Temperate Grassland Research Articles

Temperate grassland conversion to conifer forest destabilises mineral soil carbon stocks.

Tree-planting is increasingly presented as a cost-effective strategy to maximise ecosystem carbon (C) storage and thus mitigate climate change. Its success largely depends on the associated response of soil C stocks, where most terrestrial C is stored. Yet, we lack a precise understanding of how soil C stocks develop following tree planting, and particularly how it affects the form in which soil C is stored and its associated stability and resistance to climate change. Here, we present changes in C and nitrogen (N) stored as mineral-associated organic matter (OM), occluded particulate OM, free particulate OM and dissolved OM, from four regional chronosequences of Scots pine (Pinus sylvestris L.) forests planted on former grasslands across Scotland. We found that c. 58-68 years after the plantation, bulk soil C and N stocks in the organic layer and the top 20cm of mineral soil decreased by half relative to unforested grasslands - a decrease roughly equivalent to a third of the simultaneous C gain in the tree biomass. This pattern was driven predominantly by a decrease in the amount of C and N stored as mineral-associated OM, an OM fraction considered as relatively long-lived. Our findings demonstrate the need to estimate C storage in response to tree planting based both on soil C stocks and tree biomass, as the use of the latter alone may significantly over-estimate net C benefits of tree planting on permanent grasslands.

Global increase in the occurrence and impact of multiyear droughts.

Persistent multiyear drought (MYD) events pose a growing threat to nature and humans in a changing climate. We identified and inventoried global MYDs by detecting spatiotemporally contiguous climatic anomalies, showing that MYDs have become drier, hotter, and led to increasingly diminished vegetation greenness. The global terrestrial land affected by MYDs has increased at a rate of 49,279 ± 14,771 square kilometers per year from 1980 to 2018. Temperate grasslands have exhibited the greatest declines in vegetation greenness during MYDs, whereas boreal and tropical forests have had comparably minor responses. With MYDs becoming more common, this global quantitative inventory of the occurrence, severity, trend, and impact of MYDs provides an important benchmark for facilitating more effective and collaborative preparedness toward mitigation of and adaptation to such extreme events.

Drought in a warmer, CO2-rich climate restricts grassland water use and soil water mixing.

Soil water sustains terrestrial life, yet its fate is uncertain under a changing climate. We conducted a deuterium labeling experiment to determine whether elevated atmospheric carbon dioxide (CO2), warming, and drought impact soil water storage and transport in a temperate grassland. Elevated CO2 created a wetter rootzone compared with ambient conditions, whereas warming decreased soil moisture. Soil water remained well mixed in all global change treatments except for summer drought combined with warming and elevated CO2. These combined treatments caused the grassland to conserve water and restricted soil water flow to large, rapidly draining pores without mixing with small, slowly draining pores. Our results suggest that drought in a warmer, more CO2-rich climate can severely alter grassland ecohydrology by constraining postdrought soil water flow and grassland water use.

Behind the lenses: Biases in the contribution of wildlife photography to biodiversity representation

Abstract Nature‐related visual media has a significant impact on today's society by engaging the public in conservation problems and promoting pro‐environmental behaviours. Although major attention has been paid to how some types of visual media (e.g. documentaries) offer unrealistic portrayals of the natural world, biases on representation by wildlife photography remain unexplored. In the present study, we assessed biases in wildlife photography at spatial, temporal, taxonomic, conservation status and selection criteria scales, and modelled the factors influencing the probability of portrayed organisms winning a wildlife photography contest by using data on 1333 pictures featured in the Wildlife Photographer of the Year, one of the most popular wildlife photography competitions worldwide. The representation of biomes mostly coincides with their extension on the planet. However, we detected an overrepresentation of temperate (broadleaf and conifer), Mediterranean and tropical forests. We detected a positive change over time in representing historically neglected taxa, such as insects. We also detected an increase in representation of Mangroves, Marine Ecosystems, Tundra and temperate forests and grasslands. Mammals and birds were overrepresented in photographs while insects and plants were underrepresented, and so were species listed as ‘Least Concern’ and ‘Data Deficiency’. The top 10 ranking species included charismatic carnivore species. Our results showed that the jury's choice offered a more diverse representation of biodiversity than the people's choice, and the winning photographs showcased fewer taxonomic groups than the non‐winning pictures. Realm, domain and colourfulness influenced the probability of an organism's picture being winner, but the variability explained by our model reflects that there are a large number of unexplored determinants (e.g. socio‐economical, technical or emotional). Our research detected a trend towards a more balanced representation of the natural world in wildlife photography, although biases are yet large, which may influence people's perception of the current status of species and habitats they encompass. Our results highlight a need to evenly represent species and ecosystems to increase public awareness, which requires providing data on species identity and conservation status to increase public knowledge. Finally, we underscore the need to report compliance with ethical guidelines when photographing wildlife. Read the free Plain Language Summary for this article on the Journal blog.

Dual mycorrhizal associations in tea tree (Melaleuca alternifolia) differ between Australian temperate shrublands and subtropical forests

Dual mycorrhizal associations in tea tree (Melaleuca alternifolia) differ between Australian temperate shrublands and subtropical forests

Climate, plant and microorganisms jointly influence soil organic matter fractions in temperate grasslands.

Soil organic carbon (SOC) plays a critical role in mitigating climate change. Conceptualizing SOC into particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) helps us more accurately predict the responses of organic carbon, with varying chemical composition, molecular size, and degree of association with soil minerals, to environmental changes. To assess the controlling factors of particulate organic carbon (POC) and mineral-associated organic carbon (MAOC), plant and soil samples were collected from 54 temperate grassland sites in Northern China, and the impacts of climate, plants, soil properties and microorganisms on POC and MAOC contents were analyzed. The results indicated that POC slightly dominated temperate grassland topsoils. Climate, plants, and microorganisms could predict a significant portion of the variation in POC and MAOC contents. Microbial factors, represented by fungal and bacterial biomass and necromass carbon, explained 56.6% and 46.7% of the variation in POC and MAOC contents, respectively. These findings indicate that the potential of POC in soil carbon storage cannot be ignored, and microorganisms should be considered when studying the dynamics and accumulation of POC and MAOC.

Vegetation height estimation based on machine learning model driven by multi-source data in Eurasian temperate grassland

Vegetation height estimation based on machine learning model driven by multi-source data in Eurasian temperate grassland

Unveiling grassland dynamics: trends and drivers of degradation and improvement in the Eurasian Steppe since 2000

ABSTRACT As the most extensive temperate grassland in the world, the Eurasian Steppe provides various ecological services that support the environment and human well-being. However, grassland degradation has become a serious environmental issue. Most of the traditional degradation assessments ignore the sensitivity of grassland ecosystems to climatic conditions. In response, our study introduces a new comprehensive identification framework that integrates vegetation growth and climate change, using a novel long-term monitoring methodology to detect grassland degradation and improvement. The framework quantifies the area and degree of degradation and improvement in the Eurasian Steppe using long time-series data from 2000 − 2020. Then, the driving factors of grassland change were analyzed using a quantitative model. Our findings reveal a clear trend of improvement in the Eurasian Steppe was identified, with the improved area being 4.72 times larger than the degraded area (221.4 × 104 and 46.92 × 104 km2, respectively). The Tibetan Plateau and Loess Plateau led to the improvement. Simultaneously, the area surrounding the northern Caspian Sea has been severely degraded. The three areas correspond to frigid humid and semi-humid grassland, temperate humid and semi-humid grassland, and temperate arid and semi-arid grassland, respectively. Globally, the combined effects of climate change and human activities dominated the observed grassland degradation and improvement, accounting for 77.13% and 89.64%, respectively. Our method provides a robust tool for detecting grassland degradation and improvement across large scales, offering scientific support for achieving the United Nations’ Sustainable Development Goals (SDGs), particularly land degradation neutrality (LDN).

Fire and seed dormancy: A global meta-analysis.

Fire-released seed dormancy (SD) is a key trait for successful germination and plant persistence in many fire-prone ecosystems. Many local studies have shown that fire-released SD depends on heat and exposure time, dose of smoke-derived compounds, SD class, plant lineage and the fire regime. However, a global quantitative analysis of fire-released SD is lacking. We hypothesized that fire-released SD is more prevalent in fire-prone than in non-fire-prone ecosystems, and in crown-fire compared to surface-fire ecosystems. Additionally, uncovering patterns in the relationship between fire cues and SD classes at the global scale that mirror those identified in local or regional studies was expected. Totally, 246 published germination studies during 1970-2022, encompassing 1782 species from 128 families was used in our meta-analysis. Meta-analysis moderators included different fire cues, smoke application methods, smoke exposure duration and concentration, smoke compounds, fire-proneness, fire regimes, and ecosystem types. Heat released physical, and smoke released physiological and morphophysiological dormancies. For SD release, heat and smoke acted synergistically, and KAR1 was the most effective smoke compound. Fire-released SD was more prevalent in fire-prone than non-fire-prone regions; and particularly under crown fire regimes. Fire-released SD occurred mainly in Mediterranean ecosystems, temperate dry forests, and temperate warm ecosystems, whereas species from savannas and tropical grasslands, temperate grasslands, and tropical rainforests generally responded negatively to fire. Fire-released SD is strongly influenced by fire regimes the latter with significant role in shaping SD and germination patterns on a global scale. The synergistic effect of heat and smoke in dormancy release reveals more intricate interactions between fire cues than previously understood. Understanding these patterns is crucial in the context of shifting fire regimes driven by climate change, as they may disrupt plant life cycles, alter ecosystem functions, biodiversity, and community composition and provide key insights for biodiversity conservation and ecological restoration in fire-prone ecosystems.

Plant Species Diversity Assessment in the Temperate Grassland Region of China Using UAV Hyperspectral Remote Sensing

Biodiversity conservation is a critical environmental challenge, with accurate assessment being essential for conservation efforts. This study addresses the limitations of current plant diversity assessment methods, particularly in recognizing mixed and stunted grass species, by developing an enhanced species recognition approach using unmanned aerial vehicle (UAV) hyperspectral data and deep learning models in the steppe region of Xilinhot, Inner Mongolia. We compared five models—support vector machine (SVM), two-dimensional convolutional neural network (2D-CNN), three-dimensional convolutional neural network (3D-CNN), hybrid spectral CNN (HybridSN), and the improved HybridSN+—for grass species identification. The results show that SVM and 2D-CNN models have relatively poor recognition effects on mixed distribution and stunted individuals, while HybridSN and HybridSN+ models can effectively identify important grass species in the region, and the recognition accuracy of the HybridSN+ model can reach 96.45 (p < 0.05). Notably, the 3D-CNN model’s recognition performance was inferior to the HybridSN model, especially for densely populated and smaller grass species. The HybridSN+ model, optimized from the HybridSN model, demonstrated improved recognition performance for smaller grass species individuals under equivalent conditions, leading to a discernible enhancement in overall accuracy (OA). Diversity indices (Shannon–Wiener diversity, Simpson diversity, and Pielou evenness) were calculated using the identification results from the HybridSN+ model, and spatial distribution maps were generated for each index. A comparative analysis with diversity indices derived from ground survey data revealed a strong correlation and consistency, with minimal differences between the two methods. This study provides a feasible technical approach for efficient and meticulous biodiversity assessment, offering crucial scientific references for regional biodiversity conservation, management, and restoration.

Spatiotemporal dynamics of grassland aboveground biomass in northern China and the alpine region: Impacts of climate change and human activities.

Grassland plays a crucial role in the global cycles of matter, energy, water and, climate regulation. Biomass serves as one of the fundamental indicators for evaluating the ecological status of grassland. This study utilized the Carnegie-Ames-Stanford Approach (CASA) model to estimate Net Primary Productivity (NPP) from meteorological data and the Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI) remote sensing data for northern China's temperate and alpine grasslands from 1981 to 2015. NPP was subsequently converted into aboveground biomass (AGB). The dynamic changes in grassland AGB were analyzed, and the influence of climate change was examined. The results indicate strong agreement between AGB estimations from the CASA model and Gill method based on field-measured AGB, confirming the model's reliability for these regions. The dynamic changes in AGB exhibited a significant increasing trend of 1.31 g/m2. Grazing intensity (GI), soil moisture, and mean annual precipitation are identified as key factors influencing changes in grassland AGB. Our findings indicate that precipitation and soil moisture are the primary drivers of AGB accumulation during the growing season (spring, summer, and autumn), while temperature plays a critical role in supporting biomass accumulation during winter. Higher temperatures in winter contributes to increased AGB in the following spring, particularly in desert steppe and alpine meadow ecosystems. These insights highlight the complex interaction between climate factors and human activities in shaping grassland productivity across different seasons.

Complete genome sequence of strain AEG42_29 (DSM 112329), a member of the genus Paraconexibacter isolated from soil.

We report the complete genome sequence of strain AEG42_29, a representative of the genus Paraconexibacter isolated from a temperate grassland soil. Its genome codes for several genes involved in stress response, defense, and virulence, which may help this bacterium cope with fluctuating conditions in the soil environment.

Evaluation of Machine Learning Models for Estimating Grassland Pasture Yield Using Landsat-8 Imagery

Accurate estimation of pasture yield in grasslands is crucial for the sustainable utilization of pasture resources and the optimization of grassland management. This study leveraged the capabilities of machine learning techniques, supported by Google Earth Engine (GEE), to assess pasture yield in the temperate grasslands of northern China. Utilizing Landsat-8 data, band reflectances, vegetation indexes (VIs), and soil water index (SWI) were extracted from 1000 field samples across Xilingol. These data, combined with field-measured pasture yields, were employed to construct models using four machine learning algorithms: elastic net regression (Enet), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM). Among the models, XGBoost demonstrated the best performance for pasture yield estimation, with a coefficient of determination (R2) of 0.94 and a precision of 76.3%. Additionally, models that incorporated multiple VIs demonstrated superior prediction accuracy compared to those using individual VI, and including soil moisture data further enhanced predictive precision. The XGBoost model was subsequently applied to map the spatial patterns of pasture yield in the Xilingol grassland for the years 2014 and 2019. The estimated average annual pasture yield in the Xilingol grassland was 1042.38 and 1013.49 kg/ha in 2014 and 2019, respectively, showing a general decreasing trend from the northeast to the southwest. This study explored the effectiveness of common machine learning algorithms in predicting pasture yield of temperate grasslands utilizing Landsat-8 data and ground sample data and provided the valuable support for long-term historical monitoring of pasture resources. The findings also highlighted the importance of predictor selection in optimizing model performance, except for the reflectance and vegetation indices characterizing vegetation canopy information, the inclusion of soil moisture information could appropriately improve the accuracy of model predictions, especially for grasslands with relatively low vegetation cover.

Assemblies of leaf and root mycobiomes in a temperate grassland: Dispersal limitation overpowers selection

Abstract The emergence of β‐diversity of plant‐associated fungi across diverse coexisting host plant species in natural habitats is intricately linked to specific community assembly processes. Despite this, the relative contributions of various assembly processes to the observed β‐diversity patterns, as well as the influence of plant traits on these contributions, are still poorly understood. Here, we investigated the leaf/root‐associated fungal communities across nine coexisting dominant herbaceous perennials in a temperate grassland that had undergone a 17‐year mowing treatment. We elucidated the β‐diversity components and community assembly processes of these fungal communities. Furthermore, we explored relationships between leaf/root functional trait variations and fungal community assemblies. We tested the following hypotheses: (1) both species turnover and nestedness are important components of the fungal β‐diversity, with selection predominating in the fungal community assemblies; (2) mowing enhances the contributions of nestedness/selection; (3) plant trait variations significantly affect the fungal community assembly processes. Unexpectedly, our findings demonstrated a predominance of leaf/root fungal species turnover among coexisting plant hosts, contrasting with nestedness. Moreover, dispersal limitation emerged as the primary factor shaping fungal community assemblies, rather than selection processes. Although mowing significantly inhibited plant growth, its effects on the overall patterns of fungal assemblages were limited. We further observed that higher degrees of plant trait variations were primarily linked to stronger dispersal limitation, with a relatively weaker influence on heterogeneous selection. Additionally, the impact of plant traits on the selection process of root‐associated fungi was more pronounced compared to that of leaf‐associated fungi. Synthesis. Our study reveals that the β‐diversity of fungi associated with coexisting plants in natural grasslands is primarily attributed to fungal species replacement rather than gain‐and‐loss dynamics among these plants. Concurrently, this observed pattern is largely governed by dispersal limitation as opposed to selection. We propose that the primary mechanism through which plant hosts and their traits influence the structures of associated fungal communities is by limiting fungal dispersal, while niche differentiation among fungal taxa plays a secondary role. These findings offer a mechanistic insight into the assemblies of plant mycobiomes and further elucidate the plant‐mycobiome relationships within complex plant communities.

Nitrogen availability in soil controls uptake of different nitrogen forms by plants.

Nitrogen (N) uptake by plant roots from soil is the largest flux within the terrestrial N cycle. Despite its significance, a comprehensive analysis of plant uptake for inorganic and organic N forms across grasslands is lacking. Here we measured in situ plant uptake of 13 inorganic and organic N forms by dominant species along a 3000 km transect spanning temperate and alpine grasslands. To generalize our experimental findings, we synthesized data on N uptake from 60 studies encompassing 148 plant species world-wide. Our analysis revealed that alpine grasslands had faster NH4 + uptake than temperate grasslands. Most plants preferred NO3 - (65%) over NH4 + (24%), followed by amino acids (11%). The uptake preferences and uptake rates were modulated by soil N availability that was defined by climate, soil properties, and intrinsic characteristics of the N form. These findings pave the way toward more fully understanding of N cycling in terrestrial ecosystems, provide novel insights into the N form-specific mechanisms of plant N uptake, and highlight ecological consequences of chemical niche differentiation to reduce competition between coexisting plant species.

Distribution and mapping of temperate savanna in the sandy lands of eastern China

Distribution and mapping of temperate savanna in the sandy lands of eastern China

Changes in reproduction mediate the effects of climate change and grassland management on plant population dynamics.

Climate change is one of the largest threats to grassland plant species, which can be modified by land management. Although climate change and land management are expected to separately and interactively influence plant demography, this has been rarely considered in climate change experiments. We used a large-scale experiment in central Germany to quantify the effects of grassland management, climate change, and their joint effect on the demography and population growth rate of 11 plant species all native to this temperate grassland ecosystem. We parameterized integral projection models with five years of demographic data to project population growth rate. We hypothesized that plant populations perform better in the ambient than in the future climate treatment that creates hotter and drier summer conditions. Further, we hypothesized that plant performance interactively responds to climate and land management in a species-specific manner based on the drought, mowing, and grazing tolerances as well as the flowering phenology of each species. Due to extreme drought events, over half of our study species went quasi extinct, which highlights how extreme climate events can influence long-term experimental results. We found no consistent support for our expectation that plants perform better in ambient compared with future climate conditions. However, several species showed interactive responses to the treatments, indicating that optimal management strategies for plant performance are expected to shift with climate change. Changes in population growth rates of these species across treatments were mostly due to changes in plant reproduction. Experiments combined with measuring plant demographic responses provide a way to isolate the effects of different drivers on the long-term persistence of species and to identify the demographic vital rates that are critical to manage in the future. Our study suggests that it will become increasingly difficult to maintain species with preferences for moister soil conditions, and that climate and land use can interactively alter demographic responses of the remaining grassland species.

Effects of drought on optimum temperature of carbon fluxes in temperate grasslands

Abstract Ecosystem carbon flux components, including ecosystem gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem productivity (NEP), are the most direct indicators of ecosystem production capacity, carbon sequestration, and climate regulation strength. Nevertheless, little is known about how water availability affects the temperature responses of carbon flux components in water-limited ecosystems. Based on a long-term eddy observation dataset of temperate grasslands in northern China, we analyzed the effects of drought on the optimum temperature of carbon flux components ( T opt flux ) in temperate grassland ecosystems and clarified the relative contributions of vegetation and climate factors to T opt flux . We found that the optimum temperatures of carbon flux components were widespread across different grassland types, with a significant lower optimum temperature of NEP ( T opt NEP , 17.32 ± 3.21 °C) than that of GPP ( T opt GPP , 18.67 ± 2.53 °C) and ER ( T opt ER , 19.30 ± 1.94 °C). Drought significantly reduced T opt NEP , but had no significant effects on T opt GPP and T opt ER . Obvious shifts of occurrence date of T opt flux were also observed in the years with different precipitation regimes. That is, T opt GPP and T opt NEP occurred significantly earlier than seasonal maximum temperature ( T max ) in the dry years, while T opt flux significantly lagged behind the occurrence of T max in the wet years. Water availability and vegetation factors co-regulated the spatiotemporal variations of T opt flux . In the dry years, precipitation and soil water content predominated the changes in T opt GPP and T opt ER , whereas vegetation structure (leaf area index) and physiological characteristics played a more important role in the wet years. Our study not only provided the first evidence for the widespread existence of T opt flux of different carbon fluxes, but also addressed the remarkable impacts of drought on T opt flux and their occurrence date in the water-limited grasslands. Therefore, incorporating the unimodality of these observed temperature responses of ecosystem carbon fluxes into land carbon models is necessary for improving the accuracy of carbon sequestration predictions.

Mowing in place of conventional grazing increased soil organic carbon stability and altered depth-dependent protection mechanisms

Conventional grazing with high grazing pressure can decrease soil organic carbon (SOC) stability by disrupting its protective mechanisms, eliciting soil depth-dependent responses. Grazing exclusion for hay-making by mowing is usually adopted to restore grassland. However, there is still a lack of systematic evaluation of SOC stability and its impact factors in different soil layers when mowing replaces conventional grazing. Here, based on an investigation of 15 paired sites from mowing vs. conventional grazing in a temperate grassland of northeast China, we found that mowing increased mean weight diameter of soil aggregates (MWD, 5.14 %), Fe/Al associated organic carbon (Fe/Al-OC, 12.20 %), and SOC stability (11.46 %) at topmost soil layer (0–10 cm) but only increased MWD (8.50 %) at subsurface soil (10–30 cm). Mowing increased root biomass of plant variables, soil bulk density and pH of soil properties, and microbial biomass carbon (MBC) of microbial properties at the topmost layer, collectively contributing to SOC protection. However, the reduction in soil nitrate nitrogen and increasing MBC induced by mowing drove the subsurface SOC protection. The protection mechanism for SOC stability shifted from a single physical protection dominance in mowing areas to joint physical and mineral protection in conventional grazing grasslands at the topmost depth. In contrast, subsurface SOC stability was consistently governed by mineral protection regardless of grazing. Our results imply that although grassland ecosystems can initiate more protection mechanisms to cope with disturbances, mowing induced the increase of physical and mineral protection resulting from the substantial promotion in plant C input quantity and microbial biomass, combined with alteration in soil properties, finally stabilized topmost SOC. The limited impact of management practices on the subsurface SOC stability indicates that the interaction of subsurface soil and microbial properties with SOC protection should be fully considered to forecast soil C dynamics and its resistance to disturbance accurately.

Grassland irrigation and grazing prohibition have significantly affected vegetation and microbial diversity by changing soil temperature and moisture, evidences from a 6 years experiment of typical temperate grassland

Grasslands are characterized by high primary productivity and offer a diverse array of ecosystem services that contribute to human well-being. The dynamic balance between vegetation-soil in grassland ecosystems is being affected by anthropogenic activities and climate change, in which soil microbial communities play a critical regulating role. However, how microbial biodiversity interacts with vegetation-soil and responds to environmental change remains unclear. We conducted a six-year field experiment in the grasslands of Inner Mongolia to study the effects of grazing and altered precipitation on major vegetation types (or species), soil properties, and microbial community composition. The results showed that increased precipitation influenced positive associations within microbial communities, which helped to increase vegetation diversity. The biomass of Stipa.sareptana increased by 0.054 % under reduced precipitation, while it significantly increased by 2.07 % under the combination of grazing ban and reduced precipitation. Grazing prohibition had a significant negative effect on bacterial diversity and Shannon's index, but a significant positive effect on fungal diversity and abundance. Increasing precipitation had no significant effect on bacterial diversity under grazing conditions, while decreasing precipitation significantly reduced the Shannon index of bacteria. Fungal communities were very sensitive to changes in precipitation, and both increasing and decreasing precipitation significantly affected the structure of fungal communities. In summary, our results highlight how grassland irrigation and moderate grazing can be employed as a management strategy to promote plant diversity and thereby improve ecosystem functioning and resilience.