Search NASA⌕ Search

SEARCH · Search NASA

Results for “temperate forest”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Antarctic Soils Select Copiotroph-Dominated Bacteria

The life strategies of bacterial communities determine their structure and function and are an important driver of biogeochemical cycling. However, the variations in these strategies under different soil resource conditions remain largely unknown. We explored the bacterial life strategies and changes in structure and functions between Antarctic soils and forest (temperate, subtropical, and tropical) soils. The results showed that the weighted mean rRNA operon copy number in temperate soils was 19.5% lower than that in Antarctic soils, whereas no significant differences were observed among Antarctic, subtropical, and tropical soils. An unexpected result was that bacterial communities in Antarctic soils tended to be copiotrophs, such as Actinobacteriota and Bacteroidota, whereas those in temperate soils tended to be oligotrophs, such as Acidobacteriota and Chloroflexi. Functional predictions showed that in comparison to copiotrophs in Antarctic soils, temperate-inhabiting oligotrophic bacteria exhibited an 84.2–91.1% lower abundance of labile C decomposition genes (hemicellulose, cellulose, monosaccharides, and disaccharides), whereas a 74.4% higher abundance of stable C decomposition (lignin). Genes involved in N cycling (nitrogen fixation, assimilatory nitrate reduction, and denitrification) were 24.3–64.4% lower in temperate soils than in Antarctic soils. Collectively, our study provides a framework for describing the life strategies of soil bacteria, which are crucial to global biogeochemical cycles.

Microbiology↗
DOE OSTI2021

Multi-scale assessment of a grassland productivity model

Grasslands provide many important ecosystem services globally, and projecting grassland productivity in the coming decades will provide valuable information to land managers. Productivity models can be well calibrated at local scales but generally have some maximum spatial scale in which they perform well. Here we evaluate a grassland productivity model to find the optimal spatial scale for parameterization and thus for subsequently applying it in future productivity projections for North America. We also evaluated the model on new vegetation types to ascertain its potential generality. We find the model most suitable when incorporating only grasslands, as opposed to also including agriculture and shrublands, and only in the Great Plains and eastern temperate forest ecoregions of North America. The model was not well suited to grasslands in North American deserts or northwest forest ecoregions. It also performed poorly in agriculture vegetation, likely due to management activities, and shrubland vegetation, likely because the model lacks representation of deep water pools. This work allows us to perform long-term projections in areas where model performance has been verified, with gaps filled in by future modeling efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Global transpiration data from sap flow measurements: the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land–atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The “sapfluxnetr” R package – designed to access, visualize, and process SAPFLUXNET data – is available from CRAN.

58 GEOSCIENCES↗
DOE OSTI2021

Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of the numerical solution approach of a plant hydrodynamic model (v0.1) on vegetation dynamics

Abstract. Numerous plant hydrodynamic models have started to be implemented in vegetation dynamics models, reflecting the central role of plant hydraulic traits in driving water, energy, and carbon cycles, as well as plant adaptation to climate change. Different numerical approximations of the governing equations of the hydrodynamic models have been documented, but the numerical accuracy of these models and its subsequent effects on the simulated vegetation function and dynamics have rarely been evaluated. Using different numerical solution methods (including implicit and explicit approaches) and vertical discrete grid resolutions, we evaluated the numerical performance of a plant hydrodynamic module in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES-HYDRO version 0.1) based on single-point and global simulations. Our simulation results showed that when near-surface vertical grid spacing is coarsened (grid size >10 cm), the model significantly overestimates aboveground biomass (AGB) in most of the temperate forest locations and underestimates AGB in the boreal forest locations, as compared to a simulation with finer vertical grid spacing. Grid coarsening has a small effect on AGB in the tropical zones of Asia and South America. In particular, coarse surface grid resolution should not be used when there are large and prolonged water content differences among soil layers at depths due to long dry-season duration and/or well-drained soil or when soil evaporation is a dominant fraction of evapotranspiration. Similarly, coarse surface grid resolution should not be used when there is lithologic discontinuity along the soil depth. This information is useful for uncertainty quantification, sensitivity analysis, or the training of surrogate models to design the simulations when computational cost limits the use of ensemble simulations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Investigation of environmental change pattern in Japan. Investigation of the ecological environment index from observation of the regional vegetation cover and their growing condition

The author has identified the following significant results. Practical use of recognition results of LANDSAT data as the base map of the field survey or the retouching work of vegetation and land use has the effective benefit to cut down the cost, labor, and time lower than 10% of a conventional method. Correct and detailed vegetation maps were prepared using combined interpretation of repetition of data of different seasons at warm and temperate forested areas.

Maruyasu, T.↗
NASA NTRS1995

High spectral resolution remote sensing of canopy chemistry

Near infrared laboratory spectra have been used for many years to determine nitrogen and lignin concentrations in plant materials. In recent years, similar high spectral resolution visible and infrared data have been available via airborne remote sensing instruments. Using data from NASA's Airborne visible/Infrared Imaging Spectrometer (AVIRIS) we attempt to identify spectral regions correlated with foliar chemistry at the canopy level in temperate forests.

Aber, John D.↗
NASA NTRS2021

Cutting out the Middleman: Calibrating and Validating a Dynamic Vegetation Model (ED2-PROSPECT5) Using Remotely Sensed Surface Reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types. Using a single common set of parameters across all sites, the calibrated model was able to accurately reproduce surface reflectance for sites with highly varied forest composition and structure. However, the calibrated model's predictions of leaf area index (LAI) were less robust, capturing only 46 % of the variability in the observations. Comparing the ED2 radiative transfer model with another two-stream soil–leaf–canopy radiative transfer model commonly used in remote sensing studies (PRO4SAIL) illustrated structural errors in the ED2 representation of direct radiation backscatter that resulted in systematic underestimation of reflectance. In addition, we also highlight that, to directly compare with a two-stream radiative transfer model like EDR, we had to perform an additional processing step to convert the directional reflectance estimates of AVIRIS to hemispherical reflectance (also known as “albedo”). In future work, we recommend that vegetation models add the capability to predict directional reflectance, to allow them to more directly assimilate a wide range of airborne and satellite reflectance products. We ultimately conclude that despite these challenges, using dynamic vegetation models to predict surface reflectance is a promising avenue for model calibration and validation using remote sensing data.

Alexey N Shiklomanov↗
DOE OSTI2022

Demographic composition, not demographic diversity, predicts biomass and turnover across temperate and tropical forests

The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass (AGB), and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either AGB or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct DCs of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the DC of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Phenology of Photosynthesis in Winter‐Dormant Temperate and Boreal Forests: Long‐Term Observations From Flux Towers and Quantitative Evaluation of Phenology Models

Abstract We examined the seasonality of photosynthesis in 46 evergreen needleleaf (evergreen needleleaf forests (ENF)) and deciduous broadleaf (deciduous broadleaf forests (DBF)) forests across North America and Eurasia. We quantified the onset and end (Start GPP and End GPP ) of photosynthesis in spring and autumn based on the response of net ecosystem exchange of CO 2 to sunlight. To test the hypothesis that snowmelt is required for photosynthesis to begin, these were compared with end of snowmelt derived from soil temperature. ENF forests achieved 10% of summer photosynthetic capacity ∼3 weeks before end of snowmelt, while DBF forests achieved that capacity ∼4 weeks afterward. DBF forests increased photosynthetic capacity in spring faster (1.95% d −1 ) than ENF (1.10% d −1 ), and their active season length (End GPP –Start GPP ) was ∼50 days shorter. We hypothesized that warming has influenced timing of the photosynthesis season. We found minimal evidence for long‐term change in Start GPP , End GPP , or air temperature, but their interannual anomalies were significantly correlated. Warmer weather was associated with earlier Start GPP (1.3–2.5 days °C −1 ) or later End GPP (1.5–1.8 days °C −1 , depending on forest type and month). Finally, we tested whether existing phenological models could predict Start GPP and End GPP . For ENF forests, air temperature‐ and daylength‐based models provided best predictions for Start GPP , while a chilling‐degree‐day model was best for End GPP . The root mean square errors (RMSE) between predicted and observed Start GPP and End GPP were 11.7 and 11.3 days, respectively. For DBF forests, temperature‐ and daylength‐based models yielded the best results (RMSE 6.3 and 10.5 days).

Environmental Sciences & Ecology↗
NASA NTRS1993

Relating P-band AIRSAR backscatter to forest stand parameters

As part of research on forest ecosystems, the Jet Propulsion Laboratory (JPL) and collaborating research teams have conducted multi-season airborne synthetic aperture radar (AIRSAR) experiments in three forest ecosystems including temperate pine forest (Duke, Forest, North Carolina), boreal forest (Bonanza Creek Experimental Forest, Alaska), and northern mixed hardwood-conifer forest (Michigan Biological Station, Michigan). The major research goals were to improve understanding of the relationships between radar backscatter and phenological variables (e.g. stand density, tree size, etc.), to improve radar backscatter models of tree canopy properties, and to develop a radar-based scheme for monitoring forest phenological changes. In September 1989, AIRSAR backscatter data were acquired over the Duke Forest. As the aboveground biomass of the loblolly pine forest stands at Duke Forest increased, the SAR backscatter at C-, L-, and P-bands increased and saturated at different biomass levels for the C-band, L-band, and P-band data. We only use the P-band backscatter data and ground measurements here to study the relationships between the backscatter and stand density, the backscatter and mean trunk dbh (diameter at breast height) of trees in the stands, and the backscatter and stand basal area.

Wang, Yong↗
DOE OSTI2022

Arbuscular Mycorrhizal Tree Communities Have Greater Soil Fungal Diversity and Relative Abundances of Saprotrophs and Pathogens than Ectomycorrhizal Tree Communities

Trees associating with different mycorrhizas often differ in their effects on litter decomposition, nutrient cycling, soil organic matter (SOM) dynamics, and plant-soil interactions. For example, due to differences between arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) tree leaf and root traits, ECM-associated soil has lower rates of C and N cycling and lower N availability than AM-associated soil. These observations suggest that many groups of nonmycorrhizal fungi should be affected by the mycorrhizal associations of dominant trees through controls on nutrient availability. To test this overarching hypothesis, we explored the influence of predominant forest mycorrhizal type and mineral N availability on soil fungal communities using next-generation amplicon sequencing. Soils from four temperate hardwood forests in southern Indiana, United States, were studied; three forests formed a natural gradient of mycorrhizal dominance (100% AM tree basal area to 100% ECM basal area), while the fourth forest contained a factorial experiment testing long-term N addition in both dominant mycorrhizal types. We found that overall fungal diversity, as well as the diversity and relative abundance of plant pathogenic and saprotrophic fungi, increased with greater AM tree dominance. Additionally, tree community mycorrhizal associations explained more variation in fungal community composition than abiotic variables, including soil depth, SOM content, nitrification rate, and mineral N availability. Our findings suggest that tree mycorrhizal associations may be good predictors of the diversity, composition, and functional potential of soil fungal communities in temperate hardwood forests. These observations help explain differing biogeochemistry and community dynamics found in forest stands dominated by differing mycorrhizal types.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Impact of prescribed fire on soil microbial communities in a Southern Appalachian Forest clear-cut

Escalating wildfire frequency and severity, exacerbated by shifting climate patterns, pose significant ecological and economic challenges. Prescribed burns, a common forest management tool, aim to mitigate wildfire risks and protect biodiversity. Nevertheless, understanding the impact of prescribed burns on soil and microbial communities in temperate mixed forests, considering temporal dynamics and slash fuel types, remains crucial. Our study, conducted at the University of Tennessee Forest Resources AgResearch and Education Center in Oak Ridge, TN, employed controlled burns across various treatments, and the findings indicate that low-intensity prescribed burns have none or minimal short-term effects on soil parameters but may alter soil nutrient concentrations, as evidenced by significant changes in porewater acetate, formate, and nitrate concentrations. These burns also induce shifts in microbial community structure and diversity, with Proteobacteria and Acidobacteria increasing significantly post-fire, possibly aiding soil recovery. In contrast, Verrucomicrobia showed a notable decrease over time, and other specific microbial taxa correlated with soil pH, porewater nitrate, ammonium , and phosphate concentrations. Our research contributes to understanding the intricate relationships between prescribed fire, soil dynamics, and microbial responses in temperate mixed forests in the Southern Appalachian Region, which is valuable for informed land management practices in the face of evolving environmental challenges.

Microbiology↗
NASA NTRS2017

Airborne Measurements of Western U.S. Wildfire Emissions: Comparison with Prescribed Burning and Air Quality Implications

Wildfires emit significant amounts of pollutants that degrade air quality. Plumes from three wildfires in the western U.S. were measured from aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Biomass Burning Observation Project (BBOP), both in summer 2013. This study reports an extensive set of emission factors (EFs) for over 80 gases and 5 components of submicron particulate matter (PM1) from these temperate wildfires. These include rarely, or never before, measured oxygenated volatile organic compounds and multifunctional organic nitrates. The observed EFs are compared with previous measurements of temperate wildfires, boreal forest fires, and temperate prescribed fires. The wildfires emitted high amounts of PM1 (with organic aerosol (OA) dominating the mass) with an average EF that is more than 2 times the EFs for prescribed fires. The measured EFs were used to estimate the annual wildfire emissions of carbon monoxide, nitrogen oxides, total non methane organic compounds, and PM1 from 11 western U.S. states. The estimated gas emissions are generally comparable with the 2011 National Emissions Inventory (NEI). However, our PM1 emission estimate (1530 +/- 570 Gg/yr) is over 3 times that of the NEI PM2.5 estimate and is also higher than the PM2.5 emitted from all other sources in these states in the NEI. This study indicates that the source of OA from biomass burning in the western states is significantly underestimated. In addition, our results indicate that prescribed burning may be an effective method to reduce fine particle emissions.

measured oxygenated volatile organic compounds↗
NASA NTRS2021

Assessing impacts of canopy 3D structure on chlorophyll fluorescence radiance and radiative budget of deciduous forest stands using DART

Although remote sensing (RS) of solar-induced chlorophyll fluorescence (SIF) is increasingly used as a valuable source of information about vegetation photosynthetic activity, the RS SIF observations are significantly influenced by canopy-specific structural features (i.e., canopy architecture including leaf area index and presence of woody components), atmospheric conditions during their acquisition (e.g., proportion of direct and diffuse irradiance) and observational geometric configurations (e.g., sun and viewing directions). Radiative transfer (RT) models have the potential to provide a better understanding of the canopy structural effects on the SIF emission and RS signals. Here, we used the DART model to assess the daily influence, from morning to evening, of forest 3D architecture on SIF nadir radiance, emission, escape factor and nadir yield of eight 100 m × 100 m forest study plots established in a temperate deciduous forest of the Smithsonian Environmental Research Center (Edgewater, MD, USA). The 3D architecture of each plot was derived from airborne LiDAR. DART simulations of these 3D forest plots and their 1D (i.e., vertical profile of sun-adapted and shade-adapted leaves) and 0D (i.e., homogeneous layer of sun-adapted leaves above an homogeneous layer of shade-adapted leaves) abstractions were compared to assess the relative errors (ε1D−3D and ε0D−3D) associated with horizontal and vertical structural heterogeneity, respectively. Forest 3D structure, especially horizontal heterogeneity, had a great influence on forest nadir SIF radiance, resulting in ε1D−3D up to 55% at 8:00 and 18:00 (i.e., for oblique sun directions). The key indicators of this impact, in the descending order of importance, were the SIF escape factor (ε1D−3D up to 40%), the attenuation of incident photosynthetically active radiation (ε1D−3D less than 5%), and the SIF emission yield (ε1D−3D less than 2%). The influence of forest architecture on the nadir SIF escape factor and SIF yield (ε1D−3D up to 40%) varied over time, with differences in forest stand structure, and per spectral domain, being always larger between 640 and 700 nm than between 700 and 850 nm. In addition, woody elements demonstrated a large influence on forest SIF radiance due to their “shading” effect (ε up to 17%) and their “blocking” effect (ε ≈ 10%), both of them higher for far-red than for red SIF. These results underline the importance of 3D forest canopy architecture, especially 2D heterogeneity, and inclusion of woody elements in RT modeling used for interpretation of the RS SIF signal, and subsequently for the estimation of gross primary production and detection of vegetation stress.

Omar Regaieg↗
DOE OSTI2022

Cascadia Burning: The historic, but not historically unprecedented, 2020 wildfires in the Pacific Northwest, USA

Abstract Wildfires devastated communities in Oregon and Washington in September 2020, burning almost as much forest west of the Cascade Mountain crest (“the westside”) in 2 weeks (~340,000 ha) as in the previous five decades (~406,00 ha). Unlike dry forests of the interior western United States, temperate rain forests of the Pacific Northwest have experienced limited recent fire activity, and debates surrounding what drove the 2020 fires, and management strategies to adapt to similar future events, necessitate a scientific evaluation of the fires. We evaluate five questions regarding the 2020 Labor Day fires: (1) How do the 2020 fires compare with historical fires? (2) How did the roles of weather and antecedent climate differ geographically and from the recent past (1979–2019)? (3) How do fire size and severity compare to other recent fires (1985–2019), and how did forest management and prefire forest structure influence burn severity? (4) What impact will these fires have on westside landscapes? and (5) How can we adapt to similar fires in the future? Although 5 of the 2020 fires were much larger than any others in the recent past and burned ~10 times the area in high‐severity patches >10,000 ha, the 2020 fires were remarkably consistent with historical fires. Reports from the early 1900s, along with paleo‐ and dendro‐ecological records, indicate similar and potentially even larger wildfires over the past millennium, many of which shared similar seasonality (late August/early September), weather conditions, and even geographic locations. Consistent with the largest historical fires, strong east winds and anomalously dry conditions drove the rapid spread of high‐severity wildfire in 2020. We found minimal difference in burn severity among stand structural types related to previous management in the 2020 fires. Adaptation strategies for similar fires in the future could benefit by focusing on ignition prevention, fire suppression, and community preparedness, as opposed to fuel treatments that are unlikely to mitigate fire severity during extreme weather. While scientific uncertainties remain regarding the nature of infrequent, high‐severity fires in westside forests, particularly under climate change, adapting to their future occurrence will require different strategies than those in interior, dry forests.

Reilly, Matthew J.↗
DOE OSTI2023

Remote sensing of seasonal variation of LAI and fAPAR in a deciduous broadleaf forest

Climate change is affecting the phenology of terrestrial ecosystems. In deciduous forests, phenology in leaf area index (LAI) is the primary driver of seasonal variation in the fraction of absorbed photosynthetically active radiation (fAPAR), which drives photosynthesis. Remote sensing has been widely used to estimate LAI and fAPAR. However, while many studies have examined both empirical and model-based relationships among LAI, fAPAR, and spectral vegetation indices (SVI) from remote sensing, few studies have systematically and empirically examined how relationships among these variables change over the growing season. In this study, we examine how and why seasonal-scale covariation differs among time series of remotely sensed SVIs and both LAI and fAPAR based on current understanding and theory. To do this we use newly available remote sensing data sets in combination with time series of in-situ measurements and a canopy radiative transfer model to analyze how seasonal variation in canopy and environmental conditions affect relationships among remotely sensed SVIs, LAI, and fAPAR at a temperate deciduous forest site in central Massachusetts. Our results show that accounting for seasonal variation in canopy shadowing, which is driven by variation in solar zenith angle, improved remote sensing-based estimates of LAI, fAPAR, and daily total APAR. Specifically, we show that the phenology of SVIs is strongly influenced by seasonal variation in near infrared (NIR) reflectance arising from systematic variation in the canopy shadow fraction that is independent of changes in LAI or fAPAR. Therefore, results of this work provide a refined basis for understanding how remote sensing can be used to monitor and model the phenology of LAI, fAPAR, APAR, and gross primary productivity in temperate deciduous forests.

54 ENVIRONMENTAL SCIENCES↗