Using climate-FVS to project landscape-level forest carbon stores for 100 years from field and LiDAR measures of initial conditions

Background

Forest resources supply a wide range of environmental services like mitigation of increasing levels of atmospheric carbon dioxide (CO2). As climate is changing, forest managers have added pressure to obtain forest resources by following stand management alternatives that are biologically sustainable and economically profitable. The goal of this study is to project the effect of typical forest management actions on forest C levels, given a changing climate, in the Moscow Mountain area of north-central Idaho, USA. Harvest and prescribed fire management treatments followed by plantings of one of four regionally important commercial tree species were simulated, using the climate-sensitive version of the Forest Vegetation Simulator, to estimate the biomass of four different planted species and their C sequestration response to three climate change scenarios.

Results

Results show that anticipated climate change induces a substantial decrease in C sequestration potential regardless of which of the four tree species tested are planted. It was also found that Pinus monticola has the highest capacity to sequester C by 2110, followed by Pinus ponderosa, then Pseudotsuga menziesii, and lastly Larix occidentalis.

Conclusions

Variability in the growth responses to climate change exhibited by the four planted species considered in this study points to the importance to forest managers of considering how well adapted seedlings may be to predicted climate change, before the seedlings are planted, and particularly if maximizing C sequestration is the management goal.     

MERIS and the red-edge position

The Medium Resolution Imaging Spectrometer (MERIS) is a payload component of Envisat-1. MERIS will be operated over land with a standard 15 band setting acquiring images with a 300 m spatial resolution. The red-edge position (REP) is a promising variable for deriving foliar chlorophyll concentration, which plays an important role in ecosystem processes. The objectives of this paper are: (1) to study which factors effect the REP of vegetation, (2) to study whether this REP can be derived from the MERIS standard band setting and (3) to show what REP represents at the scale of MERIS data. Two different data sets were explored for simulating the REP using MERIS bands: (1) simulated data using reflectance models and (2) airborne reflectance spectra of an agricultural area obtained by the airborne visible-infrared imaging spectrometer (AVIRIS). A “linear method”, assuming a straight slope of the reflectance spectrum around the midpoint of the slope, was a robust method for determining the REP and the MERIS bands at 665, 708.75, 753.75 and 778.75 nm could be used for applying the “linear method” for REP estimation. Results of the translation to the scale of MERIS data were very promising for applying MERIS at, for instance, the ecosystem level.     

Estimation of vegetation LAI from hyperspectral reflectance data: Effects of soil type and plant architecture

The retrieval of canopy biophysical variables is known to be affected by confounding factors such as plant type and background reflectance. The effects of soil type and plant architecture on the retrieval of vegetation leaf area index (LAI) from hyperspectral data were assessed in this study. In situ measurements of LAI were related to reflectances in the red and near-infrared and also to five widely used spectral vegetation indices (VIs). The study confirmed that the spectral contrast between leaves and soil background determines the strength of the LAI–reflectance relationship. It was shown that within a given vegetation species, the optimum spectral regions for LAI estimation were similar across the investigated VIs, indicating that the various VIs are basically summarizing the same spectral information for a given vegetation species. Cross-validated results revealed that, narrow-band PVI was less influenced by soil background effects (0.15 ≤ RMSE_cv ≤ 0.56). The results suggest that, when using remote sensing VIs for LAI estimation, not only is the choice of VI of importance but also prior knowledge of plant architecture and soil background. Hence, some kind of landscape stratification is required before using hyperspectral imagery for large-scale mapping of vegetation biophysical variables.     

Hyperspectral Pixel Unmixing via Spectral Band Selection and DC-Insensitive Singular Value Decomposition

This letter proposes a linear two-class hyperspectral pixel-unmixing algorithm that uses a band selection method to determine the best bands for pixel unmixing, low-pass prefiltering to remove high-frequency content, and a new version of the well-known singular value decomposition (SVD) method, which is insensitive to dc offsets (DCI-SVD). The proposed method is compared to the best level discrete wavelet transform approach for dimensionality reduction and least squares estimation and quadratic programming for unmixing (DWT-LSE-QP). The contributions of this letter are given as follows: (1) the band selection and filter selection algorithm and (2) the DCI-SVD algorithm. The dc insensitivity of the DCI-SVD method is proven, and simulation results using data from an analytical spectral device spectroradiometer show the efficacy of the proposed method and its superiority to the DWT-LSE-QP-based approach in the harder unmixing cases.     

A Location-centred, GIS-based Methodology for Estimating the Potential Impacts of Climate Change on Nature Reserves

Climate‐space models were constructed for 241 plant species from a sample of 86 nature reserve communities in Great Britain. Convex Hull climate envelopes were used to compile Mutual Climatic Range diagrams for selected species at each site. Present‐day and potential future climatic values over the next 100 years were compared against the climatic ranges of the species. A new Combined Envelope (a quadratic logistic regression probability surface constrained by a Convex Hull envelope) was used in a Climate Change Trend Analysis to determine future climatic suitability for species at each site (defined as a change in probability of species’ presence). Results indicate that the warming climate could favour a large proportion of plants on Scottish reserves (excepting montane species) and be less favourable for many plants on reserves in the south of England. The situation appears to be one of ‘no change’ for the majority of species on Welsh reserves and those further north in England.     

Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) technologies, which has widespread usage in industry, is also regarded as an ideal solution for automated agriculture because it fulfils the accuracy, reliability and availability requirements of industrial and agricultural applications. Agriculture applications use position, velocity and heading information for automated vehicle guidance and control to enhance the yield and quality of the crop, and in order to vary the application of fertilizer and herbicides according to soil heterogeneity at sub-field level. A loosely coupled GPS/INS integration algorithm known as “AhrsKf” is introduced for automated agriculture vehicle guidance and control utilizing MEMS inertial sensors and GPS. The AhrsKf can produce high-frequency attitude solutions for the vehicle’s guidance and control system, by using inputs from a single survey grade L1/L2 antenna, eliminating the need for the previous two antenna solutions. Given its agricultural application, the AhrsKf has been implemented with some specific design features to improve the accuracy of the attitude solution including, temperature compensation of the inertial sensors, and the aid of plough lines of farm lands. To evaluate the AhrsKf solution, two benchmarking tests have been conducted by using a three-antenna GPS system and NovAtel’s SPAN-CPT. The results have demonstrated that the AhrsKf solution is stable and can correctly track the movement of the farming vehicle.     

Implications of sampling design and sample size for national carbon accounting systems

Background  

Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources.     

Alignment between nationally determined contributions and the sustainable development goals for West Africa

The UN Sustainable Development Goals (SDGs) and the 2015 Paris Agreement are two of the most important policy frameworks of the twenty-first century. However, the alignment of national commitments linked to them has not yet been analysed for West African states. Such analyses are vital to avoid perverse outcomes if states assess targets and develop SDG implementation plans, and Nationally Determined Contributions (NDC) under the Paris Agreement, without integrated planning and cross-sectoral alignment. This article provides a situation analysis guided by the following questions: (a) Which priority sectors are mentioned in relation to adaptation and mitigation in West African NDCs? (b) Are the NDCs of West African states well aligned with the SDGs? (c) What are the co-benefits of NDCs in contributing towards the SDGs? and (d) How are West African states planning to finance actions in their NDCs? The study uses iterative content analysis to explore key themes for adaptation and mitigation within NDCs of 11 West African states and their alignment to selected SDGs. A national multi-stakeholder workshop was held in Ghana to examine the co-benefits of the NDCs in contributing towards the SDGs and their implementation challenges. Results show that agriculture and energy are priority sectors where NDCs have pledged significant commitments. The analysis displays good alignment between mitigation and adaptation actions proposed in NDCs and the SDGs. These represent opportunities that can be harnessed through integration into national sectoral policies. However, cross-sectoral discussions in Ghana identify significant challenges relating to institutional capacity, a lack of coordination among institutions and agencies, and insufficient resources in moving towards integrated implementation of national planning priorities to address successfully both NDC priorities and the SDGs.

Key policy insights

• Positive alignments between West African NDCs and SDGs present opportunities for mutual benefits that can advance national development via a more climate resilient pathway.

• NDCs of West African states can provide mutual benefits across the water–energy–food nexus, such as through climate-smart agriculture and low carbon energy technologies.

• Ghanaian multi-sectoral insights show the need to empower national coordinating bodies to overcome misalignments across different sectors.

     

A kite based atmospheric sounding system

A newly developed kite based atmospheric sounding system is described that can be deployed under a wide range of weather conditions. The Delta Kite system can be flown in wind speeds ranging from 4 to 25 ms^-1, while the exceptional lift capabilities of the kite allow several kilograms of payload to be attached to the kite and/or tether. In conjunction with its battery powered winch, the Delta Kite atmospheric sounding system is ideally suited to meteorological studies in remote locations where vehicle access may not be possible.