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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]

Earth’s life-support systems are in rapid decline, yet we have few metrics or indicators with which to track these changes. The world’s governments are calling for biodiversity and ecosystem-service monitoring to guide and evaluate international conservation policy as well as to incorporate natural capital into their national accounts. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has been tasked with setting up this monitoring system. Here we explore the immediate feasibility of creating a global ecosystem-service monitoring platform under the GEO BON framework through combining data from national statistics, global vegetation models, and production function models. We found that nine ecosystem services could be annually reported at a national scale in the short term: carbon sequestration, water supply for hydropower, and non-fisheries marine products, crop, livestock, game meat, fisheries, mariculture, and timber production. Reported changes in service delivery over time reflected ecological shocks (e.g., droughts and disease outbreaks), highlighting the immediate utility of this monitoring system. Our work also identified three opportunities for creating a more comprehensive monitoring system. First, investing in input data for ecological process models (e.g., global land-use maps) would allow many more regulating services to be monitored. Currently, only 1 of 9 services that can be reported is a regulating service. Second, household surveys and censuses could help evaluate how nature affects people and provides non-monetary benefits. Finally, to forecast the sustainability of service delivery, research efforts could focus on calculating the total remaining biophysical stocks of provisioning services. Regardless, we demonstrated that a preliminary ecosystem-service monitoring platform is immediately feasible. With sufficient international investment, the platform could evolve further into a much-needed system to track changes in our planet's life-support systems. [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]

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]

The ecosystem-based management (EBM) philosophy draws upon the principle that holistic understanding of the system to be governed needs to guide the decision-making process. However, empirical evidence is growing that knowledge integration is still a main bottleneck for EBM decision-makers. This paper argues that transdisciplinary knowledge management (TKM) is a key competence in achieving knowledge integration, while simultaneously it represents an underdeveloped research area in EBM if understood as a process of human interaction. Based on a literature review, this article summarizes and reflects upon the most recent development in the field of TKM. The paper presents a detailed definition and in-depth description of TKM as a process of human interaction and a diversity of organizational structures that effectuate TKM. Theoretically discussed premises are furthermore illuminated and evaluated by a case study that exemplifies pro-active development and implementation of TKM. Deviating case observations are presented as novel contributions to the field. They suggest new ideas and inspiration for future EBM research and policy agendas. [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]

• Plant diversity and productivity are involved in explaining δ15N plant , δ15N soil, and δ15N soil-to-plant in North Tibet. • Precipitation is critical for driving spatial variability of δ15N plant , δ15N soil and δ15N soil-to-plant in North Tibet. • The δ15N plant and δ15N soil-to-plant indicate growth limitation shifts from P in meadows to N in desert-steppes. Nitrogen (N) cycling is a critical pathway by which producer, consumer, and decomposer interact with each other and with environmental circumstances simultaneously. The natural abundance composition of 15N/14N in plants and soils (termed as δ15N plant and δ15N soil), as well as the difference between them (δ15N soil-to-plant = δ15N plant −δ15N soil), is a useful tool for better understanding ecosystem N cycling. However, the drivers and mechanisms of ecosystem N cycling in alpine grasslands on the Tibetan Plateau are mostly unknown, especially across different grassland types at a regional scale. To fill this knowledge gap, we measured δ15N plant (200 samples of top-dominant species) and δ15N soil (85 samples of top-layer soils, 0–20 cm) at nine sites that represent zonal communities of alpine deserts, steppes, and meadows in North Tibet, and calculated the corresponding δ15N soil-to-plant. Our results showed that δ15N plant, δ15N soil, and δ15N soil-to-plant were significantly different among the three zonal grassland types (analysis of differences with non-parametric Kruskal Test, P < 0.05), with the lowest values in meadows and the highest values in deserts. Regression analyses showed that the δ15N plant , δ15N soil, and δ15N soil-to-plant decreased with the increases of growing season precipitation (GSP) and habitat aridity index (Aridity), soil organic carbon (SOC) and soil total nitrogen (STN), plant species richness, Shannon diversity index, and plant community productivity, whereas increased with the increases of accumulated active temperature (AccT) and soil total phosphorus (STP) across alpine grassland types at the regional scale. Multiple linear models with analysis of covariance (ANCOVA) confirmed GSP to be the most critical driver, which alone explained most variances of δ15N plant (56%), δ15N soil (62%), and δ15N soil-to-plant (35%). However, structural equation modeling performed better than multiple linear modeling in predicting δ15N plant (76% vs. 66%) and worse in predicting δ15N soil (79% vs. 84%) and δ15N soil-to-plant (31% vs. 46%), likely due to the exclusion of collinear predictors and the removal of non-significant influencing paths. Overall, this study has highlighted the importance to uncover the complexity of climate, soil nutrients, and vegetation properties in networking to drive the different components of ecosystem N cycling in alpine grasslands on the Tibetan Plateau. [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]

(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]