Deforestation and forest degradation monitoring and assessment of biomass and carbon stock of lowland rainforest in the Analanjirofo region, Madagascar

Madagascar is currently developing a policy and strategies to enhance the sustainable management of its natural resources, encouraged by United Nations Framework Convention on Climate Change (UNFCCC) and REDD. To set up a sustainable financing scheme methodologies have to be provided that estimate, prevent and mitigate leakage, develop national and regional baselines, and estimate carbon benefits. With this research study this challenge was tried to be addressed by analysing a lowland rainforest in the Analanjirofo region in the district of Soanierana Ivongo, North East of Madagascar. For two distinguished forest degradation stages: “low degraded forest” and “degraded forest” aboveground biomass and carbon stock was assessed. The corresponding rates of carbon within those two classes were calculated and linked to a multi-temporal set of SPOT satellite data acquired in 1991, 2004 and 2009. Deforestation and particularly degradation and the related carbon stock developments were analysed. With the assessed data for the 3 years 1991, 2004 and 2009 it was possible to model a baseline and to develop a forest prediction for 2020 for Analanjirofo region in the district of Soanierana Ivongo. These results, developed applying robust methods, may provide important spatial information regarding the priorities in planning and implementation of future REDD+ activities in the area.

Institutions for sustainable governance of forests: Equity, robustness and cross-level interactions in Mawlyngbna, Meghalaya, India

This study adopts Ostrom’s Social-Ecological Systems (SES) framework in empirical fieldwork to explain how local forestry institutions affect forest ecosystems and social equity in the community of Mawlyngbna in North-East India. Data was collected through 26 semi-structured interviews, participatory timeline development, policy documents, direct observation, periodicals, transect walks, and a concurrent forest-ecological study in the village. Results show that Mawlyngbna's forests provide important sources of livelihood benefits for the villagers. However, ecological disturbance and diversity varies among the different forest ownership types and forest-based livelihood benefits are inequitably distributed. Based on a bounded rationality approach, our analysis proposes a set of causal mechanisms that trace these observed social-ecological outcomes to the attributes of the resource system, resource units, actors and governance system. We analyse opportunities and constraints of interactions between the village, regional, and state levels. We discuss how Ostrom’s design principles for community-based resource governance inform the explanation of robustness but have a blind spot in explaining social equity. We report experiences made using the SES framework in empirical fieldwork. We conclude that mapping cross-level interactions in the SES framework needs conceptual refinement and that explaining social equity of forest governance needs theoretical advances.

Automatic quality control in clinical (1) H MRSI of brain cancer.

MRSI grids frequently show spectra with poor quality, mainly because of the high sensitivity of MRS to field inhomogeneities. These poor quality spectra are prone to quantification and/or interpretation errors that can have a significant impact on the clinical use of spectroscopic data. Therefore, quality control of the spectra should always precede their clinical use. When performed manually, quality assessment of MRSI spectra is not only a tedious and time-consuming task, but is also affected by human subjectivity. Consequently, automatic, fast and reliable methods for spectral quality assessment are of utmost interest. In this article, we present a new random forest-based method for automatic quality assessment of (1) H MRSI brain spectra, which uses a new set of MRS signal features. The random forest classifier was trained on spectra from 40 MRSI grids that were classified as acceptable or non-acceptable by two expert spectroscopists. To account for the effects of intra-rater reliability, each spectrum was rated for quality three times by each rater. The automatic method classified these spectra with an area under the curve (AUC) of 0.976. Furthermore, in the subset of spectra containing only the cases that were classified every time in the same way by the spectroscopists, an AUC of 0.998 was obtained. Feature importance for the classification was also evaluated. Frequency domain skewness and kurtosis, as well as time domain signal-to-noise ratios (SNRs) in the ranges 50-75 ms and 75-100 ms, were the most important features. Given that the method is able to assess a whole MRSI grid faster than a spectroscopist (approximately 3 s versus approximately 3 min), and without loss of accuracy (agreement between classifier trained with just one session and any of the other labelling sessions, 89.88%; agreement between any two labelling sessions, 89.03%), the authors suggest its implementation in the clinical routine. The method presented in this article was implemented in jMRUI's SpectrIm plugin. Copyright © 2016 John Wiley & Sons, Ltd.

An ice-core based history of Siberian forest fires since AD 1250

Forest fires play a key role in the global carbon cycle and thus, can affect regional and global climate. Although fires in extended areas of Russian boreal forests have a considerable influence on atmospheric greenhouse gas and soot concentrations, estimates of their impact on climate are hampered by a lack of data on the history of forest fires. Especially regions with strong continental climate are of high importance due to an intensified development of wildfires. In this study we reconstruct the fire history of Southern Siberia during the past 750 years using ice-core based nitrate, potassium, and charcoal concentration records from Belukha glacier in the continental Siberian Altai. A period of exceptionally high forest-fire activity was observed between AD 1600 and 1680, following an extremely dry period AD 1540-1600. Ice-core pollen data suggest distinct forest diebacks and the expansion of steppe in response to dry climatic conditions. Coherence with a paleoenvironmental record from the 200 km distant Siberian lake Teletskoye shows that the vegetational shift AD 1540-1680, the increase in fire activity AD 1600-1680, and the subsequent recovery of forests AD 1700 were of regional significance. Dead biomass accumulation in response to drought and high temperatures around AD 1600 probably triggered maximum forest-fire activity AD 1600-1680. The extreme dry period in the 16th century was also observed at other sites in Central Asia and is possibly associated with a persistent positive mode of the Pacific Decadal Oscillation (PDO). No significant increase in biomass burning occurred in the Altai region during the last 300 years, despite strongly increasing temperatures and human activities. Our results imply that precipitation changes controlled fire-regime and vegetation shifts in the Altai region during the past 750 years. We conclude that high sensitivity of ecosystems to occasional decadal-scale drought events may trigger unprecedented environmental reorganizations under global-warming conditions.

Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha-1yr-1. Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances.

Assessing sustainable forest management under REDD+: a community-based labour perspective

Reducing emissions from deforestation and forest degradation plus (REDD+) encourages economic support for reducing deforestation and conserving or increasing existing forest carbon stocks. The way in which incentives are structured affects trade-offs between local livelihoods, carbon emission reduction, and the cost-effectiveness of a REDD + programme. Looking at first-hand empirical data from 208 farming households in the Bolivian Amazon froma household economy perspective, our study explores two policy options: 1) compensated reduction of emissions fromold-growth forest clearing for agriculture, and 2) direct payments for labour input into sustainable forest anagement combined with a commitment not to clear old-growth forest. Our results indicate that direct payments for sustainable forest management – an approach that focuses on valuing farmers' labour input – can be more cost-effective than compensated reduction and in some cases is themost appropriate choice for achieving improved household incomes, permanence of changes, avoidance of leakages, and community-based institutional enforcement for sustainable forest management.

Forest dynamics during the transition from the Oldest Dryas to the Bølling–Allerød at Gerzensee—a simulation study

The aim of this study was to explore potential causes and mechanisms for the sequence and temporal pattern of tree taxa, specifically for the shift from shrub-tundra to birch–juniper woodland during and after the transition from the Oldest Dryas to the Bølling–Allerød in the region surrounding the lake Gerzensee in southern Central Europe. We tested the influence of climate, forest dynamics, community dynamics compared to other causes for delays. For this aim temperature reconstructed from a δ18O-record was used as input driving the multi-species forest-landscape model TreeMig. In a stepwise scenario analysis, population dynamics along with pollen production and transport were simulated and compared with pollen-influx data, according to scenarios of different δ18O/temperature sensitivities, different precipitation levels, with/without inter-specific competition, and with/without prescribed arrival of species. In the best-fitting scenarios, the effects on competitive relationships, pollen production, spatial forest structure, albedo, and surface roughness were examined in more detail. The appearance of most taxa in the data could only be explained by the coldest temperature scenario with a sensitivity of 0.3‰/°C, corresponding to an anomaly of − 15 °C. Once the taxa were present, their temporal pattern was shaped by competition. The later arrival of Pinus could not be explained even by the coldest temperatures, and its timing had to be prescribed by first observations in the pollen record. After the arrival into the simulation area, the expansion of Pinus was further influenced by competitors and minor climate oscillations. The rapid change in the simulated species composition went along with a drastic change in forest structure, leaf area, albedo, and surface roughness. Pollen increased only shortly after biomass. Based on our simulations, two alternative potential scenarios for the pollen pattern can be given: either very cold climate suppressed most species in the Oldest Dryas, or they were delayed by soil formation or migration. One taxon, Pinus, was delayed by migration and then additionally hindered by competition. Community dynamics affected the pattern in two ways: potentially by facilitation, i.e. by nitrogen-fixing pioneer species at the onset, whereas the later pattern was clearly shaped by competition. The simulated structural changes illustrate how vegetation on a larger scale could feed back to the climate system. For a better understanding, a more integrated simulation approach covering also the immigration from refugia would be necessary, for this combines climate-driven population dynamics, migration, individual pollen production and transport, soil dynamics, and physiology of individual pollen production.

The influence of sampling design on tree-ring-based quantification of forest growth

Tree-rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree-ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and-climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long-term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree-ring-based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short-term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree-ring-based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.

Aluminum toxicity to tropical montane forest tree seedlings in southern Ecuador: response of biomass and plant morphology to elevated Al concentrations

In acid tropical forest soils (pH < 5.5) increased mobility of aluminum might limit aboveground productivity. Therefore, we evaluated Al phytotoxicity of three native tree species of tropical montane forests in southern Ecuador. An hydroponic dose-response experiment was conducted. Seedlings of Cedrela odorata L., Heliocarpus americanus L., and Tabebuia chrysantha (Jacq.) G. Nicholson were treated with 0, 300, 600, 1200, and 2400 mu M Al and an organic layer leachate. Dose-response curves were generated for root and shoot morphologic properties to determine effective concentrations (EC). Shoot biomass and healthy leaf area decreased by 44 % to 83 % at 2400 mu M Al, root biomass did not respond (C. odorata), declined by 51 % (H. americanus), or was stimulated at low Al concentrations of 300 mu M (T. chrysantha). EC10 (i.e. reduction by 10 %) values of Al for total biomass were 315 mu M (C. odorata), 219 mu M (H. americanus), and 368 mu M (T. chrysantha). Helicarpus americanus, a fast growing pioneer tree species, was most sensitive to Al toxicity. Negative effects were strongest if plants grew in organic layer leachate, indicating limitation of plant growth by nutrient scarcity rather than Al toxicity. Al toxicity occurred at Al concentrations far above those in native organic layer leachate.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Tracing of 15N in a mountain spruce forest: comparison of experimental data with th TRACE model

Despite numerous studies about nitrogen-cycling in forest ecosystems, many uncertainties remain, especially regarding the longer-term nitrogen accumulation. To contribute to filling this gap, the dynamic process-based model TRACE, with the ability to simulate 15N tracer redistribution in forest ecosystems was used to study N cycling processes in a mountain spruce forest of the northern edge of the Alps in Switzerland (Alptal, SZ). Most modeling analyses of N-cycling and C-N interactions have very limited ability to determine whether the process interactions are captured correctly. Because the interactions in such a system are complex, it is possible to get the whole-system C and N cycling right in a model without really knowing if the way the model combines fine-scale interactions to derive whole-system cycling is correct. With the possibility to simulate 15N tracer redistribution in ecosystem compartments, TRACE features a very powerful tool for the validation of fine-scale processes captured by the model. We first adapted the model to the new site (Alptal, Switzerland; long-term low-dose N-amendment experiment) by including a new algorithm for preferential water flow and by parameterizing of differences in drivers such as climate, N deposition and initial site conditions. After the calibration of key rates such as NPP and SOM turnover, we simulated patterns of 15N redistribution to compare against 15N field observations from a large-scale labeling experiment. The comparison of 15N field data with the modeled redistribution of the tracer in the soil horizons and vegetation compartments shows that the majority of fine-scale processes are captured satisfactorily. Particularly, the model is able to reproduce the fact that the largest part of the N deposition is immobilized in the soil. The discrepancies of 15N recovery in the LF and M soil horizon can be explained by the application method of the tracer and by the retention of the applied tracer by the well developed moss layer, which is not considered in the model. Discrepancies in the dynamics of foliage and litterfall 15N recovery were also observed and are related to the longevity of the needles in our mountain forest. As a next step, we will use the final Alptal version of the model to calculate the effects of climate change (temperature, CO2) and N deposition on ecosystem C sequestration in this regionally representative Norway spruce (Picea abies) stand.

Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging

In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.

Methodical study of nitrous oxide eddy covariance measurements using quantum cascade laser spectrometery over a Swiss forest

Nitrous oxide fluxes were measured at the Lägeren CarboEurope IP flux site over the multi-species mixed forest dominated by European beech and Norway spruce. Measurements were carried out during a four-week period in October–November 2005 during leaf senescence. Fluxes were measured with a standard ultrasonic anemometer in combination with a quantum cascade laser absorption spectrometer that measured N2O, CO2, and H2O mixing ratios simultaneously at 5 Hz time resolution. To distinguish insignificant fluxes from significant ones it is proposed to use a new approach based on the significance of the correlation coefficient between vertical wind speed and mixing ratio fluctuations. This procedure eliminated roughly 56% of our half-hourly fluxes. Based on the remaining, quality checked N2O fluxes we quantified the mean efflux at 0.8±0.4 μmol m−2 h−1 (mean ± standard error). Most of the contribution to the N2O flux occurred during a 6.5-h period starting 4.5 h before each precipitation event. No relation with precipitation amount could be found. Visibility data representing fog density and duration at the site indicate that wetting of the canopy may have as strong an effect on N2O effluxes as does below-ground microbial activity. It is speculated that above-ground N2O production from the senescing leaves at high moisture (fog, drizzle, onset of precipitation event) may be responsible for part of the measured flux.