Phenology

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Zhuosen Wang - One of the best experts on this subject based on the ideXlab platform.

  • fine scale perspectives on landscape Phenology from unmanned aerial vehicle uav photography
    Agricultural and Forest Meteorology, 2018
    Co-Authors: Stephen Klosterman, Eli K Melaas, Jonathan A Wang, Arturo Martinez, Sidni Frederick, John Okeefe, David A Orwig, Zhuosen Wang
    Abstract:

    Abstract Forest Phenology is a multi-scale phenomenon, arising from processes in leaves and trees, with effects on the ecology of plant communities and landscapes. Because Phenology controls carbon and water cycles, which are commonly observed at the ecosystem scale (e.g. eddy flux measurements), it is important to characterize the relation between phenophase transition events at different spatial scales. We use aerial photography recorded from an unmanned aerial vehicle (UAV) to observe plant Phenology over a large area (5.4 ha) and across diverse communities, with spatial and temporal resolution at the scale of individual tree crowns and their phenophase transition events (10 m spatial resolution, ∼5 day temporal resolution in spring, weekly in autumn). We validate UAV-derived phenophase transition dates through comparison with direct observations of tree Phenology, PhenoCam image analysis, and satellite remote sensing. We then examine the biological correlates of spatial variance in Phenology using a detailed species inventory and land cover classification. Our results show that species distribution is the dominant factor in spatial variability of ecosystem Phenology. We also explore statistical relations governing the scaling of Phenology from an organismic scale (10 m) to forested landscapes (1 km) by analyzing UAV photography alongside Landsat and MODIS data. From this analysis we find that spatial standard deviation in transition dates decreases linearly with the logarithm of increasing pixel size. We also find that fine-scale Phenology aggregates to a coarser scale as the median and not the mean date in autumn, indicating coarser scale Phenology is less sensitive to the tails of the distribution of sub-pixel transitions in the study area. Our study is the first to observe forest Phenology in a spatially comprehensive, whole-ecosystem way, yet with fine enough spatial resolution to describe organism-level correlates and scaling phenomena.

Alemu Gonsamo - One of the best experts on this subject based on the ideXlab platform.

  • land surface Phenology derived from normalized difference vegetation index ndvi at global fluxnet sites
    Agricultural and Forest Meteorology, 2017
    Co-Authors: Dailiang Peng, Christopher M Gough, Alemu Gonsamo, Kamel Soudani, Lukas Siebicke, Altaf M Arain, Gil Bohrer, Peter M Lafleur, Matthias Peichl, Bin Fang
    Abstract:

    Abstract Phenology is an important indicator of annual plant growth and is also widely incorporated in ecosystem models to simulate interannual variability of ecosystem productivity under climate change. A comprehensive understanding of the potentials of current algorithms to detect the start and end for growing season (SOS and EOS) from remote sensing is still lacking. This is particularly true when considering the diverse interactions between Phenology and climate change among plant functional types as well as potential influences from different sensors. Using data from 60 flux tower sites (376 site-years in total) from the global FLUXNET database, we applied four algorithms to extract plant Phenology from time series of normalized difference vegetation index (NDVI) from both MODIS and SPOT-VGT sensors. Results showed that NDVI-simulated Phenology had overall low correlation (R 2

  • the match and mismatch between photosynthesis and land surface Phenology of deciduous forests
    Agricultural and Forest Meteorology, 2015
    Co-Authors: Petra Dodorico, Christopher M Gough, Alemu Gonsamo, Gil Bohrer, James Morison, Matthew Wilkinson, Paul J Hanson, Damiano Gianelle, Jose D Fuentes, Nina Buchmann
    Abstract:

    Abstract Plant Phenology is a key indicator of the terrestrial biosphere's response to climate change, as well as a driver of global climate through changes in the carbon, energy and water cycles. Remote sensing observations of seasonal canopy greenness dynamics represent a valuable means to study land surface Phenology (LSP) at scales relevant for comparison with regional climate information as well as ecosystem-level CO2 fluxes. We explore relationships among key LSP dates at the start and end of the season captured by three remote sensing products (i.e., NDVI: Normalized Difference Vegetation Index; PI: Phenology Index; MODIS Land Cover Dynamics Product based on the Enhanced Vegetation Index, EVI) over 19 deciduous broadleaf and mixed forest sites in the northern hemisphere for 2000–2012, and compare these estimates to estimates of start and end of photosynthesis Phenology extracted from gross primary productivity (GPP) from CO2 flux measurements. To derive phenological transition dates, we use analytical solutions of various derivatives from the fitted logistic curves. LSP dates estimated by the three remote sensing products were not equivalent and differed in their sign and magnitude of lags with photosynthesis Phenology dates. NDVI-derived Phenology was characterized by shorter growing seasons, while EVI prolonged it by about two weeks compared to the photosynthesis Phenology season length. PI start and end of season dates more closely matched the start (r2 = 0.84, RMSE = 7.61) and end (r2 = 0.61, RMSE = 8.57) of photosynthesis Phenology as estimated by GPP time series. PI was also found agreeing best with LSP estimates from highly spatially resolved ground digital camera observations, available for about half of the investigated FLUXNET sites. Although there were strong relationships between remotely sensed LSP and photosynthesis Phenology, the relationships were not consistent across deciduous forest ecosystems implying that the vegetative and photosynthetic timing do not always follow each other in the same direction.

  • evidence of autumn Phenology control on annual net ecosystem productivity in two temperate deciduous forests
    Ecological Engineering, 2013
    Co-Authors: Christopher M Gough, Jing M Chen, Alemu Gonsamo
    Abstract:

    Abstract Phenology exercises a critical control on annual carbon uptake by terrestrial ecosystems. Autumn Phenology, while less studied relative to spring Phenology, may also constrain annual net ecosystem productivity (NEP). Using 17-year (1992–2008) records of C flux Phenology (CFP) derived from continuous eddy covariance (EC) measurements at the Harvard Forest (HF), here we show that the autumn Phenology played a more significant role than the spring Phenology in controlling annual NEP. We found that the onset of carbon uptake (CU) in spring only explained 39% of annual NEP, compared to 66% of end of CU in autumn. Though neither onset nor end of gross primary productivity (GPP) was correlated with annual NEP, the autumn lag, i.e., the time lag between ends of GPP and CU, was found to have a particularly high potential in explaining annual NEP (R2 = 0.82, p

Christopher M Gough - One of the best experts on this subject based on the ideXlab platform.

  • land surface Phenology derived from normalized difference vegetation index ndvi at global fluxnet sites
    Agricultural and Forest Meteorology, 2017
    Co-Authors: Dailiang Peng, Christopher M Gough, Alemu Gonsamo, Kamel Soudani, Lukas Siebicke, Altaf M Arain, Gil Bohrer, Peter M Lafleur, Matthias Peichl, Bin Fang
    Abstract:

    Abstract Phenology is an important indicator of annual plant growth and is also widely incorporated in ecosystem models to simulate interannual variability of ecosystem productivity under climate change. A comprehensive understanding of the potentials of current algorithms to detect the start and end for growing season (SOS and EOS) from remote sensing is still lacking. This is particularly true when considering the diverse interactions between Phenology and climate change among plant functional types as well as potential influences from different sensors. Using data from 60 flux tower sites (376 site-years in total) from the global FLUXNET database, we applied four algorithms to extract plant Phenology from time series of normalized difference vegetation index (NDVI) from both MODIS and SPOT-VGT sensors. Results showed that NDVI-simulated Phenology had overall low correlation (R 2

  • the match and mismatch between photosynthesis and land surface Phenology of deciduous forests
    Agricultural and Forest Meteorology, 2015
    Co-Authors: Petra Dodorico, Christopher M Gough, Alemu Gonsamo, Gil Bohrer, James Morison, Matthew Wilkinson, Paul J Hanson, Damiano Gianelle, Jose D Fuentes, Nina Buchmann
    Abstract:

    Abstract Plant Phenology is a key indicator of the terrestrial biosphere's response to climate change, as well as a driver of global climate through changes in the carbon, energy and water cycles. Remote sensing observations of seasonal canopy greenness dynamics represent a valuable means to study land surface Phenology (LSP) at scales relevant for comparison with regional climate information as well as ecosystem-level CO2 fluxes. We explore relationships among key LSP dates at the start and end of the season captured by three remote sensing products (i.e., NDVI: Normalized Difference Vegetation Index; PI: Phenology Index; MODIS Land Cover Dynamics Product based on the Enhanced Vegetation Index, EVI) over 19 deciduous broadleaf and mixed forest sites in the northern hemisphere for 2000–2012, and compare these estimates to estimates of start and end of photosynthesis Phenology extracted from gross primary productivity (GPP) from CO2 flux measurements. To derive phenological transition dates, we use analytical solutions of various derivatives from the fitted logistic curves. LSP dates estimated by the three remote sensing products were not equivalent and differed in their sign and magnitude of lags with photosynthesis Phenology dates. NDVI-derived Phenology was characterized by shorter growing seasons, while EVI prolonged it by about two weeks compared to the photosynthesis Phenology season length. PI start and end of season dates more closely matched the start (r2 = 0.84, RMSE = 7.61) and end (r2 = 0.61, RMSE = 8.57) of photosynthesis Phenology as estimated by GPP time series. PI was also found agreeing best with LSP estimates from highly spatially resolved ground digital camera observations, available for about half of the investigated FLUXNET sites. Although there were strong relationships between remotely sensed LSP and photosynthesis Phenology, the relationships were not consistent across deciduous forest ecosystems implying that the vegetative and photosynthetic timing do not always follow each other in the same direction.

  • evidence of autumn Phenology control on annual net ecosystem productivity in two temperate deciduous forests
    Ecological Engineering, 2013
    Co-Authors: Christopher M Gough, Jing M Chen, Alemu Gonsamo
    Abstract:

    Abstract Phenology exercises a critical control on annual carbon uptake by terrestrial ecosystems. Autumn Phenology, while less studied relative to spring Phenology, may also constrain annual net ecosystem productivity (NEP). Using 17-year (1992–2008) records of C flux Phenology (CFP) derived from continuous eddy covariance (EC) measurements at the Harvard Forest (HF), here we show that the autumn Phenology played a more significant role than the spring Phenology in controlling annual NEP. We found that the onset of carbon uptake (CU) in spring only explained 39% of annual NEP, compared to 66% of end of CU in autumn. Though neither onset nor end of gross primary productivity (GPP) was correlated with annual NEP, the autumn lag, i.e., the time lag between ends of GPP and CU, was found to have a particularly high potential in explaining annual NEP (R2 = 0.82, p

Andrew D Richardson - One of the best experts on this subject based on the ideXlab platform.

  • mesic temperate deciduous forest Phenology
    2013
    Co-Authors: Jonathan M Hanes, Andrew D Richardson, Stephen Klosterman
    Abstract:

    Deciduous forests in temperate climates are characterized by significant seasonal changes in ecological and biogeochemical processes that are directly linked to forest Phenology. The timing of spring leaf emergence and autumn leaf senescence is heavily determined by weather and climate, and these phenological events influence the seasonal cycles of water, energy, and carbon fluxes. In addition to its role in ecological interactions and in regulating ecosystem processes, deciduous forest Phenology has also been shown to be a robust indicator of the biological impacts of climate change on forest ecosystems. With an emphasis on spring leaf emergence and autumn leaf senescence, this chapter highlights the Phenology of canopy trees in mesic temperate deciduous forests by describing the climate of these forests, environmental drivers of Phenology, feedback of Phenology on lower atmospheric processes, impacts of climate change on Phenology, and future research directions.

  • Linking near-surface and satellite remote sensing measurements of deciduous broadleaf forest Phenology
    Remote Sensing of Environment, 2012
    Co-Authors: Koen Hufkens, Tom Milliman, Bobby H. Braswell, Martin Friedl, Oliver Sonnentag, Andrew D Richardson
    Abstract:

    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.

John A Silander - One of the best experts on this subject based on the ideXlab platform.

  • predicting autumn Phenology how deciduous tree species respond to weather stressors
    Agricultural and Forest Meteorology, 2018
    Co-Authors: Xiaojing Wang, Adam M Wilson, John A Silander
    Abstract:

    Abstract Shifts in the timing of autumnal leaf coloration and leaf drop in temperate forests with climate change can have substantial impacts on community and ecosystem processes (e.g. altered carbon/nitrogen cycling and biotic interactions). However, the environmental control of autumn Phenology remains significantly understudied in striking contrast to spring Phenology. In this study, we used linear mixed effects model with ground-based Phenology observations in northeastern USA and found that both weather stressors (e.g. heat- and drought-stress and heavy rainfall) during the growing season and spring Phenology significantly affected inter-annual variation in autumn Phenology of twelve dominant deciduous tree species. While warm temperatures and drought lead to later fall Phenology for most species, heavy rainfall and heat stress lead to earlier leaf coloration and leaf drop. We also found that the phenological sensitivities to weather stressors are diversely species-specific. Under future climate change projections, we predicted that greater summer heat-stress in the future will cause abbreviated leaf coloration seasons for most species. Our mixed-effects modeling framework suggested that accounting for phenological variations among individual trees, species and sites largely improved model predictions, which should not be overlooked in phenological model development. Our study improves our understanding of how species-specific autumnal Phenology responds to weather stresses, and describes a new modeling framework to investigate both inter-annual phenological changes and local variations among trees, species, and sites. Our predictions on autumn phenological shifts will help in assessing the effects of climate change on forest community and ecosystem processes in the future.

  • deciduous forest responses to temperature precipitation and drought imply complex climate change impacts
    Proceedings of the National Academy of Sciences of the United States of America, 2015
    Co-Authors: Xiaojing Wang, John A Silander
    Abstract:

    Changes in spring and autumn Phenology of temperate plants in recent decades have become iconic bio-indicators of rapid climate change. These changes have substantial ecological and economic impacts. However, autumn Phenology remains surprisingly little studied. Although the effects of unfavorable environmental conditions (e.g., frost, heat, wetness, and drought) on autumn Phenology have been observed for over 60 y, how these factors interact to influence autumn phenological events remain poorly understood. Using remotely sensed Phenology data from 2001 to 2012, this study identified and quantified significant effects of a suite of environmental factors on the timing of fall dormancy of deciduous forest communities in New England, United States. Cold, frost, and wet conditions, and high heat-stress tended to induce earlier dormancy of deciduous forests, whereas moderate heat- and drought-stress delayed dormancy. Deciduous forests in two eco-regions showed contrasting, nonlinear responses to variation in these explanatory factors. Based on future climate projection over two periods (2041–2050 and 2090–2099), later dormancy dates were predicted in northern areas. However, in coastal areas earlier dormancy dates were predicted. Our models suggest that besides warming in climate change, changes in frost and moisture conditions as well as extreme weather events (e.g., drought- and heat-stress, and flooding), should also be considered in future predictions of autumn Phenology in temperate deciduous forests. This study improves our understanding of how multiple environmental variables interact to affect autumn Phenology in temperate deciduous forest ecosystems, and points the way to building more mechanistic and predictive models.