Environmental changes in biodiversity hotspot ecosystems of
South Ecuador: RESPonse and feedback effECTs (FOR2730)

Abstract:

This paper presents a method to extrapolate wind-speed data and to calculate wind-speed and dynamic pressure maps for the complex topography of a mountain rainforest area in the tropical Andes of southeastern Ecuador. The spatial differentiation of dynamic wind pressure in this area is claimed to be a major determinant of the altitude of the tree-line ecotone and to affect the tree line’s physiognomy. The paper presents a hybrid method encompassing statistical data analysis using the Weibull distribution and a digital terrain analysis, taking topographical shelter effects into account. The method is used to derive mean and maximum wind-speed and dynamic pressure maps to reveal whether the tree-line ecotone is influenced by direct wind effects. On average, the tree-line ecotone on the eastern slopes shows a clear average depression of ~50 m. These slopes are affected by higher dynamic wind stress, so have a more disturbed canopy. These altered vegetation structures may be caused mainly by direct wind effects and to a smaller extent by indirect effects, such as high humidity.

Abstract:

The sloping mire landscape of the investigation area, in the southern Andes of Ecuador, is dominated by stagnic soils with thick organic layers. The recursive partitioning algorithm Random Forest was used to predict the spatial water stagnation pattern and the thickness of the organic layer from terrain attributes. Terrain smoothing from 10 to 30m raster resolution was applied in order to obtain the best possible model. For the same purpose, several model tuning parameters were tested and a prepredictor selection with the R-package Boruta was applied. Model versions were evaluated and compared by 100 repetitions of the calculation of the residual mean square error of a five-fold cross-validation. Position specific density functions of the predicted soil parameters were then used to display prediction uncertainty. Prepredictor selection and tuning of the Random Forest algorithm in some cases resulted in an improved model performance.We therefore recommend testing prepredictor selection and tuning to make sure that the best possible model is chosen.This needs particular emphasis in complex tropical mountain soil-landscapes which provide a real challenge to any soil mapping approach but where Random Forest has proven to be successful due to the testing of model tuning and prepredictor selection.

Abstract:

The thermal structure of a megadiverse mountain ecosystem in southern Ecuador is examined on the basis of temperature measurements inside the natural mountain forest and at open sites along an altitudinal gradient from 1700m to 3200m. The data is used to calculated maps of monthly average minimum, mean and maximum 2m air temperature for the period 1999-2007, needed by ecological projects. The maps are generated by combining the straightforward detrending technique by using a Digital Elevation Model and satellite-based land cover classification. The results reveal a clear thermal differentiation over the year, partly triggered by the change of synoptic weather situation but also by land cover effects. Thermal amplitudes are particularly low during the main rainy season when cloudiness and air humidity are high but markedly pronounced in the relative dry season when daily irradiance and outgoing nocturnal radiation causes distinct differences between the land cover units. Particularly the lower pasture areas gained by slash and burn of the natural forest exhibit the most extreme thermal conditions while the atmosphere inside the mountain forest is slightly cooler due to the regulating effects of the dense vegetation. Thus, clearing the forest clearly reduces the thermal regulation function (regulating ecosystem services) of the ecosystem which might become problematic under future global warming.

Abstract:

The near surface humidity in a megadiverse mountain ecosystem in southern Ecuador is examined on the basis of Relative Humidity (RH) measurements inside the natural mountain forest and at open sites along an altitudinal gradient from 1700 to 3200 m. The main methodological aim of the current study is to generate a humidity regionalization tool to provide spatial datasets on average monthly mean, minimum and maximum RH, Specific Humidity (q) and Specific Saturation Deficit (DS) by using observation data of RH. The maps based on data of the period 1999–2009 are needed by ecological projects working on various plots where no climate station data are available. The humidity maps are generated by combining a straightforward detrending technique with a Digital Elevation Model and a satellite-based land cover classification which also provides the relative forest cover per pixel. The topical aim of the study is to investigate the humidity distribution and structure of both manifestations of our ecosystem (pastures and natural vegetation) with special considerations to the ecosystem regulation service by converting natural forest into pasture. The results reveal a clear differentiation over the year, partly triggered by the change of synoptic weather situation but also by land cover effects. Humidity amplitudes are particularly low during the main rainy season when cloudiness and rainfall are high, but markedly pronounced in the relative dry season when daily irradiance and outgoing nocturnal radiation causes distinct differences between the land cover units. Particularly the upper pasture areas gained by slash and burn of the natural forest exhibit the lowest humidity values while the humidity inside the mountain forest is significantly higher due to the regulating effects of the dense vegetation. Thus, clearing the forest clearly reduces the regulation function (regulating ecosystem services) of the ecosystem which might become problematic for reforestation under future global warming.

Abstract:

The thermal structure of a megadiverse mountain ecosystem in southern Ecuador is examined on the basis of temperature measurements inside the natural mountain forest and at open-sites along an altitudinal gradient from 1600 to 3200 m. The main methodological aim of the current study is to develop an air temperature regionalization tool to provide spatial datasets on average monthly mean, minimum and maximum temperature by using observation data. The maps, based on data of the period 1999?2007, are needed by ecological projects working on various plots where no climate station data are available. The temperature maps are generated by combining a straightforward detrending technique with a Digital Elevation Model and a satellite-based land cover classification which also provides the relative forest cover per pixel. The topical aim of the study is to investigate the thermal structure of both manifestations of our ecosystem (pastures and natural vegetation) with special considerations to the ecosystem temperature regulation service by converting natural forest into pasture. The results reveal a clear thermal differentiation over the year, partly triggered by the change of synoptic weather situation but also by land cover effects. Thermal amplitudes are particularly low during the main rainy season when cloudiness and air humidity are high, but markedly pronounced in the relative dry season when daily irradiance and outgoing nocturnal radiation cause distinct differences between the land cover units. Particularly the lower pasture areas gained by slash and burn of the natural forest exhibit the most extreme thermal conditions while the atmosphere inside the mountain forest is slightly cooler due to the regulating effects of the dense vegetation. Thus, clearing the forest clearly reduces the thermal regulation function (regulating ecosystem services) of the ecosystem which might become problematic under future global warming.