Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Recent studies have demonstrated the usefulness of optical indices from hyperspectral remote sensing in the assessment of vegetation biophysical variables both in forestry and agriculture. Those indices are, however, the combined response to variations of several vegetation and environmental properties, such as Leaf Area Index (LAI), leaf chlorophyll content, canopy shadows, and background soil reflectance. Of particular significance to precision agriculture is chlorophyll content, an indicator of photosynthesis activity, which is related to the nitrogen concentration in green vegetation and serves as a measure of the crop response to nitrogen application. This paper presents a combined modeling and indices-based approach to predicting the crop chlorophyll content from remote sensing data while minimizing LAI (vegetation parameter) influence and underlying soil (background) effects. This combined method has been developed first using simulated data and followed by evaluation in terms of quantitative predictive capability using real hyperspectral airborne data. Simulations consisted of leaf and canopy reflectance modeling with PROSPECT and SAILH radiative transfer models. In this modeling study, we developed an index that integrates advantages of indices minimizing soil background effects and indices that are sensitive to chlorophyll concentration. Simulated data have shown that the proposed index Transformed Chlorophyll Absorption in Reflectance Index/Optimized Soil-Adjusted Vegetation Index (TCARI/OSAVI) is both very sensitive to chlorophyll content variations and very resistant to the variations of LAI and solar zenith angle. It was therefore possible to generate a predictive equation to estimate leaf chlorophyll content from the combined optical index derived from above-canopy reflectance. This relationship was evaluated by application to hyperspectral CASI imagery collected over corn crops in three experimental farms from Ontario and Quebec, Canada. The results presented here are from the L’Acadie, Quebec, Agriculture and AgriFood Canada research site. Images of predicted leaf chlorophyll content were generated. Evaluation showed chlorophyll variability over crop plots with various levels of nitrogen, and revealed an excellent agreement with ground truth, with a correlation of r 2 =.81 between estimated <s> BIB001 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> The biogeographic variation of life has predominantly been studied using taxonomy, but this focus is changing. There is a resurging interest in understanding patterns in the distribution not only of taxa but also of the traits those taxa possess. Patterns of trait variation shed light on fundamental questions in biology, including why organisms live where they do and how they will respond to environmental change. Technological advances such as environmental genomics place microbial ecology in a unique position to move trait-based biogeography forward. We anticipate that as trait-based biogeography continues to evolve, micro- and macroorganisms will be studied in concert, establishing a science that is informed by and relevant to all domains of life. <s> BIB002 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> The high vascular plant species richness of urbanized areas in Germany is biased towards species with specific functional traits or trait states, and towards common species, as shown in the preceding chapters. The last aspect of species diversity to be analyzed here is phylogenetic diversity: In terms of species richness, an assemblage of three Poaceae species seems as diverse as an assemblage of one Poaceae, one Asteraceae and one Fagaceae species; but the former assemblage appears much less diverse when considering their phylogenetic background: The three Poaceae species belong to one family and are thus closer related to each other than the species from the three families of Poaceae, Asteraceae and Fagaceae. Phylogenetic diversity, which measures the diversity of evolutionary relationships between species, reveals these underlying patterns, and so provides valuable information for species conservation and about mechanisms of species assembly (Vane-Wright et al. 1991). <s> BIB003 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> article Variation in the foliar chemistry of humid tropical forests is poorly understood, and airborne imaging spectroscopy could provide useful information at leaf and canopy scales. However, variation in canopy structure affects our ability to estimate foliar properties from airborne spectrometer data, yet these structural affects remain poorly quantified. Using leaf spectral (400-2500 nm) and chemical data collected from 162 Australian tropical forest species, along with partial least squares (PLS) analysis and canopy radiative transfer modeling, we determined the strength of the relationship between canopy reflectance and foliar properties under conditions of varying canopy structure. At the leaf level, chlorophylls, carotenoids and specific leaf area (SLA) were highly correlated with leaf spectral reflectance (r=0.90-0.91). Foliar nutrients and water were also well represented by the leaf spectra (r=0.79-0.85). When the leaf spectra were incorporated into the canopy radiative transfer simulations with an idealistic leaf area index (LAI)=5.0, correlations between canopy reflectance spectra and leaf properties increased in strength by 4-18%. The effects of random LAI (=3.0-6.5) variation on the retrieval of leaf properties remained minimal, particularly for pigments and SLA (r=0.92-0.93). In contrast, correlations between leaf nitrogen (N) and canopy reflectance estimates decreased from r=0.87 at constant LAI=5 to r=0.65 with randomly varying LAI=3.0-6.5. Progressive increases in the structural variability among simulated tree crowns had relatively little effect on pigment, SLA and water predictions. However, N and phosphorus (P) were more sensitive to canopy structural variability. Our modeling results suggest that multiple leaf chemicals and SLA can be estimated from leaf and canopy reflectance spectroscopy, and that the high-LAI canopies found in tropical forests enhance the signal via multiple scattering. Finally, the two factors we found to most negatively impact leaf chemical predictions from canopy reflectance were variation in LAI <s> BIB004 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Aim To analyse the effects of simultaneously using spatial and phylogenetic information in removing spatial autocorrelation of residuals within a multiple regression framework of trait analysis. Location Switzerland, Europe. Methods We used an eigenvector filtering approach to analyse the relationship between spatial distribution of a trait (flowering phenology) and environmental covariates in a multiple regression framework. Eigenvector filters were calculated from ordinations of distance matrices. Distance matrices were either based on pure spatial information, pure phylogenetic information or spatially structured phylogenetic information. In the multiple regression, those filters were selected which best reduced Moran’s I coefficient of residual autocorrelation. These were added as covariates to a regression model of environmental variables explaining trait <s> BIB005 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> For two decades, remotely sensed data from imaging spectrometers have been used to estimate non-pigment biochemical constituents of vegetation, including water, nitrogen, cellulose, and lignin. This interest has been motivated by the important role that these substances play in physiological processes such as photosynthesis, their relationships with ecosystem processes such as litter decomposition and nutrient cycling, and their use in identifying key plant species and functional groups. This paper reviews three areas of research to improve the application of imaging spectrometers to quantify non-pigment biochemical constituents of plants. First, we examine recent empirical and modeling studies that have advanced our understanding of leaf and canopy reflectance spectra in relation to plant biochemistry. Next, we present recent examples of how spectroscopic remote sensing methods are applied to characterize vegetation canopies, communities and ecosystems. Third, we highlight the latest developments in using imaging spectrometer data to quantify net primary production (NPP) over large geographic areas. Finally, we discuss the major challenges in quantifying non-pigment biochemical constituents of plant canopies from remotely sensed spectra. <s> BIB006 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Tree canopies play an enormous role in the maintenance of tropical forest diversity and ecosystem function, and are therefore central to conservation, management, and resource policy development in tropical regions. However, high-resolution mapping of tropical forest canopies is very difficult, because traditional field, airborne, and satellite measurements cannot resolve the number of canopy species, or particular species of interest, over the large regional scales commensurate with conservation goals and strategies. Newer technologies, such as imaging spectroscopy and light detection and ranging (lidar), are just now reaching performance levels that will allow monitoring of tropical forest diversity from the air, but the methods for applying these technologies are not yet ready. Here, we present concepts that combine chemical and spectral remote sensing perspectives to facilitate canopy diversity mapping. Using examples from our ongoing work in the Hawaiian Islands, we demonstrate how a new “airborne sp... <s> BIB007 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> article i nfo The remote detection of water stress in a citrus orchard was investigated using leaf-level measurements of chlorophyll fluorescence and Photochemical Reflectance Index (PRI) data, seasonal time-series of crown tem- perature and PRI, and high-resolution airborne imagery. The work was conducted in an orchard where a reg- ulated deficit irrigation (RDI) experiment generated a gradient in water stress levels. Stomatal conductance (Gs) and water potential (Ψ) were measured over the season on each treatment block. The airborne data consisted on thermal and hyperspectral imagery acquired at the time of maximum stress differences among treatments, prior to the re-watering phase, using a miniaturized thermal camera and a micro-hyperspectral imager on board an unmanned aerial vehicle (UAV). The hyperspectral imagery was acquired at 40 cm resolution and 260 spectral bands in the 400-885 nm spectral range at 6.4 nm full width at half maximum (FWHM) spectral resolution and 1.85 nmsampling interval,enablingthe identificationof pure crownsfor extractingradiance andreflectance hyperspectral spectra from each tree. The FluorMOD model was used to investigate the retrieval of chlorophyll fluorescence by applying the Fraunhofer Line Depth (FLD) principle using three spectral bands (FLD3), which demonstrated that fluorescence retrievalwas feasible with the configuration of the UAV micro-hyperspectral in- strument flown over the orchard. Results demonstrated the link between seasonal PRI and crown temperature acquired from instrumented trees and field measurements of stomatal conductance and water potential. The sensitivity of PRI and Tc-Ta time-series to water stress levels demonstrated a time delay of PRI vs Tc-Ta during the recovery phase after re-watering started. At the time of the maximum stress difference among treatment blocks, the airborneimagery acquired fromthe UAV platform demonstrated that the crown temperature yielded the best coefficient of determination for Gs (r 2 <s> BIB008 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> We describe a study using the ASIA-Eagle hyperspectral sensor to measure the spectral response of spring barley over an entire climate-controlled growing season and correlate those results with the results of 25 biophysical and biochemical parameters. The spectrum of each hyperspectral image was used to calculate a range of vegetation indices (VIs) that have been recorded in the literature. Furthermore, all combinations of the 252 spectral bands were tested to calculate a range of difference vegetation indices (VIs(xy)) and reflectance value indices (R(x)) at the central wavelength (x nm) of each band (R(x)). For all three index types we examined the relationship with the vegetation variables measured on the ground by using a cross-validation procedure. The relationship between the estimated and the measured canopy chlorophyll content (CCC) was (CV, covariance of variation). An was obtained when modelling leaf area index (LAI), chlorophyll content (Chl-SPAD) as well as leaf gravimetric water content (GWC)... <s> BIB009 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Patterns of tropical forest functional diversity express processes of ecological assembly at multiple geographic scales and aid in predicting ecological responses to environmental change. Tree canopy chemistry underpins forest functional diversity, but the interactive role of phylogeny and environment in determining the chemical traits of tropical trees is poorly known. Collecting and analyzing foliage in 2,420 canopy tree species across 19 forests in the western Amazon, we discovered (i) systematic, community-scale shifts in average canopy chemical traits along gradients of elevation and soil fertility; (ii) strong phylogenetic partitioning of structural and defense chemicals within communities independent of variation in environmental conditions; and (iii) strong environmental control on foliar phosphorus and calcium, the two rock-derived elements limiting CO2 uptake in tropical forests. These findings indicate that the chemical diversity of western Amazonian forests occurs in a regionally nested mosaic driven by long-term chemical trait adjustment of communities to large-scale environmental filters, particularly soils and climate, and is supported by phylogenetic divergence of traits essential to foliar survival under varying environmental conditions. Geographically nested patterns of forest canopy chemical traits will play a role in determining the response and functional rearrangement of western Amazonian ecosystems to changing land use and climate. <s> BIB010 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Variations in photosynthesis still cause substantial uncertainties in predicting photosynthetic CO2 uptake rates and monitoring plant stress. Changes in actual photosynthesis that are not related to greenness of vegetation are difficult to measure by reflectance based optical remote sensing techniques. Several activities are underway to evaluate the sun-induced fluorescence signal on the ground and on a coarse spatial scale using space-borne imaging spectrometers. Intermediate-scale observations using airborne-based imaging spectroscopy, which are critical to bridge the existing gap between small-scale field studies and global observations, are still insufficient. Here we present the first validated maps of sun-induced fluorescence in that critical, intermediate spatial resolution, employing the novel airborne imaging spectrometer HyPlant. HyPlant has an unprecedented spectral resolution, which allows for the first time quantifying sun-induced fluorescence fluxes in physical units according to the Fraunhofer Line Depth Principle that exploits solar and atmospheric absorption bands. Maps of sun-induced fluorescence show a large spatial variability between different vegetation types, which complement classical remote sensing approaches. Different crop types largely differ in emitting fluorescence that additionally changes within the seasonal cycle and thus may be related to the seasonal activation and deactivation of the photosynthetic machinery. We argue that sun-induced fluorescence emission is related to two processes: (i) the total absorbed radiation by photosynthetically active chlorophyll; and (ii) the functional status of actual photosynthesis and vegetation stress. <s> BIB011 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Terrestrial ecosystem and carbon cycle feedbacks will significantly impact future climate, but their responses are highly uncertain. Models and tipping point analyses suggest the tropics and arctic/boreal zone carbon-climate feedbacks could be disproportionately large. In situ observations in those regions are sparse, resulting in high uncertainties in carbon fluxes and fluxes. Key parameters controlling ecosystem carbon responses, such as plant traits, are also sparsely observed in the tropics, with the most diverse biome on the planet treated as a single type in models. We analyzed the spatial distribution of in situ data for carbon fluxes, stocks and plant traits globally and also evaluated the potential of remote sensing to observe these quantities. New satellite data products go beyond indices of greenness and can address spatial sampling gaps for specific ecosystem properties and parameters. Because environmental conditions and access limit in situ observations in tropical and arctic/boreal environments, use of space-based techniques can reduce sampling bias and uncertainty about tipping point feedbacks to climate. To reliably detect change and develop the understanding of ecosystems needed for prediction, significantly, more data are required in critical regions. This need can best be met with a strategic combination of remote and in situ data, with satellite observations providing the dense sampling in space and time required to characterize the heterogeneity of ecosystem structure and function. <s> BIB012 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Abstract Impacts of human civilization on ecosystems threaten global biodiversity. In a changing environment, traditional in situ approaches to biodiversity monitoring have made significant steps forward to quantify and evaluate BD at many scales but still, these methods are limited to comparatively small areas. Earth observation (EO) techniques may provide a solution to overcome this shortcoming by measuring entities of interest at different spatial and temporal scales. This paper provides a comprehensive overview of the role of EO to detect, describe, explain, predict and assess biodiversity. Here, we focus on three main aspects related to biodiversity − taxonomic diversity, functional diversity and structural diversity, which integrate different levels of organization − molecular, genetic, individual, species, populations, communities, biomes, ecosystems and landscapes. In particular, we discuss the recording of taxonomic elements of biodiversity through the identification of animal and plant species. We highlight the importance of the spectral traits (ST) and spectral trait variations (STV) concept for EO-based biodiversity research. Furthermore we provide examples of spectral traits/spectral trait variations used in EO applications for quantifying taxonomic diversity, functional diversity and structural diversity. We discuss the use of EO to monitor biodiversity and habitat quality using different remote-sensing techniques. Finally, we suggest specifically important steps for a better integration of EO in biodiversity research. EO methods represent an affordable, repeatable and comparable method for measuring, describing, explaining and modelling taxonomic, functional and structural diversity. Upcoming sensor developments will provide opportunities to quantify spectral traits, currently not detectable with EO, and will surely help to describe biodiversity in more detail. Therefore, new concepts are needed to tightly integrate EO sensor networks with the identification of biodiversity. This will mean taking completely new directions in the future to link complex, large data, different approaches and models. <s> BIB013 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Background and Aims ::: ::: Mapping the spatial variability of vine water status within a vineyard is necessary for the efficient management of irrigation water. The objective of this study was to determine whether estimates of remotely sensed leaf water potential (Ψrem) could be employed as a precise tool for scheduling irrigation at the irrigation sector level throughout the season. ::: Methods and Results ::: ::: Three irrigation treatments were applied in a 16-ha commercial vineyard to analyse the performance of the proposed methodology for monitoring regulated deficit irrigation strategies, and to evaluate the required frequency of the acquisition of thermal images for irrigation scheduling. An aircraft equipped with a thermal sensor flew over the vineyard throughout the season, and the averaged Ψrem of each irrigation sector was used as the irrigation trigger. The acquisition of about five or six Ψrem maps over the season is recommended. The starting date for acquiring thermal images depends on canopy vegetation size and on the difficulty of extracting pure vegetation pixels. The effect of acquiring thermal imagery on days after rainfall or with low vapour pressure deficits affected the estimation of Ψrem, and these constraints need to be considered for feasible irrigation purposes. ::: Conclusions ::: ::: Remotely sensed leaf water potential was successfully used as an irrigation trigger to adopt regulated deficit irrigation strategies without any negative effect on yield and wine composition. ::: Significance of the Study ::: ::: This study presented a promising and powerful method for scheduling irrigation throughout the season at vineyard level based on estimates of remotely sensed leaf water potential. <s> BIB014 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Abstract Environmental stress causes changes in leaves and the structure of plants. Although physiological adaptations to stress by plants have been explored, the effect of stress on the spectral properties in the thermal part of the electromagnetic spectrum (3–16 μm) has not yet been investigated. In this research two plant species (European beech, Fagus sylvatica and rhododendron, Rhododendron cf. catawbiense ) that both grow naturally under temperature limited conditions were selected, representing deciduous and evergreen plants respectively. Besides TIR spectra, Leaf Water Content (LWC) and cuticle thickness were measured as possible variables that can explain the changes in TIR spectra. The results demonstrated that both species, when exposed to either water or temperature stress, showed significant changes in their TIR spectra. The changes in TIR in response to stress were similar within a species, regardless of the stress imposed on them. However, changes in TIR spectra differed between species. For rhododendron emissivity in TIR increased under stress while for beech it decreased. Both species showed depletion of Leaf Water Content (LWC) under stress, ruling LWC out as a main cause for the change in the TIR spectra. Cuticle thickness remained constant for beech, but increased for rhododendron. This suggests that changes in emissivity may be linked to changes in the cuticle thickness and possibly the structure of cuticle. It is known that spectral changes in this region have a close connection with microstructure and biochemistry of leaves. We propose detailed measurements of these changes in the cuticle to analyze the effect of microstructure on TIR spectra. <s> BIB015 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Drought is an intermittent disturbance of the water cycle that profoundly affects the terrestrial carbon cycle. However, the response of the coupled water and carbon cycles to drought and the underlying mechanisms remain unclear. Here we provide the first global synthesis of the drought effect on ecosystem water use efficiency (WUE = gross primary production (GPP)/evapotranspiration (ET)). Using two observational WUE datasets (i.e., eddy-covariance measurements at 95 sites (526 site-years) and global gridded diagnostic modelling based on existing observation and a data-adaptive machine learning approach), we find a contrasting response of WUE to drought between arid (WUE increases with drought) and semi-arid/sub-humid ecosystems (WUE decreases with drought), which is attributed to different sensitivities of ecosystem processes to changes in hydro-climatic conditions. WUE variability in arid ecosystems is primarily controlled by physical processes (i.e., evaporation), whereas WUE variability in semi-arid/sub-humid regions is mostly regulated by biological processes (i.e., assimilation). We also find that shifts in hydro-climatic conditions over years would intensify the drought effect on WUE. Our findings suggest that future drought events, when coupled with an increase in climate variability, will bring further threats to semi-arid/sub-humid ecosystems and potentially result in biome reorganization, starting with low-productivity and high water-sensitivity grassland. <s> BIB016 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Abstract The seasonal stability of solar-induced chlorophyll fluorescence (SIF) vs field-measured leaf CO2 assimilation (A) was assessed over a period of 2 years by means of airborne flights performed at midday and diurnally over a citrus (evergreen) crop canopy. The orchard was cultivated under a control treatment (ET) that received 100% of its water requirements and two regulated deficit irrigation (RDI) treatments with water supply reduced to 37% and 50% of the control level during the summer. Field measurements consisted of assimilation rate, stomatal conductance, stem water potential, leaf fluorescence and leaf reflectance. The airborne campaigns took place in 2012 and 2013, and were flown on the solar plane in order to acquire hyperspectral imagery at 40 cm resolution, 260 spectral bands and 1.85 nm/pixels in the 400–885 nm spectral region. A thermal camera was installed in tandem in all flights, acquiring imagery in the 7.5–13 μm spectral region at 640 × 480 pixel resolution, yielding a 50 cm pixel size. The robustness of the SIF quantification through the Fraunhofer Line Depth (FLD) principle based on three spectral bands (FLD3), as well as the performance of physiological and structural hyperspectral indices, was evaluated in order to understand their ability to track photosynthesis at different phenological and stress stages throughout the season. Solar induced fluorescence quantified as FLD3 was the most robust indicator of photosynthesis in all the airborne campaigns performed in the course of the two-year experiment, which comprised seven midday flights and two diurnals. The relationships between fluorescence (FLD3) and assimilation rates yielded correlation coefficients (R) between 0.64 and 0.82 across all dates, these being statistically significant with p-values between p <s> BIB017 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Evapotranspiration is a major component of the global water cycle and provides a critical nexus between terrestrial water, carbon and surface energy exchanges. Evapotranspiration is inherently difficult to measure and predict especially at large spatial scales. Remote sensing provides a cost-effective method to estimate evapotranspiration at regional to global scales. In the past three decades a large number of studies on remote sensing based evapotranspiration estimation have emerged. This review summarizes the basic theories underpinning current remote sensing based evapotranspiration estimation methods. It also lays out the development history of these methods and compares their advantages and limitations. Several key directions for further study are identified and discussed, including identification of uncertainty sources in remote sensing evapotranspiration models, merging of different remote sensing methods, application of data assimilation and fusion techniques in producing robust evapotranspiration estimates, and utilization of multi-source remote sensing data and latest sensor technologies. Further advances in the remote sensing of evapotranspiration will enhance capabilities for monitoring of the global water and energy cycles, including water availability and ecosystem responses and feedbacks to climate change and human impacts. WIREs Water 2016, 3:834–853. doi: 10.1002/wat2.1168 ::: ::: For further resources related to this article, please visit the WIREs website. <s> BIB018 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> 5. <s> Monitoring Land Surface Phenology (LSP) is important for understanding both the responses and feedbacks of ecosystems to the climate system, and for representing these accurately in terrestrial biosphere models. Moreover, by shedding light on phenological trends at a variety of scales, LSP has the potential to fill the gap between traditional phenological (field) observations and the large-scale view of global models. ::: In this study, we review and evaluate the variability and evolution of satellite-derived Growing Season Length (GSL) globally and over the past three decades. We used the longest continuous record of Normalized Difference Vegetation Index (NDVI) data available to date at global scale to derive LSP metrics consistently over all vegetated land areas and for the period 1982-2012. We tested GSL, Start- and End-Of Season metrics (SOS and EOS, respectively) for linear trends as well as for significant trend shifts over the study period. We evaluated trends using global environmental stratification information in place of commonly used land cover maps to avoid circular findings. ::: Our results confirmed an average lengthening of the growing season globally during 1982-2012 – averaging 0.22-0.34 days/year, but with spatially heterogeneous trends. 13-19% of global land areas displayed significant GSL change, and over 30% of trends occurred in the boreal/alpine biome of the Northern Hemisphere, which showed diverging GSL evolution over the past 3 decades. Within this biome, the “Cold and Mesic” environmental zone appeared as an LSP change hotspot. We also examined the relative contribution of SOS and EOS to the overall changes, finding that EOS trends were generally stronger and more prevalent than SOS trends. These findings constitute a step towards the identification of large-scale phenological drivers of vegetated land surfaces, necessary for improving phenological representation in terrestrial biosphere models. <s> BIB019
Spectral signatures, patterns and heterogeneity recorded by remote-sensing techniques are therefore proxies of spectral traits and spectral trait variations and thus the results of their state and changes through biotic and abiotic source limitations and interactions and lastly the results of drivers, processes and pressures on FH BIB013 . Therefore, the plant trait approach allows a new way of understanding some fundamental questions about forest diversity. Traits and trait variations help us to understand, "why organisms live where they do and how they will respond to environmental change" BIB002 and interact with different stressors, disturbances, resource limitations and drivers. Traits and trait variations can therefore be described as filters for status, changes, stress, disturbances or resource limitations to taxonomic, structural and functional diversity of FES and FH BIB003 BIB005 (Figures 5 and 6 ). Not every change of FH, however, can be specifically assigned to a particular trait variation. For example, bark beetle infections of Picea abies lead to a reduction of chlorophyll and subsequently to a reduction of photosynthetic activity. These symptoms can also be caused by soil limitations or acid rain. Furthermore, reduction of chlorophyll concentration is also a process of senescence in forest plant species such as deciduous trees. Only with the integration of information on process characteristics such as process duration or intensity is it possible to differentiate the processes and drivers based on ST/STV. ST/STV of FH that can be observed using different RS technologies can be: • Alterations to biochemical spectral traits such as cellulose, nitrogen and lignin BIB006 BIB008 , or changes in the composition and configuration of photosynthetically-active pigments n leaves-chlorophyll, xanthophyll, α,β carotene, xanthophyll  BIB007 BIB004 BIB010 BIB009 . Changes to the intra-and extra-cellular water content or the percentage water in plants BIB014 BIB015 BIB016 . Not every change of FH, however, can be specifically assigned to a particular trait variation. For example, bark beetle infections of Picea abies lead to a reduction of chlorophyll and subsequently to a reduction of photosynthetic activity. These symptoms can also be caused by soil limitations or acid rain. Furthermore, reduction of chlorophyll concentration is also a process of senescence in forest plant species such as deciduous trees. Only with the integration of information on process characteristics such as process duration or intensity is it possible to differentiate the processes and drivers based on ST/STV. ST/STV of FH that can be observed using different RS technologies can be: • Alterations to biochemical spectral traits such as cellulose, nitrogen and lignin BIB006 BIB008 , or changes in the composition and configuration of photosynthetically-active pigments n leaves-chlorophyll, xanthophyll, α,β carotene, xanthophyll  BIB007 BIB004 BIB010 BIB009 . Changes to the intra-and extra-cellular water content or the percentage water in plants BIB014 BIB015 BIB016 . Not every change of FH, however, can be specifically assigned to a particular trait variation. For example, bark beetle infections of Picea abies lead to a reduction of chlorophyll and subsequently to a reduction of photosynthetic activity. These symptoms can also be caused by soil limitations or acid rain. Furthermore, reduction of chlorophyll concentration is also a process of senescence in forest plant species such as deciduous trees. Only with the integration of information on process characteristics such as process duration or intensity is it possible to differentiate the processes and drivers based on ST/STV. ST/STV of FH that can be observed using different RS technologies can be: • Alterations to biochemical spectral traits such as cellulose, nitrogen and lignin BIB006 BIB008 , or changes in the composition and configuration of photosynthetically-active pigments n leaves-chlorophyll, xanthophyll, α,β carotene, xanthophyll  BIB007 BIB004 BIB010 BIB009 . Changes to the intra-and extra-cellular water content or the percentage water in plants BIB014 BIB015 BIB016 . • Variations in the physiological and functional spectral traits such as photosynthesis activity and efficiency photosynthetic pathways, carbon sequestration, plant respiration or nutrient retention BIB011 BIB017 BIB001 . • Changes and shifts in bio-functional processes (evapotranspiration, energy balance in plants and mechanisms such as the phenotypical plasticity and phenotypic shifts of plants   BIB012 BIB018 BIB019 ].