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In the Central German Uplands, Fagus sylvatica and Picea abies have been particularly affected by climate change. With the establishment of beech forests about 3000 years ago and pure spruce stands 500 years ago, they might be regarded as ‘neophytes’ in the Hessian forests. Palaeoecological investigations at wetland sites in the low mountain ranges and intramontane basins point to an asynchronous vegetation evolution in a comparatively small but heterogenous region. On the other hand, palynological data prove that sustainably managed woodlands with high proportions of Tilia have been persisting for several millennia, before the spread of beech took place as a result of a cooler and wetter climate and changes in land management. In view of increasingly warmer and drier conditions, Tilia cordata appears especially qualified to be an important silvicultural constituent of the future, not only due to its tolerance towards drought, but also its resistance to browsing, and the ability to reproduce vegetatively. Forest managers should be encouraged to actively promote the return to more stress-tolerant lime-dominated woodlands, similar to those that existed in the Subboreal chronozone.
Wetlands such as bogs, swamps, or freshwater marshes are hotspots of biodiversity. For 5.1 million km2 of inland wetlands, the dynamics of area and water storage, which strongly impact biodiversity and ecosystem services, were simulated using the global hydrological model WaterGAP. For the first time, the impacts of both human water use and man‐made reservoirs (WUR) and future climate change (CC) on wetlands around the globe were quantified. WUR impacts are concentrated in arid/semiarid regions, where WUR decreased mean wetland water storage by more than 5% on 8.2% of the mean wetland area during 1986–2005 (Am), with highest decreases in groundwater depletion area. Using output of three climate models, CC impacts on wetlands were quantified, distinguishing unavoidable impacts [i.e., at 2 °C global warming (GW)] from avoidable impacts (difference between 3 °C and 2 °C impacts). Even unavoidable CC impacts are projected to be much larger than WUR impacts, also in arid/semiarid regions. On most wetland area with reliable estimates, avoidable CC impacts are more than twice as large as unavoidable impacts. In case of 2 °C GW, half of Am is estimated to be unaffected by mean storage changes of more than 5%, but only one third in case of 3 °C GW. Temporal variability of water storage will increase for most wetlands. Wetlands in dry regions will be affected the most, particularly by water storage decreases in the dry season. Different from wealthier countries, low‐income countries will dominantly suffer from a decrease in wetland water storage due to CC.
Anthropogenic climate change is expected to impact ecosystem structure, biodiversity and ecosystem services in Africa profoundly. We used the adaptive Dynamic Global Vegetation Model (aDGVM), which was originally developed and tested for Africa, to quantify sources of uncertainties in simulated African potential natural vegetation towards the end of the 21st century. We forced the aDGVM with regionally downscaled high‐resolution climate scenarios based on an ensemble of six general circulation models (GCMs) under two representative concentration pathways (RCPs 4.5 and 8.5). Our study assessed the direct effects of climate change and elevated CO2 on vegetation change and its plant‐physiological drivers. Total increase in carbon in aboveground biomass in Africa until the end of the century was between 18% to 43% (RCP4.5) and 37% to 61% (RCP8.5) and was associated with woody encroachment into grasslands and increased woody cover in savannas. When direct effects of CO2 on plants were omitted, woody encroachment was muted and carbon in aboveground vegetation changed between –8 to 11% (RCP 4.5) and –22 to –6% (RCP8.5). Simulated biome changes lacked consistent large‐scale geographical patterns of change across scenarios. In Ethiopia and the Sahara/Sahel transition zone, the biome changes forecast by the aDGVM were consistent across GCMs and RCPs. Direct effects from elevated CO2 were associated with substantial increases in water use efficiency, primarily driven by photosynthesis enhancement, which may relieve soil moisture limitations to plant productivity. At the ecosystem level, interactions between fire and woody plant demography further promoted woody encroachment. We conclude that substantial future biome changes due to climate and CO2 changes are likely across Africa. Because of the large uncertainties in future projections, adaptation strategies must be highly flexible. Focused research on CO2 effects, and improved model representations of these effects will be necessary to reduce these uncertainties.
Increases in water demand often result in unsustainable water use, leaving insufficient amounts of water for the environment. Therefore, water-saving strategies have been introduced to the environmental policy agenda in many (semi)-arid regions. As many such interventions failed to reach their objectives, a comprehensive tool is needed to assess them. We introduced a constructive framework to assess the proposed strategies by estimating five key components of the water balance in an area: (1) Demand; (2) Availability; (3) Withdrawal; (4) Depletion and (5) Outflow. The framework was applied to assess the Urmia Lake Restoration Program (ULRP) which aimed to increase the basin outflow to the lake to reach 3.1 × 109 m3 yr−1. Results suggested that ULRP could help to increase the Outflow by up to 57%. However, successful implementation of the ULRP was foreseen to be impeded because of three main reasons: (i) decreasing return flows; (ii) increased Depletion; (iii) the impact of climate change. Decreasing return flows and increasing Depletion were expected due to the introduction of technologies that increase irrigation efficiency, while climate change could decrease future water availability by an estimated 3–15%. We suggest that to reach the intervention target, strategies need to focus on reducing water depletion rather than water withdrawals. The framework can be used to comprehensively assess water-saving strategies, particularly in water-stressed basins.
Aim: Predicting future changes in species richness in response to climate change is one of the key challenges in biogeography and conservation ecology. Stacked species distribution models (S‐SDMs) are a commonly used tool to predict current and future species richness. Macroecological models (MEMs), regression models with species richness as response variable, are a less computationally intensive alternative to S‐SDMs. Here, we aim to compare the results of two model types (S‐SDMS and MEMs), for the first time for more than 14,000 species across multiple taxa globally, and to trace the uncertainty in future predictions back to the input data and modelling approach used.
Location: Global land, excluding Antarctica.
Taxon: Amphibians, birds and mammals.
Methods: We fitted S‐SDMs and MEMs using a consistent set of bioclimatic variables and model algorithms and conducted species richness predictions under current and future conditions. For the latter, we used four general circulation models (GCMs) under two representative concentration pathways (RCP2.6 and RCP6.0). Predicted species richness was compared between S‐SDMs and MEMs and for current conditions also to extent‐of‐occurrence (EOO) species richness patterns. For future predictions, we quantified the variance in predicted species richness patterns explained by the choice of model type, model algorithm and GCM using hierarchical cluster analysis and variance partitioning.
Results: Under current conditions, species richness predictions from MEMs and S‐SDMs were strongly correlated with EOO‐based species richness. However, both model types over‐predicted areas with low and under‐predicted areas with high species richness. Outputs from MEMs and S‐SDMs were also highly correlated among each other under current and future conditions. The variance between future predictions was mostly explained by model type.
Main conclusions: Both model types were able to reproduce EOO‐based patterns in global terrestrial vertebrate richness, but produce less collinear predictions of future species richness. Model type by far contributes to most of the variation in the different future species richness predictions, indicating that the two model types should not be used interchangeably. Nevertheless, both model types have their justification, as MEMs can also include species with a restricted range, whereas S‐SDMs are useful for looking at potential species‐specific responses.
Vegetation responds to drought through a complex interplay of plant hydraulic mechanisms, posing challenges for model development and parameterization. We present a mathematical model that describes the dynamics of leaf water-potential over time while considering different strategies by which plant species regulate their water-potentials. The model has two parameters: the parameter λ describing the adjustment of the leaf water potential to changes in soil water potential, and the parameter Δψww describing the typical ‘well-watered’ leaf water potentials at non-stressed (near-zero) levels of soil water potential. Our model was tested and calibrated on 110 time-series datasets containing the leaf- and soil water potentials of 66 species under drought and non-drought conditions. Our model successfully reproduces the measured leaf water potentials over time based on three different regulation strategies under drought. We found that three parameter sets derived from the measurement data reproduced the dynamics of 53% of an drought dataset, and 52% of a control dataset [root mean square error (RMSE) < 0.5 MPa)]. We conclude that, instead of quantifying water-potential-regulation of different plant species by complex modeling approaches, a small set of parameters may be sufficient to describe the water potential regulation behavior for large-scale modeling. Thus, our approach paves the way for a parsimonious representation of the full spectrum of plant hydraulic responses to drought in dynamic vegetation models.
The abiotic and biotic drivers of rapid diversification in Andean bellflowers (Campanulaceae)
(2016)
The tropical Andes of South America, the world's richest biodiversity hotspot, are home to many rapid radiations. While geological, climatic, and ecological processes collectively explain such radiations, their relative contributions are seldom examined within a single clade. We explore the contribution of these factors by applying a series of diversification models that incorporate mountain building, climate change, and trait evolution to the first dated phylogeny of Andean bellflowers (Campanulaceae: Lobelioideae). Our framework is novel for its direct incorporation of geological data on Andean uplift into a macroevolutionary model. We show that speciation and extinction are differentially influenced by abiotic factors: speciation rates rose concurrently with Andean elevation, while extinction rates decreased during global cooling. Pollination syndrome and fruit type, both biotic traits known to facilitate mutualisms, played an additional role in driving diversification. These abiotic and biotic factors resulted in one of the fastest radiations reported to date: the centropogonids, whose 550 species arose in the last 5 million yr. Our study represents a significant advance in our understanding of plant evolution in Andean cloud forests. It further highlights the power of combining phylogenetic and Earth science models to explore the interplay of geology, climate, and ecology in generating the world's biodiversity.
The Earth's future depends on how we manage the manifold risks of climate change (CC). It is state-of-the-art to assume that risk reduction requires participatory management involving a broad range of stakeholders and scientists. However, there is still little knowledge about the optimal design of participatory climate change risk management processes (PRMPs), in particular with respect to considering the multitude of substantial uncertainties that are relevant for PRMPs. To support the many local to regional PRMPs that are necessary for a successful global-scale reduction of CC risks, we present a roadmap for designing such transdisciplinary knowledge integration processes. The roadmap suggests ways in which uncertainties can be comprehensively addressed within a PRMP. We discuss the concept of CC risks and their management and propose an uncertainty framework that distinguishes epistemic, ontological, and linguistic uncertainty as well as ambiguity. Uncertainties relevant for CC risk management are identified. Communicative and modeling methods that support social learning as well as the development of risk management strategies are proposed for each of six phases of a PRMP. Finally, we recommend how to evaluate PRMPs as such evaluations and their publication are paramount for achieving a reduction of CC risks.
The design of rainwater harvesting based gardens requires considering current climate but also climate change during the lifespan of the facility. The goal of this study is to present an approach for designing garden variants that can be safely supplied with harvested rainwater, taking into account climate change and adaptation measures. In addition, the study presents a methodology to quantify the effects of climate change on rainwater harvesting based gardening. Results of the study may not be accurate due to the assumptions made for climate projections and may need to be further refined. We used a tank flow model and an irrigation water model. Then we established three simple climate scenarios and analyzed the impact of climate change on harvested rain and horticulture production for a semi-arid region in northern Namibia. In the two climate scenarios with decreased precipitation and medium/high temperature increase; adaptation measures are required to avoid substantial decreases in horticulture production. The study found that the most promising adaptation measures to sustain yields and revenues are a more water efficient garden variant and an enlargement of the roof size. The proposed measures can partly or completely compensate the negative impacts of climate change.
Reduction of greenhouse gas (GHG) emissions to minimize climate change requires very significant societal effort. To motivate this effort, it is important to clarify the benefits of avoided emissions. To this end, we analysed the impact of four emissions scenarios on future renewable groundwater resources, which range from 1600 GtCO2 during the 21st century (RCP2.6) to 7300 GtCO2 (RCP8.5). Climate modelling uncertainty was taken into account by applying the bias-corrected output of a small ensemble of five CMIP5 global climate models (GCM) as provided by the ISI-MIP effort to the global hydrological model WaterGAP. Despite significant climate model uncertainty, the benefits of avoided emissions with respect to renewable groundwater resources (i.e. groundwater recharge (GWR)) are obvious. The percentage of projected global population (SSP2 population scenario) suffering from a significant decrease of GWR of more than 10% by the 2080s as compared to 1971–2000 decreases from 38% (GCM range 27–50%) for RCP8.5 to 24% (11–39%) for RCP2.6. The population fraction that is spared from any significant GWR change would increase from 29% to 47% if emissions were restricted to RCP2.6. Increases of GWR are more likely to occur in areas with below average population density, while GWR decreases of more than 30% affect especially (semi)arid regions, across all GCMs. Considering change of renewable groundwater resources as a function of mean global temperature (GMT) rise, the land area that is affected by GWR decreases of more than 30% and 70% increases linearly with global warming from 0 to 3 ° C. For each degree of GMT rise, an additional 4% of the global land area (except Greenland and Antarctica) is affected by a GWR decrease of more than 30%, and an additional 1% is affected by a decrease of more than 70%.