Grassland Sites Research Articles

Local adaptation of a generalist hemiparasitic plant to one of its potential host plants

Coevolution is often found in parasite–host interactions, but has not yet been described for hemiparasitic plants and their hosts. Root hemiparasites like Rhinanthus alectorolophus perform photosynthesis but also parasitize other plant species, some of which (e.g. Plantago lanceolata) may defend themselves against parasite attack by blocking the haustoria of the parasites. We grew seedlings of the hemiparasite R. alectorolophus and the potential host P. lanceolata from seven grassland sites in a factorial design. To detect differences in host defence, we also included hosts from two ‘naïve' populations from regions where the parasite does not occur. R. alectorolophus grew consistently larger and had higher fitness with sympatric than with allopatric hosts, suggesting parasite adaptation to local host populations. Moreover, R. alectorolophus remained smallest with allopatric hosts from the same region and reached intermediate sizes with allopatric hosts from other regions or naïve hosts, suggesting host adaptation to parasites at the regional scale. Parasite presence reduced the size of the host plants already after four weeks, but only that of hosts with ‘experience' of the parasite, suggesting an early host response. Follow‐up experiments confirmed that parasites attach to hosts already after four weeks and hosts respond by changing belowground allocation patterns. However, parasite roots did not preferentially grow towards sympatric hosts. Our results suggest that local adaptation to hosts can occur even in generalist parasites and does not require specialization on individual hosts. We discuss the role of potential mechanisms, including variation in chemical signalling (early) and in host defence (late effects).

Sphingomonas clade and functional distribution with simulated climate change.

Microbes are essential for the functioning of all ecosystems, and as global warming and anthropogenic pollution threaten ecosystems, it is critical to understand how microbes respond to these changes. We investigated the climate response of Sphingomonas, a widespread gram-negative bacterial genus, during an 18-month microbial community reciprocal transplant experiment across a Southern California climate gradient. We hypothesized that after 18 months, the transplanted Sphingomonas clade and functional composition would correspond with site conditions and reflect the Sphingomonas composition of native communities. We extracted Sphingomonas sequences from metagenomic data across the gradient and assessed their clade and functional composition. Representatives of at least 12 major Sphingomonas clades were found at varying relative abundances along the climate gradient, and transplanted Sphingomonas clade composition shifted after 18 months. Site had a significant effect (PERMANOVA; P < 0.001) on the distribution of both Sphingomonas functional (R2 = 0.465) and clade composition (R2 = 0.400), suggesting that Sphingomonas composition depends on climate parameters. Additionally, for both Sphingomonas clade and functional composition, ordinations revealed that the transplanted communities shifted closer to the native Sphingomonas composition of the grassland site compared with the site they were transplanted into. Overall, our results indicate that climate and substrate collectively determine Sphingomonas clade and functional composition.IMPORTANCESphingomonas is the most abundant gram-negative bacterial genus in litter-degrading microbial communities of desert, grassland, shrubland, and forest ecosystems in Southern California. We aimed to determine whether Sphingomonas responds to climate change in the same way as gram-positive bacteria and whole bacterial communities in these ecosystems. Within Sphingomonas, both clade composition and functional genes shifted in response to climate and litter chemistry, supporting the idea that bacteria respond similarly to climate at different scales of genetic variation. This understanding of how microbes respond to perturbation across scales may aid in future predictions of microbial responses to climate change.

Organic Carbon Stock in Mineral Soils in Cropland and Grassland in Latvia

This study aimed to assess soil organic carbon (SOC) concentration and stock in mineral soils in cropland and grassland in Latvia, considering soil groups and texture classes. It covered 197 sites across Latvia (152 in cropland, 45 in grassland). Soil profile description and sampling (at depths of 0–10 cm, 10–20 cm, and 20–40 cm) were conducted between 2021 and 2023. Laboratory analyses included soil bulk density (SBD), total carbon (TC), total nitrogen (TN), carbonate content, pH, and extractable phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg). SOC stock was calculated, and correlations with other soil parameters were determined. In cropland sites, Arenosols and Stagnosols had the lowest SOC concentration and stock, while Gleysols and Phaeozems had the highest. In grassland sites, Retisols exhibited the lowest SOC concentration in the 0–20 cm layer, while Planosols had the highest SOC concentration in this layer. Conversely, in the 20–40 cm layer, Retisols showed the highest SOC concentration, while Gleysols had the lowest concentration. Regarding SOC stock in grassland sites, Planosols exhibited the highest values, while the lowest values were observed for Retisols and Umbrisols. Contrary to our hypothesis that grassland exhibits higher SOC stock than cropland, our results show the reverse for Phaeozems, the dominant WRB soil group in this study: a higher average SOC concentration and stock in cropland compared to grassland. However, very low occurrence of some soil groups and lack of some soil groups for grassland sites hinders the correct interpretation of these results, and further investigations are required in future studies.

Comparing structural soil properties of boreal clay fields under contrasting soil management

AbstractSoil management significantly affects soil structure. Tillage and grassland renovation may have destructive influences, while conversion of arable land to grassland can improve pore structure and related soil functions. In crop rotations including perennial grasses, soil structure is affected by these counteracting processes. This work aimed to quantify the impacts of different soil management practices on the structure of boreal clay soils. We studied intact topsoil samples taken from two locations by X‐ray computed microtomography, image‐based flow simulations and water retention measurements. At both locations, adjacent field areas with two contrasting soil management histories were compared. Both locations had at least a 30‐year‐old grassland site, which was compared to arable soils either under no‐till management with annual crop rotation or conventional tillage with crop rotation including perennial grasses. Both imaging and water retention measurements showed significant differences in the soil macropore structure between the long‐term grassland and arable no‐till soil such that macroporosity and hydraulic conductivity of the long‐term grassland were higher than those of soil under agricultural production. On the contrary, at the second study location, differences between long‐term grassland and cultivated fields were minor and the long‐term grassland exhibited lower macroporosity. Our results confirm that soil management affects the macropore structure of boreal clay soil and that no‐till annual cropping and periodically tilled crop rotation including perennial phases exert different effects on the soil structure as compared with long‐term grassland.

Potential gains in soil carbon and nitrogen as a result of systems perenniality: Insights from on‐farm experiments and soil organic matter fractions

AbstractUnderstanding soil organic matter (SOM) dynamics along gradients of land intensification is critical to guide conservation goals towards improvements in soil carbon (C) and nitrogen (N) storage. In this study, we clarified (a) how the C and N concentrations within SOM fractions of distinct ecological relevance responded to soil management representing a cropland‐grassland gradient and (b) how these operationally defined fractions affected soil physicochemical and biological properties. We compared sites with annual row crop rotations with and without cover crops (i.e. cropland soils) with perennial grassland sites (i.e. reference soil) by sampling near‐surface soils from statewide on‐farm cover crop experiments replicated across four agro‐ecoregions in Midwest USA. Soil management had a significant main effect on C and N content in SOM fractions, but responses were site‐ and fraction‐specific. We found that C content of free particulate organic matter and water‐extractable organic matter (WEOM) of reference soils were 58%–76% and 31%–59% greater than those of the cropland soils in two of the four sites. Differences in N content of WEOM because of soil management were observed in two of the four sites. These reference soils had between 40% and 60% greater N than cropland soils. Additionally, the N content of aggregate occluded POM (o‐POM) of reference soils was three times greater than those of the cropland soils in one of the four sites. Broadly across bulk and SOM fractions, high declines in cropland C and N relative to reference soils were observed in non‐irrigated and strip‐till sites and coarse‐texture soils. Free and o‐POM C and N were strongly associated with aggregate stability, water infiltration and enzyme activity, whereas C and N contents of WEOM and MAOM were correlated with soil's ability to hold onto essential nutrients (e.g. calcium, magnesium, potassium and sodium). Although the potential of cover crops to drive changes on ecologically meaningful SOM fractions is less pronounced in the short (3 year) term, the findings demonstrate the potential of continuous living cover as an approach to agroecosystem design to improve soil functions closely related to SOM characteristics.

Extreme low air temperature and reduced moisture jointly inhibit respiration in alpine grassland on the Qinghai-Tibetan Plateau

Alpine grassland is the main vegetation on the Qinghai-Tibetan Plateau (QTP) and exhibits high sensitivity to extreme weather events. With global warming, extreme weather events are projected to become more frequent on the QTP. However, the impact of these extreme weather events on the carbon cycle of alpine grassland remains unclear. The long-term in-situ carbon fluxes data was collected from 2013 to 2022 at an alpine grassland site to examine the impact of extreme low air temperature (ELT) and reduced moisture (including air and soil) on carbon fluxes during the growing season. Our findings indicated that a significant increase in net ecosystem production (NEP) after 2019, with the average NEP increasing from 278.91 ± 43.27 g C m−2 year−1 during 2013–2018 to 415.45 ± 45.29 g C m−2 year−1 during 2019–2022. The ecosystem carbon use efficiency (CUE) increased from 0.38 ± 0.06 during 2013–2018 to 0.62 ± 0.11 during 2019–2022. By combining concurrently measured environmental factors and remote sensing data, we identified the factors responsible for the abrupt change in the NEP after 2019. This phenomenon was caused by an abrupt decrease in ecosystem respiration (Reco) after 2019, which resulted from the inhibition imposed by ELT and reduced moisture. In contrast, gross primary production (GPP) remained stable from 2013 to 2022, which was confirmed by the remotely sensed vegetation index. This study highlights that combined extreme weather events associated with climate change can significantly impact the NEP of alpine grassland, potentially affecting different carbon fluxes at different rates. These findings provide new insights into the mechanisms governing the carbon cycle of alpine grassland.

Power law in species–area relationship overestimates bacterial diversity in grassland soils at larger scales

AbstractAimSpecies–area relationships (SAR) are widely utilized for estimating the species richness and its spatial turnover across various scales. Despite the prevalent characterization of SAR using the power law in many microbial community studies, its efficacy remains unvalidated. This study aims to characterize the microbial SAR and its mechanisms in alpine grassland soils on the Qinghai‐Tibet Plateau (QTP).LocationQinghai‐Tibet Plateau, China.Time PeriodAugust 2014.Major Taxa StudiedSoil bacteria.MethodsSoil samples were collected from five alpine grassland sites on the QTP. Employing a nested sampling strategy at each site, soil samples were collected in plot sizes ranging from 0.5 × 0.5 m2 to 2048 × 2048 m2. Soil bacterial communities were analysed by sequencing 16S ribosomal RNA gene amplicons using an Illumina MiSeq.ResultsThe bacterial SAR exhibited a logarithmic power law (R2: 0.952–0.999), outperforming the power law (R2: 0.701–0.852). Consequently, the most widely adopted power law led to an overestimation of species richness by up to 15.07% in areas &gt;256 × 256 m2, and the regional maximum theoretical richness based on Chao1 by up to 9.88%. Mechanistically, the passive sampling hypothesis was refuted through the rarefied species richness analysis, and the disproportionate effect hypothesis was rejected based on analyses of the effective numbers of species number conversions for the probability of interspecific encounters (SPIE). Notably, Pearson and multiple linear regression analyses indicated that the spatial turnover of bacterial richness was determined by the environmental heterogeneity (R2: 0.855–0.999), rather or better than environmental variables themselves, supporting the ‘environment heterogeneity hypothesis’.Main ConclusionsSoil bacterial SAR in alpine grasslands exhibited a logarithmic power relationship. Spatial turnover was primarily governed by the environmental heterogeneity. In contrast, the traditional power law leads to an overestimation of soil bacterial diversity at the regional scale.

Quantification of nitrates leaching from grassland soils in winter using the Burns model

This paper presents the results of a study on the level of nitrate leaching from the 0–30 cm layer of grassland (GL) soil in the Lublin Voivodship during the winters of 2018/2019, 2019/2020 and 2020/2021. The amounts of leached nitrates were determined using the Burns model. For the calculations based on this model – directly and indirectly, the results determination of residual nitrate nitrogen, texture and organic matter in GL soils, obtained within the framework of agricultural monitoring of soils by the National Chemical and Agricultural Station (KSChR), and results of system meteorological measurements conducted by the Institute of Meteorology and Water Management – National Research Institute (IMGW-PIB) were used. The analysed soil samples were taken from 39 permanent control and measurement grassland sites. The research discovered in particular that: – the average leaching of nitrate nitrogen from GL mineral soil in the three analysed periods was 16.2 and 5.1 kg N∙ha–1 from organic soil; – on average, in autumn during the entire study period, 55.3% of NO3-N leached from the 0–30 cm layer of GL mineral soil, and 27.3% from organic soil; – among different agronomic categories of mineral soil, the highest leaching of NO3-N was recorded from medium soil (17.4 kg N∙ha–1) and the lowest from heavy soil (11.5 kg N∙ha–1); – individually determined values of NO3-N leaching from soil varied significantly from 0 to 68.5 kg N∙ha–1 for mineral soil and from 0.1 to 23.65 kg N∙ha–1 for organic soil.

Evaluation of drone surveys for ungulates in southwestern rangelands

AbstractDrone platforms are increasingly used for aerial wildlife surveys, but the validity of population counts has not been fully evaluated in all environments. Aerial surveys generally undercount the true population size and one must estimate detection probability (p) to correct for missed individuals. Detection probability for visual observers is influenced by vegetation and terrain characteristics, but the use of thermal cameras as the observer may also introduce additional factors influencing detection probability. We conducted diurnal, thermal‐based drone surveys for ungulates during February–April 2020 in South Texas, USA, on sites with varying degrees of woody cover and terrain. We examined histograms of georeferenced perpendicular distances to determine the effect of habitat on detection probabilities. We also examined precision in population estimates and variation in repeated surveys. Finally, we compared drone population estimates to independent estimates derived from helicopter, spotlight, and trail‐camera surveys. Distributions of perpendicular distances from the transect were affected by habitat characteristics. A flat grassland site had relatively few detections near the transect because thermal (solar) reflectance in the center of the footage obscured detections. A hilly brushy site had a uniform p (1.00) but resulted in a severe undercount due to the inability of the drone to follow contours of hills. The flat brushy site had a lower p (0.63), indicating visibility bias. Two additional flat, brushy sites were surveyed repeatedly (n = 5 and 9 surveys, respectively). All combinations of up to 3 repeated surveys were pooled to meet the recommended minimum number of detections for distance sampling analyses (≥60 detections). Population estimates had acceptable precision (CV ≤ 20%) 80.7% of the time and variation among repeated surveys was acceptable (CV = 9% and 23%, respectively). Drone‐based population estimates were comparable with estimates generated from corrected helicopter, spotlight, and trail‐camera surveys. Overall, diurnal drone surveys can generate population estimates for large ungulates on southwestern rangelands after accounting for visibility bias, but may be limited by terrain and thermal conditions.

Changes in the Soil Organic Carbon of Grasslands in the High Andes of Peru after Their Conversion to Croplands and Their Environmental Controls

The high-Andean grasslands of Peru provide a wide range of goods and services, not only locally, but also regionally and globally. However, land-use change and global warming are threatening these ecosystems, of which soil organic carbon (SOC) is a key element affecting their sustainability. In this study, we have analyzed the variation of SOC stocks to a depth of 20 cm in 16 paired cropland and grassland sites located in the Sullccapallcca stream micro-watershed (elevation &gt; 3600 m.a.s.l., Ayacucho, Peru). We have also analyzed the environmental controls on the SOC stocks and their variation with land-use change. We found that the studied high-Andean grasslands store high SOC contents (247 Tn SOC ha−1), whose spatial variability was partially explained by the slope of the terrain (r2 = 0.26, p &lt; 0.05). Despite the higher NDVI, the conversion of these grasslands into croplands decreased the SOC stock by 39 Tn SOC ha−1 on average, a decrease that was more pronounced when the initial SOC content of the grassland was higher (r2 = 0.60, p &lt; 0.05). This study provides the first evidence of the effects of land-use change on the SOC in the region, although the mechanisms involved still need to be investigated.

Design and partial validation of novel eDNA qPCR assays for three common North American tick (Arachnida: Ixodida) species

AbstractThe range expansion of ticks to higher latitudes poses a severe threat to human health exposing human populations who had no prior contact with ticks to several harmful tick‐borne diseases. Early detection of ticks in new areas is critical to help inform the public and medical professionals of the dangers associated with tick encounters. Environmental DNA represents a novel survey method that could provide reliable records of tick occurrences and timely warnings of their range expansions. In this study, we designed novel eDNA qPCR assays for three common North American tick species (Dermacentor variabilis, Amblyomma americanum, and Ixodes scapularis) and tested them on 51 samples of grasses and leaf litter collected from 12 grassland and forest sites in central and southern Illinois. We provide in silico and in vitro validation of all three assays; however, we were unable to generate any positive detections from field samples. Our lack of eDNA detections likely stems from low eDNA deposition rates coupled with rapid degradation in grasslands and forests, a problem exacerbated by terrestrial eDNA sampling methods limited by volume of substrate. We provide recommendations for improving sample collection methods to increase detection probability in future efforts. Continued research should focus on the viability of eDNA to detect small terrestrial invertebrates, like ticks, and it potential as early warning indicator of the spread of vector‐borne diseases.

Driving mechanisms of community biomass allocation along environmental gradients in different grasslands in China

A variable future climate would lead to changes in the biomass allocation pattern of plant communities, but its divergent changes under different environments have not been clearly explored, greatly limiting a better understanding of the responsess of grassland ecosystems to environmental changes. Herein, we conducted field samplings at 215 grassland sites in the Qinghai-Tibetan and Inner Mongolian Plateaus to analyze community biomass allocation patterns (specifically, the ratio of root to shoot, R/S) in various grasslands along environmental gradients. We found a gradual increase in R/S from humid to semi-arid and arid environments across both plateaus. In humid environment, soil factor had a significant effect on the R/S of alpine humid grassland, while climate factor had a significant effect on the R/S of humid grassland. In semi-arid environment, both climate and plant factors had significant effects on R/S in semi-arid grassland. In arid environments, climate and plant factors had significant effects on R/S in arid grassland. These findings emphasize the multifaceted role of environmental factors in shaping biomass allocations across diverse ecosystems, enriching our understanding of ecological dynamics. The current results are timely in advancing the fundamental understanding of the mechanisms of biomass allocation in grasslands and are useful for global research on grasslands in different environments.

Chronic drought decreased organic carbon content in topsoil greater than intense drought across grasslands in Northern China

Grasslands are expected to experience extreme climatic events such as extreme drought due to rising global temperatures. However, we still lack evidence of how extreme drought influence soil organic carbon (SOC) content in grassland ecosystems. We experimentally imposed extreme drought in two ways – chronic drought (66 % reduction in precipitation from May to August) and intense drought (100 % reduction in precipitation from June to July) to measure the effects of these two drought types on (SOC) content across six grassland sites that spanning desert steppe, typical steppe and meadow steppe in northern China. The experiment followed a randomized complete block design with six replicates of each treatment at each site. Our results showed that both chronic and intense drought decreased SOC content in the topsoil (0–10 cm) and the loss was higher in arid grasslands (desert steppe and typical steppe). Chronic drought decreased SOC content more than intense drought, with the effect again being strongest in arid grasslands. Furthermore, the response of SOC content to extreme drought was linked with the response of net primary productivity. Specifically, the response of SOC content was negatively correlated with drought sensitivity of above-ground net primary productivity (ANPP) but positively correlated with drought sensitivity of belowground NPP (BNPP). Overall, our results suggest that shifts in grassland SOC content with future drought will depend on the types of drought as well as the productivity responses and local climatic conditions such as precipitation, temperature, and aridity. The differential extreme drought impacts described here may facilitate predictions of climate change impacts on ecosystem carbon cycling.

Shrub Age and Water Dynamics Influence Primary Production, Carbon, and Nitrogen Stocks in a Coastal Environment

Drivers of shrub primary production and associated landscape impacts of encroachment are well known in drylands but have not been thoroughly studied in mesic and coastal habitats. The native, nitrogen-fixing shrub, Morella cerifera, has expanded into coastal grassland along the US Atlantic coast due to warming temperatures, but impacts on ecosystem function are not well known. Annual net primary production (ANPP) of Morella cerifera and key environmental drivers were measured long-term (1990 – 2007) across a chronosequence of shrub age on a mid-Atlantic barrier island. Soil and groundwater nutrients were compared with un-encroached grassland soil to evaluate impacts of vegetation on nutrient dynamics. Shrub ANPP declined with age at the same rate among all thickets, but there was variability from year to year. When climate variables were included in models, shrub age, precipitation, and freshwater table depth were consistent predictors of ANPP. Water table depth decreased over time, reducing ANPP. This may be due to rising sea-level, as well as to feedbacks with shrub age and evapotranspiration. Soil N and C increased with shrub age and were higher than adjacent grassland sites; however, there was a significant loss of N and C to groundwater. Our results demonstrate that drivers influencing the encroachment of shrubs in this coastal system (i.e., warming temperature) are not as important in predicting shrub primary production. Rather, interactions between shrub age and hydrological properties impact ANPP, contributing to coastal carbon storage.

Quest to find compromised spatial and temporal resolutions for integrating remote sensing data with an agro-ecosystem model for grasslands

This paper addressed one of the main challenges in assimilating remote sensing derived variables into process-based crop model simulations, which is the inconsistent spatial and temporal resolution between information obtained from remote sensing and the outputs of process-based agroecosystem model. We proposed an applied method to reduce the number of required simulations by identifying (i) optimal points in time where additional information from remote sensing has the largest positive influence on the model performance and (ii) options to cluster 10 m grid cells to larger cells without compromising their information content. The MONICA (Model for Nitrogen and Carbon) model was applied to simulate above and below ground biomass in two grassland sites located in southern and eastern parts of Germany. The model was calibrated using LAI values obtained from Sentinel-2 and the sensitivity of output variables to two key root parameters (Root Form factor and specific root length) was evaluated. Our results showed that one or two satellite images covering the critical time periods right after cutting events significantly improved the predictions of grass yields produced by a mechanistic agroecosystem models (by up to 30 %). A larger number of images at other grass growth stages would not further improve the predictive power of the model. We also found that the sensitivity to these critical time periods was independent of model parameters. The mixed-resolution scheme (between 10 and 50 m) achieved better results compared with the high-resolution standalone state-updating method, yet it reduced computational costs by more than 50 %. In conclusion, we proposed a methodology to reduce the number of required simulations for data assimilation by aggregating data from fine to coarse resolutions. Our method was promising for applying data assimilation over large areas and benefiting more from satellite information for real-time prediction of agricultural productivity.

Ambient dose equivalent rates of gamma radiation from natural radionuclides and 137Cs at grasslands and forests in the area of the Belarusian NPP in the pre-commissioning period (2019).

In situ gamma-spectrometric measurements were performed at grasslands (45 plots) and forests (6 plots) in the vicinity of the Belarusian nuclear power plant in September-October 2019. The aim of the study was to evaluate the baseline level of ambient dose equivalent rates of gamma radiation from natural radionuclides and 137Cs in the period preceding the commissioning of the NPP. The study revealed more than a 2-fold variability in values of the total ambient dose equivalent rate: from 29 to 72 nSv/h. This spread can be explained by variability in the content of natural radionuclides in the environment and, accordingly, ambient dose equivalent rate. At forest sites, compared to grassland sites, the values of ambient dose equivalent rates of gamma radiation from natural radionuclides were statistically significantly lower. The contribution of gamma radiation from 137Cs to the total ambient dose equivalent rate was insignificant and averaged 3% for grasslands and 6% for forests.

Grass Evolutionary Lineages Can Be Identified Using Hyperspectral Leaf Reflectance

AbstractHyperspectral remote sensing has the potential to map numerous attributes of the Earth’s surface, including spatial patterns of biological diversity. Grasslands are one of the largest biomes on Earth. Accurate mapping of grassland biodiversity relies on spectral discrimination of endmembers of species or plant functional types. We focused on spectral separation of grass lineages that dominate global grassy biomes: Andropogoneae (C4), Chloridoideae (C4), and Pooideae (C3). We examined leaf reflectance spectra (350–2,500 nm) from 43 grass species representing these grass lineages from four representative grassland sites in the Great Plains region of North America. We assessed the utility of leaf reflectance data for classification of grass species into three major lineages and by collection site. Classifications had very high accuracy (94%) that were robust to site differences in species and environment. We also show an information loss using multispectral sensors, that is, classification accuracy of grass lineages using spectral bands provided by current multispectral satellites is much lower (accuracy of 85.2% and 61.3% using Sentinel 2 and Landsat 8 bands, respectively). Our results suggest that hyperspectral data have an exciting potential for mapping grass functional types as informed by phylogeny. Leaf‐level hyperspectral separability of grass lineages is consistent with the potential increase in biodiversity and functional information content from the next generation of satellite‐based spectrometers.

Plant diversity in secondary, montane grasslands – a case study of the abandoned plantations of Mariepskop Mountain, South Africa

Grasslands are one of the most threatened terrestrial ecosystem types, and montane grasslands of particular conservation concern. Despite high rates of transformation in recent decades, croplands and plantations are being abandoned in parts of many countries, creating an opportunity for conservation of montane grasslands through restoration. We report on the changes in the cover of major vegetation types (indigenous forest, grassland, and plantations) between 1935 and 2022, in an area that was intensively afforested from 1930 to 1960 and abandoned in 2000. Montane grassland at the site declined from over 50% of all landcover to below 15%, but subsequently recovered to 30% within 20 years. Many former plantations developed into secondary grassland with estimated gamma plant species richness of 231 for herbaceous species and 45 for savanna species. These are high values considering the size of the study area (4000 ha), and comparable to estimates from primary grassland sites in the broader region. However, at the scale of 1 m2 sampling quadrats, richness in the secondary grasslands was below that recorded in the last remaining patches of primary grassland at the site (means of 2.6 versus 4.7 for graminoid species, and 1.9 versus 2.9 for forbs). Some of the former Eucalyptus plantations had transformed into novel savannas dominated by fire-tolerant, resprouting trees, and may require more active restoration. Secondary grasslands such as those reported on here could potentially make a significant contribution to the conservation of montane biodiversity over the coming decades, warranting further research (both socio-economic and ecological) on the factors that lead to abandonment and promote the emerge of secondary grasslands of high diversity.

Connecting competitor, stress-tolerator and ruderal (CSR) theory and Lund Potsdam Jena managed Land 5 (LPJmL 5) to assess the role of environmental conditions, management and functional diversity for grassland ecosystem functions

Abstract. Forage offtake, leaf biomass and soil organic carbon storage are important ecosystem services of permanent grasslands, which are determined by climatic conditions, management and functional diversity. However, functional diversity is not independent of climate and management, and it is important to understand the role of functional diversity and these dependencies for ecosystem services of permanent grasslands, since functional diversity may play a key role in mediating impacts of changing conditions. Large-scale ecosystem models are used to assess ecosystem functions within a consistent framework for multiple climate and management scenarios. However, large-scale models of permanent grasslands rarely consider functional diversity. We implemented a representation of functional diversity based on the competitor, stress-tolerator and ruderal (CSR) theory and the global spectrum of plant form and function into the Lund Potsdam Jena managed Land (LPJmL) dynamic global vegetation model (DGVM) forming LPJmL-CSR. Using a Bayesian calibration method, we parameterised new plant functional types (PFTs) and used these to assess forage offtake, leaf biomass, soil organic carbon storage and community composition of three permanent grassland sites. These are a temperate grassland and a hot and a cold steppe for which we simulated several management scenarios with different defoliation intensities and resource limitations. LPJmL-CSR captured the grassland dynamics well under observed conditions and showed improved results for forage offtake, leaf biomass and/or soil organic carbon (SOC) compared to the original LPJmL 5 version at the three grassland sites. Furthermore, LPJmL-CSR was able to reproduce the trade-offs associated with the global spectrum of plant form and function, and similar strategies emerged independent of the site-specific conditions (e.g. the C and R PFTs were more resource exploitative than the S PFT). Under different resource limitations, we observed a shift in the community composition. At the hot steppe, for example, irrigation led to a more balanced community composition with similar C, S and R PFT shares of aboveground biomass. Our results show that LPJmL-CSR allows for explicit analysis of the adaptation of grassland vegetation to changing conditions while explicitly considering functional diversity. The implemented mechanisms and trade-offs are universally applicable, paving the way for large-scale application. Applying LPJmL-CSR for different climate change and functional diversity scenarios may generate a range of future grassland productivities.

Priority effects and competitive exclusion by C4 grasses on longleaf pine savanna restoration sites

On grassland and savanna restoration sites, planted native C4 grasses can competitively exclude other co‐introduced plant functional groups, with negative implications for ecosystem functioning and restoration success. Previous studies have suggested that C4 grass competitive exclusion does not occur in longleaf pine savannas of the North American Coastal Plain; however these studies were primarily conducted on old growth xeric sites. We designed an experiment to test competitive interactions between C4 grasses and forbs introduced by seed to mesic savanna restoration sites. Research installations were established on three former bahiagrass (Paspalum notatum) pastures in Florida, within which six different seed treatments were applied: (1) C4 grasses and forbs together in years 1 and 2, (2) C4 grasses alone in year 1 and forbs alone in year 2, (3) forbs alone in year 1 and C4 grasses alone in year 2, (4) C4 grasses alone in both years, (5) forbs alone in both years, and (6) an unplanted control. All plots were sampled 1 year after the second seeding event. We found that C4 grasses competitively excluded forbs, reducing cover of forbs arriving on the site at the same time, as well as those arriving in the second year. The highest forb species richness and cover was found in the three treatments that did not contain C4 grasses in year 1, and different C4 grass species exhibited different community associations. These findings suggest that restoration seed mixes for longleaf pine savannas should account for the competitive interactions of C4 grasses.