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

Abstract:

The co-evolutionary arms race between herbivores and plants forces plants to evolve protection strategies that reduce the palatability of the plant modules attacked by the herbivores. These characteristics of traits have consequences for both the survival of plant individuals and the composition of plant communities. Thus, correlating traits of for instance leaves with herbivory is an important step toward understanding the dynamics of plant populations and communities. Traits can either be measured using conventional lab methods or recently developed spectral sensing techniques. We examined whether leaf traits of trees are related to herbivory in a multispecies approach. Furthermore, we explored whether leaf traits characterized by spectral sensing provide similar relations to herbivory as lab-based leaf traits. We established nine 1-ha square plots evenly distributed over three different forest types in Ecuadorian tropical montane rainforests where we estimated herbivory as the leaf area loss (in square centimeters) of 20 (±5) leaves sampled from the canopies of 380 tree individuals belonging to 51 tree species (7 ± 1 individuals/species) using lab- and spectral-sensing-based methods. For each methodological approach, we ran 100 linear mixed-effects models with all respective leaf traits as predictor and herbivory as response variables for data subsets containing one randomly selected tree individual of each species to estimate the range of the regression coefficients for each trait. Automated stepwise backward selections determined the frequency of each trait having an important influence on herbivory. We found no clear relations between leaf traits and herbivory for neither lab- nor spectral-sensing-based traits. A nested variance component analysis demonstrated that the observed variability was mainly due to the variation in trait concentrations between tree individuals of a species. Our results suggest that snapshot data lead to a mismatch between herbivory and the concentrations of traits during the peak of herbivory. Another explanation could be that environmental conditions or processes along the food web are more important in structuring herbivory than leaf traits.

Abstract:

High spatio-temporal variability is a characteristic of extreme rainfall. In mountainous regions like the Tropical Andes, where intricate orography and mesoscale atmospheric dynamics greatly impact rainfall systems, this particularly holds for mountain areas like the Tropical Andes. Thus, the absence of operational rainfall monitoring networks with high spatio-temporal resolution has imposed difficulties for a proper analysis of extreme rainfall events in the Ecuadorian Andes. Nowhere, we present our improved knowledge on rainfall extremes based on newly available rainfall radar data of this region. In our study we employ a clustering approach to identify types of extreme rainfall events and analyze their spatio-temporal characteristics. Based on 3 years of data obtained from an X-band scanning weather radar data, the study was conducted in the southern Ecuadorian Tropical Andes at 4450 m a.s.l. By applying a rainfall threshold, 67 extreme rainfall events were selected. The rainfall characteristics of each extreme rainfall event, such as the amount of rain, its duration, its hour, and month of occurrence were determined and used as input variables of a k-means clustering analysis to group the events into different classes. The result revealed three main classes of extreme rainfall events. The first class is characterized by highest rain intensity and lowest duration. The second class is characterized by its month of occurrence, during the first 5 months of the year. The third class showed lowest rain intensity and highest duration mainly occurred at higher elevations. The typology of events advances our understanding of the spatio-temporal characteristics of extreme rainfall in the Tropical Andes.

Abstract:

In tropical forests, herbivorous arthropods remove between 7% up to 48% of leaf area, which has forced plants to evolve defense strategies. These strategies influence the palat- ability of leaves. Palatability, which reflects a syndrome of leaf traits, in turn influences both the abundance and the mean body mass not only of particular arthropod taxa but also of the total communities. In this study, we tested two hypotheses: (H1) The abundance of two important chewer guilds (‘leaf chewers’ and ‘rostrum chewers’), dominant components of arthropod communities, is positively related to the palatability of host trees. (H2) Lower pal- atability leads to an increased mean body mass of chewers (Jarman-Bell principle). Arthro- pods were collected by fogging the canopies of 90 tropical trees representing 31 species in three plots at 1000 m and three at 2000 m a.s.l. Palatability was assessed by measuring several ‘leaf traits’ of each host tree and by conducting a feeding trial with the generalist her- bivore Gryllus assimilis (Orthoptera, Gryllidae). Leaf traits provided partial support for H1, as abundance of leaf chewers but not of rostrum chewers was positively affected by the experi- mentally estimated palatability. There was no support for H2 as neither leaf traits nor experi- mentally estimated palatability affected the mean body mass of leaf chewers. The mean body mass of rostrum chewers was positively related to palatability. Thus, leaf traits and experimentally estimated palatability influenced the abundance and mean body mass of chewing arthropods on the community level. However, the data were not consistent with the Jarman-Bell principle. Overall, our results suggest that the palatability of leaves is not among the dominant factors influencing abundance and mean body mass of the community of chewing arthropod herbivores. If other factors, such as the microclimate, predation or fur- ther (a-)biotic interactions are more important has to be analyzed in refined studies.

Abstract:

This study addresses transpiration in a tropical evergreen mountain forest in the Ecuadorian Andes from the leaf to the stand level, with emphasis on nocturnal plant-water relations. The stand level: Evapotranspiration (ET) measured over 12 months with the Eddy-Covariance (ECov) technique proved as the major share (79%) of water received from precipitation. Irre- spective of the humid climate, the vegetation transpired day and night. On average, 15.3% of the total daily ET were due to nocturnal transpiration. Short spells of drought increased daily ET, mainly by enhanced nighttime transpiration. Following leaf transpiration rather than air temperature and atmospheric water vapor deficit, ET showed its maximum already in the morning hours. The tree level: Due to the humid climate, the total water consumption of trees was generally low. Nevertheless, xylem sap flux measurements separated the investigated tree species into a group showing relatively high and another one with low sap flux rates. The leaf level: Transpiration rates of Tapirira guianensis, a member of the high- flux-rate group, were more than twice those of Ocotea aciphylla, a representative of the group showing low sap flux rates. Representatives of the Tapirira group operated at a rela- tively high leaf water potential but with a considerable diurnal amplitude, while the leaves of the Ocotea group showed low water potential and small diurnal fluctuations. Overall, the Tapirira group performed anisohydrically and the Ocotea group isohydrically. Grouping of the tree species by their water relations complied with the extents of the diurnal stem circum- ference fluctuations. Nighttime transpiration and hydrological type: In contrast to the isohy- drically performing trees of the Ocotea group, the anisohydric trees showed considerable water vapour pressure deficit (VPD)-dependent nocturnal transpiration. Therefore, we con- clude that nighttime ET at the forest level is mainly sourced by the tree species with aniso- hydric performance.

Abstract:

Biodiversity and ecosystem functions are highly threatened by global change. It has been proposed that geodiversity can be used as an easy-to-measure surrogate of biodiversity to guide conservation management. However, so far, there is mixed evidence to what extent geodiversity can predict biodiversity and ecosystem functions at the regional scale relevant for conservation planning. Here, we analyse how geodiversity computed as a compound index is suited to predict the diversity of four taxa and associated ecosystem functions in a tropical mountain hotspot of biodiversity and compare the results with the predictive power of environmental conditions and resources (climate, habitat, soil). We show that combinations of these environmental variables better explain species diversity and ecosystem functions than a geodiversity index and identified climate variables as more important predictors than habitat and soil variables, although the best predictors differ between taxa and functions. We conclude that a compound geodiversity index cannot be used as a single surrogate predictor for species diversity and ecosystem functions in tropical mountain rain forest ecosystems and is thus little suited to facilitate conservation management at the regional scale. Instead, both the selection and the combination of environmental variables are essential to guide conservation efforts to safeguard biodiversity and ecosystem functions.

Abstract:

In the past two decades, the Amazon-exposed, tropical montane rain forests in south Ecuador experienced increasing deposition of reactive N mainly from Amazonian forest fires, episodic Ca and Mg inputs from Saharan dust, and a low but constant P deposition from unknown sources. To explore the response of this tropical, perhumid ecosystem to nutrient inputs, we established in 2007 a Nutrient Manipulation Experiment (NUMEX). Since 2008, we have applied 50 kg ha−1 year−1 of N as urea, 10 kg ha−1 year−1 of P as NaH2PO4·H2O, 50 kg ha−1 year−1 of N + 10 kg ha−1 year−1 of P and 10 kg ha−1 year−1 of Ca as CaCl2·H2O in a randomized block design at 2000 m a.s.l. in a natural forest of the south Ecuadorian Andes. Previous studies have shown that alkali and alkaline earth metals had beneficial effects on the functioning of N and P co-limited tropical forests occurring on acidic soils. Therefore, we determined the response of all major aqueous ecosystem fluxes of K, Ca, Mg and Na to nutrient amendments, to understand how increasing atmospheric deposition would affect their cycling in the future. Additions of N and P decreased K leaching from the organic layer and in the mineral soil, thus tightening K cycling. This suggests that increasing future N and P availability may result in K limitation in the long term. The leaching of Ca and Mg from the canopy increased in response to amendments of N and P and we observed an enhanced uptake of these nutrients also if Ca was amended alone. Although N was applied as urea, acidity of soil solutions and leaching of K, Ca, Mg and Na did not increase following separate N amendments. In spite of the acid soils and of its low cation-exchange competitivity, Na included in the P fertilizer was only partly leached from the organic layer. We suggest that it was probably required to cover an unmet Na demand of the soil fauna. Our results demonstrate the major role in the functioning of the tropical montane forests played by K, Ca and Mg as potential future growth-limiting elements and increasingly required nutrients in response to rising N and P availability, while they also support the importance of Na as a functional element in these ecosystems.

Abstract:

Morphological traits provide the interface between species and their environment. For example, body size affects the fitness of individuals in various ways. Yet especially for ectotherms, the applicability of general rules of interspecific clines of body size and even more so of other morphological traits is still under debate. Here we tested relationships between elevation (as a proxy for temperature) and productivity with four ecologically relevant morphological traits of orthopteran assemblages that are related to fecundity (body size), dispersal (wing length), jumping ability (hind femur length), and predator detection (eye size). We measured traits of 160 orthopteran species that were sampled along an extensive environmental gradient at Mt. Kilimanjaro (Tanzania), spanning elevations from 790 to 4,410 m above sea level (a.s.l.) with different levels of plant productivity. For traits other than body size, we calculated the residuals from a regression on body length to estimate the variation of traits irrespective of body size. Bayesian analyses revealed that mean body size of assemblages, as well as the means of relative wing length, hind femur length, and eye size, decreased with increasing elevation. Body size and relative eye size also decreased with increasing productivity. Both phylogenetic relationships, as well as species‐specific adaptations, contributed to these patterns. Our results suggest that orthopteran assemblages had higher fecundity and better dispersal and escape abilities, as well as better predator detection at higher temperatures (low elevations) than at low temperatures (high elevations). Large body sizes might be advantageous in habitats with low productivity because of a reduced risk of starvation. Likewise, large eye size might be advantageous because of the ability to detect predators in habitats with low vegetation cover, where hiding possibilities are scarce. Our study highlights that changes in temperature and productivity not only lead to interspecific changes in body size but are also related to independent changes of other morphological traits that influence the ecological fit of organisms in their environment.

Abstract:

Tropical mountain ecosystems are threatened by climate and land-use changes. Their diversity and complexity make projec- tions how they respond to environmental changes challenging. A suitable way are trait-based approaches, by distinguishing between response traits that determine the resistance of species to environmental changes and efect traits that are relevant for species’ interactions, biotic processes, and ecosystem functions. The combination of those approaches with land surface models (LSM) linking the functional community composition to ecosystem functions provides new ways to project the response of ecosystems to environmental changes. With the interdisciplinary project RESPECT, we propose a research framework that uses a trait-based response-efect-framework (REF) to quantify relationships between abiotic conditions, the diversity of functional traits in communities, and associated biotic processes, informing a biodiversity-LSM. We apply the framework to a megadiverse tropical mountain forest. We use a plot design along an elevation and a land-use gradient to collect data on abiotic drivers, functional traits, and biotic processes. We integrate these data to build the biodiversity- LSM and illustrate how to test the model. REF results show that aboveground biomass production is not directly related to changing climatic conditions, but indirectly through associated changes in functional traits. Herbivory is directly related to changing abiotic conditions. The biodiversity-LSM informed by local functional trait and soil data improved the simulation of biomass production substantially. We conclude that local data, also derived from previous projects (platform Ecuador), are key elements of the research framework. We specify essential datasets to apply this framework to other mountain ecosystems.

Abstract:

Tropical Mountain Forest (TMF) provides important ecological functions like evapotranspiration (ET) that supplies moisture and energy to the atmosphere. ET observations are scarce and difficult to accomplish particularly in areas of high heterogeneity where TMF are. Remote sensing (RS) allows to quantify and to determine ET spatial variation at the landscape level. Detail imaginary improves high spatial variability retrieval. Thought the greater detail introduces cast shadows by trees which hamper image interpretation. The objective of this study is to characterize ET estimation for the TMF of the southern Ecuadorian Andes by combining meteorological data with high-resolution satellite images. Shadows from high resolution images were masked out by applying focal statistics. The analysis included two meteorological periods typical of the area; a wet period when rain prevails and a dry period when precipitation is more sporadic. The reference evapotranspiration (ET0) was calculated using the FAO-Penman Montheid method by applying data obtained from an automatic weather station. The enhanced vegetation index (EVI) was derived from 2 m resolution WorldView2 satellite images. Results showed a lower ET mean value during the wet period: 1.54 mm day−1 compared to 2.37 mm day−1. Two forest types, differentiated from its structural composition and topographical position (ravine and ridge), marked ET spatial variation. Ravine forest that has a more dense and closed canopy showed higher ET values for both meteorological conditions. A comparison between ET estimations and ET field measurements from a scintillometer device showed a good agreement (coefficient of correlation r = 0.89) that proves the validity of the method. This study demonstrates that the application of high spatial resolution improves ET estimation in TMF especially when shadows are removed. Also, emphasizes the importance of analysing spatial heterogeneity to properly assess ecosystem water flux terms.

Abstract:

Interest in atmosphere-surface flux modeling over the mountainous regions of the globe has increased recently, with a major focus on the prediction of water, carbon and other functional indicators in natural and disturbed conditions. However, less research has been centered on exploring energy fluxes (net radiation; sensible, latent and soil heat) and actual evapotranspiration (ETa) over the Neotropical Andean biome of the páramo. The present study assesses the implementation and parameterization of a state-of-art Land-Surface Model (LSM) for simulation of these fluxes over two representative páramo catchments of southern Ecuador. We evaluated the outputs of the LSM Community Land Model (CLM ver. 4.0) with (i) ground-level flux observations from the first (and highest) Eddy Covariance (EC) tower of the Northern Andean páramos; (ii) spatial ETa estimates from the energy balance-based model METRIC (based on Landsat imagery); and (iii) derived ETa from the closure of the water balance (WB). CLM’s energy predictions revealed a significant underestimation on net radiation, which impacts the sensible and soil heat fluxes (underestimation), and delivers a slight overestimation on latent heat flux. Modeled CLM ETa showed acceptable goodness-of-fit (Pearson R = 0.82) comparable to ETa from METRIC (R = 0.83). Contrarily, a poor performance of ETa WB was observed (R = 0.46). These findings provide solid evidence on the CLM’s accuracy for the ETa modeling, and give insights in the selection of other ETa methods. The study contributes to a better understanding of ecosystem functioning in terms of water loss through evaporative processes, and might help in the development of future LSMs’ implementations focused on climate / land use change scenarios for the páramo.

Abstract:

Background: The impact of selective thinning on forest diversity has been extensively studied in temperate and boreal regions. However, in the tropics, knowledge is still poor regarding the impacts of this silvicultural treatment on functional diversity, especially in tropical mountain forests, which are considered to be highly biodiverse ecosystems and also endangered by human activities. By evaluating the changes on functional diversity by using different indicators, hypothesizing that selective thinning significantly affects (directly or indirectly) tropical mountain forests, this work promotes sustainable ecosystem use. Methods: A total of 52 permanent plots of 2500 m2 each were installed in a primary mountain forest in the San Francisco Biological Reserve to assess the impact of this silvicultural treatment. Selective thinning can be defined as a controlled process, in which trees that compete with ecologically and/or valuable timber species are progressively removed to stimulate the development of profitable ones, called potential crop trees (PCT). In doing so, the best specimens remain in the forest stand until their final harvest. After PCT selection, 30 plots were chosen for the intervention, while 22 plots served as control plots. The thinning intensity fluctuated between 4 and 56 trees ha−1 (average 18.8 ± 12.1 stems ha−1). Functional Diversity (FD) indices, including the community weighted mean (CWM), were determined based on six traits using the FD package implemented in R software. The difference between initial and final conditions of functional richness (FRic), functional divergence (FDiv), functional evenness (FEve), functional dispersion (FDis), and Rao quadratic entropy (RaoQ) was modeled using linear mixed models (LMM). As fixed factors, we used all the predictors inherent to structural and ecological forest conditions before and after the selective thinning and as a random variable, we used the membership to nested sampling units. Results: Functional Richness (FRic) showed significant changes after selective thinning, the other indexes (FEve, FDis, FDiv, RaoQ) were only influenced by predictors related to ecological conditions and characteristics of the community.

Abstract:

Abstract: Research Highlights: This study determined that treatment “release from competitors” causes different reactions in selected timber species respective to diametrical growth, in which the initial size of the tree (diametric class) is important. Also, the growth habit and phenological traits (defoliation) of the species must be considered, which may have an influence on growth after release. Background and Objectives: The objective of the study was to analyze the diametric growth of nine timber species after their release to answer the following questions: (i) Can the diametric growth of the selected timber species be increased by release? (ii) Does the release cause different responses among the tree species? (iii) Are other factors important, such as the initial diameter at breast height (DBH) or the general climate conditions? Materials and Methods: Four-hundred and eighty-eight trees belonging to nine timber species were selected and monitored over a three-year period. Release was applied to 197 trees, whereas 251 trees served as control trees to evaluate the response of diametrical growth. To determine the response of the trees, a linear mixed model (GLMM, R package: LMER4) was used, which was adjusted by a one-way ANOVA test. Results: All species showed a similar annual cycle respective to diametric increases, which is due to the per-humid climate in the area. Precipitation is secondary for the diametric growth because sufficient rainfall occurs throughout year. What is more important, however, are variations in temperature. However, the species responded differently to release. This is because the initial DBH and growth habit are more important factors. Therefore, the species could be classified into three specific groups: Positive, negative and no response to release. Conclusions: Species which prefer open sites responded positively to release, while shade tolerant species and species with pronounced phenological traits responded negatively. The initial DBH was also an important factor for diametric increases. This is because trees of class I (20 cm to 30 cm DBH) responded positively to the treatment, whereas for bigger or older individuals, the differences decreased or became negative.

Abstract:

Tropical montane forests, particularly Andean rainforest, are important ecosystems for regional carbon and water cycles as well as for biological diversity and speciation. Owing to their remoteness, however, ecological key-processes are less understood as in the tropical lowlands. Remote sensing allows modeling of variables related to spatial patterns of carbon stocks and fluxes (e.g., biomass) and ecosystem functioning (e.g., functional leaf traits). However, at a landscape scale most studies conducted so far are based on airborne remote sensing data which is often available only locally and for one time-point. In contrast, multispectral satellites at moderate spectral and spatial resolutions are able to provide spatially continuous and repeated observations. Here, we investigated the effectiveness of Landsat-8 imagery in modeling tropical montane forest biomass, its productivity and selected canopy traits. Topographical, spectral and textural metrics were derived as predictors. To train and validate the models, in-situ data was sampled in 54 permanent plots in forests of southern Ecuador distributed within three study sites at 1000 m, 2000 m and 3000 m a.s.l. We used partial least squares regressions to model and map all response variables. Along the whole elevation gradient biomass and productivity models explained 31%, 43%, 69% and 63% of variance in aboveground biomass, annual wood production, fine litter production and aboveground net primary production, respectively. Regression models of canopy traits measured as community weighted means explained 62%, 78%, 65% and 65% of variance in leaf toughness, specific leaf area, foliar N concentration, and foliar P concentration, respectively. Models at single study sites hardly explained variation in aboveground biomass and the annual wood production indicating that these measures are mainly determined by the change of forest types along with elevation. In contrast, the models of fine litter production and canopy traits explained between 8%–85% in variation depending on the study site. We found spectral metrics, in particular a vegetation index using the red and the green band to provide complementary information to topographical metrics. The model performances for estimating leaf toughness, biochemical canopy traits and related fine litter production all improved when adding spectral information. Our findings therefore revealed that differences in fine litter production and canopy traits in our study area are driven by local changes in vegetation edaphically induced by topography. We conclude that Landsat-derived metrics are useful in modeling fine litter production and biochemical canopy traits, in a topographically and ecologically complex tropical montane forest.

Abstract:

Despite many eorts of the radar community, quantitative precipitation estimation (QPE) from weather radar data remains a challenging topic. The high resolution of X-band radar imagery in space and time comes with an intricate correction process of reflectivity. The steep and high mountain topography of the Andes enhances its complexity. This study aims to optimize the rainfall derivation of the highest X-band radar in the world (4450 m a.s.l.) by using a random forest (RF) model and single Plan Position Indicator (PPI) scans. The performance of the RFmodel was evaluated in comparison with the traditional step-wise approach by using both, the Marshall-Palmer and a site-specific Z–R relationship. Since rain gauge networks are frequently unevenly distributed and hardly available at real time in mountain regions, bias adjustment was neglected. Results showed an improvement in the step-wise approach by using the site-specific (instead of the Marshall-Palmer) Z–R relationship. However, both models highly underestimate the rainfall rate (correlation coecient < 0.69; slope up to 12). Contrary, the RF model greatly outperformed the step-wise approach in all testing locations and on dierent rainfall events (correlation coecient up to 0.83; slope = 1.04). The results are promising and unveil a dierent approach to overcome the high attenuation issues inherent to X-band radars.

Abstract:

The present investigation evaluates the accuracy of estimating above-ground biomass (AGB) by means of two dierent sensors installed onboard an unmanned aerial vehicle (UAV) platform (DJI Inspire I) because the high costs of very high-resolution imagery provided by satellites or light detection and ranging (LiDAR) sensors often impede AGB estimation and the determination of other vegetation parameters. The sensors utilized included an RGB camera (ZENMUSE X3) and a multispectral camera (Parrot Sequoia), whose images were used for AGB estimation in a natural tropical mountain forest (TMF) in Southern Ecuador. The total area covered by the sensors included 80 ha at lower elevations characterized by a fast-changing topography and dierent vegetation covers. From the total area, a core study site of 24 ha was selected for AGB calculation, applying two dierent methods. The firstmethod used the RGB images and applied the structure formotion (SfM) process to generate point clouds for a subsequent individual tree classification. Per the classification at tree level, tree height (H) and diameter at breast height (DBH) could be determined, which are necessary input parameters to calculate AGB (Mg ha 1) by means of a specific allometric equation for wet forests. The second method used the multispectral images to calculate the normalized dierence vegetation index (NDVI), which is the basis for AGB estimation applying an equation for tropical evergreen forests. The obtained results were validated against a previous AGB estimation for the same area using LiDAR data. The study found two major results: (i) The NDVI-based AGB estimates obtained by multispectral drone imagery were less accurate due to the saturation eect in dense tropical forests, (ii) the photogrammetric approach using RGB images provided reliable AGB estimates comparable to expensive LiDAR surveys (R2: 0.85). However, the latter is only possible if an auxiliary digital terrain model (DTM) in very high resolution is available because in dense natural forests the terrain surface (DTM) is hardly detectable by passive sensors due to the canopy layer, which impedes ground detection.

Abstract:

Mesoscale convective systems (MCSs) climatology, the thermodynamic and dynamical variables, and teleconnections influencing MCSs development are assessed for the Paute basin (PB) in the Ecuadorian Andes from 2000 to 2009. The seasonality of MCSs occurrence shows a bimodal pattern, with higher occurrence during March-April (MA) and October-November (ON), analogous to the regional rainfall seasonality. The diurnal cycle of MCSs shows a clear nocturnal occurrence, especially during the MA and ON periods. Interestingly, despite the higher occurrence of MCSs during the rainy seasons, the monthly size relative frequency remains fairly constant throughout the year. On the east of the PB, the persistent high convective available potential and low convective inhibition values from midday to nighttime are likely related to the nocturnal development of the MCSs. A significant positive correlation between the MCSs occurrence to the west of the PB and the Trans-Niño index was found, suggesting that ENSO is an important source of interannual variability of MCSs frequency with increasing development of MCSs during warm ENSO phases. On the east of the PB, the variability of MCSs is positively correlated to the tropical Atlantic sea surface temperature anomalies south of the equator, due to the variability of the Atlantic subtropical anticyclone, showing main departures from this relation when anomalous conditions occur in the tropical Pacific due to ENSO.

Abstract:

Atmospheric carbon (CO2) exchange, evapotranspiration (ET) processes, and their interactions with climatic drivers across tropical alpine grasslands are poorly understood. This lack of understanding is particularly evident for the páramo, the highest vegetated frontier in the northern Andes, the main source of water for inter-Andean cities, and a large carbon storage area. Studies of CO2 and ET fluxes via the standard Eddy Covariance (EC) technique have never been applied to this region, limiting the understanding of diurnal / nocturnal exchanges and budget estimations. In this paper, we report the first EC analysis conducted on the Andean páramo (3765?m a.s.l.); this analysis measured CO2, ET, and micrometeorological variables over two years (2016–2018) to understand their interactions with climatic / biophysical controls. The páramo was found to be a source of CO2 and exhibited a net positive exchange (mean = +99?±?30 gC m?2 per year). The light-responses of net CO2 exchange and the primary productivity were correlated and model-parameterized. Evapotranspiration was 635?±?9?mm per year (51% of the annual rainfall total), and we obtained crop coefficients for the dominant vegetation (Tussock grass) based on reference-ET models FAO56 and ASCE-ERWI (0.90 and 0.78, respectively). We also compared our results to those from other high-altitude (alpine) and high-latitude grasslands (tundra). Finally, we demonstrate that our measurement period is representative of the páramo’s longer-term climate dynamics. Our investigation contributes to the body of knowledge on the land surface-atmosphere processes of the tropical Andes and supports decision-making about ecosystem services management and the preservation of this vulnerable biome.

Abstract:

In tropical agriculture, the vigorously growing Bracken fern causes severe problems by invading pastures and out-competing the common pasture grasses. Due to infestation by that weed, pastures are abandoned after a few years, and as a fatal consequence, the biodi- versity-rich tropical forest is progressively cleared for new grazing areas. Here we present a broad physiological comparison of the two plant species that are the main competitors on the pastures in the tropical Ecuadorian Andes, the planted forage grass Setaria sphacelata and the weed Bracken (Pteridium arachnoideum).With increasing elevation, the competitive power of Bracken increases as shown by satellite data of the study region. Using data obtained from field measurements, the annual biomass production of both plant species, as a measure of their competitive strength, was modeled over an elevational gradient from 1800 to 2800 m. The model shows that with increasing elevation, biomass production of the two species shifts in favor of Bracken which, above 1800 m, is capable of outgrowing the grass. In greenhouse experiments, the effects on plant growth of the presumed key vari- ables of the elevational gradient, temperature and UV radiation, were separately analyzed. Low temperature, as well as UV irradiation, inhibited carbon uptake of the C4-grass more than that of the C3-plant Bracken. The less temperature-sensitive photosynthesis of Bracken and its effective protection from UV radiation contribute to the success of the weed on the highland pastures. In field samples of Bracken but not of Setaria, the content of flavo- noids as UV-scavengers increased with the elevation. Combining modeling with measure- ments in greenhouse and field allowed to explain the invasive growth of a common weed in upland pastures. The performance of Setaria decreases with elevation due to suboptimal photosynthesis at lower temperatures and the inability to adapt its cellular UV screen.

Abstract:

A reliable estimation of Above Ground Biomass (AGB) in Tropical Mountain Forest (TMF) is still complicated, due to fast-changing climate and topographic conditions, which modifies the forest structure within fine scales. The variations in vertical and horizontal forest structure are hardly detectable by small field plots, especially in natural TMF due to the high tree diversity and the inaccessibility of remote areas. Therefore, the present approach used remotely sensed data from a Light Detection and Ranging (LiDAR) sensor in combination with field measurements to estimate AGB accurately for a catchment in the Andes of south-eastern Ecuador. From the LiDAR data, information about horizontal and vertical structure of the TMF could be derived and the vegetation at tree level classified, differentiated between the prevailing forest types (ravine forest, ridge forest and Elfin Forest). Furthermore, topographical variables (Topographic Position Index, TPI; Morphometric Protection Index, MPI) were calculated by means of the high-resolution LiDAR data to analyse the AGB distribution within the catchment. The field measurements included different tree parameters of the species present in the plots, which were used to determine the local mean Wood Density (WD) as well as the specific height-diameter relationship to calculate AGB, applying regional scale modelling at tree level. The results confirmed that field plot measurements alone cannot capture completely the forest structure in TMF but in combination with high resolution LiDAR data, applying a classification at tree level, the AGB amount (Mg ha??1) and its distribution in the entire catchment could be estimated adequately (model accuracy at tree level: R2 > 0.91). It was found that the AGB distribution is strongly related to ridges and depressions (TPI) and to the protection of the site (MPI), because high AGB was also detected at higher elevations (up to 196.6 Mg ha??1, above 2700 m), if the site is situated in depressions (ravine forest) and protected by the surrounding terrain. In general, highest AGB is stored in the protected ravine TMF parts, also at higher elevations, which could only be detected by means of the remote sensed data in high resolution, because most of these areas are inaccessible. Other vegetation units, present in the study catchment (pasture and subpáramo) do not contain large AGB stocks, which underlines the importance of intact natural forest stands.