Enhancing Grassland Resilience and Productivity Under Climate Change

1. Introduction

Grasslands are among the most extensive and productive terrestrial ecosystems. They play a vital role in global food security, carbon cycling, and biodiversity conservation. However, they are increasingly threatened by climate change, land degradation, and unsustainable land-use practices [1,2]. Understanding how grassland systems respond to environmental stressors and management interventions is essential for informing sustainable and resilient land stewardship. Global syntheses show that grasslands account for a large share of terrestrial carbon stocks, with soils representing the dominant pool, and that their stability under climate change is critical for both food systems and climate mitigation [3,4]. Biodiversity has been shown to enhance the resistance and resilience of grassland productivity to climate extremes, further linking ecological integrity with ecosystem service provision [5]. At the same time, intensively managed grasslands can generate net warming effects that partially offset the cooling of natural and lightly grazed systems, highlighting the importance of adaptive and evidence-based management [6].

Following the success of the first volume of this Special Issue, which featured key advancements in grassland ecosystem science, we are pleased to introduce the second volume, “Advances in Grassland Productivity and Sustainability—2nd Edition”, published in Agronomy. This edition brings together fourteen original research articles spanning diverse geographic regions and methodological approaches from field-based experimentation to remote sensing and process-based modeling. Together, they offer critical insights into how grassland systems can be managed for resilience, productivity, and ecosystem service provision under accelerating climate change.

2. Overview of the SI

This new collection comprises fourteen articles that reflect ongoing and emerging research focused on enhancing grassland resilience, carbon sequestration, and sustainable management under changing environmental conditions.

The contributions in this edition showcase a breadth of studies employing diverse methodologies, from field experiments to remote sensing and modeling, to assess the productivity, ecological functions, and restoration of grasslands across varied climatic zones.

One compelling study by Qu et al. (Contribution 1) examines the net ecosystem productivity (NEP) of the Zoigê alpine grassland in China, assessing its spatiotemporal dynamics and sensitivity to climate variability, phenological shifts, and soil conditions over two decades (2000–2020). They report a statistically significant annual increase in NEP, averaging 3.18 g C m⁻² yr⁻¹. This trend shows pronounced spatial heterogeneity, with higher values in the southwestern and northeastern margins (>80 g C m⁻²) and lower, sometimes negative, values in the central region. In both alpine meadows and alpine steppes, soil moisture emerged as the dominant regulator of NEP, reflecting the combined influence of water and temperature. By integrating regional soil characteristics into their assessment, the authors provide a refined understanding of vegetation carbon sink dynamics in high-altitude grasslands, highlighting the pivotal role of soil–moisture interactions in governing carbon cycling under changing climatic conditions. Additionally, Liu et al. (Contribution 2) investigate biodiversity and biomass dynamics in the arid and semi-arid grasslands of Zhangye, China, elucidating how climate–soil interactions shape ecosystem functioning in water-limited environments. Using data from 63 field sites, the study shows that soil moisture and relative humidity are strongly and positively linked to both species diversity and biomass, while higher temperatures add further stress to these ecosystems. Soil bulk density and pH emerged as key mediating factors, indirectly influencing biomass through their control of soil moisture availability. These findings highlight the complex linkages between climatic conditions and soil properties. They offer valuable guidance for adaptive management strategies aimed at sustaining productivity and biodiversity in arid grasslands under climate change pressures. In another valuable contribution, Hu et al. (Contribution 3) investigate the combined effects of no-till seeding and fertilization on restoring degraded alpine grazing grasslands in Bayinbuluke. Using 16 treatment combinations that varied in sowing and fertilization rates, the study found substantial ecological benefits. No-till replanting with selected Poaceae species increased aboveground biomass by 81%, species richness by 55.8%, and the Shannon–Wiener diversity index by 64.2%. fertilization further enhanced productivity, with dry hay yields rising by 60.9–81%, and improved soil quality, raising total nitrogen by 50.6%, total phosphorus by 43.4%, available phosphorus by 66%, and organic matter by 31.2%. It also enhanced soil structural stability, increasing the proportion of large aggregates by 18.2%. The authors highlight soil moisture and nutrient availability as key drivers of vegetation recovery and diversity, underscoring the potential of integrated agronomic practices to rehabilitate degraded alpine grasslands and restore ecosystem functionality. Wang et al. (Contribution 4) present an innovative application of the cloud model to characterize drought dynamics and their linkages with large-scale atmospheric circulation in Inner Mongolia’s Yinshanbeilu region. Using nearly five decades of temperature and precipitation data (1971–2020), the study calculated standardized precipitation evapotranspiration indices (SPEI-3 and SPEI-12) and applied cross-wavelet analysis to reveal pronounced resonance cycles between drought variability and key teleconnection patterns, particularly the Pacific Decadal Oscillation (PDO) and El Niño–Southern Oscillation (ENSO). The findings indicate an overall intensification of drought conditions, with increasing drought occurrence and severity. They also underscore the predictive potential of the cloud model as a systematic tool for early warning, prevention, and mitigation of drought impacts in vulnerable rangeland systems. Wang et al. (Contribution 5) present a comprehensive study on meadow grasslands in northern China, examining how different management treatments such as mowing, burning, and grazing affect soil organic carbon stocks (SOCSs), total nitrogen stocks (TNSs), and total phosphorus stocks (TPSs) over the period 2020-2023. Compared to untreated control plots, both mowing and burning once a year significantly increased SOCSs (by 12.75% and 23.72%, respectively), TNSs (15.6% and 26.8%), and TPSs (12.4% and 27.2%). In contrast, grazing treatments led to notable declines in these soil nutrient reserves (13.0%, 11.8%, and 10.1%, respectively). The study also demonstrated that mowing and burning strengthened the correlations among SOCS, TNS, and TPS, whereas grazing weakened them. Soil temperature emerged as the primary controlling factor across all nutrients, while vegetation variables predominantly influenced SOCSs, and soil variables played a larger role in regulating TNSs and TPSs. The authors emphasize that the specific vegetation variables impacting SOCS differ from those influencing TNS and TPS, highlighting the complexity of ecological interactions under different treatments. This work provides valuable insight into the mechanisms driving soil nutrient dynamics and offers a scientific basis for optimizing grassland management strategies.

Nuñez et al. (Contribution 6) highlight the overlooked ecological and agricultural importance of improved permanent grasslands established on arable land in Sweden’s boreal landscapes. Drawing on large-scale environmental monitoring data, the study shows that improved permanent grasslands, alongside semi-natural grasslands, deliver complementary ecosystem services such as plant species richness, pollinator resources, and forage provision. While semi-natural grasslands with high agri-environmental scheme (AES) value support the greatest biodiversity and host numerous red-listed species, improved grasslands remain a substantial yet underrecognized contributor to agricultural productivity and ecological function, underscoring their role in sustaining multifunctional agricultural systems. Meanwhile, Cicuéndez et al. (Contribution 7) developed ecosystem light use efficiency (eLUE) models to estimate gross primary production (GPP) in Mediterranean grasslands, leveraging high-resolution Sentinel-2 NDVI data alongside meteorological variables such as minimum temperature and soil water content. Using eddy-covariance flux tower measurements for validation, the study demonstrated that Sentinel-2-based models substantially outperformed MODIS GPP products, particularly in capturing seasonal extremes during winter and summer. The findings highlight the value of integrating high-resolution remote sensing with local meteorological data for precise monitoring of carbon fluxes, offering a robust framework to support the sustainable management of grassland ecosystems under climate change. Xu et al. (Contribution 8) examined spatial patterns of plant carbon density in nine subalpine–alpine grasslands on the eastern Loess Plateau, China. They used plot-based surveys and Kriging interpolation to analyze variations across gradients of altitude, latitude, and longitude. The study found that belowground biomass accounted for approximately 75% of total carbon stocks (2676.8 g C m⁻²), with grasses contributing the largest share. Carbon density exhibited clear horizontal and vertical patterns, decreasing with altitude and varying by geographical location within northern, central, and southern subregions. Functional group composition significantly influenced these patterns, with grasses, forbs, and sedges showing distinct carbon allocation trends along geographical gradients. The findings highlight the combined role of environmental gradients and vegetation composition in shaping carbon storage dynamics in high-altitude grassland ecosystems. Milazzo et al. (Contribution 9) applied a Random Forest machine learning model to forecast the Normalized Difference Vegetation Index (NDVI) in Mediterranean permanent grasslands, using soil moisture data from two sources: in situ sensor–derived values and remotely sensed Soil Water Index (SWI) data. Forecasts were generated for 7- and 30-day intervals (2015–2022), with performance evaluated using anomaly detection via z-scores. The 7-day forecasts were consistently more accurate, particularly in capturing drought-induced declines in vegetation activity. Both soil moisture datasets proved to be reliable predictors, underscoring the potential of simple, data-driven approaches combined with remote sensing tools for operational early warning systems in drought-prone grassland environments.

Braga et al. (Contribution 10) conducted a three-year field trial in Brazil comparing two Gamba grass (Andropogon gayanus) cultivars, Planaltina and the recently developed BRS Sarandi, under continuous grazing at three stocking rates. Across multiple years, Sarandi pastures generally supported higher average daily weight gains (ADG) in Nellore bulls, with significant advantages observed in 2018 and 2020. This performance was closely linked to Sarandi’s superior canopy structure, characterized by a higher leaf–stem ratio (positively correlated with ADG, r = 0.70) and reduced stem proportion. These traits suggest that Sarandi offers a more productive and sustainable option for pasture-based livestock systems in tropical environments compared to the long-established Planaltina. Serrano et al. (Contribution 11) investigated the integration of two complementary proximal sensing technologies, the Rising Plate Meter (RPM) and an Active Optical Sensor (AOS), to estimate pasture crude protein (CP, kg ha⁻¹) by simultaneously capturing biomass and quality dimensions. The RPM provided dry matter (DM) estimates via compressed height (HRPM), while the AOS assessed pasture quality through the normalized difference vegetation index (NDVI). Across three seasonal growth stages (autumn, winter, and spring), the combined metric HRPM × NDVI showed strong predictive performance for CP during the early and intermediate phases of the cycle (autumn: R² = 0.86, LCC = 0.80; winter: R² = 0.74, LCC = 0.81). However, model accuracy declined sharply in spring (R² = 0.28, LCC = 0.42), coinciding with reduced pasture moisture and CP. This study demonstrates the potential of sensor-based approaches for supporting grazing management decisions, including stocking rates, supplementation, and rotational grazing. It also highlights the need to expand sensor datasets across diverse pasture types to improve predictive reliability and practical applicability in biodiverse dryland systems. Quatrini et al. (Contribution 12) evaluated the effectiveness of Switzerland’s policy mix for promoting the sustainable management of permanent grasslands (PGs) using a novel combination of the Cascade Framework and stakeholder sentiment analysis. The study identified 16 policy instruments, including 3 regulatory, 11 incentive-based, and 2 informational, that primarily target landscape structure and composition to enhance ecosystem service delivery. Notably, gaps were observed in demand-side policies, which may contribute to underperformance in achieving several environmental quality objectives. Despite these shortcomings, stakeholders generally perceived Swiss grassland policies as effective and democratically legitimate, underscoring the importance of inclusive governance. The authors highlight that their mixed-method approach and conceptual framework can be adapted to other regional and socio-economic contexts to inform the design of mechanism-targeted, balanced policies that support sustainable PG management and ecological restoration.

Finally, the two complementary studies by Abdalla et al. [(Contributions 13, 14)] present a global, model-based assessment of the sustainability and efficiency of Miscanthus (Miscanthus × giganteus) and willow (Salix spp.) as bioenergy crops under current and projected climate conditions. Using the MiscanFor and SalixFor models, the research evaluates multiple performance indicators, including biomass productivity, carbon intensity (CI), land-use energy intensity (LUEI), energy use efficiency (EUE), and soil organic carbon (SOC) sequestration. Under present conditions, Miscanthus generally outperforms willow in productivity (19.9 vs. 10.4 t ha⁻¹ on average), LUEI (321 vs. 164 GJ ha⁻¹), and EUE (14.45 vs. 10.22), with tropical and subtropical regions such as South America, Sub-Saharan Africa, and Southeast Asia emerging as global hotspots. However, both crops are highly sensitive to environmental conditions, with productivity declining in less favorable climates. Future climate projections (B1 and A1FI) suggest substantial geographical shifts in cultivation potential—warming trends improve viability in northern and temperate zones, while productivity in southern and arid regions declines. Under the high-emissions A1FI scenario, Miscanthus and willow show respective productivity reductions of up to 15% and 12%, accompanied by CI increases exceeding 100% for Miscanthus and 64% for willow. Energy use efficiency declines notably when transport distances increase; for Miscanthus, EUE drops by 21% when biomass is moved from 50 km to 500 km, underscoring the need for optimized supply chain logistics. SOC sequestration potential is highest in tropical regions (up to 4.57 t C ha⁻¹), but net SOC losses can occur in colder regions, and climate change significantly reduces SOC gains overall. Together, these findings demonstrate that while Miscanthus and willow have strong potential as sustainable bioenergy crops, achieving climate and energy benefits will require region-specific deployment strategies that integrate productivity, energy returns, carbon sequestration, and resilience to future climate change.

Collectively, the contributions in this second volume of this Special Issue deepen our understanding of grassland functioning and offer practical strategies to sustain productivity and ecosystem services in the face of climate stress.

3. Concluding Remarks

The second volume of this Special Issue provides a comprehensive and nuanced exploration of grassland productivity and resilience under the combined pressures of climate change and anthropogenic disturbance. Its fourteen contributions collectively advance our understanding of how biophysical factors, management interventions, and climatic drivers interact to shape grassland function, sustainability, and multifunctionality.

A recurring theme across the studies is the critical importance of context-specific management practices, such as mowing, burning, grazing exclusion, fertilization, and restoration techniques. The findings consistently demonstrate that the effectiveness of such interventions strongly depends on local ecological conditions. Some practices can enhance soil nutrient availability and ecosystem stability, while others may cause declines if applied without considering the system’s characteristics. Similar conclusions have been drawn in global syntheses, which emphasize that grassland responses to management are highly heterogeneous and mediated by local soil–climate interactions [1,7].

Several of the featured works underscore the critical role of soil moisture, temperature, and vegetation traits as key mediators of ecosystem responses, influencing carbon sequestration, biodiversity, and productivity. This aligns with broader evidence that soil–water–climate feedback largely determines grassland vulnerability and adaptive capacity [8,9]. Others illustrate the growing potential of remote sensing, machine learning, and modeling tools to provide real-time monitoring and early warning systems—essential components for adaptive management in drought-prone and climate-sensitive grasslands [10,11].

This volume also highlights the synergies and trade-offs among ecosystem services, including biodiversity conservation, forage production, and carbon storage, across both natural and improved grasslands [12]. The diversity of methodologies—from plot-level field experiments to national-scale policy analyses—reflects the increasing integration of ecological, technological, and socio-political perspectives in contemporary grassland research [13].

As grasslands face accelerating climatic and land-use pressures, the insights presented here provide robust evidence to inform resilient and sustainable land management strategies. Moving forward, the integration of ecological understanding with scalable monitoring tools and inclusive policy frameworks will be essential for safeguarding the long-term productivity, biodiversity, and multifunctionality of grassland ecosystems worldwide [14,15].