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  • 1
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    Emerging opportunities and challenges in phenology : a review (2016)
    John Wiley & Sons
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    Publication Date: 2022-05-25
    Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecosphere 7 (2016): e01436, doi:10.1002/ecs2.1436.
    Description: Plant phenology research has gained increasing attention because of the sensitivity of phenology to climate change and its consequences for ecosystem function. Recent technological development has made it possible to gather invaluable data at a variety of spatial and ecological scales. Despite our ability to observe phenological change at multiple scales, the mechanistic basis of phenology is still not well understood. Integration of multiple disciplines, including ecology, evolutionary biology, climate science, and remote sensing, with long-term monitoring data across multiple spatial scales is needed to advance understanding of phenology. We review the mechanisms and major drivers of plant phenology, including temperature, photoperiod, and winter chilling, as well as other factors such as competition, resource limitation, and genetics. Shifts in plant phenology have significant consequences on ecosystem productivity, carbon cycling, competition, food webs, and other ecosystem functions and services. We summarize recent advances in observation techniques across multiple spatial scales, including digital repeat photography, other complementary optical measurements, and solar-induced fluorescence, to assess our capability to address the importance of these scale-dependent drivers. Then, we review phenology models as an important component of earth system modeling. We find that the lack of species-level knowledge and observation data leads to difficulties in the development of vegetation phenology models at ecosystem or community scales. Finally, we recommend further research to advance understanding of the mechanisms governing phenology and the standardization of phenology observation methods across networks. With the opportunity for “big data” collection for plant phenology, we envision a breakthrough in process-based phenology modeling.
    Description: U.S. National Science Foundation Grant Numbers: PLR-1417763, DBI-959333, AGS-1005663; University of Chicago and the MBL Lillie Research Innovation Award; NEXT Program; KAKENHI (MEXT, Japan); National Science Foundation of China Grant Number: 41571103; NERC Grant Number: NE/J02080X/1
    Keywords: Cameras ; Greenness ; ILTER ; Modeling ; Phenology ; Scale ; International LTER
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
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    Relationship between leaf physiologic traits and canopy color indices during the leaf expansion period in an oak forest (2016)
    John Wiley & Sons
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    Publication Date: 2022-05-25
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecosphere 6, no. 12 (2015): 1-9, doi:10.1890/ES14-00452.1.
    Description: Plant phenology has a significant impact on the forest ecosystem carbon balance. Detecting plant phenology by capturing the time-series canopy images through digital camera has become popular in recent years. However, the relationship between color indices derived from camera images and plant physiological characters are elusive during the growing season in temperate ecosystems. We collected continuous images of forest canopy, leaf size, leaf area index (LAI) and leaf chlorophyll measured by a soil plant analysis development (SPAD) analyzer in a northern subtropical oak forest in China. Our results show that (1) the spring peak of color indices, Gcc (Green Chromatic Coordinates) and ExG (Excess Green), was 18 days earlier than the 90% maximum SPAD value; (2) the 90% maximum SPAD value coincided with the change point of Gcc and ExG immediately after their spring peak; and (3) the spring curves of Gcc and ExG before their peaks were highly synchronous with the expansion of leaf size and the development of LAI value. We suggest it needs to be adjusted if camera-derived Gcc or ExG is used as a proxy of chlorophyll or gross primary productivity, and images observation should be complemented with field phenological and physiological information to interpret the physiological meaning of leaf seasonality.
    Description: This research was funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions in the Discipline of Environmental Science and Engineering at Nanjing Forest University, Changjiang River Delta Urban Forest Ecosystem Research of CFERN (to H. Hu) and Brown University Seed Funds for International Research Projects on the Environment (to J. Tang).
    Keywords: Chlorophyll ; Greenness indices ; Leaf area index ; Leaf sizes ; Phenology ; Plant images
    Repository Name: Woods Hole Open Access Server
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  • 3
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    Using canopy greenness index to identify leaf ecophysiological traits during the foliar senescence in an oak forest (2018)
    Ecological Society of America
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    Publication Date: 2022-05-25
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecosphere 9 (2018): e02337, doi:10.1002/ecs2.2337.
    Description: Camera‐based observation of forest canopies allows for low‐cost, continuous, high temporal‐spatial resolutions of plant phenology and seasonality of functional traits. In this study, we extracted canopy color index (green chromatic coordinate, Gcc) from the time‐series canopy images provided by a digital camera in a deciduous forest in Massachusetts, USA. We also measured leaf‐level photosynthetic activities and leaf area index (LAI) development in the field during the growing season, and corresponding leaf chlorophyll concentrations in the laboratory. We used the Bayesian change point (BCP) approach to analyze Gcc. Our results showed that (1) the date of starting decline of LAI (DOY 263), defined as the start of senescence, could be mathematically identified from the autumn Gcc pattern by analyzing change points of the Gcc curve, and Gcc is highly correlated with LAI after the first change point when LAI was decreasing (R2 = 0.88, LAI 〈 2.5 m2/m2); (2) the second change point of Gcc (DOY 289) started a more rapid decline of Gcc when chlorophyll concentration and photosynthesis rates were relatively low (13.4 ± 10.0% and 23.7 ± 13.4% of their maximum values, respectively) and continuously reducing; and (3) the third change point of Gcc (DOY 295) marked the end of growing season, defined by the termination of photosynthetic activities, two weeks earlier than the end of Gcc curve decline. Our results suggested that with the change point analysis, camera‐based phenology observation can effectively quantify the dynamic pattern of the start of senescence (with declining LAI) and the end of senescence (when photosynthetic activities terminated) in the deciduous forest.
    Description: Priority Academic Program Development of Jiangsu Higher Education Institutions in Discipline of Environmental Science and Engineer in Nanjing Forest University; China Scholarship Council Grant Number: 201506190095; Brown University Seed Funds for International Research Projects on the Environment
    Keywords: Chlorophyll ; Digital camera ; Leaf area index ; Phenology ; Photosynthesis ; Senescence
    Repository Name: Woods Hole Open Access Server
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  • 4
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    Comparison of phenology estimated from reflectance-based indices and solar-induced chlorophyll fluorescence (SIF) observations in a temperate forest using GPP-based phenology as the standard (2018)
    MDPI AG
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 10 (2018): 932, doi:10.3390/rs10060932.
    Description: We assessed the performance of reflectance-based vegetation indices and solar-induced chlorophyll fluorescence (SIF) datasets with various spatial and temporal resolutions in monitoring the Gross Primary Production (GPP)-based phenology in a temperate deciduous forest. The reflectance-based indices include the green chromatic coordinate (GCC), field measured and satellite remotely sensed Normalized Difference Vegetation Index (NDVI); and the SIF datasets include ground-based measurement and satellite-based products. We found that, if negative impacts due to coarse spatial and temporal resolutions are effectively reduced, all these data can serve as good indicators of phenological metrics for spring. However, the autumn phenological metrics derived from all reflectance-based datasets are later than the those derived from ground-based GPP estimates (flux sites). This is because the reflectance-based observations estimate phenology by tracking physiological properties including leaf area index (LAI) and leaf chlorophyll content (Chl), which does not reflect instantaneous changes in phenophase transitions, and thus the estimated fall phenological events may be later than GPP-based phenology. In contrast, we found that SIF has a good potential to track seasonal transition of photosynthetic activities in both spring and fall seasons. The advantage of SIF in estimating the GPP-based phenology lies in its inherent link to photosynthesis activities such that SIF can respond quickly to all factors regulating phenological events. Despite uncertainties in phenological metrics estimated from current spaceborne SIF observations due to their coarse spatial and temporal resolutions, dates in middle spring and autumn—the two most important metrics—can still be reasonably estimated from satellite SIF. Our study reveals that SIF provides a better way to monitor GPP-based phenological metrics.
    Description: This research was supported by U. S. Department of Energy Office of Biological and Environmental Research Grant DE-SC0006951, National Science Foundation Grants DBI 959333 and AGS-1005663, and the University of Chicago and the MBL Lillie Research Innovation Award to Jianwu Tang and China Scholarship Council No. 201506190095 to Z. Liu. Xiaoliang Lu was also supported by the open project grant (LBKF201701) of Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences.
    Keywords: Solar-induced chlorophyll fluorescence ; Reflectance ; Phenology ; Fall phenological events
    Repository Name: Woods Hole Open Access Server
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  • 5
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    Seasonal patterns of canopy photosynthesis captured by remotely sensed sun-induced fluorescence and vegetation indexes in mid-to-high latitude forests : a cross-platform comparison (2018)
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2018. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Science of The Total Environment 644 (2018): 439-451, doi:10.1016/j.scitotenv.2018.06.269.
    Description: Characterized by the noticeable seasonal patterns of photosynthesis, mid-to-high latitude forests are sensitive to climate change and crucial for understanding the global carbon cycle. To monitor the seasonal cycle of the canopy photosynthesis from space, several remote sensing based indexes, such as normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and leaf area index (LAI), have been implemented within the past decades. Recently, satellite-derived sun-induced fluorescence (SIF) has shown great potentials of providing retrievals that are more related to photosynthesis process. However, the potentials of different canopy measurements have not been thoroughly assessed in the context of recent advances of new satellites and proposals of improved indexes. Here, we present a cross-site intercomparison of one emerging remote sensing based index of phenological index (PI) and two SIF datasets against the conventional indexes of NDVI, EVI and LAI to capture the seasonal cycles of canopy photosynthesis. NDVI, EVI, LAI and PI were calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements, while SIF were evaluated from Global Ozone Monitoring Experiment-2 (GOME-2) and Orbiting Carbon Observatory-2 (OCO-2) observations. Results indicated that GOME-2 SIF was highly correlated with gross primary productivity (GPP) and absorbed photosynthetically active radiation (APAR) during the growing seasons. Key phenological metrics captured by SIF from GOME-2 and OCO-2 matched closely with photosynthesis phenology as inferred by GPP. However, the applications of OCO-2 SIF for phenological studies may be limited only for a small range of sites (at site-level) due to a limited spatial sampling. Among the MODIS estimations, PI and NDVI provided most reliable predictions of start of growing seasons, while no indexes accurately captured the end of growing seasons.
    Description: This work was supported by the Chinese Arctic and Antarctic Administration, National Natural Science Foundation of China (Grant Nos. 41676176 and 41676182), the Chinese Polar Environment Comprehensive Investigation, Assessment Program (Grant No. 312231103). This work was also supported by the Fundamental Research Funds for the 440 Central Universities
    Description: 2020-07-11
    Keywords: Phenology ; Remote sensing ; Photosynthesis ; OCO-2 ; SIF ; NDVI ; EVI ; PI ; LAI
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
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  • 6
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    Seasonal variability of multiple leaf traits captured by leaf spectroscopy at two temperate deciduous forests (2016)
    Details
    Publication Date: 2022-05-26
    Description: Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here for personal use, not for redistribution. The definitive version was published in Remote Sensing of Environment 179 (2016): 1-12, doi:10.1016/j.rse.2016.03.026.
    Description: Understanding the temporal patterns of leaf traits is critical in determining the seasonality and magnitude of terrestrial carbon and water fluxes. However, robust and efficient ways to monitor the temporal dynamics of leaf traits are lacking. Here we assessed the potential of using leaf spectroscopy to predict leaf traits across their entire life cycle, forest sites, and light environments (sunlit vs. shaded) using a weekly sampled dataset across the entire growing season at two temperate deciduous forests. The dataset includes field measured leaf-level directional-hemispherical reflectance/transmittance together with seven important leaf traits [total chlorophyll (chlorophyll a and b), carotenoids, mass-based nitrogen concentration (Nmass), mass-based carbon concentration (Cmass), and leaf mass per area (LMA)]. All leaf properties, including leaf traits and spectra, varied significantly throughout the growing season, and displayed trait-specific temporal patterns. We used a Partial Least Square Regression (PLSR) analysis to estimate leaf traits from spectra, and found a significant capability of PLSR to capture the variability across time, sites, and light environment of all leaf traits investigated (R2=0.6~0.8 for temporal variability; R2=0.3~0.7 for cross-site variability; R2=0.4~0.8 for variability from light environments). We also tested alternative field sampling designs and found that for most leaf traits, biweekly leaf sampling throughout the growing season enabled accurate characterization of the leaf trait seasonal patterns. Increasing the sampling frequency improved in the estimation of Nmass, Cmass and LMA comparing with foliar pigments. Our results, based on the comprehensive analysis of spectra-trait relationships across time, sites and light environments, highlight the capacity and potential limitations to use leaf spectra to estimate leaf traits with strong seasonal variability, as an alternative to time-consuming traditional wet lab approaches.
    Description: This research was supported by the Brown University–Marine Biological Laboratory graduate program in Biological and Environmental Sciences, and Marine Biological Laboratory start-up funding for JT. JT was also partially supported by the U.S. Department of Energy (U.S. DOE) Office of Biological and Environmental Research grant DE-SC0006951 and the National Science Foundation grants DBI-959333 and AGS-1005663. SPS was supported in part by the U.S. DOE contract No. DE-SC00112704 to Brookhaven National Laboratory. JW was supported by the NASA Earth and Space Science Fellowship (NESSF2014).
    Keywords: Phenology ; Leaf physiology ; Foliar chemistry ; Carbon cycle ; Chlorophyll ; Carotenoids ; Nitrogen ; Leaf mass per area ; Partial least square regression (PLSR) ; Sun and shaded leaves
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
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  • 7
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    Beyond leaf color : comparing camera-based phenological metrics with leaf biochemical, biophysical, and spectral properties throughout the growing season of a temperate deciduous forest (2014)
    John Wiley & Sons
    Details
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 119 (2014): 181-191, doi:10.1002/2013JG002460.
    Description: Plant phenology, a sensitive indicator of climate change, influences vegetation-atmosphere interactions by changing the carbon and water cycles from local to global scales. Camera-based phenological observations of the color changes of the vegetation canopy throughout the growing season have become popular in recent years. However, the linkages between camera phenological metrics and leaf biochemical, biophysical, and spectral properties are elusive. We measured key leaf properties including chlorophyll concentration and leaf reflectance on a weekly basis from June to November 2011 in a white oak forest on the island of Martha's Vineyard, Massachusetts, USA. Concurrently, we used a digital camera to automatically acquire daily pictures of the tree canopies. We found that there was a mismatch between the camera-based phenological metric for the canopy greenness (green chromatic coordinate, gcc) and the total chlorophyll and carotenoids concentration and leaf mass per area during late spring/early summer. The seasonal peak of gcc is approximately 20 days earlier than the peak of the total chlorophyll concentration. During the fall, both canopy and leaf redness were significantly correlated with the vegetation index for anthocyanin concentration, opening a new window to quantify vegetation senescence remotely. Satellite- and camera-based vegetation indices agreed well, suggesting that camera-based observations can be used as the ground validation for satellites. Using the high-temporal resolution dataset of leaf biochemical, biophysical, and spectral properties, our results show the strengths and potential uncertainties to use canopy color as the proxy of ecosystem functioning.
    Description: This research was supported by the Brown University– Marine Biological Laboratory graduate program in Biological and Environmental Sciences, Brown–ECI phenology working group, Brown Office of International Affairs Seed Grant on phenology, and Marine Biological Laboratory start-up funding for JT.
    Description: 2014-09-30
    Keywords: Green-up ; Senescence ; Phenology ; Leaf physiology ; Chlorophyll ; Vegetation spectroscopy
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 8
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    Ecotypic differences in the phenology of the tundra species Eriophorum vaginatum reflect sites of origin (2017)
    John Wiley & Sons
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    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecology and Evolution 7 (2017): 9775–9786, doi:10.1002/ece3.3445.
    Description: Eriophorum vaginatum is a tussock-forming sedge that contributes significantly to the structure and primary productivity of moist acidic tussock tundra. Locally adapted populations (ecotypes) have been identified across the geographical distribution of E. vaginatum; however, little is known about how their growth and phenology differ over the course of a growing season. The growing season is short in the Arctic and therefore exerts a strong selection pressure on tundra species. This raises the hypothesis that the phenology of arctic species may be poorly adapted if the timing and length of the growing season change. Mature E. vaginatum tussocks from across a latitudinal gradient (65–70°N) were transplanted into a common garden at a central location (Toolik Lake, 68°38′N, 149°36′W) where half were warmed using open-top chambers. Over two growing seasons (2015 and 2016), leaf length was measured weekly to track growth rates, timing of senescence, and biomass accumulation. Growth rates were similar across ecotypes and between years and were not affected by warming. However, southern populations accumulated significantly more biomass, largely because they started to senesce later. In 2016, peak biomass and senescence of most populations occurred later than in 2015, probably induced by colder weather at the beginning of the growing season in 2016, which caused a delayed start to growth. The finish was delayed as well. Differences in phenology between populations were largely retained between years, suggesting that the amount of time that these ecotypes grow has been selected by the length of the growing seasons at their respective home sites. As potential growing seasons lengthen, E. vaginatum may be unable to respond appropriately as a result of genetic control and may have reduced fitness in the rapidly warming Arctic tundra.
    Description: National Science Foundation Grant Numbers: 1417645, 1417763, 1418010
    Keywords: Arctic tundra ; Common garden ; Ecotypes ; Eriophorum vaginatum ; Growing season length ; Local adaptation ; Phenology ; Senescence
    Repository Name: Woods Hole Open Access Server
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