Action to reduce anthropogenic impact on the environment and species within it will be most effective when targeted towards activities that have the greatest impact on biodiversity. To do this effectively we need to better understand the relative importance of different activities and how they drive changes in species’ populations. Here, we present a novel, flexible framework that reviews evidence for the relative importance of these drivers of change and uses it to explain recent alterations in species’ populations. We review drivers of change across four hundred species sampled from a broad range of taxonomic groups in the UK. We found that species’ population change (~1970–2012) has been most strongly impacted by intensive management of agricultural land and by climatic change. The impact of the former was primarily deleterious, whereas the impact of climatic change to date has been more mixed. Findings were similar across the three major taxonomic groups assessed (insects, vascular plants and vertebrates). In general, the way a habitat was managed had a greater impact than changes in its extent, which accords with the relatively small changes in the areas occupied by different habitats during our study period, compared to substantial changes in habitat management. Of the drivers classified as conservation measures, low-intensity management of agricultural land and habitat creation had the greatest impact. Our framework could be used to assess the relative importance of drivers at a range of scales to better inform our policy and management decisions. Furthermore, by scoring the quality of evidence, this framework helps us identify research gaps and needs.

a b s t r a c tEcological restoration frequently involves setting fixed species or habitat targets to be achieved by prescribed restoration activities or through natural processes. Where no reference systems exist for defining outcomes or where restoration is planned on a large spatial scale, a more 'open-ended' approach to defining outcomes may be appropriate. Such approaches require changes to the definition of goals and the design of monitoring and evaluation activities. We suggest that in open-ended projects restoration goals should be framed in terms of promoting natural processes, mobile landscape mosaics and improved ecosystem services. Monitoring can then focus on the biophysical processes that underpin the development of habitat mosaics and the provision of ecosystem services, on the way habitat mosaics change through time and on species that can indicate the changing landscape attributes of connectivity and scale. Stakeholder response should be monitored since an open-ended restoration approach is unusual and can encounter institutional and societal constraints. Evaluation should focus on reporting changing restoration impacts and benefits rather than on achieving a pre-defined concept of ecological success.

Species distribution atlases often rely on volunteer effort to achieve their desired coverage, an activity now typically discussed, at least in academia, under the general theme of “citizen science”. Such data, however, are rarely without complex biases, particularly with respect to the estimation of trends in species’ distributions over many decades. The data of the Botanical Society of Britain and Ireland (BSBI) are no exception to this, and both careful thought in data aggregation (spatial, temporal, and taxonomic) and appropriate modelling procedures are required to overcome these challenges. We discuss these issues, with a primary focus on the statistical models that have been put forward to adjust for such biases. Such models include the Telfer method, various “reporting rate” approaches based on generalised linear models, the frequency scaling using local occupancy (“Frescalo”) model, occupancy models, and spatial smoothing methods. In each case the strengths and limitations in relation to estimating trends from distribution data with important time-varying biases are assessed. Various properties of BSBI data, in particular the increasing numbers of records at fine spatial and temporal scales over the past century, coupled with a general lack of re-visits to sites at such finer scales and the time-varying biases previously mentioned, imply that methods that can be sensibly applied at coarser levels are likely to be most appropriate for estimating accurate long-term trends in distributions. We conclude that Frescalo, which can be seen as a type of occupancy model where an adjustment for overlooked species is made in relation to spatial rather than temporal replication, whilst simultaneously adjusting for variable regional effort, is currently the most sophisticated tool for achieving this. Although recording community-accepted adjustments to data collection practices may allow for a greater application of occupancy modelling or other approaches in the future, methods that seek accurate trends over the long-term are necessarily limited either to scales at which various properties of the data in hand are most likely to be unbiased, or at which the biases are well enough understood to be modelled accurately.

Restoration of degraded land is recognized by the international community as an important way of enhancing both biodiversity and ecosystem services, but more information is needed about its costs and benefits. In Cambridgeshire, U.K., a long-term initiative to convert drained, intensively farmed arable land to a wetland habitat mosaic is driven by a desire both to prevent biodiversity loss from the nationally important Wicken Fen National Nature Reserve (Wicken Fen NNR) and to increase the provision of ecosystem services. We evaluated the changes in ecosystem service delivery resulting from this land conversion, using a new Toolkit for Ecosystem Service Site-based Assessment (TESSA) to estimate biophysical and monetary values of ecosystem services provided by the restored wetland mosaic compared with the former arable land. Overall results suggest that restoration is associated with a net gain to society as a whole of $199 ha−1y−1, for a one-off investment in restoration of $2320 ha−1. Restoration has led to an estimated loss of arable production of $2040 ha−1y−1, but estimated gains of $671 ha−1y−1 in nature-based recreation, $120 ha−1y−1 from grazing, $48 ha−1y−1 from flood protection, and a reduction in greenhouse gas (GHG) emissions worth an estimated $72 ha−1y−1. Management costs have also declined by an estimated $1325 ha−1y−1. Despite uncertainties associated with all measured values and the conservative assumptions used, we conclude that there was a substantial gain to society as a whole from this land-use conversion. The beneficiaries also changed from local arable farmers under arable production to graziers, countryside users from towns and villages, and the global community, under restoration. We emphasize that the values reported here are not necessarily transferable to other sites.

A low‐intervention approach to restoration that also allows restoration outcomes to be framed as trajectories of ecosystem change can be described as “open‐ended” restoration. It is an approach which recognizes that long‐term ecosystem behavior involves continual change at small and large spatial and temporal scales. There are a number of situations in which it is appropriate to adopt an open‐ended approach to restoration including: in remote and large areas, where ecological limiting factors will be changed by future climates, where antecedent conditions cannot be replicated, where there are novel starting points for restoration, where restoration relies strongly on processes outside the restoration area, in inherently dynamic systems, where costs are high and where the public demands “wildness.” Where this approach is adopted managers need to explain the project and deal with public expectations and public risk. Monitoring biotic and abiotic components of the project are very important as an open‐ended approach does not equate to “abandon and ignore it.”