Browsing by Author "Baxter, Robert"
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Item Photosynthesis and productivity in heterogeneous arctic tundra: consequences for ecosystem function of mixing vegetation types at stand edges(2012-03) Fletcher, Benjamin J.; Gornall, Jemma L.; Poyatos, Rafael; Press, Malcom C.; Stoy, Paul C.; Huntley, Brian; Baxter, Robert; Phoenix, Gareth K.1. Arctic vegetation tends to be spatially heterogeneous and can have large areas of mixed ‘transition zone’ vegetation between stands dominated by a single or few species. If plant photosynthesis and growth within these transition zones differs significantly from main vegetation stands, and if transition zones are not considered when extrapolating stand-level findings to larger scales in space, then transition zones will provide considerable error to landscape-level estimates of gross primary productivity (GPP). 2. In a heterogeneous sub-Arctic tundra landscape, we undertook a detailed assessment of plant and ecosystem photosynthesis and plant growth in stands dominated by the short-stature evergreen dwarf shrub Empetrum hermaphroditum, the deciduous dwarf shrub Betula nana, the taller deciduous shrub Salix glauca and also the transition zones between them. 3. Our findings show that plants in transition zones towards taller and more productive vegetation types frequently showed reduced shoot growth, equal or reduced light-saturated photosynthesis (Pmax) and other typical shade responses (e.g. increased leaf chlorophyll and leaf area per mass) when compared with conspecific plants in main stands where the species is dominant. Critically, whole-ecosystem GPP per leaf area was 20–40% lower in transition zones than in main vegetation stands as a consequence. A modelling analysis suggests that the under-productivity of some transition zones results from the lack of a clear ‘winner’ in the competition for light, such that active leaves of some species are shaded by relatively inactive leaves of others. 4. These findings highlight how biotic interactions can considerably influence plant performance to the extent that productivity of mixed vegetation (transition zones) cannot be predicted from their main stands either side. How the consequences of mixing vegetation relate to mechanisms in biodiversity-function theory is discussed. 5. Synthesis: Our work shows that the productivity of transition zones of arctic vegetation is considerably lower than may be estimated from the main stands on either side. This reduced GPP in transition zones, therefore, must be considered when modelling carbon fluxes at the landscape scale and suggests that the impact of transition zones on ecosystem function needs further investigation in heterogeneous landscapes, where they make up a significant proportion of the land cover.Item Upscaling as ecological information transfer: A simple framework with application to arctic ecosystem carbon exchange(2009-06) Stoy, Paul C.; Williams, Mathew; Prieto-Blanco, Ana; Huntley, Brian; Baxter, Robert; Lewis, PhilipTransferring ecological information across scale often involves spatial aggregation, which alters information content and may bias estimates if the scaling process is nonlinear. Here, a potential solution, the preservation of the information content of fine-scale measurements, is highlighted using modeled net ecosystem exchange (NEE) of an Arctic tundra landscape as an example. The variance of aggregated normalized difference vegetation index (NDVI), measured from an airborne platform, decreased linearly with log(scale), resulting in a linear relationship between log(scale) and the scale-wise modeled NEE estimate. Preserving three units of information, the mean, variance and skewness of fine-scale NDVI observations, resulted in upscaled NEE estimates that deviated less than 4% from the fine-scale estimate. Preserving only the mean and variance resulted in nearly 23% NEE bias, and preserving only the mean resulted in larger error and a change in sign from CO2 sink to source. Compressing NDVI maps by 70–75% using wavelet thresholding with the Haar and Coiflet basis functions resulted in 13% NEE bias across the study domain. Applying unique scale-dependent transfer functions between NDVI and leaf area index (LAI) decreased, but did not remove, bias in modeled flux in a smaller expanse using handheld NDVI observations. Quantifying the parameters of statistical distributions to preserve ecological information reduces bias when upscaling and makes possible spatial data assimilation to further reduce errors in estimates of ecological processes across scale.