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Estimates of present and future extreme sub-hourly rainfall are derived from a daily spatial followed by a sub-daily temporal downscaling, the latter of which incorporates a novel, and crucial, temperature sensitivity. Specifically, daily global climate fields are spatially downscaled to local temperature T and precipitation P, which are then disaggregated to a temporal resolution of 10 min using a multiplicative random cascade model. The scheme is calibrated and validated with a group of 21 station records of 10-min resolution in Germany. The cascade model is used in the classical (denoted as MC) and in the new T-sensitive (MC+) version, which respects local Clausius-Clapeyron (CC) effects such as CC scaling. Extreme P is positively biased in both MC versions. Observed T sensitivity is absent in MC but well reproduced by MC+. Long-term positive trends in extreme sub-hourly P are generally more pronounced and more significant in MC+ than in MC. In units of 10-min rainfall, observed centennial trends in annual exceedance counts (EC) of P > 5 mm are +29% and in 3-yr return levels (RL) +27%. For the RCP4.5-simulated future, higher extremes are projected in both versions MC and MC+: per century, EC increases by 30% for MC and by 83% for MC+; the RL rises by 14% for MC and by 33% for MC+. Because the projected daily P trends are negligible, the sub-daily signal is mainly driven by local temperature.
Climate change will likely affect population dynamics of numerous plant species by modifying several aspects of the life cycle. Because plant regeneration from seeds may be particularly vulnerable, here we assess the possible effects of climate change on seed characteristics and present an integrated analysis of seven seed traits (nutrient concentrations, samara mass, seed mass, wing length, seed viability, germination percentage, and seedling biomass) of Acer platanoides and A. pseudoplatanus seeds collected along a wide latitudinal gradient from Italy to Norway. Seed traits were analyzed in relation to the environmental conditions experienced by the mother trees along the latitudinal gradient. We found that seed traits of A. platanoides were more influenced by the climatic conditions than those of A. pseudoplatanus. Additionally, seed viability, germination percentage, and seedling biomass of A. platanoides were strongly related to the seed mass and nutrient concentration. While A. platanoides seeds were more influenced by the environmental conditions (generally negatively affected by rising temperatures), compared to A. pseudoplatanus, A. platanoides still showed higher germination percentage and seedling biomass than A. pseudoplatanus. Thus, further research on subsequent life-history stages of both species is needed. The variation in seed quality observed along the climatic gradient highlights the importance of studying the possible impact of climate change on seed production and species demography.
Impacts of warming and changes in precipitation frequency on the regeneration of two Acer species
(2015)
Environmental change is likely to have a strong impact on biodiversity, and many species may shift their distribution in response. In this study, we aimed at projecting the availability of suitable habitat for an endangered amphibian species, the Fire-bellied toad Bombina bombina, in Brandenburg (north-eastern Germany). We modelled a potential habitat distribution map based on (1) a database with 10,581 presence records for Bombina from the years 1990 to 2009, (2) current estimates for ecogeographical variables (EGVs) and (3) the future projection of these EGVs according to the statistical regional model, respectively, the soil and water integrated model, applying the maximum entropy approach (Maxent). By comparing current and potential future distributions, we evaluated the projected change in distribution of suitable habitats and identified the environmental variables most associated with habitat suitability that turned out to be climatic variables related to the hydrological cycle. Under the applied scenario, our results indicate increasing habitat suitability in many areas and an extended range of suitable habitats. However, even if the environmental conditions in Brandenburg may change as predicted, it is questionable whether the Fire-bellied toad will truly benefit, as dispersal abilities of amphibian species are limited and strongly influenced by anthropogenic disturbances, that is, intensive agriculture, habitat destruction and fragmentation. Furthermore, agronomic pressure is likely to increase on productive areas with fertile soils and high water retention capacities, indeed those areas suitable for B. bombina. All these changes may affect temporary pond hydrology as well as the reproductive success and breeding phenology of toads.
East Africa hosts a striking diversity of terrestrial ecosystems, which vary both in space and time due to complex regional topography and a dynamic climate. The structure and functioning of these ecosystems under this environmental setting can be studied with dynamic vegetation models (DVMs) in a spatially explicit way. Yet, regional applications of DVMs to East Africa are rare and a comprehensive validation of such applications is missing. Here, we simulated the present-day and mid-Holocene vegetation of East Africa with the DVM, LPJ-GUESS and we conducted an exhaustive comparison of model outputs with maps of potential modern vegetation distribution, and with pollen records of local change through time. Overall, the model was able to reproduce the observed spatial patterns of East African vegetation. To see whether running the model at higher spatial resolutions (10′ × 10′) contribute to resolve the vegetation distribution better and have a better comparison scale with the observational data (i.e. pollen data), we run the model with coarser spatial resolution (0.5° × 0.5°) for the present-day as well. Both the area- and point-wise comparison showed that a higher spatial resolution allows to better describe spatial vegetation changes induced by the complex topography of East Africa. Our analysis of the difference between modelled mid-Holocene and modern-day vegetation showed that whether a biome shifts to another is best explained by both the amount of change in precipitation it experiences and the amount of precipitation it received originally. We also confirmed that tropical forest biomes were more sensitive to a decrease in precipitation compared to woodland and savanna biomes and that Holocene vegetation changes in East Africa were driven not only by changes in annual precipitation but also by changes in its seasonality.
The present-day vegetation in the tropics is mainly characterized by forests worldwide except in tropical East Africa, where forests only occur as patches at the coast and in the uplands. These forest patches result from the peculiar aridity that is linked to the uplift of the region during the Late Cenozoic. The Late Cenozoic vegetation history of East Africa is of particular interest as it has set the scene for the contemporary events in mammal and hominin evolution. In this study, we investigate the conditions under which these forest patches could have been connected, and a previous continuous forest belt could have extended and fragmented. We apply a dynamic vegetation model with a set of climatic scenarios in which we systematically alter the present-day environmental conditions such that they would be more favourable for a continuous forest belt in tropical East Africa. We consider varying environmental factors, namely temperature, precipitation and atmospheric CO2 concentrations. Our results show that all of these variables play a significant role in supporting the forest biomes and a continuous forest belt could have occurred under certain combinations of these settings. With our current knowledge of the palaeoenvironmental history of East Africa, it is likely that the region hosted these conditions during the Late Cenozoic. Recent improvements on environmental hypotheses of hominin evolution highlight the role of periods of short and extreme climate variability during the Late Cenozoic specific to East Africa in driving evolution. Our results elucidate how the forest biomes of East Africa can appear and disappear under fluctuating environmental conditions and demonstrate how this climate variability might be recognized on the biosphere level.
Jointly with the Global North, the rise of the Global South has come at a high cost to the environment. Driven by its high energy intensity and the use of fossil fuels, the South has contributed a significant portion of global emissions during the last 30 years, and is now contributing some 63% of today's total GHG emissions (including land-use change and forestry). Similar to the Global North, the Global South's emissions are heavily concentrated: India and China alone account for some 60% and the top 10 countries for some 78% of the group's emissions, while some 120 countries account for only 22%. Without highlighting such differences, it makes little sense to use the term 'Global South'. Its members are affected differently, and contribute differently to global climate change. They neither share a common view, nor do they pursue joint interests when it comes to international climate negotiations. Instead, they are organised into more than a dozen subgroups of the global climate regime. There is no single climate strategy for the Global South, and climate action will differ enormously from country to country. Furthermore, just and equitable transitions may be particularly challenging for some countries.
This thesis describes the development and application of the impacts module of the ICLIPS model, a global integrated assessment model of climate change. The presentation of the technical aspects of this model component is preceded by a discussion of the sociopolitical context for model-based integrated assessments, which defines important requirements for the specification of the model. Integrated assessment of climate change comprises a broad range of scientific efforts to support the decision-making about objectives and measures for climate policy, whereby many different approaches have been followed to provide policy-relevant information about climate impacts. Major challenges in this context are the large diversity of the relevant spatial and temporal scales, the multifactorial causation of many climate impacts', considerable scientific uncertainties, and the ambiguity associated with unavoidable normative evaluations. A hierarchical framework is presented for structuring climate impact assessments that reflects the evolution of their practice and of the underlying theory. Integrated assessment models of climate change (IAMs) are scientific tools that contain simplified representations of the relevant components of the coupled society-climate system. The major decision-analytical frameworks for IAMs are evaluated according to their ability to address important aspects of the pertinent social decision problem. The guardrail approach is presented as an inverse' framework for climate change decision support, which aims to identify the whole set of policy strategies that are compatible with a set of normatively specified constraints (guardrails'). This approach combines, to a certain degree, the scientific rigour and objectivity typical of predictive approaches with the ability to consider virtually all decision options that is at the core of optimization approaches. The ICLIPS model is described as the first IAM that implements the guardrail approach. The representation of climate impacts is a key concern in any IAM. A review of existing IAMs reveals large differences in the coverage of impact sectors, in the choice of the impact numeraire(s), in the consideration of non-climatic developments, including purposeful adaptation, in the handling of uncertainty, and in the inclusion of singular events. IAMs based on an inverse approach impose specific requirements to the representation of climate impacts. This representation needs to combine a level of detail and reliability that is sufficient for the specification of impact guardrails with the conciseness and efficiency that allows for an exploration of the complete domain of plausible climate protection strategies. Large-scale singular events can often be represented by dynamic reduced-form models. This approach, however, is less appropriate for regular impacts where the determination of policy-relevant results generally needs to consider the heterogeneity of climatic, environmental, and socioeconomic factors at the local or regional scale. Climate impact response functions (CIRFs) are identified as the most suitable reduced-form representation of regular climate impacts in the ICLIPS model. A CIRF depicts the aggregated response of a climate-sensitive system or sector as simulated by a spatially explicit sectoral impact model for a representative subset of plausible futures. In the CIRFs presented here, global mean temperature and atmospheric CO2 concentration are used as predictors for global and regional impacts on natural vegetation, agricultural crop production, and water availability. Application of a pattern scaling technique makes it possible to consider the regional and seasonal patterns in the climate anomalies simulated by several general circulation models while ensuring the efficiency of the dynamic model components. Efforts to provide quantitative estimates of future climate impacts generally face a trade-off between the relevance of an indicator for stakeholders and the exactness with which it can be determined. A number of non-monetary aggregated impact indicators for the CIRFs is presented, which aim to strike the balance between these two conflicting goals while taking into account additional constraints of the ICLIPS modelling framework. Various types of impact diagrams are used for the visualization of CIRFs, each of which provides a different perspective on the impact result space. The sheer number of CIRFs computed for the ICLIPS model precludes their comprehensive presentation in this thesis. Selected results referring to changes in the distribution of biomes in different biogeographical regions, in the agricultural potential of various countries, and in the water availability in selected major catchments are discussed. The full set of CIRFs is accessible via the ICLIPS Impacts Tool, a graphical user interface that provides convenient access to more than 100,000 impact diagrams developed for the ICLIPS model. The technical aspects of the software are described as well as the accompanying database of CIRFs. The most important application of CIRFs is in inverse' mode, where they are used to translate impact guardrails into simultaneous constraints for variables from the optimizing ICLIPS climate-economy model. This translation is facilitated by algorithms for the computation of reachable climate domains and for the parameterized approximation of admissible climate windows derived from CIRFs. The comprehensive set of CIRFs, together with these algorithms, enables the ICLIPS model to flexibly explore sets of climate policy strategies that explicitly comply with impact guardrails specified in biophysical units. This feature is not found in any other intertemporally optimizing IAM. A guardrail analysis with the integrated ICLIPS model is described that applies selected CIRFs for ecosystem changes. So-called necessary carbon emission corridors' are determined for a default choice of normative constraints that limit global vegetation impacts as well as regional mitigation costs, and for systematic variations of these constraints. A brief discussion of recent developments in integrated assessment modelling of climate change connects the work presented here with related efforts.
Conservation actions need to account for global climate change and adapt to it. The body of the literature on adaptation options is growing rapidly, but their feasibility and current state of implementation are rarely assessed. We discussed the practicability of adaptation options with conservation managers analysing three fields of action: reducing the vulnerability of conservation management, reducing the vulnerability of conservation targets (i.e. biodiversity) and climate change mitigation. For all options, feasibility, current state of implementation and existing obstacles to implementation were analysed, using the Federal State of Brandenburg, Germany, as a case study. Practitioners considered a large number of options useful, most of which have already been implemented at least in part. Those options considered broadly implemented resemble mainly conventional measures of conservation without direct relation to climate change. Managers are facing several obstacles for adapting to climate change, including political reluctance to change, financial and staff shortages in conservation administrations and conflictive EU funding schemes in agriculture. A certain reluctance to act, due to the high degree of uncertainty with regard to climate change scenarios and impacts, is widespread. A lack of knowledge of appropriate methods such as adaptive management often inhibits the implementation of adaptation options in the field of planning and management. Based on the findings for Brandenburg, we generally conclude that it is necessary to focus in particular on options that help to reduce vulnerability of conservation management itself, i.e. those that enhance management effectiveness. For instance, adaptive and proactive risk management can be applied as a no-regrets option, independently from specific climate change scenarios or impacts, strengthening action under uncertainty.
The Southern Ocean ecosystem is characterized by extreme seasonal changes in environmental factors such as day length, sea ice extent and food availability. The key species Antarctic krill (Euphausia superba) has evolved metabolic and behavioural seasonal rhythms to cope with these seasonal changes. We investigate the switch between a physiological less active and active period for adult krill, a rhythm which seems to be controlled by internal biological clocks. These biological clocks can be synchronized by environmental triggers such as day length and food availability. They have evolved for particular environmental regimes to synchronize predictable seasonal environmental changes with important life cycle functions of the species. In a changing environment the time when krill is metabolically active and the time of peak food availability may not overlap if krill's seasonal activity is solely determined by photoperiod (day length). This is especially true for the Atlantic sector of the Southern Ocean where the spatio-temporal ice cover dynamics are changing substantially with rising average temperatures. We developed an individual-based model for krill to explore the impact of photoperiod and food availability on the growth and demographics of krill. We simulated dynamics of local krill populations (with no movement of krill assumed) along a south-north gradient for different triggers of metabolic activity and different levels of food availability below the ice. We also observed the fate of larval krill which cannot switch to low metabolism and therefore are likely to overwinter under ice. Krill could only occupy the southern end of the gradient, where algae bloom only lasts for a short time, when alternative food supply under the ice was high and metabolic activity was triggered by photoperiod. The northern distribution was limited by lack of overwintering habitat for krill larvae due to short duration of sea ice cover even for high food content under the ice. The variability of the krill's length-frequency distributions varied for different triggers of metabolic activity, but did not depend on the sea ice extent. Our findings suggest a southward shift of krill populations due to reduction in the spatial sea ice extent, which is consistent with field observations. Overall, our results highlight the importance of the explicit consideration of spatio-temporal sea ice dynamics especially for larval krill together with temporal synchronization through internal clocks, triggered by environmental factors (photoperiod and food) in adult krill for the population modelling of krill. (C) 2015 Elsevier B.V. All rights reserved.
Modelling of environmental change impacts on water resources and hydrological extremes in Germany
(2012)
Water resources, in terms of quantity and quality, are significantly influenced by environmental changes, especially by climate and land use changes. The main objective of the present study is to project climate change impacts on the seasonal dynamics of water fluxes, spatial changes in water balance components as well as the future flood and low flow conditions in Germany. This study is based on the modeling results of the process-based eco-hydrological model SWIM (Soil and Water Integrated Model) driven by various regional climate scenarios on one hand. On the other hand, it is supported by statistical analysis on long-term trends of observed and simulated time series. In addition, this study evaluates the impacts of potential land use changes on water quality in terms of NO3-N load in selected sub-regions of the Elbe basin. In the context of climate change, the actual evapotransipration is likely to increase in most parts of Germany, while total runoff generation may decrease in south and east regions in the scenario period 2051-2060. Water discharge in all six studied large rivers (Ems, Weser, Saale, Danube, Main and Neckar) would be 8 – 30% lower in summer and autumn compared to the reference period (1961 – 1990), and the strongest decline is expected for the Saale, Danube and Neckar. The 50-year low flow is likely to occur more frequently in western, southern and central Germany after 2061 as suggested by more than 80% of the model runs. The current low flow period (from August to September) may be extended until the late autumn at the end of this century. Higher winter flow is expected in all of these rivers, and the increase is most significant for the Ems (about 18%). No general pattern of changes in flood directions can be concluded according to the results driven by different RCMs, emission scenarios and multi-realizations. An optimal agricultural land use and management are essential for the reduction in nutrient loads and improvement of water quality. In the Weiße Elster and Unstrut sub-basins (Elbe), an increase of 10% in the winter rape area can result in 12-19% more NO3-N load in rivers. In contrast, another energy plant, maize, has a moderate effect on the water environment. Mineral fertilizers have a much stronger effect on the NO3-N load than organic fertilizers. Cover crops, which play an important role in the reduction of nitrate losses from fields, should be maintained on cropland. The uncertainty in estimating future high flows and, in particular, extreme floods remain high due to different RCM structures, emission scenarios and multi-realizations. In contrast, the projection of low flows under warmer climate conditions appears to be more pronounced and consistent. The largest source of uncertainty related to NO3-N modelling originates from the input data on the agricultural management.
Risk-based insurance is a commonly proposed and discussed flood risk adaptation mechanism in policy debates across the world such as in the United Kingdom and the United States of America. However, both risk-based premiums and growing risk pose increasing difficulties for insurance to remain affordable. An empirical concept of affordability is required as the affordability of adaption strategies is an important concern for policymakers, yet such a concept is not often examined. Therefore, a robust metric with a commonly acceptable affordability threshold is required. A robust metric allows for a previously normative concept to be quantified in monetary terms, and in this way, the metric is rendered more suitable for integration into public policy debates. This paper investigates the degree to which risk-based flood insurance premiums are unaffordable in Europe. In addition, this paper compares the outcomes generated by three different definitions of unaffordability in order to investigate the most robust definition. In doing so, the residual income definition was found to be the least sensitive to changes in the threshold. While this paper focuses on Europe, the selected definition can be employed elsewhere in the world and across adaption measures in order to develop a common metric for indicating the potential unaffordability problem.
Flood disasters severely impact human subjective well-being (SWB). Nevertheless, few studies have examined the influence of flood events on individual well-being and how such impacts may be limited by flood protection measures. This study estimates the long term impacts on individual subjective well-being of flood experiences, individual subjective flood risk perceptions, and household flood preparedness decisions. These effects are monetised and placed in context through a comparison with impacts of other adverse events on well-being. We collected data from households in flood-prone areas in France. The results indicate that experiencing a flood has a large negative impact on subjective well-being that is incompletely attenuated over time. Moreover, individuals do not need to be directly affected by floods to suffer SWB losses since subjective well-being is lower for those who expect their flood risk to increase or who have seen a neighbour being flooded. Floodplain inhabitants who prepared for flooding by elevating their home have a higher subjective well-being. A monetisation of the aforementioned well-being impacts shows that a flood requires Euro150,000 in immediate compensation to attenuate SWB losses. The decomposition of the monetised impacts of flood experience into tangible losses and intangible effects on SWB shows that intangible effects are about twice as large as the tangible direct monetary flood losses. Investments in flood protection infrastructure may be under funded if the intangible SWB benefits of flood protection are not taken into account.
The effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171 km(2) in size and cover different climate zones. 15 regional climate model outputs and 8 different statistical downscaling methods, which are broadly categorized as change factor and bias correction based methods, were used for the comparative analyses. Different hydrological models were implemented in different catchments to simulate daily runoff. A set of flood indices were derived from daily flows and their changes have been evaluated by comparing their values derived from simulations corresponding to the current and future climate. Most of the implemented downscaling methods project an increase in the extreme flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall dominated flood regime. In these catchments, the downscaling methods also project an increase in the extreme precipitation in the seasons when the extreme flows occur. In catchments where the flooding is mainly caused by spring/summer snowmelt, the downscaling methods project a decrease in the extreme flows in three of the four catchments considered. A major portion of the variability in the projected changes in the extreme flow indices is attributable to the variability of the climate model ensemble, although the statistical downscaling methods contribute 35-60% of the total variance. (C) 2016 Elsevier B.V. All rights reserved.
Elevated annual average temperature has been found to impact macro-economic growth. However, various fundamental elements of the economy are affected by deviations of daily temperature from seasonal expectations which are not well reflected in annual averages. Here we show that increases in seasonally adjusted day-to-day temperature variability reduce macro-economic growth independent of and in addition to changes in annual average temperature. Combining observed day-to-day temperature variability with subnational economic data for 1,537 regions worldwide over 40 years in fixed-effects panel models, we find that an extra degree of variability results in a five percentage-point reduction in regional growth rates on average. The impact of day-to-day variability is modulated by seasonal temperature difference and income, resulting in highest vulnerability in low-latitude, low-income regions (12 percentage-point reduction). These findings illuminate a new, global-impact channel in the climate–economy relationship that demands a more comprehensive assessment in both climate and integrated assessment models.
Evaluating climate geoengineering proposals in the context of the Paris Agreement temperature goals
(2018)
Current mitigation efforts and existing future commitments are inadequate to accomplish the Paris Agreement temperature goals. In light of this, research and debate are intensifying on the possibilities of additionally employing proposed climate geoengineering technologies, either through atmospheric carbon dioxide removal or farther-reaching interventions altering the Earth’s radiative energy budget. Although research indicates that several techniques may eventually have the physical potential to contribute to limiting climate change, all are in early stages of development, involve substantial uncertainties and risks, and raise ethical and governance dilemmas. Based on present knowledge, climate geoengineering techniques cannot be relied on to significantly contribute to meeting the Paris Agreement temperature goals.
Both climate change and land use regimes affect the viability of populations, but they are often studied separately. Moreover, population viability analyses (PVAs) often ignore the effects of large environmental gradients and use temporal resolutions that are too coarse to take into account that different stages of a population's life cycle may be affected differently by climate change. Here, we present the High-resolution Large Environmental Gradient (HiLEG) model and apply it in a PVA with daily resolution based on daily climate projections for Northwest Germany. We used the large marsh grasshopper (LMG) as the target species and investigated (1) the effects of climate change on the viability and spatial distribution of the species, (2) the influence of the timing of grassland mowing on the species and (3) the interaction between the effects of climate change and grassland mowing. The stageand cohort-based model was run for the spatially differentiated environmental conditions temperature and soil moisture across the whole study region. We implemented three climate change scenarios and analyzed the population dynamics for four consecutive 20-year periods. Climate change alone would lead to an expansion of the regions suitable for the LMG, as warming accelerates development and due to reduced drought stress. However, in combination with land use, the timing of mowing was crucial, as this disturbance causes a high mortality rate in the aboveground life stages. Assuming the same date of mowing throughout the region, the impact on viability varied greatly between regions due to the different climate conditions. The regional negative effects of the mowing date can be divided into five phases: (1) In early spring, the populations were largely unaffected in all the regions; (2) between late spring and early summer, they were severely affected only in warm regions; (3) in summer, all the populations were severely affected so that they could hardly survive; (4) between late summer and early autumn, they were severely affected in cold regions; and (5) in autumn, the populations were equally affected across all regions. The duration and start of each phase differed slightly depending on the climate change scenario and simulation period, but overall, they showed the same pattern. Our model can be used to identify regions of concern and devise management recommendations. The model can be adapted to the life cycle of different target species, climate projections and disturbance regimes. We show with our adaption of the HiLEG model that high-resolution PVAs and applications on large environmental gradients can be reconciled to develop conservation strategies capable of dealing with multiple stressors.
Patterns of phenotypic trait variation in two temperate forest herbs along a broad climatic gradient
(2015)
Phenotypic trait variation plays a major role in the response of plants to global environmental change, particularly in species with low migration capabilities and recruitment success. However, little is known about the variation of functional traits within populations and about differences in this variation on larger spatial scales. In a first approach, we therefore related trait expression to climate and local environmental conditions, studying two temperate forest herbs, Milium effusum and Stachys sylvatica, along a similar to 1800-2500 km latitudinal gradient. Within each of 9-10 regions in six European countries, we collected data from six populations of each species and recorded several variables in each region (temperature, precipitation) and population (light availability, soil parameters). For each plant, we measured height, leaf area, specific leaf area, seed mass and the number of seeds and examined environmental effects on within-population trait variation as well as on trait means. Most importantly, trait variation differed both between and within populations. Species, however, differed in their response. Intrapopulation variation in Milium was consistently positively affected by higher mean temperatures and precipitation as well as by more fertile local soil conditions, suggesting that more productive conditions may select for larger phenotypic variation. In Stachys, particularly light availability positively influenced trait variation, whereas local soil conditions had no consistent effects. Generally, our study emphasises that intra-population variation may differ considerably across larger scales-due to phenotypic plasticity and/or underlying genetic diversity-possibly affecting species response to global environmental change.
Gene flow is an important factor determining the evolution of a species, since it directly affects population structure and species’ adaptation. Here, we investigated population structure, population history, and migration among populations covering the entire distribution of the geographically isolated South-West European common lizard (Zootoca vivipara louislantzi) using 34 newly developed polymorphic microsatellite markers. The analyses unravelled the presence of isolation by distance, inbreeding, recent bottlenecks, genetic differentiation, and low levels of migration among most populations, suggesting that Z. vivipara louislantzi is threatened. The results point to discontinuous populations and are in line with physical barriers hindering longitudinal migration south to the central Pyrenean cordillera and latitudinal migration in the central Pyrenees. In contrast, evidence for longitudinal migration exists from the lowlands north to the central Pyrenean cordillera and the Cantabrian Mountains. The locations of the populations south to the central Pyrenean cordillera were identified as the first to be affected by global warming; thus, management actions aimed at avoiding population declines should start in this area.
P>Despite ample research, understanding plant spread and predicting their ability to track projected climate changes remain a formidable challenge to be confronted. We modelled the spread of North American wind-dispersed trees in current and future (c. 2060) conditions, accounting for variation in 10 key dispersal, demographic and environmental factors affecting population spread. Predicted spread rates vary substantially among 12 study species, primarily due to inter-specific variation in maturation age, fecundity and seed terminal velocity. Future spread is predicted to be faster if atmospheric CO2 enrichment would increase fecundity and advance maturation, irrespective of the projected changes in mean surface windspeed. Yet, for only a few species, predicted wind-driven spread will match future climate changes, conditioned on seed abscission occurring only in strong winds and environmental conditions favouring high survival of the farthest-dispersed seeds. Because such conditions are unlikely, North American wind-dispersed trees are expected to lag behind the projected climate range shift.