Person: Hufkens, Koen
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Hufkens
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Koen
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Hufkens, Koen
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Publication Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery(Copernicus GmbH, 2014) Klosterman, Stephen; Hufkens, Koen; Gray, J. M.; Melaas, E.; Sonnentag, O.; Lavine, I.; Mitchell, L.; Norman, R.; Friedl, M. A.; Richardson, AndrewPlant phenology regulates ecosystem services at local and global scales and is a sensitive indicator of global change. Estimates of phenophase transition dates, such as the start of spring or end of autumn, can be derived from sensor-based time series data at the near-surface and remote scales, but must be interpreted in terms of biologically relevant events. We use the PhenoCam archive of digital repeat photography to implement a consistent protocol for visual assessment of canopy phenology at 13 temperate deciduous forest sites throughout eastern North America, as well as to perform digital image analysis for time series-based estimates of phenology dates. We then compare these near-surface results to remote sensing metrics of phenology at the landscape scale, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) sensors. We present a new type of curve fit, using a generalized sigmoid, to estimate phenology dates. We quantify the statistical uncertainty of phenophase transition dates estimated using this method and show that the generalized sigmoid results in less statistical uncertainty than other curve-fitting methods. Additionally, we find that dates derived from analysis of high-frequency PhenoCam imagery have smaller uncertainties than remote sensing metrics of phenology, and that dates derived from the remotely-sensed enhanced vegetation index (EVI) have smaller uncertainty than those derived from the normalized difference vegetation index (NDVI). Near-surface time series estimates for the start of spring are found to closely match visual assessment of leaf out, as well as remote sensing-derived estimates of the start of spring. However late spring and autumn phenology exhibit larger differences between near-surface and remote scales. Differences in late spring phenology between near-surface and remote scales are found to correlate with a landscape metric of deciduous forest cover. These results quantify the effect of landscape heterogeneity when aggregating to the coarser spatial scales of remote sensing, and demonstrate the importance of accurate curve fitting and vegetation index selection when analyzing and interpreting phenology time series.Publication Greenness indices from digital cameras predict the timing and seasonal dynamics of canopy-scale photosynthesis(Ecological Society of America, 2014) Toomey, Michael; Friedl, Mark; Frolking, Steve; Hufkens, Koen; Klosterman, Stephen; Sonnentag, Oliver; Baldocchi, Dennis; Bernacchi, Carl; Biraud, Sebastien; Bohrer, Gil; Brzostek, Edward; Burns, Sean P.; Coursolle, Carole; Hollinger, David Y.; Margolis, Hank A.; McCaughey, Harry; Monson, Russell K.; Munger, J.; Pallardy, Stephen; Phillips, Richard P.; Torn, Margaret; Wharton, Sonia; Zeri, Marcello; Richardson, AndrewThe proliferation of digital cameras co-located with eddy covariance instrumentation provides new opportunities to better understand the relationship between canopy phenology and the seasonality of canopy photosynthesis. In this paper we analyze the abilities and limitations of canopy color metrics measured by digital repeat photography to track seasonal canopy development and photosynthesis, determine phenological transition dates, and estimate intra-annual and interannual variability in canopy photosynthesis. We used 59 site-years of camera imagery and net ecosystem exchange measurements from 17 towers spanning three plant functional types (deciduous broadleaf forest, evergreen needle leaf forest and grassland/crops) to derive color indices and estimate gross primary productivity (GPP). GPP was strongly correlated with greenness derived from camera imagery in all three plant functional types. Specifically, the beginning of the photosynthetic period in deciduous broadleaf forest and grassland/crops and the end of the photosynthetic period in grassland/crops were both correlated with changes in greenness; changes in redness were correlated with the end of the photosynthetic period in deciduous broadleaf forest. However, it was not possible to accurately identify the beginning or ending of the photosynthetic period using camera greenness in evergreen needle leaf forest. At deciduous broadleaf sites, anomalies in integrated greenness and total GPP were significantly correlated up to 60 days after the mean onset date for the start of spring. More generally, results from this work demonstrate that digital repeat photography can be used to quantify both the duration of the photosynthetically active period as well as total GPP in deciduous broadleaf forest and grassland/crops, but that new and different approaches are required before comparable results can be achieved in evergreen needleleaf forest.Publication Season Spotter: Using Citizen Science to Validate and Scale Plant Phenology from Near-Surface Remote Sensing(MDPI AG, 2016) Kosmala, Margaret; Crall, Alycia; Cheng, Rebecca; Hufkens, Koen; Henderson, Sandra; Richardson, AndrewAbstract: The impact of a rapidly changing climate on the biosphere is an urgent area of research for mitigation policy and management. Plant phenology is a sensitive indicator of climate change and regulates the seasonality of carbon, water, and energy fluxes between the land surface and the climate system, making it an important tool for studying biosphere-atmosphere interactions. To monitor plant phenology at regional and continental scales, automated near-surface cameras are being increasingly used to supplement phenology data derived from satellite imagery and data from ground-based human observers. We used imagery from a network of phenology cameras in a citizen science project called Season Spotter to investigate whether information could be derived from these images beyond standard, color-based vegetation indices. We found that engaging citizen science volunteers resulted in useful science knowledge in three ways: first, volunteers were able to detect some, but not all, reproductive phenology events, connecting landscape-level measures with field-based measures. Second, volunteers successfully demarcated individual trees in landscape imagery, facilitating scaling of vegetation indices from organism to ecosystem. And third, volunteers’ data were used to validate phenology transition dates calculated from vegetation indices and to identify potential improvements to existing algorithms to enable better biological interpretation. As a result, the use of citizen science in combination with near-surface remote sensing of phenology can be used to link ground-based phenology observations to satellite sensor data for scaling and validation. Well-designed citizen science projects targeting improved data processing and validation of remote sensing imagery hold promise for providing the data needed to address grand challenges in environmental science and Earth observation.Publication Aboveground vs. Belowground Carbon Stocks in African Tropical Lowland Rainforest: Drivers and Implications(Public Library of Science, 2015) Doetterl, Sebastian; Kearsley, Elizabeth; Bauters, Marijn; Hufkens, Koen; Lisingo, Janvier; Baert, Geert; Verbeeck, Hans; Boeckx, PascalBackground: African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors. Principal Findings Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock) were only half compared to an area with lower tree height (= smaller aboveground carbon stock). This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system. Conclusions/Significance: We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to the terrestrial C budget.Publication Functional community structure of African monodominant Gilbertiodendron dewevrei forest influenced by local environmental filtering(John Wiley and Sons Inc., 2016) Kearsley, Elizabeth; Verbeeck, Hans; Hufkens, Koen; Van de Perre, Frederik; Doetterl, Sebastian; Baert, Geert; Beeckman, Hans; Boeckx, Pascal; Huygens, DriesAbstract Monodominant patches of forest dominated by Gilbertiodendron dewevrei are commonly found in central African tropical forests, alongside forests with high species diversity. Although these forests are generally found sparsely distributed along rivers, their occurrence is not thought to be (clearly) driven by edaphic conditions but rather by trait combinations of G. dewevrei that aid in achieving monodominance. Functional community structure between these monodominant and mixed forests has, however, not yet been compared. Additionally, little is known about nondominant species in the monodominant forest community. These two topics are addressed in this study. We investigate the functional community structure of 10 one‐hectare plots of monodominant and mixed forests in a central region of the Congo basin, in DR Congo. Thirteen leaf and wood traits are measured, covering 95% (basal area weighted) of all species present in the plots, including leaf nutrient contents, leaf isotopic compositions, specific leaf area, wood density, and vessel anatomy. The trait‐based assessment of G. dewevrei shows an ensemble of traits related to water use and transport that could be favorable for its location near forest rivers. Moreover, indications have been found for N and P limitations in the monodominant forest, possibly related to ectomycorrhizal associations formed with G. dewevrei. Reduced leaf N and P contents are found at the community level for the monodominant forest and for different nondominant groups, as compared to those in the mixed forest. In summary, this work shows that environmental filtering does prevail in the monodominant G. dewevrei forest, leading to lower functional diversity in this forest type, with the dominant species showing beneficial traits related to its common riverine locations and with reduced soil N and P availability found in this environment, both coregulating the tree community assembly.