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Satellite-derived Ecosystem Functional Types (EFTs) are increasingly used in ecology and conservation to characterize ecosystem heterogeneity. The diversity of EFTs, also known as Ecosystem Functional Diversity (EFD), has been suggested both as a potential metric of ecosystem-level biodiversity and as a predictor for ecosystem functioning, ecosystem services, and resilience. However, the impact of key methodological choices on patterns of EFTs and EFD have not been formally assessed. Using Costa Rica as a study system, we compared EFTs and EFD, derived from MODIS and Landsat data using different methodological assumptions, at both national and local extents. Our results showed that the regional spatial patterns of EFTs and EFD derived from 250 m MODIS and 30 m Landsat are notably different. The selection of sensors for deriving EFTs and EFD is dependent on the study area, data quality, and the research objective. Given its finer spatial resolution, Landsat has greater capacity to differentiate more EFTs than MODIS, though MODIS could be a better choice in frequently cloudy areas due to its shorter revisiting time. We also found that the selection of spatial extent used to derive EFD is critical, as smaller extents (e.g., at a local rather than a national scale) can show much higher diversity. However, diversity levels derived at smaller extents appear to be nested within the diversity levels derived at larger extents. As EFTs and EFD continue to develop as a tool for ecosystem ecology, we highlight the important methodological choices to ensure that these metrics best fit research objectives. [ABSTRACT FROM AUTHOR]

We present a conceptual model in which plant-soil interactions in grasslands are characterized by the extent to which water is limiting. Plant-soil interactions in dry grasslands, those dominated by water limitation ('belowground-dominance'), are fundamentally different fromplant-soil interactions in subhumid grasslands, where resource limitations vary in time and space among water, nitrogen, and light ('indeterminate dominance'). In the belowground-dominance grasslands, the strong limitation of soil water leads to complete (though uneven) occupation of the soil by roots, but insufficient resources to support continuous aboveground plant cover. Discontinuous aboveground plant cover leads to strong biological and physical forces that result in the accumulation of soil materials beneath individual plants in resource islands. The degree of accumulation in these resource islands is strongly influenced by plant functional type (lifespan, growth form, root:shoot ratio, photosynthetic pathway), with the largest resource islands accumulating under perennial bunchgrasses. Resource islands develop over decadal time scales, but may be reduced to the level of bare ground following death of an individual plant in as little as 3 years. These resource islands may have a great deal of significance as an index of recovery from disturbance, an indicator of ecosystem stability or harbinger of desertification, or may be significant because of possible feedbacks to plant establishment. In the grasslands in whichthe dominant resource limiting plant community dynamics is indeterminate, plant cover is relatively continuous, and thus the major force in plant-soil interactions is related to the feedbacks among plant biomass production, litter quality and nutrient availability. With increasing precipitation, the over-riding importance of water as a limiting factor diminishes, and four other factors become important in determining plant community and ecosystem dynamics: soil nitrogen, herbivor [ABSTRACT FROM AUTHOR]

Plant community structure is expected to regulate the microbial processes of nitrification and denitrification by controlling the availability of inorganic N substrates. Thus it could also be a factor in the concomitant release of NO and N2O from soils as a resultof these processes. C-3 and C-4 plants differ in several attributes related to the cycling of nitrogen and were hypothesized to yield differences in trace gas exchange between soil and atmosphere. In this study we estimated fluxes of NO, N2O and CH4 from soils of shortgrass steppe communities dominated by either C-3 plants, C-4 plants or mixtures of the two types. We collected gas samplesweekly from two sites, a sandy clay loam and a clay, throughout the growing seasons of 1995 and 1996. Plant functional type effects on gas fluxes at the clay site were not apparent, however we found severaldifferences among plant communities on the sandy clay loam. CH4 uptake from atmosphere to soil was significantly greater on C-4 plots than C-3 plots in both years. NO fluxes were significantly greater from C-4 plots than from C-3 plots in 1995. NO fluxes from C-3 and mixed plots were not significantly different between 1995 and 1996, however fluxes from C-4 plots were significantly greater in 1995 compared to 1996. Results indicate that under certain environmental conditions, particularly when factors such as moisture and temperature an not limiting, plant community composition can play an important role in regulating trace gas exchange. [ABSTRACT FROM AUTHOR]

Few old-growth stands remain in the matrix of secondary forests that dominates the eastern North American landscape. These remnant stands offer insight on the potential carbon (C) storage capacity of now-recovering secondary forests. We surveyed the remaining old-growth forests on sites characteristic of the general Mid-Atlantic United States and estimated the size of multiple components of forest C storage. Within and between old-growth stands, variability in C density is high and related to overstory tree species composition. The sites contain 219 ± 46 Mg C/ha (mean ± SD), including live and dead aboveground biomass, leaf litter, and the soil O horizon, with over 20% stored in downed wood and snags. Stands dominated by tulip poplar (Liriodendron tulipifera) store the most live biomass, while the mixed oak (Quercus spp.) stands overall store more dead wood. Total C density is 30% higher (154 Mg C/ha), and dead wood C density is 1800% higher (46 Mg C/ha) in the old-growth forests than in the surrounding younger forests (120 and 5 Mg C/ha, respectively). The high density of dead wood in old growth relative to secondary forests reflects a stark difference in historical land use and, possibly, the legacy of the local disturbance (e.g., disease) history. Our results demonstrate the potential for dead wood to maintain the sink capacity of secondary forests for many decades to come. [ABSTRACT FROM AUTHOR]

Question: How do interactions between the physical environment and biotic properties of vegetation influence the formation of small patterned-ground features along the Arctic bioclimate gradient? Location: At 68° to 78°N: six locations along the Dalton Highway in arctic Alaska and three in Canada (Banks Island, Prince Patrick Island and Ellef Ringnes Island). Methods: We analysed floristic and structural vegetation, biomass and abiotic data (soil chemical and physical parameters, the n-factor [a soil thermal index] and spectral information [NDVI, LAI]) on 147 microhabitat relevés of zonal-patterned-ground features. Using mapping, table analysis (JUICE) and ordination techniques (NMDS). Results: Table analysis using JUICE and the phi-coefficient to identify diagnostic species revealed clear groups of diagnostic plant taxa in four of the five zonal vegetation complexes. Plant communities and zonal complexes were generally well separated in the NMDS ordination. The Alaska and Canada communities were spatially separated in the ordination because of different glacial histories and location in separate floristic provinces, but there was no single controlling environmental gradient. Vegetation structure, particularly that of bryophytes and total biomass, strongly affected thermal properties of the soils. Patterned-ground complexes with the largest thermal differential between the patterned-ground features and the surrounding vegetation exhibited the clearest patterned-ground morphologies. Conclusions: Characterizing the composition and structure of small-scale plant communities growing on distinctive microhabitats within patterned-ground complexes was necessary to understand the biological and physical controls of vegetation on patterned-ground morphology. Coarser-scale vegetation units, referred to here as 'zonal patterned-ground vegetation complexes' (groups of patterned-ground plant communities within zonal landscapes), were useful for landscape and regional-level comparisons and for extrapolation of information collected at plot scales to larger regions. Vegetation maps of the representative landscapes in each subzone were needed for extrapolation. Different growth characteristics of plants growing in northern and southern parts of the gradient have an important effect in stabilizing highly frost-active soils. A conceptual diagram summarizes the interactions between vegetation and patterned-ground morphology along the Arctic climate gradient. [ABSTRACT FROM AUTHOR]

The utility of sheer volumes of very high spatial resolution (VHSR) commercial imagery in mapping the Arctic region is new and actively evolving. Commercial satellite sensors typically record image data in low-resolution multispectral (MS) and high-resolution panchromatic (PAN) mode. Spatial resolution is needed to accurately describe feature shapes and textural patterns, such as ice-wedge polygons (IWPs) that are rapidly transforming surface features due to degrading permafrost, while spectral resolution allows capturing of land-use and land-cover types. Data fusion, the process of combining PAN and MS images with complementary characteristics often serves as an integral component of remote sensing mapping workflows. The fusion process generates spectral and spatial artifacts that may affect the classification accuracies of subsequent automated image analysis algorithms, such as deep learning (DL) convolutional neural nets (CNN). We employed a detailed multidimensional assessment to understand the performances of an array of eight application-oriented data fusion algorithms when applied to VHSR image scenes for DLCNN-based mapping of ice-wedge polygons. Our findings revealed the scene dependency of data fusion algorithms and emphasized the need for careful selection of the proper algorithm. Results suggested that the fusion algorithms that preserve spatial character of original PAN imagery favor the DLCNN model performances. The choice of fusion approach needs to be considered of equal importance to the required training dataset for successful applications using DLCNN on VHRS imagery in order to enable an accurate mapping effort of permafrost thaw across the Arctic region. [ABSTRACT FROM AUTHOR]

• An index of the stage of vegetation phenology (P scalar) was derived from PhenoCams. • A daily GPP model was developed for semi-arid grasslands. • Our daily GPP product can track vegetation responses to short-term disturbances. The accurate estimation of temporally-continuous gross primary production (GPP) is important for a mechanistic understanding of the global carbon budget, as well as the carbon exchange between land and atmosphere. Ground-based PhenoCams can provide near-surface observations of plant phenology with high temporal resolution and possess great potential for use in modeling the seasonal dynamics of GPP. However, due to the site-level empirical approaches for estimating the fraction of absorbed photosynthetically active radiation (fAPAR), a broad application of PhenoCams in GPP modeling has been restricted. In this study, the stage of vegetation phenology (P scalar) is proposed, which is calculated from the excess green index (ExGI) derived from PhenoCam data. We integrate P scalar with the enhanced vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to generate a daily time-series of the fAPAR (fAPAR CAM), and then to estimate daily GPP (GPP CAM) with a light use efficiency model in a semi-arid grassland area from 2012 to 2014. Over the three continuous years, the daily fAPAR CAM exhibited similar temporal behavior to the eddy covariance–measured GPP (GPP EC), and the overall determination coefficients (R2) were all > 0.81. GPP CAM agreed well with GPP EC , and these agreements were highly statistically significant (p < 0.01); R2 varied from 0.80 to 0.87, the relative error (RE) varied from -2.9% to 2.81%, and the root mean square error (RMSE) ranged from 0.83 to 0.98 gC/m2/d. GPP CAM was then resampled to 8-day temporal resolution (GPP CAM8d), and further evaluated by comparisons with MODIS GPP products (GPP MOD17) and vegetation photosynthesis model (VPM)–derived GPP (GPP VPM). Validation revealed that the variance explained by GPP CAM8d was still the greatest among these three GPP products. The RMSE and RE of GPP CAM8d were also lower than those of the other two GPP products. The explanatory power of predictors in GPP modeling was also explored; the fAPAR was found to be the most influential predictor, followed by photosynthetically active radiation (PAR). The contributions of the environmental stress indices of temperature and water (T scalar and W scalar , respectively) were less than that of PAR. These results highlight the potential for PhenoCam images in high temporal resolution GPP modeling. Our GPP modeling method will help reduce uncertainties by using PhenoCam images for monitoring the seasonal development of vegetation production. [ABSTRACT FROM AUTHOR]

The reliability of remote sensing technology is essential for its efficient operational applications in nature conservation practices. In our study, multi-temporal, multispectral, and hyperspectral data from an Unoccupied Aerial Vehicle (UAV) with a ground sampling distance (GSD) of 3 cm were applied to a permanent research plot (1 ha), while spaceborne PlanetScope multi-temporal data with GSD of 3 m were used for a wider area of 250 ha. The main aim of the study was to evaluate the potential of these data for monitoring vegetation at the species level in the Central European relict arcto-alpine tundra (in the Krkonoše Mountains, Czech Republic). We evaluated both types of data and their performance for various classifiers, and the benefits of adding multi-temporal aspects to the classification and robustness of remote sensing for monitoring grass species. This study addresses the requirements of nature conservation practices in the Krkonoše Mts. National Park to find a suitable method for monitoring changes in dominant and expanding grass species in response to global warming. The object-based Support Vector Machine, pixel-based Random Forest and Maximum Likelihood classifiers were evaluated. We confirmed that the UAV multispectral and hyperspectral data with GSD of 3 cm can monitor dominant grass species (Nardus stricta , Calamagrostis villosa , Molinia caerulea , Deschampsia cespitosa) in tundra with excellent accuracy (95.9% and 94.0% overall accuracy for multi-temporal and mono-temporal composites, respectively). The best F1-scores for these species ranged from 94.7 to 99.4%. However, the accuracies were substantially lower for small and sparse growing species (Avenella flexuosa and Carex bigelowii). Unexpectedly, the UAV multispectral and hyperspectral data yielded comparable results. The multi-temporal approach improved the accuracy of all types of data. Overall, we confirmed the robustness of the remote sensing approach for grass monitoring at the species level given the high spatial match between various classification outputs. Our study established a workflow for reliable monitoring of tundra grass vegetation according to the requirements of nature conservation and proposed innovative measures for the spatial accuracy assessment of classification outputs. • Unique multispectral and hyperspectral multi-temporal UAV datasets (pixel 3 cm) used. • UAV datasets compared to PlanetScope satellite multi-temporal data. • Classification accuracy of dominant grass species is excellent (∼99%). • Accuracy increased with spatial and temporal, but not with spectral resolution. • Measures for spatial accuracy assessment of classification outputs proposed. [ABSTRACT FROM AUTHOR]

The role of wind in changing the spatial heterogeneity of soil resources in erosion-dominated semiarid ecosystems is well known. Yet the effect of windblown sediment deposition on soil nutrient distribution and ecosystem dynamics at local and landscape scales has received little attention. We examined the effects of enhanced sediment deposition on the spatial distribution of soil nutrients at the Jornada Experimental Range, southern New Mexico. Enhanced sediment deposition was obtained as a result of grass cover reduction in the upwind portion of the experiment in two sites co-dominated by mesquite and one of two grass species with different morphologies. The spatial characteristics of soil available nitrogen (including ammonium, nitrite, and nitrate), phosphate, potassium, and calcium were quantified using a variety of traditional and geostatistical analyses. Our results showed that enhanced deposition led to considerable reduction in both mean soil nutrient concentrations and coefficients of variation over a two-year period (2004–2006). Given the observed increase in the scale of spatial dependence for available nitrogen, but not for potassium, phosphate, and calcium following enhanced sediment deposition, we suggest that soil available nitrogen may be particularly responsive to increased aeolian activities due to livestock grazing and other anthropogenic activities that remove vegetation. Our study further suggests that soil particles deposited in the downwind area may be “nutrient-imbalanced.” Specifically, the lower-than-normal available nitrogen concentrations in the wind-deposited soils may inhibit the growth of grasses and the germination of seeds. For wind-erodible ecosystems found in southern New Mexico, structures of Bouteloua-dominated communities may be particularly susceptible to change under enhanced soil erosion conditions. [ABSTRACT FROM AUTHOR]

• The responses of soil respiration to alterations of organic matter input varied depending on thinning density. • The major biotic and abiotic variables driving soil respiration were identified. • Our findings have implications for improving our ability to predict soil carbon balance influenced by forest thinning. Plantation management practices may influence carbon dioxide (CO 2) uptake dynamics; however, the responses of carbon losses, such as soil respiration, to management (e.g. thinning) have not been sufficiently studied. We evaluated the effects of forest thinning (no thinning (NT), low thinning (LT), medium thinning (MT), and high thinning (HT) and organic matter manipulation (intact soil (untreated control, UC), exclusion of aboveground litter (EL), and exclusion of both aboveground litter and roots (ELR)) on soil respiration in a Larix principis-rupprechtii plantation. During the period from 2015–2018, soil respiration was continuously monitored from May to October (growing season). Meanwhile, soil temperature and soil moisture at a depth of 5 cm were also measured. In addition, three soil samples were collected to measure biochemical properties of soil. We found that mean soil respiration (R s) was significantly greater in MT than that in NT (by 21.5 %). R S in HT was significantly greater than NT in 2015 (by 25.0 %) and then finally lower than NT (14.8 %) in 2018. However, R S in LT compared with NT showed no response to thinning during our observation period. The organic matter manipulation also affected soil respiration. Mean reduction of soil respiration in EL (R EL) and in ELR (R ELR) compared to R s ranged from 25.9%–39.2% and 40.8%–53.6% across all thinning regimes, respectively. The temperature sensitivity (Q 10) values of R S , R EL , R ELR ranged from 2.23 to 2.72, 2.21–2.60, and 2.31–2.90, respectively. The model with the best fitting temperature and moisture factors explained 63.8 % - 75.4 % changes in R S , 65.9 % - 74.7 % changes in R EL and 70.4 % - 74.1 % changes in R ELR. Stepwise regression analyses showed that soil temperature, ratio of soil carbon and nitrogen in the topsoil explained the pattern of R S across the thinning scenarios. R EL showed a high sensitivity to changing in some soil chemical properties and hydrolases activities, whereas R ELR showed a high sensitivity to changing in microbial activity combined with temperature and pH of soil. Overall, our data show that the response of organic matter inputs to thinning has an important impact on soil CO 2 fluxes of plantation, and emphasize the difference of the response between aboveground and underground organic matter inputs to soil CO 2 fluxes. [ABSTRACT FROM AUTHOR]

The relict arctic-alpine tundra provides a natural laboratory to study the potential impacts of climate change and anthropogenic disturbance on tundra vegetation. The Nardus stricta -dominated relict tundra grasslands in the Krkonoše Mountains have experienced shifting species dynamics over the past few decades. Changes in species cover of the four competing grasses- Nardus stricta , Calamagrostis villosa , Molinia caerulea , and Deschampsia cespitosa -were successfully detected using orthophotos. Leaf functional traits (anatomy/morphology, element accumulation, leaf pigments, and phenolic compound profiles) , were examined in combination with in situ chlorophyll fluorescence in order to shed light on their respective spatial expansions and retreats. Our results suggest a diverse phenolic profile in combination with early leaf expansion and pigment accumulation has aided the expansion of C. villosa , while microhabitats may drive the expansion and decline of D. cespitosa in different areas of the grassland. N. stricta -the dominant species-is retreating, while M. caerulea did not demonstrate significant changes in territory between 2012 and 2018. We propose that the seasonal dynamics of pigment accumulation and canopy formation are important factors when assessing potential "spreader" species and recommend that phenology be taken into account when monitoring grass species using remote sensing.

The impacts of climatic changes on forests may appear gradually on time scales of years to centuries due to the long generation times of trees. Consequently, current forest extent may not reflect current climatic patterns. In contrast with these lagged responses, abrupt transitions in forests under climate change may occur in environments where alternative vegetation states are influenced by disturbances, such as fire. The Klamath forest landscape (northern California and southwest Oregon, USA) is currently dominated by high biomass, biodiverse temperate coniferous forests, but climate change could disrupt the mechanisms promoting forest stability (e.g. growth, regeneration and fire tolerance). Using a landscape simulation model, we estimate that about one-third of the Klamath forest landscape (500,000 ha) could transition from conifer-dominated forest to shrub/hardwood chaparral, triggered by increased fire activity coupled with lower post-fire conifer establishment. Such shifts were widespread under the warmer climate change scenarios (RCP 8.5) but were surprisingly prevalent under the climate of 1949-2010, reflecting the joint influences of recent warming trends and the legacy of fire suppression that may have enhanced conifer dominance. Our results demonstrate that major forest ecosystem shifts should be expected when climate change disrupts key stabilizing feedbacks that maintain the dominance of long-lived, slowly regenerating trees.

Background: Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models., Scope: Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation., Conclusions: Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings., (Published by Oxford University Press on behalf of the Annals of Botany Company 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Many arid grassland communities are changing from grass dominance to shrub dominance, but the mechanisms involved in this conversion process are not completely understood. Aeolian processes likely contribute to this conversion from grassland to shrubland. The purpose of this research is to provide information regarding how vegetation changes occur in an arid grassland as a result of aeolian sediment transport. The experimental design included three treatment blocks, each with a 25 × 50 m area where all grasses, semi-shrubs, and perennial forbs were hand removed, a 25 × 50 m control area with no manipulation of vegetation cover, and two 10 × 25 m plots immediately downwind of the grass-removal and control areas in the prevailing wind direction, 19° north of east, for measuring vegetation cover. Aeolian sediment flux, soil nutrients, and soil seed bank were monitored on each treatment area and downwind plot. Grass and shrub cover were measured on each grass-removal, control, and downwind plot along continuous line transects as well as on 5 × 10 m subplots within each downwind area over four years following grass removal. On grass-removal areas, sediment flux increased significantly, soil nutrients and seed bank were depleted, and Prosopis glandulosa shrub cover increased compared to controls. Additionally, differential changes for grass and shrub cover were observed for plots downwind of vegetation-removal and control areas. Grass cover on plots downwind of vegetation-removal areas decreased over time (2004-2007) despite above average rainfall throughout the period of observation, while grass cover increased downwind of control areas; P. glandulosa cover increased on plots downwind of vegetation-removal areas, while decreasing on plots downwind of control areas. The relationships between vegetation changes and aeolian sediment flux were significant and were best described by a logarithmic function, with decreases in grass cover and increases in shrub cover occurring with small increases in aeolian sediment flux.

Ecosystem processes in semiarid landscape mosaics are strongly affected by the interactions among water utilization, plant growth, and vegetation patterns. Management of these semiarid landscapes can be improved with better understanding of the complex interactions between ecology and hydrology that determine the water-use efficiency at landscape and regional scales. However, quantifying the effects of runoff and applying ecohydrological principles toward the improvement of land-use management requires additional research to integrate the ecological and hydrological processes. This study highlights the importance of runoff in the management of vegetation to retard desertification by reducing soil erosion. By coupling a plant growth model with a simple GIS-based model of water redistribution and use, we analyzed the interactions among runoff generation, "runon" reabsorption, and plant growth, in a small watershed in the semiarid sandy grassland area of northern China. Net primary productivity (NPP) and water utilization for the watershed were calculated for different managerial schemes. Annual aboveground NPP (NPPa), maximum leaf biomass (Mleafmax), and water use simulated with runoff effects were 18%, 21%, and 8% greater, respectively, than those simulated without runoff redistribution. Furthermore, simulation with a proposed management strategy for sandy grassland landscapes, which prescribes different plant functional types (grasses, shrubs, and trees) distributed at different slope positions, led to increasing NPPa, Mleafmax, and water use by 34%, 38%, and 28%, respectively, compared to the current land use. The increases in NPP and biomass in turn would reduce wind erosion and associated dust-storm generation and enhance capacity of the system to retard degradation. The coupled model thus can be used as a tool to quantify effects of runoff redistribution for optimal land management and environmental protection, and the study has important managerial implications for semiarid systems, where degradation is of major concern, and runoff redistribution is important.

Ecosystems where plant-available nitrogen (N) is limited by constraints on decomposition may be quite capable of retaining additional N. However, there are many factors that will control the quantity of N retained, with potential implications for system carbon and nitrogen storage. We examined the retention and allocation of (15)N 2 years after labeling a semiarid, shortgrass steppe ecosystem in northeastern Colorado. The plant community of the study area is a patchy mixture of C3 (cool-season) and C4 (warm-season) graminoids; we hypothesized that differences in allocation patterns between the two plant types would lead to differing rates of N retention in this grazed system. We found that after three growing seasons (just over 2 years), an average of 28.3% of the original (15)N was retained in our plots, with nearly all of this N in soils (24.9%) rather than plants. Plots dominated by C3 plants had significantly less (15)N retained after 2 years than mixed C3-C4 plots. A high initial rate of retention by C3 plants, combined with a propensity for allocation to shoots rather than roots, likely led to this result in a system that typically has much of its aboveground tissue removed by grazers. In comparing our retention patterns to those of other studies in the shortgrass steppe, we found that the distribution of added (15)N to various ecosystem compartments (plants, mineral soil, soil organic matter) was similar across studies regardless of the experimental conditions, duration of study, and amount of (15)Nretained. We additionally observed the beginning of the formation of "resource islands," with (15)N being physically and biologically redistributed under plants from between plants.