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Peatland restoration is experiencing a global upsurge as a tool to protect and provide various ecosystem services. As the range of peatland types being restored diversifies, do previous findings present overly optimistic restoration expectations? In an eroding and restored upland peatland we assessed short-term (0–4 year) effects of restoration on ecohydrological functions. Restoration significantly reduced discharge from the site, transforming peat pans into pools. These retained surface water over half the time and were deeper during wet periods than before. In the surrounding haggs water tables stabilised, as drawdown during dry conditions reduced, increasing the saturated peat thickness. Despite these changes, there were no effects on photosynthesis, ecosystem respiration or dissolved organic carbon loads leaving the site. Soil respiration did not decrease as water tables rose, but methane emissions were higher from rewet pools. Restoration has had a dramatic effect on hydrology, however, consequent changes in other ecosystem functions were not measured in the 4 years after restoration. Whilst restoration is crucial in halting the expansion of degraded peatland areas, it is vital that practitioners and policymakers advocating for restoration are realistic about the expected outcomes and timescales over which these outcomes may manifest.

Natural flood management (NFM) methods work with natural processes to reduce flood risk, while often providing additional benefits such as water quality improvement or habitat provision. Increasingly, the activity of an animal—beavers—is recognised to potentially provide flow attenuation, along with multiple benefits for the environment and society, but there can also be associated challenges. We use Q‐Methodology to elicit and understand human perspectives of beavers and their potential role in flood management among communities living downstream of beavers at three sites in England (Cornwall, Yorkshire and the Forest of Dean). This is the first time a study has focused on downstream communities as the primary stakeholders. We identify diverse perspectives that exhibit a range of value judgements. We suggest a catchment‐based approach to beaver management and public engagement may facilitate deeper recognition of contextual perspectives in decision‐making and enable knowledge dissemination with communities. Further, we examine the relationship between beavers and other NFM methods through these perspectives. In doing so we identify features that relate to the unique element of relying on the natural behaviour of beavers for flood management, rather than human flood managers being the primary decision‐makers.

Quantifying the extent of soil erosion at a fine spatial resolution can be time consuming and costly; however, proximal remote sensing approaches to collect topographic data present an emerging alternative for quantifying soil volumes lost via erosion. Herein we compare terrestrial laser scanning (TLS), and both aerial (UAV) and ground-based (GP) SfM derived topography. We compare the cost-effectiveness and accuracy of both SfM techniques to TLS for erosion gully surveying in upland landscapes, treating TLS as a benchmark. Further, we quantify volumetric soil loss estimates from upland gullies using digital surface models derived by each technique and subtracted from an interpolated pre-erosion surface. Soil loss estimates from UAV and GP SfM reconstructions were comparable to those from TLS, whereby the slopes of the relationship between all three techniques were not significantly different from 1:1 line. Only for the TLS to GP comparison the intercept was significantly different from zero, showing that GP is more capable of measuring the volumes of very small erosion features. In terms of cost-effectiveness in data collection and processing time, both UAV and GP were comparable with the TLS on a per-site basis (13.4 and 8.2 person-hours versus 13.4 for TLS); however GP was less suitable for surveying larger areas (127 person-hours per ha-1 versus 4.5 for UAV and 3.9 for TLS). Annual repeat surveys using GP were capable of detecting mean vertical erosion change on peaty soils. These first published estimates of whole gully erosion rates (0.077 m a-1) suggest that combined erosion rates on gully floors and walls are around three times the value of previous estimates, which largely characterise wind and rainsplash erosion of gully walls.

In the UK, tree, hedgerow, and woodland (THaW) habitats are key havens for biodiversity and support many related ecosystem services. The UK is entering a period of agricultural policy realignment with respect to natural capital and climate change, meaning that now is a critical time to evaluate the distribution, resilience, and dynamics of THaW habitats. The fine‐grained nature of habitats like hedgerows necessitates mapping of these features at relatively fine spatial resolution—and freely available public archives of airborne laser scanning (LiDAR) data at <2 m spatial resolution offer a means of doing so within UK settings. The high cost of LiDAR prohibits use for regular monitoring of THaW change, but space‐borne sensors such as Sentinel‐1 Synthetic Aperture Radar (SAR at ca. 10 m resolution) can potentially meet this need once baseline distributions are established. We address two aims in this manuscript—(1) to rapidly quantify THaW across UK landscapes using LiDAR data and (2) to monitor canopy change intra‐ and inter‐annually using SAR data. We show that workflows applied to airborne LiDAR data can deliver THaW baselines at 2 m resolution, with positional accuracy of >90%. It was also possible to combine LiDAR mapping data and Sentinel‐1 SAR data to rapidly track canopy change through time (i.e., every 3 months) using, cloud‐based processing via Google Earth Engine. The resultant toolkit is also provided as an open‐access web app. The results highlight that whilst nearly 90% of the tallest trees (above 15 m) are captured within the National Forest Inventory (NFI) database only 50% of THaW with a canopy height range of 3–15 m are recorded. Current estimates of tree distribution neglect these finer‐grained features (i.e., smaller or less contiguous THaW canopies), which we argue will account for a significant proportion of landscape THaW cover. We address two aims in this manuscript—(1) to rapidly quantify THaW across UK landscapes using LiDAR data and (2) to monitor canopy change intra‐ and inter‐annually using SAR data.

Drought conditions are expected to increase in frequency and severity as the climate changes, representing a threat to carbon sequestered in peat soils. Downstream water treatment works are also at risk of regulatory compliance failures and higher treatment costs due to the increase in riverine dissolved organic carbon (DOC) often observed after droughts. More frequent droughts may also shift dominant vegetation in peatlands from Sphagnum moss to more drought-tolerant species. This paper examines the impact of drought on the production and treatability of DOC from four vegetation litters (Calluna vulgaris, Juncus effusus, Molinia caerulea and Sphagnum spp.) and a peat soil. We found that mild droughts caused a 39.6 % increase in DOC production from peat and that peat DOC that had been exposed to oxygen was harder to remove by conventional water treatment processes (coagulation/flocculation). Drought had no effect on the amount of DOC production from vegetation litters; however large variation was observed between typical peatland species (Sphagnum and Calluna) and drought-tolerant grassland species (Juncus and Molinia), with the latter producing more DOC per unit weight. This would therefore suggest the increase in riverine DOC often observed post-drought is due entirely to soil microbial processes and DOC solubility rather than litter layer effects. Long-term shifts in species diversity may, therefore, be the most important impact of drought on litter layer DOC flux, whereas pulses related to drought may be observed in peat soils and are likely to become more common in the future. These results provide evidence in support of catchment management which increases the resilience of peat soils to drought, such as ditch blocking to raise water tables.

Peatland ecosystem services include drinking water provision, flood mitigation, habitat provision and carbon sequestration. Dissolved organic carbon (DOC) removal is a key treatment process for the supply of potable water downstream from peat-dominated catchments. A transition from peat-forming Sphagnum moss to vascular plants has been observed in peatlands degraded by (a) land management, (b) atmospheric deposition and (c) climate change. Here within we show that the presence of vascular plants with higher annual above-ground biomass production leads to a seasonal addition of labile plant material into the peatland ecosystem as litter recalcitrance is lower. The net effect will be a smaller litter carbon pool due to higher rates of decomposition, and a greater seasonal pattern of DOC flux. Conventional water treatment involving coagulation-flocculation-sedimentation may be impeded by vascular plant-derived DOC. It has been shown that vascular plant-derived DOC is more difficult to remove via these methods than DOC derived from Sphagnum , whilst also being less susceptible to microbial mineralisation before reaching the treatment works. These results provide evidence that practices aimed at re-establishing Sphagnum moss on degraded peatlands could reduce costs and improve efficacy at water treatment works, offering an alternative to ‘end-of-pipe’ solutions through management of ecosystem service provision.

Across the semiarid ecosystems of the southwestern USA, there has been widespread encroachment of woody shrubs and trees including species into former grasslands. Quantifying vegetation biomass in such ecosystems is important because semiarid ecosystems are thought to play an important role in the global land carbon (C) sink, and changes in plant biomass also have implications for primary consumers and potential bioenergy feedstock. Oneseed juniper ( ) is common in desert grasslands and pinyon-juniper rangelands across the intermountain region of southwestern North America; however, there is limited information about the aboveground biomass (AGB) and sapwood area (SWA) for this species, causing uncertainties in estimates of C stock and transpiration fluxes. In this study, we report on canopy area (CA), stem diameter, maximum height, and biomass measurements from trees sampled from central New Mexico. Dry biomass ranged between 0.4 kg and 625 kg, and cross-sectional SWA was measured on n = 200 stems using image analysis. We found a strong linear relationship between CA and AGB (r = 0.96), with a similar slope to that observed in other juniper species, suggesting that this readily measured attribute is well suited for upscaling studies. There was a 9% bias between different approaches to measuring CA, indicating care should be taken to account for these differences to avoid systematic biases. We found equivalent stem diameter (ESD) was a strong predictor of biomass, but that existing allometric models underpredicted biomass in larger trees. We found SWA could be predicted from individual stem diameter with a power relationship, and that tree-level SWA should be estimated by summing the SWA predictions from individual stems rather than ESD. Our improved allometric models for support more accurate and robust measurements of C storage and transpiration fluxes in -dominated ecosystems.

Image‐based modeling, and more precisely, Structure from Motion (SfM) and Multi‐View Stereo (MVS), is emerging as a flexible, self‐service, remote sensing tool for generating fine‐grained digital surface models (DSMs) in the Earth sciences and ecology. However, drone‐based SfM + MVS applications have developed at a rapid pace over the past decade and there are now many software options available for data processing. Consequently, understanding of reproducibility issues caused by variations in software choice and their influence on data quality is relatively poorly understood. This understanding is crucial for the development of SfM + MVS if it is to fulfill a role as a new quantitative remote sensing tool to inform management frameworks and species conservation schemes. To address this knowledge gap, a lightweight multirotor drone carrying a Ricoh GR II consumer‐grade camera was used to capture replicate, centimeter‐resolution image datasets of a temperate, intensively managed grassland ecosystem. These data allowed the exploration of method reproducibility and the impact of SfM + MVS software choice on derived vegetation canopy height measurement accuracy. The quality of DSM height measurements derived from four different, yet widely used SfM‐MVS software—Photoscan, Pix4D, 3DFlow Zephyr, and MICMAC, was compared with in situ data captured on the same day as image capture. We used both traditional agronomic techniques for measuring sward height, and a high accuracy and precision differential GPS survey to generate independent measurements of the underlying ground surface elevation. Using the same replicate image dataset (n = 3) as input, we demonstrate that there are 1.7, 2.0, and 2.5 cm differences in RMSE (excluding one outlier) between the outputs from different SfM + MVS software using High, Medium, and Low quality settings, respectively. Furthermore, we show that there can be a significant difference, although of small overall magnitude between replicate image datasets (n = 3) processed using the same SfM + MVS software, following the same workflow, with a variance in RMSE of up to 1.3, 1.5, and 2.7 cm (excluding one outlier) for “High,” “Medium,” and “Low” quality settings, respectively. We conclude that SfM + MVS software choice does matter, although the differences between products processed using “High” and “Medium” quality settings are of small overall magnitude. In this manuscript, we show that while centimetric resolution aerial photographic data captured from a low‐flying multirotor drone can deliver new insights into the spatial heterogeneity of an intensively managed grassland sward, there are important, previously neglected, methodological uncertainties. We show that there are significant differences in the quality of the information derived from replicate image datasets and different image‐based modeling software. This understanding is crucial for the development of drone and image‐based modeling workflows if it is to fulfill a role as a new quantitative remote sensing tool to inform management frameworks and species conservation schemes.

Accurate and up‐to‐date land cover maps are vital for underpinning evidence‐based landscape management decision‐making. However, the technical skills required to extract tailored information about land cover dynamics from these open‐access geospatial data often limit their use by those making landscape management decisions. Using Dartmoor National Park as an example, we demonstrate an open‐source toolkit which uses open‐source software (QGIS and RStudio) to process freely available Sentinel‐2 and public LiDAR data sets to produce fine scale (10 m2 grain size) land cover maps. The toolbox has been designed for use by staff within the national park, for example, enabling land cover maps to be updated as required in the future. An area of 945 km2 was mapped using a trained random forest classifier following a classification scheme tailored to the needs of the national park. A 2019 land cover map had an overall user's accuracy of 79%, with 13 out of 17 land cover classes achieving greater than 70% accuracy. Spatially, accuracy was related via logistical regression to blue band surface reflectance in the spring and topographic slope derived from LiDAR (1 m resolution), with greater accuracy in steeper terrain and areas exhibiting higher blue reflectance. Between an earlier (2017–2019) and later (2019–2021) time frame, 8% of pixels changed, most of the change by area occurred in the most common classes. However, the largest proportional increase occurred in Upland Meadows, Lowland Meadows and Blanket Bog, all habitats subject to restoration efforts. Identifying areas of change enables future field work to be better targeted. We discuss the application of this mapping to land management within the Dartmoor national park and of the potential of tailored land cover and land cover change mapping, via this toolbox, to evidence‐based environmental decision‐making more widely. Customizable land cover & change toolbox for non‐specialists using open‐source data and software with a step‐by‐step guide: map what habitats are where in the area you manage, shown here for Dartmoor (England).

Eurasian beaver (Castor fiber) were nearly hunted to extinction but have recovered to occupy much of their former range. Beaver were extirpated from Great Britain c. 400 years ago but have recently been reintroduced. The River Otter catchment, Devon was the site of the first licensed wild release of beavers in England. With further releases being considered, there is a need to better understand population dynamics of this native, keystone species to inform conservation and management. Field signs were surveyed from 2015 to 2021. A semi‐automated territory detection method was adopted to estimate territory counts. A spatially explicit model was developed to estimate the ecological territory capacity of the catchment. Future territory expansion was modelled using logistic growth curves; initial growth rate was estimated from observed territory counts and the estimated territory capacity range was used to define the limiting value of the growth curve. Beaver territory removal was simulated, across a range of management intensities and start times, to determine potential impacts of translocation or lethal control upon population dynamics. Territory numbers increased from four to 18, inclusive of four additionally released individuals, during study period. In the absence of population management, the territory capacity of the catchment was estimated to range between 120 and 183; this may be reached between 2028 and 2057. Simulated territory removal, where territories were removed at a fixed rate from the sum of the estimated total population and the population increase for that year, demonstrated large uncertainties in predicted population responses. Simulations with territory removals >3/year all predicted potential population collapse. This finding emphasizes the need for caution when considering population management strategies; translocation of animals out of the catchment or culling should be considered only when populations are established and all alternatives have been considered. These results provide critical information for the expected rate and magnitude of beaver population change in the River Otter catchment. The methods provide a reproducible and generalizable approach for understanding beaver population change, which can inform policy on the reintroduction of beavers and the potential timing and intensity of future beaver population management. Beaver field signs were surveyed annually in the River Otter Catchment, England to map the distribution of beaver activity between 2015 and 2021. These data were used to estimate the territory expansion rate over the period which was then used to inform predictive models for future population change. A range of territory removal simulations were tested to predict the impact of potential future management strategies showing significant uncertainty in projected responses to population control.