MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL.

Cerrado is the Brazilian neotropical savanna threatened by invasive African grasses. We aimed to quantify the impact of invasive Melinis minutiflora and Urochloa brizantha on the cover of different functional groups (native graminoids, forbs, shrubs) and the structure (bare soil and the cover of natives' and invasives' dead biomass) of regenerating plant communities. We hypothesized that the impact of invasives would be negative and more pronounced in the rainy period, given the great influence of seasonality in savannas. In three community types (non-invaded, invaded by M. minutiflora and invaded by U. brizantha) we evaluated the cover of functional groups and structural components by sampling 120 1 m 9 1 m plots, four times a year. Using the Cohen's D impact index, we showed that both invasive species reduced the cover of all native functional groups, decreased bare soil and increased total dead cover. Greatest effects occurred when M. minutiflora was present. M. minutiflora's impact on total graminoids varied from positive in the Early-Dry season to negative in the Mid-Dry season, while the negative impact of U. brizantha on bare soil became more pronounced from the dry to the rainy season. Differences in the impacts caused by the invasive species are probably due to the large biomass produced by M. minutiflora versus the fast colonization and soil occupancy by U. brizantha. Overall, invaded versus non-invaded communities differed in structure, as well as both invaded communities differed from each other. Our results demonstrate the need to control these species for conservation and restoration of Cerrado ecosystems.

Effective long-term management is needed to address the impacts of invasive alien species (IAS) that cannot be eradicated. We describe the fundamental characteristics of long-term management policies for IAS, diagnose a major shortcoming, and outline how to produce effective IAS management. Key international and transnational management policies conflate addressing IAS impacts with controlling IAS populations. This serious purpose–implementation gap can preclude the development of broader portfolios of interventions to tackle IAS impacts. We posit that IAS management strategies should directly address impacts via impact-based interventions, and we propose six criteria to inform the choice of these interventions. We review examples of interventions focused on tackling IAS impacts, including IAS control, which reveal the range of interventions available and their varying effectiveness in counteracting IAS impacts. As the impacts caused by IAS increase globally, stakeholders need to have access to a broader and more effective set of tools to respond.

Formulating effective management plans for addressing the impacts of invasive non-native species (INNS) requires the definition of clear priorities and tangible targets, and the recognition of the plurality of societal values assigned to these species. These tasks require a multi-disciplinary approach and the involvement of stakeholders. Here, we describe procedures to integrate multiple sources of information to formulate management priorities, targets, and high-level actions for the management of INNS. We follow five good-practice criteria: justified, evidence-informed, actionable, quantifiable, and flexible. We used expert knowledge methods to compile 17 lists of ecological, social, and economic impacts of lodgepole pines (Pinus contorta) and American mink (Neovison vison) in Chile and Argentina, the privet (Ligustrum lucidum) in Argentina, the yellow-jacket wasp (Vespula germanica) in Chile, and grasses (Urochloa brizantha and Urochloa decumbens) in Brazil. INNS plants caused a greater number of impacts than INNS animals, although more socio-economic impacts were listed for INNS animals than for plants. These impacts were ranked according to their magnitude and level of confidence on the information used for the ranking to prioritise impacts and assign them one of four high-level actions—do nothing, monitor, research, and immediate active management. We showed that it is possible to formulate management priorities, targets, and high-level actions for a variety of INNS and with variable levels of available information. This is vital in a world where the problems caused by INNS continue to increase, and there is a parallel growth in the implementation of management plans to deal with them.

With the aim to identify future challenges and opportunities in vegetation science, we brought together a group of 22 early career vegetation scientists from diverse backgrounds to perform a horizon scan. In this contribution, we present a selection of 15 topics that were ranked by participants as the most emergent and impactful for vegetation science in the face of global change. We highlight methodological tools that we expect will play a critical role in resolving emerging issues by providing ways to unveil new aspects of plant community dynamics and structure. These tools include next generation sequencing, plant spectral imaging, process‐based species distribution models, resurveying studies and permanent plots. Further, we stress the need to integrate long‐term monitoring, the study of novel ecosystems, below‐ground traits, pollination interactions and global networks of near‐surface microclimate data at fine spatio‐temporal resolutions to fully understand and predict the impacts of climate change on vegetation dynamics. We also emphasize the need to integrate traditional forms of knowledge and a diversity of stakeholders into research, teaching, management and policy‐making to advance the field of vegetation science. The conclusions reached by this horizon scan naturally reflect the background, expertise and interests of a representative pool of early career vegetation scientists, which should serve as basis for future developments in the field.

Invasive Alien Species (IAS) threaten biodiversity, ecosystem functions and services, modify landscapes and impose costs to national economies. Management efforts are underway globally to reduce these impacts, but little attention has been paid to optimising the use of the scarce available resources when IAS are impossible to eradicate, and therefore population reduction and containment of their advance are the only feasible solutions. CONTAIN, a three-year multinational project involving partners from Argentina, Brazil, Chile and the UK, started in 2019. It develops and tests, via case study examples, a decision-making toolbox for managing different problematic IAS over large spatial extents. Given that vast areas are invaded, spatial prioritisation of management is necessary, often based on sparse data. In turn, these characteristics imply the need to make the best decisions possible under likely heavy uncertainty. Our decision-support toolbox will integrate the following components: (i) the relevant environmental, social, cultural, and economic impacts, including their spatial distribution; (ii) the spatio-temporal dynamics of the target IAS (focusing on dispersal and population recovery); (iii) the relationship between the abundance of the IAS and its impacts; (iv) economic methods to estimate both benefits and costs to inform the spatial prioritisation of cost-effective interventions. To ensure that our approach is relevant for different contexts in Latin America, we are working with model species having contrasting modes of dispersal, which have large environmental and/or economic impacts, and for which data already exist (invasive pines, privet, wasps, and American mink). We will also model plausible scenarios for data-poor pine and grass species, which impact local people in Argentina, Brazil and Chile. We seek the most effective strategic management actions supported by empirical data on the species’ population dynamics and dispersal that underpin reinvasion, and on intervention costs in a spatial context. Our toolbox serves to identify key uncertainties driving the systems, and especially to highlight gaps where new data would most effectively reduce uncertainty on the best course of action. The problems we are tackling are complex, and we are embedding them in a process of co-operative adaptive management, so that both researchers and managers continually improve their effectiveness by confronting different models to data. Our project is also building research capacity in Latin America by sharing knowledge/information between countries and disciplines (i.e., biological, social and economic), by training early-career researchers through research visits, through our continuous collaboration with other researchers and by training and engaging stakeholders via workshops. Finally, all these activities will establish an international network of researchers, managers and decision-makers. We expect that our lessons learned will be of use in other regions of the world where complex and inherently context-specific realities shape how societies deal with IAS.

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