Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract Leaves from ten tree species, including three conifers from a woodlot in southern Ontario were sampled at weekly intervals for a period of 150 days spanning the phenological events in deciduous trees of leaf development and expansion (flushing), leaf maturity and leaf senescence. The highly diverse seasonal red-edge reflection patterns were studied collectively and individually both from the perspective of long-term trends and relatively short-term or oscillating trends. The phenological events characteristic of deciduous trees were most effectively described using the red-edge position (λpg) and the chlorophyll-well position (λog ) derived from the inverted Gaussian model. Moreover, these parameters appeared consistent with what is known about the seasonal turnover of leaf chlorophyll and with other parameters R550 or Rog which more specifically quantify leaf chlorophyll. By these terms of reference chlorophyll declines considerably earlier in the season than the onset of other physiological or ... <s> BIB001 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Using a helicopter-mounted portable spectroradiometer and continuous eddy covariance data we were able to evaluate the photochemical reflectance index (PRI) as an indicator of canopy photosynthetic light-use efficiency (LUE) in four boreal forest species during the Boreal Ecosystem Atmosphere experiment (BOREAS). PRI was calculated from narrow waveband reflectance data and correlated with LUE calculated from eddy covariance data. Significant linear correlations were found between PRI and LUE when the four species were grouped together and when divided into functional type: coniferous and deciduous. Data from the helicopter-mounted spectroradiometer were then averaged to represent data generated by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). We calculated PRI from these data and relationships with canopy LUE were investigated. The relationship between PRI and LUE was weakened for deciduous species but strengthened for the coniferous species. The robust nature of this relationship suggests that relative photosynthetic rates may be derived from remotely-sensed reflectance measurements. ©2000 Elsevier Science B.V. All rights reserved. <s> BIB002 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Carbon exchange between the terrestrial biosphere and the atmosphere is one of the key processes that need to be assessed in the context of the Kyoto Protocol. Several studies suggest that the terrestrial biosphere is gaining carbon, but these estimates are obtained primarily by indirect methods, and the factors that control terrestrial carbon exchange, its magnitude and primary locations, are under debate. Here we present data of net ecosystem carbon exchange, collected between 1996 and 1998 from 15 European forests, which confirm that many European forest ecosystems act as carbon sinks. The annual carbon balances range from an uptake of 6.6 tonnes of carbon per hectare per year to a release of nearly 1 t C ha(-1) yr(-1), with a large variability between forests. The data show a significant increase of carbon uptake with decreasing latitude, whereas the gross primary production seems to be largely independent of latitude. Our observations indicate that, in general, ecosystem respiration determines net ecosystem carbon exchange. Also, for an accurate assessment of the carbon balance in a particular forest ecosystem, remote sensing of the normalized difference vegetation index or estimates based on forest inventories may not be sufficient. <s> BIB003 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Summary ::: This paper presents CO2 flux data from 18 forest ecosystems, studied in the European Union funded EUROFLUX project. Overall, mean annual gross primary productivity (GPP, the total amount of carbon (C) fixed during photosynthesis) of these forests was 1380 ± 330 gC m−2 y−1 (mean ±SD). On average, 80% of GPP was respired by autotrophs and heterotrophs and released back into the atmosphere (total ecosystem respiration, TER = 1100 ± 260 gC m−2 y−1). Mean annual soil respiration (SR) was 760 ± 340 gC m−2 y−1 (55% of GPP and 69% of TER). ::: ::: Among the investigated forests, large differences were observed in annual SR and TER that were not correlated with mean annual temperature. However, a significant correlation was observed between annual SR and TER and GPP among the relatively undisturbed forests. On the assumption that (i) root respiration is constrained by the allocation of photosynthates to the roots, which is coupled to productivity, and that (ii) the largest fraction of heterotrophic soil respiration originates from decomposition of young organic matter (leaves, fine roots), whose availability also depends on primary productivity, it is hypothesized that differences in SR among forests are likely to depend more on productivity than on temperature. ::: ::: At sites where soil disturbance has occurred (e.g. ploughing, drainage), soil espiration was a larger component of the ecosystem C budget and deviated from ::: ::: the relationship between annual SR (and TER) and GPP observed among the less-disturbed forests. At one particular forest, carbon losses from the soil were so large, that in some years the site became a net source of carbon to the atmosphere. Excluding the disturbed sites from the present analysis reduced mean SR to 660 ± 290 gC m−2 y−1, representing 49% of GPP and 63% of TER in the relatively undisturbed forest ecosystems. <s> BIB004 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success. <s> BIB005 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> The UNFCCC and interest in the source of the missing terrestrial carbon sink are prompting research and development into methods for carbon accounting in forest ecosystems. Here we present a canopy height quantile-based approach for quantifying above ground carbon content (AGCC) in a temperate deciduous woodland, by means of a discrete-return, small-footprint airborne LiDAR. Fieldwork was conducted in Monks Wood National Nature Reserve UK to estimate the AGCC of five stands from forest mensuration and allometric relations. In parallel, a digital canopy height model (DCHM) and a digital terrain model (DTM) were derived from elevation measurements obtained by means of an Optech Airborne Laser Terrain Mapper 1210. A quantile-based approach was adopted to select a representative statistic of height distributions per plot. A forestry yield model was selected as a basis to estimate stemwood volume per plot from these heights metrics. Agreement of r=0.74 at the plot level was achieved between ground-based AGCC estimates and those derived from the DCHM. Using a 20×20 m grids superposed to the DCHM, the AGCC was estimated at the stand level and at the woodland level. At the stand level, the agreement between the plot data upscaled in proportion to area and the LiDAR estimates was r=0.85. At the woodland level, LiDAR estimates were nearly 24% lower than those from the upscaled plot data. This suggests that field-based approaches alone may not be adequate for carbon accounting in heterogeneous forests. Conversely, the LiDAR 20×20 m grid approach has an enhanced capability of monitoring the natural variability of AGCC across the woodland. <s> BIB006 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Sources and sinks of carbon associated with forests depend strongly on the management regime and spa- tial patterns in potential productivity. Satellite remote sensing can provide spatially explicit information on land cover, stand- age class, and harvesting. Carbon-cycle process models cou- pled to regional climate databases can provide information on potential rates of production and related rates of decomposi- tion. The integration of remote sensing and modeling thus produces spatially explicit information on carbon storage and flux. This integrated approach was employed to compare car- bon flux for the period 1992-1997 over two 165-km 2 areas in western Oregon. The Coast Range study area was predomi- nately private land managed for timber production, whereas the West Cascades study area was predominantly public land that was less productive but experienced little harvesting in the 1990s. In the Coast Range area, 17% of the land base was harvested between 1991 and 2000. Much of the area was in relatively young, productive-age classes that simula- tions indicate are a carbon sink. Mean annual harvest remov- als from the Coast Range were greater than mean annual net ecosystem production. On the West Cascades study area, a relatively small proportion ( 1%) of the land was harvested and the area as a whole was accumulating carbon. The spa- tially and temporally explicit nature of this approach permits identification of mechanisms underlying land base carbon flux. Forests are large reservoirs of carbon as well as po- tential carbon sinks and sources to the atmosphere. In temperate North America, forest carbon sinks are be- lieved to offset a significant proportion of carbon emis- sions associated with fossil fuel combustion (Bosquet and others 2000). In the United States, forest carbon sinks have been estimated to offset up to 24% of the fossil fuel source (USDA Forest Service 2001). Thus, the ability to monitor forest carbon sequestration is of great interest in relation to understanding the current status of the global carbon cycle and to meeting re- quirements in the United Nations Framework Conven- tion on Climate Change to quantify carbon sources and sinks associated with land use (UN FCCC 1992; Parson and others 1992). Analysis of forest inventory data provides a capability <s> BIB007 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> The relationships between ecosystem-level light use efficiency (LUE) obtained from an eddy covariance flux tower and MODIS-derived values of a scaled Photochemical Reflectance Index (sPRI) were investigated for a boreal aspen stand (Populus tremuloides Michx.) in Saskatchewan, Canada. Using MODIS ocean band 11 at 531 nm, we tried to detect variations in canopy reflectance related to the xanthophyll cycle. We tested several other MODIS bands as the reference band because the 570 nm reference band that had been determined to be optimum for calculating PRI in earlier studies is not available on MODIS. While LUE varied greatly within the 2001, 2002, and 2003 growing seasons, the Normalized Difference Vegetation Index (NDVI) calculated from tower sensors remained stable. LUE had a negative exponential relationship with vapor pressure deficit and air temperature, and was at a maximum when absorbed PAR was <200 Amol m � 2 s � 1 . The range and magnitude of tower-based LUE values were smaller on clear days, when MODIS acquisitions were possible, than they were overall. Furthermore, the orbital parameters of the Terra and Aqua satellites restricted MODIS acquisitions to a 2.5-h period in early afternoon at our study site when LUE values were typically lower than they were earlier in the day. Strong correlations between MODIS-sPRI and LUE were found only for backscatter reflectance scenes when band 13 (667 nm) was used as the reference band. The correlations were higher for sPRI calculated from top of atmosphere reflectances than for surface reflectances (r 2 =0.76 and 0.53, respectively). The absolute backscatter reflectance of bands 11, 12 (551 nm), and 13 all decreased with increasing LUE. The decrease in band 13 suggests that the correlation between sPRI and LUE that we observed was caused by reductions in canopy chlorophyll content from 2001 to 2003 and/or by increased visibility of brighter non-photosynthetic material. Regional values of sPRI from 260 deciduous forest pixels in the 10,000 km 2 vicinity of the tower for two contrasting days, one in 2001 and one in 2003, were consistent <s> BIB008 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Leaf phenology remains one of the most difficult processes to parameterize in terrestrial ecosystem models because our understanding of the physical processes that initiate leaf onset and senescence is incomplete. While progress has been made at the molecular level, for example by identifying genes that are associated with senescence and flowering for selected plant species, a picture of the processes controlling leaf phenology is only beginning to emerge. A variety of empirical formulations have been used with varying degrees of success in terrestrial ecosystem models for both extratropical and tropical biomes. For instance, the use of growing degree-days (GDDs) to initiate leaf onset has received considerable recognition and this approach is used in a number of models. There are, however, limitations when using GDDs and other empirically based formulations in global transient climate change simulations. The phenology scheme developed for the Canadian Terrestrial Ecosystem Model (CTEM), designed for inclusion in the Canadian Centre for Climate Modelling and Analysis coupled general circulation model, is described. The representation of leaf phenology is general enough to be applied over the globe and sufficiently robust for use in transient climate change simulations. Leaf phenology is functionally related to the (possibly changing) climate state and to atmospheric composition rather than to geographical boundaries or controls implicitly based on current climate. In this approach, phenology is controlled by environmental conditions as they affect the carbon balance. A carbon-gain-based scheme initiates leaf onset when it is beneficial for the plant, in carbon terms, to produce new leaves. Leaf offset is initiated by unfavourable environmental conditions that incur carbon losses and these include shorter day length, cooler temperatures, and dry soil moisture conditions. The comparison of simulated leaf onset and offset times with observation-based estimates for temperate and boreal deciduous, tropical evergreen, and tropical deciduous plant functional types at selected locations indicates that the phenology scheme performs satisfactorily. Model simulated leaf area index and stem and root biomass are also compared with observational estimates to illustrate the performance of CTEM. <s> BIB009 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> The European CARBOEUROPE/FLUXNET monitoring sites, spatial remote sensing observations via the EOS‐MODIS sensor and ecosystem modelling provide independent and complementary views on the effect of the 2003 heatwave on the European biosphere's productivity and carbon balance. In our analysis, these data streams consistently demonstrate a strong negative anomaly of the primary productivity during the summer of 2003. FLUXNET eddy‐covariance data indicate that the drop in productivity was not primarily caused by high temperatures (‘heat stress’) but rather by limitation of water (drought stress) and that, contrary to the classical expectation about a heat wave, not only gross primary productivity but also ecosystem respiration declined by up to more than to 80gCm$^{-2}$month$^{-1}$. Anomalies of carbon and water fluxes were strongly correlated. While there are large between‐site differences in water‐use efficiency (WUE, 1–6 kg Ckg$^{−1}$H$_2$O) here defined as gross carbon uptake divided by evapotranspiration (WUE=GPP/ET), the year‐to‐year changes in WUE were small (<1gkg$^{−1}$) and quite similar for most sites (i.e. WUE decreased during the year of the heatwave). Remote sensing data from MODIS and AVHRR both indicate a strong negative anomaly of the fraction of absorbed photosynthetically active radiation in summer 2003, at more than five standard deviations of the previous years. The spatial differentiation of this anomaly follows climatic and land‐use patterns: Largest anomalies occur in the centre of the meteorological anomaly (central Western Europe) and in areas dominated by crops or grassland. A preliminary model intercomparison along a gradient from data‐oriented models to process‐oriented models indicates that all approaches are similarly describing the spatial pattern of ecosystem sensitivity to the climatic 2003 event with major exceptions in the Alps and parts of Eastern Europe, but differed with respect to their interannual variability. <s> BIB010 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Plants are finely tuned to the seasonality of their environment, and shifts in the timing of plant activity (i.e. phenology) provide some of the most compelling evidence that species and ecosystems are being influenced by global environmental change. Researchers across disciplines have observed shifting phenology at multiple scales, including earlier spring flowering in individual plants and an earlier spring green-up' of the land surface revealed in satellite images. Experimental and modeling approaches have sought to identify the mechanisms causing these shifts, as well as to make predictions regarding the consequences. Here, we discuss recent advances in several fields that have enabled scaling between species responses to recent climatic changes and shifts in ecosystem productivity, with implications for global carbon cycling. <s> BIB011 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Photosynthetic efficiency is greatly affected by internal and external factors and until now no remote sensing approach is available to globally quantify photosynthetic efficiency from air- or space-borne platforms. Quantification of sun-induced steady State fluorescence that can be detected in the atmospheric absorption bands is currently the most promising approach towards a global monitoring platform. This approach was recently highlighted due to the selection of the FLEX proposal as one of the future candidate missions for an ‘Earth Explorer’. Currently several modeling, laboratory and field studies are undertaken to (i) better understand the technical feasibility to monitor the comparably weak fluorescence signals from space; (ii) to proof the correlation of steady State fluorescence with photosynthetic carbon uptake; and (iii) to test the approach for a better modeling of regional carbon fluxes. This paper gives an overview over the status of this ESA project that may be the first and most ambitious remote sensing approach ever undertaken to globally map photosynthesis. <s> BIB012 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Interest in remote sensing (RS) of solar-induced chlorophyll fluorescence (F) by terrestrial vegetation is motivated by the link of F to photosynthetic efficiency which could be exploited for large scale monitoring of plant status and functioning. Today, passive RS of F is feasible with different prototypes and commercial ground-based, airborne, and even spaceborne instruments under certain conditions. This interest is generating an increasing number of research projects linking F and RS, such as the development of new F remote retrieval techniques, the understanding of the link between the F signal and vegetation physiology and the feasibility of a satellite mission specifically designed for F monitoring. This paper reviews the main issues to be addressed for estimating F from RS observations. Scattered information about F estimation exists in the literature. Here, more than 40 scientific papers dealing with F estimation are reviewed and major differences are found in approaches, instruments and experimental setups. Different approaches are grouped into major categories according to RS data requirements (i.e. radiance or reflectance, multispectral or hyperspectral) and techniques used to extract F from the remote signal. Theoretical assumptions, advantages and drawbacks of each method are outlined and provide perspectives for future research. Finally, applications of the measured F signal at the three scales of observation (ground, aircraft and satellite) are presented and discussed to provide the state of the art in F estimation. <s> BIB013 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract Flowering status including flowering date and flower amount could reflect ecological process in assessing plant phenological response to global warming. However, little information is available so far for monitoring flowering status through remote sensing. To provide an ecological indicator for monitoring plant phenology from remotely sensed data, we conducted a field survey in an alpine meadow on the Tibetan Plateau where flower color in July is dominantly yellow due to flowering of Halerpestes tricuspis (Ranunculaceae). We used flower coverage to indicate the flowering status of this species and proposed a flower index derived from in situ hyperspectral data (HFI) to estimate the flower coverage. Results demonstrate that the flower coverage of H. tricuspis can be estimated with high accuracy from the hyperspectral measurements. The indicating ability was further improved when the flower coverage was higher than 0.10 or the fractional coverage of soil was low or known in advance. A simulation also shows that a quadrat or pixel with flower coverage higher than 0.066 can be detected with existence of flower by HFI if soil fraction is less than 50%. These results indicate that HFI is applicable for estimating flower coverage of this species from hyperspectral measurement. The study suggests that the hyperspectral remote sensing technique can be applied for monitoring flowering status, and therefore the technique can provide an important ecological indicator for monitoring plant phenology. <s> BIB014 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> (i) the yellow flower of H. tricuspis significantly increased the red band canopy reflectance, but without apparent variations in near-infrared or blue band reflectance; (ii) the increase in red band reflectance significantly reduced the NDVI and EVI values; and (iii) the EVI was more sensitive than the NDVI to changes in the flower cover. Furthermore, clear decreases were observed in the NDVI and EVI values of the Moderate Resolution Imaging Spectroradiometer (MODIS) product for the study site caused by flower effects. These results suggest that there is a need to examine the effects of flower cover on the NDVI and EVI when they are used for types of vegetation that have profuse seasonal blooms. <s> BIB015 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> In tropical areas, Dynamic Global Vegetation Models (DGVMs) still have deficiencies in simulating the timing of vegetation phenology. To start addressing this problem, standard Fourier-based methods are applied to aerosol screened monthly remotely sensed phenology time series (Enhanced Vegetation Index, EVI) and two major driving factors of phenology: solar radiation and precipitation (for March 2000 through December 2006 over northern South America). At 1 × 1 km scale using, power (or variance) spectra on good quality aerosol screened time series, annual cycles in EVI are detected across 58.24% of the study area, the strongest (largest amplitude) occurring in the savanna. Terra Firme forest have weak but significant annual cycles in comparison with savannas because of the heterogeneity of vegetation and nonsynchronous phenological events within 1 × 1 km scale pixels. Significant annual cycles for radiation and precipitation account for 86% and 90% of the region, respectively, with different spatial patterns to phenology. Cross-spectral analysis was used to compare separately radiation with phenology/EVI, precipitation with phenology/EVI and radiation with precipitation. Overall the majority of the Terra Firme forest appears to have radiation as the driver of phenology (either radiation is in phase or leading phenology/EVI at the annual scale). These results are in agreement with previous research, although in Acre, central and eastern Peru and northern Bolivia there is a coexistence of ‘in phase’ precipitation over Terra Firme forest. In contrast in most areas of savanna precipitation appears to be a driver and savanna areas experiencing an inverse (antiphase) relationship between radiation and phenology is consistent with inhibited grassland growth due to soil moisture limitation. The resulting maps provide a better spatial understanding of phenology–driver relationships offering a bench mark to parameterize ecological models. <s> BIB016 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract. High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or light detection and ranging (LiDAR) samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high-resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (> 40%) of the Colombian Amazon – a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i) employing a universal approach to airborne LiDAR-calibration with limited field data; (ii) quantifying environmental controls over carbon densities; and (iii) developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon maps have 14% uncertainty at 1 ha resolution, and the regional map based on stratification has 28% uncertainty in any given hectare. High-resolution approaches with quantifiable pixel-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions. <s> BIB017 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract Freshwater resources are becoming increasingly limited in many parts of the world, and decision makers are demanding new tools for monitoring water availability and rates of consumption. Remotely sensed thermal-infrared imagery collected by Landsat provides estimates of land-surface temperature that allow mapping of evapotranspiration (ET) at the spatial scales at which water is being used. This paper explores the utility of moderate-resolution thermal satellite imagery in water resource management. General modeling techniques for using land-surface temperature in mapping the surface energy balance are described, including methods developed to safeguard ET estimates from expected errors in the remote sensing inputs. Examples are provided of how remotely sensed maps of ET derived from Landsat thermal imagery are being used operationally by water managers today: in monitoring water rights, negotiating interstate compacts, estimating water-use by invasive species, and in determining allocations for agriculture, urban use, and endangered species protection. Other applications include monitoring drought and food insecurity, and evaluation of large-scale land-surface and climate models. To better address user requirements for high-resolution, time-continuous ET data, novel techniques have been developed to improve the spatial resolution of Landsat thermal-band imagery and temporal resolution between Landsat overpasses by fusing information from other wavebands and satellites. Finally, a strategy for future modification to the Landsat program is suggested, improving our ability to track changes in water use due to changing climate and growing population. The long archive of global, moderate resolution TIR imagery collected by the Landsat series is unmatched by any other satellite program, and will continue to be an invaluable asset to better management of our earth's water resources. <s> BIB018 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> The phenology of growth in temperate deciduous forests, including the timing of leaf emergence and senescence, has strong control over ecosystem properties such as productivity and nutrient cycling, and has an important role in the carbon economy of understory plants. Extended leaf phenology, whereby understory species assimilate carbon in early spring before canopy closure or in late autumn after canopy fall, has been identified as a key feature of many forest species invasions, but it remains unclear whether there are systematic differences in the growth phenology of native and invasive forest species or whether invaders are more responsive to warming trends that have lengthened the duration of spring or autumn growth. Here, in a 3-year monitoring study of 43 native and 30 non-native shrub and liana species common to deciduous forests in the eastern United States, I show that extended autumn leaf phenology is a common attribute of eastern US forest invasions, where non-native species are extending the autumn growing season by an average of 4 weeks compared with natives. In contrast, there was no consistent evidence that non-natives as a group show earlier spring growth phenology, and non-natives were not better able to track interannual variation in spring temperatures. Seasonal leaf production and photosynthetic data suggest that most non-native species capture a significant proportion of their annual carbon assimilate after canopy leaf fall, a behaviour that was virtually absent in natives and consistent across five phylogenetic groups. Pronounced differences in how native and non-native understory species use pre- and post-canopy environments suggest eastern US invaders are driving a seasonal redistribution of forest productivity that may rival climate change in its impact on forest processes. <s> BIB019 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Predicting forest responses to warming climates relies on assumptions about niche and temperature sensitivity that remain largely untested. Observational studies have related current and historical temperatures to phenological shifts, but experimental evidence is sparse, particularly for autumn responses. A 4 year field experiment exposed four deciduous forest species from contrasting climates (Liquidambar styraciflua, Quercus rubra, Populus grandidentata, and Betula alleghaniensis) to air temperatures 2 and 4 °C above ambient controls, using temperature-controlled open top chambers. Impacts of year-round warming on bud burst (BB), senescence, and abscission were evaluated in relation to thermal provenance. Leaves emerged earlier in all species by an average of 4–9 days at +2 °C and 6–14 days at +4 °C. Magnitude of advance varied with species and year, but was larger for the first 2 °C increment than for the second. Effect of warming increased with early BB, favoring Liquidambar, but even BB of northern species advanced, despite temperatures exceeding those of the realized niche. Treatment differences in BB were inadequately explained by temperature sums alone. In autumn, chlorophyll was retained an average of 4 and 7 days longer in +2 and +4 °C treatments, respectively, and abscission delayed by 8 and 13 days. Growing seasons in the warmer atmospheres averaged 5–18 days (E2) and 6–28 days (E4) longer, according to species, with the least impact in Quercus. Results are compared with a 16 years record of canopy onset and offset in a nearby upland deciduous forest, where BB showed similar responsiveness to spring temperatures (2–4 days °C−1). Offset dates in the stand tracked August–September temperatures, except when late summer drought caused premature senescence. The common garden-like experiment provides evidence that warming alone extends the growing season, at both ends, even if stand-level impacts may be complicated by variation in other environmental factors. <s> BIB020 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Several models have been fitted in the past to smooth time-series vegetation index data from different satellite sensors to estimate vegetation phenological parameters. However, differences between the models and fine tuning of model parameters lead to potential differences, uncertainty and bias between the results amongst users. The current research assessed four techniques: Fourier analysis, asymmetric Gaussian model, double logistic model and the Whittaker filter for smoothing multi-temporal satellite sensor observations with the ultimate purpose of deriving an appropriate annual vegetation growth cycle and estimating phenological parameters reliably. The research used Level 3 Medium Resolution Imaging Spectrometer (MERIS, spatial resolution ~ 4.6 km) Terrestrial Chlorophyll Index (MTCI) data over the years 2004 to 2006 composited at eight day intervals covering the Indian sub-continent. First, the four models were fitted to representative sample time-series of the major vegetation types in India, and the quality of the fit was analysed. Second, the effect of noise on model fitting was analysed by adding Gaussian noise to a standard profile. Finally, the four models were fitted to the whole study area to characterise variation in the quality of model fitting as a function of single and double vegetation seasons. These smoothed data were used to estimate the onset of greenness (OG), a major phenological parameter. The models were evaluated using the root mean square error (RMSE), Akaike Information Criteria (AIC), and Bayesian Information Criteria (BIC). The first test (fitting to representative sample time series) revealed the consistently superior performance of the Whittaker and Fourier approaches in most cases. The second test (fitting after the addition of Gaussian noise) revealed the superior performance of the double logistic and Fourier approaches. Finally, when the approaches were applied to the whole study, thus, including vegetation with different phenological profiles and multiple growing seasons (third test), it was found that it was necessary to tune each of the models according to the number of annual growing seasons to produce reliable fits. The double logistic and asymmetric Gaussian models did not perform well for areas with more than one growing season per year. The mean absolute deviation in OG derived from these models was a maximum (3 to 4 weeks) within the dry deciduous vegetation type and minimum (1 week) in evergreen vegetation. All techniques yielded consistent results over the south-western and north-eastern regions of India characterised by tropical climate. <s> BIB021 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Field observations and time series of vegetation greenness data from satellites provide evidence of changes in terrestrial vegetation activity over the past decades for several regions in the world. Changes in vegetation greenness over time may consist of an alternating sequence of greening and/or browning periods. This study examined this effect using detection of trend changes in normalized difference vegetation index (NDVI) satellite data between 1982 and 2008. Time series of 648 fortnightly images were analyzed using a trend breaks analysis (BFAST) procedure. Both abrupt and gradual changes were detected in large parts of the world, especially in (semi-arid) shrubland and grassland biomes where abrupt greening was often followed by gradual browning. Many abrupt changes were found around large-scale natural influences like the Mt Pinatubo eruption in 1991 and the strong 1997/98 El Nino event. The net global figure – considered over the full length of the time series – showed greening since the 1980s. This is in line with previous studies, but the change rates for individual short-term segments were found to be up to five times higher. Temporal analysis indicated that the area with browning trends increased over time while the area with greening trends decreased. The Southern Hemisphere showed the strongest evidence of browning. Here, periods of gradual browning were generally longer than periods of gradual greening. Net greening was detected in all biomes, most conspicuously in croplands and least conspicuously in needleleaf forests. For 15% of the global land area, trends were found to change between greening and browning within the analysis period. This demonstrates the importance of accounting for trend changes when analyzing long-term NDVI time series. <s> BIB022 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Green leaf phenology is known to be sensitive to climate variation. Phenology is also important because it exerts significant control on terrestrial carbon cycling and sequestration. High-quality measurements of green leaf phenology are therefore increasingly important for understanding the effects of climate change on ecosystem function and biosphere–atmosphere interactions. In this paper, we compare “near-surface” and satellite remote sensing-based observations of vegetation phenology at four deciduous forest sites. Specifically, we addressed three questions related to how observations of plant phenology measured by red–green–blue (RGB) cameras mounted on towers above forest canopies are related to measurements of phenology acquired by moderate resolution sensors on satellites. First, how are estimated phenophase transition dates — or the observable stages in the life cycle of plants — influenced by the choice of vegetation index (VI) measured by remote sensing? Second, are VIs and phenological metrics derived from near-surface and satellite remote sensing comparable, and what is the nature and magnitude of covariation between near-surface and satellite-remote sensing-based estimates of phenology at seasonal and interannual time scales? Third, does near-surface remote sensing data provide a basis for validating satellite-derived land surface phenology products and what are the requirements for achieving this goal? Our study provides substantial support for future efforts linking satellite and near-surface remote sensing. We show significant agreement between phenological time series and metrics derived from these two data sources. However, issues of scale and representation strongly influence the relationship between near surface and satellite remote sensing measures of phenology. In particular, intra- and interannual correlation between time series from each source are dependent on how representative the camera FOV is of the regional landscape. Further, our results show that the specific VI used to monitor phenology exerts substantial influence on satellite VI derived phenological metrics, and by extension, how they compare to VI time series and metrics obtained from near-surface remote sensing. These results improve understanding of how near-surface and satellite remote sensing complement each other. However, more work is required to develop formal protocols for evaluating, calibrating and validating satellite remote sensing phenology products using near surface remote sensing at a regional to continental scale. <s> BIB023 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> The present study investigated the utility of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived sPRI (scaled photochemical reflectance index) and its relationship to photosynthetic light-use efficiency (LUE) calculated from eddy covariance tower data. The analysis was performed over two consecutive years (2003–2004) in a Mediterranean Quercus cerris L. forest site in Italy. Temperature and rainfall conditions differed markedly over the study period, with 2003 being a notable drought year and 2004 a non-drought year. MODIS ocean bands 11 (centred at 531 nm) and 12 (centred at 551 nm) were used for calculating sPRI. LUE exhibited substantial variability within 2003 and 2004, and a moderate relationship between MODIS-sPRI and LUE was observed during the wet year, and for backscattering scenes. This demonstrated the capacity of sPRI to detect xanthophyll cycle activation by vegetation during high light conditions. However, our results show that sPRI should be used with care, particularly under sev... <s> BIB024 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract Sun-induced chlorophyll fluorescence (Fs) is the radiation flux emitted from chlorophyll molecules and can be used as a remote sensing (RS) observable to be linked to plant photosynthesis. Recently, significant progress has been made to quantify Fs from RS data, but both retrieval and interpretation of Fs remain challenging. In the case of airborne sensors with a medium spectral resolution ( 2 absorption bands. Most critical for accurate Fs retrievals based on such methods is the characterization of atmospheric scattering and absorption processes during data acquisition. So far, detailed experimental evidence on the retrieval accuracy of airborne measured Fs is lacking. We performed an experiment using a low-flying aircraft equipped with a non-imaging spectrometer acquiring medium spectral resolution data during the course of one day, using a repeat-track approach with changing flight altitudes. Fs in the near infrared was retrieved using a semi-empirical approach constraining the FLD based Fs retrieval from the O 2 -A absorption band at 760 nm by using non-fluorescent surfaces. We used a local sensitivity analysis to assess Fs retrieval biases related to observational and atmospheric parameters. Our results demonstrate a reliable Fs retrieval from airborne data using reference surfaces and indicate the need for accurate knowledge of atmospheric scattering and absorption processes. This study contributes to an estimation of the total error budget of Fs retrievals and will serve as a practical guideline for Fs retrieval schemes to be applied to medium resolution airborne spectroscopy data. <s> BIB025 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> The updated Global Inventory Modeling and Mapping Studies (GIMMS) third generation global satellite Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) dataset provides very detailed global information on the state of vegetation from 1982 to 2011. Using these data we investigated the changes in the vegetation photosynthetic activity in the Asia-Pacific (AP) (including Australia, South East Asia, China, and the Pacific Coast of North America) region, by discerning gradual changes into two key metrics: 1) the cumulative annual NDVI in each year and 2) the seasonality or variance in that index. We then assessed changes using break and turning points using three statistical models (least-square linear, expanded paired-consecutive linear and piecewise regression models). We found that the AP region overall experienced increasing NDVI from 1982 through 2011 with an average rate of 530 x 10(-4) NDVI yr(-1) (0.13% yr(-1)). The annual NDVI increased from 1982 at a faster rate of 26.14 x 10(-4) NDVI yr-1 (0.65% yr(-1)) until a break in the trend after 1991 (after that the trend reduced to 5.78 x 10(-4) NDVI yr(-1)). In the Asia-Australia (AA) subarea of the AP, vegetation greening slowly increased at 8.71 x 10(-4) NDVI yr(-1) before 2003 and then increased to 28.30 x 10(-4) NDVI yr(-1) after 2003. In contrast, in the North America (NA) subarea NDVI rapidly increased initially at 18.72 x 10(-4) NDVI yr(-1) before 1992 and then marginally increased (3.96 x 10(-4) NDVI yr(-1)) after 1992. The turning points were found to be 2008 and 1987 for the AA and NA subareas respectively. Analysis of monthly NDVI data showed that the trends were positive for most of the months of the study period, particularly during the growing season. Geospatial analyses demonstrated that cumulative annual NDVI and the variance or seasonality across the large AP region varied across the different subareas. As well, we found evidence for different spatial patterns of the NDVI changes with strong spatial heterogeneity in the patterns of the break and turning points. This suggests complex and nonlinear responses of vegetation photosynthetic activity to regional climatic changes and other drivers. (C) 2014 Elsevier Inc. All rights reserved. <s> BIB026 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Terrestrial carbon conservation can provide critical environmental, social, and climate benefits. Yet, the geographically complex mosaic of threats to, and opportunities for, conserving carbon in landscapes remain largely unresolved at national scales. Using a new high-resolution carbon mapping approach applied to Peru, a megadiverse country undergoing rapid land use change, we found that at least 0.8 Pg of aboveground carbon stocks are at imminent risk of emission from land use activities. Map-based information on the natural controls over carbon density, as well as current ecosystem threats and protections, revealed three biogeographically explicit strategies that fully offset forthcoming land-use emissions. High-resolution carbon mapping affords targeted interventions to reduce greenhouse gas emissions in rapidly developing tropical nations. <s> BIB027 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including—in the latter case—x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called “out-of-bag”), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha−1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation. <s> BIB028 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Theory and experiment agree that climate warming will increase carbon fluxes between terrestrial ecosystems and the atmosphere. The effect of this increased exchange on terrestrial carbon storage is less predictable, with important implications for potential feedbacks to the climate system. We quantified how increased mean annual temperature (MAT) affects ecosystem carbon storage in above- and belowground live biomass and detritus across a well-constrained 5.2 °C MAT gradient in tropical montane wet forests on the Island of Hawaii. This gradient does not systematically vary in biotic or abiotic factors other than MAT (i.e. dominant vegetation, substrate type and age, soil water balance, and disturbance history), allowing us to isolate the impact of MAT on ecosystem carbon storage. Live biomass carbon did not vary predictably as a function of MAT, while detrital carbon declined by ~14 Mg of carbon ha � 1 for each 1 °C rise in temperature – a trend driven entirely by coarse woody debris and litter. The largest detrital pool, soil organic carbon, was the most stable with MAT and averaged 48% of total ecosystem carbon across the MAT gradient. Total ecosystem carbon did not vary significantly with MAT, and the distribution of ecosystem carbon between live biomass and detritus remained relatively constant across the MAT gradient at ~44% and ~56%, respectively. These findings suggest that in the absence of alterations to precipitation or disturbance regimes, the size and distribution of carbon pools in tropical montane wet forests will be less sensitive to rising MAT than predicted by ecosystem models. This article also provides needed detail on how individual carbon pools and ecosystem-level carbon storage will respond to future warming. <s> BIB029 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> article i nfo Vegetation carbon uptake and respiration constitute the largest carbon cycle of the planet with an annual turn- overinthe orderof120GT.Currently,neitherecosystemcarbon uptake (throughphotosynthesis)norecosystem carbon release (through respiration) can be measured directly during the daytime. Instead, flux-tower measure- ments rely on nighttime respiration based on the assumption of zero carbon uptake which are then projected to daytime using an exponential relationship to soil temperature at shallow soil depth. As an alternative to this approach, R could possibly also be determined from combining daytime eddy covariance measurements of net ecosystem production (NEP) and spectral observations of gross primary production (GPP). In previous work, we have shown that multi-angular observations can be used to determine GPP from the absorbed photosynthet- ically active radiation (APAR) and spectrally obtained observations of light-use efficiency (e). The difference of NEPandGPPsuggeststhatdaytime respirationisgreaterandmoredynamicthanconventionalestimatesderived from nighttime flux values. Our findings also suggest that an accelerated ecosystem metabolism results in an exponential increase in respiration which eventually diminishes net ecosystem production. Respiration was also closely related to air and soil temperature. We conclude that tower-level spectral measurements provide considerable new insights into ecosystem fluxes as they allow independent yet complementary measurements of different aspects of the carbon and energy cycle. <s> BIB030 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <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> BIB031 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract Sun-induced chlorophyll fluorescence (SIF) is a radiation flux emitted from chlorophyll molecules and is considered an indicator of the actual functional state of plant photosynthesis. The remote measurement of SIF opens a new perspective to assess actual photosynthesis at larger, ecologically relevant scales and provides an alternative approach to study the terrestrial carbon cycle. Recent studies demonstrated the reliability of measured SIF signals and showed significant relationships between SIF and gross primary production (GPP) at ecosystem and global scales. Despite these encouraging results, understanding the complex mechanisms between SIF and GPP remains challenging before SIF can be finally utilized to constrain estimates of GPP. In this study, we present a comprehensive assessment of the relationship between far-red SIF retrieved at 760 nm (SIF760) and GPP, and its transferability across three structurally and physiologically contrasting ecosystems: perennial grassland, cropland and mixed temperate forest. We use multi-temporal imaging spectroscopy (IS) data acquired with the Airborne Prism EXperiment (APEX) sensor as well as eddy covariance (EC) flux tower data to evaluate the relationship between SIF760 and GPPEC. We use simulations performed with the coupled photosynthesis–fluorescence model SCOPE to prove trends obtained from our observational data and to assess apparent confounding factors such as physiological and structural interferences or temporal scaling effects. Observed relationships between SIF760 and GPPEC were asymptotic and ecosystem-specific, i.e., perennial grassland (R2 = 0.59, rRMSE = 27.1%), cropland (R2 = 0.88, rRMSE = 3.5%) and mixed temperate forest (R2 = 0.48, rRMSE = 15.88%). We demonstrate that asymptotic leaf level relationships between SIF760 and GPPEC became more linear at canopy level and scaled with temporal aggregation. We conclude that remote sensing of SIF provides a new observational approach to decrease uncertainties in estimating GPP across ecosystems but requires dedicated strategies to compensate for the various confounding factors impacting SIF–GPP relationships. Our findings help in bridging the gap between mechanistic understanding at leaf level and ecosystem-specific observations of the relationships between SIF and GPP. <s> BIB032 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <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> BIB033 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> The area of tree plantations in the humid subtropical region of Northern Argentina has recently increased five folds. However, the impact of this land use change on evapotranspiration (ET), one of the main components of the hydrologic cycle, has not been evaluated. We studied the ET at tree and ecosystem levels for native forests and three tree plantations (Pinus taeda, Araucaria angustifolia and Eucalyptus grandis). Water consumption of individual trees was estimated using sap flow measurements. Ecosystem ET was characterized using both remote sensing derived data products (ETMODIS) for 2000-2011 and scaling up from tree sap flow measurements to stand level. Canopy conductance (g(c)) was estimated using both sap flow measurements and ETMODIS data. At individual level, transpiration was positively related to the size of the tree, and the relationship was well described by an exponential function when all species (both native and cultivated trees) were included in the analysis. The average annual leaf area index was similar between native forest and tree plantations. The ET estimates obtained from scaling up sap flow measurements and from ETmorms were relatively similar in most cases and differed by 4-34%, depending on the ecosystem. The tree plantations, regardless of density or age, did not show higher ETMODIS than native forests. The ET ranged from 1161 to 1389 mm per year across native forests and tree plantations according to remote sensing, representing 58-69% of the annual precipitation. Furthermore, the good agreement between ET estimates, with the exception of E. grandis, obtained using sap flow and remote sensing provide a good basis for predicting the effects of land conversion from native forest to most non-native tree plantations on regional ET. Monthly ETMODIS increased with increasing monthly air saturation deficit (ASD) up to 0.8 kPa, value at which ETMODIS did not increase further probably due to stomatal control and low values of g(c). Different negative exponential relationships between g(c) and ASD were obtained when g(c) was calculated by scaling up daily tree sap flow to ecosystem level. Canopy conductance (estimated by remote sensing) declined in a similar negative exponential fashion with increasing ASD, and no differences were observed across ecosystem types. The result of increasing the time step, from daily to monthly, and the spatial scale from individual tree to stand level, had the consequence to lower, even to eliminate differences in annual ET and g(c) among ecosystems in their responses to climate drivers. This suggests that the nature of ET regulation at individual and ecosystem levels could be different, which should be taken into account when predicting the effects of changes in land use on regional hydrology. (C) 2015 Elsevier B.V. All rights reserved. <s> BIB034 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Understanding the environmental and biotic drivers of respiration at the ecosystem level is a prerequisite to further improve scenarios of the global carbon cycle. In this study we investigated the relevance of physiological phenology, defined as seasonal changes in plant physiological properties, for explaining the temporal dynamics of ecosystem respiration (RECO) in deciduous forests. Previous studies showed that empirical RECO models can be substantially improved by considering the biotic dependency of RECO on the short-term productivity (e.g., daily gross primary production, GPP) in addition to the well-known environmental controls of temperature and water availability. Here, we use a model-data integration approach to investigate the added value of physiological phenology, represented by the first temporal derivative of GPP, or alternatively of the fraction of absorbed photosynthetically active radiation, for modeling RECO at 19 deciduous broadleaved forests in the FLUXNET La Thuile database. The new data-oriented semiempirical model leads to an 8% decrease in root mean square error (RMSE) and a 6% increase in the modeling efficiency (EF) of modeled RECO when compared to a version of the model that does not consider the physiological phenology. The reduction of the model-observation bias occurred mainly at the monthly time scale, and in spring and summer, while a smaller reduction was observed at the annual time scale. The proposed approach did not improve the model performance at several sites, and we identified as potential causes the plant canopy heterogeneity and the use of air temperature as a driver of ecosystem respiration instead of soil temperature. However, in the majority of sites the model-error remained unchanged regardless of the driving temperature. Overall, our results point toward the potential for improving current approaches for modeling RECO in deciduous forests by including the phenological cycle of the canopy. <s> BIB035 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Our knowledge of long-term changes in vegetation activity is incomplete, hindering understanding of Earth system dynamics. A comprehensive global assessment of vegetation phenology now shows that vegetation activity changed severely on 54% of the global land surface between 1981 and 2012. <s> BIB036 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> BACKGROUND AND AIMS ::: Autumn leaf senescence marks the end of the growing season in temperate ecosystems. Its timing influences a number of ecosystem processes, including carbon, water and nutrient cycling. Climate change is altering leaf senescence phenology and, as those changes continue, it will affect individual woody plants, species and ecosystems. In contrast to spring leaf out times, however, leaf senescence times remain relatively understudied. Variation in the phenology of leaf senescence among species and locations is still poorly understood. ::: ::: ::: METHODS ::: Leaf senescence phenology of 1360 deciduous plant species at six temperate botanical gardens in Asia, North America and Europe was recorded in 2012 and 2013. This large data set was used to explore ecological and phylogenetic factors associated with variation in leaf senescence. ::: ::: ::: KEY RESULTS ::: Leaf senescence dates among species varied by 3 months on average across the six locations. Plant species tended to undergo leaf senescence in the same order in the autumns of both years at each location, but the order of senescence was only weakly correlated across sites. Leaf senescence times were not related to spring leaf out times, were not evolutionarily conserved and were only minimally influenced by growth habit, wood anatomy and percentage colour change or leaf drop. These weak patterns of leaf senescence timing contrast with much stronger leaf out patterns from a previous study. ::: ::: ::: CONCLUSIONS ::: The results suggest that, in contrast to the broader temperature effects that determine leaf out times, leaf senescence times are probably determined by a larger or different suite of local environmental effects, including temperature, soil moisture, frost and wind. Determining the importance of these factors for a wide range of species represents the next challenge for understanding how climate change is affecting the end of the growing season and associated ecosystem processes. <s> BIB037 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract The aim of this paper was to create a model that predicts the different phenological BBCH macro-stages of barley in laboratory on the plot scale and to transfer the most suitable model to the landscape scale. To characterise the phenology, eight vitality and phenology-related vegetation parameters like leaf area index (LAI), Chl-SPAD content, C-content, N-content, C/N-content, canopy chlorophyll content (CCC), gravimetric water content (GWC) and vegetation height at the same time as all imaging hyperspectral measurements (AISA-EAGLE, 395–973 nm). These biochemical–biophysical vegetation parameters were investigated according to the different phenological macro-stages of barley. The predictive models were developed using four different types of vegetation indices (VI): (I) published VI’s, (II) reflectance VI’s as well as (III) VI (xy) formula combinations and (IV) a combination of all VI index types using the Library for Support Vector Machines (LibSVM) and tested with a recursive conditional correlation weighting selection algorithm (RCCW) to reduce the number of variables. To increase the performance of the model a 10-fold cross-validation was carried out for all statistical models. The GWC was found to be the most important variable for differentiating between the phenological macro-stages of barley. The most suitable model for predicting the phenological BBCH macro-stages was achieved by a model that combined all three kinds of VI’s: published VI’s, reflectance VI’s and formula combination VI’s with a classification accuracy of 84.80%. With the classification model for the reflectance VI’s Y = 746 nm and for the VI formula combinations Y = (527 + 612) nm and Y = (540 + 639) nm. The best predictive model was applied to the airborne AISA-EAGLE hyperspectral data to model the phenological macro-stages of barley at the landscape level. The classification error of the best predictive model of 12.80% as well as disturbance factors such as channels and areas with weeds or ruderal vegetation lead to misclassifications of BBCH macro-stages at the landscape level. By using One Sensor At Different Scales-Approach (OSADIS), sensor-specific differences in the model building and model transfer can be eliminated. The approach described in the paper for determining the phenology based on imaging hyperspectral RS data shows that in the process of plant phonological development a number of biochemical–biophysical vegetation traits in vegetation change, which can be thoroughly recorded with hyperspectral remote sensing technology. For this reason, hyperspectral RS constitutes an ideal, cost-effective and comparable approach, with whose help vegetation traits and changes can be quantified, which are key for ecological modelling. <s> BIB038 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract We tested the suitability and accuracy of hyperspectral data to produce the first African flowering and short-term floral cycle map. The spatial distribution and abundance, as well as the floral cycle, of melliferous plants are of utmost importance for evaluating pollination effects and to understand the relationship between melliferous plants in the landscape and the quantity and quality of bee keeping products. For a study site in Kenya, airborne AISA/Eagle hyperspectral data with 60 cm pixel resolution (400 to 990 nm spectral ranges) was captured in January 2014, at the beginning of the prime flowering period, and during the prime flowering period in February 2013. Aerial digital imagery with 10 cm pixel size and Smartphone captures in the field were used for reference data collection. The flowering species were grouped into functional flowering plant groups. Linear spectral unmixing and Change Vector Analysis (CVA) were used on the bi-temporal AISA/Eagle data to produce a hard cover map showing the spatial distribution, abundance and short-term flowering cycle of melliferous plants. Overall accuracies were slightly higher in the February 2013 imagery at the prime flowering period; all flowering plant groups together (“All”) could be mapped with an overall accuracy of 83% ( n = 512). The “White forbs” flowering plant group was most accurately mapped in both AISA/Eagle acquisition dates. Based on Duncan's inter-class similarity test, the “White forbs” group was also most distinct from other flowering plant groups. There is a need to investigate the effect of spectral endmember variability and upscaling options for space-borne monitoring of the floral cycle at key sites in Africa. Floral cycle maps can help decision makers and bee keepers to understand how bee colonies interact with the floral environment and what to expect from an apiary in terms of honey flow. <s> BIB039 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Several studies have demonstrated that Monteith's approach can efficiently predict forest gross primary production (GPP), while the modeling of net ecosystem production (NEP) is more critical, requiring the additional simulation of forest respirations. The NEP of different forest ecosystems in Italy was currently simulated by the use of a remote sensing driven parametric model (modified C-Fix) and a biogeochemical model (BIOME-BGC). The outputs of the two models, which simulate forests in quasi-equilibrium conditions, are combined to estimate the carbon fluxes of actual conditions using information regarding the existing woody biomass. The estimates derived from the methodology have been tested against daily reference GPP and NEP data collected through the eddy correlation technique at five study sites in Italy. The first test concerned the theoretical validity of the simulation approach at both annual and daily time scales and was performed using optimal model drivers (i.e., collected or calibrated over the site measurements). Next, the test was repeated to assess the operational applicability of the methodology, which was driven by spatially extended data sets (i.e., data derived from existing wall-to-wall digital maps). A good estimation accuracy was generally obtained for GPP and NEP when using optimal model drivers. The use of spatially extended data sets worsens the accuracy to a varying degree, which is properly characterized. The model drivers with the most influence on the flux modeling strategy are, in increasing order of importance, forest type, soil features, meteorology, and forest woody biomass (growing stock volume). <s> BIB040 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Vegetation carbon turnover processes in forest ecosystems and their dominant drivers are far from being understood at a broader scale. Many of these turnover processes act on long time-scales and include a lateral dimension and thus can hardly be investigated by plot-level studies alone. Making use of remote sensing based products of net primary productivity (NPP) and biomass, here we show that spatial gradients of carbon turnover rate (k) in Northern Hemisphere boreal and temperate forests are explained by different climate-related processes depending on the ecosystem. k is related to frost damage effects and the trade-off between growth and frost adaptation in boreal forests, while drought stress and climate effects on insects and pathogens can explain an elevated k in temperate forests. By identifying relevant processes underlying broad-scale patterns in k, we provide the basis for a detailed exploration of these mechanisms in field studies, and ultimately the improvement of their representations in global vegetation models (GVMs). <s> BIB041 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> This study presents a comparison and integration of three methods commonly used to estimate the amount of forest ecosystem carbon (C) available for storage. In particular, we examine the representation of living above- and below-ground biomass change (net accumulation) using plot-level biometry and repeat airborne laser scanning (ALS) of three dimensional forest plot structure. These are compared with cumulative net CO2 fluxes (net ecosystem production, NEP) from eddy covariance (EC) over a six-year period within a jack pine chronosequence of four stands (~ 94, 30, 14 and 3 years since establishment from 2005) located in central Saskatchewan, Canada. Combining the results of the two methods yield valuable observations on the partitioning of C within ecosystems. Subtracting total living biomass C accumulation from NEP results in a residual that represents change in soil and litter C storage. When plotted against time for the stands investigated, the curve produced is analogous to the soil C dynamics described in Covington (1981). Here, ALS biomass accumulation exceeds EC-based NEP measured in young stands, with the residual declining with age as stands regenerate and litter decomposition stabilizes. During the 50–70 year age-period, NEP and live biomass accumulation come into balance, with the soil and litter pools of stands 70–100 years post-disturbance becoming a net store of C. Biomass accumulation was greater in 2008–2011 compared to 2005–2008, with the smallest increase in the 94-year-old “old jack pine” stand and greatest in the 14-year-old “harvested jack pine 1994” stand, with values of 1.4 (± 3.2) tC ha− 1 and 12.0 (± 1.6) tC ha− 1, respectively. The efficiency with which CO2 was stored in accumulated biomass was lowest in the youngest and oldest stands, but peaked during rapid regeneration following harvest (14-year-old stand). The analysis highlights that the primary source of uncertainty in the data integration workflow is in the calculation of biomass expansion factors, and this aspect of the workflow needs to be implemented with caution to avoid large error propagations. We suggest that the adoption of integrated ALS, in situ and atmospheric flux monitoring frameworks is needed to improve spatio-temporal partitioning of C balance components at sub-decadal scale within rapidly changing forest ecosystems and for use in national carbon accounting programs. <s> BIB042 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <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> BIB043 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> The Stratospheric Observatory For Infrared Astronomy (SOFIA) is a 2.5-m telescope mounted inside of a Boeing 747SP. Planning and executing astronomical observations from an aircraft moving at 500 miles per hour has its own unique challenges and advantages. Scheduling and optimizing an entire year of science observations is a balancing act with target availability, instrument availability, and operational constraints. A SOFIA flight is well choreographed, and successfully executing observations on SOFIA requires many systems and people to work together- from the telescope assembly compensating for the continual vibration and movement of the plane in order to accurately point the telescope, the expertise of the telescope operators to prepare the telescope for use by the instrument operators, aircraft operations ensuring that the aircraft is ready for flight, and the mission systems control computers keeping track of all the data. In this paper we will discuss what it takes to plan a SOFIA flight, and what we do once we’re in the air. We will share a typical science flight, as well as more challenging and unique observations that require SOFIA being in the right place at the right time. <s> BIB044 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Understanding relations among forest carbon (C) uptake and water use is critical for predicting forest-climate interactions. Although the basic properties of tree-water relations have long been known, our understanding of broader-scale patterns is limited by several factors including: 1) incomplete understanding of drivers of change in coupled C and water fluxes, and water use efficiency (WUE); 2) difficulty in reconciling WUE estimates obtained at different scales; and 3) uncertainty in how evapotranspiration (ET) and WUE vary with other important resources such as nitrogen (N). To address these issues, we examined ET, gross primary production (GPP) and WUE at eleven AmeriFlux sites across North America. Our analysis spanned leaf and ecosystem scales, and included foliar δ13C, δ18O and %N measurements, eddy covariance estimates of GPP and ET, and remotely sensed estimates of canopy %N. We used flux data to derive ecosystem WUE (WUEe) and foliar δ13C to infer intrinsic WUE (iWUE). We found that GPP, ET and WUEe scaled with canopy %N, even when environmental variables were considered, and discuss the implications of these relationships for forest-atmosphere-climate interactions. We observed opposing patterns of WUE at leaf and ecosystem scales, and examined uncertainties to help explain these opposing patterns. Nevertheless, significant relationship between C isotope-derived ci/ca and GPP indicates that δ13C can be an effective predictor of forest GPP. Finally, we show that incorporating species functional traits - wood anatomy, hydraulic strategy and foliar %N -into a conceptual model improved the interpretation of Δ13C and δ18O vis-a-vis leaf to canopy water-carbon fluxes. <s> BIB045 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Climate models require an understanding of ecosystem-scale respiration and photosynthesis, yet there is no way of measuring these two fluxes directly; here, new instrumentation is used to determine these fluxes in a temperate forest, showing, for instance, that respiration is less during the day than at night. <s> BIB046 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> In evergreen tropical forests, the extent, magnitude, and controls on photosynthetic seasonality are poorly resolved and inadequately represented in Earth system models. Combining camera observations with ecosystem carbon dioxide fluxes at forests across rainfall gradients in Amazonia, we show that aggregate canopy phenology, not seasonality of climate drivers, is the primary cause of photosynthetic seasonality in these forests. Specifically, synchronization of new leaf growth with dry season litterfall shifts canopy composition toward younger, more light-use efficient leaves, explaining large seasonal increases (~27%) in ecosystem photosynthesis. Coordinated leaf development and demography thus reconcile seemingly disparate observations at different scales and indicate that accounting for leaf-level phenology is critical for accurately simulating ecosystem-scale responses to climate change. <s> BIB047 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <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> BIB048 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Questions ::: ::: Pollination is an ecosystem function that varies at local spatial scales. Remote sensing may help to quantify and map the resulting patterns for a better understanding of ecosystem functioning. This task is challenging because the signal measured by sensors is dominated by leaf and canopy optical traits that determine the vegetation spectrum. No direct influence of pollination types (i.e. wind, insect and self-pollination) can be expected. We thus ask: (1) how strongly are pollination types at the community level linked with optical traits; and (2) do these links allow us to map spatial patterns of pollination types with remote sensing data? ::: ::: ::: ::: Location ::: ::: Mires and Molinia grasslands in Bavaria, southern Germany. ::: ::: ::: ::: Methods ::: ::: We sampled vascular plant species composition, as well as traits related to optical spectral signals, for 100 plots. Information on pollination types and additional optical traits were compiled from established plant trait databases. Simultaneously with the field sampling, image data of the study site were acquired using the airborne sensor AISA Dual. We tested for correlations between pollination types and optical traits. Based on these results, we regressed the plot-based information on pollination types against the corresponding spectral signal extracted from the image data. We inverted the models using the image in order to obtain maps of the pollination type distribution across the study site. ::: ::: ::: ::: Results ::: ::: In our study site, pollination types and optical traits were significantly correlated, up to R = −0.813 in the case of wind pollination and leaf dry matter content. These relations are, however, not necessarily transferable to other ecosystems, phenological stages and spatial scales, and their physical interpretation requires careful consideration. We were able to statistically model the spatial distribution of pollination types with a RMSE < 10.5%. The resulting maps provide detailed insights into the spatial distribution of pollination types at the community level. ::: ::: ::: ::: Conclusions ::: ::: The results show that pollination types are indeed related to canopy reflectance in a way that allows their mapping using remote sensing. More research is needed in order to improve our knowledge about transferable relations between pollination types and plant traits in other ecosystems and at different phenological stages. <s> BIB049 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> This study developed an approach for remote estimation of Vegetation Fraction (VF) and Flower Fraction (FF) in oilseed rape, which is a crop species with conspicuous flowers during reproduction. Canopy reflectance in green, red, red edge and NIR bands was obtained by a camera system mounted on an unmanned aerial vehicle (UAV) when oilseed rape was in the vegetative growth and flowering stage. The relationship of several widely-used Vegetation Indices (VI) vs. VF was tested and found to be different in different phenology stages. At the same VF when oilseed rape was flowering, canopy reflectance increased in all bands, and the tested VI decreased. Therefore, two algorithms to estimate VF were calibrated respectively, one for samples during vegetative growth and the other for samples during flowering stage. The results showed that the Visible Atmospherically Resistant Index (VARIgreen) worked most accurately for estimating VF in flower-free samples with an Root Mean Square Error (RMSE) of 3.56%, while the Enhanced Vegetation Index (EVI2) was the best in flower-containing samples with an RMSE of 5.65%. Based on reflectance in green and NIR bands, a technique was developed to identify whether a sample contained flowers and then to choose automatically the appropriate algorithm for its VF estimation. During the flowering season, we also explored the potential of using canopy reflectance or VIs to estimate FF in oilseed rape. No significant correlation was observed between VI and FF when soil was visible in the sensor’s field of view. Reflectance at 550 nm worked well for FF estimation with coefficient of determination (R2) above 0.6. Our model was validated in oilseed rape planted under different nitrogen fertilization applications and in different phenology stages. The results showed that it was able to predict VF and FF accurately in oilseed rape with RMSE below 6%. <s> BIB050 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Context ::: Evidence-based nature conservation focuses on ecological facts and the incorporation of knowledge on the ecology of species, including its entire life cycle. In butterflies, imagos and its larvae often demand specific and diverging micro-habitat structures and resources. In consequence, ecological requirements of the imaginal and pre-imaginal stage have to be taken into consideration to conduct effective conservation management. <s> BIB051 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> We examined whether variations in photosynthetic capacity are linked to variations in theenvironment and/or associated leaf traits for tropical moist forests (TMFs) in the Andes/west-ern Amazon regions of Peru. We compared photosynthetic capacity (maximal rate of carboxylation of Rubisco (Vcmax),and the maximum rate of electron transport (Jmax)), leaf mass, nitrogen (N) and phosphorus(P) per unit leaf area (Ma,Naand Pa, respectively), and chlorophyll from 210 species at 18ﬁeld sites along a 3300-m elevation gradient. Western blots were used to quantify the abun-dance of the CO₂-ﬁxing enzyme Rubisco. Area- and N-based rates of photosynthetic capacity at 25°C were higher in upland than low-land TMFs, underpinned by greater investment of N in photosynthesis in high-elevation trees. Soil [P] and leaf Pa were key explanatory factors for models of area-based Vcmax and Jmax but did not account for variations in photosynthetic N-use efﬁciency. At any given Na and Pa, the fraction of N allocated to photosynthesis was higher in upland than lowland species. For a smallsubset of lowland TMF trees examined, a substantial fraction of Rubisco was inactive. These results highlight the importance of soil- and leaf-P in deﬁning the photosyntheticcapacity of TMFs, with variations in N allocation and Rubisco activation state further inﬂuenc-ing photosynthetic rates and N-use efﬁciency of these critically important forests. <s> BIB052 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Abstract Larch, a deciduous needle-leaf gymnosperm, is widely distributed in cool temperate and boreal forests of the Northern Hemisphere. Thus, evaluating evapotranspiration (ET) in larch forests is important to elucidate energy and water cycles on a global scale. In addition, severe forest disturbance is expected to change ET and energy balance through a drastic change in the canopy structure. However, knowledge related to the environmental functions of larch forests in cool temperate regions remains lacking compared with Siberian larch forests. Furthermore, few reports describe quantified changes in ET and energy balance before and after forest disturbance. Therefore, for more than a decade, we measured sensible and latent heat fluxes using the eddy covariance technique above a larch forest in northern Japan and its succeeding ex-forest after a stand-replacing disturbance caused by windthrow. In general, the larch forest’s ET was not limited by water in contrast to that of a Siberian larch forest. Although the aboveground biomass decreased by 97% through the disturbance, both cumulative ET and latent heat flux normalized by incident solar radiation (lE/ R g ) during the snow-free period of about seven months were decreased by only 24% in the second year after disturbance. The 24% decrease was caused by 17% decrease in the partition of incident solar radiation to net radiation ( R g / R n ) and 9% decrease in the partition of net radiation to ET (lE/ R n ). The former resulted from increased albedo and decreased net longwave radiation, and the latter was mainly due to decrease in surface conductance. According to the vegetation recovery of shrubs and herbaceous plants, cumulative ET during the snow-free period increased gradually and almost reached pre-disturbance levels in six years. However, normalized ET by solar radiation (lE/ R g ) decreased in the 11th and 12th years after reaching the pre-disturbance level. Positive relationship between cumulative ET and vegetation indices indicates that the ET recovery was due to vegetation recovery. <s> BIB053 </s> Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics <s> Physiological and Functional ST <s> Leaf aging is a fundamental driver of changes in leaf traits, thereby regulating ecosystem processes and remotely sensed canopy dynamics. We explore leaf reflectance as a tool to monitor leaf age and develop a spectra-based partial least squares regression (PLSR) model to predict age using data from a phenological study of 1099 leaves from 12 lowland Amazonian canopy trees in southern Peru. Results demonstrated monotonic decreases in leaf water (LWC) and phosphorus (Pmass ) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (Nmass ) and carbon (Cmass ) contents showed monotonic but tree-specific age responses. We observed large age-related variation in leaf spectra across trees. A spectra-based model was more accurate in predicting leaf age (R2 = 0.86; percent root mean square error (%RMSE) = 33) compared with trait-based models using single (R2 = 0.07-0.73; %RMSE = 7-38) and multiple (R2 = 0.76; %RMSE = 28) predictors. Spectra- and trait-based models established a physiochemical basis for the spectral age model. Vegetation indices (VIs) including the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), normalized difference water index (NDWI) and photosynthetic reflectance index (PRI) were all age-dependent. This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing. <s> BIB054
Photosynthesis, photosynthesis pathway, chlorophyll fluorescence FD BIB052 BIB002 BIB008 BIB024 BIB025 BIB013  BIB031  BIB032 BIB012 BIB026 Carbon sequestration FD   BIB027 BIB028 BIB017 BIB033 BIB006 BIB029 BIB040 BIB041 BIB042  BIB007 Evapotranspiration FD BIB043 BIB018  BIB044 BIB045 BIB053 BIB034 Leaf respiration FD BIB046 BIB035 BIB030 BIB003 BIB010 BIB004 Phenology and senescence ST Leaf phenology type, leaf age, leaf development FD BIB054 BIB001 BIB047 BIB009 BIB036 BIB037 BIB019 Plant and canopy phenology FD BIB038 BIB005 BIB011 BIB016 BIB020 BIB048 BIB021   BIB022 BIB023 Flower mapping (Pollination types) TD, ST, FD BIB049 BIB014 BIB015 BIB050  BIB039 BIB051 