Lotte Korell

Understanding and predicting future plant biodiversity and productivity is critical for prioritizing global change mitigation, conservation, and restoration efforts. One major challenge is that we know remarkably little about how interspecific interactions may modulate the effects of global change factors on diversity and productivity. Here, we develop and test a synthetic conceptual framework about how different ‘biotic modulators’ (herbivory, plant–plant interactions, pathogens, mycorrhiza) can either amplify or mitigate the effects of global change drivers (nutrient and CO ₂ enrichment, changes in rainfall and temperature) on plant community biomass and diversity. We report that herbivores mitigated both biomass increases and diversity decline caused by different global change drivers, while plant competition did not significantly alter global change impacts due to mixed effects (both amplification and mitigation). Pathogens tended to function similarly to herbivores, while mycorrhiza both amplified and mitigated community responses. Our conceptual framework further identifies mechanisms by which species interactions can modify global change effects, provides new testable hypotheses, and identifies research gaps and future research directions. We conclude that plant consumers can be important agents for stabilizing plant productivity and safeguarding plant biodiversity in the Anthropocene, but that more research is urgently needed to understand the role of other biotic modulators.

Climate warming is one of the most pressing environmental challenges for plant populations, communities, and ecosystems on earth. Warming experiments are an important tool for establishing causal relationships between climate change and plant diversity responses. However, results from such experiments vary in direction and magnitude. We hypothesize that such variation arises from context‐dependent factors, such as the magnitude of the temperature manipulation, the study duration, the spatial grain of the analysis, the background climate in which the study was conducted, and the biodiversity metrics used. Here, we present a comprehensive synthesis of primary data from 42 warming experiments, mostly from tundra and grassland ecosystems. We examined how warming influenced composition and how responses of plant diversity varied at the alpha (= plot), beta (= plot‐to‐plot), and gamma (= site) scales. Context‐dependent factors explained some of the variation observed in responses across studies. Higher magnitudes of warming led to stronger declines in species richness at the alpha scale. Experimental warming led to stronger declines in species richness in plant communities with warmer background summer temperature (e.g., desert grasslands) compared to those in communities exposed to colder background summer temperatures (e.g., tundra communities). Warming decreased evenness at the local (alpha) scale, but increased evenness at the beta scale, indicating that replicate warming plots diverged in their abundance distribution over time. Warming changed the composition of plant communities, particularly through species turnover rather than in the nestedness component, suggesting that warming leads to novel species assemblages. Our study highlights that responses of terrestrial plant communities to warming depend on experimental methodology, environmental context, and the spatial grain of investigation.

Ecological data are increasingly collected by networks of collaborators using replicated designs and methods, which can significantly improve the quality and quantity of data throughout the ecological niche and geographic range of species or communities. The coordinated generation and management of data is critical for producing datasets (Standard Data Products) across multiple sites that can be used by different researchers, over extended time periods and for multiple purposes. We describe and use a Quality Assurance framework for the design, collection and production of reproducible Standard Data Products for distributed ecology projects. We identified six critical project elements of a Quality Assurance framework (QA1‐6) to produce ecological Standard Data Products with high immediate and future value. We applied the Quality Assurance framework to the Plantpopnet project as a case‐study. Plantpopnet is a coordinated distributed system for population macroecology using the model species Plantago lanceolata . We mapped Plantpopnet activities to the Quality Assurance Framework as follows: (QA1) Measurable objectives : research project objectives with data requirements, (QA2) Process control : governance policies, (QA3) Project specific procedures : model organism selection and data collection protocol, (QA4) Supporting production of high quality data : recruitment, retention and engagement of participants, (QA5) Data management : data management plan and reproducible data cleaning workflow, (QA6) Production and management of outputs : Standard Data Products and papers. Explicit use of Quality Assurance, project and data management tools together with standardised ecological methods facilitated the design, collection, maintenance and sustainability of high‐quality data products. We provide a Quality Assurance framework together with governance documents, code and data for a reproducible Standard Data Product. This framework supports a distributed funding model which can be sustainably applied to facilitate future research and applications of coordinated distributed ecology projects.

Aim: The Global Biodiversity Information Facility (GBIF) is the most prominent source of species occurrence data for modeling climate niches, but exhibits strong unevenness in its data coverage across different geographic regions. The impact of this spatial bias on the reliability of GBIF-based plant climate niches in Europe remains unexplored. This study aims to address this gap, and to investigate whether the targeted integration of additional atlas data can reduce the potential impact of the spatial bias. Location: Europe. Time period: 1950s - 2024 Major taxa studied: European grassland plant species. Methods: We analyzed the climate niches of a large number of grassland species, with diverse distribution patterns across Europe, based on a) GBIF and b) on an enriched version of GBIF with national atlas data from Eastern European countries (GBIF+), where data coverage is currently low in GBIF. We followed best practices in niche characterization, particularly by performing environmental subsampling. The accuracy in climate niche properties was determined by comparing niches based on GBIF and GBIF+ data with niches based on a careful implementation of expert range maps as reference dataset. We focused on niche optimum position and niche similarity. Additionally, we investigated how biogeographical indicators can predict variability in climate niche accuracy. Results: Most species exhibited reliable climate niche characterization using GBIF data, especially for widely distributed species. Yet, reliability decreased with continentality; that is, when species were primarily distributed in Eastern Europe. Integrating additional data did not significantly reduce this bias in niche characterization. Main conclusions: Despite the spatial bias in its records, GBIF can be used to reliably characterize the climate niches of many species in Europe if uneven sampling effort is accounted for. The laborious integration of additional data to address spatial bias does not yield the desired increase in niche reliability.

Understanding and predicting future plant biodiversity and productivity is critical for prioritizing global change mitigation, conservation, and restoration efforts. One major challenge is that we know remarkably little of how interspecific interactions may modulate the effects of global change factors on diversity and productivity. Here, we develop and test a synthetic conceptual framework about how different ‘biotic modulators’ (herbivory, plant-plant interactions, pathogens, mycorrhiza) can either amplify or mitigate the effects of global change drivers (nutrient and CO ₂ enrichment, changes in rainfall and temperature) on plant community biomass and diversity. We report that herbivores mitigated both biomass increment and diversity decline caused by different global change drivers, while plant competition did not significantly alter global change impacts due to mixed effects (both amplification and mitigation). Pathogens tended to function similarly to herbivores, while mycorrhiza both amplified and mitigated community responses. Our conceptual framework further identifies mechanisms by which species interactions can modify global change effects, provides new testable hypotheses, and identifies research gaps and future research directions. We conclude that plant consumers can be important agents stabilizing plant productivity and safeguarding plant biodiversity in the Anthropocene, while more research is urgently needed to understand the role of other biotic modulators.

Plants are consumed by a variety of organisms, including herbivores and pathogens, which significantly impact plant biomass, diversity, community composition, and ecosystem functioning. While the impacts of vertebrate herbivores are well established, the effects of consumer groups such as insect herbivores, mollusks, and fungal pathogens on plant communities are less clear and remain understudied in many systems. Existing evidence of how they affect plant biomass, diversity, and community composition is mixed, and most studies have focused on individual consumer groups in isolation. However, different consumer groups interact with each other, directly or indirectly, in ways that alter their impacts on plants, and the consequences of these interactions for plant community structure and ecosystem function remain understudied. Further, consumer impacts vary across environmental gradients and likely depend on abiotic conditions such as climate, soil type, or elevation, and biotic conditions such as plant productivity, diversity, or community composition. Existing studies testing the impacts of invertebrate herbivores and fungal pathogens on plant communities differ substantially in methodology, making generalities across large scales difficult. This calls for experimental approaches that implement standardized protocols across many sites. Here, we introduce and report on the methodology of a novel global research network, The Bug‐Network (BugNet), that implements standardized consumer‐reduction experiments across 5 continents and 18 countries in diverse, herbaceous‐ or shrub‐dominated ecosystems to investigate: (1) the influence of fungal pathogens, insect herbivores, and mollusks on plant diversity and ecosystem functioning, (2) interactions among these consumer groups, and (3) the abiotic and biotic drivers of context‐dependent consumer impacts. BugNet aims to advance a predictive understanding of plant‐consumer interactions in order to test fundamental ecological hypotheses and improve predictions of global change impacts on biodiversity and ecosystem functioning.

Individual plant size often determines the vital rates of growth, survival and reproduction. However, size can be measured in several ways (e.g. height, biomass, leaf length). There is no consensus on the best size metric for modelling vital rates in plants. Demographic datasets are expanding in geographic extent, leading to choices about how to represent size for the same species in multiple ecological contexts. If the choice of size variable varies among locations, inter‐population comparative demography increases in complexity. Here, we present a framework to perform size metric selection in large‐scale demographic studies. We highlight potential pitfalls and suggest methods applicable to diverse study organisms. We assessed the performance of five different size metrics for the perennial herb Plantago lanceolata , across 55 populations on three continents within its native and non‐native ranges, using the spatially replicated demographic dataset PlantPopNet. We compared the performance of each candidate size metric for four vital rates (growth, survival, flowering probability and reproductive output) using generalized linear mixed models. We ranked the candidate size metrics based on their overall performance (highest generalized R ² ) and homogeneity of performance across populations (lowest total magnitude of, and variance in, population‐level error). While all size variables performed well for modelling vital rates, the number of leaves (modelled as a discrete variable, without transformation) was selected as the best size metric, followed by leaf length. We show how to interrogate potential trade‐offs between overall explanatory power and homogeneity of predictions across populations in any organism. Synthesis . Size is an important determinant of vital rates. Using a dataset of unprecedented spatial extent, we find (a) consistent size‐based models of growth, survival and reproduction across native and non‐native populations of this cosmopolitan plant species and (b) that several tested size metrics perform similarly well. This is encouraging for large‐scale demographic studies and for comparative projects using different size metrics, as they may be robust to this methodological difference.

Anthropogenic biodiversity decline threatens the functioning of ecosystems and the many benefits they provide to humanity¹. As well as causing species losses in directly affected locations, human influence might also reduce biodiversity in relatively unmodified vegetation if far-reaching anthropogenic effects trigger local extinctions and hinder recolonization. Here we show that local plant diversity is globally negatively related to the level of anthropogenic activity in the surrounding region. Impoverishment of natural vegetation was evident only when we considered community completeness: the proportion of all suitable species in the region that are present at a site. To estimate community completeness, we compared the number of recorded species with the dark diversity-ecologically suitable species that are absent from a site but present in the surrounding region². In the sampled regions with a minimal human footprint index, an average of 35% of suitable plant species were present locally, compared with less than 20% in highly affected regions. Besides having the potential to uncover overlooked threats to biodiversity, dark diversity also provides guidance for nature conservation. Species in the dark diversity remain regionally present, and their local populations might be restored through measures that improve connectivity between natural vegetation fragments and reduce threats to population persistence.

Climate and land‐use change are key drivers of global change. Full‐factorial field experiments in which both drivers are manipulated are essential to understand and predict their potentially interactive effects on the structure and functioning of grassland ecosystems. Here, we present 8 years of data on grassland dynamics from the Global Change Experimental Facility in Central Germany. On large experimental plots, temperature and seasonal patterns of precipitation are manipulated by superimposing regional climate model projections onto background climate variability. Climate manipulation is factorially crossed with agricultural land‐use scenarios, including intensively used meadows and extensively used (i.e., low‐intensity) meadows and pastures. Inter‐annual variation of background climate during our study years was high, including three of the driest years on record for our region. The effects of this temporal variability far exceeded the effects of the experimentally imposed climate change on plant species diversity and productivity, especially in the intensively used grasslands sown with only a few grass cultivars. These changes in productivity and diversity in response to alterations in climate were due to immigrant species replacing the target forage cultivars. This shift from forage cultivars to immigrant species may impose additional economic costs in terms of a decreasing forage value and the need for more frequent management measures. In contrast, the extensively used grasslands showed weaker responses to both experimentally manipulated future climate and inter‐annual climate variability, suggesting that these diverse grasslands are more resistant to climate change than intensively used, species‐poor grasslands. We therefore conclude that a lower management intensity of agricultural grasslands, associated with a higher plant diversity, can stabilize primary productivity under climate change.