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Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.

Aim: Climate change impacts forest functioning and services through two inter‐related effects. First, it impacts tree growth, with effects, for example, on biomass production. Second, climate change also reshuffles community composition, with further effects on forest functioning. However, the relative importance of these two effects has rarely been studied. Here, we developed a new modelling approach to investigate these relative importances for forest productivity. Location: Eleven forest sites in central Europe. Time period: Historical (1990) and end‐of‐21st‐century climate‐like conditions. We simulated 2,000 years of forest dynamics for each set of conditions. Major taxa studied: Twenty‐five common tree species in European temperate forests. Methods: We coupled species distribution models and a forest succession model, working at complementary spatial and temporal scales, to simulate the climatic filtering that shapes potential tree species pools, the biotic filtering that shapes realized communities and the functioning of these realized communities in the long‐term. Results: Under an average temperature increase (relative to 1901–1990) of between 1.5 and 1.7 °C, changes in simulated forest productivity were caused mostly by changes in the growth of persisting tree species. With an average temperature increase of 3.6–4.0 °C, changes in simulated productivity at sites that currently have a mild climate were again caused predominantly by changes in tree species growth. However, at the warmest and coldest sites, changes in productivity were related mostly to shifts in species composition. In general, at the coldest sites, forest productivity is likely to be enhanced by climate change, whereas at the warmest sites the productivity might increase or decrease depending on the future precipitation regime. Main conclusions: A combination of two complementary modelling approaches that address questions at the interface between biogeography, community ecology and ecosystem functioning, reveals that climate change‐driven community reshuffling in the long term might be crucially important for ecosystem functioning. [ABSTRACT FROM AUTHOR]

Abstract Livestock production is important for local food security and as a source of income in sub-Saharan Africa. The human population of the region is expected to double by 2050, and at the same time climate change is predicted to negatively affect grazing resources vital to livestock. Therefore, it is essential to model the potential grazing output of sub-Saharan Africa in both present and future climatic conditions. Standard tools to simulate plant productivity are dynamic vegetation models (DVMs). However, as they typically allocate carbon to plant growth at an annual time step, they have a limited capability to simulate grazing. Here, we present a novel implementation of daily carbon allocation for grasses into the DVM Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) and apply this to study the grazing potential for the Kordofan region in Sudan. The results show a latitudinal split in grazing resources, where the northern parts of Kordofan are unexploited and southern parts are overused. Overall, we found that the modeled grazing potential of Kordofan is 16% higher than the livestock usage reported in the Food and Agricultural Organization of the United Nations, indicating a mitigation potential in the form of a spatial relocation of the herds. [ABSTRACT FROM AUTHOR]

Satellite derived normalized difference vegetation index (NDVI) is a common data source for monitoring regional and global ecosystem properties. In dry lands it has contributed to estimation of inter-annual and seasonal vegetation dynamics and phenology. However, due to the spectral properties of NDVI it can be affected by clouds which can introduce missing data in the time series. Remotely sensed soil moisture has in contrast to NDVI the benefit of being unaffected by clouds due to the measurements being made in the microwave domain. There is therefore a potential in combining the remotely sensed NDVI with remotely sensed soil moisture to enhance the quality and estimate the missing data. We present a step towards the usage of remotely sensed soil moisture for estimation of savannah NDVI. This was done by evaluating the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture and three of its individual products with respect to their relative performance. The individual products are from the advance scatterometer (ASCAT), Soil Moisture and Ocean Salinity (SMOS), and the Land Parameter Retrieval Model-Advanced Microwave Scanning Radiometer-Earth Observing System (LPRM-AMSR-E). Each dataset was used to simulate NDVI, which was subsequently compared to remotely sensed NDVI from MODIS. Differences in their ability to estimate NDVI indicated that, on average, CCI soil moisture differs from its individual products by showing a higher average correlation with measured NDVI. Overall NDVI modelled from CCI soil moisture gave an average correlation of 0.81 to remotely sensed NDVI which indicates its potential to be used to estimate seasonal variations in savannah NDVI. Our result shows promise for further development in using CCI soil moisture to estimate NDVI. The modelled NDVI can potentially be used together with other remotely sensed vegetation datasets to enhance the phenological information that can be acquired, thereby, improving the estimates of savannah vegetation phenology. [ABSTRACT FROM AUTHOR]

Background: Late blight (caused by Phytophthora infestans) is a devastating potato disease that has been found to occur earlier in the season over the last decades in Fennoscandia. Up until now the reasons for this change have not been investigated. Possible explanations for this change are climate alterations, changes in potato production or changes in pathogen biology, such as increased fitness or changes in gene flow within P. infestans populations. The first incidence of late blight is of high economic importance since fungicidal applications should be typically applied two weeks before the first signs of late blight and are repeated on average once a week. Methods: We use field observations of first incidence of late blight in experimental potato fields from five sites in Sweden and Finland covering a total of 30 years and investigate whether the earlier incidence of late blight can be related to the climate. Results: We linked the field data to meteorological data and found that the previous assumption, used in common late blight models, that the disease only develops at relative humidity levels above 90% had to be rejected. Rather than the typically assumed threshold relationship between late blight disease development and relative humidity we found a linear relationship. Our model furthermore showed two distinct responses of late blight to climate. At the beginning of the observation time (in Sweden until the early 90s and in Finland until the 2000s) the link between climate and first incidence was very weak. However, for the remainder of the time period the link was highly significant, indicating a change in the biological properties of the pathogen which could for example be a change in the dominating reproduction mode or a physiological change in the response of the pathogen to climate. Conclusions: The study shows that models used in decision support systems need to be checked and re-parametrized regularly to be able to capture changes in pathogen biology. While this study was performed with data from Fennoscandia this new pathogen biology and late blight might spread to (or already be present at) other parts of the world as well. The strong link between climate and first incidence together with the presented model offers a tool to assess late blight incidence in future climates. [ABSTRACT FROM AUTHOR]

Forest fires are an important disturbance factor of boreal forests, annually burning about 0.5% of the forested area in Canada. Wildfire regimes are influenced by climate and a number of studies project an increase in wildfire activity with climate change. Another factor influencing wildfires is human intervention (fire suppression), and one factor that has rarely been assessed is fuel fragmentation. Studies evaluating the effect of forest fire suppression concluded that in areas with strong suppression effort the burned area as well as the fire size decreased. Here we evaluate wildfire distributions over the last three decades for two areas that differ mainly in their level of forest management and fire suppression: the Boreal Shield (unmanaged) and the Boreal Plain regions (intensively managed) in the Canadian Province of Saskatchewan. We calculate a fuel fragmentation index and relate fire sizes and burned areas to fire weather. We use the concept of the characteristic fire size (CFS); hence we analyze how much burned area is contributed to the total burned area per fire size class. Both areas show a uni-modal distribution of the CFS, indicating that the majority of burned area was contributed by medium sized fires (Boreal Shield 6.39 · 10 4 ha, the Boreal Plain 8.79 · 10 4 ha). Burned area as well as fuel fragmentation is lower in the managed forest compared to the unmanaged area. The fuel fragmentation index constantly increased since the 1980s in both regions. Despite the large efforts of fire suppression in the Boreal Plains, the CFS is slightly larger in this managed region. Neither the burned area nor the fire size could be linked statistically to the weather conditions, at the time of the fire (using the Canadian Fire Weather Index). We argue that the high fragmentation over the last decades have decreased the burned area. The slightly higher characteristic fire size in the managed area might be explained by the considerably lower fragmentation, counteracting fire suppression efforts. Fuel fragmentation is likely to decrease over the next decades due re-growth. Though a strong link between fire weather and burned area at the fine scale of this study could not be detected we expect that a decrease in fragmentation in combination with an increase in fire prone weather conditions (as expected for the future) might increase the risk of large fires in both areas. We suggest that future fire risk analysis should include an assessment of the effect of fuel fragmentation. [ABSTRACT FROM AUTHOR]

Aim To project the potential European distribution of seven broad habitat categories (needle-leaved, broad-leaved, mixed and mediterranean forest, urban, grassland and cropland) in order to assess effects of land use, climate change and increase in CO2 on predicted habitat changes up to the year 2050. Location Europe. Method We modelled the response of European vegetation to changes in land use, climate and CO2 by combining the land-use model Dyna- CLUE (based on the CORINE land-cover data) and the dynamic vegetation model LPJ-GUESS. Two reforestation options were explored: maintaining the current range of tree species ( EFI) or promoting naturally occurring tree species ( NAT). Climate data from two general circulation models and two SRES scenarios ( A2 and B1) were used. The broad habitat types were classified according to a combination of land use and the dominant plant species. Results Our models predicted that croplands and grasslands are expected to decrease due to land-use change. Although climate change has a negative effect on needle-leaved forest, it is expected to maintain its area or even increase in the EFI reforestation option while mediterranean, broad-leaved and mixed forests are expected to increase markedly. All investigated drivers have shown some effect, but land use is the dominant contributor to broad habitat change except for needle-leaved and mixed which are mainly influenced by climate change. Main conclusions Land use is predicted to have the greatest effect on broad habitat distribution according to our simulations. Hence in most parts of Europe mitigating actions should focus on land-use change rather than climate change. According to our simulation, the effects of the different drivers are not in general additive. In some cases they act synergistically and in some cases antagonistically. The projected habitat changes are a valuable tool for species distribution modelling and are available online. [ABSTRACT FROM AUTHOR]

Land use and climate changes induce shifts in plant functional diversity and community structure, thereby modifying ecosystem processes. This is particularly true for litter decomposition, an essential process in the biogeochemical cycles of carbon and nutrients. In this study, we asked whether changes in functional traits of living leaves in response to changes in land use and climate were related to rates of litter potential decomposition, hereafter denoted litter decomposability, across a range of 10 contrasting sites. To disentangle the different control factors on litter decomposition, we conducted a microcosm experiment to determine the decomposability under standard conditions of litters collected in herbaceous communities from Europe and Israel. We tested how environmental factors (disturbance and climate) affected functional traits Of living leaves and how these traits then modified litter quality and subsequent litter decomposability. Litter decomposability appeared proximately linked to initial litter quality, with particularly clear negative correlations with lignin-dependent indices (litter lignin concentration, lignin : nitrogen ratio, and fiber component). Litter quality was directly related to community-weighted mean traits. Lignin-dependent indices of litter quality were positively correlated with community-weighted mean leaf dry matter content (LDMC), and negatively correlated with community-weighted mean leaf nitrogen concentration (LNC). Consequently, litter decomposability was correlated negatively with community-weighted mean LDMC, and positively with community-weighted mean LNC. Environmental factors (disturbance and climate) influenced community-weighted mean traits. Plant communities experiencing less frequent or less intense disturbance exhibited higher community-weighted mean LDMC, and therefore higher litter lignin content and slower litter decomposability. LDMC therefore appears as a powerful marker of both changes in land use and of the pace of nutrient cycling across 10 contrasting sites. [ABSTRACT FROM AUTHOR]

Abstract: The influence of different drivers on changes in North American and European boreal forests biomass burning (BB) during the Holocene was investigated based on the following hypotheses: land use was important only in the southernmost regions, while elsewhere climate was the main driver modulated by changes in fuel type. BB was reconstructed by means of 88 sedimentary charcoal records divided into six different site clusters. A statistical approach was used to explore the relative contribution of (a) pollen‐based mean July/summer temperature and mean annual precipitation reconstructions, (b) an independent model‐based scenario of past land use (LU), and (c) pollen‐based reconstructions of plant functional types (PFTs) on BB. Our hypotheses were tested with: (a) a west‐east northern boreal sector with changing climatic conditions and a homogeneous vegetation, and (b) a north‐south European boreal sector characterized by gradual variation in both climate and vegetation composition. The processes driving BB in boreal forests varied from one region to another during the Holocene. However, general trends in boreal biomass burning were primarily controlled by changes in climate (mean annual precipitation in Alaska, northern Quebec, and northern Fennoscandia, and mean July/summer temperature in central Canada and central Fennoscandia) and, secondarily, by fuel composition (BB positively correlated with the presence of boreal needleleaf evergreen trees in Alaska and in central and southern Fennoscandia). Land use played only a marginal role. A modification towards less flammable tree species (by promoting deciduous stands over fire‐prone conifers) could contribute to reduce circumboreal wildfire risk in future warmer periods. [ABSTRACT FROM AUTHOR]

In this study, a global vegetation model (LPJ-GUESS) is forced with spatial information (Nomenclature of Units for Territorial Statistics (NUTS) 2 level) of land-use intensity change in the form of nitrogen (N) fertilization derived from a model chain which informed the Common Agricultural Policy Regionalized Impact (CAPRI) model. We analysed the combined role of climate change and land-use intensity change for trade-offs between agricultural yield and N leaching in the European Union under two plausible scenarios up until 2040. Furthermore, we assessed both driver importance and uncertainty in future trends based on an alternative land-use intensity dataset derived from an integrated assessment model. LPJ-GUESS simulated an increase in wheat and maize yield but also N leaching for most regions when driven by changes in land-use intensity and climate under RCP 8.5. Under RCP 4.5, N leaching is reduced in 53% of the regions while there is a trade-off in crop productivity. The most important factors influencing yield were CO 2 (wheat) and climate (maize), but N application almost equaled these in importance. For N leaching, N application was the most important factor, followed by climate. Therefore, using a constant N application dataset in the absence of future projections has a substantial effect on simulated ecosystem responses, especially for maize yield and N leaching. This study is a first assessment of future N leaching and yield responses based on projections of climate and land-use intensity. It further highlights the importance of accounting for changes in future N applications and land-use intensity in general when evaluating environmental impacts over long time periods. [ABSTRACT FROM AUTHOR]