Publications by authors named "Koen Hufkens"

Banana Bunchy Top Disease (BBTD) has been reported in southwestern Rwanda since the 1980s. Recent sporadic observations of BBTD in western and central regions, made by extension services and the Rwanda Agriculture and Animal Resources Development Board (RAB), merited a comprehensive field survey across the country. This survey was performed in 2022-2023 to confirm and map the presence of BBTD in suspected areas in Rwanda.

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A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or 'proximal' remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site-level eddy-covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high-spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions.

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Urban focused semantically segmented datasets (e.g. ADE20k or CoCo) have been crucial in boosting research and applications in urban areas by providing rich sources of delineated objects in Street View Images (SVI).

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Tropical forest phenology directly affects regional carbon cycles, but the relation between species-specific and whole-canopy phenology remains largely uncharacterized. We present a unique analysis of historical tropical tree phenology collected in the central Congo Basin, before large-scale impacts of human-induced climate change. Ground-based long-term (1937-1956) phenological observations of 140 tropical tree species are recovered, species-specific phenological patterns analyzed and related to historical meteorological records, and scaled to characterize stand-level canopy dynamics.

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Recent studies have suggested the presence of moonlight mediated behaviour in avian aerial insectivores, such as swifts. Here, we use the combined analysis of state-of-the-art activity logger data across three swift species, the common, pallid and alpine swifts, to quantify flight height and activity in responses to moonlight-driven crepuscular and nocturnal light conditions. Our results show a significant response in flight heights to moonlight illuminance for common and pallid swifts, i.

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Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal - bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data.

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Land carbon dynamics in temperate and boreal ecosystems are sensitive to environmental change. Accurately simulating gross primary productivity (GPP) and its seasonality is key for reliable carbon cycle projections. However, significant biases have been found in early spring GPP simulations of northern forests, where observations often suggest a later resumption of photosynthetic activity than predicted by models.

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Leaf phenology is key for regulating total growing-season mass and energy fluxes. Long-term temporal trends towards earlier leaf unfolding are observed across Northern Hemisphere forests. Phenological dates also vary between years, whereby end-of-season (EOS) dates correlate positively with start-of-season (SOS) dates and negatively with growing-season total net CO assimilation (A).

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In deciduous forests, spring leaf development and fall leaf senescence regulate the timing and duration of photosynthesis and transpiration. Being able to model these dates is therefore critical to accurately representing ecosystem processes in biogeochemical models. Despite this, there has been relatively little effort to improve internal phenology predictions in widely used biogeochemical models.

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Long-term atmospheric CO concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength.

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Article Synopsis
  • Arctic warming is impacting snow cover and soil hydrology, which in turn affects carbon sequestration in tundra ecosystems.
  • A study using 119 site-years of data revealed that earlier snowmelt boosts carbon sequestration and plant productivity in early summer (June-July) but reduces them in August.
  • Despite higher evapotranspiration leading to potential soil drying, earlier snowmelt did not significantly decrease soil moisture, suggesting that without continued carbon uptake in late summer, the benefits of a longer growing season may not be realized.
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Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower-based CO flux measurements, and a predictive model to simulate seasonal canopy color dynamics.

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The CONterminous United States (CONUS) presents a large range of climate conditions and biomes where terrestrial primary productivity and its inter-annual variability are controlled regionally by rainfall and/or temperature. Here, the response of ecosystem productivity to those climate variables was investigated across different biomes from 2010 to 2018 using three climate datasets of precipitation, air temperature or drought severity, combined with several proxies of ecosystem productivity: a remote sensing product of aboveground biomass, an net primary productivity (NPP) remote sensing product, an NPP model-based product and four gross primary productivity products. We used an asymmetry index (AI) where positive AI indicates a greater increase of ecosystem productivity in wet years compared to the decline in dry years, and negative AI indicates a greater decline of ecosystem productivity in dry years compared to the increase in wet years.

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Leaf optical properties impact leaf energy balance and thus leaf temperature. The effect of leaf development on mid-infrared (MIR) reflectance, and hence thermal emissivity, has not been investigated in detail. We measured a suite of morphological characteristics, as well as directional-hemispherical reflectance from ultraviolet to thermal infrared wavelengths (250 nm to 20 µm) of leaves from five temperate deciduous tree species over the 8 wk following spring leaf emergence.

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Monitoring vegetation phenology is critical for quantifying climate change impacts on ecosystems. We present an extensive dataset of 1783 site-years of phenological data derived from PhenoCam network imagery from 393 digital cameras, situated from tropics to tundra across a wide range of plant functional types, biomes, and climates. Most cameras are located in North America.

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Many plant phenological events are sensitive to temperature, leading to changes in the seasonal cycle of ecosystem function as the climate warms. To evaluate the current and future implications of temperature changes for plant phenology, researchers commonly use a metric of temperature sensitivity, which quantifies the change in phenology per degree change in temperature. Here, we examine the temperature sensitivity of phenology, and highlight conditions under which the widely used days-per-degree sensitivity approach is subject to methodological issues that can generate misleading results.

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Changes in terrestrial tropical carbon stocks have an important role in the global carbon budget. However, current observational tools do not allow accurate and large-scale monitoring of the spatial distribution and dynamics of carbon stocks. Here, we used low-frequency L-band passive microwave observations to compute a direct and spatially explicit quantification of annual aboveground carbon (AGC) fluxes and show that the tropical net AGC budget was approximately in balance during 2010 to 2017, the net budget being composed of gross losses of -2.

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Increasing evidence is available for a positive effect of biodiversity on ecosystem productivity and standing biomass, also in highly diverse systems as tropical forests. Biodiversity conservation could therefore be a critical aspect of climate mitigation policies. There is, however, limited understanding of the role of individual species for this relationship, which could aid in focusing conservation efforts and forest management planning.

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Premise Of The Study: We investigated the spatial and temporal patterns of vegetation phenology with phenometrics derived from PhenoCam imagery. Specifically, we evaluated the Bioclimatic Law proposed by Hopkins, which relates phenological transitions to latitude, longitude, and elevation.

Methods: "Green-up" and "green-down" dates-representing the start and end of the annual cycles of vegetation activity-were estimated from measures of canopy greenness calculated from digital repeat photography.

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Snow is important for local to global climate and surface hydrology, but spatial and temporal heterogeneity in the extent of snow cover make accurate, fine-scale mapping and monitoring of snow an enormous challenge. We took 184,453 daily near-surface images acquired by 133 automated cameras and processed them using crowdsourcing and deep learning to determine whether snow was present or absent in each image. We found that the crowdsourced data had an accuracy of 99.

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Shifts in vegetation phenology are a key example of the biological effects of climate change. However, there is substantial uncertainty about whether these temperature-driven trends will continue, or whether other factors-for example, photoperiod-will become more important as warming exceeds the bounds of historical variability. Here we use phenological transition dates derived from digital repeat photography to show that experimental whole-ecosystem warming treatments of up to +9 °C linearly correlate with a delayed autumn green-down and advanced spring green-up of the dominant woody species in a boreal Picea-Sphagnum bog.

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In deciduous forests, spring leaf phenology controls the onset of numerous ecosystem functions. While most studies have focused on a single annual spring event, such as budburst, ecosystem functions like photosynthesis and transpiration increase gradually after budburst, as leaves grow to their mature size. Here, we examine the "velocity of green-up," or duration between budburst and leaf maturity, in deciduous forest ecosystems of eastern North America.

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Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones.

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Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America.

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