.1 g m-2 to 422.2 g m-2). SAVI effectively tracked increases in biomass across all plant communities although values exhibited a low dynamic range across large differences in plant biomass. Field data regarding reproductive phenology constitute counts for given phenophases by species. Such measures of abundance are most informative to remotely sensed interpretations of phenology where there are clear dominant species. Nonetheless, the field perspective is historically unrivaled for highlighting species responses to climate drivers and is being evaluated further. The range in vegetation physiognomy and productivity at the JRN LTER is well-suited for field validation exercises for land surface phenology and retrieval of biophysical parameters via remote sensing. Plant responses to changes in climate (e.g., temperature and amount/seasonality of rainfall) manifest through phenological patterns. Therefore, field-tested protocols for monitoring plant phenology hold great promise for landscape monitoring and quantifying ecosystem responses to climate change.

}, author = {Dawn M. Browning and A. Rango and John P. Anderson and Debra C. Peters} } @proceedings {50016, title = {Field validation of biomass retrieved from Landsat for rangeland assessment and monitoring}, year = {2010}, month = {July 25-30, 2010}, publisher = {International Symposium on Geoscience and Remote Sensing}, address = {Honolulu, HI}, abstract = {

Measures of terrestrial biomass that are accurate and repeatable are important to monitoring and modeling productivity in the world{\textquoteright}s grassland and savanna (i.e., rangeland) ecosystems. Remote sensing offers potential to characterize seasonal changes in biomass in a consistent non-destructive manner. We capitalized on long-term measurements of aboveground biomass at the Jornada Basin (JRN) Long-Term Ecological Research site in the northern Chihuahuan desert. We sought to answer two questions (1) Does Landsat 5 Thematic Mapper (TM) imagery serve as a reliable and accurate proxy for vegetation biomass in this highly heterogeneous arid ecosystem? and (2) How do differences in vegetation structure influence biomass/SVI relationships? For this pilot study, seven images corresponding to biomass sampling dates from Nov 2006 to Nov 2008 were selected from the Landsat image archive to relate biomass to image-based indicators of vegetative vigor. TM images were processed to yield top of atmosphere radiance values corrected for atmospheric effects using the image-based COST method. We evaluated the performance of four SVIs normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), soil-adjusted vegetation index (SAVI), and modified soil-adjusted vegetation index (MSAVI2). To facilitate comparison of results from Landsat and the MODIS sensor in this arid ecosystem, we report values for EVI. EVI values are reported as the mean of 25 TM pixel values corresponding to the 150-m X 150-m area centered on the fifteen 0.5-ha study sites. Relationships between EVI and biomass were linear and consistent for sites within each of five vegetation communities (i.e. creosote, mesquite, tarbush, grassland, and playas). Field measurements of biomass ranged widely over time and across sites (0 to 422.2 g/m2). EVI tracked changes in biomass reasonably well with R2 values ranging from 0.238 (for playa sites) to 0.789 (for mesquite sites). EVI exhibited a low dynamic range in values across large differences in plant biomass. Grassland EVI responses do not always clearly reflect changes in biomass which may be due to the prominence of senescent vegetation at grassland and playa sites or confounded by the prominence of bare soil in arid ecosystems. On-going analyses will evaluate the performance of other SVIs. The range in physiognomy and productivity at the JRN is well-suited for field validation exercises for biophysical parameters retrieved via remote sensing. Accurate and robust relationships between spectral vegetation indices derived from freely available satellite imagery and field measurements of biomass are powerful tools for monitoring landscape condition in arid and semi-arid rangelands.

}, url = {/files/bibliography/10-028.pdf}, author = {Dawn M. Browning and Debra C. Peters and Caitriana Steele and A. Rango} } @proceedings {50015, title = {Local and global patterns of shrub proliferation - changes in autocorrelation in an arid rangeland ecosystem from 1937-2008.}, year = {2010}, month = {June 25-30, 2010}, abstract = {The proliferation of trees and shrubs in grassland and savanna ecosystems has been widely observed, although future trajectories remain difficult to ascertain. Spatial manifestations of shrub proliferation bear relevance on surface hydrology and the spread of disturbance. We quantify changes in spatial autocorrelation in shrub cover in an arid grassland ecosystem to test the validity of a conceptual framework highlighting the role of shrub patch dynamics in the shrub encroachment process. We build upon the framework to suggest how the encroachment and stabilization phases manifest spatially. We suggest that indicators of spatial autocorrelation illustrate where local interactions are more prevalent, thereby functioning as an indicator of biotic regulation and stabilization in shrub cover. We analyzed binary maps of shrub cover from 1937 to 2008 derived from time series aerial photography. Spatial analyses entailed resampling 1-m depictions of shrub patches to percent shrub cover within 20-m X 20-m quadrats to examine the spatial autocorrelation with Moran{\textquoteright}s I using GeoDa software. We decomposed the global index of spatial association into contributions from local neighborhoods using Local Indicator of Spatial Association, which quantifies the extent to which cells are similar to or different from their neighbors. Shrub cover in 1937 was highly heterogenous and became more dispersed and less patchy over the 71 years. As shrub cover increased, it became increasingly positively autocorrelated with Moran{\textquoteright}s I increasing from 0.383 in 1937 to 0.742 in 2008. We found no clear evidence of self-organization, although we did detect clear evidence of local effects that resulted in broad scale patterns with hot-spots of low and high cover. The trend highlights the potential for edaphic or geomorphic constraints on shrub cover. We anticipate collecting field data on vegetation structure, cover, and soil properties to discern whether segregated patterns in autocorrelation are related to land surface conditions.}, author = {Dawn M. Browning and Andrea S. Laliberte and A. Rango} } @proceedings {50018, title = {Spatial autocorrelation of shrub cover in an arid rangleand ecosystem from 1937-2008}, year = {2010}, abstract = {The proliferation of trees and shrubs in grassland and savanna ecosystems has been widely observed, although future trajectories remain difficult to ascertain. Spatial manifestations of shrub proliferation bear relevance on surface hydrology and the spread of disturbance. We quantify changes in spatial autocorrelation in shrub cover in an arid grassland ecosystem to test the validity of a conceptual framework highlighting the role of shrub patch dynamics in the shrub encroachment process. We build upon the framework to suggest how the encroachment and stabilization phases manifest spatially. We suggest that indicators of spatial autocorrelation illustrate where local interactions are more prevalent, thereby functioning as an indicator of biotic regulation and stabilization in shrub cover. We analyzed binary maps of shrub cover from 1937 to 2008 derived from time series aerial photography. Spatial analyses entailed resampling 1-m depictions of shrub patches to percent shrub cover within 20-m X 20-m quadrats to examine the spatial autocorrelation with Moran\’s I using GeoDa software. We decomposed the global index of spatial association into contributions from local neighborhoods using Local Indicator of Spatial Association, which quantifies the extent to which cells are similar to or different from their neighbors. Shrub cover in 1937 was highly heterogenous and became more dispersed and less patchy over the 71 years. As shrub cover increased, it became increasingly positively autocorrelated with Moran\’s I increasing from 0.383 in 1937 to 0.742 in 2008. We found no clear evidence of self-organization, although we did detect clear evidence of local effects that resulted in broad scale patterns with hot-spots of low and high cover. Assessment of shrub patch dynamics (i.e., coalescence, fragmentation of patches) is on-going to identify mechanisms associated with changes in autocorrelation.}, keywords = {remote sensing, shrub cover}, author = {Dawn M. Browning and Andrea S. Laliberte and A. Rango and Moreno, A.} } @conference {50017, title = {Species{\textendash}specific contributions to moderate resolution vegetation indices derived from sub-decimeter aerial photography {\textendash} Prospects for phenological monitoring}, booktitle = {American Society for Photogrammetry and Remote sensing Proceedings}, year = {2010}, month = {04/2010}, address = {San Diego, California}, abstract = {

High spatial heterogeneity in ground cover, large amounts of exposed bare soil, and modest cover from shrubs and grasses in arid and semi-arid ecosystems challenge the integration of field observations of phenology and remotely sensed data to monitor changes in land surface phenology. This research conducted at the Jornada Basin Long-Term Ecological Research (LTER) site in southern New Mexico capitalizes on object-based classification of sub-decimeter (4 cm) aerial photography to examine species-specific contributions to vegetation index values calculated across a range of grain sizes. Drawing on established field protocols for reproductive phenology, sub-decimeter imagery (4 cm), and object-based image analysis, we explore the relationship between field phenology and vegetation index values and quantify the contribution of individual species to spectral vegetation index values derived from 4 cm imagery aggregated incrementally to 30 m spatial resolution. Color-infrared imagery from a digital mapping camera was collected June 2007 across 15 LTER study sites that transect five distinct vegetation communities along a continuum of grass to shrub dominance. Object-based image analysis of 4 cm imagery provides a detailed depiction of ground cover and allows us to extract species-specific contributions to spectral vegetation indices. The ability to discern species- or functional-group contributions to remotely sensed signals of vegetation greenness can greatly enhance the design of field sampling protocols for phenological research. Furthermore, imagery from unmanned aerial vehicles (UAV) is a cost-effective and increasingly available resource and generation of UAV mosaics has been accomplished so that larger study areas can be addressed. This technology can provide a robust basis for scaling relationships for phenology-based research applications.

}, author = {Dawn M. Browning and Andrea S. Laliberte and A. Rango} } @conference {50082, title = {Does livestock grazing influence spatial patterns of woody plant proliferation?}, booktitle = {Ecological Society of America Abstracts}, year = {2009}, month = {August 2009}, pages = {COS 127-10}, abstract = {Patterns of woody plant proliferation in grasslands and savannas influence rates of erosion, spread of disturbance, and nutrient pools.~ Spatial pattern is the outcome of plant dispersal, recruitment, competition/facilitation, and disturbance. We quantified effects of livestock grazing, a widely cited driver of shrub encroachment, on the spatial patterns of velvet mesquite (Prosopis velutina) distribution and recruitment in southeastern Arizona. ~Field surveys of plant canopy size and location spanning 74 years (1932, 1948, and 2006) were conducted on areas grazed by livestock since the late 1800s and on areas protected from livestock since 1932.~ Point pattern analysis and Moran{\textquoteright}s I were used to quantify changes in distribution and spatial autocorrelation over time.}, keywords = {erosion, grasslands, nutrient, savannas, spatial pattern}, author = {Dawn M. Browning and Steven R. Archer and Janet Franklin and Guertin, D. P.} } @article {50083, title = {Field validation of 1930s aerial photography: What are we missing?}, journal = {Journal of Arid Environments}, volume = {73}, year = {2009}, month = {06/2009}, pages = {844-853}, chapter = {844}, abstract = {

Aerial photography from the 1930s serves as the earliest synoptic depiction of vegetation cover. We generated a spatially explicit database of shrub (Prosopis velutina) stand structure within two 1.8 ha field plots established in 1932 to address two questions: (1) What are the detection limits of panchromatic 1936 aerial photography?, and (2) How do these influence P. velutina biomass estimates? Shrub polygons were manually digitized on 1936 imagery and linked to 1932 field measurements of P. velutina canopy area. Aboveground 1932 P. velutina biomass was estimated using a site-specific allometric relationship for field-measured canopy area. Shrub canopy detection limits on the 1936 imagery were comparable to those reported for contemporary imagery. Based on a conservative shrub size detection threshold of 3.8 m2, 5.8\% of P. velutina biomass was missed. Spatial resolution (0.6 vs. 1.0 m) did not influence detection limits, but the overall accuracy of shrub cover estimates was greater on 1.0 m images. Presence of the sub-shrub Isocoma tenuisecta may also have significantly influenced estimates of P. velutina canopy area. These analyses illustrate the importance of standardizing aerial photo interpretation protocols, accounting for uncertainty estimating shrub biomass, and caution species-specific interpretations for historic aerial photography.

}, keywords = {aboveground woody biomass, detection limites, error assessment, historid aerial photography, land cover, panchromatic, retrospective ground truth, retrospective mapping, Santa Rita, Sonoran Desert}, doi = {10.1016/j.jaridenv.2009.04.003}, url = {/files/bibliography/09-019.pdf}, author = {Dawn M. Browning and Steven R. Archer and Byrne, A.T.} } @conference {50081, title = {Grazing effect on woody plant recruitment in a Sonoran Desert grassland across space and time}, booktitle = {US International Association for Landscape Ecology}, year = {2009}, month = {04/2009}, publisher = {US, IALE}, organization = {US, IALE}, address = {Snowbird, Utah}, abstract = {

Livestock grazing is a commonly cited factor contributing to shrub encroachment in savannas and grasslands. Patterns of woody plant proliferation are known to influence rates of erosion and spread of disturbance and are of practical importance to livestock management with regard to forage distribution and abundance. However, the effects of grazing on woody plant population dynamics and stand structure are poorly understood, owing to a paucity of long-term, spatially-explicit data. We explored the spatial patterns of distribution and recruitment for velvet mesquite (Prosopis velutina) using field surveys spanning 74 years (1932, 1948, and 2006) on areas grazed by livestock since the late 1800s and protected from livestock since 1932. Univariate analyses with Ripley\’s K and neighborhood density functions (NDF) revealed mesquite plants were randomly distributed in 1932. In 1948, following 16 years of protection from livestock, plants on the protected area were clustered at all distances (1 to 20m), while mesquite on the grazed area were clustered at short distances (1 to 4m) only. In 2006, mesquite on the protected area remained clustered at all distances, with a marked peak in clustering at short distances (1 to 4m), whereas mesquite on the grazed area were randomly distributed. Bivariate analyses with Ripley\’s K and NDF indicated that juvenile mesquite plants (\<1m height) were significantly clustered around adult plants from 2 to 5m on the protected area in 2006; but there were no significant patterns of association between juveniles and adults on the grazed area through time. Previous analyses revealed that spatial autocorrelation in mesquite density did not deviate from random on the grazed area, whereas associations on the protected area became increasingly positive. Grazing influenced recruitment-driven changes in population structure from 1932 to 2006 and protection from livestock facilitated formation of high density shrub clusters and open areas generating high spatial heterogeneity.

}, keywords = {erosion, grasslands, livestock management, point pattern analysis, proliferation, Santa Rita Experimental Range, savannas, shrub encroachment, spatial ecology, velvet mesquite, woody}, author = {Dawn M. Browning and Janet Franklin and Steven R. Archer} } @conference {50080, title = {Prospects of phenological monitoring in an arid southwestern U.S. rangeland using field observations with hyperspatial and moderate resolution imagery}, booktitle = {American Geophysical Union Fall Meeting}, year = {2009}, month = {12/2009}, address = {San Francisco, California}, abstract = {

Relating field observations of plant phenological events to remotely sensed depictions of land surface phenology remains a challenge to the vertical integration of data from disparate sources. This research conducted at the Jornada Basin Long-Term Ecological Research site in southern New Mexico capitalizes on legacy datasets pertaining to reproductive phenology and biomass and hyperspatial imagery. Large amounts of exposed bare soil and modest cover from shrubs and grasses in these arid and semi-arid ecosystems challenge the integration of field observations of phenology and remotely sensed data to monitor changes in land surface phenology. Drawing on established field protocols for reproductive phenology, hyperspatial imagery (4 cm), and object-based image analysis, we explore the utility of two approaches to scale detailed observations (i.e., field and 4 cm imagery) to the extent of long-term field plots (50 x 50m) and moderate resolution Landsat Thematic Mapper (TM) imagery (30 x 30m). Very high resolution color-infrared imagery was collected June 2007 across 15 LTER study sites that transect five distinct vegetation communities ranging from grass to shrub dominance. We examined two methods for scaling spectral vegetation indices (SVI) at 4 cm resolution: pixel averaging and object-based integration. Pixel averaging yields the mean SVI value for all pixels within the plot or TM pixel. Alternatively, the object-based method is based on a weighted average of SVI values that correspond to discrete image objects (e.g., individual shrubs or grass patches). Object-based image analysis of 4 cm imagery provides a detailed depiction of ground cover and allows us to extract species-specific contributions to upscaled SVI values. The ability to discern species- or functional-group contributions to remotely sensed signals of vegetation greenness can greatly enhance the design of field sampling protocols for phenological research. Furthermore, imagery from unmanned aerial vehicles (UAV) is a cost-effective and increasingly available resource and generation of UAV mosaics has been accomplished so that larger study areas can be addressed. This technology can provide a robust basis for scaling relationships for phenology-based research applications.

}, keywords = {computational methods, data processing, phenological, remote sensing}, author = {Dawn M. Browning and Andrea S. Laliberte and A. Rango and Jeffrey E. Herrick} }