Laboratory for
Climatology and Remote Sensing

Abstract:

Land-use and climate change are major threats to biodiversity and ecosystem functions. Most of the current biodiversity monitoring systems are based on periodic records of the populations of a set of threatened or popular ‘?agship’ indicator species. In contrast to the abundance-based monitoring of species, also speci?c indicators of processes and functional interactions in an ecosystem may become targets of a more functional monitoring which can unveil early responses of an ecosystem to environmental changes at different spatial and temporal scales. The contributions of this Special Issue present such functional indicators for assessing and predicting responses to environmental changes of ecosystem functions in a hotspot of tropical biodiversity.

Abstract:

The effects of an increasing moisture on trees of the tropical species-rich mountain rain forest in the South Ecuadorian Andes was investigated, using the daily total water consumption (TWC) and the instantaneous water use ef?ciency (WUE, ratio of photosynthetic CO2 uptake per water loss by transpiration) as eco- physiological indicators. Two canopy and one sub-canopy tree species, (Vismia tomentosa, Clusiaceae, an as of yet unknown Lauracee, and Spirotheca rosea, Bombacaceae) were the experimental objects. Seasonal changes as well as a long-term (18 months) trend of increasing precipitation caused an inverse reaction of the TWC of the trees. Because of a rather unlimited water supply to the trees from a permanently high water content of the soil, transpiration followed mainly the atmospheric demand of water vapor, and increasing moisture hence reduced water loss by transpiration. It was hypothesized that in spite of the reduction in transpiratory water loss photosynthetic carbon acquisition would be not or less affected due to an increase in water use ef?ciency. Concomitant measurements of photosynthetic net CO2 uptake showed the expected increase of WUE in V. tomentosa and S. rosea, but no clear reaction of the Lauracee. Accompanying measurements of stem extension growth con?rmed an undiminished growth of V. tomen- tosa and S. rosea but showed also suspended growth of the Lauracee during the wettest months. While TWC can be continuously monitored with the heat dissipation technique, WUE is determined by leaf porometry in campaigns for which access to the canopy is required. Simultaneous recordings of the gas exchange of leaves at 4 different positions in the crown of one of the experimental trees (V. tomentosa) showed the usability of the trait WUE in combination with the total daily water consumption as indicator set for assessing the response of trees to a subtly changing climate. However, not all tree species appear as likewise useful indicator trees

Abstract:

Grünländer der gemäßigten Breiten liefern wichtige Ökosystemdienstleistungen die von der Biomasseproduktion abhängen. Letztere nimmt mit geringeren Niederschlägen und höheren Niederschlagsvariabilitäten ab, während höhere Lufttemperaturen fördernd wirken können. Zusätzlich sollen höhere atmosphärische CO2-Konzentrationen ([CO2]s) die Biomasse durch direkte Stimulation der Photosynthese und Wassereinsparung (CO2-Düngeeffekt) erhöhen. Somit ist die Biomasseproduktivität durch teils gegenläufige Auswirkungen wechselnder klimatischer Bedingungen und [CO2] gesteuert. Die Studie untersucht diese Einflüsse des globalen Wandels auf Grundlage eines Freiluftexperiments zur CO2-Anreicherung (~20% über Umgebungs-[CO2]; 18 J.) um die oberirdische Sommer-Biomasse (AGB) Mitte des 21. Jhdt. statistisch vorherzusagen. Ein informationstheoretisches Screening lieferte die wichtigsten Prädiktoren, basierend auf Lufttemperatur- und Niederschlagsmessungen. Die AGB-Produktion wurde für verschiedene Klimaregime, abgeleitet aus den Beobachtungen des Versuchszeitraums, geschätzt. Wir fanden, dass die zukünftige AGB-Produktion hauptsächlich von der Niederschlagsmenge abhängt, gefolgt von Lufttemperatur und Niederschlagsvariabilität. Variablere Niederschläge reduzierten die AGB und umgekehrt. Die AGB-Produktion unter trockenen Bedingungen verringerte sich mit steigenden Lufttemperaturen weiter. Im Kontrast zu weithin erwarteter Ertragssteigerungen durch erhöhte [CO2]s, führen solche Bedingungen zu AGB-Vorhersagen unter denen der aktuellen AGBs. Da Klimamodelle für Sommer in Mitteleuropa steigende Lufttemperaturen und abnehmende Niederschlagsmengen mit zunehmender Variabilität projizieren, deuten unsere Ergebnisse trotz steigender [CO2]s auf eine reduzierte zukünftige Grünland-Sommer-AGB hin.

Abstract:

This study investigates the temporal dynamics of the drop size distribution (DSD) and its influence on the relationship between the liquid water content (LWC) and the radar reflectivity (Z) in fogs. Data measured during three radiation fog events at the Marburg Ground Truth and Profiling Station in Linden-Leihgestern, Germany, form the basis of this analysis. Specifically, we investigated the following questions: (1) Do the different fog life cycle stages exhibit significantly different DSDs? (2) Is it possible to identify characteristic DSDs for each life cycle stage? (3) Is it possible to derive reliable Z-LWCrelationships by means of a characteristic DSD? The results showed that there were stage-dependent differences in the fog life cycles, although each fog event was marked by unique characteristics, and a general conclusion about the DSD during the different stages could not be made. A large degree of variation within each stage also precludes the establishment of a representative average spectrum.

Abstract:

This paper focuses on the analysis of precipita- tion patterns, using a Local Area Weather Radar to collect information about the precipitation distribution in an Andean region of southern Ecuador (cities of Loja, Zamora and Catamayo). 54 representative events were selected to develop daily precipitation maps and to obtain their rele- vant characteristics, which were related to the topography and the season. The results showed that a strong correlation between the areas covered by precipitation (RA coef?cient) and the season exists. In general, humid air masses come from the east (Amazon Basin), but during the main rainy season (December to April), humidity also frequently enters the study region from the west (Paci?c Ocean). The rainy season is characterized by convective precipitation, associated with higher evaporation rates during austral summer. The relatively dry season is formed between May and November, but considerable precipitation amounts are registered, too, due to advective moisture transport from the Amazon Basin, a result of the predominant tropical easterlies carrying the humidity up the eastern escarpment of the Andes, generally following the natural course of the drainage systems.

Abstract:

Texture information from passive remote sensing images provides surrogates for habitat structure, which is relevant for modeling biodiversity across space and time and for developing effective ecological indicators. However, the applicability of this information might differ among taxa and diversity measures. We compared the ability of indicators developed from texture analysis of remotely sensed images to predict species richness and species turnover of six taxa (trees, pyraloid moths, geometrid moths, arctiinae moths, ants, and birds) in a megadiverse Andean mountain rainforest ecosystem. Partial least-squares regression models were fitted using 12 predictors that characterize the habitat and included three topographical metrics derived from a high-resolution digital elevation model and nine texture metrics derived from very high-resolution multi-spectral orthophotos. We calculated image textures derived from mean, correlation, and entropy statistics within a relatively broad moving window (102 m × 102 m) of the near infra-red band and two vegetation indices. The model performances of species richness were taxon dependent, with the lowest predictive power for arctiinae moths (4%) and the highest for ants (78%). Topographical metrics sufficiently modeled species richness of pyraloid moths and ants, while models for species richness of trees, geometrid moths, and birds benefited from texture metrics. When more complexity was added to the model such as additional texture statistics calculated from a smaller moving window (18 m × 18 m), the predictive power for trees and birds increased significantly from 12% to 22% and 13% to 27%, respectively. Gradients of species turnover, assessed by non-metric two-dimensional scaling (NMDS) of Bray-Curtis dissimilarities, allowed the construction of models with far higher predictability than species richness across all taxonomic groups, with predictability for the first response variable of species turnover ranging from 64% (birds) to 98% (trees) of the explained change in species composition, and predictability for the second response variable of species turnover ranging from 33% (trees) to 74% (pyraloid moths). The two NMDS axes effectively separated compositional change along the elevational gradient, explained by a combination of elevation and texture metrics, from more subtle, local changes in habitat structure surrogated by varying combinations of texture metrics. The application of indicators arising from texture analysis of remote sensing images differed among taxa and diversity measures. However, these habitat indicators improved predictions of species diversity measures of most taxa, and therefore, we highly recommend their use in biodiversity research.

Abstract:

Though the relevance of pasture degradation on the Qinghai-Tibet Plateau (QTP) is widely postulated, its extent is still unknown. Due to the enormous spatial extent, remote sensing provides the only possibility to investigate pasture degradation via frequently used proxies such as vegetation cover and aboveground biomass (AGB). However, unified remote sensing approaches are still lacking. This study tests the appli- cability of hyper- and multispectral in situ measurements to map vegetation cover and AGB on regional scales. Using machine learning techniques, it is tested whether the full hyperspectral information is needed or if multispectral information is sufficient to accurately estimate pasture degradation prox- ies. To regionalize pasture degradation proxies, the transferability of the locally derived ML-models to high resolution multispectral satellite data is assessed. 1183 hyperspectral measurements and vegeta- tion records were performed at 18 locations on the QTP. Random Forests models with recursive feature selection were trained to estimate vegetation cover and AGB using narrow-band indices (NBI) as predic- tors. Separate models were calculated using NBI from hyperspectral data as well as from the same data resampled to WorldView-2, QuickBird and RapidEye channels. The hyperspectral results were compared to the multispectral results. Finally, the models were applied to satellite data to map vegetation cover and AGB on a regional scale. Vegetation cover was accurately predicted by Random Forest if hyperspectral measurements were used (cross validated R2 = 0.89). In contrast, errors in AGB estimations were consid- erably higher (cross validated R2 = 0.32). Only small differences in accuracy were observed between the models based on hyperspectral compared to multispectral data. The application of the models to satellite images generally resulted in an increase of the estimation error. Though this reflects the challenge of applying in situ measurements to satellite data, the results still show a high potential to map pasture degradation proxies on the QTP. Thus, this study presents robust methodology to remotely detect and monitor pasture degradation at high spatial resolutions.

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.