Laboratory for
Climatology and Remote Sensing

Abstract:

Ecosystem water regulation couples energy and water balance, depends on the integrity of the ecosystem, and responds to changes in climate. Changes in tree-water relationships in the biodiversity hotspot of the tropical Andes in southern Ecuador might be potentially observed at the level of individual trees, thus providing an efficient ecosystem monitoring method with applications in forest management and conservation at the tree and landscape levels. In this study,we combine area-average measurements froma laser scintillometer above the forestwith optical satellite data at high spatial resolution to obtain area-wide evapotranspiration data. The processing of field data includes the calculation of energy storage in forest biomass and the partitioning of evapotranspiration into transpiration and evaporation. Satellite-based estimates are calibrated by using tower flux measurements and meteorological data within periods of humid and less-humid atmosphere. The annual evapotranspiration was 1316 mm, of which 1086 mm per year corresponds to the forest transpiration at the study site. Average values of 4.7 and 4.1 mm d?1 per tree crown are observed under humid and less-humid atmospheric conditions, respectively, when applying high-resolution area-wide evapotranspiration in individual crown analysis. Approximately 24% of the observed crowns show a positive monthly change in ET, and 51% of the crowns show a significant change in the daily ET, which can be considered sensitive individuals concerning water relationships. The limitations in the area-wide evapotranspiration at the crown level can be explained by considering the spectral responses of the crown individuals. The presented method can be robustly deployed in the ecological monitoring of mountain forests.

Abstract:

Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This paper presents the first comprehensive map of MCF distribution for the entire island. For its creation, a Random Forest model was trained with vegetation plots from the National Vegetation Database of Taiwan that were classified as “MCF” or “non-MCF”. This model predicted the distribution of MCF from a raster data set of parameters derived from a digital elevation model (DEM), Landsat channels and texture measures derived from them as well as ground fog frequency data derived from the Moderate Resolution Imaging Spectroradiometer. While the DEM parameters and Landsat data predicted much of the cloud forest’s location, local deviations in the altitudinal distribution of MCF linked to the monsoonal influence as well as the Massenerhebung effect (causing MCF in atypically low altitudes) were only captured once fog frequency data was included. Therefore, our study suggests that ground fog data are most useful for accurately mapping MCF.

Abstract:

The increase in atmospheric greenhouse gas concentrations from anthropogenic activities is the major driver of recent global climate change1. The stimulation of plant photosynthesis due to rising atmospheric carbon dioxide concentrations ([CO2]) is widely assumed to increase the net primary productivity (NPP) of C3 plants—the CO2 fertilization effect (CFE). However, the magnitude and persistence of the CFE under future climates, including more frequent weather extremes, are controversial. Here we use data from 16 years of temperate grassland grown under ‘free-air carbon dioxide enrichment’ conditions to show that the CFE on above-ground biomass is strongest under local average environmental conditions. The observed CFE was reduced or disappeared under wetter, drier and/or hotter conditions when the forcing variable exceeded its intermediate regime. This is in contrast to predictions of an increased CO2 fertilization effect under drier and warmer conditions. Such extreme weather conditions are projected to occur more intensely and frequently under future climate scenarios. Consequently, current biogeochemical models might overestimate the future NPP sink capacity of temperate C3 grasslands and hence underestimate future atmospheric [CO2] increase.

Abstract:

Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This thesis presents the first comprehensive map of MCF distribution for the entire island. For its creation, a Random Forest model was trained with vegetation plots from the National Vegetation Database of Taiwan that were classified as “MCF” or “non-MCF”. This model predicted the distribution of MCF from a raster data set of parameters derived from a digital elevation model (DEM), Landsat channels and texture measures derived from them as well as ground fog frequency data. The latter have been derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). For the detection of ground fog in MODIS imagery a new algorithm has been developed. It does not rely on cloud microphysical assumptions and was validated using camera data.

Abstract:

Due to the significant impact of fog and low stratus (FLS) on economy, ecology and traffic systems, there is a growing demand for high-resolution information on FLS occurrence. In this study, a baseline climatology of FLS h day?1 based on data recorded from 2006–2015 by the Spinning Enhanced Visible and Infrared Imager system (SEVIRI) aboard the Meteosat Second Generation satellites is computed for Europe to provide the requested information. It is the first 10 year, spatially explicit climatology for FLS based on data with a temporal resolution of 15 min. The dataset is validated against Meteorological Aviation Routine Weather Reports (METAR) and shows good accordance with an average Heidke Skill Score of 0.45. Temporal and spatial variations in FLS frequency as well as interannual trends are analyzed. Winter shows the highest FLS occurrence, but a general decrease over the investigated period. Spring, summer and autumn show less pronounced trends and lower average FLS frequencies. Possible reasons for these distributions are discussed.

Abstract:

The increase of atmospheric greenhouse gas concentrations resulting from anthropogenic activities is the major driver of global climate change. A net sink effect caused by stimulated plant photosynthesis through rising atmospheric carbon dioxide concentrations ([CO2]) and, consequently, an increased net primary productivity (NPP) of C3 plants (termed the CO2 fertilization effect, CFE) is widely assumed. However, knowledge about the magnitude and persistence of the CFE under future climates including more frequent weather extremes is still lacking. Therefore, we have investigated the CFE in dependence to its accompanying environmental conditions in the long-term time series (16 years) of a temperate grassland grown under “Free Air Carbon dioxide Enrichment” in Gießen, the GiFACE. Our results reveal that the CFE is strongest under local average environmental conditions and reduced or disappeared under wetter, drier and/or hotter conditions. This is in contrast to predictions of an increased CO2 fertilization under drier and warmer conditions. The results are of utmost importance because respective weather and climate conditions are projected in climate scenarios. Consequently, the state-of-art biogeochemical models might overestimate the future NPP sink capacity of temperate C3 grasslands. Since temperate grasslands represent an important portion of the Earth’s terrestrial surface, and therefore the global carbon cycle, atmospheric [CO2] might increase faster than currently expected.

Abstract:

Human activities during the last decades provoked a notable reduction in global forest cover. Knowing that forest stands act as stock and sinks for carbon and other greenhouse gases, it is important to determine the existing forest cover at country level and to calculate annual deforestation rates. This work uses NOAA satellite images in a resolution of 1 km x 1 km to classify the surface of continental Ecuador in “forest” – “non-forest” pixels and to estimate the annual deforestation rate from 1986 to 2001 as well as from 2001 to 2008. The method is based on a decision tree algorithm that includes different spectral bands of the NOAA-AVHRR sensor and additional topographic and meteorological parameters. The results show that the total forest cover of continental Ecuador was reduced from 48.1 % in 1986 to 36.8 % in 2008. The calculated annual deforestation rates indicate that forest reduction increased during the last decade. The most affected area is the Coastal Lowland, due to the enhanced population pressure, followed by the Amazon Basin, not only caused by the governmental supported oil and mining industry, but also due to the uncontrolled timber extraction. The Andean Highland has been less affected, because the major parts of this region were deforested before, during the Pre-Columbian-Era.

Abstract:

Sea salt (NaCl) has recently been proven to be of the utmost importance for ecosystem functioning in Amazon lowland forests because of its impact on herbivory, litter decomposition and, thus, carbon cycling. Sea salt deposition should generally decline as distance from its marine source increases. For the Amazon, a negative east–west gradient of sea salt availability is assumed as a consequence of the barrier effect of the Andes Mountains for Pacific air masses. However, this generalized pattern may not hold for the tropical mountain rainforest in the Andes of southern Ecuador. To analyse sea salt availability, we investigated the deposition of sodium (Na+) and chloride (Cl?), which are good proxies of sea spray aerosol. Because of the complexity of the terrain and related cloud and rain formation processes, sea salt deposition was analysed from both, rain and occult precipitation (OP) along an altitudinal gradient over a period between 2004 and 2009. To assess the influence of easterly and westerly air masses on the deposition of sodium and chloride over southern Ecuador, sea salt aerosol concentration data from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis data set and back-trajectory statistical methods were combined. Our results, based on deposition time series, show a clear difference in the temporal variation of sodium and chloride concentration and Na+???Cl? ratio in relation to height and exposure to winds. At higher elevations, sodium and chloride present a higher seasonality and the Na+???Cl? ratio is closer to that of sea salt. Medium- to long-range sea salt transport exhibited a similar seasonality, which shows the link between our measurements at high elevations and the sea salt synoptic transport. Although the influence of the easterlies was predominant regarding the atmospheric circulation, the statistical analysis of trajectories and hybrid receptor models revealed a stronger impact of the north equatorial Atlantic, Caribbean, and Pacific sea salt sources on the atmospheric sea salt concentration in southern Ecuador. The highest concentration in rain and cloud water was found between September and February when air masses originated from the north equatorial Atlantic, the Caribbean Sea and the equatorial Pacific. Together, these sources accounted for around 82.4?% of the sea salt budget over southern Ecuador.

Abstract:

Hyperspectral imaging (HSI) is increasingly gaining acceptance in the medical field. Up until now, HSI has been used in conjunction with rigid endoscopy to detect cancer in vivo. The logical next step is to pair HSI with flexible endoscopy, since it improves access to hard-to-reach areas. While the flexible endoscope’s fiber optic cables provide the advantage of flexibility, they also introduce an interfering honeycomb-like pattern onto images. Due to the substantial impact this pattern has on locating cancerous tissue, it must be removed before the HS data can be further processed. Thereby, the loss of information is to minimize avoiding the suppression of small-area variations of pixel values. We have developed a system that uses flexible endoscopy to record HS cubes of the larynx and designed a special filtering technique to remove the honeycomb-like pattern with minimal loss of information. We have confirmed its feasibility by comparing it to conventional filtering techniques using an objective metric and by applying unsupervised and supervised classifications to raw and pre-processed HS cubes. Compared to conventional techniques, our method successfully removes the honeycomb-like pattern and considerably improves classification performance, while preserving image details.

Abstract:

High landscape diversity is assumed to increase the number and level of ecosystem services. However, the interactions between ecosystem service provision, disturbance and landscape composition are poorly understood. Here we present a novel approach to include uncertainty in the optimization of land allocation for improving the provision of multiple ecosystem services. We refer to the rehabilitation of abandoned agricultural lands in Ecuador including two types of both afforestation and pasture rehabilitation, together with a succession option. Our results show that high compositional landscape diversity supports multiple ecosystem services (multifunction effect). This implicitly provides a buffer against uncertainty. Our work shows that active integration of uncertainty is only important when optimizing single or highly correlated ecosystem services and that the multifunction effect on landscape diversity is stronger than the uncertainty effect. This is an important insight to support a land-use planning based on ecosystem services.

Abstract:

The increase in atmospheric greenhouse gas concentrations from anthropogenic activities is the major driver of global climate change. The rising atmospheric carbon dioxide (CO2 ) concentrations may stimulate plant photosynthesis and, thus, cause a net sink effect in the global carbon cycle. As a consequence of an enhanced photosynthesis, an increase in the net primary productivity (NPP) of C3 plants (termed CO2 fertilization) is widely assumed. This process is associated with a reduced stomatal conductance of leaves as the carbon demand of photosynthesis is met earlier. This causes a higher water-use efficiency and, hence, may reduce water stress in plants exposed to elevated CO2 concentrations ([eCO2 ]). However, the magnitude and persistence of the CO2 fertilization effect under a future climate including more frequent weather extremes are controversial. To test the CO2 fertilization effect for Central European grasslands, a data set comprising 16 years of biomass samples and environmental variables such as local weather and soil conditions was analysed by means of a novel approach. The data set was recorded on a “Free Air Carbon dioxide Enrichment” (FACE) experimental site which allows to quantify the CO2 fertilization effect under naturally occurring climate variations. The results indicate that the CO2 fertilization effect on the aboveground biomass is strongest under local average environmental conditions. Such intermediate regimes were defined by the mean +/- 1 standard deviation of the long-term average in the respective variable three months before harvest. The observed CO2 fertilization effect was reduced or vanished under drier, wetter and hotter conditions when the respective variable exceeded the bounds of the intermediate regimes. Comparable conditions, characterized by a higher frequency of more extreme weather conditions, are predicted for the future by climate projections. Consequently, biogeochemical models may overestimate the future NPP sink capacity of temperate C3 grasslands. Because temperate grasslands represent an important part of the Earth’s terrestrial surface and therefore the global carbon cycle, atmospheric CO2 concentrations [CO2 ] might increase faster than currently expected.

Abstract:

Technical development during the last two decades has brought new potential and new applications for mobile measurements. In this paper, we present six case studies where mobile measurement devices were used to acquire data for meteorological and climatological research. Three case studies deal with groundbased mobile measurements – on buses for urban climate measurements and on a vessel on a lake – and three with airborne platforms – on a cable car and on an unmanned aerial vehicle for vertical soundings and on a tethered balloon sonde for cloud physics. For each study, we describe the measurement set-up and address the potential and drawbacks of these applications. At the end, we discuss general aspects related to mobile observations especially concerning the time and space dimension of measurements.

Abstract:

The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ? 40, classification errors significantly increase.

Abstract:

The relationship between canopy-level evapotranspiration (ETSci) and leaf-level transpiration (Tleaf) as well as photosynthesis (Pleaf) for a homogeneous tropical montane pasture was analyzed over five days using a combination of methods involving a laser scintillometer and a porometer. Weather conditions ranged from overcast to sunny during the period of study. The gas exchange of the leaves of the dominant pasture grass Setaria sphacelata (transpiration vs. photosynthetic CO2 net uptake ) was measured with a porometer and physiologically interpreted on the background of microclimate variables (photosynthetic active radiation (PAR) as proxy for total light intensity, temperature, water vapor deficit of the air) and soil moisture data. Water use efficiency (WUE, photosynthetic CO2 net uptake vs water loss by leaf transpiration) of the pasture was used to analyze the grass’ range of response to the environmental variables of the research area. PAR and water vapor deficit of the air (VPD) appeared to be the determinant factors for Tleaf and ETSci. WUE for the Setaria sphacelata pasture ranged from 1.9 to 5.8 µmol CO2 mmol-1 H20 day-1 and is particularly low during periods of high VPD combined with enhanced insolation during cloudless periods. ET measurements collected by the scintillometer demonstrated a strong correlation with water flux calculated using the Penman-Monteith approach (TPM) (r² = 0.95). Also, Tleaf measured with the porometer showed reasonable coincidence with the ET observations (r² = 0.78). Values of ETSci ranged from 2.26 to 4.96 mm day-1 and Tleaf ranged from 0.83 to 2.41 mm day-1, but only ETSci showed good correspondence with the available energy (net radiation). The lower correlation between Tleaf and canopy-level ETSci compared to that between ETSci and TPM was tested against contaminations from the adjacent fetch area of the scintillometer path, but no effects were found. Likewise, soil water limitations of Tleaf could be ruled out. Therefore, different correlations of ETSci and Tleaf with the incoming energy and VPD may be traced back to a direct effect of the VPD on ET in contrast to its indirect effect on Tleaf which is additionally regulated by physiological processes in the leaf stomata.

Abstract:

Ecosystems worldwide are threatened by the increasing impact of land use and climate change. To protect their diversity and functionality, spatially explicit monitoring systems are needed. In remote areas, monitoring is difficult and recurrent field surveys are costly. By using Lidar or the more cost-effective and repetitive optical satellite data, remote sensing could provide proxies for habitat structure supporting measures for the conservation of biodiversity. Here we compared the explanatory power of both, airborne Lidar and optical satellite data in modeling the spatial distribution of biodiversity of birds across a complex tropical mountain forest ecosystem in southeastern Ecuador. Weused data fromfield surveys of birds and chose three measures as proxies for different aspects of diversity: (i) Shannon diversity as a measure of ?-diversity that also includes the relative abundance of species, (ii) phylodiversity as a first proxy for functional diversity, and (iii) community composition as a proxy for combined ?- and ?-diversity.We modeled these diversity estimates using partial least-square regression of Lidar and optical texturemetrics separately and compared themodels using a leave-one-out validated R2 and root mean square error. Bird community information was best predicted by both remote sensing datasets, followed by Shannon diversity and phylodiversity. Our findings reveal a high potential of optical texture metrics for predicting Shannon diversity and a measure of community composition, but not for modeling phylodiversity. Generalizing from the investigated tropical mountain ecosystem,we conclude that texture information retrieved from multispectral data of operational satellite systems could replace costly airborne laser-scanning for modeling certain aspects of biodiversity.

Abstract:

Understanding of evapotranspiration (ET) processes over Andean mountain environments is crucial, particularly due to the importance of these regions to deliver water-related ecosystem services. In this context, the detection of spatio-temporal changes in ET remains poorly investigated for specific Andean ecosystems, like the páramo. To overcome this lack of knowledge, we implemented the energy-balance model METRIC with Landsat 7 ETM+ and MODIS-Terra imagery for a páramo catchment. The implementation contemplated adjustments for complex terrain in order to obtain daily, monthly and annual ET maps (between 2013 and 2014). In addition, we compared our results to the global ET product MOD16. Finally, a rigorous validation of the outputs was conducted with residual ET from the water balance. ET retrievals from METRIC (Landsat-based) showed good agreement with the validation-related ET at monthly and annual steps (mean bias error <8 mm·month?1 and annual deviation <17%). However, METRIC (MODIS-based) outputs and the MOD16 product were revealed to be unsuitable for our study due to the low spatial resolution. At last, the plausibility of METRIC to obtain spatial ET retrievals using higher resolution satellite data is demonstrated, which constitutes the first contribution to the understanding of spatially-explicit ET over an alpine catchment in the neo-tropical Andes.

Abstract:

Phylogenetic niche conservatism (PNC) is the tendency of species within a clade to retain ancestral traits and to persist in their primary ecological niches on geological time scales. It links evolutionary and ecological processes and has been hypothesized to explain patterns of species richness and the composition of species assemblages. Decreasing patterns of species richness along latitudinal gradients were often explained by the combination of ancient tropical climates, trait retention of tropical lineages and environmental filtering. PNC also predicts decreasing phylodiversity and family age with decreasing tropicality and has been invoked to explain these patterns along climatic gradients across latitudinal as well as elevational gradients. However, recent studies on tree assemblages along latitudinal and elevational gradients in South America found patterns contradicting the PNC framework. Our study aims to shed light on these contradictions using three different metrics of the phylogenetic composition that form a gradient from recent evolutionary history to deep phylogenetic relationships. We analyzed the relationships between elevation and taxonomic species richness, phylodiversity and family age of tree assemblages in Andean rainforests in Ecuador. In contrast to predictions of the PNC we found no associations of elevation with species richness of trees and increasing clade level phylodiversity and family age of the tree assemblages with elevation. Interestingly, we found that patterns of phylodiversity across the studied elevation gradient depended especially on the deep nodes in the phylogeny. We therefore suggest that the dispersal of evolutionarily old plant lineages with extra-tropical origins influences the recent composition of tree assemblages in the Andes. Further studies spanning broader ecological gradients and using better resolved phylogenies to estimate family and species ages are needed to obtain a deeper mechanistic understanding of the processes that drive the assembly of tree communities along elevational gradients.