Solute fluxes via bulk precipitation, throughfall & stemflow in a humid tropical lowland rainforest, Costa Rica

Tropische Regenwälder könnten eine große Rolle in der globalen Kohlenstoffbilanz spielen, da sie als eine der größten terrestrischen C-Senken angesehen werden. Anhand vieler Studien wird deshalb versucht den Beitrag und die Verteilung von Nährstoffflüssen in Ökosystemen zu quantifizieren. Wüsste man erst einmal über momentane Umsatzraten bescheid, könnte man vorhersehen wie sich Veränderungen der Nährstoffzusammensetzung in Zukunft auf ein Ökosystem auswirken. Derzeit besteht die Möglichkeit dass sich der Status der tropischen Regenwälder als C-Senken aufgrund von anthropogenen Eingriffen (Abholzung von Regenwäldern, Landwirtschaft und vermehrter Düngereintrag) insofern umkehren könnte, als dass sie letztendlich zu C-Quellen werden könnten. Im Zuge dieser Diplomarbeit in einem tropischen Tieflandregenwald in Costa Rica wurde in mehreren Arbeitsgruppen versucht die Dynamik und Stoffflüsse des außerordentlich diversen Ökosystems zu quantifizieren. Die Datenerhebung umfasste zahlreiche Aufnahmen: Angefangen von der Ausweisung der vorgesehenen Untersuchungsflächen, Messung des pflanzlichen Biomasse-Zuwachs mittels Dendrometerbändern, Besammlung von Laubstreu und Charakterisierung des C/N-Verhältnisses, über die Bestimmung der Flussmengen von Kronentrauf, Stammabfluss und des Bodenwassergehalts, bis hin zu Untersuchungen der Nährstoff-turnover Prozesse anhand von pool-dilution Experimenten mittels stabiler Isotope. Es wurden insbesondere die Stoffflüsse und Quellen der häufigsten Nährstoffe, in Form von DOC, DON und der An- und Kationen Cl-, NO3-, SO42-, PO43- und Na+, K+, NH4+, Mg2+ und Ca2+ untersucht und deren Herkunft und Verteilung in einem tropischen Waldökosystem beschrieben. Dazu wurden Proben von Laubstreu, Regenwasser, Kronentrauf, Stammabfluss und Bodenwasser zur Beantwortung der Fragestellungen betreffend der Dekomposition, nutrient use efficiency (NUE) und turnover Prozesse des Ökosystems Regenwald entnommen und in konservierter Form zur Analyse an das Department überstellt. Die darauf folgende Laborarbeit bezog sich vor allem auf die Quantifizierung des gesammelten Probenmaterials durch Analyse von Bodenextrakten, Blattmaterial, Groblitter und Wasserproben. Für die Bestimmung und Auswertung der Stoffflüsse der Hydrologie wurden Analysen mittels HPLC-Ionenchromatographie, Massenspektrometrie, Photometrie und TOC/TN Analysen verwendet. Die Studie ergab im Wesentlichen, dass der Eintrag von Nährstoffen durch Freilandniederschlag, Kronentrauf und Stammabfluss im Zeitraum von einem Jahr extremen Schwankungen unterliegt, welche auf mehrere Faktoren zurückzuführen waren. Hauptsächlich bestimmten die Faktoren: Saisonalität, Topographie, Geologie, Sukzession etc. die Nährstoffverfügbarkeit auf den unterschiedlichen Standorten. Es konnten auch gemeinsame Quellen betreffend der Herkunft von Nährstoffen ausgewiesen werden. So wurden Na, Cl, Mg und SO4 etwa hauptsächlich durch Verdunstungsprozesse an der Meeresoberfläche eingebracht während Stoffflüsse von NO3 und PO4 der besseren Versorgung von Nährstoffen auf unterschiedlich situierten Standorten zugewiesen werden konnten. Obwohl Unterschiede im Diversitäts- und Blattflächenindex zwischen verschiedenen Sukzessionsstadien nachgewiesen werden konnten, war es nicht möglich die Zusammensetzung der Baumarten der einzelnen Standorte mit den Nährstoffflüssen zu korrelieren. Dies mag daran liegen das der ausgesprochene Artenreichtum von über 200 Baumarten in der Region des Esquinas Nationalparks, die unterliegenden Differenzierungen betreffend der Zusammensetzung und Verteilung von Nährstoffen in diesem tropischen Ökosystem überschattet. Tropische Regenwälder gehören zu den diversesten Ökosystemen der Erde und daher wird es weiterhin eine Herausforderung bleiben darin Stoffflüsse zu messen, zu quantifizieren und zu beschreiben. Diese Studie bietet einen weiteren Einblick in die Funktionen und Mechanismen von Nährstoffflüssen, welche in Zukunft hinsichtlich der Kohlenstoff-Bilanz, besonders in Zeiten globaler Erwärmung, von erhöhter Bedeutung sein könnten.Tropical rainforests are considered to play major roles as sinks in the planet’s carbon budget; therefore numerous studies try to quantify the input, cycling and dispersal of nutrients. By calculating present states and turnover rates we will be able to foresee the impact of shifts in nutrient fluxes in future scenarios (e.g. global warming caused by the alteration of pristine landscapes) which may invert the current status insofar as tropical regions might soon act as carbon source instead. In this study measurements of Bulk Precipitation, throughfall and stemflow were used to investigate nutrient fluxes in three forest sites in different stages of succession. Collectors for throughfall (n=45), stemflow (n=36), soil water content (n=9) and litter percolate (n=6) were put into three forest sites of 0.12 hectares each, and sampled on event basis up to intervals of two weeks over a period of 2 years. Nutrients (H+, Na+, HH4+, K+, Mg2+, Ca2+, Cl-, NO32-, CO32-, SO42-, PO43-, DOC and DON) were determined by HPLC (Dionex) and tested statistically to investigate significant differences between sites by one-way and two-way ANOVA, after log normalization of data, and Tuckey-HSD post-hoc test. Here, we constitute an innovative approach for the quantification of nutrient inputs via net throughfall fluxes (NTF) deriving from BP and DD, based on the multiple regression model (Lovett & Lindberg 1984) which announced that the role of canopy exchange is of major importance in terms of tropical nutrient cycling, whereas the influence of dry deposition was weak since largely independent of rainfall. We moreover investigated the major controls on NTF such as soil fertility, topography, canopy structure and species assemblage. The use of a Sun Scan probe (estimating canopy closure) did reveal significant differences between forest sites, but spearman-rank correlation of NTF and canopy closure showed no significant coherency. Investigating species inventory, Fisher’s alpha diversity index, ANOSIM and SIMPER analysis indicated differences in species composition between pristine and secondary forests. However, relating resemblance matrices showed no significant influence of species assemblages on nutrient composition of forest sites. The clustering of nutrients revealed by PCA gave insight on origin and sources of associated solutes in NTF

Optimal balancing of xylem efficiency and safety explains plant vulnerability to drought

In vast areas of the world, forests and vegetation are water limited and plant survival depends on the ability to avoid catastrophic hydraulic failure. Therefore, it is remarkable that plants take hydraulic risks by operating at water potentials (psi) that induce partial failure of the water conduits (xylem). Here we present an eco-evolutionary optimality principle for xylem conduit design that explains this phenomenon based on the hypothesis that conductive efficiency and safety are optimally co-adapted to the environment. The model explains the relationship between the tolerance to negative water potential (psi(50)) and the environmentally dependent minimum psi (psi(min)) across a large number of species, and along the xylem pathway within individuals of two species studied. The wider hydraulic safety margin in gymnosperms compared to angiosperms can be explained as an adaptation to a higher susceptibility to accumulation of embolism. The model provides a novel optimality-based perspective on the relationship between xylem safety and efficiency

A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region

Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25 % and up to 60 %, respectively. Our comparison metrics provide a quantitative measure for model–data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products

Nitrogen dynamics in Turbic Cryosols from Siberia and Greenland

Turbic Cryosols (permafrost soils characterized by cryoturbation, i.e., by mixing of soil layers due to freezing and thawing) are widespread across the Arctic, and contain large amounts of poorly decomposed organic material buried in the subsoil. This cryoturbated organic matter exhibits retarded decomposition compared to organic material in the topsoil. Since soil organic matter (SOM) decomposition is known to be tightly linked to N availability, we investigated N transformation rates in different soil horizons of three tundra sites in north-eastern Siberia and Greenland. We measured gross rates of protein depolymerization, N mineralization (ammonification) and nitrification, as well as microbial uptake of amino acids and NH4+ using an array of 15N pool dilution approaches. We found that all sites and horizons were characterized by low N availability, as indicated by low N mineralization compared to protein depolymerization rates (with gross N mineralization accounting on average for 14% of gross protein depolymerization). The proportion of organic N mineralized was significantly higher at the Greenland than at the Siberian sites, suggesting differences in N limitation. The proportion of organic N mineralized, however, did not differ significantly between soil horizons, pointing to a similar N demand of the microbial community of each horizon. In contrast, absolute N transformation rates were significantly lower in cryoturbated than in organic horizons, with cryoturbated horizons reaching not more than 32% of the transformation rates in organic horizons. Our results thus indicate a deceleration of the entire N cycle in cryoturbated soil horizons, especially strongly reduced rates of protein depolymerization (16% of organic horizons) which is considered the rate-limiting step in soil N cycling.publishedVersio

Effects of soil organic matter properties and microbial community composition on enzyme activities in cryoturbated arctic soils

Enzyme-mediated decomposition of soil organic matter (SOM) is controlled, amongst other factors, by organic matter properties and by the microbial decomposer community present. Since microbial community composition and SOM properties are often interrelated and both change with soil depth, the drivers of enzymatic decomposition are hard to dissect. We investigated soils from three regions in the Siberian Arctic, where carbon rich topsoil material has been incorporated into the subsoil (cryoturbation). We took advantage of this subduction to test if SOM properties shape microbial community composition, and to identify controls of both on enzyme activities. We found that microbial community composition (estimated by phospholipid fatty acid analysis), was similar in cryoturbated material and in surrounding subsoil, although carbon and nitrogen contents were similar in cryoturbated material and topsoils. This suggests that the microbial community in cryoturbated material was not well adapted to SOM properties. We also measured three potential enzyme activities (cellobiohydrolase, leucine-amino-peptidase and phenoloxidase) and used structural equation models (SEMs) to identify direct and indirect drivers of the three enzyme activities. The models included microbial community composition, carbon and nitrogen contents, clay content, water content, and pH. Models for regular horizons, excluding cryoturbated material, showed that all enzyme activities were mainly controlled by carbon or nitrogen. Microbial community composition had no effect. In contrast, models for cryoturbated material showed that enzyme activities were also related to microbial community composition. The additional control of microbial community composition could have restrained enzyme activities and furthermore decomposition in general. The functional decoupling of SOM properties and microbial community composition might thus be one of the reasons for low decomposition rates and the persistence of 400 Gt carbon stored in cryoturbated material

Performance of Laser-Based Electronic Devices for Structural Analysis of Amazonian Terra-Firme Forests

Tropical vegetation biomass represents a key component of the carbon stored in global forest ecosystems. Estimates of aboveground biomass commonly rely on measurements of tree size (diameter and height) and then indirectly relate, via allometric relationships and wood density, to biomass sampled from a relatively small number of harvested and weighed trees. Recently, however, novel in situ remote sensing techniques have been proposed, which may provide nondestructive alternative approaches to derive biomass estimates. Nonetheless, we still lack knowledge of the measurement uncertainties, as both the calibration and validation of estimates using different techniques and instruments requires consistent assessment of the underlying errors. To that end, we investigate different approaches estimating the tropical aboveground biomass in situ. We quantify the total and systematic errors among measurements obtained from terrestrial light detection and ranging (LiDAR), hypsometer-based trigonometry, and traditional forest inventory. We show that laser-based estimates of aboveground biomass are in good agreement (<10% measurement uncertainty) with traditional measurements. However, relative uncertainties vary among the allometric equations based on the vegetation parameters used for parameterization. We report the error metrics for measurements of tree diameter and tree height and discuss the consequences for estimated biomass. Despite methodological differences detected in this study, we conclude that laser-based electronic devices could complement conventional measurement techniques, thereby potentially improving estimates of tropical vegetation biomass

Climatic and edaphic controls over tropical forest diversity and vegetation carbon storage

Tropical rainforests harbor exceptionally high biodiversity and store large amounts of carbon in vegetation biomass. However, regional variation in plant species richness and vegetation carbon stock can be substantial, and may be related to the heterogeneity of topoedaphic properties. Therefore, aboveground vegetation carbon storage typically differs between geographic forest regions in association with the locally dominant plant functional group. A better understanding of the underlying factors controlling tropical forest diversity and vegetation carbon storage could be critical for predicting tropical carbon sink strength in response to projected climate change. Based on regionally replicated 1-ha forest inventory plots established in a region of high geomorphological heterogeneity we investigated how climatic and edaphic factors affect tropical forest diversity and vegetation carbon storage. Plant species richness (of all living stems >10 cm in diameter) ranged from 69 to 127 ha-1 and vegetation carbon storage ranged from 114 to 200 t ha-1. While plant species richness was controlled by climate and soil water availability, vegetation carbon storage was strongly related to wood density and soil phosphorus availability. Results suggest that local heterogeneity in resource availability and plant functional composition should be considered to improve projections of tropical forest ecosystem functioning under future scenarios

Global forest management data for 2015 at a 100 m resolution

Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (https://www.geo-wiki.org/). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services

The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

International audienceForest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (aGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. aGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. all plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities