Geodiversity—the diversity of abiotic features and processes of the Earth's surface and subsurface—is an increasingly used concept in ecological research. A growing body of scientific literature has provided evidence of positive links between geodiversity and biodiversity. These studies highlight the potential of geodiversity to improve our understanding of biodiversity patterns and to complement current biodiversity conservation practices and strategies. However, definitions of geodiversity in ecological research vary widely. This can hinder the progress of geodiversity–biodiversity research and make it difficult to synthesize findings across studies. We therefore call for greater awareness of how geodiversity is currently defined and for more consistent use of the term ‘geodiversity’ in biodiversity research.

The metabolome is the biochemical basis of plant form and function, but we know little about its macroecological variation across the plant kingdom. Here, we used the plant functional trait concept to interpret leaf metabolome variation among 457 tropical and 339 temperate plant species. Distilling metabolite chemistry into five metabolic functional traits reveals that plants vary on two major axes of leaf metabolic specialization-a leaf chemical defense spectrum and an expression of leaf longevity. Axes are similar for tropical and temperate species, with many trait combinations being viable. However, metabolic traits vary orthogonally to life-history strategies described by widely used functional traits. The metabolome thus expands the functional trait concept by providing additional axes of metabolic specialization for examining plant form and function.

Summary The plant metabolome encompasses the biochemical mechanisms through which evolutionary and ecological processes shape plant form and function 1,2 . However, while the metabolome should thus be an important component of plant life-history variation 3 , we know little about how it varies across the plant kingdom. Here, we use the plant functional trait concept 4 – a powerful framework for describing plant form and function 5–7 – to interpret leaf metabolome variation among 457 tropical and 339 temperate plant species. Distilling metabolite chemistry into five discriminant metabolic functional traits reveals that plants vary along two major axes of leaf metabolic specialization – a leaf chemical defense spectrum and an expression of leaf longevity. These axes are qualitatively consistent for tropical and temperate species, with many trait combinations being viable. However, axes of leaf metabolic specialization vary orthogonally to life-history strategies described by widely used functional traits 5–7 , while being at least equally important to them. Our findings question classical trait 6 and plant defense 8 theory that predicts relationships between the leaf chemical phenotype, plant productivity, and pace of life. Moreover, we show that metabolic functional traits describe unique dimensions of plant life-history variation that are complementary to, and independent from, those captured by existing plant functional traits.

ABSTRACT A shared goal within macroecology, biogeography and population ecology research is to understand biodiversity patterns and the processes driving them across spatial and taxonomic scales. A common approach to study macroecological patterns and processes involves developing and testing ecogeographical rules or hypotheses. The much-debated ‘abundant-centre’ hypothesis posits that species’ abundances are highest in their range centres and decline towards their range edges. We perform the largest global test of the hypothesis to date, on 3,675 species, using 6,055,549 abundance observations. Using meta-analytical approaches, we summarised species-level abundance–distance correlations exploring the effects of dispersal-related species traits on abundance–distance relationships. Overall, animals did not follow abundant-centre patterns, whereas plants tended to. Larger-bodied mammals were more likely to conform to abundant-centre patterns, as were mammals and freshwater fishes from higher latitudes. Perennial life cycles and large range sizes were significant predictors of abundant-centre patterns in plants. Trees and shrubs with larger seeds showed more support for abundant-centre patterns. Accounting for species dispersal improves models of abundant-centre patterns across geographic space. Assuming abundant-centre patterns represent optimal equilibria within nature, our findings suggest that abundant-centre relationships are not a general ecological phenomenon but tend to manifest only in species with higher dispersal capabilities.

Our world contains many ecosystems, from tropical forests to coral reefs to urban parks. Ecosystems help us in important ways, including cleaning our air and water, storing carbon, and producing food. People have been shaping most ecosystems for at least 12,000 years. Human impact has become so intense that many ecosystems are now threatened. That is why the United Nations has decided that the next 10 years are the Decade on Ecosystem Restoration. But what is ecosystem restoration and how do we do it? In this article, we will tell you why ecosystem restoration is important and why it can be difficult. We will explain how it can be done well, and give examples from a range of projects. Successful restoration must include local people and requires lots of data. Restoration should not always return ecosystems back to what they were like once before.

A major aim of ecology is to upscale attributes of individuals to understand processes at population, community and ecosystem scales. Such attributes are typically described using functional traits, that is, standardised characteristics that impact fitness via effects on survival, growth and/or reproduction. However, commonly used functional traits (e.g. wood density, SLA) are becoming increasingly criticised for not being truly mechanistic and for being questionable predictors of ecological processes. This Special Feature reviews and studies how the metabolome (i.e. the thousands of unique metabolites that underpin physiology) can enhance trait‐based ecology and our understanding of plant and ecosystem functioning. In this Editorial, we explore how the metabolome relates to plant functional traits, with reference to life‐history trade‐offs governing fitness between generations and plasticity shaping fitness within generations. We also identify solutions to challenges of acquiring, interpreting and contextualising metabolome data, and propose a roadmap for integrating the metabolome into ecology. We next summarise the seven studies composing the Special Feature, which use the metabolome to examine mechanisms behind plant community assembly, plant‐organismal interactions and effects of plants and soil micro‐organisms on ecosystem processes. Synthesis . We demonstrate the potential of the metabolome to improve mechanistic and predictive power in ecology by providing a high‐resolution coupling between physiology and fitness. However, applying metabolomics to ecological questions is currently limited by a lack of conceptual, technical and data frameworks, which needs to be overcome to realise the full potential of the metabolome for ecology.

Future cities are set to face ever increasing population and climate pressures, ecosystem services offered by urban forests have been recognised as providing significant mitigation for these pressures. Therefore, the ability to accurately quantify the extent and structure of urban forests, across large and highly dynamic cities, is vital for determining the value of services provided and to assess the effectiveness of policy to promote these important assets. Current inventory methods used in urban forestry are mostly reliant on plot networks measuring a range of structural and demographic metrics; however, limited sampling (spatially and temporally) cannot fully capture the dynamics and spatial heterogeneity of the urban matrix. The rapid increase in the availability of open-access remote sensing data and processing tools offers an opportunity for monitoring and assessment of urban forest structure that is synoptic and at high spatial and temporal resolutions. Here we present a framework to estimate urban forest structure that uses open-access data and software, is robust to differences in data sources, is reproducible and is transferable between cities. The workflow is demonstrated by estimating three metrics of 3D forest structure (canopy cover, canopy height and tree density) across the Greater London area (1577 km(2)). Random Forest was trained with open-access airborne LiDAR or iTree Eco inventory data, with predictor variables derived from Sentinel 2, climatic and topography data sets. Output were maps of forest structure at 100 m and 20 m resolution. Results indicate that forest structure can be accurately estimated across large urban areas; Greater London has a mean canopy cover of similar to 16.5% (RMSE 11-17%), mean canopy height of 8.1-15.0 m (RMSE 4.9-6.2 m) m and is home to similar to 4.6 M large trees (projected crown area >10 m(2)). Transferability to other cities is demonstrated using the UK city of Southampton, where estimates were generated from local and Greater London training data sets indicating application beyond geographic domains is feasible. The methods presented here can augment existing inventory practices and give city planners, urban forest managers and greenspace advocates across the globe tools to generate consistent and timely information to help assess and value urban forests.