A new lab facility for measuring bidirectional reflectance/emittance distribution functions of soils and canopies

Recently, a laboratory measurement facility has been realized for assessing the anisotropic reflectance and emittance behaviour of soils, leaves and small canopies under controlled illumination conditions. The facility consists of an ASD FieldSpec 3 spectroradiometer covering the spectral range from 350 – 2500 nm at 1 nm spectral sampling interval. The spectroradiometer is deployed using a fiber optic cable with either a 1°, 8° or 25° instantaneous field of view (IFOV). These measurements can be used to assess the plant pigment (chlorophyll, xanthophyll, etc.) and non-pigment system (water, cellulose, lignin, nitrogen, etc.). The thermal emittance is measured using a NEC TH9100 Infrared Thermal Imager. It operates in a single band covering the spectral range from 8 – 14 mm with a resolution of 0.02 K. Images are 320 (H) by 240 (V) pixels with an IFOV of 1.2 mrad. A 1000 W Quartz Tungsten Halogen (QTH) lamp is used as illumination source, approximating the radiance distribution of the sun. This one is put at a fixed position during a measurement session. Multi-angular measurements are achieved by using a robotic positioning system allowing to perform either reflectance or emittance measurements over almost a complete hemisphere. The hemisphere can be sampled continuously between 0° and 80° from nadir and up to a few degrees from the hot-spot configuration (depending on the IFOV of the measurement device) for a backscattering target. Measurement distance to targets can be varied between 0.25 and 1 m, although with a distance of more than 0.6 m it is not possible to cover the full hemisphere. The goal is to infer the BRDF (bidirectional reflectance distribution function) and BTDF (bidirectional thermal distribution function) from these multi-angular measurements for various surface types (like soils, agricultural crops, small tree canopies and artificial objects) and surface roughness. The steering of the robotic arm and the reading of the spectroradiometer and the thermal camera are all fully automated

Peatlands and the carbon cycle: from local processes to global implications - a synthesis

Peatlands cover only 3% of the Earth's land surface but boreal and subarctic peatlands store about 15-30% of the world's soil carbon ( C) as peat. Despite their potential for large positive feedbacks to the climate system through sequestration and emission of greenhouse gases, peatlands are not explicitly included in global climate models and therefore in predictions of future climate change. In April 2007 a symposium was held in Wageningen, the Netherlands, to advance our understanding of peatland C cycling. This paper synthesizes the main findings of the symposium, focusing on (i) small-scale processes, (ii) C fluxes at the landscape scale, and (iii) peatlands in the context of climate change. The main drivers controlling most are related to some aspects of hydrology. Despite high spatial and annual variability in Net Ecosystem Exchange ( NEE), the differences in cumulative annual NEE are more a function of broad scale geographic location and physical setting than internal factors, suggesting the existence of strong feedbacks. In contrast, trace gas emissions seem mainly controlled by local factors. Key uncertainties remain concerning the existence of perturbation thresholds, the relative strengths of the CO2 and CH4 feedback, the links among peatland surface climate, hydrology, ecosystem structure and function, and trace gas biogeochemistry as well as the similarity of process rates across peatland types and climatic zones. Progress on these research areas can only be realized by stronger co-operation between disciplines that address different spatial and temporal scales

The Laegeren site: an augmented forest laboratory combining 3-D reconstruction and radiative transfer models for trait-based assessment of functional diversity

Given the increased pressure on forests and their diversity in the context of global change, new ways of monitoring diversity are needed. Remote sensing has the potential to inform essential biodiversity variables on the global scale, but validation of data and products, particularly in remote areas, is difficult. We show how radiative transfer (RT) models, parameterized with a detailed 3-D forest reconstruction based on laser scanning, can be used to upscale leaf-level information to canopy scale. The simulation approach is compared with actual remote sensing data, showing very good agreement in both the spectral and spatial domains. In addition, we compute a set of physiological and morphological traits from airborne imaging spectroscopy and laser scanning data and show how these traits can be used to estimate the functional richness of a forest at regional scale. The presented RT modeling framework has the potential to prototype and validate future spaceborne observation concepts aimed at informing variables of biodiversity, while the trait-based mapping of diversity could augment in situ networks of diversity, providing effective spatiotemporal gap filling for a comprehensive assessment of changes to diversity

Framing the concept of satellite remote sensing essential biodiversity variables: challenges and future directions

Although satellite-based variables have for long been expected to be key components to a unified and global biodiversity monitoring strategy, a definitive and agreed list of these variables still remains elusive. The growth of interest in biodiversity variables observable from space has been partly underpinned by the development of the essential biodiversity variable (EBV) framework by the Group on Earth Observations – Biodiversity Observation Network, which itself was guided by the process of identifying essential climate variables. This contribution aims to advance the development of a global biodiversity monitoring strategy by updating the previously published definition of EBV, providing a definition of satellite remote sensing (SRS) EBVs and introducing a set of principles that are believed to be necessary if ecologists and space agencies are to agree on a list of EBVs that can be routinely monitored from space. Progress toward the identification of SRS-EBVs will require a clear understanding of what makes a biodiversity variable essential, as well as agreement on who the users of the SRS-EBVs are. Technological and algorithmic developments are rapidly expanding the set of opportunities for SRS in monitoring biodiversity, and so the list of SRS-EBVs is likely to evolve over time. This means that a clear and common platform for data providers, ecologists, environmental managers, policy makers and remote sensing experts to interact and share ideas needs to be identified to support long-term coordinated actions

Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation

Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land–climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles

Climate sensitivity of shrub growth across the tundra biome

The tundra biome is experiencing rapid temperature increases that have been linked to a shift in tundra vegetation composition towards greater shrub dominance. Shrub expansion can amplify warming by altering the surface albedo, energy and water balance, and permafrost temperatures. To account for these feedbacks, global climate models must include realistic projections of vegetation dynamics, and in particular tundra shrub expansion, yet the mechanisms driving shrub expansion remain poorly understood. Dendroecological data consisting of multi-decadal time series of annual growth of shrub species provide a previously untapped resource to explore climate-growth relationships across the tundra biome. We analysed a dataset of approximately 42,000 annual growth records from 1821 individuals, comprising 25 species from eight genera, from 37 arctic and alpine sites. Our analyses demonstrate that the sensitivity of shrub growth to climate was (1) heterogeneous across the tundra biome, (2) greater at sites with higher soil moisture and (3) strongest for taller shrub species growing at the northern or upper elevational edge of their range. Across latitudinal gradients in the Arctic, climate sensitivity of growth was greatest at the boundary between low- and high-arctic vegetation zones, where permafrost conditions are changing and the majority of the global permafrost soil carbon pool is stored. Thus, in order to more accurately estimate feedbacks among shrub change, albedo, permafrost thaw, carbon storage and climate, the observed variation in climate-growth relationships of shrub species across the tundra biome will need to be incorporated into earth system models.JRC.H.3-Forest Resources and Climat