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Grassland biodiversity is vulnerable to land use change. How to best manage semi-natural grasslands for maintaining biodiversity is still unclear in many cases because land-use processes may depend on environmental conditions and the indirect effects of land-use on biodiversity mediated by altered abiotic and biotic factors are rarely considered. Here we evaluate the relative importance of the direct and indirect effects of grazing intensity on plant communities along an elevational gradient on a large topographic scale in the Eastern Carpathians in Ukraine. We sampled for two years 31 semi-natural grasslands exposed to cattle grazing. Within each grassland site we measured plant community properties such as the number of species, functional groups, and the proportion of species undesirable for grazing. In addition, we recorded cattle density (as a proxy for grazing intensity), soil properties (bare soil exposure, soil organic carbon, and soil pH) and densities of soil decomposers (earthworms and soil microorganisms). We used structural equation modelling to explore the direct and indirect effects of grazing intensity on plant communities along the elevation gradient. We found that cattle density decreased plant species and functional diversity but increased the proportion of undesirable species. Some of these effects were directly linked to grazing intensity (i.e., species richness), while others (i.e., functional diversity and proportion of undesirable species) were mediated via bare soil exposure. Although grazing intensity decreased with elevation, the effects of grazing on the plant community did not change along the elevation gradient. Generally, elevation had a strong positive direct effect on plant species richness as well as a negative indirect effect, mediated via altered soil acidity and decreased decomposer density. Our results indicate that plant diversity and composition are controlled by the complex interplay among grazing intensity and changing environmental conditions along an elevation gradient. Furthermore, we found lower soil pH, organic carbon and decomposer density with elevation, indicating that the effects of grazing on soil and related ecosystem functions and services in semi-natural grasslands may be more pronounced with elevation. This demonstrates that we need to account for environmental gradients when attempting to generalize effects of land-use intensity on biodiversity. [ABSTRACT FROM AUTHOR]

Flower nectar is a sugar-rich ephemeral habitat for microorganisms. Nectar-borne yeasts are part of the microbial community and can affect pollination by changing nectar chemistry, attractiveness to pollinators or flower temperature if yeast population densities are high. Pollinators act as dispersal agents in this system; however, pollination events lead potentially to shrinking nectar yeast populations. We here examine how sufficiently high cell densities of nectar yeast can develop in a flower. In laboratory experiments, we determined the remaining fraction of nectar yeast cells after nectar removal, and used honeybees to determine the number of transmitted yeast cells from one flower to the next. The results of these experiments directly fed into a simulation model providing an insight into movement and colonization ecology of nectar yeasts. We found that cell densities only reached an ecologically relevant size for an intermediate pollination probability. Too few pollination events reduce yeast inoculation rate and too many reduce yeast population size strongly. In addition, nectar yeasts need a trait combination of at least an intermediate growth rate and an intermediate remaining fraction to compensate for highly frequent decimations. Our results can be used to predict nectar yeast dispersal, growth and consequently their ecological effects. [ABSTRACT FROM AUTHOR]

Water limited ecosystems such as savannas are characterized by strong interactions between water fluxes and vegetation. However, the fraction of mean annual rainfall that is transformed into plant available water, is not only dependent on the prevailing vegetation cover, but also on abiotic factors such as soil texture and topography as well as intra-annual precipitation patterns. Most models projecting savanna vegetation cover dynamics have not accounted for these factors until now. Here, it is highlighted how and why spatial heterogeneity in water availability and vegetation cover is closely related to abiotic conditions. The role of soil texture, slope and precipitation patterns on water availability and emergent vegetation patterns are systematically tested by using the process-based, spatially explicit model EcoHyD. The analysis shows that the same overall precipitation will result in qualitatively different vegetation cover, depending on environmental conditions. This highlights that models of savanna systems should indeed resolve water dynamics and the feedbacks between water and vegetation with care. In addition the study discusses that future savanna models should go one step further and include phenotypic plasticity and demographic processes to better resolve individual plant responses towards water stress. [ABSTRACT FROM AUTHOR]

Our current understanding regarding the functioning of the savanna ecosystem describes savannas as either competition- or disturbance-dependent. Within this generalized view, the role and importance of facilitation have been mostly neglected. This study presents a mathematical model of savannas with coupled soil moisture–vegetation dynamics, which includes interspecific competition and environmental disturbance. We find that there exist environmental and climatic conditions where grass facilitation toward trees plays an important role in supporting tree cover and by extension preserving the savanna biome. We, therefore, argue that our theoretical results in combination with the first empirical studies on the subject should stimulate further research into the role of facilitation in the savanna ecosystem, particularly when analyzing the impact of past and projected climatic changes on it. [ABSTRACT FROM AUTHOR]

We analyzed relative sensitivities of small- and medium-sized carnivores to livestock husbandry (stocking rates and predator control) in Kalahari, South Africa, rangelands at a regional scale. We monitored small carnivores using track counts on 22 Kalahari farms across a land-use gradient ranging from low to high stocking rates and also interviewed each farm manager to identify farmers' perception of small carnivores as potential predators for livestock. We recorded 12 species of small- and medium-sized carnivores across 22 Kalahari farms. Stocking rate was the most important driving variable for local carnivore abundance. Abundance of all species was lowest on farms where stocking rate was high. Most farm managers perceived medium-sized carnivores, in particular, African wildcat (Felis silvestris lybica), blackbacked jackal (Canis mesomelas), and caracal (Caracal caracal ), as potential predators of livestock. Multiple regression analysis shows that blackbacked jackal, African wildcat, and caracal were negatively affected by predator control measures, whereas bat-eared fox (Otocyon megalotis), cape fox (Vulpes chama), and small-spotted genet (Genetta genetta) were positively affected. Our results show a need for expanding research and conservation activities toward small- and medium-sized carnivores in southern African savannah rangelands. We, therefore, suggest developing a monitoring program combining passive tracking with indigenous knowledge of local Khoisan Bushmen to monitor carnivore populations, and we recommend additional predator removal experiments that manipulate predator densities. [ABSTRACT FROM AUTHOR]

1. Sustainable land use under climate change requires detailed knowledge of the system dynamics. This applies particularly for the management of domestic livestock in semi-arid and arid grazing systems, where the risk of degradation is high and likely climate change may have a strong impact. A suitable way to assess potential future trends of these complex systems is through the application of simulation models. 2. We reviewed 41 models published between 1995 and 2005 simulating semi-arid and arid livestock grazing systems. The models were categorized according to the model aim and type, their temporal and spatial scale, and several indicators of model complexity. Additionally, we developed a list of model requirements for adequately simulating the effects of climate change. Based on these requirements, we evaluated the potential of current models to simulate impacts of climate change and determine important shortcomings. 3. Three general model types could be distinguished, namely state and transition, difference and differential equation, and rule-based models. Over time, we found that the number of models aiming to improve management strategies increased, while there were fewer models that aimed to understand system dynamics. This was accompanied by a trend to simplify model descriptions of hydrological relationships. 4. Important shortcomings of current models included the impact of increased CO2 levels on plant productivity and the ability to resolve changes in intra-annual precipitation patterns. The consideration of both external drivers is crucial under climate change, hence sustainable long-term decision making is currently lacking important information. 5. Synthesis and applications. Sustainable livestock management in semi-arid and arid systems requires knowledge about effects of future climate change to adjust livestock density adequately. Producers’ experiences from current weather conditions are not necessarily transferable to future conditions, thus models could help to support management. However, an analysis of current models has shown that few existing models are able to assess the impacts of the predicted climate change. Therefore, we call for the development of new dynamic grazing models that provide land managers with the necessary tools to face the threat of future climate changes. [ABSTRACT FROM AUTHOR]

Abstract: The overuse of rainforests in the last century and its consequences necessitate a rethinking of logging policies. To this end models have been developed to simulate rainforest dynamics and to allow optional management strategies to be evaluated. Parameterisation of presently existing models for a certain site needs a lot of work, thus the parameterisation effort is too high to apply the models to a wide range of rainforests. Hence, in this paper we introduce the simplified model FORREG using the knowledge we have gained from a more complex model, FORMIX3-Q. The FORREG model uses differential equations to determine the volume growth of three successional species groups. Parameterisation is simplified by a genetic algorithm, which determines the required internal model parameters from characteristics of the forest dynamics. The new model is employed to assess the sustainability of various logging policies in terms of yield and damage. Results for three forests are discussed: (1) the tropical lowland rain forest in the Deramakot Forest Reserve, (2) the Lambir National Park in Malaysia and (3) a subtropical forest in Paraguay. Our model reproduces both undisturbed forest dynamics and dynamics of logged forests simulated with FORMIX3-Q very well. However, the resultant volumes of yield and damage differ slightly from those gained by FORMIX3-Q if short logging cycles are simulated. Choosing longer logging cycles leads to a good correspondence of both models. For the Deramakot Forest Reserve different logging cycles are compared and discussed. [Copyright &y& Elsevier]

Organisms are prone to different stressors and have evolved various defense mechanisms. One such defense mechanism is priming, where a mild preceding stress prepares the organism toward an improved stress response. This improved response can strongly vary, and primed organisms have been found to respond with one of three response strategies: a shorter delay to stress, a faster buildup of their response or a more intense response. However, a universal comparative assessment, which response is superior under a given environmental setting, is missing. We investigate the benefits of the three improved responses for microorganisms with an ordinary differential equation model, simulating the impact of an external stress on a microbial population that is either naïve or primed. We systematically assess the resulting population performance for different costs associated with priming and stress conditions. Our results show that independent of stress type and priming costs, the stronger primed response is most beneficial for longer stress phases, while the faster and earlier responses increase population performance and survival probability under short stresses. Competition increases priming benefits and promotes the early stress response. This dependence on the ecological context highlights the importance of including primed response strategies into microbial stress ecology. [ABSTRACT FROM AUTHOR]

Abstract: A global ecological restoration agenda has led to ambitious programs in environmental policy to mitigate declines in biodiversity and ecosystem services. Current restoration programs can incompletely return desired ecosystem service levels, while resilience of restored ecosystems to future threats is unknown. It is therefore essential to advance understanding and better utilize knowledge from ecological literature in restoration approaches. We identified an incomplete linkage between global change ecology, ecosystem function research, and restoration ecology. This gap impedes a full understanding of the interactive effects of changing environmental factors on the long‐term provision of ecosystem functions and a quantification of trade‐offs and synergies among multiple services. Approaches that account for the effects of multiple changing factors on the composition of plant traits and their direct and indirect impact on the provision of ecosystem functions and services can close this gap. However, studies on this multilayered relationship are currently missing. We therefore propose an integrated restoration agenda complementing trait‐based empirical studies with simulation modeling. We introduce an ongoing case study to demonstrate how this framework could allow systematic assessment of the impacts of interacting environmental factors on long‐term service provisioning. Our proposed agenda will benefit restoration programs by suggesting plant species compositions with specific traits that maximize the supply of multiple ecosystem services in the long term. Once the suggested compositions have been implemented in actual restoration projects, these assemblages should be monitored to assess whether they are resilient as well as to improve model parameterization. Additionally, the integration of empirical and simulation modeling research can improve global outcomes by raising the awareness of which restoration goals can be achieved, due to the quantification of trade‐offs and synergies among ecosystem services under a wide range of environmental conditions. [ABSTRACT FROM AUTHOR]

Vegetation productivity is an essential variable in ecosystem functioning. Vegetation dynamics of dryland ecosystems are most strongly determined by water availability and consequently by rainfall and there is a need to better understand how water limited ecosystems respond to altered rainfall amounts and variability. This response is partly determined by the vegetation functional response to rainfall (β) approximated by the unit change in annual vegetation productivity per unit change in annual rainfall. Here, we show how this functional response from 1983 to 2011 is affected by below and above average rainfall in two arid to semi-arid subtropical regions in West Africa (WA) and South West Africa (SWA) differing in interannual variability of annual rainfall (higher in SWA, lower in WA). We used a novel approach, shifting linear regression models (SLRs), to estimate gridded time series of β. The SLRs ingest annual satellite based rainfall as the explanatory variable and annual satellite-derived vegetation productivity proxies (NDVI) as the response variable. Gridded β values form unimodal curves along gradients of mean annual precipitation in both regions. β is higher in SWA during periods of below average rainfall (compared to above average) for mean annual precipitation <600 mm. In WA, β is hardly affected by above or below average rainfall conditions. Results suggest that this higher β variability in SWA is related to the higher rainfall variability in this region. Vegetation type-specific β follows observed responses for each region along rainfall gradients leading to region-specific responses for each vegetation type. We conclude that higher interannual rainfall variability might favour a more dynamic vegetation response to rainfall. This in turn may enhance the capability of vegetation productivity of arid and semi-arid regions to better cope with periods of below average rainfall conditions. [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]

Microbes in nature are exposed to complex environmental stressors which challenge their functioning or survival. Priming is the improved reaction of an organism to an environmental stressor following a preceding, often milder stress event. This phenomenon, also known as cross-protection, predictive response strategy or acquired stress resistance, is becoming an increasingly well-established research topic in microbiology, which has so far been examined from the perspective of a single organism or population. However, microbes in nature occur as part of communities; thus it is timely to highlight the need to also include this level beyond the individual species in studies of priming effects. We here introduce a conceptual framework for such studies at the level of the microbial assemblage and also chart a way forward for empirical and theoretical study. We illustrate some of the elements of our framework with a simple simulation model. Given the dynamic habitat of many microbes, incorporating priming is important for a more complete understanding of microbial community responses to stress. [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]

Morphological plasticity is a striking characteristic of plants in natural communities. In the context of foraging behavior particularly, root plasticity has been documented for numerous species. Root plasticity is known to mitigate competitive interactions by reducing the overlap of the individuals' rhizospheres. But despite its obvious effect on resource acquisition, plasticity has been generally neglected in previous empirical and theoretical studies estimating interaction intensity among plants. In this study, we developed a semi-mechanistic model that addresses this shortcoming by introducing the idea of compensatory growth into the classical-zone-of influence (ZOI) and field-of-neighborhood (FON) approaches. The model parameters describing the belowground plastic sphere of influence (PSI) were parameterized using data from an accompanying field experiment. Measurements of the uptake of a stable nutrient analogue at distinct distances to the neighboring plants showed that the study species responded plastically to belowground competition by avoiding overlap of individuals' rhizospheres. An unexpected finding was that the sphere of influence of the study species Bromus hordeaceus could be best described by a unimodal function of distance to the plant's center and not with a continuously decreasing function as commonly assumed. We employed the parameterized model to investigate the interplay between plasticity and two other important factors determining the intensity of competitive interactions: overall plant density and the distribution of individuals in space. The simulation results confirm that the reduction of competition intensity due to morphological plasticity strongly depends on the spatial structure of the competitive environment. We advocate the use of semi-mechanistic simulations that explicitly consider morphological plasticity to improve our mechanistic understanding of plant interactions. [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]

Aim: It is widely accepted that biodiversity is influenced by both niche-related and spatial processes from local to global scales. Their relative importance, however, is still disputed, and empirical tests are surprisingly scarce at the global scale. Here, we compare the importance of area (as a proxy for pure spatial processes) and environmental heterogeneity (as a proxy for niche-related processes) for predicting native mammal species richness world-wide and within biogeographical regions. Location: Global. Time period: We analyse a spatial snapshot of richness data collated by the International Union for Conservation of Nature. Major taxa studied: All terrestrial mammal species, including possibly extinct species and species with uncertain presence. Methods: We applied a spreading dye algorithm to analyse how native mammal species richness changes with area and environmental heterogeneity. As measures for environmental heterogeneity, we used elevation ranges and precipitation ranges, which are well-known correlates of species richness. Results: We found that environmental heterogeneity explained species richness relationships better than did area, suggesting that niche-related processes are more prevalent than pure area effects at broad scales. Main conclusions: Our results imply that niche-related processes are essential to understand broad-scale species--area relationships and that habitat diversity is more important than area alone for the protection of global biodiversity. [ABSTRACT FROM AUTHOR]

Manipulative experiments typically show a decrease in dryland biocrust cover and altered species composition under climate change. Biocrust‐forming lichens, such as the globally distributed Diploschistes diacapsis, are particularly affected and show a decrease in cover with simulated climate change. However, the underlying mechanisms are not fully understood, and long‐term interacting effects of different drivers are largely unknown due to the short‐term nature of the experimental studies conducted so far.We addressed this gap and successfully parameterised a process‐based model for D. diacapsis to quantify how changing atmospheric CO2, temperature, rainfall amount and relative humidity affect its photosynthetic activity and cover. We also mimicked a long‐term manipulative climate change experiment to understand the mechanisms underlying observed patterns in the field.The model reproduced observed experimental findings: warming reduced lichen cover, whereas less rainfall had no effect on lichen performance. This warming effect was caused by the associated decrease in relative humidity and non‐rainfall water inputs, which are major water sources for biocrust‐forming lichens. Warming alone, however, increased cover because higher temperatures promoted photosynthesis during early morning hours with high lichen activity. When combined, climate variables showed non‐additive effects on lichen cover, and effects of increased CO2 levelled off with decreasing levels of relative humidity.Synthesis. Our results show that a decrease in relative humidity, rather than an increase in temperature, may be the key factor for the survival of the lichen D. diacapsis under climate change and that effects of increased CO2 levels might be offset by a reduction in non‐rainfall water inputs in the future. Because of a global trend towards warmer and drier air and the widespread global distribution of D. diacapsis, this will affect lichen‐dominated dryland biocrust communities and their role in regulating ecosystem functions worldwide. [ABSTRACT FROM AUTHOR]

Leaf water potential regulation is a key process in whole plant and ecosystem functioning. While low water potentials induced by open stomata may initially be associated with greater CO2 supply and a higher water flux from the rhizosphere to the canopy, they also inhibit cell growth, photosynthesis and ultimately water supply. Here, we show that plants regulate their leaf water potential in an optimal manner under given constraints using a simple leaf water status regulation model and data from a global dryland leaf water potential database. Model predictions agree strongly with observations across locations and species and are further supported by experimental data. Leaf water potentials non-linearly decline with soil water potential, underlining the shift from maximizing water supply to avoiding stress with declining water availability. Our results suggest that optimal regulation of the leaf water status under varying water supply and stress tolerance is a ubiquitous property of plants in drylands. The proposed model moreover provides a novel quantitative framework describing how plants respond to short- and long-term changes in water availability and may help elaborating models of plant and ecosystem functioning. [ABSTRACT FROM AUTHOR]

Abstract The biodiversity-productivity relationship is critical for better predicting ecosystem responses to climate change and human disturbance. However, it remains unclear about the effects of climate change, land use shifts, plant diversity, and their interactions on productivity partitioning above- and below-ground components in alpine grasslands on the Tibetan Plateau. To answer this question, we conducted field surveys at 33 grazed vs. fenced paired sites that are distributed across the alpine meadow, steppe, and desert-steppe zones on the northern Tibetan Plateau in early August of 2010–2013. Generalized additive models (GAMs) showed that aboveground net primary productivity (ANPP) linearly increased with growing season precipitation (GSP) while belowground net primary productivity (BNPP) decreased with growing season temperature (GST). Compared to grazed sites, short-term fencing did not alter the patterns of ANPP along climatic gradients but tended to decrease BNPP at moderate precipitation levels of 200 mm < GSP <450 mm. We also found that ANPP and BNPP linearly increased with species richness, ANPP decreased with Shannon diversity index, and BNPP did not correlate with the Shannon diversity index. Fencing did not alter the relationships between productivity components and plant diversity indices. Generalized additive mixed models furtherly confirmed that the interaction of localized plant diversity and climatic condition nonlinearly regulated productivity partitioning of alpine grasslands in this area. Finally, structural equation models (SEMs) revealed the direction and strength of causal links between biotic and abiotic variables within alpine grassland ecosystems. ANPP was controlled directly by GSP (0.53) and indirectly via species richness (0.41) and Shannon index (−0.12). In contrast, BNPP was influenced directly by GST (−0.43) and indirectly by GSP via species richness (0.05) and Shannon index (−0.02). Therefore, we recommend using a joint approach of GAMs and SEMs for better understanding mechanisms behind the relationship between biodiversity and ecosystem function under climate change and human disturbance. Highlights • Fencing did not significantly alter the plant diversity-productivity partitioning relationship. • Plant diversity and climate are interacted to influence productivity partitioning nonlinearly. • Productivity partitioning is influenced directly by climate and indirectly via plant diversity. [ABSTRACT FROM AUTHOR]

Highlights • Seed and seedling availability of fire-killed plants decrease under drier climate. • Drier climate affects demographic stages (seeds, seedlings, adults) differently. • Fire-killed plant populations require longer inter-fire period to survive. • Mismatch between required longer and projected shorter fire intervals. Abstract Mediterranean-type ecosystems (MTEs) harbor an exceptionally high biodiversity of vascular plants. At the same time, climatic conditions in many MTE regions are projected to become both drier and hotter, and fire intervals shorter. The Interval Squeeze conceptual model integrates the potential effects of a changing climate and fire regimes on perennial plant population persistence and postulates that warmer, drier conditions will negatively affect multiple plant demographic processes. Dependent on species-specific traits, the required fire intervals that allow for population persistence might become longer, while projected future fire intervals are shorter, leading to a potential mismatch. However, conceptual models are per se not able to quantify outcomes of multiple stochastic processes or to simulate temporal dynamics. Here, we develop a simple, process-based model for a fire-sensitive woody plant species to evaluate the response of demographic processes to future climatic conditions and to quantify the potential impact also of future changes in fire interval. This allowed us to assess key assumptions of the interval squeeze model, particularly in relation to demographic drivers. We simulated populations of Banksia hookeriana , a typical fire-killed shrub found in MTEs of South-West Australia which stores its seeds in a canopy (serotinous) seedbank and shows strong cohort recruitment in the first year after fire. We estimated suitable fixed fire intervals for population persistence under historic climatic conditions and evaluated impacts of a higher dry year frequency (as projected under future climate by two representative concentration pathways, RCP4.5 and RCP8.5). Our findings support the Interval Squeeze Model: the fire interval allowing plant population persistence is squeezed from currently 10–28 years to 13–28 years for RCP4.5. For RCP8.5 population persistence is not possible under any of the tested fire intervals because of low seed production and low survival probability of both seedlings and adult plants. The results show that projected drier conditions alone will cause a higher extinction risk for fire-sensitive perennial plant populations in MTEs, which is further pronounced in combination with shorter fire intervals. This will likely lead to a strong shift in community composition and a loss of biodiversity. Fire management practices may need to be modified to attempt to counteract prospective biodiversity loss and ecosystem structure change. [ABSTRACT FROM AUTHOR]

The distribution of rainfed agriculture, which accounts for approximately ¾ of global croplands, is expected to respond to climate change and human population growth and these responses may be especially pronounced in water limited areas. Because the environmental conditions that support rainfed agriculture are determined by climate, weather, and soil conditions that affect overall and transient water availability, predicting this response has proven difficult, especially in temperate regions that support much of the world’s agriculture. Here, we show that suitability to support rainfed agriculture in temperate dryland climates can be effectively represented by just two daily environmental variables: moist soils with warm conditions increase suitability while extreme high temperatures decrease suitability. 21st century projections based on daily ecohydrological modeling of downscaled climate forecasts indicate overall increases in the area suitable for rainfed agriculture in temperate dryland regions, especially at high latitudes. The regional exception to this trend was Europe, where suitability in temperate dryland portions will decline substantially. These results clarify how rising temperatures interact with other key drivers of moisture availability to determine the sustainability of rainfed agriculture and help policymakers, resource managers, and the agriculture industry anticipate shifts in areas suitable for rainfed cultivation. [ABSTRACT FROM AUTHOR]

Fluxes of organic and inorganic carbon within the Amazon basin are considerably controlled by annual flooding, which triggers the export of terrigenous organic material to the river and ultimately to the Atlantic Ocean. The amount of carbon imported to the river and the further conversion, transport and export of it depend on temperature, atmospheric CO2, terrestrial productivity and carbon storage, as well as discharge. Both terrestrial productivity and discharge are influenced by climate and land use change. The coupled LPJmL and RivCM model system (Langerwisch et al., 2016) has been applied to assess the combined impacts of climate and land use change on the Amazon riverine carbon dynamics. Vegetation dynamics (in LPJmL) as well as export and conversion of terrigenous carbon to and within the river (RivCM) are included. The model system has been applied for the years 1901 to 2099 under two deforestation scenarios and with climate forcing of three SRES emission scenarios, each for five climate models. We find that high deforestation (business-as-usual scenario) will strongly decrease (locally by up to 90 %) riverine particulate and dissolved organic carbon amount until the end of the current century. At the same time, increase in discharge leaves net carbon transport during the first decades of the century roughly unchanged only if a sufficient area is still forested. After 2050 the amount of transported carbon will decrease drastically. In contrast to that, increased temperature and atmospheric CO2 concentration determine the amount of riverine inorganic carbon stored in the Amazon basin. Higher atmospheric CO2 concentrations increase riverine inorganic carbon amount by up to 20% (SRES A2). The changes in riverine carbon fluxes have direct effects on carbon export, either to the atmosphere via outgassing or to the Atlantic Ocean via discharge. The outgassed carbon will increase slightly in the Amazon basin, but can be regionally reduced by up to 60% due to deforestation. The discharge of organic carbon to the ocean will be reduced by about 40% under the most severe deforestation and climate change scenario. These changes would have local and regional consequences on the carbon balance and habitat characteristics in the Amazon basin itself as well as in the adjacent Atlantic Ocean. [ABSTRACT FROM AUTHOR]

(1) Ecohydrological models of savanna rangeland systems typically aggregate plant species to very broad plant functional types (PFTs), which are characterized by their trait combinations. However, neglecting trait variability within modelled PFTs may hamper our ability to understand the effects of climate or land use change on vegetation composition and thus on ecosystem processes. (2) In this study we extended and parameterized the ecohydrological savanna model EcoHyD, which originally considered only three broad PFTs (perennial grasses, annuals and shrubs). We defined several sub-types of perennial grasses (sub-PFTs) to assess the effect of environmental conditions on vegetation composition and ecosystem functioning. These perennial sub-PFTs are defined by altering distinct trait values based on a trade-off approach for (i) the longevity of plants and (ii) grazing-resistance. (3) We find that increasing grazing intensity leads to a dominance of the fast-growing and short-lived perennial grass type as well as a dominance of the poorly palatable grass type. Increasing precipitation dampens the magnitude of grazing-induced shifts between perennial grass types. The diversification of perennial grass PFTs generally increases the total perennial grass cover and ecosystem water use efficiency, but does not protect the community from shrub encroachment. (4) We thus demonstrate that including trait heterogeneity into ecosystem models will allow for an improved representation of ecosystem responses to environmental change in savannas. This will help to better assess how ecosystem functions might be impacted under future conditions. [ABSTRACT FROM AUTHOR]

Earth's life-support systems are in flux, yet no centralized system to monitor and report these changes exists. Recognizing this, 77 nations agreed to establish the Group on Earth Observations (GEO). The GEO Biodiversity Observation Network (GEO BON) integrates existing data streams into one platform in order to provide a more complete picture of Earth's biological and social systems. We present a conceptual framework envisioned by the GEO BON Ecosystem Services Working Group, designed to integrate national statistics, numerical models, remote sensing, and in situ measurements to regularly track changes in ecosystem services across the globe. This information will serve diverse applications, including stimulating new research and providing the basis for assessments. Although many ecosystem services are not currently measured, others are ripe for reporting. We propose a framework that will continue to grow and inspire more complete observation and assessments of our planet's life-support systems. [ABSTRACT FROM AUTHOR]

•Climate change will very likely affect most forests in Amazonia during the course of the 21st century, but the direction and intensity of the change are uncertain, in part because of differences in rainfall projections. In order to constrain this uncertainty, we estimate the probability for biomass change in Amazonia on the basis of rainfall projections that are weighted by climate model performance for current conditions. •We estimate the risk of forest dieback by using weighted rainfall projections from 24 general circulation models (GCMs) to create probability density functions (PDFs) for future forest biomass changes simulated by a dynamic vegetation model (LPJmL). •Our probabilistic assessment of biomass change suggests a likely shift towards increasing biomass compared with nonweighted results. Biomass estimates range between a gain of 6.2 and a loss of 2.7 kg carbon m−2 for the Amazon region, depending on the strength of CO2 fertilization. •The uncertainty associated with the long-term effect of CO2 is much larger than that associated with precipitation change. This underlines the importance of reducing uncertainties in the direct effects of CO2 on tropical ecosystems. [ABSTRACT FROM AUTHOR]

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future. • Generalized additive model revealed nonlinear climatic and anthropogenic impacts on ecosystems. • Climate change dominantly drove grassland productivity changes on the Qinghai-Tibetan Plateau. • Human impacts on grassland productivity on the Qinghai-Tibetan Plateau weakened in past decades. [ABSTRACT FROM AUTHOR]

The timing regimes of precipitation can exert profound impacts on grassland ecosystems. However, it is still unclear how the peak aboveground biomass (AGBpeak) of alpine grasslands responds to the temporal variability of growing season precipitation (GSP) on the northern Tibetan Plateau. Here, the temporal variability of precipitation was defined as the number and intensity of precipitation events as well as the time interval between consecutive precipitation events. We conducted annual field measurements of AGBpeak between 2009 and 2016 at four sites that were representative of alpine meadow, meadow-steppe, alpine steppe, and desert-steppe. Thus, an empirical model was established with the time series of the field-measured AGBpeak and the corresponding enhanced vegetation index (EVI) (R2 = 0.78), which was used to estimate grassland AGBpeak at the regional scale. The relative importance of the three indices of the temporal variability of precipitation, events, intensity, and time interval on grassland AGBpeak was quantified by principal component regression and shown in a red–green–blue (RGB) composition map. The standardized importance values were used to calculate the vegetation sensitivity index to the temporal variability of precipitation (VSIP). Our results showed that the standardized VSIP was larger than 60 for only 15% of alpine grassland pixels and that AGBpeak did not change significantly for more than 60% of alpine grassland pixels over the past decades, which was likely due to the nonsignificant changes in the temporal variability of precipitation in most pixels. However, a U-shaped relationship was found between VSIP and GSP across the four representative grassland types, indicating that the sensitivity of grassland AGBpeak to precipitation was dependent on the types of grassland communities. Moreover, we found that the temporal variability of precipitation explained more of the field-measured AGBpeak variance than did the total amount of precipitation alone at the site scale, which implies that the mechanisms underlying how the temporal variability of precipitation controls the AGBpeak of alpine grasslands should be better understood at the local scale. We hypothesize that alpine grassland plants promptly respond to the temporal variability of precipitation to keep community biomass production more stable over time, but this conclusion should be further tested. Finally, we call for a long-term experimental study that includes multiple natural and anthropogenic factors together, such as warming, nitrogen deposition, and grazing and fencing, to better understand the mechanisms of alpine grassland stability on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]