A systematic literature review was undertaken to analyse the linkages between different biodiversity attributes and 11 ecosystem services. The majority of relationships between attributes and ecosystem services cited in the 530 studies were positive. For example, the services of water quality regulation, water flow regulation, mass flow regulation and landscape aesthetics were improved by increases in community and habitat area. Functional traits, such as richness and diversity, also displayed a predominantly positive relationship across the services, most commonly discussed for atmospheric regulation, pest regulation and pollination. A number of studies also discussed a positive correlation with stand age, particularly for atmospheric regulation. Species level traits were found to benefit a number of ecosystem services, with species abundance being particularly important for pest regulation, pollination and recreation, and species richness for timber production and freshwater fishing. Instances of biodiversity negatively affecting the examined ecosystem services were few in number for all ecosystem services, except freshwater provision. The review showed that ecosystem services are generated from numerous interactions occurring in complex systems. However, improving understanding of at least some of the key relationships between biodiversity and service provision will help guide effective management and protection strategies

There is no unified evidence base to help decision-makers understand how the multiple components of natural capital interact to deliver ecosystem services. We systematically reviewed 780 papers, recording how natural capital attributes (29 biotic attributes and 11 abiotic factors) affect the delivery of 13 ecosystem services. We develop a simple typology based on the observation that five main attribute groups influence the capacity of natural capital to provide ecosystem services, related to: A) the physical amount of vegetation cover; B) presence of suitable habitat to support species or functional groups that provide a service; C) characteristics of particular species or functional groups; D) physical and biological diversity; and E) abiotic factors that interact with the biotic factors in groups A–D. ‘Bundles’ of services can be identified that are governed by different attribute groups. Management aimed at maximising only one service often has negative impacts on other services and on biological and physical diversity. Sustainable ecosystem management should aim to maintain healthy, diverse and resilient ecosystems that can deliver a wide range of ecosystem services in the long term. This can maximise the synergies and minimise the trade-offs between ecosystem services and is also compatible with the aim of conserving biodiversity

Small unmanned aerial systems (UAS) have allowed the mapping of vegetation at very high spatial resolution, but a lack of standardisation has led to uncertainties regarding data quality. For reflectance measurements and vegetation indices (Vis) to be comparable between sites and over time, careful flight planning and robust radiometric calibration procedures are required. Two sources of uncertainty that have received little attention until recently are illumination geometry and the effect of flying height. This study developed methods to quantify and visualise these effects in imagery from the Parrot Sequoia, a UAV-mounted multispectral sensor. Change in illumination geometry over one day (14 May 2018) had visible effects on both individual images and orthomosaics. Average near-infrared (NIR) reflectance and NDVI in regions of interest were slightly lower around solar noon, and the contrast between shadowed and well-illuminated areas increased over the day in all multispectral bands. Per-pixel differences in NDVI maps were spatially variable, and much larger than average differences in some areas. Results relating to flying height were inconclusive, though small increases in NIR reflectance with height were observed over a black sailcloth tarp. These results underline the need to consider illumination geometry when carrying out UAS vegetation surveys.

Arctic tundra ecosystems are currently facing amplified rates of climate warming. Since these ecosystems store significant amounts of soil organic carbon, which can be mineralized to carbon dioxide (CO₂) and methane (CH₄), rising temperatures may cause increasing greenhouse gas fluxes to the atmosphere. To understand how net the ecosystem exchange (NEE) of CO₂ will respond to changing climatic and environmental conditions, it is necessary to understand the individual responses of the processes contributing to NEE. Therefore, this study aimed to partition NEE at the soil–plant–atmosphere interface in an arctic tundra ecosystem and to identify the main environmental drivers of these fluxes. NEE was partitioned into gross primary productivity (GPP) and ecosystem respiration (R_eco) and further into autotrophic (R_A) and heterotrophic respiration (R_H). The study examined CO₂ flux data collected during the growing season in 2015 using closed-chamber measurements in a polygonal tundra landscape in the Lena River Delta, northeastern Siberia. To capture the influence of soil hydrology on CO₂ fluxes, measurements were conducted at a water-saturated polygon center and a well-drained polygon rim. These chamber-measured fluxes were used to model NEE, GPP, R_eco, R_H, R_A, and net primary production (NPP) at the pedon scale (1–10 m) and to determine cumulative growing season fluxes. Here, the response of in situ measured R_A and R_H fluxes from permafrost-affected soils of the polygonal tundra to hydrological conditions have been examined. Although changes in the water table depth at the polygon center sites did not affect CO₂ fluxes from R_H, rising water tables were linked to reduced CO₂ fluxes from R_A. Furthermore, this work found the polygonal tundra in the Lena River Delta to be a net sink for atmospheric CO₂ during the growing season. The NEE at the wet, depressed polygon center was more than twice that at the drier polygon rim. These differences between the two sites were caused by higher GPP fluxes due to a higher vascular plant density and lower R_eco fluxes due to oxygen limitation under water-saturated conditions at the polygon center in comparison to the rim. Hence, soil hydrological conditions were one of the key drivers for the different CO₂ fluxes across this highly heterogeneous tundra landscape.

Peatland restoration projects are being employed worldwide as a form of climate change mitigation due to their potential for long-term carbon sequestration. Monitoring these environments (e.g., cover of keystone species) is therefore essential to evaluate success. However, existing studies have rarely examined peatland vegetation at fine scales due to its strong spatial heterogeneity and seasonal canopy development. The present study collected centimetre-scale multispectral Uncrewed Aerial Vehicle (UAV) imagery with a Parrot Sequoia camera (2.8 cm resolution; Parrot Drones SAS, Paris, France) in a temperate peatland over a complete growing season. Supervised classification algorithms were used to map the vegetation at the single-species level, and the Maximum Likelihood classifier was found to perform best at the site level (69% overall accuracy). The classification accuracy increased with the spatial resolution of the input data, and a large reduction in accuracy was observed when employing imagery of >11 cm resolution. Finally, the most accurate classifications were produced using imagery collected during the peak (July–August) or early growing season (start of May). These findings suggest that despite the strong heterogeneity of peatlands, these environments can be mapped at the species level using UAVs. Such an approach would benefit studies estimating peatland carbon emissions or using the cover of keystone species to evaluate restoration projects.