Leaf trait plasticity reveals interactive effects of temporally disjunct grazing and warming on plant communities.

Changes in climate and grazing intensity influence plant-community compositions and their functional structure. Yet, little is known about their possible interactive effects when climate change mainly has consequences during the growing season and grazing occurs off growing season (dormant season grazing). We examined the contribution of trait plasticity to the immediate responses in the functional structure of plant community due to the interplay between these two temporally disjunct drivers. We conducted a field experiment in the northern Mongolian steppe, where climate was manipulated by open-top chambers (OTCs) for two growing seasons, increasing temperature and decreasing soil moisture (i.e., increased aridity), and grazing was excluded for one dormant season between these two growing seasons. We calculated the community-weighted mean (CWM) and the functional diversity (FD) of six leaf traits. Based on a variance partitioning approach, we evaluated how much of the responses in CWM and FD to OTCs and dormant season grazing occur through plasticity. The interactive effect of OTCs and the dormant season grazing were detected only after considering the role of trait plasticity. Overall, OTCs influenced the responses in CWM more than in FD, but the effects of OTCs were much less pronounced where dormant season grazing occurred. Thus, warming (together with decreased soil moisture) and the elimination of dormant season grazing could interact to impact the functional trait structure of plant communities through trait plasticity. Climate change effects should be considered in the context of altered land use, even if temporally disjunct.

Widespread homogenization of plant communities in the Anthropocene.

Native biodiversity decline and non-native species spread are major features of the Anthropocene. Both processes can drive biotic homogenization by reducing trait and phylogenetic differences in species assemblages between regions, thus diminishing the regional distinctiveness of biotas and likely have negative impacts on key ecosystem functions. However, a global assessment of this phenomenon is lacking. Here, using a dataset of >200,000 plant species, we demonstrate widespread and temporal decreases in species and phylogenetic turnover across grain sizes and spatial extents. The extent of homogenization within major biomes is pronounced and is overwhelmingly explained by non-native species naturalizations. Asia and North America are major sources of non-native species; however, the species they export tend to be phylogenetically close to recipient floras. Australia, the Pacific and Europe, in contrast, contribute fewer species to the global pool of non-natives, but represent a disproportionate amount of phylogenetic diversity. The timeline of most naturalisations coincides with widespread human migration within the last ~500 years, and demonstrates the profound influence humans exert on regional biotas beyond changes in species richness.

Temperature and pH define the realised niche space of arbuscular mycorrhizal fungi.

The arbuscular mycorrhizal (AM) fungi are a globally distributed group of soil organisms that play critical roles in ecosystem function. However, the ecological niches of individual AM fungal taxa are poorly understood. We collected > 300 soil samples from natural ecosystems worldwide and modelled the realised niches of AM fungal virtual taxa (VT; approximately species-level phylogroups). We found that environmental and spatial variables jointly explained VT distribution worldwide, with temperature and pH being the most important abiotic drivers, and spatial effects generally occurring at local to regional scales. While dispersal limitation could explain some variation in VT distribution, VT relative abundance was almost exclusively driven by environmental variables. Several environmental and spatial effects on VT distribution and relative abundance were correlated with phylogeny, indicating that closely related VT exhibit similar niche optima and widths. Major clades within the Glomeraceae exhibited distinct niche optima, Acaulosporaceae generally had niche optima in low pH and low temperature conditions, and Gigasporaceae generally had niche optima in high precipitation conditions. Identification of the realised niche space occupied by individual and phylogenetic groups of soil microbial taxa provides a basis for building detailed hypotheses about how soil communities respond to gradients and manipulation in ecosystems worldwide.

Applying the dark diversity concept to nature conservation.

Linking diversity to biological processes is central for developing informed and effective conservation decisions. Unfortunately, observable patterns provide only a proportion of the information necessary for fully understanding the mechanisms and processes acting on a particular population or community. We suggest conservation managers use the often overlooked information relative to species absences and pay particular attention to dark diversity (i.e., a set of species that are absent from a site but that could disperse to and establish there, in other words, the absent portion of a habitat-specific species pool). Together with existing ecological metrics, concepts, and conservation tools, dark diversity can be used to complement and further develop conservation prioritization and management decisions through an understanding of biodiversity relativized by its potential (i.e., its species pool). Furthermore, through a detailed understanding of the population, community, and functional dark diversity, the restoration potential of degraded habitats can be more rigorously assessed and so to the likelihood of successful species invasions. We suggest the application of the dark diversity concept is currently an underappreciated source of information that is valuable for conservation applications ranging from macroscale conservation prioritization to more locally scaled restoration ecology and the management of invasive species.

Large-scale dark diversity estimates: new perspectives with combined methods.

Large-scale biodiversity studies can be more informative if observed diversity in a study site is accompanied by dark diversity, the set of absent although ecologically suitable species. Dark diversity methodology is still being developed and a comparison of different approaches is needed. We used plant data at two different scales (European and seven large regions) and compared dark diversity estimates from two mathematical methods: species co-occurrence (SCO) and species distribution modeling (SDM). We used plant distribution data from the Atlas Florae Europaeae (50 × 50 km grid cells) and seven different European regions (10 × 10 km grid cells). Dark diversity was estimated by SCO and SDM for both datasets. We examined the relationship between the dark diversity sizes (type II regression) and the overlap in species composition (overlap coefficient). We tested the overlap probability according to the hypergeometric distribution. We combined the estimates of the two methods to determine consensus dark diversity and composite dark diversity. We tested whether dark diversity and completeness of site diversity (log ratio of observed and dark diversity) are related to various natural and anthropogenic factors differently than simple observed diversity. Both methods provided similar dark diversity sizes and distribution patterns; dark diversity is greater in southern Europe. The regression line, however, deviated from a 1:1 relationship. The species composition overlap of two methods was about 75%, which is much greater than expected by chance. Both consensus and composite dark diversity estimates showed similar distribution patterns. Both dark diversity and completeness measures exhibit relationships to natural and anthropogenic factors different than those exhibited by observed richness. In summary, dark diversity revealed new biodiversity patterns which were not evident when only observed diversity was examined. A new perspective in dark diversity studies can incorporate a combination of methods.

Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution dataset mergers, such as the one exemplified here, can serve as a baseline towards comprehensive species distribution datasets.

Pattern without bias: local-regional richness relationship revisited.

For decades, ecologists have been testing for species saturation by using regression analysis to determine the relationship between local and regional species richness. The cumulative result of scores of studies and meta-analyses has led to a general consensus that evidence of species saturation is relatively uncommon. However, the bias induced on the regression by the arbitrary choice of local and regional area has threatened to undermine this consensus and has even led to the proposal to abandon the regression method entirely. Nonetheless, the use of regression analysis to determine local-regional richness relationships continues. We performed a meta-analysis of almost 100 data sets using a log-ratio-based regression model that is free of the scale-induced bias inherent in more commonly used models. This reanalysis contradicts the general consensus: saturated relationships are at least as common as unsaturated patterns. However, a discouragingly large proportion of studies produce no discernable patterns at all. An explanation for such a plethora of species saturation patterns poses a challenge to our understanding of the processes that govern community assembly.