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Savannas are characterized by water scarcity and degradation, making them highly vulnerable to increased uncertainties in water availability resulting from climate change. This poses a significant threat to ecosystem services and rural livelihoods that depend on them. In addition, the lack of consensus among climate models on precipitation change makes it difficult for land managers to plan for the future. Therefore, Savanna rangeland management needs to develop strategies that can sustain Savanna resilience and avoid tipping points under an uncertain future climate.Our study aims to analyse the impacts of climate change and rangeland management on degradation in Savanna ecosystems of southern Africa, providing insights for the management of semi‐arid Savannas under uncertain conditions worldwide. To achieve this, we simulated the effects of projected changes in temperature and precipitation, as predicted by 10 global climate models, on water resources and vegetation (cover, functional diversity, tipping points (transition from grass‐dominated to shrub‐dominated vegetation)). We simulated three different rangeland management options (herbivore communities dominated by grazers, by browser and by mixed feeders), each with low and high animal densities, using the ecohydrological model EcoHyD.Our results identified intensive grazing as the primary contributor to the increased risk of degradation in response to changing climatic conditions across all climate change scenarios. This degradation encompassed a reduction in available water for plant growth within the context of predicted climate change. It also entails a decline in the overall vegetation cover, the loss of functionally important plant species and the inefficient utilization of available water resources, leading to earlier tipping points.Synthesis and applications. Our findings underscore that, in the face of climate uncertainty, farmers' most effective strategy for securing their livelihoods and ecosystem stability is to integrate browsers and apply management of mixed herbivore communities. This management approach not only significantly delays or averts tipping points but also maintained greater plant functional diversity, fostering a more robust and resilient ecosystem that acts as a vital buffer against adverse climatic conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Biocrusts are ecosystem engineers in drylands and structure the landscape through their ecohydrological effects. They regulate soil infiltration and evaporation but also surface water redistribution, providing important resources for vascular vegetation. Spatially-explicit ecohydrological models are useful tools to explore such ecohydrological mechanisms, but biocrusts have rarely been included in them. We contribute to closing this gap and assess how biocrusts shape spatio-temporal water fluxes and availability in a dryland landscape and how landscape hydrology is affected by climate-change induced shifts in the biocrust community. We extended the spatially-explicit, process-based ecohydrological dryland model EcoHyD by a biocrust layer which modifies water in- and outputs from the soil and affects surface runoff. The model was parameterized for a dryland hillslope in South-East Spain using field and literature data. We assessed the effect of biocrusts on landscape-scale soil moisture distribution, plant-available water and the hydrological processes behind it. To quantify the biocrust effects, we ran the model with and without biocrusts for a wet and dry year. Finally, we compared the effect of incipient and well-developed cyanobacteria- and lichen biocrusts on surface hydrology to evaluate possible paths forward if biocrust communities change due to climate change. Our model reproduced the runoff source-sink patterns typical of the landscape. The spatial differentiation of soil moisture in deeper layers matched the observed distribution of vascular vegetation. Biocrusts in the model led to higher water availability overall and in vegetated areas of the landscape and that this positive effect in part also held for a dry year. Compared to bare soil and incipient biocrusts, well-developed biocrusts protected the soil from evaporation thus preserving soil moisture despite lower infiltration while at the same time redistributing water toward downhill vegetation. Biocrust cover is vital for water redistribution and plant-available water but potential changes of biocrust composition and cover can reduce their ability of being a water source and sustaining dryland vegetation. The process-based model used in this study is a promising tool to further quantify and assess long-term scenarios of climate change and how it affects ecohydrological feedbacks that shape and stabilize dryland landscapes. [ABSTRACT FROM AUTHOR]

Questions: Soil resource heterogeneity influences the outcome of plant–plant interactions and, consequently, species co‐existence and diversity patterns. The magnitude and direction of heterogeneity effects vary widely, and the processes underlying such variations are not fully understood. In this study, we explored how and under what resource conditions small‐scale heterogeneity modulates grassland plant diversity. Location: Oderhänge Mallnow, Potsdam, Brandenburg, Germany. Methods: We expanded the individual‐based plant community model (IBC‐grass) to incorporate dynamic below‐ground resource maps, simulating spatial heterogeneity of resource availability. Empirical centimeter‐scale data of soil C/N ratio were integrated into the model, accounting for both configurational and compositional heterogeneity. We then analyzed the interplay between small‐scale heterogeneity and resource availability on the interaction and co‐existence of plant species and overall diversity. Results: Our results showed significant differences between the low‐ and high‐resource scenarios, with both configurational and compositional heterogeneity having a positive effect on species richness and Simpson's diversity, but only under low‐resource conditions. As compositional heterogeneity in the fine‐scale C/N ratio increased, we observed a positive shift in Simpson's diversity and species richness, with the highest effects at the highest level of variability tested. We observed little to no effect in nutrient‐rich scenarios, and a shift to negative effects at the intermediate resource level. The study demonstrates that site‐specific resource levels underpin how fine‐scale heterogeneity influences plant diversity and species co‐existence, and partly explains the divergent effects recorded in different empirical studies. Conclusions: This study provides mechanistic insights into the complex relationship between resource heterogeneity and diversity patterns. It highlights the context‐dependent effects of small‐scale heterogeneity, which can be positive under low‐resource, neutral under high‐resource, and negative under intermediate‐resource conditions. These findings provide a foundation for future investigations into small‐scale heterogeneity–diversity relationships, contributing to a deeper understanding of the processes that promote species co‐existence in plant communities. [ABSTRACT FROM AUTHOR]

Under a changing climate, soil fungal communities will increasingly be subject to periods of heat stress. These periods can affect the performance of individual fungi and their competition for space and resources. Competition between fungi is strongly controlled by the exudation of inhibitory compounds, resulting in different competitive outcomes that range from overgrowth of the inferior competitor to a deadlock, where the competing fungi inhibit each other. As heat stress can alter the competitive outcome between fungi, the community composition can also change strongly. So far, a general understanding of the mechanisms that drive the competitive outcome between fungi under heat stress is still missing. However, this understanding is essential to assess important community functions, such as decomposition or mediation of plant nutrition, which strongly depend on the fungal community composition. Here, we used a partial differential equation (PDE) model simulating two fungal competitors in a two‐dimensional space, to mechanistically explain the observed change of fungal competition under heat stress. The model describes mycelial growth, the production and secretion of antifungal compounds and the synthesis of heat shock proteins of interacting colonies. We found a heat stress‐induced lag phase favouring the accumulation of antifungal compounds and the build‐up of inhibitor fields. This led to a qualitative change of the competitive outcome, reducing the occurrence of overgrowth by two thirds. The changes in competitive outcome favoured slower growing species, which benefit more strongly from the additional time during a stress‐induced lag to build up a defence or block territory that would otherwise be quickly claimed by faster competitors. Our work is an important step towards understanding how environmental changes may lead to qualitative changes in competitive outcomes. Our results show the importance of explicitly including species interactions into studies of climate change effects. [ABSTRACT FROM AUTHOR]

Forage supply and soil organic carbon storage are two important ecosystem functions 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 functions of permanent grasslands. Especially 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 CSR theory and the global spectrum of plant form and function into the LPJmL dynamic global vegetation model forming LPJmL-CSR. Using a Bayesian calibration method, we parameterised new plant functional types and used these to assess forage supply, soil organic carbon storage and community composition of three permanent grassland sites. These are a temperate grassland, 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 supply and/or SOC compared to LPJmL 5.3 at 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 S-PFTs). Under different resource limitations, we observed a shift of 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 above-ground 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 productivity. [ABSTRACT FROM AUTHOR]

Savannas are characterized by the coexistence of two contrasting plant life‐forms: woody and herbaceous vegetation. During the last decades, there has been a global trend of an increase in woody cover and the spread of shrubs and trees into areas that were previously dominated by grasses. This process, termed bush encroachment, is associated with severe losses of ecosystem functions and typically difficult to reverse. It is assumed to be an example of a critical transition between two alternative stable states. Overgrazing due to unsustainable rangeland management has been identified as one of the main causes of this transition, as it can trigger several self‐reinforcing feedback loops. However, the dynamic role of grazing within such feedback loops has received less attention. We used a set of coupled differential equations to describe the competition between shrubs and grasses, as well as plant biomass consumption via grazing and browsing. Grazers were assumed to receive a certain level of care from farmers, so that grazer densities emerge dynamically from the combined effect of vegetation abundance and farmer support. We quantified all self‐reinforcing and self‐dampening feedback loops at play and analyzed their relative importance in shaping system (in‐)stability. Bistability, the presence of a grass dominated and a shrub dominated state, emerges for intermediate levels of farmer support due to positive feedback that arises from competition between shrubs and grasses and from herbivory. We furthermore demonstrate that disturbances, such as drought events, trigger abrupt transitions from the grass dominated to the shrub dominated state and that the system becomes more susceptible to disturbances with increasing farmer support. Our results thus highlight the potential of interaction networks in combinations with feedback loop analysis for improving our understanding of critical transitions in general, and bush encroachment in particular. [ABSTRACT FROM AUTHOR]

Maintaining the resilience and functionality of savannas is key to sustaining the ecosystem services they provide. This maintenance is largely dependent on the resilience of savannas to stressors, such as prolonged droughts. The resilience to drought is largely determined by the interaction of herbivores and the functional composition of vegetation. So far, our understanding and ability to predict the response of savannas to drought under different types of rangeland use and as a function of vegetation composition are still limited.In this study, we used the ecohydrological, spatially‐explicit savanna model EcoHyD to determine if the resilience of a savanna rangeland towards prolonged droughts can be enhanced by the choice of rangeland use type (grazer‐dominated, mixed‐feeders or browser‐dominated) and animal density. We evaluated the ability of a Namibian savanna system to withstand droughts and recover from droughts based on its perennial grass cover and the overall species composition.Generally, we determined a low resilience under high grazer densities. Most importantly, we found that functional diversification of herbivores and plants acted as resilience insurance against droughts, leading to greater resistance and recovery of perennial grasses. In particular, a higher proportion of herbivores allowed for higher resilience, probably also due to a short‐term switch to more drought‐resistant or unpalatable species.In this case, herbivore diversification was of high self‐regulatory value by reestablishing trophic complexity, reducing the need for additional management interventions.Synthesis and applications: Savanna systems will be more resistant to drought if (i) a dense perennial grass cover is maintained, protecting the topsoil from heat‐induced water losses and erosion, encompassing functionally important species that are particularly well adapted to water stress and that are palatable, if (ii) the grazing pressure is adjusted to the productivity of the system, and (iii) the herbivore community includes browsers. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? Principal component regressions revealed the climate sensitivity of Tibetan arid desert scrubs. Plant nutrient traits and soil nutrient availability regulate desert scrubs' climate sensitivity. What is the implication of the main finding? Scrubs' sensitivity to temperature is mainly regulated by the nitrogen contents of soils and leaves. Scrubs' sensitivity to precipitation is affected by the leaf carbon content of dominant species. Neither soil nor plant nutritional properties alone can well explain scrubs' sensitivity to droughts. Climate models predict the further intensification of global warming in the future. Drylands, as one of the most fragile ecosystems, are vulnerable to changes in temperature, precipitation, and drought extremes. However, it is still unclear how plant traits interact with soil properties to regulate drylands' responses to seasonal and interannual climate change. The vegetation sensitivity index (VSI) of desert scrubs in the Qaidam Basin (NE Tibetan Plateau) was assessed by summarizing the relative contributions of temperature (SGST), precipitation (SGSP), and drought (temperature vegetation dryness index, STVDI) to the dynamics of the normalized difference vegetation index (NDVI) during plant growing months yearly from 2000 to 2015. Nutrient contents, including carbon, nitrogen, phosphorus, and potassium in topsoils and leaves of plants, were measured for seven types of desert scrub communities at 22 sites in the summer of 2016. Multiple linear and structural equation models were used to reveal how leaf and soil nutrient regimes affect desert scrubs' sensitivity to climate variability. The results showed that total soil nitrogen (STN) and leaf carbon content (LC), respectively, explained 25.9% and 17.0% of the VSI variance across different scrub communities. Structural equation modeling (SEM) revealed that STN and total soil potassium (STK) mediated desert scrub's VSI indirectly via SGST (with standardized path strength of −0.35 and +0.32, respectively) while LC indirectly via SGST and SGSP (with standardized path strength of −0.31 and −0.19, respectively). Neither soil nor leave nutrient contents alone could explain the VSI variance across different sites, except for the indirect influences of STN and STK via STVDI (−0.18 and 0.16, respectively). Overall, this study disentangled the relative importance of plant nutrient traits and soil nutrient availability in mediating the climatic sensitivity of desert scrubs in the Tibetan Plateau. Integrating soil nutrient availability with plant functional traits together is recommended to better understand the mechanisms behind dryland dynamics under global climate change. [ABSTRACT FROM AUTHOR]

Changing climatic conditions and unsustainable land use are major threats to savannas worldwide. Historically, many African savannas were used intensively for livestock grazing, which contributed to widespread patterns of bush encroachment across savanna systems. To reverse bush encroachment, it has been proposed to change the cattle‐dominated land use to one dominated by comparatively specialized browsers and usually native herbivores. However, the consequences for ecosystem properties and processes remain largely unclear. We used the ecohydrological, spatially explicit model EcoHyD to assess the impacts of two contrasting, herbivore land‐use strategies on a Namibian savanna: grazer‐ versus browser‐dominated herbivore communities. We varied the densities of grazers and browsers and determined the resulting composition and diversity of the plant community, total vegetation cover, soil moisture, and water use by plants. Our results showed that plant types that are less palatable to herbivores were best adapted to grazing or browsing animals in all simulated densities. Also, plant types that had a competitive advantage under limited water availability were among the dominant ones irrespective of land‐use scenario. Overall, the results were in line with our expectations: under high grazer densities, we found heavy bush encroachment and the loss of the perennial grass matrix. Importantly, regardless of the density of browsers, grass cover and plant functional diversity were significantly higher in browsing scenarios. Browsing herbivores increased grass cover, and the higher total cover in turn improved water uptake by plants overall. We concluded that, in contrast to grazing‐dominated land‐use strategies, land‐use strategies dominated by browsing herbivores, even at high herbivore densities, sustain diverse vegetation communities with high cover of perennial grasses, resulting in lower erosion risk and bolstering ecosystem services. [ABSTRACT FROM AUTHOR]

Summary: Priming, an inducible stress defence strategy that prepares an organism for an impending stress event, is common in microbes and has been studied mostly in isolated organisms or populations. How the benefits of priming change in the microbial community context and, vice versa, whether priming influences competition between organisms, remain largely unknown. In this study, we grew different isolates of soil fungi that experienced heat stress in isolation and pairwise competition experiments and assessed colony extension rate as a measure of fitness under priming and non‐priming conditions. Based on this data, we developed a cellular automaton model simulating the growth of the ascomycete Chaetomium angustispirale competing against other fungi and systematically varied fungal response traits to explain similarities and differences observed in the experimental data. We showed that competition changes the priming benefit compared with isolated growth and that it can even be reversed depending on the competitor's traits such as growth rate, primeability and stress susceptibility. With this study, we transfer insights on priming from studies in isolation to competition between species. This is an important step towards understanding the role of inducible defences in microbial community assembly and composition. [ABSTRACT FROM AUTHOR]

Crop models are crucial in assessing the reliability and sustainability of soil water conservation practices. The AquaCrop model was tested and validated for maize productivity under the selected climate smart agriculture (CSA) practices in the rainfed production systems. The model was validated using final biomass (B) and grain yield (GY) data from field experiments involving seven CSA practices (halfmoon pits, 2 cm thick mulch, 4 cm thick mulch, 6 cm thick mulch, 20 cm deep permanent planting basins (PPB), and 30 cm deep) and the control (conventional practice) where no CSA was applied. Statistics for coefficient of determination (R2), Percent bias (Pbias), and Nash–Sutcliffe (E) for B and GY indicate that the AquaCrop model was robust to predict crop yield and biomass as illustrated by the value of R2 > 0.80, Pbias −1.52–1.25% and E > 0.68 for all the CSA practices studied. The relative changes between the actual and simulated water use efficiency (WUE) of grain yield was observed in most of the CSA practices. However, measured WUE was seemingly better in the 2 cm thick mulch, indicating a potential for water saving and yield improvement. Therefore, the AquaCrop model is recommended as a reliable tool for assessing the effectiveness of the selected CSA practices for sustainable and improved maize production; although, the limitations in severely low soil moisture conditions and water stressed environments should be further investigated considering variations in agroecological zones. [ABSTRACT FROM AUTHOR]

In sub-humid regions, declining maize (Zea mays L.) yield is majorly attributed to unreliable rainfall and high evapotranspiration demand during critical growth stages. However, there are limited farm technologies for conserving soil water and increasing water use efficiency (WUE) in rainfed production systems amidst a changing climate. This study aimed at assessing the performance of different climate smart agriculture (CSA) practices, such as mulching and permanent planting basins (PPB), on maize growth, yield, water use efficiency and soil moisture storage. Field experiments involving mulches of 2 cm (M_2 cm), 4 cm (M_4 cm) and 6 cm (M_6 cm) thickness, permanent planting basins of 20 cm (PPB_20 cm) and 30 cm (PPB_30 cm) depths and the control/or conventional treatments were conducted for three maize growing seasons in the sub-humid climate of Western Uganda. Results indicate that maize biomass significantly increased under the tested CSA practices in the study area. Use of permanent planting basins relatively increased maize grain yield (11–66%) and water use efficiency (33–94%) compared to the conventional practice. Additionally, plots treated with mulch achieved an increase in grain yield (18–65%) and WUE (28–85%) relative to the control. Soil amendment with M_4 cm and M_6 cm significantly increased soil moisture storage compared to permanent planting basins and the conventional practice. Overall, the results highlight the positive impact of CSA practices on improving maize yield and water use efficiency in rainfed agriculture production systems which dominate the sub-humid regions. [ABSTRACT FROM AUTHOR]

Climate change continues to affect maize production, food security and livelihoods of smallholder farmers in most of the developing countries. Climate smart agriculture (CSA) practices can enhance agricultural production by alleviating adverse climate effects on maize productivity through improved soil moisture storage, water use efficiency, increased soil carbon (C) and nutrient supply with long-term resilience to climate change. This study investigated the effectiveness of CSA practices (mulching at 0, 2, 4 and 6 cm thicknesses), permanent planting basins (20 and 30 cm deep), and halfmoon pits as a mitigation and adaptation strategy for improving maize productivity in rainfed production systems in the sub-humid regions of Sub-Saharan Africa. We used the AquaCrop model of the Food and Agriculture Organization (FAO, 2018), AquaCrop version 6.1 to evaluate potential benefits of the CSA practices: half-moon, mulching (using different thickness) and permanent planting basins compared to a control treatment in rainfed production systems. The performance of CSA practices was evaluated using field experiments under present and future conditions. We first parameterized the model based on a three-season field experiment (2019-2020). We then run the model under projected future trends (2010–2039) using four general circulation models in each two greenhouse gas (GHG) emission representation concentration pathways (RCP4.5 and RCP8.5) for the Coupled Model Inter-comparison Project 5 (CMIP5). Finally, we evaluated resulting maize growth, grain yield, and water use efficiency for all the treatments. Our results indicated that use of mulching, especially 6 cm thick mulch increased maize grain yield and water use efficiency under present and future conditions. It was noted that CSA practices would increase grain yield by 14–37% under RCP8.5 climate scenario. Projections revealed increases in mean temperature of 0.5 °C and 1.0 °C under RCP4.5 and RCP8.5, respectively, in the 30 years (2010–2039). The model also projected a decrease (4.7%) and increase (2%) of the annual averages of rainfall in the future under RCP4.5 and RCP8.5, respectively. Our findings highlight the key role of CSA practices in reducing the climate change effects on maize production in the sub-humid regions. Therefore, national governments should prioritize adoption of climate smart agriculture practices as a key strategy for improving and sustaining maize productivity in rainfed systems of the sub-humid region. [Display omitted] • In Uganda, temperatures are projected to increase by 0.5-1.0 ºC while rainfall will decrease from 2010-2039. • The impacts of climate smart agriculture (CSA) on maize productivity under changing climate were evaluated and projected. • AquaCrop model projections indicate that CSA will increase maize grain yield by 14-37% in rainfed production systems. • Mulching and permanent planting basins were the most effective for improved maize yield and water use efficiency. [ABSTRACT FROM AUTHOR]

Biogeochemical models of vegetation dynamics could potentially be used to complement empirical studies on the effect of plant species richness. A key precondition is the simulation of species coexistence. While community scale models regularly incorporate respective processes, models at the field or landscape scale used for larger scale assessments, require additional model development. However, it is unclear how the particular process description within these models affects simulations of species performance and resulting ecosystem functions. We compare simulations of two grassland models of different complexity for monocultures and two-species mixtures in a grassland experiment in Jena, Germany. By providing an in-depth analysis of the models' process descriptions, we evaluate their ability to simulate the response of different species, their interactions and their joint performance to drought and mowing. Both models simulated similar average above-ground biomass (AGB) but showed different intra-annual variability. Generally, the models had difficulties representing a balanced species composition in multiple species mixtures and competition for space was the main driver of community composition in both models. The resulting communities were dominated by the more competitive species, while the weak competitor was only marginally present in most mixtures independent of drought and mowing. The competitive strength which we derived from the calibrated parameter sets of the species differed between the models and the agreement on which species dominate specific mixtures was mixed. While both models simulated reduced soil water content and above-ground biomass in response to drought, the strength and duration of these responses differed. Despite these differences, simulated species interactions were barely affected, and strong competitors remained dominant. Mowing had opposing effects on the competition for space in the models, which could be attributed to the different representations of plants in the two models. The models selected for the comparison are two representatives for local- and large-scale applications and use widely applied approaches for which our comparison highlighted strengths and weaknesses. To enable the investigated models (and those with similar complexity) to simulate coexistence of multiple species, niche differentiation needs to be improved. This requires a stricter separation of access to different resources and improved representation of different ecological strategies for which community scale models that are able to simulate coexistence may be an inspiration. Our approach may serve as an example for other modellers looking for ways to identify important model processes for further model development in the context of species interaction. • The model comparison showed similar biomass (AGB) with different seasonal patterns. • Competition for space was the main driver of species interaction. • Assessed grassland models have deficiencies in simulating stable coexistence. • To improve niche differentiation, incorporation of below-ground traits is needed. • Approaches from community scale models could inspire models at larger scales. [ABSTRACT FROM AUTHOR]