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To determine if non-native plant species are homogenizing species composition among widely dispersed plant communities. Twenty localities in North America. Species lists among localities were compared to measure the influence of non-native species richness at each locality on the Jaccard Index (JI) of similarity between localities. After removing the effects of distance, because shared native species decreased with distance, three (nonexclusive) lines of evidence indicate that non-native species promote homogenization. First, pairs of sites with a high combined total of non-native species tend to have higher similarity than those with a low total of non-natives. Second, for a given distance, more non-native than native species tended to be shared among localities. Third, whereas most of the site comparisons with high total non-native richness have a non-native/native JI ratio greater than 1 (often much greater), only half of the comparisons with low total non-native richness have a ratio greater than one. These findings provide quantitative support for the widely held, but rarely tested, notion that non-native species tend to homogenize biological communities because they are more commonly shared among communities. Such testing is important as non-native species could theoretically have no impact or even reduce homogenization among communities, if non-native colonizers consist of different species pools. [ABSTRACT FROM AUTHOR]

Extensive dieback of salt marsh dominated by the perennial grass Spartina alterniflora occurred throughout the Mississippi River deltaic plain during 2000. More than 100,000 ha were affected, with 43,000 ha severely damaged. The aim of this work was to determine if sudden dieback could have been caused by a coincident drought and to assess the significance of this event with respect to long-term changes in coastal vegetation. Multiple dieback sites and reference sites were established along 150 km of shoreline in coastal Louisiana, USA. Aerial and ground surveys were conducted from June 2000 to September 2001 to assess soil conditions and plant mortality and recovery. Dieback areas ranged in size from ∼300 m2−5 km2 in area with 50–100% mortality of plant shoots and rhizomes in affected zones. Co-occurring species such as Avicennia germinans (black mangrove) and Juncus roemerianus (needlegrass rush) were unaffected. Historical records indicate that precipitation, river discharge, and mean sea level were unusually low during the previous year. Although the cause of dieback is currently unknown, plant and soil characteristics were consistent with temporary soil desiccation that may have reduced water availability, increased soil salinity, and/or caused soil acidification (via pyrite oxidation) and increased uptake of toxic metals such as Fe or Al. Plant recovery 15 months after dieback was variable (0–58% live cover), but recovering plants were vigorous and indicated no long-lasting effects of the dieback agent. These findings have relevance for global change models of coastal ecosystems that predict vegetation responses based primarily on long-term increases in sea level and submergence of marshes. Our results suggest that large-scale changes in coastal vegetation may occur over a relatively short time span through climatic extremes acting in concert with sea-level fluctuations and pre-existing soil conditions. [ABSTRACT FROM AUTHOR]

Aim: Functional diversity indices that summarize trait variation between organisms within communities are widely used tools in community ecology. Although intraspecific trait variation is often an important component of the total variation, traditional functional diversity indices neglect this component. Recently, Carmona et al. proposed a framework to overcome this limitation based on fitting trait probability distributions (TPDs). Unfortunately, this article does not contain any guidance on pooling data before fitting TPDs. Innovation: Reliable fitting of TPDs needs larger sample size than usually used. This larger sample size can be reached pooling of data comes from different localities. If the TPD is the same in these localities, pooling results in a more reliable estimation. Moreover, if pooled data represent different TPDs, the fitted distribution is an artefact. In this paper, we suggest an algorithm for the automated selection of optimal pooling. It is based on fitting Gaussian mixture models and model selection using Bayes information criterion (BIC). Main conclusions: The new algorithm was able to select the optimal pooling of data, which is illustrated using artificial data. Analysis of field data examples showed that optimal pooling is often not obvious: both merging all data and analysing measurements from each locality separately might result in unreliable estimates. [ABSTRACT FROM AUTHOR]

Motivation: Documenting potential interactions between species represents a major step towards understanding and predicting the spatial and temporal structure of multi‐trophic communities and their functioning. The metaweb concept summarizes the potential trophic (and non‐trophic) interactions in a given species pool. As such, it generalizes the regional species pool of community ecology by incorporating the potential relationships between species from different trophic levels along with their functional characteristics. However, although this concept is very attractive theoretically, it has rarely been used to understand the structure of an ecological network, mostly because of data availability. Here, we provide a continental‐scale, species‐level metaweb for all tetrapods (mammals, breeding birds, reptiles and amphibians) occurring in Europe and in the Northern Mediterranean basin. This metaweb is based on data extracted from the scientific literature, including published papers, books and grey literature. Main type of variable contained: For each species considered, we built the network of potential two‐way trophic interactions. Spatial location and grain: We considered all species occurring in the entire European subcontinent, from Macaronesia (including only the islands belonging politically to Spain and Portugal) to the Ural Mountains (west to east) and from Fennoscandia and U.K. islands to the Mediterranean (north to south). We included Turkey, geographically part of Asia, to provide a complete picture of the north‐eastern Mediterranean coast. Time period: The data represent information published and/or collected during the last 50 years. Major taxa studied and level of measurement: We focused our metaweb on terrestrial tetrapods occurring in the study area. Only species introduced in historical times and currently naturalized were considered; new introductions were excluded. In total, we included 288 mammals, 509 regularly breeding birds, 250 reptiles and 104 amphibians. Software format: Data are supplied as semicolon‐separated text files. [ABSTRACT FROM AUTHOR]

Aim Multiple spatial and non-spatial processes are involved in determining the complex patterns underlying the spatial variation of individual species and their assemblages. This complexity, and the logistical challenges involved in following dispersal for multiple species across multiple sites, make it challenging to infer the processes underlying metacommunity spatial heterogeneity. The goal of our paper is to present a robust quantitative framework for inferring spatial patterns across multiple ecological communities. Innovation Unlike numerous metapopulation studies that have inferred migration rates based on landscape connectivity metrics which take into account the spatial positioning of occupied and empty patches, metacommunity studies have relied on spatial predictors built without considering such information. Here, we introduce a novel method called the multi-species spatial network ( MSSN) to detect and explain spatial variability in community assemblies using a graph-theoretical approach. The MSSN approach can be best described as a reconciliation between the spatial positioning of sites and their patterns of patch occupation. Main conclusions Our simulation and real data analyses showed that our MSSN approach was better at detecting spatial patterns within metacommunities than the commonly used MEM method (Moran's eigenvector maps). In addition, our proposed framework is also useful in estimating the levels of spatial connectivity for each local community. Finally, our framework is flexible enough to incorporate different types of functions, metrics and algorithms to detect complex spatial patterns. [ABSTRACT FROM AUTHOR]

Aim In this paper, we applied the concept of 'hierarchical filters' in community ecology to model marine species distribution at nested spatial scales. Location Global, Mediterranean Sea and the Gulf of Gabes ( Tunisia). Methods We combined the predictions of bioclimatic envelope models ( BEMs) and habitat models to assess the current distribution of 20 exploited marine species in the Gulf of Gabes. BEMs were first built at a global extent to account for the full range of climatic conditions encountered by a given species. Habitat models were then built using fine-grained habitat variables at the scale of the Gulf of Gabes. We also used this hierarchical filtering approach to project the future distribution of these species under both climate change (the A2 scenario implemented with the Mediterranean climatic model NEMOMED8) and habitat loss (the loss of Posidonia oceanica meadows) scenarios. Results The hierarchical filtering approach predicted current species geographical ranges to be on average 56% smaller than those predicted using the BEMs alone. This pattern was also observed under the climate change scenario. Combining the habitat loss and climate change scenarios indicated that the magnitude of range shifts due to climate change was larger than from the loss of P. oceanica meadows. Main conclusions Our findings emphasize that BEMs may overestimate current and future ranges of marine species if species-habitat relationships are not also considered. A hierarchical filtering approach that accounts for fine-grained habitat variables limits the uncertainty associated with model-based recommendations, thus ensuring their outputs remain applicable within the context of marine resource management. [ABSTRACT FROM AUTHOR]

Aim Climate change and loss of apex predators can affect ecosystem structure and function through modified limitation processes. We investigated, on a continental scale, whether mesopredator abundance is limited from the top down by large predators, as predicted by the mesopredator release hypothesis, or by bottom-up factors. The mesopredator in focus is the red fox Vulpes vulpes, a key predator in many ecosystems due to its strong effects on prey abundance. Location Europe and northern Asia. Methods Data on red fox density were compiled from published papers and reports. For each site, we collated presence-absence data on large carnivores ( Lynx lynx, Canis lupus, Canis aureus) and remote sensing data for factors potentially related to bottom-up limitation (winter severity, summer temperature, human density, primary productivity, tree cover). The data were analysed through structural equation modelling. Results The presence of lynx had a direct negative effect on red foxes, suppressing fox abundance. Also winter severity had a negative effect on red fox abundance, and in Eurasia as a whole this effect was partially mediated through lynx. Within the lynx distribution range, winter severity was the only bottom-up factor significantly affecting red fox abundance. Outside the lynx distribution range, primary productivity, summer temperature and human density had a positive effect on red fox abundance. Main conclusions Our results show that apex predators can limit mesopredator abundance on a continental scale, thus supporting the mesopredator release hypothesis. Winter severity also affected red fox abundance, partially due to an interaction between lynx and winter conditions. On the continental scale a complex network of processes operates with varying effects depending on mediation processes. Our results imply that apex predators can have an important effect on ecosystem structure by limiting mesopredator abundance, and we suggest that apex predators may dampen increases in mesopredator abundance driven by global warming. [ABSTRACT FROM AUTHOR]

Aim The emission of chlorofluorocarbon compounds eroded the ozone layer, raising incident ultraviolet B radiation to levels that affect biota. However, the role of UVB radiation (280-315 nm), which remains elevated to date, as a possible driver of the widespread global deterioration of marine ecosystems has not yet been fully quantified. In this paper we assess the magnitude of the impacts of elevated UVB radiation and evaluate the relative sensitivity to UVB across marine taxa and processes. Location The analyses presented are based on 1784 experimental assessments of the impacts of UVB performed with natural radiation and organisms from different geographical areas, as well as with artificial radiation and cultured organisms at many laboratories around the world. Methods First we compiled the published literature concerning experimental evaluation of the impacts of UVB on marine biota. Then a meta-analysis was conducted with the data set obtained to evaluate the responses of marine organisms and processes to enhanced and reduced UVB levels. Results Increased UVB radiation leads to a sharp increase in mortality rates across marine taxa, with protists, corals, crustaceans and fish eggs and larvae being most sensitive. A general relationship between relative changes in UVB doses and mortality rates was developed. This relationship can help assess the effects of changes in incident UVB radiation (past, present or future) on marine organisms. Main conclusions This meta-analysis demonstrates that mortality rates of marine biota increase rapidly in response to elevated UVB radiation. The enhanced mortality rates associated with currently elevated UVB levels may represent a major threat to marine biota, possibly underlying recent widespread declines in the abundance of marine organisms ranging from corals to fish and krill. [ABSTRACT FROM AUTHOR]

Two of the oldest observations in plant geography are the increase in plant diversity from the poles towards the tropics and the global geographic distribution of vegetation physiognomy (biomes). The objective of this paper is to use a process-based vegetation model to evaluate the relationship between modelled and observed global patterns of plant diversity and the geographic distribution of biomes. The global terrestrial biosphere. We implemented and tested a novel vegetation model aimed at identifying strategies that enable plants to grow and reproduce within particular climatic conditions across the globe. Our model simulates plant survival according to the fundamental ecophysiological processes of water uptake, photosynthesis, reproduction and phenology. We evaluated the survival of an ensemble of 10,000 plant growth strategies across the range of global climatic conditions. For the simulated regional plant assemblages we quantified functional richness, functional diversity and functional identity. A strong relationship was found (correlation coefficient of 0.75) between the modelled and the observed plant diversity. Our approach demonstrates that plant functional dissimilarity increases and then saturates with increasing plant diversity. Six of the major Earth biomes were reproduced by clustering grid cells according to their functional identity (mean functional traits of a regional plant assemblage). These biome clusters were in fair agreement with two other global vegetation schemes: a satellite image classification and a biogeography model (kappa statistics around 0.4). Our model reproduces the observed global patterns of plant diversity and vegetation physiognomy from the number and identity of simulated plant growth strategies. These plant growth strategies emerge from the first principles of climatic constraints and plant functional trade-offs. Our study makes important contributions to furthering the understanding of how climate affects patterns of plant diversity and vegetation physiognomy from a process-based rather than a phenomenological perspective. [ABSTRACT FROM AUTHOR]

Humid tropical alpine environments are crucial ecosystems that sustain biodiversity, biological processes, carbon storage and surface water provision. They are identified as one of the terrestrial ecosystems most vulnerable to global environmental change. Despite their vulnerability, and the importance for regional biodiversity conservation and socio-economic development, they are among the least studied and described ecosystems in the world. This paper reviews the state of knowledge about tropical alpine environments, and provides an integrated assessment of the potential threats of global climate change on the major ecosystem processes. Humid tropical alpine regions occur between the upper forest line and the perennial snow border in the upper regions of the Andes, the Afroalpine belt and Indonesia and Papua New Guinea. Climate change will displace ecosystem boundaries and strongly reduce the total area of tropical alpine regions. Displacement and increased isolation of the remaining patches will induce species extinction and biodiversity loss. Drier and warmer soil conditions will cause a faster organic carbon turnover, decreasing the below-ground organic carbon storage. Since most of the organic carbon is currently stored in the soils, it is unlikely that an increase in above-ground biomass will be able to offset soil carbon loss at an ecosystem level. Therefore a net release of carbon to the atmosphere is expected. Changes in precipitation patterns, increased evapotranspiration and alterations of the soil properties will have a major impact on water supply. Many regions are in danger of a significantly reduced or less reliable stream flow. The magnitude and even the trend of most of these effects depend strongly on local climatic, hydrological and ecological conditions. The extreme spatial gradients in these conditions put the sustainability of ecosystem management at risk. [ABSTRACT FROM AUTHOR]

Aim In any region affected, fires exhibit a strong seasonal cycle driven by the dynamic of fuel moisture and ignition sources throughout the year. In this paper we investigate the global patterns of fire seasonality, which we relate to climatic, anthropogenic, land-cover and land-use variables. Location Global, with detailed analyses from single 1°× 1° grid cells. Methods We use a fire risk index, the Chandler burning index (CBI), as an indicator of the ‘natural’, eco-climatic fire seasonality, across all types of ecosystems. A simple metric, the middle of the fire season, is computed from both gridded CBI data and satellite-derived fire detections. We then interpret the difference between the eco-climatic and observed metrics as an indicator of the human footprint on fire seasonality. Results Deforestation, shifting cultivation, cropland production or tropical savanna fires are associated with specific timings due to land-use practices, sometimes largely decoupled from the CBI dynamics. Detailed time series from relevant locations provide comprehensive information about these practices and how they are adapted to eco-climatic conditions. Main conclusions We find a great influence of anthropogenic activities on global patterns of fire seasonality. The specificity of the main fire practices and their easy identification from global observation is a potential tool to support land-use monitoring efforts. Our results should also prove valuable in the development of a methodological approach for improving the representation of anthropogenic fire practices in dynamic global vegetation models. [ABSTRACT FROM AUTHOR]

It has been suggested that alien species with close indigenous relatives in the introduced range may have reduced chances of successful establishment and invasion (Darwin's naturalization hypothesis). Studies trying to test this have in fact been addressing four different hypotheses, and the same data can support some while rejecting others. In this paper, we argue that the phylogenetic pattern will change depending on the spatial and phylogenetic scales considered. Expectations and observations from invasion biology and the study of natural communities are that at the spatial scale relevant to competitive interactions, closely related species will be spatially separated, whereas at the regional scale, species in the same genera or families will tend to co-occur more often than by chance. We also argue that patterns in the relatedness of indigenous and naturalized plants are dependent on the continental/island setting, spatial occupancy levels, and on the group of organisms under scrutiny. Understanding how these factors create a phylogenetic pattern in invasions will help us predict which groups are more likely to invade where, and should contribute to general ecological theory. [ABSTRACT FROM AUTHOR]

Aim Rainfall reliability has been neglected as a determinant of plant trait convergence and divergence in mediterranean-climate ecosystems. This paper reports on patterns of rainfall reliability — quantified as interannual variation in monthly and seasonal rainfall, and as the frequency of individual events in terms of their size, duration and intensity — for four fire-prone mediterranean-climate ecosystems. Location The four mediterranean-climate regions of the world with fire-prone ecosystems, namely SW Cape (South Africa), SW Australia, California and the Mediterranean Basin (Andalusia, Spain). Methods Using long-term monthly rainfall data from stations dispersed across the four regions, we computed monthly means and interannual variation for each month of the year — the latter quantified as the coefficient of variation (CV) — and divided these into winter and summer seasons. We also computed the mean number of rainfall events, the mean frequency in various categories of event duration (days), the amount of rainfall per event (mm) and the rainfall intensity per event (mm/day) per year for winter and summer seasons for a subset of the rainfall stations. Results The fraction of rain falling in summer was lowest in California (5%) and similarly low ( c. 25%) in the other three regions. The hierarchy of values of coefficient of variation (CV) of monthly rainfall during the winter period was as follows: California > Andalusia >> SW Cape > SW Australia; results for summer were: California > > Andalusia >> SW Australia ∼ SW Cape. SW Australian sites experienced the greatest frequency of short, small and low-intensity rainfall events in both seasons; patterns in the SW Cape were intermediate between Australia and the two northern hemisphere sites which both received fewer, larger and more intense events. Overall, the two southern hemisphere regions (SW Australia and the SW Cape) had significantly more reliable regimes than the two northern hemisphere ones (Mediterranean Basin and California). Main conclusions These differences in rainfall reliability regimes may provide a novel perspective on the distribution of certain plant life-history traits in mediterranean-climate ecosystems. Less reliable regimes would select for germination and seedling survival traits that enable persistence of genets in the face of uncertain moisture conditions during the winter and spring establishment phase. Study systems that accommodate for phylogenetic constraints, namely invasive species derived from mediterranean-climate ecosystems, as well as shared lineages, provide good opportunities to develop and test hypotheses on the implication of different rainfall reliability regimes. One of the novel implications of this study is that the distinctive trait of assemblages in the southern hemisphere regions may be a consequence not so much of their shared nutrient-poor soils as of their similarly reliable rainfall regimes. [ABSTRACT FROM AUTHOR]

The objective of this paper is to obtain a net primary production (NPP) regression model based on the geographically weighted regression (GWR) method, which includes spatial non-stationarity in the parameters estimated for forest ecosystems in China. We used data across China. We examine the relationships between NPP of Chinese forest ecosystems and environmental variables, specifically altitude, temperature, precipitation and time-integrated normalized difference vegetation index (TINDVI) based on the ordinary least squares (OLS) regression, the spatial lag model and GWR methods. The GWR method made significantly better predictions of NPP in simulations than did OLS, as indicated both by corrected Akaike Information Criterion (AICc) and R2. GWR provided a value of 4891 for AICc and 0.66 for R2, compared with 5036 and 0.58, respectively, by OLS. GWR has the potential to reveal local patterns in the spatial distribution of a parameter, which would be ignored by the OLS approach. Furthermore, OLS may provide a false general relationship between spatially non-stationary variables. Spatial autocorrelation violates a basic assumption of the OLS method. The spatial lag model with the consideration of spatial autocorrelation had improved performance in the NPP simulation as compared with OLS (5001 for AICc and 0.60 for R2), but it was still not as good as that via the GWR method. Moreover, statistically significant positive spatial autocorrelation remained in the NPP residuals with the spatial lag model at small spatial scales, while no positive spatial autocorrelation across spatial scales can be found in the GWR residuals. We conclude that the regression analysis for Chinese forest NPP with respect to environmental factors and based alternatively on OLS, the spatial lag model, and GWR methods indicated that there was a significant improvement in model performance of GWR over OLS and the spatial lag model. [ABSTRACT FROM AUTHOR]

Interannual land cover change plays a significant role in food security, ecosystem processes, and regional and global climate modelling. Measuring the magnitude and location and understanding the driving factors of interannual land cover change are therefore of utmost importance to improve our understanding and prediction of these impacts and to better differentiate between natural and human causes of land cover change. Despite advances in quantifying the magnitude of land cover change, the interpretation of the observed land cover change in terms of climatic, ecological and anthropogenic processes still remains a complex issue. In this paper, we map land cover change across sub-Saharan Africa and examine the influences of rainfall fluctuations on interannual change.The analysis was applied to sub-Saharan Africa.Ten-day rainfall estimates (RFE) obtained from National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Center (CPC) were used to extract information on inter and intra-annual rainfall fluctuations. The magnitude of land cover change was quantified based on the multitemporal change vector method measuring year-to-year differences in bidirectional reflectance distribution function (BRDF) corrected 16-day enhanced vegetation index (EVI) data from the Moderate Resolution Imaging Spectro-radiometer (MODIS). Statistical models were used to estimate the relationship between short-term rainfall variability and the magnitude of land cover change. The analysis was stratified first by physiognomic vegetation type and second by chorological data on species distribution to gain insights into spatial variations in response to short-term rainfall fluctuations.The magnitude of land cover change was significantly related to rainfall variability at the 5% level. Stratification considerably strengthened the relationship between the magnitude of change and rainfall variability. Explanatory power of the models ranged fromR2 = 0.22 for the unstratified model to 0.40–0.96 for the individual models stratified by patterns of species distribution. The total variability explained by the combined models including the influence of rainfall and differences in vegetation response ranged from 22% for the model not stratified by vegetation to 76% when stratified by chorological data.Using this methodology, we were able to measure the contribution of natural variation in precipitation to land cover change. Several ecosystems across sub-Saharan Africa are highly sensitive to short-term rainfall variability. [ABSTRACT FROM AUTHOR]

This paper presents a probabilistic method of pollen spectra analysis. The method relies on a pollen taxon characterization using biotic and abiotic plant attribute modes, and their occurrence in a given pollen spectrum at a specific site. This type of analysis can provide an interpretation, which can lead to the reconstruction of the biome and, to an extent, of the abiotic conditions at the site.The analysis has been carried out at the European scale using data provided by the European Pollen Database for about 1000 sites. This dataset contains about 50,000 pollen spectra from the last 21 ka. In these spectra, each pollen taxon has been characterized by a set of 10 chosen attributes. These have been selected with regard to their relevance in biome reconstruction, but also on the basis of available literature. By using the probability of occurrence of each taxon in a given pollen spectrum, it is possible to calculate an affinity index for the spectrum to the attribute considered. To overcome difficulties caused by pollen identification in low diversified pollen spectra, a co-occurrence concept has been used to give more information.The method has been validated on a set of 1327 modern surface samples by comparing the results to the major climatic and environmental variables that control the distribution of the vegetation. A reconstruction exercise on various characteristics of the plants was then carried out on a 6-ka dataset. This confirmed previous studies by showing a strong dominance of deciduous forest over most of Europe, related to a milder climate than at present in the north and a wetter and colder climate than at present in the south. By analysing the change in pollen/seed dispersion strategies and the light requirement, we show that the history of vegetation dynamics in relation to human influences can be assessed using this method.Our results show that the probabilistic method is an objective tool for pollen assemblage analysis. It allows reconstruction of various characteristics of the vegetation at the continental and global scale for periods and sites with significantly different climate conditions. This method can also be used to compare maps of vegetation attributes for the validation of the new generalized dynamic ecosystems models. [ABSTRACT FROM AUTHOR]

This paper investigates the use of an ecosystem simulation model, FOREST-BGC, to estimate the main ecophysiological processes (transpiration and photosynthesis) of Mediterranean coastal forest areas using remotely sensed data. Model testing was carried out at two protected forest sites in central Italy, one of which was covered by Turkey oak (Circeo National Park) and the other by holm-oak (Castelporziano Estate). At both sites, transpiration and photosynthesis measurements were collected in the field during the growing seasons over a four-year period (1999 and 2001 for the Turkey oak; 1997, 1999 and 2000 for the holm-oak). Calibration of the model was obtained through combining information derived from ground measurements and remotely sensed data. In particular, remote sensing estimates of the Leaf Area Index derived from 1 × 1-km NOAA AVHRR Normalized Difference Vegetation Index data were used to improve the adaptation of the model to local forest conditions. The results indicated different strategies regarding water use efficiency, ‘water spending’ for Turkey oak and ‘water saving’ for holm-oak. The water use efficiency for the holm-oak was consistently higher than that for the Turkey oak and the relationship between VPD and WUE for the holm-oak showed a higher coefficient of determination ( R2 = 0.9238). Comparisons made between the field measurements of transpiration and photosynthesis and the model estimates showed that the integration procedure used for the deciduous oak forest was effective, but that there is a need for further studies regarding the sclerophyllous evergreen forest. In particular, for Turkey oak the simulations of transpiration yielded very good results, with errors lower than 0.3 mm H2O/day, while the simulation accuracy for photosynthesis was lower. In the case of holm-oak, transpiration was markedly overestimated for all days considered, while the simulations of photosynthesis were very accurate. Overall, the approach offers interesting operational possibilities for the monitoring of Mediterranean forest ecosystems, particularly in view of the availability of new satellite sensors with a higher spatial and temporal resolution, which have been launched in recent years. [ABSTRACT FROM AUTHOR]

This paper examines species richness, abundance, and body size in deep-sea gastropods and how they vary over depth, which is a strong correlate of nutrient input. Previous studies have documented the empirical relationships among these properties in terrestrial and coastal ecosystems, but a full understanding of how these patterns arise has yet to be obtained. Examining the relationships among macroecological variables is a logical progression in deep-sea ecology, where patterns of body size, diversity, and abundance have been quantified separately but not linked together. 196–5042 m depth in the western North Atlantic. Individuals analysed represent all Vetigastropoda and Caenogastropoda (Class Gastropoda) with intact shells, excluding Ptenoglossa, collected by the Woods Hole Benthic Sampling Program (3424 individuals representing 80 species). Biovolume was measured for every individual separately (i.e. allowing the same species to occupy multiple size classes) and divided into log2 body size bins. Analyses were conducted for all gastropods together and separated into orders and depth regions (representing different nutrient inputs). A kernel smoothing technique, Kolmogorov-Smirnov test of fit, and OLS and RMA were used to characterize the patterns. Overall, the relationship between the number of individuals and species is right skewed. There is also a positive linear relationship between the number of individuals and the number of species, which is independent of body size. Variation among these relationships is seen among the three depth regions. At depths inferred to correspond with intermediate nutrient input levels, species are accumulated faster given the number of individuals and shift from a right-skewed to a log-normal distribution. A strong link between body size, abundance, and species richness appears to be ubiquitous over a variety of taxa and environments, including the deep sea. However, the nature of these relationships is affected by the productivity regime and scale at which they are examined. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim This paper presents a probabilistic method for the characterization of pollen taxa using attributes, and for the reconstitution of past biomes. The probabilities are calculated on the basis of European floristic and pollen databases sufficiently large and exhaustive to provide robust estimates. Location The analysis is based on data from approximately 1000 sites throughout Europe. Method We use all the pollen data from the European Pollen Database (EPD), which contains about 50 000 pollen assemblages distributed across Europe and covering the period from the Last Glacial Maximum to the present. Using existing floras, each pollen taxon has been characterized by allocating one or more modes of several attributes, chosen according to the biogeography and phenology of the taxon. With this information, conditional probabilities are defined, representing the chance of a given attribute mode occurring in a given pollen spectrum, when the taxa assemblage is known. The concept of co-occurrence is used to provide a greater amount of information to compensate for difficulties in the identification of pollen grains, allowing a better interpretation when there is little diversity in the pollen assemblage. Results The method has been validated using a dataset of modern samples against existing methods of biome classification and remote sensing data. An application is proposed in which the new method is used to produce biomes for pollen data 6000 years ago. This confirms previous results showing an extension of the deciduous forest to the north, east and south, explained by milder winters in western and northern Europe, and cooler and wetter climate in the Mediterranean region. Conclusion The results show the new method to be efficient, reliable and flexible and to be an improvement over the previous method of biomization. They will be used to test simulations of earth system models running on periods with climate significantly different from the present day,... [ABSTRACT FROM AUTHOR]

Abstract The objective of the European Terrestrial Ecosystem Modelling Activity (ETEMA) was to address some of the major challenges in developing generalized models to examine responses of natural and seminatural ecosystems to environmental change at the regional to European scale. The approach described herein was to break down the totality of ecosystem functioning into its key components, each with its characteristic spatial and temporal scales. A conceptual framework was developed describing the configuration of these components as modules within a generalized simulation model. The framework describes the key inputs, outputs and state variables, their spatial and temporal contexts, and information flows between modules. The ‘backbone’ of the model is a system of nested timing loops corresponding to the disparate time scales at which different ecosystem processes occur. The framework is a theoretical construct into which ecosystem models at levels of complexity ranging from the very general to the highly detailed can be mapped, and thus provides a guide for development of models for novel, particularly regional-scale, applications. A number of subsystem studies of the major components of ecosystem functioning, i.e. modules of the conceptual framework, are briefly introduced herein. The general aim of the subsystem studies was to identify the key alternative formulations (as opposed to minor variants) and test these against observational data. The various subsystem studies concern planetary boundary layer–ecosystem interactions, ecosystem CO2 and H2O fluxes, vegetation physiology and phenology, biogeography and vegetation dynamics, detritus and SOM dynamics, soil moisture and human and natural disturbances and, as individual papers, they complete this special ETEMA issue. [ABSTRACT FROM AUTHOR]

1 The role of undisturbed tropical land ecosystems in the global carbon budget is not well understood. It has been suggested that interannual climate variability can affect the capacity of these ecosystems to store carbon in the short term. In this paper, we use a transient version of the Terrestrial Ecosystem Model (TEM) to estimate annual carbon storage in undisturbed Amazonian ecosystems during the period 1980-94, and to understand the underlying causes of the year-to-year variations in net carbon storage for this region. 2 We estimate that the total carbon storage in the undisturbed ecosystems of the Amazon Basin in 1980 was 127.6 Pg C, with about 94.3 Pg C in vegetation and 33.3 Pg C in the reactive pool of soil organic carbon. About 83% of the total carbon storage occurred in tropical evergreen forests. Based on our model's results, we estimate that, over the past 15 years, the total carbon storage has increased by 3.1 Pg C (+ 2%), with a 1.9Pg C (+2%) increase in vegetation carbon and a 1.2-Pg C (+4%) increase in reactive soil organic carbon. The modelled results indicate that the largest relative changes in net carbon storage have occurred in tropical deciduous forests, but that the largest absolute changes in net carbon storage have occurred in the moist and wet forests of the Basin. 3 Our results show that the strength of interannual variations in net carbon storage of undisturbed ecosystems in the Amazon Basin varies from a carbon source of 0.2 Pg C/year to a carbon sink of 0.7 Pg C/year. Precipitation, especially the amount received during the drier months, appears to be a major controller of annual net carbon storage in the Amazon Basin. Our analysis indicates further that changes in precipitation combine with changes in temperature to affect net carbon storage through influencing soil moisture and nutrient availability. 4 On average, our results suggest that the undisturbed Amazonian ecosystems accumulated 0.2 Pg C/year as a result of climate... [ABSTRACT FROM AUTHOR]