Sustaining altitude pastures in mountain landscapes-a fuzzy cognitive model approach.

Similarly to other European mountain areas, in Serra da Estrela the grazing pressure has been reducing due to social and economic drivers that have pushed shepherds and sheep to the foothill, or plainly out of the sector. Shrub encroachment on commons and other previously grazed land is one of the most tangible effects of pastoral abandonment in Serra de Estrela. The impacts of the resulting increase in landscape continuity and biomass availability were made clear in the severe fires of 2017 and 2022. As fire risk is likely to increase with climate change, it becomes urgent to understand what strategies can be deployed to keep fragmentation in these landscapes. Key actors such as shepherds should be involved in this discussion to understand their perceptions, points of view and reasons for abandoning upland pastures. In this study, we use fuzzy cognitive mapping to identify the key variables and mechanisms affecting the pastoral system according to local shepherds. In our study, we developed with local stakeholders a framework outlining the local pastoral system. Based on that, we carried out the fuzzy cognitive mapping collecting 14 questionnaires. We found that shepherds' income is a central issue, but that it is highly dependent on many factors. Increasing the Common Agricultural Policy payments alone is not enough to incentivise the use of upland pastures. More targeted strategies, such as more support for shrub clearing, and direct payments conditional to transhumance are more impactful. Despite a contentious discourse between conservation and shepherding values in Serra da Estrela, we find that shepherd's values are aligned with biodiversity conservation and a potential nature-based solution for minimizing fire risk through woody fuel management. This opens up possibilities for new governance strategies, that put Serra da Estrela's social, environmental and cultural values at its core.

Different microbial functional traits drive bulk and rhizosphere soil phosphorus mobilization in an alpine meadow after nitrogen input.

Enhanced nitrogen (N) input is expected to influence the soil phosphorus (P) cycling through biotic and abiotic factors. Among these factors, soil microorganisms play a vital role in regulating soil P availability. However, the divergent contribution of functional microorganisms to soil P availability in the rhizosphere and bulk soil under N addition remains unclear. We conducted an N addition experiment with four N input rates (0, 5, 10, and 15 g N m-2 year-1) in an alpine meadow over three years. Metagenomics was employed to investigate the functional microbial traits in the rhizosphere and bulk soil. We showed that N addition had positive effects on microbial functional traits related to P-cycling in the bulk and rhizosphere soil. Specifically, high N addition significantly increased the abundance of most microbial genes in the bulk soil but only enhanced the abundance of five genes in the rhizosphere soil. The soil compartment, rather than the N addition treatment, was the dominant factor explaining the changes in the diversity and network of functional microorganisms. Furthermore, the abundance of functional microbial genes had a profound effect on soil available P, particularly in bulk soil P availability driven by the ppa and ppx genes, as well as rhizosphere soil P availability driven by the ugpE gene. Our results highlight that N addition stimulates the microbial potential for soil P mobilization in alpine meadows. Distinct microbial genes play vital roles in soil P availability in bulk and rhizosphere soil respectively. This indicates the necessity for models to further our knowledge of P mobilization processes from the bulk soil to the rhizosphere soil, allowing for more precise predictions of the effects of N enrichment on soil P cycling.

Large-scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand.

Grasslands provide important ecosystem services to society, including biodiversity, water security, erosion control, and forage production. Grasslands are also vulnerable to droughts, rendering their future vitality under climate change uncertain. Yet, the grassland response to drought is not well understood, especially for heterogeneous Central European grasslands. We here fill this gap by quantifying the spatiotemporal sensitivity of grasslands to drought using a novel remote sensing dataset from Landsat/Sentinel-2 paired with climate re-analysis data. Specifically, we quantified annual grassland vitality at fine spatial scale and national extent (Germany) from 1985 to 2021. We analyzed grassland sensitivity to drought by testing for statistically robust links between grassland vitality and common drought indices. We furthermore explored the spatiotemporal variability of drought sensitivity for 12 grassland habitat types given their different biotic and abiotic features. Grassland vitality maps revealed a large-scale reduction of grassland vitality during past droughts. The unprecedented drought of 2018-2019 stood out as the largest multi-year vitality decline since the mid-1980s. Grassland vitality was consistently coupled to drought (R2 = .09-.22) with Vapor Pressure Deficit explaining vitality best. This suggests that high atmospheric water demand, as observed during recent compounding drought and heatwave events, has major impacts on grassland vitality in Central Europe. We found a significant increase in drought sensitivity over time with highest sensitivities detected in periods of extremely high atmospheric water demand, suggesting that drought impacts on grasslands are becoming more severe with ongoing climate change. The spatial variability of grassland drought sensitivity was linked to different habitat types, with declining sensitivity from dry and mesic to wet habitats. Our study provides the first large-scale, long-term, and spatially explicit evidence of increasing drought sensitivities of Central European grasslands. With rising compound droughts and heatwaves under climate change, large-scale grassland vitality loss, as in 2018-2019, will thus become more likely in the future.

Effects of management practices on the ecosystem-service multifunctionality of temperate grasslands.

Human wellbeing depends on ecosystem services, highlighting the need for improving the ecosystem-service multifunctionality of food and feed production systems. We study Swiss agricultural grasslands to assess how employing and combining three widespread aspects of grassland management and their interactions can enhance 22 plot-level ecosystem service indicators, as well as ecosystem-service multifunctionality. The three management aspects we assess are i) organic production system, ii) an eco-scheme prescribing extensive management (without fertilization), and iii) harvest type (pasture vs. meadow). While organic production system and interactions between the three management aspects play a minor role, the main effects of eco-scheme and harvest type considerably shape single services. Moreover, the eco-scheme 'extensive management' and the harvest type 'pasture' enhance plot-scale ecosystem-service multifunctionality, mostly through facilitating cultural services at the expense of provisioning services. These changes in ecosystem-service supply occur mainly via changes in land-use intensity, i.e., reduced fertilizer input and harvest frequency. In conclusion, diversifying grassland management where this is currently homogeneous across farms and landscapes depicts an important first step to improve landscape-scale multifunctionality for sustainable grassland systems. To meet societal ecosystem services demand, the three studied management aspects can be systematically combined to increase ecosystem services that are in short supply.

Effects of experimental drought and plant diversity on multifunctionality of a model system for crop rotation.

In low-diversity productive grasslands, modest changes to plant diversity (richness, composition and relative abundance) may affect multiple ecosystem functions (multifunctionality), including yield. Despite the economic importance of productive grasslands, effects of plant diversity and environmental disturbance on multifunctionality are very rarely quantified. We systematically varied species richness, composition, and relative abundance of grassland ley communities and manipulated water supply (rainfed and drought) to quantify effects of diversity and environmental disturbance on multifunctionality. We then replaced the grassland leys with a monoculture crop to investigate 'follow-on' effects. We measured six agronomy-related ecosystem functions across one or both phases: yield, yield consistency, digestibility and weed suppression (grassland ley phase), legacy effect (effect on follow-on crop yield), and nitrogen fertiliser efficiency (full rotation). Drought reduced most ecosystem functions, although effects were species- and function-specific. Increased plant diversity affected mean performance, and reduced variation, across the six functions (contributing to multifunctional stability). Multifunctionality index values across a wide range of mixture diversity were higher than the best monoculture under both rainfed and drought conditions (transgressive over-performance). Higher-diversity, lower-nitrogen (150N) mixtures had higher multifunctionality than a low-diversity, higher-nitrogen (300N) grass monoculture. Plant diversity in productive grasslands is a practical farm-scale management action to mitigate drought impacts and enhance multifunctionality of grassland-crop rotation systems.

Permanent areas and changes in forests, grasslands, and wetlands in the North European Plain since the eighteenth century-a case study of the Koscian Plain in Poland.

This study investigates the intricate and enduring interplay of historical events, human activities, and natural processes shaping the landscape of North European Plain in western Poland over 230 years. Topographic maps serve as reliable historical data sources to quantify changes in forest, grassland, and wetland areas, scrutinizing their fragmentation and persistence. The primary objectives are to identify the permanent areas of the landscape and propose a universal cartographic visualization method for effectively mapping these changes. Using topographic maps and historical data, this research quantifies land cover changes, especially in forest, grassland, and wetland areas. With the help of retrogressive method we process raster historical data into vector-based information. Over time, wetlands experienced a substantial reduction, particularly in 1960-1982, attributed to both land reclamation and environmental factors. Grassland areas fluctuated, influenced by wetland and drier habitat dynamics. Fragmentation in grassland areas poses biodiversity and ecosystem health concerns, whereas forested areas showed limited fluctuations, with wetland forests nearly disappearing. These findings highlight wetland ecosystems' sensitivity to human impacts and emphasize the need to balance conservation and sustainable development to preserve ecological integrity. This study advances landscape dynamics understanding, providing insights into historical, demographic, economic, and environmental transformations. It underscores the imperative for sustainable land management and conservation efforts to mitigate human impacts on ecosystems and biodiversity in the North European Plain.

Environmental conditions associated with initial northern expansion of anatomically modern humans.

The ability of our ancestors to switch food sources and to migrate to more favourable environments enabled the rapid global expansion of anatomically modern humans beyond Africa as early as 120,000 years ago. Whether this versatility was largely the result of environmentally determined processes or was instead dominated by cultural drivers, social structures, and interactions among different groups, is unclear. We develop a statistical approach that combines both archaeological and genetic data to infer the more-likely initial expansion routes in northern Eurasia and the Americas. We then quantify the main differences in past environmental conditions between the more-likely routes and other potential (less-likely) routes of expansion. We establish that, even though cultural drivers remain plausible at finer scales, the emergent migration corridors were predominantly constrained by a combination of regional environmental conditions, including the presence of a forest-grassland ecotone, changes in temperature and precipitation, and proximity to rivers.

Seeds of the Settler Colony: How Peasant and Kazakh Knowledge, Environment, and Bureaucracy Shaped Steppe Agronomy in the Late Russian Empire.

At the turn of the twentieth century, Russian imperial officials hoped to transform the Kazakh Steppe from a zone of pastoral nomadism into a zone of sedentary grain farms. They planned to accomplish this transformation by importing peasants from European Russia and settling them in the steppe along with advanced scientific agricultural practices, equipment, and infrastructure. It was a project that linked steppe settlement and the Russian Empire to a global story of settler colonialism, science, and technology in the first decades of the twentieth century. An examination of this project through the lens of the expansion of grain farming reveals that the changes it wrought were not solely due to European science and technology but were contingent, dependent on local knowledge, the vagaries of climate, and adaptation to the realities of the steppe environment.

Grazing exclusion is more effective for vegetation restoration and nutrient transfer in the heavily degraded desert steppe.

BACKGROUND: Grazing exclusion is an efficient practice to restore degraded grassland ecosystems by eliminating external disturbances and improving ecosystems' self-healing capacities, which affects the ecological processes of soil-plant systems. Grassland degradation levels play a critical role in regulating these ecological processes. However, the effects of vegetation and soil states at different degradation stages on grassland ecosystem restoration are not fully understood. To better understand this, desert steppe at three levels of degradation (light, moderate, and heavy degradation) was fenced for 6 years in Inner Mongolia, China. Community characteristics were investigated, and nutrient concentrations of the soil (0-10 cm depth) and dominant plants were measured. RESULTS: We found that grazing exclusion increased shoots' carbon (C) concentrations, C/N, and C/P, but significantly decreased shoots' nitrogen (N) and phosphorus (P) concentrations for Stipa breviflora and Cleistogenes songorica. Interestingly, there were no significant differences in nutrient concentrations of these two species among the three degraded desert steppes after grazing exclusion. After grazing exclusion, annual accumulation rates of aboveground C, N, and P pools in the heavily degraded area were the highest, but the aboveground nutrient pools were the lowest among the three degraded grasslands. Similarly, the annual recovery rates of community height, cover, and aboveground biomass in the heavily degraded desert steppe were the highest among the three degraded steppes after grazing exclusion. These results indicate that grazing exclusion is more effective for vegetation restoration in the heavily degraded desert steppe. The soil total carbon, total nitrogen, total phosphorus, available nitrogen, and available phosphorus concentrations in the moderately and heavily degraded desert steppes were significantly decreased after six years of grazing exclusion, whereas these were no changes in the lightly degraded desert steppe. Structural equation model analysis showed that the grassland degradation level mainly altered the community aboveground biomass and aboveground nutrient pool, driving the decrease in soil nutrient concentrations and accelerating nutrient transfer from soil to plant community, especially in the heavily degraded grassland. CONCLUSIONS: Our study emphasizes the importance of grassland degradation level in ecosystem restoration and provides theoretical guidance for scientific formulation of containment policies.

Comparative venation costs of monocotyledon and dicotyledon species in the eastern Colorado steppe.

MAIN CONCLUSION: Leaf vein network cost (total vein surface area per leaf volume) for major veins and vascular bundles did not differ between monocot and dicot species in 21 species from the eastern Colorado steppe. Dicots possessed significantly larger minor vein networks than monocots. Across the tree of life, there is evidence that dendritic vascular transport networks are optimized, balancing maximum speed and integrity of resource delivery with minimal resource investment in transport and infrastructure. Monocot venation, however, is not dendritic, and remains parallel down to the smallest vein orders with no space-filling capillary networks. Given this departure from the "optimized" dendritic network, one would assume that monocots are operating at a significant energetic disadvantage. In this study, we investigate whether monocot venation networks bear significantly greater carbon/construction costs per leaf volume than co-occurring dicots in the same ecosystem, and if so, what physiological or ecological advantage the monocot life form possesses to compensate for this deficit. Given that venation networks could also be optimized for leaf mechanical support or provide herbivory defense, we measured the vascular system of both monocot and dicots at three scales to distinguish between leaf investment in mechanical support (macroscopic vein), total transport and capacitance (vascular bundle), or exclusively water transport (xylem) for both parallel and dendritic venation networks. We observed that vein network cost (total vein surface area per leaf volume) for major veins and vascular bundles was not significantly different between monocot species and dicot species. Dicots, however, possess significantly larger minor vein networks than monocots. The 19 species subjected to gas-exchange measurement in the field displayed a broad range of Amax and but demonstrated no significant relationships with any metric of vascular network size in major or minor vein classes. Given that monocots do not seem to display any leaf hydraulic disadvantage relative to dicots, it remains an important research question why parallel venation (truly parallel, down to the smallest vessels) has not arisen more than once in the history of plant evolution.

Quantitative analysis of the impact of climate variability and human activities on grassland productivity of the Qilian Mountain National Park, China.

To quantitatively analyze the impact of climate variability and human activities on grassland productivity of China's Qilian Mountain National Park, this study used Carnegic-Ames-Stanford Approach model (CASA) and Integrated Vegetation model improved by the Comprehensive and Sequential Classification System (CSCS) to assess the trends of grassland NPP from 2000 to 2015, the residual trend analysis method was used to quantify the impact of human activities and climate change on the grassland based on the NPP changes. The actual grassland NPP accumulation mainly occurred in June, July and August (autumn); the actual NPP showed a fluctuating upward trend with an average increase of 2.2 g C·m-2 a-1, while the potential NPP increase of 1.6 g C·m-2 a-1 and human-induced NPP decreased of 0.5 g C·m-2 a-1. The annual temperature showed a fluctuating upward trend with an average increase of 0.1°C 10a-1, but annual precipitation showed a fluctuating upward trend with an average annual increase of 1.3 mm a-1 from 2000 to 2015. The area and NPP of grassland degradation caused by climate variability was significantly greater than that caused by human activities and mainly distributed in the northwest and central regions, but area and NPP of grassland restored caused by human activities was significantly greater than that caused by climate variability and mainly distributed in the southeast regions. In conclusion, grassland in Qilian Mountain National Park showed a trend of degradation based on distribution area, but showed a trend of restoration based on actual NPP. Climate variability was the main cause of grassland degradation in the northwestern region of study area, and restoration of grassland in the eastern region was the result of the combined effects of human activities and climate variability. Under global climate change, the establishment of Qilian Mountain National Park was of great significance to the grassland's protection and the grasslands ecological restoration that have been affected by humans.

Biological response to Przewalski's horse reintroduction in native desert grasslands: a case study on the spatial analysis of ticks.

BACKGROUND: Reintroduction represents an effective strategy for the conservation of endangered wildlife, yet it might inadvertently impact the native ecosystems. This investigation assesses the impact of reintroducing endangered Przewalski's horses into the desert grassland ecosystem of the Kalamaili Nature Reserve (KNR), particularly its effect on the spatial distribution of ticks. In a 25 km2 core area of Przewalski's horse distribution, we set up 441 tick sampling sites across diverse habitats, including water sources, donkey trails, and grasslands, recording horse feces and characteristics to analyze the occurrence rate of ticks. Additionally, we gathered the data of 669 fresh feces of horses. To evaluate the spatial dynamics between these feces and ticks, we used methods such as Fixed Kernel Estimation (FKE), Moran's I spatial autocorrelation index, and Generalized Linear Models (GLM). RESULTS: The dominant species of ticks collected in the core area were adult Hyalomma asiaticum (91.36%). Their occurrence rate was higher near donkey trails (65.99%) and water sources (55.81%), particularly in areas with the fresh feces of Przewalski's horses. The ticks' three risk areas, as defined by FKE, showed significant overlap and positive correlation with the distribution of Przewalski's horses, with respective overlap rates being 90.25% in high risk, 33.79% in medium risk, and 23.09% in low risk areas. Moran's I analysis revealed a clustering trend of the fresh feces of Przewalski's horses in these areas. The GLM confirmed a positive correlation between the distribution of H. asiaticum and the presence of horse fresh feces, alongside a negative correlation with the proximity to water sources and donkey trails. CONCLUSIONS: This study reveals the strong spatial correlation between Przewalski's horses and H. asiaticum in desert grasslands, underlining the need to consider interspecific interactions in wildlife reintroductions. The findings are crucial for shaping effective strategies of wildlife conservation and maintaining ecological balance.

Diversity inhibits foliar fungal diseases in grasslands: Potential mechanisms and temperature dependence.

A long-standing debate exists among ecologists as to how diversity regulates infectious diseases (i.e., the nature of diversity-disease relationships); a dilution effect refers to when increasing host diversity inhibits infectious diseases (i.e., negative diversity-disease relationships). However, the generality, strength, and potential mechanisms underlying negative diversity-disease relationships in natural ecosystems remain unclear. To this end, we conducted a large-scale survey of 63 grassland sites across China to explore diversity-disease relationships. We found widespread negative diversity-disease relationships that were temperature-dependent; non-random diversity loss played a fundamental role in driving these patterns. Our study provides field evidence for the generality and temperature dependence of negative diversity-disease relationships in grasslands, becoming stronger in colder regions, while also highlighting the role of non-random diversity loss as a mechanism. These findings have important implications for community ecology, disease ecology, and epidemic control.

Co-located ecological data for exploring top- and subsoil carbon dynamics across grassland-woodland contrasts.

Soil organic carbon (SOC) is a soil health indicator and understanding dynamics changing SOC stocks will help achieving net zero goals. Here we present four datasets featuring 11,750 data points covering co-located aboveground and below-ground metrics for exploring ecosystem SOC dynamics. Five sites across England with an established land use contrast, grassland and woodland next to each other, were rigorously sampled for aboveground (n = 109), surface (n = 33 soil water release curves), topsoil, and subsoil metrics. Commonly measured soil metrics were analysed in five soil increments for 0-1 metre (n = 4550). Less commonly measured soil metrics which were assumed to change across the soil profile were measured on a subset of samples only (n = 3762). Additionally, we developed a simple method for soil organic matter fractionation using density fractionation which is part of the less common metrics. Finally, soil metrics which may impact SOC dynamics, but with less confidence as to their importance across the soil profile were only measured on topsoil (~5-15 cm = mineral soil) and subsoil (below 50 cm) samples (n = 2567).

Modeling population dynamics of invasive pines to optimize their control in native grasslands of Argentina.

The spread of invasive alien species over natural environments has become one of the most serious threats to biodiversity and the functioning of ecosystems worldwide. Understanding the population attributes that allow a given species to become invasive is crucial for improving prevention and control interventions. Pampas grasslands are particularly sensitive to the invasion of exotic woody plants. In particular, the Ventania Mountains undergo the advance of alien woody plants; among which the Aleppo pine (Pinus halepensis) stands out due to the extension of the area it covers and the magnitude of the ecological changes associated to its presence. Using a model that describes the population dynamics of the species in the area, we evaluated the expected behavior of the population under different environmental conditions and different management scenarios. When the effect of stochastic fires was simulated, the growth rate was greater than 1 for all the frequencies considered, peaking under fires every nine years, on average. When evaluating the effect of periodic mechanical control of the adult population, the reduction in growth rate was insufficient, except for cutting intensities that significantly exceeded the current operational capacity of the area. Under prescribed fire scenarios, on the other hand, burning frequencies greater than seven years resulted in population reductions. The results highlight the importance of fire in regulating the population of P. halepensis in the Ventania Mountains, with contrasting effects depending on the frequency with which it occurs, which allows considering it as an effective environmental management option for the control of the species.

Interannual precipitation variability dominates the growth of alpine grassland above-ground biomass at high elevations on the Tibetan Plateau.

The impact of global climate change on mountainous regions with significant elevational gaps is complex and often unpredictable. In particular, alpine grassland ecosystems, are experiencing changes in their spatial patterns along elevational gradients, which increases their vulnerability to degradation. Therefore, a more detailed understanding of spatiotemporal changes in alpine grassland productivity along elevational gradients and an elevation-dependent characterization of the effects of climatic variables on grassland productivity dynamics are essential. Thus, we conducted a study in the Tibetan Plateau, where we collected 2251 above-ground biomass (AGB) observations collected from 1986 to 2020. Mean annual temperature (TMP), annual precipitation (PRE), interannual precipitation variability (CVP), and snowmelt (SNMM) were chosen as influential variables. Using the Random Forest algorithm, we generated an AGB raster dataset covering the period 1989-2020 based on earth observation data at 30 m resolution to examine the dynamics of alpine grasslands and their response to climate change with respect to elevation. The results showed that the AGB of alpine grassland on the Tibetan Plateau was 49.17 g/m2. We observed an increasing trend in grassland AGB at high elevations, with a growth rate of about 0.28 g/m2 per year within the interval of 3100-4800 m. However, above the elevation of approximately 4400-4600 m, we observed a decoupling trend between grassland AGB and TMP. Moreover, at most elevations, the proportion of maximum partial correlation coefficients for CVP, PRE, and SNMM surpassed that of TMP. We found the dominant role of precipitation variability on grassland AGB dynamics, with 22.80 % and 18.86 % for CVP+ and CVP-, respectively. The proportion of CVP+ did not vary much at different elevations, whereas the proportion of CVP- increased with elevation, varying between 12.85 and 30.25 %. In the future, precipitation on the Tibetan plateau is expected to increase, potentially reversing its original positive impact.

A general pattern of plant traits and their relationships with environmental factors and microbial life-history strategies.

The trait-based unidimensional plant economics spectrum provides a valuable framework for understanding plant adaptation strategies to the environment. However, it is still uncertain whether there is a general multidimensionality of how variation of both leaf and fine root traits are influenced by environmental factors, and how these relate to microbial resource strategies. Here, we examined the coordination patterns of four pairs of similar leaf and fine root traits of herbaceous plants in an alpine meadow at the community-level, and their environmental driving patterns. We then assessed their correlation with microbial life-history strategies, as these exhibit analogous resource strategies with plants in terms of growth and resource utilization efficiency. Results exhibited an analogous multidimensionality of the economics spectrum for leaf and fine root traits: the first dimension, collaboration gradient, primarily represented a tradeoff between lifespan and resource foraging efficiency; the second dimension, conservation gradient, primarily represented a tradeoff between conservation and acquisition in resource uptake. Climate variables had a stronger impact on both dimensions for leaf and fine root traits than soil variables did; whereas, the primary drivers were more complex for fine root traits than for leaf traits. The collaboration gradient of leaf and fine root traits exhibited consistent relationships with soil microbial life-history strategies, both showed negative and positive correlation with bacterial and fungal strategies, respectively. Our findings suggest that both leaves and fine roots have general multidimensional strategies for adapting to new environments and provide a solid basis for further understanding the relationships between the adaptive strategies of plants and microbes.

Soil pore characteristics and the fate of new switchgrass-derived carbon in switchgrass and prairie bioenergy cropping systems.

Monoculture switchgrass and restored prairie are promising perennial feedstock sources for bioenergy production on the lands unsuitable for conventional agriculture. Such lands often display contrasting topography that influences soil characteristics and interactions between plant growth and soil C gains. This study aimed at elucidating the influences of topography and plant systems on the fate of C originated from switchgrass plants and on its relationships with soil pore characteristics. For that, switchgrass plants were grown in intact soil cores collected from two contrasting topographies, namely steep slopes and topographical depressions, in the fields in multi-year monoculture switchgrass and restored prairie vegetation. The 13C pulse labeling allowed tracing the C of switchgrass origin, which X-ray computed micro-tomography enabled in-detail characterization of soil pore structure. In eroded slopes, the differences between the monoculture switchgrass and prairie in terms of total and microbial biomass C were greater than those in topographical depressions. While new switchgrass increased the CO2 emission in depressions, it did not significantly affect the CO2 emission in slopes. Pores of 18-90 µm Ø facilitated the accumulation of new C in soil, while > 150 µm Ø pores enhanced the mineralization of the new C. These findings suggest that polyculture prairie located in slopes can be particularly beneficial in facilitating soil C accrual and reduce C losses as CO2.

Predicting the responses of European grassland communities to climate and land cover change.

European grasslands are among the most species-rich ecosystems on small spatial scales. However, human-induced activities like land use and climate change pose significant threats to this diversity. To explore how climate and land cover change will affect biodiversity and community composition in grassland ecosystems, we conducted joint species distribution models (SDMs) on the extensive vegetation-plot database sPlotOpen to project distributions of 1178 grassland species across Europe under current conditions and three future scenarios. We further compared model accuracy and computational efficiency between joint SDMs (JSDMs) and stacked SDMs, especially for rare species. Our results show that: (i) grassland communities in the mountain ranges are expected to suffer high rates of species loss, while those in western, northern and eastern Europe will experience substantial turnover; (ii) scaling anomalies were observed in the predicted species richness, reflecting regional differences in the dominant drivers of assembly processes; (iii) JSDMs did not outperform stacked SDMs in predictive power but demonstrated superior efficiency in model fitting and predicting; and (iv) incorporating co-occurrence datasets improved the model performance in predicting the distribution of rare species. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

The rectangular tile classification model based on Sentinel integrated images enhances grassland mapping accuracy: A case study in Ordos, China.

Arid zone grassland is a crucial component of terrestrial ecosystems and plays a significant role in ecosystem protection and soil erosion prevention. However, accurately mapping grassland spatial information in arid zones presents a great challenge. The accuracy of remote sensing grassland mapping in arid zones is affected by spectral variability caused by the highly diverse landscapes. In this study, we explored the potential of a rectangular tile classification model, constructed using the random forest algorithm and integrated images from Sentinel-1A (synthetic aperture radar imagery) and Sentinel-2 (optical imagery), to enhance the accuracy of grassland mapping in the semiarid to arid regions of Ordos, China. Monthly Sentinel-1A median value images were synthesised, and four MODIS vegetation index mean value curves (NDVI, MSAVI, NDWI and NDBI) were used to determine the optimal synthesis time window for Sentinel-2 images. Seven experimental groups, including 14 experimental schemes based on the rectangular tile classification model and the traditional global classification model, were designed. By applying the rectangular tile classification model and Sentinel-integrated images, we successfully identified and extracted grasslands. The results showed the integration of vegetation index features and texture features improved the accuracy of grassland mapping. The overall accuracy of the Sentinel-integrated images from EXP7-2 was 88.23%, which was higher than the accuracy of the single sensor Sentinel-1A (53.52%) in EXP2-2 and Sentinel-2 (86.53%) in EXP5-2. In all seven experimental groups, the rectangular tile classification model was found to improve overall accuracy (OA) by 1.20% to 13.99% compared to the traditional global classification model. This paper presents novel perspectives and guidance for improving the accuracy of remote sensing mapping for land cover classification in arid zones with highly diverse landscapes. The study presents a flexible and scalable model within the Google Earth Engine framework, which can be readily customized and implemented in various geographical locations and time periods.