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

Abstract:

Ratios of stable oxygen isotopes in tree rings (δ18O) are a valuable proxy for reconstructing past climates. Such reconstructions allow us to gain better knowledge of climate dynamics under different (eg warmer) environmental conditions, which also forms the basis for effective risk management. The latter aspect is particularly relevant for our study site on the western flanks of the Andes in Southern Ecuador, since the region is frequently affected by droughts and heavy precipitation events during the rainy season (January to April), leading to enormous social and economic losses. In particular, we focus on precipitation amounts and moisture source regions as they are known to influence the δ18O signature of tree rings. Moisture source regions are based on 240 h backward trajectories that were calculated with the trajectory model LAGRANTO for the rainy seasons 2008 to 2017. A moisture source diagnostic was applied to the air parcel pathways. The resulting moisture source regions were analyzed by calculating composites based on precipitation amounts, season, and calendar year. The precipitation amounts were derived from data of a local Automatic Weather Station (AWS). The analysis confirms that our study site receives its moisture both, from the Atlantic and the Pacific Oceans. Heavy precipitation events are linked to higher moisture contributions from the Pacific, and local SST anomalies along the coast of Ecuador are of higher importance than those off the coast toward the central Pacific. Moreover, we identified increasing moisture contributions from the Pacific over the course of the rainy season. This change and also rain amount effects are detectable in preliminary data of δ18O variations in tree rings of Bursera graveolens. These signatures can be a starting point for investigating atmospheric and hydroclimatic processes, which trigger δ18O variations in tree rings, more extensively in future studies.

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:

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 efficiency (WUE, ratio of photosynthetic CO2 uptake per water loss by transpiration) as ecophysiological 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 efficiency. 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 confirmed an undiminished growth of V. tomentosa 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:

Tropical forests and the trees as their principal components have been investigated in detail. However, due to its complexity, their interactions, adaptations and response to climate variations require much more research. In this study, dendrochronological techniques were applied to evaluate the potential of tree-rings from tropical tree species as climate records. Two ecosystems with very distinct climate scenarios were selected from a dry and humid forest in southern Ecuador. A comparative analysis between these two forest types was performed by applying three dendrochronological methods. First, Tree Ring Width (TRW) measurements from tree species with distinct ring boundaries were dated to develop ring-width chronologies. Second, stable carbon isotopes (?13C) were measured from whole-wood and alpha-cellulose of dated annual tree-rings. Finally, concentrations of more than 23 chemical elements were determined from individual dated tree-rings after dissolving the wooden material in HNO3. The results showed the high potential of tropical tree species as climate archives, Bursera graveolens and Maclura tinctoria for the dry forest and Cedrela montana for the humid forest. Radial growth variations in tree species from the dry forest revealed a strong and reliable precipitation signal. Then, for these tropical regions, the first ring-width based wet-season precipitation reconstruction over the past century was developed, and spatial correlations unraveled a strong connection to the climatic conditions of the central Pacific precipitation and temperature variability. Interseries correlations of the TRW from the trees of the humid forest revealed a weak common signal. Stable carbon isotopes evidenced higher climate sensitivity than TRW measurements in the humid forest. However, to infer a reliable climate reconstruction from stable carbon isotopes, more ?13C time series were needed. ?13C values from whole-wood and alpha-cellulose reflected local and regional signals of precipitation and humidity. Meanwhile, nutrient concentration in the wood was higher in the dry forest, but common patterns and trends of nutrients were more distinct in the humid forest. For both study sites, two groups of nutrients with opposite radial distribution were identified (Group 1: Ca, Sr, Ba, Ga; and Group 2: K, P, Rb). In conclusion, TRW of tree species from the dry forest have a high paleoclimate potential, especially to reconstruct precipitation amounts in arid zones of southern Ecuador. Stable carbon isotopes constitute a promising tool to perform climatic reconstructions in both ecosystems. Finally, the valuable historical information of nutrient concentration evidenced in tree-rings opens promising ways to study tree growth dynamics especially in the humid forest.

Abstract:

The South Ecuadorian Andes are one of the hottest global hotspots of biodiversity and currently threatened by land use and climate change. Forest structure and composition are crucial factors for understanding the capacity of forest support species in changing environments. In order to prioritize limited conservation resources a better understanding of tree diversity patterns is needed. The use of image texture measures, as a proxy for spatial and forest structure has shown useful possibilities in explaining patterns of tree diversity and species richness. My goal was to evaluate the performance of different texture measures on NDVI, EVI and two broad-band combinations on high resolution (0.3m) aerial photography to predict tree diversity. Bayesian Model Averaging (BMA) was used to relate in situ measurements of tree diversity to measures of image texture. Texture explained up to 44.7% of the variability of tree diversity with measures related to habitat heterogeneity, particularly variance, providing highest explanatory power. Image texture measures bear considerable potential for predicting tree diversity in the tropics and can contribute to improvements on conservation efforts and management planning.