The phenological state of vegetation significantly affects exchanges of heat, mass, and momentum between the Earth's surface and the atmosphere. Although current patterns can be estimated from satellites, we lack the ability to predict future trends in response to climate change. We searched the literature for a common set of variables that might be combined into an index to quantify the greenness of vegetation throughout the year. We selected as variables: daylength (photoperiod), evaporative demand (vapor pressure deficit), and suboptimal (minimum) temperatures. For each variable we set threshold limits, within which the relative phenological performance of the vegetation was assumed to vary from inactive (0) to unconstrained (1). A combined Growing Season Index (GSI) was derived as the product of the three indices. Ten-day mean GSI values for nine widely dispersed ecosystems showed good agreement (r>0.8) with the satellite-derived Normalized Difference Vegetation Index (NDVI). We also tested the model at a temperate deciduous forest by comparing model estimates with average field observations of leaf flush and leaf coloration. The mean absolute error of predictions at this site was 3 days for average leaf flush dates and 2 days for leaf coloration dates. Finally, we used this model to produce a global map that distinguishes major differences in regional phenological controls. The model appears sufficiently robust to reconstruct historical variation as well as to forecast future phenological responses to changing climatic conditions.

A generalized, bioclimatic index to predict foliar phenology in response to climate

Wise use of mires and peatlands

The impact of climate change on the treatability of dissolved organic matter (DOM) in upland water supplies: A UK perspective

Plant biomass is an important parameter for crop management and yield estimation. However, since biomass cannot be determined non-destructively, other plant parameters are used for estimations. In this study, plant height and hyperspectral data were used for barley biomass estimations with bivariate and multivariate models. During three consecutive growing seasons a terrestrial laser scanner was used to establish crop surface models for a pixel-wise calculation of plant height and manual measurements of plant height confirmed the results (R2 up to 0.98). Hyperspectral reflectance measurements were conducted with a field spectrometer and used for calculating six vegetation indices (VIs), which have been found to be related to biomass and LAI: GnyLi, NDVI, NRI, RDVI, REIP, and RGBVI. Furthermore, biomass samples were destructively taken on almost the same dates. Linear and exponential biomass regression models (BRMs) were established for evaluating plant height and VIs as estimators of fresh and dry biomass. Each BRM was established for the whole observed period and pre-anthesis, which is important for management decisions. Bivariate BRMs supported plant height as a strong estimator (R2 up to 0.85), whereas BRMs based on individual VIs showed varying performances (R2: 0.07–0.87). Fused approaches, where plant height and one VI were used for establishing multivariate BRMs, yielded improvements in some cases (R2 up to 0.89). Overall, this study reveals the potential of remotely-sensed plant parameters for estimations of barley biomass. Moreover, it is a first step towards the fusion of 3D spatial and spectral measurements for improving non-destructive biomass estimations.

Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass

http://eprints.gla.ac.uk/110120/1/110120.pdf

Restoration of blanket peatlands

Summary


In the UK, drainage for agricultural reclamation during the 19th and 20th centuries is responsible for an alteration of the ecological and hydrological functioning of peatlands, in turn, affecting a whole suite of ecosystem services. Today, initiatives are in place throughout the UK to reinstate this eco-hydrological functioning by blocking drainage ditches. Effects on ecosystem services remain unclear, as does the overlapping impact of climate change on peatland recovery.
This article uses a conceptual model to present the effects of restoration on ecosystem services, that is, water provision and quality, carbon storage, biodiversity, food and fibre provision and cultural services, both immediately after ditch blocking and in the few years post-restoration. The model is then applied in the context of Exmoor National Park, in South West England and used to perform a cost–benefit analysis of the restoration and monitoring programme, as these shallow peatlands are located in geographically marginal areas, and therefore more sensitive to climate change.
Past research indicates that some processes tend to return progressively to their predisturbance state, but whether the complete recovery of peatlands to functioning mires occurs after restoration remains unclear, partly due to the difference between the temporal and spatial scale at which processes occur (i.e. up to decadal) and are monitored (typically a few years).
Overall, on Exmoor, the long-term benefit of peatland restoration to some ecosystem services, such as a reduction in carbon losses and improvement of water storage and quality, has the potential to balance high financial investment.
Synthesis and applications. Gaining a better understanding of the effects of peatland restoration on ecosystem services provided is essential to assess the potential value of restoration projects. Using the case of the shallow peatlands of Exmoor National Park, located in geographically marginal areas in the UK and therefore more vulnerable to the effects of climate change, we find that there is potential for both the value of carbon storage and water provision to offset the costs of restoration in the long-term. Our results from Exmoor can provide ecological analogues of impending change further north.

https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2664.12039

Evaluating ecosystem goods and services after restoration of marginal upland peatlands in South-West England

New approaches to the restoration of shallow marginal peatlands.

Antecedent conditions control carbon loss and downstream water quality from shallow, damaged peatlands

Airborne laser scanning systems (Light Detection And Ranging, LiDAR) are very well suited to the study of landscape and vegetation structure over large extents. Spatially distributed measurements describing the three-dimensional character of landscape surfaces and vegetation architecture can be used to understand eco-geomorphic and ecohydrological processes, and this is particularly pertinent in peatlands given the increasing recognition that these landscapes provide a variety of ecosystem services (water provision, flood mitigation and carbon sequestration). In using LiDAR data for monitoring peatlands, it is important to understand how well peatland surface structures (with fine length scales) can be described. Our approach integrates two laser scanning technologies, namely terrestrial laser scanning (TLS) and airborne LiDAR surveys, to assess how effective airborne LiDAR is at measuring these fine-scale microtopographic ecohydrological structures. By combining airborne and TLS, we demonstrate an improved spatial understanding of the signal measured by the airborne LiDAR. Critically, results demonstrate that LiDAR digital surface models are subject to specific errors related to short-sward ecosystem structure, causing the vegetation canopy height and surface-drainage network depth to be underestimated. TLS is shown to be effective at describing these structures over small extents, allowing the information content and accuracy of airborne LiDAR to be understood and quantified more appropriately. These findings have important implications for the appropriate degree of confidence ecohydrologists can apply to such data when using them as a surrogate for field measurements. They also illustrate the need to couple LiDAR data with ground validation data in order to improve assessment of ecohydrological function in such landscapes. Copyright © 2014 John Wiley & Sons, Ltd.

/pdf/what-does-airborne-lidar-really-measure-in-upland-ecosystems-4ypmqhpy5x.pdf

Naomi Gatis

Papers

Evaluating ecosystem goods and services after restoration of marginal upland peatlands in South-West England

New approaches to the restoration of shallow marginal peatlands.

Antecedent conditions control carbon loss and downstream water quality from shallow, damaged peatlands

What does airborne LiDAR really measure in upland ecosystems

How does drainage alter the hydrology of shallow degraded peatlands across multiple spatial scales