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Question: Is there a relationship between size and death in the Iona-lived, deep-rooted tree, Acacia erioloba, in a semi-arid savanna? What is the size-class distribution of A. erioloba mortality? Does the mortality distribution differ from total tree size distribution? Does A. erioloba mortality distribution match the mortality distributions recorded thus far in other environments? Location: Dronfield Ranch, near Kimberley, Kalahari, South Africa. Methods: A combination of aerial photographs and a satellite image covering 61 year was used to provide long-term spatial data on mortality. We used aerial photographs of the study area from 1940, 1964, 1984, 1993 and a satellite image from 2001 to follow three plots covering 510 ha. We were able to identify and individually follow ca. 3000 individual trees from 1940 till 2001. Results: The total number of trees increased over time. No relationship between total number of trees and mean tree size was detected. There were no trends over time in total number of deaths per plot or in size distributions of dead trees. Kolmogorov-Smirnov tests showed no differences in size class distributions for living trees through time. The size distribution of dead trees was significantly different from the size distribution of all trees present on the plots. Overall, the number of dead trees was low in small size classes, reached a peak value when canopy area was 20 - 30 m(2), and declined in lamer size-classes. Mortality as a ratio of dead vs. total trees peaked at intermediate canopy sizes too. Conclusion: A. erioloba mortality was size-dependent, peaking at intermediate sizes. The mortality distribution differs from all other tree mortality distributions recorded thus far. We suggest that a possible mechanism for this unusual mortality distribution is intraspecific competition for water in this semi-arid environment.
Retrieval of water constituents from hyperspectral in-situ measurements under variable cloud cover
(2018)
Remote sensing and field spectroscopy of natural waters is typically performed under clear skies, low wind speeds and low solar zenith angles. Such measurements can also be made, in principle, under clouds and mixed skies using airborne or in-situ measurements; however, variable illumination conditions pose a challenge to data analysis. In the present case study, we evaluated the inversion of hyperspectral in-situ measurements for water constituent retrieval acquired under variable cloud cover. First, we studied the retrieval of Chlorophyll-a (Chl-a) concentration and colored dissolved organic matter (CDOM) absorption from in-water irradiance measurements. Then, we evaluated the errors in the retrievals of the concentration of total suspended matter (TSM), Chl-a and the absorption coefficient of CDOM from above-water reflectance measurements due to highly variable reflections at the water surface. In order to approximate cloud reflections, we extended a recent three-component surface reflectance model for cloudless atmospheres by a constant offset and compared different surface reflectance correction procedures. Our findings suggest that in-water irradiance measurements may be used for the analysis of absorbing compounds even under highly variable weather conditions. The extended surface reflectance model proved to contribute to the analysis of above-water reflectance measurements with respect to Chl-a and TSM. Results indicate the potential of this approach for all-weather monitoring.