Find research datasets worth reusing

Rangeland Analysis Platform - vegetation cover 1998

Rangeland Analysis Platform vegetation cover 1998 These data represent rangeland cover estimates determined by Jones et al. (2018) and as accessible on the Rangeland Analysis Platform (https://rangelands.app). Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses Band 2 - bare ground Band 3 - litter Band 4 - perennial forbs and grasses Band 5 - shrubs Band 6 - trees No Data value = 255 Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Cover estimates may not be suitable in other ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution is approximately 30m. Please attribute these data to: Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J. Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver. 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430. http://dx.doi.org/10.1002/ecs2.2430

Rangeland Analysis Platform - vegetation cover 2007

Rangeland Analysis Platform vegetation cover 2007 These data represent rangeland cover estimates determined by Jones et al. (2018) and as accessible on the Rangeland Analysis Platform (https://rangelands.app). Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses Band 2 - bare ground Band 3 - litter Band 4 - perennial forbs and grasses Band 5 - shrubs Band 6 - trees No Data value = 255 Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Cover estimates may not be suitable in other ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution is approximately 30m. Please attribute these data to: Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J. Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver. 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430. http://dx.doi.org/10.1002/ecs2.2430

Rangeland Analysis Platform - vegetation cover 2005

Rangeland Analysis Platform vegetation cover 2005 These data represent rangeland cover estimates determined by Jones et al. (2018) and as accessible on the Rangeland Analysis Platform (https://rangelands.app). Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses Band 2 - bare ground Band 3 - litter Band 4 - perennial forbs and grasses Band 5 - shrubs Band 6 - trees No Data value = 255 Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Cover estimates may not be suitable in other ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution is approximately 30m. Please attribute these data to: Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J. Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver. 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430. http://dx.doi.org/10.1002/ecs2.2430

Rangeland Analysis Platform - vegetation cover 2004

Rangeland Analysis Platform vegetation cover 2004 These data represent rangeland cover estimates determined by Jones et al. (2018) and as accessible on the Rangeland Analysis Platform (https://rangelands.app). Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses Band 2 - bare ground Band 3 - litter Band 4 - perennial forbs and grasses Band 5 - shrubs Band 6 - trees No Data value = 255 Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Cover estimates may not be suitable in other ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution is approximately 30m. Please attribute these data to: Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J. Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver. 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430. http://dx.doi.org/10.1002/ecs2.2430

Rangeland Analysis Platform - vegetation cover 2014

Rangeland Analysis Platform vegetation cover 2014 These data represent rangeland cover estimates determined by Jones et al. (2018) and as accessible on the Rangeland Analysis Platform (https://rangelands.app). Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses Band 2 - bare ground Band 3 - litter Band 4 - perennial forbs and grasses Band 5 - shrubs Band 6 - trees No Data value = 255 Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Cover estimates may not be suitable in other ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution is approximately 30m. Please attribute these data to: Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J. Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver. 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430. http://dx.doi.org/10.1002/ecs2.2430

Rangeland Analysis Platform - vegetation cover 2015

Rangeland Analysis Platform vegetation cover 2015 These data represent rangeland cover estimates determined by Jones et al. (2018) and as accessible on the Rangeland Analysis Platform (https://rangelands.app). Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses Band 2 - bare ground Band 3 - litter Band 4 - perennial forbs and grasses Band 5 - shrubs Band 6 - trees No Data value = 255 Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Cover estimates may not be suitable in other ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution is approximately 30m. Please attribute these data to: Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J. Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver. 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430. http://dx.doi.org/10.1002/ecs2.2430

opencc-by-4.0Jul 2020View details →

Replication data for: Conservation Gaps in Traditional Vegetables Native to Europe and Fennoscandia

Vegetables are rich in vitamins and other micronutrients and are important crops for healthy diets and diversification of the food system, and many traditional (also termed underutilized or indigenous) species may play a role. The current study analyzed 35 vegetables with a European region of diversity with the effort to map the conservation status in Fennoscandia and beyond. We mapped georeferenced occurrences and current genebank holdings based on global databases and conducted conservation gaps analysis based on representativeness scores in situ and ex situ. Out of the 35 target species, 19 got at a high priority score for further conservation initiatives, while another 14 species got a medium priority score. We identified a pattern where traditional vegetables are poorly represented in genebank holdings. This corresponds well to a lack of attention in the scientific community measured in number of published papers. Considering the grand challenges ahead in terms of climate change, population growth and demand for sustainability, traditional vegetables deserve greater attention. Our contribution is to provide a basis for conservation priorities among the identified vegetables species native to Fennoscandia.

opencc-zeroJun 2021View details →

Data from: Global vegetation patterns of the past 140,000 years

Aim Insight into global biome responses to climatic and other environmental changes is essential to address key questions about past and future impacts of such changes. By simulating global biome patterns 140 ka to present we aimed to address important questions about biome changes during this interval. Location Global. Taxon Plantae. Methods Using the LPJ-GUESS dynamic global vegetation model, we made 89 simulations driven using ice-core atmospheric CO2 concentrations, Earth's obliquity, and outputs from a pre-industrial and 88 palaeoclimate experiments run using HadCM3. Experiments were run for 81 time slices between 1 ka and 140 ka, seven 'hosing' experiments also being run, using a 1 Sv freshwater flux to the North Atlantic, for time slices corresponding to Heinrich Events H0 – H7. Using a rule-based approach, based on carbon mass and leaf area index of the LPJ-GUESS plant functional types, the biome was inferred for each grid cell. Biomes were mapped, and the extent and total vegetation biomass of each biome, and total global vegetation biomass, estimated. Results Substantial changes in biome extents and locations were found on all vegetated continents. Although the largest-magnitude changes were in Eurasia, important changes were seen in tropical latitudes and the Southern Hemisphere. Total global extent of most biomes varied on multi-millennial (orbital) time scales, although some (e.g. Tropical Raingreen Forest) responded principally to the ca. 100 kyr glacial–interglacial cycle and others (e.g. Temperate Broad-leaved Evergreen Forest) mainly to the ca. 20 kyr precession cycle. Many also responded to millennial contrasts between stadial ('hosing') and interstadial climates, with some (e.g. Tropical Evergreen Forest) showing stronger responses than to the multi-millennial changes. Main conclusions No two time slices had identical biome patterns. Even equivalent Holocene and last interglacial time slices, and the last and penultimate glacial maxima, showed important differences. Only a small proportion of global land area experienced no biome change since 140 ka; many places experienced multiple biome changes. These modelling experiments provided little evidence for long-term biome stability.

opencc-by-4.0Aug 2020View details →

Hakea vegetation dataset for training and evaluating segmentation network

This dataset is the version used for both training and evaluation of the models discussed the (in press) publication in Methods in Ecology and Evolution, "Detecting plant species in the field with deep learning and drone technology". Also included in this upload, results_inference_images.tar includes the output predictions for each of the trained models on the unseen test set.

opencc-by-4.0Dec 2019View details →

Supporting data for "A convolution method to assess subgrid-scale interactions between flow and patchy vegetation in biogeomorphic models"

Dataset necessary to reproduce the results and analyses presented in the paper: Gourgue, O., van Belzen, J., Schwarz, C., Bouma, T.J., van de Koppel, J. & Temmerman, S. (2020) A convolution method to assess subgrid-scale interactions between flow and patchy vegetation in biogeomorphic models, Journal of Advances in Modeling Earth Systems, submitted. The dataset contains: <ul> <li>Process-based model simulations, including their input files and the Python scripts to generate them (pre-processing), as well as the output files and Python scripts to post-process them.</li> <li>Flume experiment data processed for the model calibration.</li> <li>Python scripts to generate the figures and tables of the manuscript.</li> </ul>

opencc-zeroAug 2020View details →

Data from: Defining a spectrum of integrative trait-based vegetation canopy structural types

Vegetation canopy structure is a fundamental characteristic of terrestrial ecosystems that defines vegetation types and drives ecosystem functioning. We use the multivariate structural trait composition of vegetation canopies to classify ecosystems within a global canopy structure spectrum. Across the temperate forest subset of this spectrum we assess gradients in canopy structural traits, characterize canopy structural types (CST), and evaluate drivers and functional consequences of canopy structural variation. We derive CSTs from multivariate canopy structure data, illustrating variation along three primary structural axes and resolution into six largely distinct and functionally relevant CSTs. Our results illustrate that within-ecosystem successional processes and disturbance legacies can produce variation in canopy structure similar to that associated with sub-continental variation in forest types and ecoclimatic zones. The potential to classify ecosystems into CSTs based on suites of structural traits represents an important advance in understanding and modeling structure-function relationships in vegetated ecosystems.

opencc-zeroSep 2020View details →

VTFT_Demography: global ageclass simulation data from the LPJ-wsl v2.0 Dynamic Global Vegetation Model

Forest ecosystem processes follow classic responses with age, peaking production around canopy closure and declining thereafter. Although age dynamics might be more dominant in certain regions over others, demographic effects on net primary production (NPP) and heterotrophic respiration (Rh) are bound to exist. Yet, explicit representation of ecosystem demography is notably absent in most global ecosystem models. This is concerning because the global community relies on these models to regularly update our collective understanding of the global carbon cycle. This paper aims to fill this gap in understanding by presenting the technical developments of a computationally-efficient approach for representing age-class dynamics within a global ecosystem model, the LPJ-wsl v2.0 Dynamic Global Vegetation Model. The modeled age-classes are initially created by fire feedbacks, wood harvesting, and abandonment of managed land, otherwise aging naturally until a stand-clearing disturbance is simulated or prescribed. In this paper, we show that the age-module can capture classic demographic patterns in stem density and tree height compared to inventory data, and that patterns of ecosystem function follow classic responses with age. We also present a few scientific applications of the model to assess the modeled age-class distribution over time and to determine the demographic effect on ecosystem fluxes relative to climate. Simulations show that, between 1860 and 2016, zonal age distribution on Earth was driven predominately by fire, causing a ~45-year difference in ages between boreal (50N-90N) and tropical (23S-23N) latitudes. Land use change and land management was responsible for an additional decrease in zonal age by -6 years in boreal and by -21 years in temperate (23N-50N) and tropical latitudes, with the anthropogenic effect on zonal age distribution increasing over time. A statistical model helped reduced LPJ-wsl complexity by predicting per-grid-cell annual NPP and Rh fluxes by three terms: precipitation, temperature and age-class; at global scales, R2 was between 0.95 and 0.98. As determined by the statistical model, the demographic effect on ecosystem function was often less than 0.10 kg C m-2 yr-1 but as high as 0.60 kg C m-2 yr-1 where the effect was greatest. In eastern forests of North America, the demographic effect was of similar magnitude, or greater than, the effects of climate; demographic effects were similarly important in large regions of every vegetated continent. Spatial datasets are provided for global ecosystem ages and the estimated coefficients for effects of precipitation, temperature and demography on ecosystem function. The discussion focuses on our finding of an increasing role of demography in the global carbon cycle, the effect of demography on relaxation times (resilience) following a disturbance event and its implications at global scales, and a finding of a 40-Pg C increase in turnover from age dynamics at global scales. Whereas time is the only mechanism that increases ecosystem age, any additional disturbance not explicitly modeled will decrease age. This LPJ-based age-module therefore simulates the upper limit of age-class distributions on Earth and represents another step forward towards understanding the role of demography in global ecosystems.

opencc-zeroSep 2020View details →

Grazing and climate change have site-dependent interactive effects on vegetation in Asian montane rangelands

1. Climate over Asian montane rangelands is changing faster than the global average, posing serious threats to the future of the region's livestock-based economies and cultures. Effects of climate change on rangeland vegetation likely depend on grazing by herbivores but the potential responses of vegetation to such changes in climate and grazing regimes remains unclear. 2. We examined vegetation responses to experimentally simulated climate change (warming, drought and increased rainfall) and grazing (clipping vegetation) between 2015-2018 at two mountain rangeland sites: Spiti valley, in the Indian Trans-Himalaya and Tost, in the Gobi-Altai Mountains in Mongolia. 3. Clipping and climate change manipulations interactively reduced vegetation cover and biomass but did not affect species richness. Treatment effects and their interactions varied between sites. In ungrazed plots, vegetation cover and biomass declined sharply in response to warming (18-35%) and drought (20-50%) at the two sites, and, surprisingly also declined slightly in response to increased rainfall (20%) at Tost. While the effects of climate treatments were largely similar in the grazed and ungrazed plots in Tost, they were larger in the ungrazed plots in Spiti. The decline in vegetation cover was driven by a decline in the cover of both forbs and grasses. 4. In combination, grazing and warming (Tost) or drought (Spiti) had sub-additive effects, i.e., the decrease in vegetation cover in response to grazing and warming/drought was less than the sum of their independent effects but greater than the effect of either manipulation alone. Of the two, warming had a greater effect than drought at the more arid site (Tost), while drought had a larger effect at the more mesic site (Spiti). Synthesis and applications. Our findings show that future changes in climate, including just over 1oC of warming, could undermine the sustainability of pastoral economies and the persistence of wildlife across Asian montane rangelands. Further, grazing by herbivores will play an important role in mediating rangeland responses to climate change; thus, pasture management in concert with local pastoralists will be crucial in mitigating the adverse effects of climate change on rangelands, pastoral livelihoods and wildlife populations.

opencc-zeroOct 2020View details →

Improving the representation of high-latitude vegetation distribution in dynamic global vegetation models

Vegetation is an important component in global ecosystems, affecting the physical, hydrological and biogeochemical properties of the land surface. Accordingly, the way vegetation is parameterised strongly influences predictions of future climate by Earth system models. To capture future spatial and temporal changes in vegetation cover and its feedbacks to the climate system, dynamic global vegetation models (DGVM) are included as important components of land surface models. Variation in the predicted vegetation cover from DGVMs therefore has large impacts on modelled radiative and non-radiative properties, especially over high-latitude regions. DGVMs are mostly evaluated by remotely sensed products, but rarely by other vegetation products or by in-situ field observations. In this study, we evaluate the performance of three methods for spatial representation of vegetation cover with respect to prediction of plant functional type (PFT) profiles – one based upon distribution models (DM), one that uses a remote sensing (RS) dataset and a DGVM (CLM4.5BGCDV). PFT profiles obtained from an independently collected vegetation data set from Norway were used for the evaluation. We found that RS-based PFT profiles matched the reference dataset best, closely followed by DM, whereas predictions from DGVM often deviated strongly from the reference. DGVM predictions overestimated the area covered by boreal needleleaf evergreen trees and bare ground at the expense of boreal broadleaf deciduous trees and shrubs. Based on environmental predictors identified by DM as important, we suggest implementation of three novel PFT-specific thresholds for establishment in the DGVM. We performed a series of sensitivity experiments to demonstrate that these thresholds improve the performance of the DGVM. The results highlight the potential of using PFT-specific thresholds obtained by DM in development and benchmarking of DGVMs for broader regions. Also, we emphasize the potential of establishing DM as a reliable method for providing PFT distributions for evaluation of DGVMs alongside RS.

opencc-zeroNov 2020View details →

Post-fire vegetation succession in the Siberian subarctic tundra over 45 years

Wildfires are relatively rare in subarctic tundra ecosystems, but they can strongly change ecosystem properties. Short-term fire effects on subarctic tundra vegetation are well documented, but long-term vegetation recovery has been studied less. The frequency of tundra fires will increase with climate warming. Understanding the long-term effects of fire is necessary to predict future ecosystem changes. We used a space-for-time approach to assess vegetation recovery after fire over more than four decades. We studied soil and vegetation patterns on three large fire scars (>44, 28 and 12 years old) in dry, lichen-dominated forest tundra in Western Siberia. On 60 plots, we determined soil temperature and permafrost thaw depth, sampled vegetation and measured plant functional traits. We assessed trends in NDVI to support the field-based results on vegetation recovery.Soil temperature, permafrost thaw depth and total vegetation cover had recovered to pre-fire levels after >44 years, as well as total vegetation cover. In contrast, after >44 years, functional groups had not recovered to the pre-fire state. Burnt areas had lower lichen and higher bryophyte and shrub cover. The dominating shrub species, Betula nana, exhibited a higher vitality (higher specific leaf area and plant height) on burnt compared with control plots, suggesting a fire legacy effect in shrub growth. Our results confirm patterns of shrub encroachment after fire that were detected before in other parts of the Arctic and Subarctic. In the so far poorly studied Western Siberian forest tundra we demonstrate for the first time, long-term fire-legacies on the functional composition of relatively dry shrub- and lichen-dominated vegetation.

opencc-zeroDec 2020View details →

Vegetation cover and plant diversity on cold climate green roofs

Both vegetation abundances and community compositions play important roles for the functions of green roofs (e.g. stormwater retention, habitat provision, aesthetic appearance). However, green roof vegetation can change significantly over time, which may consequently affect the functions related to them. This study investigated vascular plant covers and species compositions on 41 roof sections located in Sweden's subarctic and continental climate zones. For the roof sections with a known originally intended vascular plant composition (n=32), on average 24±9% of the intended species were present in surveys while unintended species made up 69±3% of the the species found. The Intended species dominated plant cover (93±3%) and Sedum acre (58±36% cover) was the most commonly found species. As revealed in previous studies, substrate depth had a positive relationship with plant cover and species richness. The vascular plant cover of the roofs in this study was not related to species richness as hypothesized but instead had a significant negative correlation with moss cover. The results in this study emphasize the importance of substrate depth for both plant abundance and species diversity, and that even in a cold climate, colonising unintended species can have a great contribution to the species richness of green roofs. However, since most colonising species formed sparse cover on the roofs, their potential benefit to green roof functions that benefit from a dense vegetation cover (e.g. stormwater management and thermal performance) could be limited while the intended vegetation performs these functions more effectively.

opencc-byDec 2020View details →

Data for manuscript: An ecogeomorphic framework coupling sediment modeling with invasive riparian vegetation dynamics

Datasets (aside from the publicly available GIS datasets) used in the analyses presented in the manuscript "An ecogeomorphic framework coupling sediment modeling with invasive riparian vegetation dynamics."

opencc-by-4.0Jan 2021View details →

Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses

Basic data from publication <a href="https://doi.org/10.3390/rs13010147">https://doi.org/10.3390/rs13010147</a> All_TDRdata.csv contains the data from 48 TDR sensors (30 cm) installed in the three rainout shelters. <ul> <li>Sensors 1 - 18 were installed vertically to obtain soil moisture content averaged over the 10 - 40 cm profile, on 6 locations per shelter</li> <li>Sensors 19-21 were installed diagonally to obtain soil moisture content averaged over the 20 - 40 cm profile on one location per shelter</li> <li>Sensors 22-24 were installed diagonally to obtain soil moisture content averaged over the 40 - 60 cm profile on one location per shelter</li> <li>Sensors 25-27 were installed horizontally to obtain soil moisture content at 10 cm depth on one location per shelter</li> <li>Sensors 28-30 were installed horizontally to obtain soil moisture content at 20 cm depth on one location per shelter</li> <li>Sensors 31-33 were installed horizontally to obtain soil moisture content at 30 cm depth on one location per shelter</li> <li>Sensors 34-36 were installed horizontally to obtain soil moisture content at 40 cm depth on one location per shelter</li> <li>Sensors 37-39 were installed horizontally to obtain soil moisture content at 50 cm depth on one location per shelter</li> <li>Sensors 40-42 were installed horizontally to obtain soil moisture content at 60 cm depth on one location per shelter</li> <li>Sensors 43-45 were installed horizontally to obtain soil moisture content at 70 cm depth on one location per shelter</li> <li>Sensors 46-48 were installed horizontally to obtain soil moisture content at 80 cm depth on one location per shelter</li> </ul> Climate.txt contains the daily averaged microclimatic data PhenotypingData.csv contains the phenotypic data from the UAV flights and the breeder scores

opencc-zeroJan 2021View details →

Size-selective exclusion of mammals and invertebrates differently affects grassland plant communities depending on vegetation type

Human-caused loss of vertebrate and invertebrate animals, defaunation, is increasing, and potentially affects plant community structure of diverse grassland ecosystems worldwide. We experimentally simulated defaunation using size-selective fences to progressively exclude large-, medium- and small-sized mammals, and invertebrates from two subalpine vegetation types in the Swiss National Park (SNP): intensively grazed short-grass and moderately grazed tall-grass vegetation. We assessed plant community properties yearly from 2009 to 2013, and examined treatment effects on plant community structure in the two grassland types. In the short-grass vegetation, the exclusion of large mammals increased total plant biomass, while the exclusion of large and medium-sized mammals increased total, grass and forb biomass compared to when all animals had access. These increases became stronger when also invertebrates were excluded. The exclusion of all mammals and invertebrates increased biomass of grasses by 205%, forbs by 100% and total plant biomass by 118% compared to when all animals had access, hence enhancing relative biomass of grasses from 43.6% to 60%, changing plant species composition and lowering richness of forbs by 16%, the number of plant families by 13% and family-level Shannon diversity by 23%. In contrast to these significant community-level responses found in the short-grass vegetation, there was no evidence that the size-selective exclusion of animals altered the plant community structure of the tall-grass vegetation. The contrasting results were due to the difference in plant community composition prior to our experiment, which were related to differences in quantity and quality of forage and in grazing intensities of herbivores between the two grassland types. Synthesis. Our results showed that different-sized animals, in particular large mammals and invertebrates, contributed to maintain the plant community structure in the short-grass vegetation, highlighting the importance of multiple, functionally different animal groups for ecosystem functioning and stability. In contrast to the short-grass vegetation, we could not detect such a top-down control by animals in the tall-grass vegetation. Our results suggest that potential defaunation effects on grassland plant community structure depend on the degree of grazing pressure release and grassland vegetation type.