(Table 1) Bioclimatic subzones and soil characteristics along the Yamal Arctic Transect, northwestern Siberia

Sustainability of tundra vegetation under changing climate on the Yamal Peninsula, northwestern Siberia, home to the world's largest area of reindeer husbandry, is of crucial importance to the local native community. An integrated investigation is needed for better understanding of the effects of soils, climate change and grazing on tundra vegetation in the Yamal region. In this study we applied a nutrient-based plant community model - ArcVeg - to evaluate how two factors (soil organic nitrogen (SON) levels and grazing) interact to affect tundra responses to climate warming across a latitudinal climatic gradient on the Yamal Peninsula. Model simulations were driven by field-collected soil data and expected grazing patterns along the Yamal Arctic Transect (YAT), within bioclimate subzones C (high arctic), D (northern low arctic) and E (southern low arctic). Plant biomass and NPP (net primary productivity) were significantly increased with warmer bioclimate subzones, greater soil nutrient levels and temporal climate warming, while they declined with higher grazing frequency. Temporal climate warming of 2 °C caused an increase of 665 g/m**2 in total biomass at the high SON site in subzone E, but only 298 g/m**2 at the low SON site. When grazing frequency was also increased, total biomass increased by only 369 g/m**2 at the high SON site in contrast to 184 g/m**2 at the low SON site in subzone E. Our results suggest that high SON can support greater plant biomass and plant responses to climate warming, while low SON and grazing may limit plant response to climate change. In addition to the first order factors (SON, bioclimate subzones, grazing and temporal climate warming), interactions among these significantly affect plant biomass and productivity in the arctic tundra and should not be ignored in regional scale studies.

Sampling sites, sampled birds and plants of young larch plantations in Tokachi district, eastern Hokkaido, northern Japan, 2011

Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.

Enhanced seasonal CO_2 exchange caused by amplified plant productivity in northern ecosystems, link to model results

Atmospheric monitoring of high northern latitudes (> 40°N) has shown an enhanced seasonal cycle of carbon dioxide (CO2) since the 1960s but the underlying mechanisms are not yet fully understood. The much stronger increase in high latitudes compared to low ones suggests that northern ecosystems are experiencing large changes in vegetation and carbon cycle dynamics. Here we show that the latitudinal gradient of the increasing CO2 amplitude is mainly driven by positive trends in photosynthetic carbon uptake caused by recent climate change and mediated by changing vegetation cover in northern ecosystems. Our results emphasize the importance of climate-vegetation-carbon cycle feedbacks at high latitudes, and indicate that during the last decades photosynthetic carbon uptake has reacted much more strongly to warming than carbon release processes.

Isotopic composition of terrestrial plant waxes (dD and d13C of n-alkanes) of sediment core SO188_342 from the Northern Bay of Bengal for the last 18 ka

The Indian Summer Monsoon (ISM) is a major global climatic phenomenon. Long-term precipitation proxy records of the ISM, however, are often fragmented and discontinuous, impeding an estimation of the magnitude of precipitation variability from the Last Glacial to the present. To improve our understanding of past ISM variability, we provide a continuous reconstructed record of precipitation and continental vegetation changes from the lower Ganges-Brahmaputra-Meghna catchment and the Indo-Burman ranges over the last 18,000 years (18 ka). The records derive from a marine sediment core from the northern Bay of Bengal (NBoB), and are complemented by numerical model results of spatial moisture transport and precipitation distribution over the Bengal region. The isotopic composition of terrestrial plant waxes (dD and d13C of n-alkanes) are compared to results from an isotope-enabled general atmospheric circulation model (IsoCAM) for selected time slices (pre-industrial, mid-Holocene and Heinrich Stadial 1). Comparison of proxy and model results indicate that past changes in the dD of precipitation and plant waxes were mainly driven by the amount effect, and strongly influenced by ISM rainfall. Maximum precipitation is detected for the Early Holocene Climatic Optimum (EHCO; 10.5-6 ka BP), whereas minimum precipitation occurred during the Heinrich Stadial 1 (HS1; 16.9-15.4 ka BP). The IsoCAM model results support the hypothesis of a constant moisture source (i.e. the NBoB) throughout the study period. Relative to the pre-industrial period the model reconstructions show 20% more rain during the mid-Holocene (6 ka BP) and 20% less rain during the Heinrich Stadial 1 (HS1), respectively. A shift from C4-plant dominated ecosystems during the glacial to subsequent C3/C4-mixed ones during the interglacial took place. Vegetation changes were predominantly driven by precipitation variability, as evidenced by the significant correlation between the dD and d13C alkane records. When compared to other records across the ISM domain, precipitation and vegetation changes inferred from our records and the numerical model results provide evidence for a coherent regional variability of the ISM from the Last Glacial to the present.

Distribution models for mountain plant species: The value of elevation

The climatic conditions of mountain habitats are greatly influenced by topography. Large differences in microclimate occur with small changes in elevation, and this complex interaction is an important determinant of mountain plant distributions. In spite of this, elevation is not often considered as a relevant predictor in species distribution models (SDMs) for mountain plants. Here, we evaluated the importance of including elevation as a predictor in SDMs for mountain plant species. We generated two sets of SDMs for each of 73 plant species that occur in the Pacific Northwest of North America; one set of models included elevation as a predictor variable and the other set did not. AUC scores indicated that omitting elevation as a predictor resulted in a negligible reduction of model performance. However, further analysis revealed that the omission of elevation resulted in large over-predictions of species' niche breadths-this effect was most pronounced for species that occupy the highest elevations. In addition, the inclusion of elevation as a predictor constrained the effects of other predictors that superficially affected the outcome of the models generated without elevation. Our results demonstrate that the inclusion of elevation as a predictor variable improves the quality of SDMs for high-elevation plant species. Because of the negligible AUC score penalty for over-predicting niche breadth, our results support the notion that AUC scores alone should not be used as a measure of model quality. More generally, our results illustrate the importance of selecting biologically relevant predictor variables when constructing SDMs.

Plant Functional Type (PFT) map over Siberia derived from GlobCover 2005 dataset, link to dataset in NetCDF format

High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover data sets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing Earth system models. Earth system models also require specific land cover classification systems based on plant functional types (PFTs), rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover data sets against one another and with auxiliary data to identify key uncertainties that contribute to variability in PFT classifications that would introduce errors in Earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, vegetation continuous fields (MODIS VCFs) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover data set, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFT maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT data set, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to represent the water and carbon cycles in northern latitudes better. Updated land cover data sets are critical for improving and maintaining the relevance of Earth system models for assessing climate and human impacts on biogeochemistry and biophysics.

Tropical climate and vegetation simulations during the Heinrich event 1 using an Earth System Model of Intermediate Complexity (EMIC) - the University of Victoria Earth System-Climate Model (UVic ESCM)

Abrupt climate changes from 18 to 15 thousand years before present (kyr BP) associated with Heinrich Event 1 (HE1) had a strong impact on vegetation patterns not only at high latitudes of the Northern Hemisphere, but also in the tropical regions around the Atlantic Ocean. To gain a better understanding of the linkage between high and low latitudes, we used the University of Victoria (UVic) Earth System-Climate Model (ESCM) with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era, the Last Glacial Maximum (LGM), and a Heinrich-like event with two different climate backgrounds (interglacial and glacial). We calculated mega-biomes from the plant-functional types (PFTs) generated by the model to allow for a direct comparison between model results and palynological vegetation reconstructions. Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well with biome reconstructions of the modern and LGM time slices, respectively, except that our pre-industrial simulation predicted the dominance of grassland in southern Europe and our LGM simulation resulted in more forest cover in tropical and sub-tropical South America. The HE1-like simulation with a glacial climate background produced sea-surface temperature patterns and enhanced inter-hemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. We found that the cooling of the Northern Hemisphere caused a southward shift of those PFTs that are indicative of an increased desertification and a retreat of broadleaf forests in West Africa and northern South America. The mega-biomes from our HE1 simulation agreed well with paleovegetation data from tropical Africa and northern South America. Thus, according to our model-data comparison, the reconstructed vegetation changes for the tropical regions around the Atlantic Ocean were physically consistent with the remote effects of a Heinrich event under a glacial climate background.

Stable carbon isotopic analyses of n-alkanes and the calculated C4 plant-derived fractions in the dust samples

Atmospheric dust samples collected along a transect off the West African coast have been investigated for their lipid content and compound-specific stable carbon isotope compositions. The saturated hydrocarbon fractions of the organic solvent extracts consist mainly of long-chain n-alkanes derived from epicuticular wax coatings of terrestrial plants. Backward trajectories for each sampling day and location were calculated using a global atmospheric circulation model. The main atmospheric transport took place in the low-level trade-wind layer, except in the southern region, where long-range transport in the mid-troposphere occurred. Changes in the chain length distributions of the n-alkane homologous series are probably related to aridity, rather than temperature or vegetation type. The carbon preference of the leaf-wax n-alkanes shows significant variation, attributed to a variable contribution of fossil fuel- or marine-derived lipids. The effect of this nonwax contribution on the d13C values of the two dominant n-alkanes in the aerosols, n-C29 and n-C31 alkane, is, however, insignificant. Their d13C values were translated into a percentage of C4 vs. C3 plant type contribution, using a two-component mixing equation with isotopic end-member values from the literature. The data indicate that only regions with a predominant C4 type vegetation, i.e. the Sahara, the Sahel, and Gabon, supply C4 plant-derived lipids to dust organic matter. The stable carbon isotopic compositions of leaf-wax lipids in aerosols mainly reflect the modern vegetation type along their transport pathway. Wind abrasion of wax particles from leaf surfaces, enhanced by a sandblasting effect, is most probably the dominant process of terrigenous lipid contribution to aerosols.