Institute of Ecology and Botany

The human impact on life on Earth has increased sharply since the 1970s, driven by the demands of a growing population with rising average per capita income. Nature is currently supplying more materials than ever before, but this has come at the high cost of unprecedented global declines in the extent and integrity of ecosystems, distinctness of local ecological communities, abundance and number of wild species, and the number of local domesticated varieties. Such changes reduce vital benefits that people receive from nature and threaten the quality of life of future generations. Both the benefits of an expanding economy and the costs of reducing nature's benefits are unequally distributed. The fabric of life on which we all depend-nature and its contributions to people-is unravelling rapidly. Despite the severity of the threats and lack of enough progress in tackling them to date, opportunities exist to change future trajectories through transformative action. Such action must begin immediately, however, and address the root economic, social, and technological causes of nature's deterioration.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Understanding the scale, location and nature conservation values of the lands over which Indigenous Peoples exercise traditional rights is central to implementation of several global conservation and climate agreements. However, spatial information on Indigenous lands has never been aggregated globally. Here, using publicly available geospatial resources, we show that Indigenous Peoples manage or have tenure rights over at least ~38 million km2 in 87 countries or politically distinct areas on all inhabited continents. This represents over a quarter of the world’s land surface, and intersects about 40% of all terrestrial protected areas and ecologically intact landscapes (for example, boreal and tropical primary forests, savannas and marshes). Our results add to growing evidence that recognizing Indigenous Peoples’ rights to land, benefit sharing and institutions is essential to meeting local and global conservation goals. The geospatial analysis presented here indicates that collaborative partnerships involving conservation practitioners, Indigenous Peoples and governments would yield significant benefits for conservation of ecologically valuable landscapes, ecosystems and genes for future generations. Land management and ownership by Indigenous Peoples are critical components of conservation strategies, but information on these has previously never been aggregated. Here, global data is compiled to show that Indigenous Peoples have tenure rights or manage a quarter of the world’s land area and 40% of all protected areas and intact ecosystems.

Abstract Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve complex fitting procedures and make several assumptions, in particular about the distribution of residual and random effects. Violations of these assumptions are common in real datasets, yet it is not always clear how much these violations matter to accurate and unbiased estimation. Here we address the consequences of violations in distributional assumptions and the impact of missing random effect components on model estimates. In particular, we evaluate the effects of skewed, bimodal and heteroscedastic random effect and residual variances, of missing random effect terms and of correlated fixed effect predictors. We focus on bias and prediction error on estimates of fixed and random effects. Model estimates were usually robust to violations of assumptions, with the exception of slight upward biases in estimates of random effect variance if the generating distribution was bimodal but was modelled by Gaussian error distributions. Further, estimates for (random effect) components that violated distributional assumptions became less precise but remained unbiased. However, this particular problem did not affect other parameters of the model. The same pattern was found for strongly correlated fixed effects, which led to imprecise, but unbiased estimates, with uncertainty estimates reflecting imprecision. Unmodelled sources of random effect variance had predictable effects on variance component estimates. The pattern is best viewed as a cascade of hierarchical grouping factors. Variances trickle down the hierarchy such that missing higher‐level random effect variances pool at lower levels and missing lower‐level and crossed random effect variances manifest as residual variance. Overall, our results show remarkable robustness of mixed‐effects models that should allow researchers to use mixed‐effects models even if the distributional assumptions are objectively violated. However, this does not free researchers from careful evaluation of the model. Estimates that are based on data that show clear violations of key assumptions should be treated with caution because individual datasets might give highly imprecise estimates, even if they will be unbiased on average across datasets.

Abstract Question: Is Rao's quadratic entropy a suitable measure of functional diversity if several traits are considered? Methods: It is checked whether Rao's quadratic entropy ( FD Q ) satisfies a priori criteria suggested by Mason et al. A real data set is used to show that there are often zeros in abundance distributions which maximize functional diversity. Results and Conclusion: FD Q fulfils all a priori criteria and it surpasses other proposed indices, because it includes species abundances and more than one trait. Therefore, it seems to be an improvement compared to measures of functional diversity that are currently available. An unexpected property of FD Q is that its value may decrease if species richness increases. The reason is that functional diversity is influenced by both species‐abundance based diversity and differences among species. Introduction of a new species into the community increases the species‐abundance based diversity, while it may decrease the average dissimilarity among species.

Effective policies to halt biodiversity loss require knowing which anthropogenic drivers are the most important direct causes. Whereas previous knowledge has been limited in scope and rigor, here we statistically synthesize empirical comparisons of recent driver impacts found through a wide-ranging review. We show that land/sea use change has been the dominant direct driver of recent biodiversity loss worldwide. Direct exploitation of natural resources ranks second and pollution third; climate change and invasive alien species have been significantly less important than the top two drivers. The oceans, where direct exploitation and climate change dominate, have a different driver hierarchy from land and fresh water. It also varies among types of biodiversity indicators. For example, climate change is a more important driver of community composition change than of changes in species populations. Stopping global biodiversity loss requires policies and actions to tackle all the major drivers and their interactions, not some of them in isolation.

There is compelling evidence that more diverse ecosystems deliver greater benefits to people, and these ecosystem services have become a key argument for biodiversity conservation. However, it is unclear how much biodiversity is needed to deliver ecosystem services in a cost-effective way. Here we show that, while the contribution of wild bees to crop production is significant, service delivery is restricted to a limited subset of all known bee species. Across crops, years and biogeographical regions, crop-visiting wild bee communities are dominated by a small number of common species, and threatened species are rarely observed on crops. Dominant crop pollinators persist under agricultural expansion and many are easily enhanced by simple conservation measures, suggesting that cost-effective management strategies to promote crop pollination should target a different set of species than management strategies to promote threatened bees. Conserving the biological diversity of bees therefore requires more than just ecosystem-service-based arguments.

The Brazilian Amazon is currently experiencing the world9s highest absolute rate of forest destruction and is likely to suffer even greater degradation in the future because of government plans to invest $40 billion from 2000 to 2007 in dozens of major new highways and infrastructure projects. We developed two computer models that integrate spatial data on deforestation, logging, mining, highways and roads, navigable rivers, vulnerability to wildfires, protected areas, and existing and planned infrastructure projects, in an effort to predict the condition of Brazilian Amazonian forests by the year 2020. Both models suggest that the region9s forests will be drastically altered by current development schemes and land-use trends over the next 20 years.

Abstract. Statistical measures of fidelity, i.e. the concentration of species occurrences in vegetation units, are reviewed and compared. The focus is on measures suitable for categorical data which are based on observed species frequencies within a vegetation unit compared with the frequencies expected under random distribution. Particular attention is paid to Bruelheide's u value. It is shown that its original form, based on binomial distribution, is an asymmetric measure of fidelity of a species to a vegetation unit which tends to assign comparatively high fidelity values to rare species. Here, a hypergeometric form of u is introduced which is a symmetric measure of the joint fidelity of species to a vegetation unit and vice versa. It is also shown that another form of the binomial u value may be defined which measures the asymmetric fidelity of a vegetation unit to a species. These u values are compared with phi coefficient, chi‐square, G statistic and Fisher's exact test. Contrary to the other measures, phi coefficient is independent of the number of relevés in the data set, and like the hypergeometric form of u and the chi‐square it is little affected by the relative size of the vegetation unit. It is therefore particularly useful when comparing species fidelity values among differently sized data sets and vegetation units. However, unlike the other measures it does not measure any statistical significance and may produce unreliable results for small vegetation units and small data sets. The above measures, all based on the comparison of observed/expected frequencies, are compared with the categorical form of the Dufrêne‐Legendre Indicator Value Index, an index strongly underweighting the fidelity of rare species. These fidelity measures are applied to a data set of 15 989 relevés of Czech herbaceous vegetation. In a small subset of this data set which simulates a phytosociological table, we demonstrate that traditional table analysis fails to determine diagnostic species of general validity in different habitats and large areas. On the other hand, we show that fidelity calculations used in conjunction with large data sets can replace expert knowledge in the determination of generally valid diagnostic species. Averaging positive fidelity values for all species within a vegetation unit is a useful approach to measure quality of delimination of the vegetation unit. We propose a new way of ordering species in synoptic species‐by‐relevé tables, using fidelity calculations.

Abstract Question: Is Rao's quadratic entropy a suitable measure of functional diversity if several traits are considered? Methods: It is checked whether Rao's quadratic entropy (FDQ) satisfies a priori criteria suggested by Mason et al. A real data set is used to show that there are often zeros in abundance distributions which maximize functional diversity. Results and Conclusion: FDQ fulfils all a priori criteria and it surpasses other proposed indices, because it includes species abundances and more than one trait. Therefore, it seems to be an improvement compared to measures of functional diversity that are currently available. An unexpected property of FDQ is that its value may decrease if species richness increases. The reason is that functional diversity is influenced by both species-abundance based diversity and differences among species. Introduction of a new species into the community increases the species-abundance based diversity, while it may decrease the average dissimilarity among species.

A list of plant species used for food in Hungary and among Hungarian ethnic groups of the Carpathian Basin during the 19th and 20th centuries was compiled from 71 ethnographic and ethnobotanical sources and a survey among contemporary Hungarian botanists. Species used as food, spice, beverage or occasional snacks were collected. Sources mention 236 plant species belonging to 68 families. Most wild fleshy fruits (mostly <em>Rosa</em>, <em>Ru</em><em>bus</em>, <em>Cornus</em>, <em>Ri</em><em>bes</em>, <em>Vaccinium </em>spp.), dry fruits and seeds (<em>Fagus</em>, <em>Quercus</em>, <em>Corylus</em>, <em>Castanea</em>, <em>Trapa </em>spp.), several green vegetables (e.g. <em>Rumex</em>, <em>Urtica</em>, <em>Humulus</em>, <em>Chenopodiaceae </em>spp., <em>Ranunculus ficaria</em>), bulbs and tubers (<em>Lathyrus tuberosus</em>, <em>Helianthus tuberosus</em>, <em>Chaerophyllum bulbosum</em>, <em>Allium </em>spp.) used for food in Europe, are also known to be consumed in Hungary. A characteristic feature of Hungarian plant use was the mass consumption of the underground parts of several marsh (e.g. <em>Typha</em>, <em>Phragmites</em>, <em>Sagittaria</em>, <em>Alisma</em>, <em>Butomus</em>, <em>Bolboschoenus </em>spp., as well as the endemic <em>Armoracia macrocarpa</em>) and steppe species (e.g. <em>Crambe tataria</em>, <em>Rumex pseudonatronatus</em>). Consuming wild food plants is still important among Hungarians living in Transylvania: even nowadays more than 40 species are gathered and used at some locations.

Agricultural landscape homogenization has detrimental effects on biodiversity and key ecosystem services. Increasing agricultural landscape heterogeneity by increasing seminatural cover can help to mitigate biodiversity loss. However, the amount of seminatural cover is generally low and difficult to increase in many intensively managed agricultural landscapes. We hypothesized that increasing the heterogeneity of the crop mosaic itself (hereafter "crop heterogeneity") can also have positive effects on biodiversity. In 8 contrasting regions of Europe and North America, we selected 435 landscapes along independent gradients of crop diversity and mean field size. Within each landscape, we selected 3 sampling sites in 1, 2, or 3 crop types. We sampled 7 taxa (plants, bees, butterflies, hoverflies, carabids, spiders, and birds) and calculated a synthetic index of multitrophic diversity at the landscape level. Increasing crop heterogeneity was more beneficial for multitrophic diversity than increasing seminatural cover. For instance, the effect of decreasing mean field size from 5 to 2.8 ha was as strong as the effect of increasing seminatural cover from 0.5 to 11%. Decreasing mean field size benefited multitrophic diversity even in the absence of seminatural vegetation between fields. Increasing the number of crop types sampled had a positive effect on landscape-level multitrophic diversity. However, the effect of increasing crop diversity in the landscape surrounding fields sampled depended on the amount of seminatural cover. Our study provides large-scale, multitrophic, cross-regional evidence that increasing crop heterogeneity can be an effective way to increase biodiversity in agricultural landscapes without taking land out of agricultural production.

Lichens are symbiotic organisms of fungi and algae or cyanobacteria. Lichen-forming fungi synthesize a great variety of secondary metabolites, many of which are unique. Developments in analytical techniques and experimental methods have resulted in the identification of about 1050 lichen substances (including those found in cultures). In addition to their role in lichen chemotaxonomy and systematics, lichen secondary compounds have several possible biological roles, including photoprotection against intense radiation, as well as allelochemical, antiviral, antitumor, antibacterial, antiherbivore, and antioxidant action. These compounds are also important factors in metal homeostasis and pollution tolerance of lichen thalli. Although our knowledge of the contribution of these extracellular products to the success of the lichen symbiosis has increased significantly in the last decades, their biotic and abiotic roles have not been entirely explored.

The search for predictions of species diversity across environmental gradients has challenged ecologists for decades. The humped-back model (HBM) suggests that plant diversity peaks at intermediate productivity; at low productivity few species can tolerate the environmental stresses, and at high productivity a few highly competitive species dominate. Over time the HBM has become increasingly controversial, and recent studies claim to have refuted it. Here, by using data from coordinated surveys conducted throughout grasslands worldwide and comprising a wide range of site productivities, we provide evidence in support of the HBM pattern at both global and regional extents. The relationships described here provide a foundation for further research into the local, landscape, and historical factors that maintain biodiversity.

Local biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15-91 years) collected across Europe, using a comprehensive dataset comprising ~6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe.

Abstract Aim Primary forests have high conservation value but are rare in Europe due to historic land use. Yet many primary forest patches remain unmapped, and it is unclear to what extent they are effectively protected. Our aim was to (1) compile the most comprehensive European‐scale map of currently known primary forests, (2) analyse the spatial determinants characterizing their location and (3) locate areas where so far unmapped primary forests likely occur. Location Europe. Methods We aggregated data from a literature review, online questionnaires and 32 datasets of primary forests. We used boosted regression trees to explore which biophysical, socio‐economic and forest‐related variables explain the current distribution of primary forests. Finally, we predicted and mapped the relative likelihood of primary forest occurrence at a 1‐km resolution across Europe. Results Data on primary forests were frequently incomplete or inconsistent among countries. Known primary forests covered 1.4 Mha in 32 countries (0.7% of Europe’s forest area). Most of these forests were protected (89%), but only 46% of them strictly. Primary forests mostly occurred in mountain and boreal areas and were unevenly distributed across countries, biogeographical regions and forest types. Unmapped primary forests likely occur in the least accessible and populated areas, where forests cover a greater share of land, but wood demand historically has been low. Main conclusions Despite their outstanding conservation value, primary forests are rare and their current distribution is the result of centuries of land use and forest management. The conservation outlook for primary forests is uncertain as many are not strictly protected and most are small and fragmented, making them prone to extinction debt and human disturbance. Predicting where unmapped primary forests likely occur could guide conservation efforts, especially in Eastern Europe where large areas of primary forest still exist but are being lost at an alarming pace.

Abstract The European Vegetation Archive ( EVA ) is a centralized database of European vegetation plots developed by the IAVS Working Group European Vegetation Survey. It has been in development since 2012 and first made available for use in research projects in 2014. It stores copies of national and regional vegetation‐ plot databases on a single software platform. Data storage in EVA does not affect on‐going independent development of the contributing databases, which remain the property of the data contributors. EVA uses a prototype of the database management software TURBOVEG 3 developed for joint management of multiple databases that use different species lists. This is facilitated by the SynBioSys Taxon Database, a system of taxon names and concepts used in the individual European databases and their corresponding names on a unified list of European flora. TURBOVEG 3 also includes procedures for handling data requests, selections and provisions according to the approved EVA Data Property and Governance Rules. By 30 June 2015, 61 databases from all European regions have joined EVA , contributing in total 1 027 376 vegetation plots, 82% of them with geographic coordinates, from 57 countries. EVA provides a unique data source for large‐scale analyses of European vegetation diversity both for fundamental research and nature conservation applications. Updated information on EVA is available online at http://euroveg.org/eva-database .

Abstract Aim The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats. Location Europe. Methods We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment.

Intact Forest Landscapes ( IFL s) are critical strongholds for the environmental services that they provide, not least for their role in climate protection. On the basis of information about the distributions of IFL s and Indigenous Peoples’ lands, we examined the importance of these areas for conserving the world's remaining intact forests. We determined that at least 36% of IFL s are within Indigenous Peoples’ lands, making these areas crucial to the mitigation action needed to avoid catastrophic climate change. We also provide evidence that IFL loss rates have been considerably lower on Indigenous Peoples’ lands than on other lands, although these forests are still vulnerable to clearing and other threats. World governments must recognize Indigenous Peoples’ rights, including land tenure rights, to ensure that Indigenous Peoples play active roles in decision‐making processes that affect IFL s on their lands. Such recognition is critical given the urgent need to reduce deforestation rates in the face of escalating climate change and global biodiversity loss.

Worldwide, human appropriation of ecosystems is disrupting plant-pollinator communities and pollination function through habitat conversion and landscape homogenisation. Conversion to agriculture is destroying and degrading semi-natural ecosystems while conventional land-use intensification (e.g. industrial management of large-scale monocultures with high chemical inputs) homogenises landscape structure and quality. Together, these anthropogenic processes reduce the connectivity of populations and erode floral and nesting resources to undermine pollinator abundance and diversity, and ultimately pollination services. Ecological intensification of agriculture represents a strategic alternative to ameliorate these drivers of pollinator decline while supporting sustainable food production, by promoting biodiversity beneficial to agricultural production through management practices such as intercropping, crop rotations, farm-level diversification and reduced agrochemical use. We critically evaluate its potential to address and reverse the land use and management trends currently degrading pollinator communities and potentially causing widespread pollination deficits. We find that many of the practices that constitute ecological intensification can contribute to mitigating the drivers of pollinator decline. Our findings support ecological intensification as a solution to pollinator declines, and we discuss ways to promote it in agricultural policy and practice.