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Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait-environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.

The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming.

Previous studies of Eurasian grasslands have suggested that nutrient ratios, rather than absolute nutrient availabilities and associated productivity, may be driving plant species richness patterns. However, the underlying assumption that species occupy distinct niches along nutrient ratio gradients remains to be tested. We analysed plant community composition and nutrient status of 644 Eurasian wet grassland plots. The importance of nutrient ratios driving variation in species composition was analysed using ordination methods (DCA and CCA). Subsequently, we assessed the niche position and width along the most important nutrient ratio gradient [N:P] for each species. We found that the N:P ratio explained part of the variation in species composition independent from conventional explanatory variables. The N:P ratio explained less variation than soil moisture or pH, but more than productivity or the availability of N and P separately, highlighting its importance for grassland species composition. Species occupied distinct niches along the N:P gradient, and species' niche widths decreased toward extreme nutrient limitation. After correcting for niche position, there was no overall difference in niche width between endangered and non-endangered species. Surprisingly, endangered species with niche optima at the extreme P-limited end of the gradient had broader niches than their non-endangered counterparts. As species occupied distinct niches along a nutrient ratio gradient, future grassland conservation efforts may benefit from targeting changes in nutrient ratios, i.e. the balance between N and P, rather than only focussing on a general reduction in nutrient availability. However, what management interventions can be used for this purpose remains unclear.

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means., Competing Interests: The authors declare no conflict of interest.

During the last decade many electronic databases of vegetation plots were established in many countries around the world. These databases contain valuable phytosociological information assisting both governmental and NGO (Non-governmental organizations) agencies to formulate strategies and on-ground plans to manage and protect nature resources. This paper provides an account on aims, current status and perspectives of building of a vegetation database for the Central Region (Najd) of Saudi Arabia - the founding element of the Saudi Vegetation Database (SVD). The data stored by the database are sample plots (vegetation relevés) collected according to the field techniques of the Braun-Blanquet approach (lists of taxa accompanied by semi-quantitative cover assessment), and are accompanied by general vegetation characteristics such as vegetation layering and cover, information on life-form of the recorded species, geographical coordinates, altitude, soil typology, topography and many more. More than 2900 vegetation-plot records (relevés) have so far been collected in the Najd region; of these more than 2000 have already been stored using the Turboveg database platform. These field records cover many habitats such as depressions, wadis (dry river beds), agricultural lands, sand dunes, sabkhas, and ruderal habitats. The ecological information collected in the database is currently the largest set of vegetation data collated into a database in the Middle East. These data are of great importance for biodiversity studies in Saudi Arabia, since the region is recording a loss of biodiversity at a fast rate due to environmental problems such as global warming and land-use changes. We envisage that this database would catalyze further data collection on vegetation of the entire Arabian Peninsula, and shall serve as one of the most important datasets for classification and mapping of the vegetation of the Kingdom of Saudi Arabia.

The biodiversity-productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, showing that continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The value of biodiversity in maintaining commercial forest productivity alone-US$166 billion to 490 billion per year according to our estimation-is more than twice what it would cost to implement effective global conservation. This highlights the need for a worldwide reassessment of biodiversity values, forest management strategies, and conservation priorities., (Copyright © 2016, American Association for the Advancement of Science.)

The knowledge about potential climate change impacts on forests is continuously expanding and some changes in growth, drought induced mortality and species distribution have been observed. However despite a significant body of research, a knowledge and communication gap exists between scientists and non-scientists as to how climate change impact scenarios can be interpreted and what they imply for European forests. It is still challenging to advise forest decision makers on how best to plan for climate change as many uncertainties and unknowns remain and it is difficult to communicate these to practitioners and other decision makers while retaining emphasis on the importance of planning for adaptation. In this paper, recent developments in climate change observations and projections, observed and projected impacts on European forests and the associated uncertainties are reviewed and synthesised with a view to understanding the implications for forest management. Current impact assessments with simulation models contain several simplifications, which explain the discrepancy between results of many simulation studies and the rapidly increasing body of evidence about already observed changes in forest productivity and species distribution. In simulation models uncertainties tend to cascade onto one another; from estimating what future societies will be like and general circulation models (GCMs) at the global level, down to forest models and forest management at the local level. Individual climate change impact studies should not be uncritically used for decision-making without reflection on possible shortcomings in system understanding, model accuracy and other assumptions made. It is important for decision makers in forest management to realise that they have to take long-lasting management decisions while uncertainty about climate change impacts are still large. We discuss how to communicate about uncertainty - which is imperative for decision making - without diluting the overall message. Considering the range of possible trends and uncertainties in adaptive forest management requires expert knowledge and enhanced efforts for providing science-based decision support., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Evidence for declining populations of both wild and managed bees has raised concern about a potential global pollination crisis. Strategies to mitigate bee loss generally aim to enhance floral resources. However, we do not really know whether loss of preferred floral resources is the key driver of bee decline because accurate assessment of host plant preferences is difficult, particularly for species that have become rare. Here we examine whether population trends of wild bees in The Netherlands can be explained by trends in host plants, and how this relates to other factors such as climate change. We determined host plant preference of bee species using pollen loads on specimens in entomological collections that were collected before the onset of their decline, and used atlas data to quantify population trends of bee species and their host plants. We show that decline of preferred host plant species was one of two main factors associated with bee decline. Bee body size, the other main factor, was negatively related to population trend, which, because larger bee species have larger pollen requirements than smaller species, may also point toward food limitation as a key factor driving wild bee loss. Diet breadth and other potential factors such as length of flight period or climate change sensitivity were not important in explaining twentieth century bee population trends. These results highlight the species-specific nature of wild bee decline and indicate that mitigation strategies will only be effective if they target the specific host plants of declining species.