Observer error structure in bull trout redd counts in Montana streams: Implications for inference on true redd numbers

USGS Publications Warehouse

Muhlfeld, Clint C.; Taper, Mark L.; Staples, David F.; Shepard, Bradley B.

2006-01-01

Despite the widespread use of redd counts to monitor trends in salmonid populations, few studies have evaluated the uncertainties in observed counts. We assessed the variability in redd counts for migratory bull trout Salvelinus confluentus among experienced observers in Lion and Goat creeks, which are tributaries to the Swan River, Montana. We documented substantially lower observer variability in bull trout redd counts than did previous studies. Observer counts ranged from 78% to 107% of our best estimates of true redd numbers in Lion Creek and from 90% to 130% of our best estimates in Goat Creek. Observers made both errors of omission and errors of false identification, and we modeled this combination by use of a binomial probability of detection and a Poisson count distribution of false identifications. Redd detection probabilities were high (mean = 83%) and exhibited no significant variation among observers (SD = 8%). We applied this error structure to annual redd counts in the Swan River basin (1982–2004) to correct for observer error and thus derived more accurate estimates of redd numbers and associated confidence intervals. Our results indicate that bias in redd counts can be reduced if experienced observers are used to conduct annual redd counts. Future studies should assess both sources of observer error to increase the validity of using redd counts for inferring true redd numbers in different basins. This information will help fisheries biologists to more precisely monitor population trends, identify recovery and extinction thresholds for conservation and recovery programs, ascertain and predict how management actions influence distribution and abundance, and examine effects of recovery and restoration activities.

The challenge of assessing social dimensions of avoided deforestation: Examples from Cambodia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pasgaard, M., E-mail: mase@life.ku.dk

Reduced Emissions from Deforestation and Forest Degradation in developing countries (REDD +) has moved to the central stage of the climate change debate by being promoted as a significant, cheap, and quick win-win strategy to reduce greenhouse gas emissions and thereby mitigate climate change. In order to be successful in reducing emissions while providing the projected social and environmental co-benefits, REDD + needs to overcome key challenges of insecure forest tenure and inequity in the distribution of benefits. Such challenges threaten to affect the livelihoods and well-being in the local communities and in turn the effectiveness of REDD+. While REDDmore » + programs will affect the participating communities, there is limited knowledge as to what social impacts these projects may bring to the local population. Similarly, assessment of these social dimensions has received little attention until recently, and is consequently out of sync with the realities of REDD + projects. The present paper aims to shed light on the methodological and contextual challenges in the assessment of the social dimensions of REDD+. Some of the main social concerns of REDD + are outlined with an emphasis on the uniqueness and complexity of REDD + interventions. Recently proposed approaches to assess social impacts in REDD + are critically assessed in terms of the diversity of frameworks proposed, choice of social indicators, and data collection requirements. Specifically, these methodological implications are further discussed in the light of the social dimensions and the prescribed regulations of REDD + in a Cambodian context. - Highlights: Black-Right-Pointing-Pointer Insecure tenure and inequitable benefit sharing are main social concerns in REDD +. Black-Right-Pointing-Pointer Two guides to social assessments in REDD + are critically reviewed. Black-Right-Pointing-Pointer Mismatch between social assessment requirements and the reality of REDD + is analyzed. Black-Right-Pointing-Pointer Concrete, topical examples from Cambodian REDD + are used. Black-Right-Pointing-Pointer Support the claim to add qualitative assessment of social dimensions in REDD +.« less

Is There an Ideal REDD+ Program? An Analysis of Policy Trade-Offs at the Local Level

PubMed Central

Dyer, George A.; Matthews, Robin; Meyfroidt, Patrick

2012-01-01

We use economy-wide simulation methods to analyze the outcome of a simple REDD+ program in a mixed subsistence/commercial-agriculture economy. Alternative scenarios help trace REDD+’s causal chain, revealing how trade-offs between the program’s public and private costs and benefits determine its effectiveness, efficiency and equity (the 3Es). Scenarios reveal a complex relationship between the 3Es not evident in more aggregate analyses. Setting aside land as a carbon sink always influences the productivity of agriculture and its supply of non-market goods and services; but the overall returns to land and labor–which ultimately determine the opportunity cost of enrollment, the price of carbon and the distribution of gains and losses–depend on local conditions. In the study area, market-oriented landowners could enroll 30% of local land into a cost-effective program, but local subsistence demands would raise their opportunity costs as REDD+ unfurls, increasing the marginal cost of carbon. A combination of rent and wage changes would create net costs for most private stakeholders, including program participants. Increasing carbon prices undermines the program’s efficiency without solving its inequities; expanding the program reduces inefficiencies but increases private costs with only minor improvements in equity. A program that prevents job losses could be the best option, but its efficiency compared to direct compensation could depend on program scale. Overall, neither the cost nor the 3Es of alternative REDD+ programs can be assessed without accounting for local demand for subsistence goods and services. In the context of Mexico’s tropical highlands, a moderate-sized REDD+ program could at best have no net impact on rural households. REDD+ mechanisms should avoid general formulas by giving local authorities the necessary flexibility to address the trade-offs involved. National programs themselves should remain flexible enough to adjust for spatially and temporally changing contexts. PMID:23300681

Identifying Where REDD+ Financially Out-Competes Oil Palm in Floodplain Landscapes Using a Fine-Scale Approach

PubMed Central

MacMillan, Douglas C.; Xofis, Panteleimon; Ancrenaz, Marc; Tzanopoulos, Joseph; Ong, Robert; Goossens, Benoit; Koh, Lian Pin; Del Valle, Christian; Peter, Lucy; Morel, Alexandra C.; Lackman, Isabelle; Chung, Robin; Kler, Harjinder; Ambu, Laurentius; Baya, William; Knight, Andrew T.

2016-01-01

Reducing Emissions from Deforestation and forest Degradation (REDD+) aims to avoid forest conversion to alternative land-uses through financial incentives. Oil-palm has high opportunity costs, which according to current literature questions the financial competitiveness of REDD+ in tropical lowlands. To understand this more, we undertook regional fine-scale and coarse-scale analyses (through carbon mapping and economic modelling) to assess the financial viability of REDD+ in safeguarding unprotected forest (30,173 ha) in the Lower Kinabatangan floodplain in Malaysian Borneo. Results estimate 4.7 million metric tons of carbon (MgC) in unprotected forest, with 64% allocated for oil-palm cultivations. Through fine-scale mapping and carbon accounting, we demonstrated that REDD+ can outcompete oil-palm in regions with low suitability, with low carbon prices and low carbon stock. In areas with medium oil-palm suitability, REDD+ could outcompete oil palm in areas with: very high carbon and lower carbon price; medium carbon price and average carbon stock; or, low carbon stock and high carbon price. Areas with high oil palm suitability, REDD+ could only outcompete with higher carbon price and higher carbon stock. In the coarse-scale model, oil-palm outcompeted REDD+ in all cases. For the fine-scale models at the landscape level, low carbon offset prices (US $3 MgCO2e) would enable REDD+ to outcompete oil-palm in 55% of the unprotected forests requiring US $27 million to secure these areas for 25 years. Higher carbon offset price (US $30 MgCO2e) would increase the competitiveness of REDD+ within the landscape but would still only capture between 69%-74% of the unprotected forest, requiring US $380–416 million in carbon financing. REDD+ has been identified as a strategy to mitigate climate change by many countries (including Malaysia). Although REDD+ in certain scenarios cannot outcompete oil palm, this research contributes to the global REDD+ debate by: highlighting REDD+ competitiveness in tropical floodplain landscapes; and, providing a robust approach for identifying and targeting limited REDD+ funds. PMID:27276218

Identifying Where REDD+ Financially Out-Competes Oil Palm in Floodplain Landscapes Using a Fine-Scale Approach.

PubMed

Abram, Nicola K; MacMillan, Douglas C; Xofis, Panteleimon; Ancrenaz, Marc; Tzanopoulos, Joseph; Ong, Robert; Goossens, Benoit; Koh, Lian Pin; Del Valle, Christian; Peter, Lucy; Morel, Alexandra C; Lackman, Isabelle; Chung, Robin; Kler, Harjinder; Ambu, Laurentius; Baya, William; Knight, Andrew T

2016-01-01

Reducing Emissions from Deforestation and forest Degradation (REDD+) aims to avoid forest conversion to alternative land-uses through financial incentives. Oil-palm has high opportunity costs, which according to current literature questions the financial competitiveness of REDD+ in tropical lowlands. To understand this more, we undertook regional fine-scale and coarse-scale analyses (through carbon mapping and economic modelling) to assess the financial viability of REDD+ in safeguarding unprotected forest (30,173 ha) in the Lower Kinabatangan floodplain in Malaysian Borneo. Results estimate 4.7 million metric tons of carbon (MgC) in unprotected forest, with 64% allocated for oil-palm cultivations. Through fine-scale mapping and carbon accounting, we demonstrated that REDD+ can outcompete oil-palm in regions with low suitability, with low carbon prices and low carbon stock. In areas with medium oil-palm suitability, REDD+ could outcompete oil palm in areas with: very high carbon and lower carbon price; medium carbon price and average carbon stock; or, low carbon stock and high carbon price. Areas with high oil palm suitability, REDD+ could only outcompete with higher carbon price and higher carbon stock. In the coarse-scale model, oil-palm outcompeted REDD+ in all cases. For the fine-scale models at the landscape level, low carbon offset prices (US $3 MgCO2e) would enable REDD+ to outcompete oil-palm in 55% of the unprotected forests requiring US $27 million to secure these areas for 25 years. Higher carbon offset price (US $30 MgCO2e) would increase the competitiveness of REDD+ within the landscape but would still only capture between 69%-74% of the unprotected forest, requiring US $380-416 million in carbon financing. REDD+ has been identified as a strategy to mitigate climate change by many countries (including Malaysia). Although REDD+ in certain scenarios cannot outcompete oil palm, this research contributes to the global REDD+ debate by: highlighting REDD+ competitiveness in tropical floodplain landscapes; and, providing a robust approach for identifying and targeting limited REDD+ funds.

Composition and location of simulated lake-shore redds influence incubation success in kokanee, Oncorhynchus nerka

USGS Publications Warehouse

Fincel, M.J.; Chipps, S.R.; Bennett, D.H.

2009-01-01

Methods for improving spawning habitat for lakeshore spawning kokanee, Oncorhynchus nerka (Walbaum), were explored by quantifying incubation success of embryos exposed to three substrate treatments in Lake Pend Oreille, Idaho, USA. Substrate treatments included no modification that used existing gravels in the lake (EXISTING), a cleaned substrate treatment where existing gravels were sifted in the water column to remove silt (CLEANED) and the addition of new, silt-free gravel (ADDED). Incubation success was evaluated using Whitlock-Vibert incubation boxes buried within each substrate treatment that contained recently fertilised embryos. Upon retrieval, live and dead sac fry and eyed eggs were enumerated to determine incubation success (sac fry and eyed eggs ?? 100/number of fertilised embryos). Incubation success varied significantly among locations and redd treatments. In general, incubation success among ADDED redds (0.0-13.0%) was significantly lower than that for EXISTING (1.4-61.0%) and CLEANED (0.4-62.5%) redds. Adding new gravel to spawning areas changed the morphometry of the gravel-water interface and probably exposed embryos to disturbance from wave action and reduced embryo survival. Moreover, efforts to improve spawning habitat for lakeshore spawning kokanee should consider water depth and location (e.g. protected shorelines) as important variables. Adding clean gravel to existing spawning areas may provide little benefit if water depth or lake-bottom morphometry are altered. ?? 2009 Blackwell Publishing Ltd.

Reducing emissions from deforestation and forest degradation (REDD+): game changer or just another quick fix?

PubMed

Venter, Oscar; Koh, Lian Pin

2012-02-01

Reducing emissions from deforestation and forest degradation (REDD+) provides financial compensation to land owners who avoid converting standing forests to other land uses. In this paper, we review the main opportunities and challenges for REDD+ implementation, including expectations for REDD+ to deliver on multiple environmental and societal cobenefits. We also highlight a recent case study, the Norway-Indonesia REDD+ agreement and discuss how it might be a harbinger of outcomes in other forest-rich nations seeking REDD+ funds. Looking forward, we critically examine the fundamental assumptions of REDD+ as a solution for the atmospheric buildup of greenhouse gas emissions and tropical deforestation. We conclude that REDD+ is currently the most promising mechanism driving the conservation of tropical forests. Yet, to emerge as a true game changer, REDD+ must still demonstrate that it can access low transaction cost and high-volume carbon markets or funds, while also providing or complimenting a suite of nonmonetary incentives to encourage a developing nation's transition from forest losing to forest gaining, and align with, not undermine, a globally cohesive attempt to mitigate anthropogenic climate change. © 2012 New York Academy of Sciences.

REDD+ emissions estimation and reporting: dealing with uncertainty

NASA Astrophysics Data System (ADS)

Pelletier, Johanne; Martin, Davy; Potvin, Catherine

2013-09-01

The United Nations Framework Convention on Climate Change (UNFCCC) defined the technical and financial modalities of policy approaches and incentives to reduce emissions from deforestation and forest degradation in developing countries (REDD+). Substantial technical challenges hinder precise and accurate estimation of forest-related emissions and removals, as well as the setting and assessment of reference levels. These challenges could limit country participation in REDD+, especially if REDD+ emission reductions were to meet quality standards required to serve as compliance grade offsets for developed countries’ emissions. Using Panama as a case study, we tested the matrix approach proposed by Bucki et al (2012 Environ. Res. Lett. 7 024005) to perform sensitivity and uncertainty analysis distinguishing between ‘modelling sources’ of uncertainty, which refers to model-specific parameters and assumptions, and ‘recurring sources’ of uncertainty, which refers to random and systematic errors in emission factors and activity data. The sensitivity analysis estimated differences in the resulting fluxes ranging from 4.2% to 262.2% of the reference emission level. The classification of fallows and the carbon stock increment or carbon accumulation of intact forest lands were the two key parameters showing the largest sensitivity. The highest error propagated using Monte Carlo simulations was caused by modelling sources of uncertainty, which calls for special attention to ensure consistency in REDD+ reporting which is essential for securing environmental integrity. Due to the role of these modelling sources of uncertainty, the adoption of strict rules for estimation and reporting would favour comparability of emission reductions between countries. We believe that a reduction of the bias in emission factors will arise, among other things, from a globally concerted effort to improve allometric equations for tropical forests. Public access to datasets and methodology used to evaluate reference level and emission reductions would strengthen the credibility of the system by promoting accountability and transparency. To secure conservativeness and deal with uncertainty, we consider the need for further research using real data available to developing countries to test the applicability of conservative discounts including the trend uncertainty and other possible options that would allow real incentives and stimulate improvements over time. Finally, we argue that REDD+ result-based actions assessed on the basis of a dashboard of performance indicators, not only in ‘tonnes CO2 equ. per year’ might provide a more holistic approach, at least until better accuracy and certainty of forest carbon stocks emission and removal estimates to support a REDD+ policy can be reached.

Effects of fine sediment on fish populations

Treesearch

Russ Thurow; Jack King

1991-01-01

To describe conditions in natural redds of steelhead trout (Oncorhynchus mykiss), we evaluated the particle size distribution of egg pockets, redd pits and tailspills, artificially constructed redds, and undisturbed substrate outside redds. Egg pockets were located in upper strata an average of 14.9 cm below the substrate surface. Egg pockets contained fewer fines (...

Spatial patterns of carbon, biodiversity, deforestation threat, and REDD+ projects in Indonesia.

PubMed

Murray, Josil P; Grenyer, Richard; Wunder, Sven; Raes, Niels; Jones, Julia P G

2015-10-01

There are concerns that Reduced Emissions from Deforestation and forest Degradation (REDD+) may fail to deliver potential biodiversity cobenefits if it is focused on high carbon areas. We explored the spatial overlaps between carbon stocks, biodiversity, projected deforestation threats, and the location of REDD+ projects in Indonesia, a tropical country at the forefront of REDD+ development. For biodiversity, we assembled data on the distribution of terrestrial vertebrates (ranges of amphibians, mammals, birds, reptiles) and plants (species distribution models for 8 families). We then investigated congruence between different measures of biodiversity richness and carbon stocks at the national and subnational scales. Finally, we mapped active REDD+ projects and investigated the carbon density and potential biodiversity richness and modeled deforestation pressures within these forests relative to protected areas and unprotected forests. There was little internal overlap among the different hotspots (richest 10% of cells) of species richness. There was also no consistent spatial congruence between carbon stocks and the biodiversity measures: a weak negative correlation at the national scale masked highly variable and nonlinear relationships island by island. Current REDD+ projects were preferentially located in areas with higher total species richness and threatened species richness but lower carbon densities than protected areas and unprotected forests. Although a quarter of the total area of these REDD+ projects is under relatively high deforestation pressure, the majority of the REDD+ area is not. In Indonesia at least, first-generation REDD+ projects are located where they are likely to deliver biodiversity benefits. However, if REDD+ is to deliver additional gains for climate and biodiversity, projects will need to focus on forests with the highest threat to deforestation, which will have cost implications for future REDD+ implementation. © 2015 The Authors. Conservation Biology published by Wiley Periodicals, Inc., on behalf of Society for Conservation Biology.

Salmon redd identification using environmental DNA (eDNA)

USGS Publications Warehouse

Pilliod, David S.; Laramie, Matthew B.

2016-06-10

IntroductionThe purpose of this project was to develop a technique to use environmental DNA (eDNA) to distinguish between redds made by Chinook salmon (Oncorhynchus tshawytscha) and redds made by Coho salmon (O. kisutch) and to distinguish utilized redds from test/abandoned redds or scours that have the appearance of redds. The project had two phases:Phase 1. Develop, test, and optimize a molecular assay for detecting and identifying Coho salmon DNA and differentiating it from Chinook salmon DNA.Phase 2. Demonstrate the efficacy of the technique.Collect and preserve water samples from the interstitial spaces of 10 known redds (as identified by expert observers) of each species and 10 gravel patches that do not include a redd of either species.Collect control samples from the water column adjacent to each redd to establish background eDNA levels.Analyze the samples using the developed molecular assays for Coho salmon (phase I) and Chinook salmon (Laramie and others, 2015).Evaluate whether samples collected from Chinook and Coho redds have significantly higher levels of eDNA of the respective species than background levels (that is, from gravel, water column).Evaluate whether samples collected from the interstitial spaces of gravel patches that are not redds are similar to background eDNA levels.The Sandy River is a large tributary of the Columbia River. The Sandy River meets the Columbia River approximately 23 km upstream of Portland, Oregon. The Sandy River Basin provides overlapping spawning habitat for both Chinook and Coho salmon.Samples provided by Portland Water Bureau for analysis were collected from the Bull Run River, Sixes Creek, Still Creek, Arrah Wanna Side Channel, and Side Channel 18.

Salmon Spawning Effects on Streambed Stability

NASA Astrophysics Data System (ADS)

Buxton, T. H.; Buffington, J. M.; Yager, E.; Fremier, A. K.; Hassan, M. A.

2014-12-01

Female salmon build nests ("redds") in streambeds to protect their eggs from predation and damage by bed scour. During spawning, streambed material is mixed, fine sediment is winnowed downstream, and sediment is moved into a tailspill mound resembling the shape of a dune. Redd surfaces are coarser and better sorted than unspawned beds, which is thought to increase redd stability because larger grains are heavier and harder to move and sorting leads to higher friction angles for grain mobility. However, spawning also loosens sediment and creates topography that accelerates flow, both of which may increase particle mobility. We address factors controlling the relative stability of redds and unspawned beds using simulated salmon redds and water worked ("unspawned") beds composed of mixed-grain surfaces in a laboratory flume. Results show that simulated spawning lowered packing resistance to particle mobility on redds by an average of 32-39% compared to unspawned beds. Reductions in packing were sufficient to counter the higher inherent stability of relatively coarse, well sorted grains on redds, overall reducing critical shear stress by 8-20% relative to unspawned beds. In addition, boundary shear stress was 13-41% higher on redds due to flow convergence over the tailspill structure. Finally, redd instability relative to unspawned beds was observed in visual measurements of grain mobility, where bed-averaged shear stress was 22% lower at incipient motion and 29% lower at the discharge that mobilized all grain sizes on redds. Results of these complementary observations, along with sediment mass transport rates being nearly five times higher on a redd than an unspawned bed, indicate that redds are unstable compared to unspawned beds. Given these findings, further research is needed to investigate linkages between spawning disturbance and streambed mobility that may affect salmon reproduction in streams, and to assess whether a certain level of bed disturbance from spawning is required to restore ecosystem functions in streams with threatened populations of salmon.

Scour of chinook salmon redds on suction dredge tailings

Treesearch

Bret C. Harvey; Thomas E. Lisle

1999-01-01

Abstract - We measured scour of the redds of chinook salmon Oncorhynchus tshawytscha on dredge tailings and natural substrates in three tributaries of the Klamath River, California. We measured maximum scour with scour chains and net scour by surveying before and after high winter flows. Scour of chinook salmon redds located on dredge tailings exceeded scour of redds...

Combining satellite, aerial and ground measurements to assess forest carbon stocks in Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Beaumont, Benjamin; Bouvy, Alban; Stephenne, Nathalie; Mathoux, Pierre; Bastin, Jean-François; Baudot, Yves; Akkermans, Tom

2015-04-01

Monitoring tropical forest carbon stocks changes has been a rising topic in the recent years as a result of REDD+ mechanisms negotiations. Such monitoring will be mandatory for each project/country willing to benefit from these financial incentives in the future. Aerial and satellite remote sensing technologies offer cost advantages in implementing large scale forest inventories. Despite the recent progress made in the use of airborne LiDAR for carbon stocks estimation, no widely operational and cost effective method has yet been delivered for central Africa forest monitoring. Within the Maï Ndombe region of Democratic Republic of Congo, the EO4REDD project develops a method combining satellite, aerial and ground measurements. This combination is done in three steps: [1] mapping and quantifying forest cover changes using an object-based semi-automatic change detection (deforestation and forest degradation) methodology based on very high resolution satellite imagery (RapidEye), [2] developing an allometric linear model for above ground biomass measurements based on dendrometric parameters (tree crown areas and heights) extracted from airborne stereoscopic image pairs and calibrated using ground measurements of individual trees on a data set of 18 one hectare plots and [3] relating these two products to assess carbon stocks changes at a regional scale. Given the high accuracies obtained in [1] (> 80% for deforestation and 77% for forest degradation) and the suitable, but still to be improved with a larger calibrating sample, model (R² of 0.7) obtained in [2], EO4REDD products can be seen as a valid and replicable option for carbon stocks monitoring in tropical forests. Further improvements are planned to strengthen the cost effectiveness value and the REDD+ suitability in the second phase of EO4REDD. This second phase will include [A] specific model developments per forest type; [B] measurements of afforestation, reforestation and natural regeneration processes and [C] study of Sentinel satellite data series potential use.

Spatial patterns of carbon, biodiversity, deforestation threat, and REDD+ projects in Indonesia

PubMed Central

Murray, Josil P; Grenyer, Richard; Wunder, Sven; Raes, Niels; Jones, Julia PG

2015-01-01

There are concerns that Reduced Emissions from Deforestation and forest Degradation (REDD+) may fail to deliver potential biodiversity cobenefits if it is focused on high carbon areas. We explored the spatial overlaps between carbon stocks, biodiversity, projected deforestation threats, and the location of REDD+ projects in Indonesia, a tropical country at the forefront of REDD+ development. For biodiversity, we assembled data on the distribution of terrestrial vertebrates (ranges of amphibians, mammals, birds, reptiles) and plants (species distribution models for 8 families). We then investigated congruence between different measures of biodiversity richness and carbon stocks at the national and subnational scales. Finally, we mapped active REDD+ projects and investigated the carbon density and potential biodiversity richness and modeled deforestation pressures within these forests relative to protected areas and unprotected forests. There was little internal overlap among the different hotspots (richest 10% of cells) of species richness. There was also no consistent spatial congruence between carbon stocks and the biodiversity measures: a weak negative correlation at the national scale masked highly variable and nonlinear relationships island by island. Current REDD+ projects were preferentially located in areas with higher total species richness and threatened species richness but lower carbon densities than protected areas and unprotected forests. Although a quarter of the total area of these REDD+ projects is under relatively high deforestation pressure, the majority of the REDD+ area is not. In Indonesia at least, first-generation REDD+ projects are located where they are likely to deliver biodiversity benefits. However, if REDD+ is to deliver additional gains for climate and biodiversity, projects will need to focus on forests with the highest threat to deforestation, which will have cost implications for future REDD+ implementation. Los Patrones Espaciales del Carbono, la Biodiversidad, la Amenaza de Deforestación y los Proyectos REDD+ en Indonesia Resumen Actualmente hay preocupación por que las Emisiones Reducidas de la Deforestación y Degradación del Bosque (REDD+, en inglés) puedan fallar en la entrega de co–beneficios potenciales de la biodiversidad si se enfocan en áreas de alto carbono. Exploramos los traslapes espaciales entre los stocks de carbono, la biodiversidad, las amenazas proyectadas de deforestación y la ubicación de proyectos REDD+ en Indonesia, un país tropical a la vanguardia del desarrollo REDD+. Para la biodiversidad, reunimos datos sobre la distribución de vertebrados terrestres (hábitats de anfibios, mamíferos, aves y reptiles) y plantas (modelos de distribución de especies para ocho familia). Después investigamos la congruencia entre las diferentes medidas de la riqueza de la biodiversidad y los stocks de carbono en la escala nacional y sub–nacional. Finalmente mapeamos proyectos REDD+ activos e investigamos la densidad de carbono y la riqueza potencial de la biodiversidad y modelamos presiones de deforestación dentro de estos bosques en relación con áreas protegidas y no protegidas. Hubo poco traslape interno entre los diferentes hotspots (el 10% más rico de las celdas) de riqueza de especies. Tampoco hubo congruencia espacial consecuente entre los stocks de carbono y las medidas de la biodiversidad: una correlación negativa débil en la escala nacional enmascaró las relaciones altamente variables y no-lineales isla por isla. Los proyectos REDD+ actuales estuvieron ubicados preferencialmente en áreas con una riqueza total de especies y con una riqueza de especies amenazadas más altas pero con densidades de carbono más bajas que en las áreas protegidas y los bosques sin protección. Aunque un cuarto del área total de estos proyectos REDD+ está bajo una presión de deforestación relativamente alta, la mayoría del área REDD+ no lo está. Por lo menos en Indonesia, los proyectos REDD+ de primera generación están ubicados en donde tengan probabilidad de entregar beneficios para la biodiversidad. Sin embargo, si se espera que REDD+ entregue beneficios adicionales para el clima y la biodiversidad, los proyectos necesitarán enfocarse en los bosques con la mayor amenaza de deforestación, lo que tendrá implicaciones de costo para la implementación futura de REDD+. PMID:25864538

National Satellite Forest Monitoring systems for REDD+

NASA Astrophysics Data System (ADS)

Jonckheere, I. G.

2012-12-01

Reducing Emissions from Deforestation and Forest Degradation (REDD) is an effort to create a financial value for the carbon stored in forests, offering incentives for developing countries to reduce emissions from forested lands and invest in low-carbon paths to sustainable development. "REDD+" goes beyond deforestation and forest degradation, and includes the role of conservation, sustainable management of forests and enhancement of forest carbon stocks. In the framework of getting countries ready for REDD+, the UN-REDD Programme assists developing countries to prepare and implement national REDD+ strategies. For the monitoring, reporting and verification, FAO supports the countries to develop national satellite forest monitoring systems that allow for credible measurement, reporting and verification (MRV) of REDD+ activities. These are among the most critical elements for the successful implementation of any REDD+ mechanism. The UN-REDD Programme through a joint effort of FAO and Brazil's National Space Agency, INPE, is supporting countries to develop cost- effective, robust and compatible national monitoring and MRV systems, providing tools, methodologies, training and knowledge sharing that help countries to strengthen their technical and institutional capacity for effective MRV systems. To develop strong nationally-owned forest monitoring systems, technical and institutional capacity building is key. The UN-REDD Programme, through FAO, has taken on intensive training together with INPE, and has provided technical help and assistance for in-country training and implementation for national satellite forest monitoring. The goal of the support to UN-REDD pilot countries in this capacity building effort is the training of technical forest people and IT persons from interested REDD+ countries, and to set- up the national satellite forest monitoring systems. The Brazilian forest monitoring system, TerraAmazon, which is used as a basis for this initiative, allows countries to adapt it to country needs and the training on the TerraAmazon system is a tool to enhance existing capacity on carbon monitoring systems. The support with the National Forest Monitoring System will allow these countries to follow all actions related to the implementation of its national REDD+ policies and measures. The monitoring system will work as a platform to obtain information on their REDD+ results and actions, related directly or indirectly to national REDD+ strategies and may also include actions unrelated to carbon assessment, such as forest law enforcement. With the technical assistance of FAO, INPE and other stakeholders, the countries will set up an autonomous operational forest monitoring system. An initial version and the methodologies of the system for DRC and PNG has been launched in Durban, South Africa during COP 17 and in 2012 Paraguay, Viet Nam and Zambia will be launched in Doha, Qatar at COP 18. The access to high-quality satellite data for these countries is crucial for the set-up.

A bottom-up approach to estimating cost elements of REDD+ pilot projects in Tanzania

PubMed Central

2012-01-01

Background Several previous global REDD+ cost studies have been conducted, demonstrating that payments for maintaining forest carbon stocks have significant potential to be a cost-effective mechanism for climate change mitigation. These studies have mostly followed highly aggregated top-down approaches without estimating the full range of REDD+ costs elements, thus underestimating the actual costs of REDD+. Based on three REDD+ pilot projects in Tanzania, representing an area of 327,825 ha, this study explicitly adopts a bottom-up approach to data assessment. By estimating opportunity, implementation, transaction and institutional costs of REDD+ we develop a practical and replicable methodological framework to consistently assess REDD+ cost elements. Results Based on historical land use change patterns, current region-specific economic conditions and carbon stocks, project-specific opportunity costs ranged between US$ -7.8 and 28.8 tCOxxxx for deforestation and forest degradation drivers such as agriculture, fuel wood production, unsustainable timber extraction and pasture expansion. The mean opportunity costs for the three projects ranged between US$ 10.1 – 12.5 tCO2. Implementation costs comprised between 89% and 95% of total project costs (excluding opportunity costs) ranging between US$ 4.5 - 12.2 tCO2 for a period of 30 years. Transaction costs for measurement, reporting, verification (MRV), and other carbon market related compliance costs comprised a minor share, between US$ 0.21 - 1.46 tCO2. Similarly, the institutional costs comprised around 1% of total REDD+ costs in a range of US$ 0.06 – 0.11 tCO2. Conclusions The use of bottom-up approaches to estimate REDD+ economics by considering regional variations in economic conditions and carbon stocks has been shown to be an appropriate approach to provide policy and decision-makers robust economic information on REDD+. The assessment of opportunity costs is a crucial first step to provide information on the economic baseline situation of deforestation and forest degradation agents and on the economic incentives required to halt unsustainable land use. Since performance based REDD+ carbon payments decrease over time (as deforestation rates drop and for each saved ha of forest payments occur once), investments in REDD+ implementation have a crucial role in triggering sustainable land use systems by investing in the underlying assets and the generation of sustainable revenue streams to compensate for opportunity costs of land use change. With a potential increase in the land value due to effective REDD+ investments, expenditures in an enabling institutional environment for REDD+ policies are crucial to avoid higher deforestation pressure on natural forests. PMID:22877419

The regulated in development and DNA damage response 2 (REDD2) gene mediates human monocyte cell death through a reduction in thioredoxin-1 expression.

PubMed

Imen, Jguirim-Souissi; Billiet, Ludivine; Cuaz-Pérolin, Clarisse; Michaud, Nadège; Rouis, Mustapha

2009-05-15

In a previous study, we identified the regulated in development and DNA damage response 2 (REDD2) gene as a highly expressed gene in human atherosclerotic lesions in comparison to normal artery, as well as in cultured human macrophages, and showed its implication in oxidized low-density lipoprotein (LDL)-induced macrophage death sensitivity. In this article, we attempt to identify the mechanism by which REDD2 induces such a phenomenon. Transient transfection of U-937 monocytic cells with a pCI.CMV.REDD2 expression vector increased by approximately twofold the mRNA levels of REDD2 in comparison to control cells transfected with pCI.CMV.GFP. Reactive oxygen species (ROS) production was significantly induced in REDD2-transfected cells compared with control cells (157+/-48 and 100+/-8 arbitrary units/mg cell protein, respectively; p<0.05). Moreover, a significant increase in parameters known to reflect the oxidative modifications of LDL was observed. Among enzymes involved in ROS production or degradation, we found a specific reduction in thioredoxin-1 (Trx-1) mRNA ( approximately 52+/-7% decrease, p<0.01 vs control cells) and protein ( approximately 60+/-4% decrease, p<0.001 vs control cells) levels in cells overexpressing REDD2 in comparison to control cells. In contrast, transfection of U-937 cells with siRNA against REDD2 decreased the mRNA levels of REDD2 by approximately 60% and increased Trx-1 mRNA and protein levels. Moreover, we observed no or a moderate increase in Bax (proapoptotic) and a significant decrease in Bcl2 (antiapoptotic) gene expression in cells that overexpress REDD2 compared to control cells. In addition, we showed that Trx-1 mRNA and protein levels were increased at low H(2)O(2) doses and decreased at higher doses. Interestingly, macrophages isolated from human atherosclerotic lesions differentially express REDD2 and Trx-1. Indeed, in certain patients, levels of REDD2 mRNA were low and those of Trx-1 mRNA were high. In contrast, in other patients, levels of REDD2 were high and levels of Trx-1 mRNA were low.

Fine-scale characteristics of fluvial bull trout redds and adjacent sites in Rapid River, Idaho, 1993-2007

Treesearch

John W. Guzevich; Russell F. Thurow

2017-01-01

From 1993 to 2007, we used single pass, September surveys to locate and measure fluvial bull trout (Salvelinus confluentus) redds in Rapid River, Idaho. Here we describe substrate sizes, redd dimensions, and water depths, velocities, and temperatures within and adjacent to 337 redds. Most (79%) spawning sites had fewer than 20% surface fines (< 2 mm) and mean,...

REDD1 induction regulates the skeletal muscle gene expression signature following acute aerobic exercise.

PubMed

Gordon, Bradley S; Steiner, Jennifer L; Rossetti, Michael L; Qiao, Shuxi; Ellisen, Leif W; Govindarajan, Subramaniam S; Eroshkin, Alexey M; Williamson, David L; Coen, Paul M

2017-12-01

The metabolic stress placed on skeletal muscle by aerobic exercise promotes acute and long-term health benefits in part through changes in gene expression. However, the transducers that mediate altered gene expression signatures have not been completely elucidated. Regulated in development and DNA damage 1 (REDD1) is a stress-induced protein whose expression is transiently increased in skeletal muscle following acute aerobic exercise. However, the role of this induction remains unclear. Because REDD1 altered gene expression in other model systems, we sought to determine whether REDD1 induction following acute exercise altered the gene expression signature in muscle. To do this, wild-type and REDD1-null mice were randomized to remain sedentary or undergo a bout of acute treadmill exercise. Exercised mice recovered for 1, 3, or 6 h before euthanization. Acute exercise induced a transient increase in REDD1 protein expression within the plantaris only at 1 h postexercise, and the induction occurred in both cytosolic and nuclear fractions. At this time point, global changes in gene expression were surveyed using microarray. REDD1 induction was required for the exercise-induced change in expression of 24 genes. Validation by RT-PCR confirmed that the exercise-mediated changes in genes related to exercise capacity, muscle protein metabolism, neuromuscular junction remodeling, and Metformin action were negated in REDD1-null mice. Finally, the exercise-mediated induction of REDD1 was partially dependent upon glucocorticoid receptor activation. In all, these data show that REDD1 induction regulates the exercise-mediated change in a distinct set of genes within skeletal muscle. Copyright © 2017 the American Physiological Society.

Exploring the use of environmental DNA to determine the species of salmon redds

USGS Publications Warehouse

Strobel, Burke; Laramie, Matthew; Pilliod, David S.

2017-01-01

Annual redd counts are used to monitor the status and trends of salmonid populations, but methods to easily and reliably determine which of sympatric species made specific redds are lacking. We explored whether environmental DNA (eDNA) analysis might prove useful for determining the species of salmon redds. We collected eDNA samples from the interstitial spaces of redds of Chinook Salmon Oncorhynchus tshawytscha, redds of Coho Salmon O. kisutch, and areas of undisturbed gravel (n = 10, each), as well as from the water column adjacent to each of those sites in the Sandy River basin, Oregon, USA during the fall of 2013. The concentrations of Chinook and Coho eDNA were quantified within each sample using real-time PCR. The water in the interstitial spaces of redds contained significantly higher eDNA concentrations of the species that made the redd than (1) the other species and (2) the adjacent water column. In contrast, neither Chinook nor Coho eDNA was significantly more concentrated than the other in the water from the interstitial spaces of undisturbed gravel. The interstitial water of undisturbed gravel contained significantly higher eDNA concentrations of Coho than the adjacent water column. In contrast, Chinook eDNA concentration was similar in the interstitial water of undisturbed gravel and the adjacent water column. Both species’ redds had significantly higher concentrations of their respective species’ eDNA than did undisturbed gravel, but conclusions were confounded by differences in the timing and locations of sampling. This initial investigation highlights the potential value and some of the complexity of using eDNA analysis to indicate redd species.

REDD+ on the rocks? Conflict Over Forest and Politics of Justice in Vietnam.

PubMed

Sikor, Thomas; Cầm, Hoàng

In Vietnam, villagers involved in a REDD+ (reduced emissions from deforestation and forest degradation) pilot protect areas with rocks which have barely a tree on them. The apparent paradox indicates how actual practices differ from general ideas about REDD+ due to ongoing conflict over forest, and how contestations over the meaning of justice are a core element in negotiations over REDD+. We explore these politics of justice by examining how the actors involved in the REDD+ pilot negotiate the particular subjects, dimensions, and authority of justice considered relevant, and show how politics of justice are implicit to practical decisions in project implementation. Contestations over the meaning of justice are an important element in the practices and processes constituting REDD+ at global, national and local levels, challenging uniform definitions of forest justice and how forests ought to be managed.

Deepwater Spawning of Fall Chinook Salmon (Oncorhynchus tshawtscha) Near Ives and Pierce Island of the Columbia River, 2003-2004 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mueller, Robert

2004-10-01

Pacific Northwest National Laboratory conducted video-based boat surveys in fall 2003 to identify spawning areas for fall Chinook salmon (Oncorhynchus tshawytscha) in deep water (>1 m) downstream of Bonneville Dam. This report documents the number and extent of Chinook salmon spawning near Ives and Pierce islands of the Columbia River, and is the fifth in a series of reports prepared since 1999. The primary objective of this study was to find deepwater spawning locations of fall Chinook salmon in the main Columbia River channel, collect additional data on physical habitat parameters at spawning sites, and provide estimates of adult spawnersmore » in the surveyed area. The secondary objective was to document the occurrence of any chum salmon (O. keta) redds in the deeper sections near below Hamilton Creek. Results from the 2003 study show a continuing trend upward in the number of fall Chinook salmon redds found within the survey zones. The number of fall Chinook redds found in the Ives Pierce Island complex (river km 228.5) has increased by a factor of five since the surveys began in 1999. The total number of redds found during 2003 was 336, which compares to 192 in 2002, 43 in 2001, 76 in 2000, and 64 in 1999. The redds encompassed an area of 13.7 ha occurring adjacent to the lower part of Ives Island and Pierce Island. Peak spawning activity, based on redd counts and live fish seen near redds, was on or near November 24, 2003. An expanded redd count based on percentage of video coverage in the primary and secondary search zones was 3,218 fall Chinook salmon redds in water exceeding 1 m deep and flowing at about 125 kcfs. Fall Chinook salmon redds were found at water depths from 1.07 to 7.6 m and were constructed predominantly of medium cobbles ranging from 7.6 to 15.2 cm in diameter. Two chum salmon redds were found in a small location downstream from Hamilton Creek in water depths of approximately 1 m. No salmon redds were found in other areas searched, including near Woodward, Tanner, and McCord creeks.« less

Altered nutrient response of mTORC1 as a result of changes in REDD1 expression: effect of obesity vs. REDD1 deficiency

PubMed Central

Li, Zhuyun; Tuder, Rubin M.; Feinstein, Elena; Kimball, Scot R.; Dungan, Cory M.

2014-01-01

Although aberrant mTORC1 signaling has been well established in models of obesity, little is known about its repressor, REDD1. Therefore, the initial goal of this study was to determine the role of REDD1 on mTORC1 in obese skeletal muscle. REDD1 expression (protein and message) and mTORC1 signaling (S6K1, 4E-BP1, raptor-mTOR association, Rheb GTP) were examined in lean vs. ob/ob and REDD1 wild-type (WT) vs. knockout (KO) mice, under conditions of altered nutrient intake [fasted and fed or diet-induced obesity (10% vs. 60% fat diet)]. Despite higher (P < 0.05) S6K1 and 4E-BP1 phosphorylation, two models of obesity (ob/ob and diet-induced) displayed elevated (P < 0.05) skeletal muscle REDD1 expression compared with lean or low-fat-fed mouse muscle under fasted conditions. The ob/ob mice displayed elevated REDD1 expression (P < 0.05) that coincided with aberrant mTORC1 signaling (hyperactive S6K1, low raptor-mTOR binding, elevated Rheb GTP; P < 0.05) under fasted conditions, compared with the lean, which persisted in a dysregulated fashion under fed conditions. REDD1 KO mice gained limited body mass on a high-fat diet, although S6K1 and 4E-BP1 phosphorylation remained elevated (P < 0.05) in both the low-fat and high-fat-fed KO vs. WT mice. Similarly, the REDD1 KO mouse muscle displayed blunted mTORC1 signaling responses (S6K1 and 4E-BP1, raptor-mTOR binding) and circulating insulin under fed conditions vs. the robust responses (P < 0.05) in the WT fed mouse muscle. These studies suggest that REDD1 in skeletal muscle may serve to limit hyperactive mTORC1, which promotes aberrant mTORC1 signaling responses during altered nutrient states. PMID:24876363

Assessing the Claims of Participatory Measurement, Reporting and Verification (PMRV) in Achieving REDD+ Outcomes: A Systematic Review

PubMed Central

Hawthorne, Sandra; Boissière, Manuel; Felker, Mary Elizabeth; Atmadja, Stibniati

2016-01-01

Participation of local communities in the Measurement, Reporting and Verification (MRV) of forest changes has been promoted as a strategy that lowers the cost of MRV and increases their engagement with REDD+. This systematic review of literature assessed the claims of participatory MRV (PMRV) in achieving REDD+ outcomes. We identified 29 PMRV publications that consisted of 20 peer-reviewed and 9 non peer-reviewed publications, with 14 publications being empirically based studies. The evidence supporting PMRV claims was categorized into empirical finding, citation or assumption. Our analysis of the empirical studies showed that PMRV projects were conducted in 17 countries in three tropical continents and across various forest and land tenure types. Most of these projects tested the feasibility of participatory measurement or monitoring, which limited the participation of local communities to data gathering. PMRV claims of providing accurate local biomass measurements and lowering MRV cost were well-supported with empirical evidence. Claims that PMRV supports REDD+ social outcomes that affect local communities directly, such as increased environmental awareness and equity in benefit sharing, were supported with less empirical evidence than REDD+ technical outcomes. This may be due to the difficulties in measuring social outcomes and the slow progress in the development and implementation of REDD+ components outside of experimental research contexts. Although lessons from other monitoring contexts have been used to support PMRV claims, they are only applicable when the enabling conditions can be replicated in REDD+ contexts. There is a need for more empirical evidence to support PMRV claims on achieving REDD+ social outcomes, which may be addressed with more opportunities and rigorous methods for assessing REDD+ social outcomes. Integrating future PMRV studies into local REDD+ implementations may help create those opportunities, while increasing the participation of local communities as local REDD+ stakeholders. Further development and testing of participatory reporting framework are required to integrate PMRV data with the national database. Publication of empirical PMRV studies is encouraged to guide when, where and how PMRV should be implemented. PMID:27812110

Integrating remotely sensed fires for predicting deforestation for REDD.

PubMed

Armenteras, Dolors; Gibbes, Cerian; Anaya, Jesús A; Dávalos, Liliana M

2017-06-01

Fire is an important tool in tropical forest management, as it alters forest composition, structure, and the carbon budget. The United Nations program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to sustainably manage forests, as well as to conserve and enhance their carbon stocks. Despite the crucial role of fire management, decision-making on REDD+ interventions fails to systematically include fires. Here, we address this critical knowledge gap in two ways. First, we review REDD+ projects and programs to assess the inclusion of fires in monitoring, reporting, and verification (MRV) systems. Second, we model the relationship between fire and forest for a pilot site in Colombia using near-real-time (NRT) fire monitoring data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The literature review revealed fire remains to be incorporated as a key component of MRV systems. Spatially explicit modeling of land use change showed the probability of deforestation declined sharply with increasing distance to the nearest fire the preceding year (multi-year model area under the curve [AUC] 0.82). Deforestation predictions based on the model performed better than the official REDD early-warning system. The model AUC for 2013 and 2014 was 0.81, compared to 0.52 for the early-warning system in 2013 and 0.68 in 2014. This demonstrates NRT fire monitoring is a powerful tool to predict sites of forest deforestation. Applying new, publicly available, and open-access NRT fire data should be an essential element of early-warning systems to detect and prevent deforestation. Our results provide tools for improving both the current MRV systems, and the deforestation early-warning system in Colombia. © 2017 by the Ecological Society of America.

Loss of REDD1 augments the rate of the overload-induced increase in muscle mass

PubMed Central

Liu, Chang; Steiner, Jennifer L.; Nader, Gustavo A.; Jefferson, Leonard S.; Kimball, Scot R.

2016-01-01

The overload-induced increase in muscle mass is accompanied by protein accretion; however, the initiating events are poorly understood. Regulated in Development and DNA Damage 1 (REDD1), a repressor of the mechanistic target of rapamycin in complex 1 (mTORC1), blunts the elevation in protein synthesis induced by acute muscle contractions. Therefore, this study was designed to determine whether REDD1 alters the rate of the overload-induced increase in muscle mass. Wild-type (WT) and REDD1-null mice underwent unilateral functional overload (OV) of the plantaris, while the contralateral sham leg served as a control. After 3 and 5 days of OV, puromycin incorporation was used as a measurement of protein synthesis. The percent increase in plantaris wet weight and protein content was greater in REDD1-null mice after 3, 5, and 10 days OV. The overload-stimulated rate of protein synthesis in the plantaris was similar between genotypes after 3 days OV, but translational capacity was lower in REDD1-null mice, indicating elevated translational efficiency. This was likely due to elevated absolute mTORC1 signaling [phosphorylation of p70S6K1 (Thr-389) and 4E-BP1 (Ser-65)]. By 5 days of OV, the rate of protein synthesis in REDD1-null mice was lower than WT mice with no difference in absolute mTORC1 signaling. Additionally, markers of autophagy (LC3II/I ratio and p62 protein) were decreased to a greater absolute extent after 3 days OV in REDD1-null mice. These data suggest that loss of REDD1 augments the rate of the OV-induced increase in muscle mass by altering multiple protein balance pathways. PMID:27465734

Can REDD+ Help the Conservation of Restricted-Range Island Species? Insights from the Endemism Hotspot of São Tomé

PubMed Central

de Lima, Ricardo Faustino; Olmos, Fábio; Dallimer, Martin; Atkinson, Philip W.; Barlow, Jos

2013-01-01

REDD+ aims to offset greenhouse gas emissions through “Reduced Emissions from Deforestation and forest Degradation”. Some authors suggest that REDD+ can bring additional benefits for biodiversity, namely for the conservation of extinction-prone restricted-range species. Here, we assess this claim, using São Tomé Island (Democratic Republic of São Tomé and Príncipe) as a case study. We quantified the abundance of bird and tree species, and calculated the aboveground carbon stocks across a gradient of land-use intensity. We found a strong spatial congruence between carbon and the presence and abundance of endemic species, supporting the potential of REDD+ to protect these taxa. We then assessed if REDD+ could help protect the forests of São Tomé and Príncipe. To do so, we used OSIRIS simulations to predict country-level deforestation under two different REDD+ designs. These simulations showed that REDD+ could promote the loss of forests in São Tomé and Príncipe through leakage. This happened even when additional payments for biodiversity were included in the simulations, and despite São Tomé and Príncipe having the fourth highest carbon stocks per land area and the second highest biodiversity values according to the OSIRIS database. These results show weaknesses of OSIRIS as a planning tool, and demonstrate that the benefits that REDD+ might bring for biodiversity are strongly dependent on its careful implementation. We recommend that payment for ecosystem services programmes such as REDD+ develop safeguards to ensure that biodiversity co-benefits are met and perverse outcomes are avoided across all tropical countries. In particular, we advise specific safeguards regarding the conservation of extinction-prone groups, such as island restricted-range species. PMID:24066109

The start-up phase of the national satellite forest monitoring systems for DRC and PNG: a joint venture between FAO and INPE

NASA Astrophysics Data System (ADS)

Jonckheere, I. G.; FAO UN-REDD Team Forestry Department

2011-12-01

Reducing Emissions from Deforestation and Forest Degradation (REDD) is an effort to create a financial value for the carbon stored in forests, offering incentives for developing countries to reduce emissions from forested lands and invest in low-carbon paths to sustainable development. "REDD+" goes beyond deforestation and forest degradation, and includes the role of conservation, sustainable management of forests and enhancement of forest carbon stocks. In the framework of getting countries ready for REDD+, the UN-REDD Programme, a partnership between UNEP, FAO and UNDP, assists developing countries to prepare and implement national REDD+ strategies. Designed collaboratively by a broad range of stakeholders, national UN-REDD Programmes are informed by the technical expertise of FAO, UNDP and UNEP. For the monitoring, reporting and verification, FAO supports the countries to develop satellite forest monitoring systems that allow for credible measurement, reporting and verification (MRV)of REDD+ activities. These are among the most critical elements for the successful implementation of any REDD+ mechanism, also following the COP 16 decisions in Cancun last year. The UN-REDD Programme through a joint effort of FAO and Brazil's National Space Agency, INPE, is supporting countries to develop cost-effective, robust and compatible national monitoring and MRV systems, providing tools, methodologies, training and knowledge sharing that help countries to strengthen their technical and institutional capacity for effective MRV systems. To develop strong nationally-owned forest monitoring systems, technical and institutional capacity building is key. The UN-REDD Programme, through FAO, has taken on intensive training together with INPE, and has provided technical help and assistance for in-country training and implementation for national satellite forest monitoring. The goal of the start-up phase for DRC and Papua New Guinea (PNG) in this capacity building effort is the training of technical forest people and IT persons from these two interested REDD+ countries, and to set-up the national satellite forest monitoring systems. The Brazilian forest monitoring system, TerraAmazon, which is used as a basis for this initiative, allows countries to adapt it to country needs and the training on the TerraAmazon system is a tool to enhance existing capacity on carbon monitoring systems. The start-up phase of the National Forest Monitoring System for DRC and PNG will allow these countries to follow all actions related to the implementation of its national REDD+ policies and measures. The monitoring system will work as a platform to obtain information on their REDD+ results and actions, related directly or indirectly to national REDD+ strategies and may also include actions unrelated to carbon assessment, such as forest law enforcement. With the technical assistance of FAO, INPE and other stakeholders, the countries will set up an autonomous operational forest monitoring system. An initial version and the methodologies of these syste,s will be launched in Durban, South Africa during COP 17 and is presented here.

Reproductive Potential of Salmon Spawning Substrates Inferred from Grain Size and Fish Length

NASA Astrophysics Data System (ADS)

Riebe, C. S.; Sklar, L. S.; Overstreet, B. T.; Wooster, J. K.; Bellugi, D. G.

2014-12-01

The river restoration industry spends millions of dollars every year on improving salmon spawning in riverbeds where sediment is too big for fish to move and thus use during redd building. However, few studies have addressed the question of how big is too big in salmon spawning substrates. Hence managers have had little quantitative basis for gauging the amount of spawning habitat in coarse-bedded rivers. Moreover, the scientific framework has remained weak for restoration projects that seek to improve spawning conditions. To overcome these limitations, we developed a physically based, field-calibrated model for the fraction of the bed that is fine-grained enough to support spawning by fish of a given size. Model inputs are fish length and easy-to-measure indices of bed-surface grain size. Model outputs include the number of redds and eggs the substrate can accommodate when flow depth, temperature, and other environmental factors are not limiting. The mechanistic framework of the model captures the biophysical limits on sediment movement and the space limitations on redd building and egg deposition in riverbeds. We explored the parameter space of the model and found a previously unrecognized tradeoff in salmon size: bigger fish can move larger sediment and thus use more riverbed area for spawning; they also tend to have higher fecundity, and so can deposit more eggs per redd; however, because redd area increases with fish length, the number of eggs a substrate can accommodate is highest for moderate-sized fish. One implication of this tradeoff is that differences in grain size may help regulate river-to-river differences in salmon size. Thus, our model suggests that population diversity and, by extension, species resilience are linked to lithologic, geomorphic, and climatic factors that determine grain size in rivers. We cast the model into easy-to-use look-up tables, charts, and computer applications, including a JavaScript app that works on tablets and mobile phones. We explain how these tools can be used in a new, mechanistic approach to assessing spawning substrates and optimizing gravel augmentation projects in coarse-bedded rivers.

Characteristics of fall chum salmon spawning habitat on a mainstem river in Interior Alaska

USGS Publications Warehouse

Burril, Sean E.; Zimmerman, Christian E.; Finn, James E.

2010-01-01

Chum salmon (Oncorhynchus keta) are the most abundant species of salmon spawning in the Yukon River drainage system, and they support important personal use, subsistence, and commercial fisheries. Chum salmon returning to the Tanana River in Interior Alaska are a significant contribution to the overall abundance of Yukon River chum salmon and an improved understanding of habitat use is needed to improve conservation of this important resource. We characterized spawning habitat of chum salmon using the mainstem Tanana River as part of a larger study to document spawning distributions and habitat use in this river. Areas of spawning activity were located using radiotelemetry and aerial helicopter surveys. At 11 spawning sites in the mainstem Tanana River, we recorded inter-gravel and surface-water temperatures and vertical hydraulic gradient (an indication of the direction of water flux) in substrate adjacent to salmon redds. At all locations, vertical hydraulic gradient adjacent to redds was positive, indicating that water was upwelling through the gravel. Inter-gravel temperatures adjacent to redds generally were warmer than surface water at most locations and were more stable than surface-water temperature. Inter-gravel water temperature adjacent to redds ranged from 2.6 to 5.8 degrees Celsius, whereas surface-water temperature ranged from greater than 0 to 5.5 degrees Celsius. Some sites were affected more by extremes in air temperature than others. At these sites, inter-gravel water temperature profiles were variable (with ranges similar to those observed in surface water), suggesting that even though upwelling habitats provide a stable thermal incubation environment, eggs and embryos still may be affected by extremes in air temperature. Fine sand and silt covered redds at multiple sites and were evidence of increased river flow during the winter months, which may be a potential source of increased mortality during egg-to-fry development. This study provides documentation of spawning by fall chum salmon and is the first study to continuously measure inter-gravel water temperature at sites in the mainstem Tanana River.

Building the evidence base for REDD+: Study design and methods for evaluating the impacts of conservation interventions on local well-being

PubMed Central

Sills, Erin O.; de Sassi, Claudio; Jagger, Pamela; Lawlor, Kathleen; Miteva, Daniela A.; Pattanayak, Subhrendu K.; Sunderlin, William D.

2018-01-01

Climate change mitigation in developing countries is increasingly expected to generate co-benefits that help meet sustainable development goals. This has been an expectation and a hotly contested issue in REDD+ (reducing emissions from deforestation and forest degradation) since its inception. While the core purpose of REDD+ is to reduce carbon emissions, its legitimacy and success also depend on its impacts on local well-being. To effectively safeguard against negative impacts, we need to know whether and which well-being outcomes can be attributed to REDD+. Yet, distinguishing the effects of choosing particular areas for REDD+ from the effects of the interventions themselves remains a challenge. The Global Comparative Study (GCS) on REDD+ employed a quasi-experimental before-after-control-intervention (BACI) study design to address this challenge and evaluate the impacts of 16 REDD+ pilots across the tropics. We find that the GCS approach allows identification of control groups that represent the counterfactual, thereby permitting attribution of outcomes to REDD+. The GCS experience belies many of the common critiques of the BACI design, especially concerns about collecting baseline data on control groups. Our findings encourage and validate the early planning and up-front investments required to evaluate the local impacts of global climate change mitigation efforts with confidence. The stakes are high, both for the global environment and for local populations directly affected by those efforts. The standards for evidence should be concomitantly high. PMID:29681690

Building the evidence base for REDD+: Study design and methods for evaluating the impacts of conservation interventions on local well-being.

PubMed

Sills, Erin O; de Sassi, Claudio; Jagger, Pamela; Lawlor, Kathleen; Miteva, Daniela A; Pattanayak, Subhrendu K; Sunderlin, William D

2017-03-01

Climate change mitigation in developing countries is increasingly expected to generate co-benefits that help meet sustainable development goals. This has been an expectation and a hotly contested issue in REDD+ (reducing emissions from deforestation and forest degradation) since its inception. While the core purpose of REDD+ is to reduce carbon emissions, its legitimacy and success also depend on its impacts on local well-being. To effectively safeguard against negative impacts, we need to know whether and which well-being outcomes can be attributed to REDD+. Yet, distinguishing the effects of choosing particular areas for REDD+ from the effects of the interventions themselves remains a challenge. The Global Comparative Study (GCS) on REDD+ employed a quasi-experimental before-after-control-intervention (BACI) study design to address this challenge and evaluate the impacts of 16 REDD+ pilots across the tropics. We find that the GCS approach allows identification of control groups that represent the counterfactual, thereby permitting attribution of outcomes to REDD+. The GCS experience belies many of the common critiques of the BACI design, especially concerns about collecting baseline data on control groups. Our findings encourage and validate the early planning and up-front investments required to evaluate the local impacts of global climate change mitigation efforts with confidence. The stakes are high, both for the global environment and for local populations directly affected by those efforts. The standards for evidence should be concomitantly high.

Secondary Forests from Agricultural Abandonment in Amazonia 2000-2009

NASA Technical Reports Server (NTRS)

Morton, Douglas

2010-01-01

Ongoing negotiations to include reducing emissions from tropical deforestation and forest degradation (REDD+) in a post-Kyoto climate agreement highlight the critical role of satellite data for accurate and transparent accounting of forest cover changes. In addition to deforestation and degradation, knowledge of secondary forest dynamics is essential for full carbon accounting under REDD+. Land abandonment to secondary forests also frames one of the key tradeoffs for agricultural production in tropical forest countries-whether to incentivize secondary forest growth (for carbon sequestration and biodiversity conservation) or low-carbon expansion of agriculture or biofuels production in areas of secondary forests. We examined patterns of land abandonment to secondary forest across the arc of deforestation in Brazil and Bolivia using time series of annual Landsat and MODIS data from 2000-2009. Rates of land abandonment to secondary forest during 2002-2006 were less than 5% of deforestation rates in these years. Small areas of new secondary forest were scattered across the entire arc of deforestation, rather than concentrated in any specific region of the basin. Taken together, our analysis of the satellite data record emphasizes the difficulties of addressing the pool of new secondary forests in the context of REDD+ in Amazonia. Due to the small total area of secondary forests, land sparing through agricultural intensification will be an important element of efforts to reduce deforestation rates under REDD+ while improving agricultural productivity in Amazonia.

Deepwater Spawning of Fall Chinook Salmon (Oncorhynchus tshawytscha) near Ives and Pierce Island of the Columbia River, 2004-2005 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mueller, Robert

2005-10-01

Pacific Northwest National Laboratory conducted video-based boat surveys to identify fall Chinook salmon (Oncorhynchus tshawytscha) spawning areas located in deep water (greater than 1 m) downstream of Bonneville Dam in fall 2004. This report documents the number and extent of Chinook salmon spawning near Ives and Pierce Islands of the Columbia River and is the sixth in a series of reports prepared since 1999. The main objectives of this study were to find deepwater spawning locations of fall Chinook salmon in the main Columbia River channel, collect additional data on physical habitat parameters at spawning sites, and provide estimates ofmore » adult spawners in the surveyed area. The primary search area was adjacent to the upper portion of Pierce Island, and the secondary search zone was downstream of this area near the lower portion of Pierce Island. A secondary objective was to document the occurrence of any chum salmon (O. keta) redds in the deeper sections downstream of Hamilton Creek (slough zone search area). Fall Chinook salmon redd numbers were down slightly from the record number found during 2003. The number of fall Chinook redds found in the Ives-Pierce Island complex (river km 228.5) during 2004 was 293, which does not include the number of shallow water redds found by visual observation by boat by the Oregon Department of Fish and Wildlife. The redds encompassed an area of 14.6 ha occurring adjacent to the lower part of Ives Island and Pierce Island. Peak spawning activity, based on redd counts and live fish seen near redds, was on or near November 16, 2004. An expanded redd count based on percentage video coverage in the primary and secondary search zones was 3,198 fall Chinook salmon redds at water depths exceeding approximately 1.0 m (approximately 125 kcfs) with an estimated spawning population of 10,800. Fall Chinook salmon redds were found at water depths from 1.07 to 7.6 m and were constructed predominantly of medium cobbles ranging in size from 7.6 to 15.2 cm in diameter. Near-bed water velocity readings taken in the secondary search ranged from 0.04 to 0.98 m/s (median 0.45 m/s). No chum salmon redds were found in a limited area within the relatively deeper sections of Hamilton Slough below Hamilton Creek. No additional salmon or chum redds were found in other areas searched, including near Woodward, Tanner, and McCord Creeks.« less

Section summary: Institutional context, drivers and detectability in REDD+ implementation

Treesearch

Patricia Manley

2013-01-01

REDD+ and Forest DegradationREDD+ implementation requires two key steps: (1) establish a reference emission level or reference level (RL); and (2) monitor performance against the reference level (RL). A monitoring system must be able to monitor the performance of implementing action plans to reduce emissions....

The Role of Satellite Data for the National Forest Monitoring Systems in the Context of REDD+

NASA Astrophysics Data System (ADS)

Jonckheere, Inge

2012-04-01

Reducing Emissions from Deforestation and Forest Degradation (REDD) is an effort to create a financial value for the carbon stored in forests, offering incentives for developing countries to reduce emissions from forested lands and invest in low-carbon paths to sustainable development. “REDD+” goes beyond deforestation and forest degradation, and includes the role of conservation, sustainable management of forests and enhancement of forest carbon stocks. In the framework of getting countries ready for REDD+, the UN-REDD Programme assists developing countries to prepare and implement national REDD+ strategies. For the monitoring, reporting and verification (MRV), FAO supports the countries to develop national forest monitoring systems (NFMS) based on satellite data that allow for credible MRV of REDD+ activities through time. The UN-REDD Programme through a joint effort of FAO and Brazil's National Space Agency, INPE, is supporting countries to develop cost- effective, robust and compatible national monitoring and MRV systems, providing tools, methodologies, training and knowledge sharing that help countries to strengthen their technical and institutional capacity for effective MRV systems. The Brazilian forest monitoring system, TerraAmazon, which is used as a multi-user basis, allows countries to adapt it to country needs. With the technical assistance of FAO, INPE and other stakeholders, the countries will set up an autonomous operational satellite forest monitoring systems. A beta version and the methodologies of the system for DRC and PNG are launched in Durban (SA) during COP 17, while Paraguay, Zambia and Viet Nam are in development in 2012.

Maximizing biodiversity co-benefits under REDD+: a decoupled approach

NASA Astrophysics Data System (ADS)

Potts, Matthew D.; Kelley, Lisa C.; Doll, Hannah M.

2013-06-01

Current debates on biodiversity co-benefits under REDD+ are marked by considerable ambiguity and contention. Nevertheless, REDD+ continues to represent one of the most important opportunities for global biodiversity conservation, and the question of how best to achieve biodiversity co-benefits remains an important one. Thus far, most biodiversity conservation in the context of REDD+ is predicated on the notion that services are co-located on a landscape. In contrast, this letter argues that decoupling biodiversity and carbon services on a landscape through national-level planning is a better approach to biodiversity conservation under REDD+. We discuss the fundamental ecological differences between the two services and use principles of resource economics to demonstrate that a decoupled approach will be more efficient, more flexible, and better able to mobilize sufficient finance for biodiversity conservation than a coupled approach.

Deepwater Spawning of Fall Chinook Salmon (Oncorhynchus tshawtscha) Near Ives and Pierce Island of the Columbia River, 2002-2003 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mueller, Robert

2003-09-01

Pacific Northwest National Laboratory conducted video-based boat surveys to identify fall chinook salmon (Oncorhynchus tshawytscha) spawning areas located in deep water (>1 m) downstream of Bonneville Dam in the fall of 2002. This report documents the number and extent of chinook salmon spawning near Ives and Pierce Islands of the Columbia River, and is the fourth in a series of reports prepared since 1999. The main objective of this study was to find deepwater spawning locations of fall chinook salmon in the main Columbia River channel, collect additional data on physical habitat parameters at spawning sites, and provide estimates ofmore » adult spawners in the surveyed area. The secondary objective was to document the occurrence of any chum salmon (O. keta) redds located in the deeper sections near below Hamilton Creek. There was a significant increase in the number of fall chinook salmon redds found in the locations surveyed during the 2002 surveys when compared to previous surveys by Pacific Northwest National Laboratory. A total of 192 redds were found in two general locations adjacent to Pierce Island (river km 228.5) encompassing an area of approximately 9.31 ha. Peak spawning activity, based on redd counts and live fish seen near redds, was on or near November 15, 2002. An estimated 1,768 fall chinook salmon redds at water depths exceeding {approx}1.m ({approx} 125 kcfs) were documented in 2002. This estimate is the expanded number based on the number of redds found within the pre-defined survey area. Fall chinook salmon redds were found at water depths from 0.9 to 8.5 m and were constructed in gravel to large cobble ranging in size from 4.83 to 13.4 cm in diameter. No chum salmon redds were found in areas surveyed during 2002, although several carcasses were found at the mouth of Woodward Creek and in the deeper sections below Hamilton Creek.« less

Attributes of Yellowstone cutthroat trout redds in a tributary of the Snake River, Idaho

Treesearch

Russell F. Thurow; John G. King

1994-01-01

We characterized spawning sites of Yellowstone cutthroat trout Oncorhynchus clarki bouvieri, described the microhabitat of completed redds, and tested the influence of habitat conditions on the morphology of completed redds in Pine Creek, Idaho. Cutthroat trout spawned in June as flows subsided after peak stream discharge. During spawning, minimum and maximum water...

Comparing methods for assessing the effectiveness of subnational REDD+ initiatives

NASA Astrophysics Data System (ADS)

Bos, Astrid B.; Duchelle, Amy E.; Angelsen, Arild; Avitabile, Valerio; De Sy, Veronique; Herold, Martin; Joseph, Shijo; de Sassi, Claudio; Sills, Erin O.; Sunderlin, William D.; Wunder, Sven

2017-07-01

The central role of forests in climate change mitigation, as recognized in the Paris agreement, makes it increasingly important to develop and test methods for monitoring and evaluating the carbon effectiveness of REDD+. Over the last decade, hundreds of subnational REDD+ initiatives have emerged, presenting an opportunity to pilot and compare different approaches to quantifying impacts on carbon emissions. This study (1) develops a Before-After-Control-Intervention (BACI) method to assess the effectiveness of these REDD+ initiatives; (2) compares the results at the meso (initiative) and micro (village) scales; and (3) compares BACI with the simpler Before-After (BA) results. Our study covers 23 subnational REDD+ initiatives in Brazil, Peru, Cameroon, Tanzania, Indonesia and Vietnam. As a proxy for deforestation, we use annual tree cover loss. We aggregate data into two periods (before and after the start of each initiative). Analysis using control areas (‘control-intervention’) suggests better REDD+ performance, although the effect is more pronounced at the micro than at the meso level. Yet, BACI requires more data than BA, and is subject to possible bias in the before period. Selection of proper control areas is vital, but at either scale is not straightforward. Low absolute deforestation numbers and peak years influence both our BA and BACI results. In principle, BACI is superior, with its potential to effectively control for confounding factors. We conclude that the more local the scale of performance assessment, the more relevant is the use of the BACI approach. For various reasons, we find overall minimal impact of REDD+ in reducing deforestation on the ground thus far. Incorporating results from micro and meso level monitoring into national reporting systems is important, since overall REDD+ impact depends on land use decisions on the ground.

Top-down, Bottom-up and Sideways: The Multilayered Complexities of Multi-level Actors Shaping Forest Governance and REDD+ Arrangements in Madre de Dios, Peru.

PubMed

Rodriguez-Ward, Dawn; Larson, Anne M; Ruesta, Harold Gordillo

2018-01-03

This study examines the role multilevel governance plays in the adoption of sustainable landscape management initiatives in emerging arrangements aimed at reducing emissions from deforestation and forest degradation (REDD+). It sheds light on the challenges these multiple layers of actors and interests encounter around such alternatives in a subnational jurisdiction. Through transcript analysis of 93 interviews with institutional actors in the region of Madre de Dios, Peru, particularly with regard to five sites of land-use change, we identified the multiple actors who are included and excluded in the decision-making process and uncovered their complex interactions in forest and landscape governance and REDD+ arrangements. Madre de Dios is a useful case for studying complex land-use dynamics, as it is home to multiple natural resources, a large mix of actors and interests, and a regional government that has recently experienced the reverberations of decentralization. Findings indicate that multiple actors shaped REDD+ to some extent, but REDD+ and its advocates were unable to shape land-use dynamics or landscape governance, at least in the short term. In the absence of strong and effective regional regulation for sustainable land use alternatives and the high value of gold on the international market, illegal gold mining proved to be a more profitable land-use choice. Although REDD+ created a new space for multilevel actor interaction and communication and new alliances to emerge, the study questions the prevailing REDD+ discourse suggesting that better coordination and cooperation will lead to integrated landscape solutions. For REDD+ to be able to play a role in integrated landscape governance, greater attention needs to be paid to grassroots actors, power and authority over territory and underlying interests and incentives for land-use change.

Evaluating probability sampling strategies for estimating redd counts: an example with Chinook salmon (Oncorhynchus tshawytscha)

Treesearch

Jean-Yves Courbois; Stephen L. Katz; Daniel J. Isaak; E. Ashley Steel; Russell F. Thurow; A. Michelle Wargo Rub; Tony Olsen; Chris E. Jordan

2008-01-01

Precise, unbiased estimates of population size are an essential tool for fisheries management. For a wide variety of salmonid fishes, redd counts from a sample of reaches are commonly used to monitor annual trends in abundance. Using a 9-year time series of georeferenced censuses of Chinook salmon (Oncorhynchus tshawytscha) redds from central Idaho,...

Dynamics of chinook salmon populations within Idaho's Frank Church Wilderness: implications for persistence

Treesearch

Russell F. Thurow

2000-01-01

Research was begun in 1995 to describe factors influencing the spatial dynamics and persistence of federally listed chinook salmon within the Frank Church River of No Return Wilderness. Results addressed two objectives: 1) description of chinook salmon redd distributions, and 2) comparison of index and total redd counts. Annual redd counts ranged from 20 to 661, and 99...

Spatial variation in spawning habitat of cutthroat trout in a sediment-rich basin

Treesearch

James P. Magee; Thomas E. McMahon; Russell F. Thurow

1996-01-01

We examined distribution and habitat characteristics of spawning sites of cutthroat trout Oncorhynchus clarki at various spatial scales to assess effects of sedimentation within a large basin in Montana. Redd density varied widely across the basin; nearly all (99%) of the 362 redds observed occurred in two high-elevation headwater tributaries. Redd density at the reach...

Options for sampling and stratification for national forest inventories to implement REDD+ under the UNFCCC

PubMed Central

2010-01-01

Background Developing countries that are willing to participate in the recently adopted (16th Session of the Conference of Parties (COP) in Cancun) mitigation mechanism of Reducing emissions from Deforestation and Forest Degradation - and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks (REDD+) - will have to establish a national forest monitoring system in order to assess anthropogenic forest-related greenhouse gas emissions by sources and removals by sinks. Such a system should support the Measurement, Reporting and Verification (MRV) requirement of the United Nations Framework Convention on Climate Change (UNFCCC) as the REDD+ mechanism is results-based. A national forest inventory (NFI) is one potential key component of such an MRV system. Following the Decision adopted during the 15th Session of the COP in Copenhagen, the most recent Intergovernmental Panel on Climate Change (IPCC) Guidance and Guidelines should be used as a basis for estimating anthropogenic forest-related greenhouse gas emissions by sources and removals by sinks and changes in forest carbon stocks and area. Results First, we present the key indispensable elements of the IPCC Guidance and Guidelines that have been developed to fulfil the UNFCCC reporting requirements. This is done in order to set the framework to develop the MRV requirement in which a NFI for REDD+ implementation could be developed. Second, within this framework, we develop and propose a novel scheme for the stratification of forest land for REDD+. Finally, we present some non-exhaustive optional elements within this framework that a country could consider to successfully operationalise and implement its REDD+ NFI. Conclusion Evidently, both the methodological guidance and political decisions on REDD+ under the UNFCCC will continue to evolve. Even so, and considering that there exists decades of experience in setting up traditional NFIs, developing a NFI that a country may use to directly support REDD+ activities under the UNFCCC represents the development of a new challenge in this field. It is therefore important that both the scientific community and national implementing agencies acquaint themselves with both the context and content of this challenge so that REDD+ mitigation actions may be implemented successfully and with environmental integrity. This paper provides important contributions to the subject through our proposal of the stratification of forest land for REDD+. PMID:21187009

PERSPECTIVE: REDD pilot project scenarios: are costs and benefits altered by spatial scale?

NASA Astrophysics Data System (ADS)

Carlson, Kimberly M.; Curran, Lisa M.

2009-09-01

Kimberly M Carlson Payments for reducing carbon emissions due to deforestation and degradation (REDD) have garnered considerable global interest and investments. These financial incentives aim to alter the drivers of land use change by reducing opportunity costs of retaining forest cover, and are often promoted as multipartite solutions that not only generate profits and reduce carbon emissions but provide benefits for human development and biodiversity. Currently, the United Nations Framework Convention on Climate Change (UNFCCC) is debating a post-Kyoto protocol with national or sub-national emission reduction targets. Anticipating the inclusion of REDD in this agreement, >80% of pilot REDD projects are being established in tropical regions (table 1). While the capacity of REDD projects to meet their stated objectives must be assessed post- implementation, land use change models are powerful tools for generating potential outcomes from these pilot initiatives. Table 1. Extent and emissions reductions for all REDD projects as reported by Ecosystem Marketplace, which maintains a comprehensive and up-to-date inventory of REDD projects that are selling credits and/or are verified by a third-party verifier. Adapted from Forest Carbon Portal (2009). Geographical zoneContinentProjects (#) Area (km2) Emissions reductions (Mt C) Tropical and Subtropical Africa2775019.50 Asia28100109.60 South America 9183 880278.24 TemperateAustralia1140.18 North America115N/A Totals15199 759407.52 In this issue of ERL, Gaveau et al (2009) use a spatially-explicit model to explore the potential of a REDD pilot project in northern Sumatra, Indonesia, to reduce deforestation and conserve orangutan biodiversity. This project is conceived by the Provincial Government of Aceh, financed by Merrill Lynch, and co-managed by carbon trading firm Carbon Conservation and NGO Flora and Fauna International. Project managers estimate CO2 emissions reductions at 3.4 Mt y-1 over 30 years across a 7500 km2 area (Forest Carbon Portal 2009). From a time-series of Landsat satellite images, Gaveau et al calculate deforestation rates from 1990-2000 and 2000-2006. They apply these annual rates to deforestation probability maps, generated from forest condition in 2006 and six static spatial variables, to predict potential locations of future deforestation through 2030 under three different scenarios: (i) a business-as- usual with no REDD project; (ii) the current 7500 km2 project; and (iii) an extensive 65 000 km2 REDD scheme extending across the Aceh and Sumatra Utara provinces. Gaveau et al's chief contribution is identifying locations where forest carbon projects potentially have the greatest benefits for forest and orangutan conservation. By processing Landsat satellite imagery - now freely available - with relatively few spatial model inputs, this approach also has great potential for widespread application in tropical countries developing historical deforestation baselines. Yet Landsat satellite data also impose limitations for REDD. For example, Gaveau et al are unable to calculate forest degradation, which is highly problematic both to define and detect with Landsat imagery, yet critical especially in Indonesia with extensive logged forests (Curran et al 2004, Ramankutty et al 2007, Asner et al 2006). Nevertheless, Landsat remains one of the most appropriate satellite data products available for countries calculating previous rates of forest change. Assuming that technical roadblocks to REDD are overcome, another challenge surrounds assessing the feasibility of emission reduction scenarios, including those presented by Gaveau et al. Their estimates show that carbon and biodiversity gains would be 6- to 7-fold greater if the pilot project encompassed the 65 000 km2 northern Sumatra region. Yet, developers chose to implement this REDD project across 7500 km2, ~ 10% of Gaveau et al's expanded scenario region. If REDD programs are to be realized across large spatial scales (e.g., provinces/states), what factors constrain effective implementation? First, high transaction costs and investment risks appear to be major barriers to establishing carbon concessions across large, heterogeneous regions. Identifying who should receive compensation as well as negotiating transparent and effective payment arrangements, is at best challenging especially with ambiguous land use rights and government jurisdiction in Indonesia (Ebeling and Yasué 2008). Protecting fragmented forests from multiple threats of logging, agriculture, and fire is fraught with complexities; who should be held accountable for defending 65 000 km2 from fire especially during ENSO- associated droughts (Siegert et al 2001, Langner and Siegert 2008)? REDD's effectiveness will require support from people who live in and near REDD projects; Gaveau et al address only biodiversity and forest loss in their paper, but incorporating the potential effects of REDD programs on livelihoods and social dynamics is one of the most critical components of effective assessments via scenario-building and modeling (Soares-Filho et al 2006). Another major obstacle to establishing REDD across large regions is the opportunity costs of carbon concessions. Recent estimates show that profits from protecting aboveground biomass for carbon payments in Indonesian non-peat forests are far below the benefits garnered from converting these forests to plantation agriculture (Butler et al 2009). Yet in order to mitigate forest conversion as proposed by Gaveau et al, carbon must compete with alternative high-value commodities (e.g., palm oil). Although forest carbon credits currently are traded in voluntary markets, carbon prices are considerably higher in compliance markets than in voluntary markets (World Bank 2008). If the UNFCCC generates consensus in December 2009 incorporating REDD in formal market-based trading mechanisms to meet compliance targets, REDD may become a financially competitive land use option even in highly-threatened lowland forests, including those in northern Sumatra. Ultimately, REDD implementation is an iterative process, requiring regular appraisals and improvements at local (i.e., REDD projects) through international (i.e., UNFCCC) levels. The overarching value of REDD pilot initiatives such as this groundbreaking Aceh project and Gaveau et al's innovative assessments is to identify suitable approaches as well as shortcomings, allowing revised and refined efforts that will mitigate forest degradation via financial mechanisms. The next iteration of REDD program evaluations will also need to incorporate: (i) empirical measurements of carbon stock change attributed to forest degradation; (ii) evaluations of economic incentives for a diverse suite of agents such as local and urban communities as well as the private sector; and, (iii) explicitly consider the fluctuating price of carbon vis-à-vis competing commodity prices. References Asner G P, Broadbent E N, Oliveira P J C, Keller M, Knapp D E and Silva J N M 2006 Condition and fate of logged forests in the Brazilian Amazon Proc. Natl Acad. Sci. USA 103 12947-50 Butler R A, Koh L P and Ghazoul J 2009 REDD in the red: palm oil could undermine carbon payment schemes Conserv. Lett. 2 67-73 Curran L M, Trigg S N, Mcdonald A K, Astiani D, Hardiono Y M, Siregar P, Caniago I and Kasischke E 2004 Lowland forest loss in protected areas of Indonesian Borneo Science 303 1000-3 Ebeling J and Yasué M 2008 Generating carbon finance through avoided deforestation and its potential to create climatic, conservation and human development benefits Phil. Trans. R. Soc. B 363 1917-24 Forest Carbon Portal 2009 Forest Carbon Inventory Project www.forestcarbonportal.com Gaveau D, Wich S, Epting J, Juhn D, Kanninen M and Leader-Williams N 2009 The future of forests and orangutans (Pongo abelii) in Sumatra: predicting impacts of oil palm plantations, road construction, and mechanisms for reducing carbon emissions from deforestation Environ. Res. Lett. 4 034013 Langner A and Siegert F 2009 Spatiotemporal fire occurrence in Borneo over a period of 10 years Glob. Change Biol. 15 48-62 Ramankutty N, Gibbs H K, Achard F, Defries R, Foley J A and Houghton R A 2007 Challenges to estimating carbon emissions from tropical deforestation Glob. Change Biol. 13 51-66 Siegert F, Ruecker G, Hinrichs A and Hoffmann A A 2001 Increased damage from fires in logged forests during droughts caused by El Nino Nature 414 437-40 Soares-Filho B S, Nepstad D C, Curran L M, Cerqueira G C, Garcia R A, Ramos C A, Voll E, Mcdonald A, Lefebvre P and Schlesinger P 2006 Modelling conservation in the Amazon basin Nature 440 520-3 World Bank 2008 State and Trends of the Carbon Market 2008 (Washington, DC: World Bank)

Painting the world REDD: addressing scientific barriers to monitoring emissions from tropical forests

NASA Astrophysics Data System (ADS)

Asner, Gregory P.

2011-06-01

In December 2010, parties to the United Nations Framework Convention on Climate Change (UNFCCC) agreed to encourage reductions in greenhouse gas emissions from forest losses with the financial support of developed countries. This important international agreement followed about seven years of effort among governments, non-governmental organizations (NGO) and the scientific community, and is called REDD+, the program for Reducing Emissions from Deforestation and Forest Degradation. REDD+ could achieve its potential to slow emissions from deforestation and forest degradation either as a new market option to offset emissions from developed nations, or as a mitigation option for developing countries themselves. Aside from representing an important step towards reducing greenhouse gas emissions, a growing list of potential co-benefits to REDD+ include improved forestry practices, forest restoration, sustainable development, and biodiversity protection. Indeed the agreement is heralded as a win-win for climate change mitigation and tropical forest conservation, and it could end up contributing to a global economy based on carbon and ecosystem services. That's good news, and some governments are now working to become 'REDD ready' in preparation for the forthcoming international program. This is important because, according to the agreements made by governments in the UNFCCC, developing countries which voluntarily decide to take part in REDD+ must establish their own national forest monitoring system to report changes in emissions from forests (UNFCCC 2009). But as of today, no developing country has implemented a system for monitoring, reporting and verifying (MRV) emission reductions for REDD+. Of course, it is all still very new, but many REDD-type projects have been underway for years now (Parker et al 2008), and many MRV practitioners involved in those projects are the same people being asked to help with government-led, national MRV programs. Yet going from the project scale to program readiness is a big step for all involved, and many are finding that it is not easy. Current barriers to national monitoring of forest carbon stocks and emissions range from technical to scientific, and from institutional to operational. In fact, a recent analysis suggested that about 3% of tropical countries currently have the capacity to monitor and report on changes in forest cover and carbon stocks (Herold 2009). But until now, the scientific and policy-development communities have had little quantitative information on exactly which aspects of national-scale monitoring are most uncertain, and how that uncertainty will affect REDD+ performance reporting. A new and remarkable study by Pelletier, Ramankutty and Potvin (2011) uses an integrated, spatially-explicit modeling technique to explore and quantify sources of uncertainty in carbon emissions mapping throughout the Republic of Panama. Their findings are sobering: deforestation rates would need to be reduced by a full 50% in Panama in order to be detectable above the statistical uncertainty caused by several current major monitoring problems. The number one uncertainty, accounting for a sum total of about 77% of the error, rests in the spatial variation of aboveground carbon stocks in primary forests, secondary forests and on fallow land. The poor quality of and insufficient time interval between land-cover maps account for the remainder of the overall uncertainty. These findings are a show-stopper for REDD+ under prevailing science and technology conditions. The Pelletier et al study highlights the pressing need to improve the accuracy of forest carbon and land cover mapping assessments in order for REDD+ to become viable, but how can the uncertainties be overcome? First, with REDD+ nations required to report their emissions, and with verification organizations wanting to check on the reported numbers, there is a clear need for shared measurement and monitoring approaches. One of the major stumbling blocks actually starts with the scientific community, which needs not only to develop highly accurate deforestation, degradation and carbon emission monitoring methods, but also to make those methods available to national governments and the supporting organizations orbiting those governments. This 'giving away' of the methods starts, but does not end, with the training provided by the scientific experts on the use of the monitoring tools. This effort must also involve a commitment to sustained support and capacity building until non-expert monitoring and reporting becomes routine. The scientific community must also make clear what is operational and what is research. Operational does not necessarily mean less accurate. Rather, achieving both operational status and high accuracy requires innovation. While an innovative, but one-time or infrequent, mapping of forest cover or carbon stocks has been the most common scientific contribution to REDD+, it alone does not constitute operational monitoring. However, it can contribute to a portfolio of techniques and products that must come together to form an operational monitoring and modeling approach. Australia's National Carbon Accounting System (NCAS; www.climatechange.gov.au/) is one such approach, and there are others developing (www.csr.ufmg.br/simamazonia/). Importantly, carbon accounting models can meet the REDD+ challenge, but only if the observations—the measurements—are high quality, high resolution, and synoptic in geographic scale (Asner 2009). Is there hope, and if so, is it based on real and present scientific progress? Real progress is being made, but much of the innovation has not landed in the reports provided by and for the UN and Intergovernmental Panel on Climate Change (IPCC). Yet this innovation is breaking serious barriers that extend and/or replace traditional forest inventory techniques, that use the latest satellite and aircraft technology on a cost-effective and repeated basis, and which simultaneously produce non-expert users of those technologies. And some government and academic science organizations are making their previously expert-only deforestation monitoring software widely available. For example, the Carnegie Institution's CLASlite system routinely tracks deforestation and degradation, and is now in use by more than 150 organizations throughout nine countries (http://claslite.ciw.edu). Carbon stock and emissions mapping is also becoming routine, but still involves combined effort by government and expert science partners to get it right (http://geoservidor.minam.gob.pe/intro/). Data accessibility is also critically important, and a few countries, such as Brazil and the United States, are leading the way by providing satellite imagery essential to lowering the uncertainties documented by Pelletier et al (2011). Finally, the uncertainty in MRV may be addressed faster at the sub-national level. Developing states and provinces are often responsible for implementing forest policies and land-use zoning, and many have their own forest monitoring programs. Thirteen tropical states and provinces, from Mexico to Brazil and Indonesia, are forging ahead in developing their own jurisdiction-wide REDD+ programs in collaboration with the US State of California, which has created the world's first greenhouse gas emission cap-and-trade policy that allows international offsets. In fact, this collaboration may soon create the first regulated REDD+ carbon market as California (USA), Acre (Brazil) and Chiapas (Mexico) forge an historic linkage agreement under the auspices of the Governors' Climate and Forest Task Force (http://gcftaskforce.org). Once created, this REDD+ market, in which regulated California industries achieve a portion of their emissions reductions through investments in Acre and Chiapas REDD+ programs, could expand to include new buyers and new providers. A key component of this program involves highly accurate, operational MRV on both sides of the carbon trading table, and at these state-level geographic scales, the science and technology are proving to be the most robust and accurate. Scientific innovation, combined with appropriate up-scaling from jurisdiction to jurisdiction, will likely prove most effective in bringing REDD+ to fruition. References Asner G P 2009 Tropical forest carbon assessment: integrating satellite and airborne mapping approaches Environ. Res. Lett. 4 034009 Herold M 2009 An assessment of national forest monitoring capabilities in tropical non-Annex I countries: Recommendations for capacity building (Friedrich-Schiller-Universität Jena and GOFC-GOLD Land Cover Project Office) (available at: http://unfccc.int/files/methods_science/redd/country_specific_information/application/pdf/redd_nat_capacity_report_herold_july09_publ.pdf) Parker C, Mitchell A, Trivedi M and Mardas N 2008 The little REDD book: a guide to governmental and non-governmental proposals for reducing emissions from deforestation and degradation (GlobalCanopy Programme) (available at: http://www.globalcanopy.org/materials/little-redd-book) Pelletier J, Ramankutty N and Potvin C 2011 Diagnosing the uncertainty and detectability of emission reductions for REDD+ under current capabilities: an example for Panama Environ. Res. Lett. 6 024005 UNFCCC 2009 Methodological guidance for activities relating to reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancements of forest carbon stocks in developing countries United National Framework Convention on Climate Change Decision 4/CP.15 (available at: http://unfccc.int/resource/docs/2009/cop15/eng/11a01.pdf#page=11)

Avoiding re-inventing the wheel in a people-centered approach to REDD+.

PubMed

Holmes, Ignacia; Potvin, Catherine

2014-10-01

One important debate regarding Reducing Emissions from Deforestation and Forest Degradation (REDD+) in developing countries concerns the manner in which its implementation might affect local and indigenous communities. New ways to implement this mechanism without harming the interests of local communities are emerging. To inform this debate, we conducted a qualitative research synthesis to identify best practices (BPs) from people-centered approaches to conservation and rural development, developed indicators of BPs, and invited development practitioners and researchers in the field to assess how the identified BPs are being adopted by community-level REDD+ projects in Latin America. BPs included: local participation in all phases of the project; project supported by a decentralized forest governance framework; project objectives matching community livelihood priorities; project addressing community development needs and expectations; project enhancing stakeholder collaboration and consensus building; project applying an adaptive management approach; and project developing national and local capacities. Most of the BPs were part of the evaluated projects. However, limitations of some of the projects related to decentralized forest governance, matching project objectives with community livelihood priorities, and addressing community development needs. Adaptive management and free and prior informed consent have been largely overlooked. These limitations could be addressed by integrating conservation outcomes and alternative livelihoods into longer-term community development goals, testing nested forest governance approaches in which national policies support local institutions for forest management, gaining a better understanding of the factors that will make REDD+ more acceptable to local communities, and applying an adaptive management approach that allows for social learning and capacity building of relevant stakeholders. Our study provides a framework of BPs and indicators that could be used by stakeholders to improve REDD+ project design, monitoring, and evaluation, which may help reconcile national initiatives and local interests without reinventing the wheel. © 2014 Society for Conservation Biology.

On fair, effective and efficient REDD mechanism design

PubMed Central

2009-01-01

The issues surrounding 'Reduced Emissions from Deforestation and Forest Degradation' (REDD) have become a major component of continuing negotiations under the United Nations Framework Convention on Climate Change (UNFCCC). This paper aims to address two key requirements of any potential REDD mechanism: first, the generation of measurable, reportable and verifiable (MRV) REDD credits; and secondly, the sustainable and efficient provision of emission reductions under a robust financing regime. To ensure the supply of MRV credits, we advocate the establishment of an 'International Emission Reference Scenario Coordination Centre' (IERSCC). The IERSCC would act as a global clearing house for harmonized data to be used in implementing reference level methodologies. It would be tasked with the collection, reporting and subsequent processing of earth observation, deforestation- and degradation driver information in a globally consistent manner. The IERSCC would also assist, coordinate and supervise the computation of national reference scenarios according to rules negotiated under the UNFCCC. To overcome the threats of "market flooding" on the one hand and insufficient economic incentives for REDD on the other hand, we suggest an 'International Investment Reserve' (IIR) as REDD financing framework. In order to distribute the resources of the IIR we propose adopting an auctioning mechanism. Auctioning not only reveals the true emission reduction costs, but might also allow for incentivizing the protection of biodiversity and socio-economic values. The introduced concepts will be vital to ensure robustness, environmental integrity and economic efficiency of the future REDD mechanism. PMID:19943927

A three-dimensional model for analyzing the effects of salmon redds on hyporheic exchange and egg pocket habitat

Treesearch

Daniele Tonina; John M. Buffington

2009-01-01

A three-dimensional fluid dynamics model is developed to capture the spatial complexity of the effects of salmon redds on channel hydraulics, hyporheic exchange, and egg pocket habitat. We use the model to partition the relative influences of redd topography versus altered hydraulic conductivity (winnowing of fines during spawning) on egg pocket conditions for a...

Knowledge representation and qualitative simulation of salmon redd functioning. Part I: qualitative modeling and simulation.

PubMed

Guerrin, F; Dumas, J

2001-02-01

This work aims at representing empirical knowledge of freshwater ecologists on the functioning of salmon redds (spawning areas of salmon) and its impact on mortality of early stages. For this, we use Qsim, a qualitative simulator. In this first part, we provide unfamiliar readers with the underlying qualitative differential equation (QDE) ontology of Qsim: representing quantities, qualitative variables, qualitative constraints, QDE structure. Based on a very simple example taken of the salmon redd application, we show how informal biological knowledge may be represented and simulated using an approach that was first intended to analyze qualitatively ordinary differential equations systems. A companion paper (Part II) gives the full description and simulation of the salmon redd qualitative model. This work was part of a project aimed at assessing the impact of the environment on salmon populations dynamics by the use of models of processes acting at different levels: catchment, river, and redds. Only the latter level is dealt with in this paper.

An assessment of monitoring requirements and costs of 'Reduced Emissions from Deforestation and Degradation'

PubMed Central

Böttcher, Hannes; Eisbrenner, Katja; Fritz, Steffen; Kindermann, Georg; Kraxner, Florian; McCallum, Ian; Obersteiner, Michael

2009-01-01

Background Negotiations on a future climate policy framework addressing Reduced Emissions from Deforestation and Degradation (REDD) are ongoing. Regardless of how such a framework will be designed, many technical solutions of estimating forest cover and forest carbon stock change exist to support policy in monitoring and accounting. These technologies typically combine remotely sensed data with ground-based inventories. In this article we assess the costs of monitoring REDD based on available technologies and requirements associated with key elements of REDD policy. Results We find that the design of a REDD policy framework (and specifically its rules) can have a significant impact on monitoring costs. Costs may vary from 0.5 to 550 US$ per square kilometre depending on the required precision of carbon stock and area change detection. Moreover, they follow economies of scale, i.e. single country or project solutions will face relatively higher monitoring costs. Conclusion Although monitoring costs are relatively small compared to other cost items within a REDD system, they should be shared not only among countries but also among sectors, because an integrated monitoring system would have multiple benefits for non-REDD management. Overcoming initialization costs and unequal access to monitoring technologies is crucial for implementation of an integrated monitoring system, and demands for international cooperation. PMID:19709413

Quantifying the behavioral response of spawning chum salmon to elevated discharges from Bonneville Dam, Columbia River, USA

USGS Publications Warehouse

Tiffan, K.F.; Haskell, C.A.; Kock, T.J.

2010-01-01

Chum salmon Oncorhynchus keta that spawn in main-stem habitats below Bonneville Dam on the Columbia River, USA, are periodically subjected to elevated discharges that may alter spawning behaviour. We investigated behavioural responses of spawning chum salmon to increased water velocities associated with experimental increases in tailwater elevation using acoustic telemetry and a dual-frequency identification sonar. Chum salmon primarily remained near their redds at base tailwater elevations (3.5 m above mean sea level), but displayed different movement and behavioural responses as elevations were increased to either 4.1 or 4.7m for 8-h periods. When velocities remained suitable (<0.8m s-1) during elevated-tailwater tests, female chum salmon remained near their redds but exhibited reduced digging activity as water velocities increased. However, when velocities exceeded 0.8m s-1, the females that remained on their redds exhibited increased swimming activity and digging virtually ceased. Female and male chum salmon that left their redds when velocities became unsuitable moved mean distances ranging from 32 to 58 m to occupy suitable velocities, but returned to their redds after tailwaters returned to base levels. Spawning events (i.e. egg deposition) were observed for five of nine pairs of chum salmon following tests indicating any disruptions to normal behaviour caused by elevated tailwaters were likely temporary. We believe a chum salmon's decision to either remain on, or leave, its redd during periods of unsuitably high water velocities reflects time invested in the redd and the associated energetic costs it is willing to incur. ?? 2009 John Wiley & Sons, Ltd.

The footprint of salmonids on river morphology

NASA Astrophysics Data System (ADS)

Hassan, M. A.; Tonina, D.

2012-12-01

Female salmonids dig a pit in the streambed where they lay their eggs, which then cover with sediment from a second pit forming an egg nest call redd. This formation results in a shape resembling a dune with an amplitude, which is the vertical difference between bottom of the pit and crest of the hump, varying from few centimetres (for small fish, chum or sockeye salmon) to tenths of a meter (for large fish, Chinook salmon). During redd construction, salmonids alter streambed topography, winnow away fine sediment and mix streambed material within a layer as thick as 50 cm, for the large chinook salmon. The spawning activities may result in additional roughness at the local scale due to redds. However, redd construction may smooth large-scale topography reducing roughness due the macro-bedform. These topographical changes vary streambed roughness, which in turn may affect shear stress distribution. Redds have been suggested to increase the overall flow resistance due to form drag resulting in lower grain shear stress and less particle mobility. However, the mixing of the sediment could prevent armouring of the streambed surface allowing higher than with armouring sediment transport. Here, we use detailed pre- and post-spawning bathymetries coupled with accurate 2-dimensional hydraulic numerical modelling to test which of these two effects has potentially more impact on sediment transport. Our results show that topographical roughness added by sockeye salmons, which build small redds with 15cm amplitude and 1 meter wavelength (longitudinal length of a redd), has negligible effect on shear stress at the reach-scale and limited at the local scale. Conversely, sediment mixing has an important effect on reducing armouring, increasing sediment mobility, which results in potentially more sediment transport in reaches with than without redds. Consequently, salmonid bioturbation due to mass-spawning fish can be a dominant element for sediment transport in mountain drainage basins

REDD+ projects in the Democratic Republic of Congo: impacts on future emissions, income and biodiversity

NASA Astrophysics Data System (ADS)

Mosnier, Aline; Bocqueho, Geraldine; Mant, Rebecca; Obersteiner, Michael; Havlik, Petr; Kapos, Val; Fritz, Steffen; Botrill, Leo

2014-05-01

The Democratic Republic of Congo (DRC) encompasses a large rainforest area which has been rather preserved up to now. However, pressure on the forests is increasing with high population growth, transition toward political stability and the abundance of minerals in the country. REDD+ is a developing mechanism under the UNFCCC that aims to support developing countries that want to make efforts to reduce their emissions from deforestation and forest degradation. The REDD+ strategy in DRC combines an independent national fund and independent REDD+ projects at the local level that are at the initial stage of implementation. The objective of this paper is to assess i) emissions reduction due to the implementation of the REDD+ pilot projects taking into account potential leakage and ii) potential co-benefits of REDD+ pilot projects in terms of biodiversity and rural income by 2030. We use the land use economic model CongoBIOM adapted from GLOBIOM which represents land-based activities and land use changes at a 50x50km resolution level. It includes domestic and international demand for agricultural products, fuel wood and minerals which are the main deforestation drivers in the Congo Basin region. Finally, we run a sensitivity analysis on emissions from land use change according to three different above and below ground living biomass estimates: downscaled FAO, NASA and WHRC.

Monitoring Strategies for REDD+: Integrating Field, Airborne, and Satellite Observations of Amazon Forests

NASA Technical Reports Server (NTRS)

Morton, Douglas; Souza, Carlos, Jr.; Souza, Carlos, Jr.; Keller, Michael

2012-01-01

Large-scale tropical forest monitoring efforts in support of REDD+ (Reducing Emissions from Deforestation and forest Degradation plus enhancing forest carbon stocks) confront a range of challenges. REDD+ activities typically have short reporting time scales, diverse data needs, and low tolerance for uncertainties. Meeting these challenges will require innovative use of remote sensing data, including integrating data at different spatial and temporal resolutions. The global scientific community is engaged in developing, evaluating, and applying new methods for regional to global scale forest monitoring. Pilot REDD+ activities are underway across the tropics with support from a range of national and international groups, including SilvaCarbon, an interagency effort to coordinate US expertise on forest monitoring and resource management. Early actions on REDD+ have exposed some of the inherent tradeoffs that arise from the use of incomplete or inaccurate data to quantify forest area changes and related carbon emissions. Here, we summarize recent advances in forest monitoring to identify and target the main sources of uncertainty in estimates of forest area changes, aboveground carbon stocks, and Amazon forest carbon emissions.

Historic emissions from deforestation and forest degradation in Mato Grosso, Brazil: 1) source data uncertainties

PubMed Central

2011-01-01

Background Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from credited mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008. Results Deforestation estimates showed good agreement for multi-year periods of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by > 20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C ha-1, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas. Conclusions Estimates of source data uncertainties are essential for REDD+. Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions. PMID:22208947

Building capacity for national level carbon Measurement, Reporting, and Verification (MRV) systems for a ``Reduction of Emissions from Deforestation and Degradation'' (REDD)

NASA Astrophysics Data System (ADS)

Laporte, N.; Goetz, S. J.; Baccini, A.; Walker, W. S.; Ndunda, P.; Mekui, P.; Kellndorfer, J. M.; Knight, D.

2010-12-01

An international policy mechanism is under negotiation for compensating tropical nations that succeed in lowering their greenhouse gas emissions from tropical deforestation and forest degradation, responsible for approximately one-fifth of worldwide carbon emissions. One of the barriers to its success is the adoption of a unique MRV system and the participation of developing countries in carbon monitoring. A successful REDD policy must rely on a robust, scalable, cost effective method that will allow the Measurement Reporting and Verification from local to national scales, while also developing well-trained technical personnel to implement national REDD carbon monitoring systems. Participation of governments and forest stakeholders in forest and carbon monitoring methods at WHRC is achieved through ongoing technical workshops which include training of participants to collect field data to calibrate biomass models, and an annual Scholar’s Program where forest officers from the tropical regions of Latin America, Africa and Southeast Asia work with Woods Hole Research Center scientsts to improve skills in forest measurement and remote sensing monitoring techniques . Capacity building activities focus on technical aspects and approaches to forest-cover and carbon mapping and the use of satellite imagery together with ground-based measurement techniques in the development of forest cover and carbon-stock maps. After two years, the three-year project has involved more than 200 forest specialists from governments and NGOs in Bolivia, Cambodia, Colombia, the Democratic Republic of Congo, Gabon, Indonesia, Lao PDR, Kenya, Uganda, Vietnam and Zambia, among others with participation of ten scholars actively participating in the developement of National REDD plans for forest mapping and monitoring. Field Training Mbandaka- DR Congo 2010

Salmon habitat assessment for conservation planning in the lower White Salmon River, Washington

USGS Publications Warehouse

Hardiman, Jill M.; Allen, M. Brady

2015-01-01

In 2011, Condit Dam was removed from the White Salmon River, Washington. Since dam removal, there has been interest among scientists (State and Federal), Tribes, non-profit organizations, and the general public in assessing Pacific salmon habitat and use in the White Salmon River for conservation planning and potential fishery management actions. The study area extended from the lower 6 miles of the White Salmon River to the confluence with the Columbia River, including the former reservoir area. The Mid-Columbia Fisheries Enhancement Group received a grant to initiate efforts to plan for salmon habitat protection in the lower 6 river miles of the White Salmon River. As part of efforts by the Mid-Columbia Fisheries Enhancement Group to conduct conservation planning, the U.S. Geological Survey (USGS) used current and historical habitat information to assist in the planning process. The USGS compiled existing georeferenced habitat data into a Geographic Information System to identify areas of high quality habitat for salmon, potential areas for restoration/improvement, and areas that could be threatened. The primary sources of georeferenced data for this project include a lidar flight contracted by PacifiCorp, bathymetry from USGS, and fall Chinook salmon redd surveys from the U.S. Fish and Wildlife Service and Washington Department of Fish and Wildlife. Redd observations provided support that the study area is a migratory corridor for salmon and steelhead and that the lowest 2–3 miles had the highest concentration of documented fall Chinook salmon redds. The study area has potential for restoration/conservation areas to improve/conserve salmon habitat.

A participatory approach to elucidate the consequences of land invasions on REDD+ initiatives: A case study with Indigenous communities in Panama

PubMed Central

Vergara-Asenjo, Gerardo; Alvarado, Alexis; Potvin, Catherine

2017-01-01

Land tenure and tenure security are among the most important factors determining the viability and success of Reducing Emissions from Deforestation and Forest Degradation (REDD+) initiatives. The premise of the present paper is that territorial conflicts lead to forest loss and compromise the successful implementation of REDD+. Within this context, the main objectives of this paper are to (i) document, relying on participatory methods, the extent to which land conflicts drive deforestation and (ii) reflect on the legal context of REDD+ examining if, from an Indigenous perspective, it offers tools to resolve such conflicts. We used the Upper Bayano Watershed in eastern Panama as a case study of complex land tenure dynamics, and their effects on forest conservation in the context of REDD+. Combining a range of participatory methods including participatory mapping and forest carbon stock assessment, we estimated the consequences of land invasions on forest carbon stocks. Our analysis shows that invasions of Indigenous territories amounted to 27.6% of the total deforestation for the period of 2001–2014. The situation is of paramount concern in the Embera territory of Majé where 95.4% of total deforestation was caused by colonist invaders. Using and validating the maps made freely available by the Global Forest Change initiative of the University of Maryland, we then developed a reference level for the watershed and carried out a back of the envelop estimation of likely REDD+ revenue, showing its potential to bring much needed income to Indigenous communities striving to protect their forest estate. Our analysis of current legislation in Panama highlights confusion and important legal voids and emphasizes the strong links between land tenure, carbon ownership, and territorial invasions. The options and shortcoming of implementing REDD+ in Indigenous territories is discussed in the conclusion taking our legal review into account. PMID:29261704

A participatory approach to elucidate the consequences of land invasions on REDD+ initiatives: A case study with Indigenous communities in Panama.

PubMed

Vergara-Asenjo, Gerardo; Mateo-Vega, Javier; Alvarado, Alexis; Potvin, Catherine

2017-01-01

Land tenure and tenure security are among the most important factors determining the viability and success of Reducing Emissions from Deforestation and Forest Degradation (REDD+) initiatives. The premise of the present paper is that territorial conflicts lead to forest loss and compromise the successful implementation of REDD+. Within this context, the main objectives of this paper are to (i) document, relying on participatory methods, the extent to which land conflicts drive deforestation and (ii) reflect on the legal context of REDD+ examining if, from an Indigenous perspective, it offers tools to resolve such conflicts. We used the Upper Bayano Watershed in eastern Panama as a case study of complex land tenure dynamics, and their effects on forest conservation in the context of REDD+. Combining a range of participatory methods including participatory mapping and forest carbon stock assessment, we estimated the consequences of land invasions on forest carbon stocks. Our analysis shows that invasions of Indigenous territories amounted to 27.6% of the total deforestation for the period of 2001-2014. The situation is of paramount concern in the Embera territory of Majé where 95.4% of total deforestation was caused by colonist invaders. Using and validating the maps made freely available by the Global Forest Change initiative of the University of Maryland, we then developed a reference level for the watershed and carried out a back of the envelop estimation of likely REDD+ revenue, showing its potential to bring much needed income to Indigenous communities striving to protect their forest estate. Our analysis of current legislation in Panama highlights confusion and important legal voids and emphasizes the strong links between land tenure, carbon ownership, and territorial invasions. The options and shortcoming of implementing REDD+ in Indigenous territories is discussed in the conclusion taking our legal review into account.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sathaye, Jayant; Andrasko, Ken; Chan, Peter

Greenhouse gas emissions from the forestry sector are estimated to be 8.4 GtCO2-eq./year or about 17percent of the global emissions. We estimate that the cost forreducing deforestation is low in Africa and several times higher in Latin America and Southeast Asia. These cost estimates are sensitive to the uncertainties of how muchunsustainable high-revenue logging occurs, little understood transaction and program implementation costs, and barriers to implementation including governance issues. Due to lack of capacity in the affected countries, achieving reduction or avoidance of carbon emissions will require extensive REDD-plus programs. Preliminary REDD-plus Readiness cost estimates and program descriptions for Indonesia,more » Democratic Republic of the Congo, Ghana, Guyana and Mexico show that roughly one-third of potential REDD-plus mitigation benefits might come from avoided deforestation and the rest from avoided forest degradation and other REDD-plus activities.« less

Building capacity for national carbon measurements for reducing emissions from deforestation and forest degradation

NASA Astrophysics Data System (ADS)

Goetz, S. J.; Laporte, N.; Horning, N.; Pelletier, J.; Jantz, P.; Ndunda, P.

2014-12-01

Many tropical countries are now working on developing their strategies for reducing emissions from deforestation and forest degradation, including activities that result in conservation or enhancement of forest carbon stocks and sustainable management of forests to effectively decrease atmospheric carbon emissions (i.e. REDD+). A new international REDD+ agreement is at the heart of recent negotiations of the parties to the UN Framework Convention on Climate Change (UNFCCC). REDD+ mechanisms could provide an opportunity to not only diminish an important source of emissions, but also to promote large-scale conservation of tropical forests and establish incentives and opportunities to alleviate poverty. Most tropical countries still lack basic information for developing and implementing their forest carbon stock assessments, including the extent of forest area and the rate at which forests are being cleared and/or degraded, and the carbon amounts associated with these losses. These same countries also need support to conduct integrated assessments of the most promising approaches for reducing emissions, and in identifying those policy options that hold the greatest potential while minimizing potential negative impacts of REDD+ policies. The WHRC SERVIR project in East Africa is helping to provide these data sets to countries via best practice tools and methods to support cost effective forest carbon monitoring solutions and more informed decision making processes under REDD+. We will present the results of our capacity building activites in the region and planned future efforts being coordinated with the NASA-SERVIR Hub in Kenya to support to REDD+ decision support.

Grande Ronde Basin Spring Chinook Salmon Captive Broodstock Program, 1995-2002 Summary Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoffnagle, Timothy; Carmichael, Richard; Noll, William

2003-12-01

The Grande Ronde Basin once supported large runs of chinook salmon Oncorhynchus tshawytscha and estimated peak escapements in excess of 10,000 occurred as recently as the late 1950's (U.S. Army Corps of Engineers 1975). Natural escapement declines in the Grande Ronde Basin have been severe and parallel those of other Snake River populations. Reduced productivity has primarily been attributed to increased mortality associated with downstream and upstream migration past eight dams and reservoirs in the Snake and Columbia rivers. Reduced spawner numbers, combined with human manipulation of previously important spawning and rearing habitat in the Grande Ronde Basin, have resultedmore » in decreased spawning distribution and population fragmentation of chinook salmon in the Grande Ronde Basin (Figure 1; Table 1). Escapement of spring/summer chinook salmon in the Snake River basin included 1,799 adults in 1995, less than half of the previous record low of 3,913 adults in 1994. Catherine Creek, Grande Ronde River and Lostine River were historically three of the most productive populations in the Grande Ronde Basin (Carmichael and Boyce 1986). However, productivity of these populations has been poor for recent brood years. Escapement (based on total redd counts) in Catherine Creek and Grande Ronde and Lostine rivers dropped to alarmingly low levels in 1994 and 1995. A total of 11, 3 and 16 redds were observed in 1994 in Catherine Creek, upper Grande Ronde River and Lostine River, respectively, and 14, 6 and 11 redds were observed in those same streams in 1995. In contrast, the maximum number of redds observed in the past was 505 in Catherine Creek (1971), 304 in the Grande Ronde River (1968) and 261 in 1956 in the Lostine River (Tranquilli et al 2003). Redd counts for index count areas (a standardized portion of the total stream) have also decreased dramatically for most Grande Ronde Basin streams from 1964-2002, dropping to as low as 37 redds in the 119.5 km in the index survey areas in 1995 from as high as 1,205 redds in the same area in 1969 (Table 1). All streams reached low points (0-6 redds in the index areas) in the 1990's, except those in which no redds were found for several years and surveys were discontinued, such as Spring, Sheep and Indian creeks which had a total of 109 redds in 1969. The Minam and Wenaha rivers are tributaries of the Grande Ronde River located primarily in wilderness areas. Chinook salmon numbers in these two streams (based on redd counts) also decreased dramatically beginning in the early 1970's (Table 1). Since then there have been a few years of increasing numbers of redds but counts have generally been 25-40% of the number seen in the 1960's. No hatchery fish have been released into either of these streams and we monitor them during spawning ground surveys for the presence of hatchery strays. These populations will be used as a type of control for evaluating our supplementation efforts in Catherine Creek, upper Grande Ronde River and Lostine River. In this way, we can attempt to filter out the effects of downstream variables, over which we have no control, when we interpret the results of the captive broodstock program as the F1 and F2 generations spawn and complete their life cycles in the wild. The Grande Ronde Basin Captive Broodstock Program was initiated because these chinook salmon populations had reached critical levels where dramatic and unprecedented efforts were needed to prevent extinction and preserve any future options for use of endemic fish for artificial propagation programs for recovery and mitigation. This program was designed to quickly increase numbers of returning adults, while maintaining the genetic integrity of each endemic population.« less

Spawning patterns of Pacific Lamprey in tributaries to the Willamette River, Oregon

USGS Publications Warehouse

Mayfield, M.P.; Schultz, Luke; Wyss, Lance A.; Clemens, B. J.; Schreck, Carl B.

2014-01-01

Addressing the ongoing decline of Pacific Lamprey Entosphenus tridentatus across its range along the west coast of North America requires an understanding of all life history phases. Currently, spawning surveys (redd counts) are a common tool used to monitor returning adult salmonids, but the methods are in their infancy for Pacific Lamprey. To better understand the spawning phase, our objective was to assess temporal spawning trends, redd abundance, habitat use, and spatial patterns of spawning at multiple spatial scales for Pacific Lamprey in the Willamette River basin, Oregon. Although redd density varied considerably across surveyed reaches, the observed temporal patterns of spawning were related to physical habitat and hydrologic conditions. As has been documented in studies in other basins in the Pacific Northwest, we found that redds were often constructed in pool tailouts dominated by gravel, similar to habitat used by spawning salmonids. Across the entire Willamette Basin, Pacific Lampreys appeared to select reaches with alluvial geology, likely because this is where gravel suitable for spawning accumulated. At the tributary scale, spawning patterns were not as strong, and in reaches with nonalluvial geology redds were more spatially clumped than in reaches with alluvial geology. These results can be used to help identify and conserve Pacific Lamprey spawning habitat across the Pacific Northwest.

Elements for the expected mechanisms on 'reduced emissions from deforestation and degradation, REDD' under UNFCCC

NASA Astrophysics Data System (ADS)

Mollicone, D.; Freibauer, A.; Schulze, E. D.; Braatz, S.; Grassi, G.; Federici, S.

2007-10-01

Carbon emissions from deforestation and degradation account for about 20% of global anthropogenic emissions. Strategies and incentives for reduced emissions from deforestation and degradation (REDD) have emerged as one of the most active areas in the international climate change negotiations under the United Nations Framework Convention on Climate Change (UNFCCC). While the current negotiations focus on a REDD mechanism in developing countries, it should be recognized that risks of carbon losses from forests occur in all climate zones and also in industrialized countries. A future climate change agreement would be more effective if it included all carbon losses and gains from land use in all countries and climate zones. The REDD mechanism will be an important step towards reducing emissions from land use change in developing countries, but needs to be followed by steps in other land use systems and regions. A national approach to REDD and significant coverage globally are needed to deal with the risk that deforestation and degradation activities are displaced rather than avoided. Favourable institutional and governance conditions need to be established that guarantee in the long-term a stable incentive and control system for maintaining forest carbon stocks. Ambitious emission reductions from deforestation and forest degradation need sustained financial incentives, which go beyond positive incentives for reduced emissions but also give incentives for sustainable forest management. Current data limitations need—and can be—overcome in the coming years to allow accurate accounting of reduced emissions from deforestation and degradation. A proper application of the conservativeness approach in the REDD context could allow a simplified reporting of emissions from deforestation in a first phase, consistent with the already agreed UNFCCC reporting principles.

Kootenai River Fisheries Investigations: Salmonid Studies Project Progress Report, 2007-2008 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paragamian, Vaughn L.; Walters, Jody; Maiolie, Melo

2009-04-09

This research report addresses bull trout Salvelinus confluentus and Redband trout Oncorhynchus mykiss redd surveys, population monitoring, trout distribution, and abundance surveys in the Kootenai River drainage of Idaho. The bull trout is one of several sport fish native to the Kootenai River, Idaho that no longer supports a fishery. Because bull trout are listed under the Endangered Species Act, population data will be vital to monitoring status relative to recovery goals. Thirty-three bull trout redds were found in North and South Callahan creeks and Boulder Creek in 2007. This is a decrease from 2006 and 2005 and less thanmore » the high count in 2003. However, because redd numbers have only been monitored since 2002, the data series is too short to determine bull trout population trends based on redd counts. Redband trout still provide an important Kootenai River sport fishery, but densities are low, at least partly due to limited recruitment. The redband trout proportional stock density (PSD) in 2007 increased from 2006 for a second year after a two-year decline in 2004 and 2005. This may indicate increased recruitment to or survival in the 201-305 mm length group due to the minimum 406 mm (16 inches) length limit initiated in 2002. We conducted 13 redd surveys and counted 44 redband trout redds from May 7 to June 3, 2007 in a 3.8 km survey reach on Twentymile Creek. We surveyed streams in the Kootenai River valley to look for barriers to trout migration. Man-made barriers, for at least part of the year, were found on Caboose, Debt, Fisher, and Twenty Mile creeks. Removing these barriers would increase spawning and rearing habitat for trout and help to restore trout fisheries in the Kootenai River.« less

Completing the Picture: Importance of Considering Participatory Mapping for REDD+ Measurement, Reporting and Verification (MRV)

PubMed Central

Rafanoharana, Serge; Boissière, Manuel; Wijaya, Arief; Wardhana, Wahyu

2016-01-01

Remote sensing has been widely used for mapping land cover and is considered key to monitoring changes in forest areas in the REDD+ Measurement, Reporting and Verification (MRV) system. But Remote Sensing as a desk study cannot capture the whole picture; it also requires ground checking. Therefore, complementing remote sensing analysis using participatory mapping can help provide information for an initial forest cover assessment, gain better understanding of how local land use might affect changes, and provide a way to engage local communities in REDD+. Our study looked at the potential of participatory mapping in providing complementary information for remotely sensed maps. The research sites were located in different ecological and socio-economic contexts in the provinces of Papua, West Kalimantan and Central Java, Indonesia. Twenty-one maps of land cover and land use were drawn with local community participation during focus group discussions in seven villages. These maps, covering a total of 270,000ha, were used to add information to maps developed using remote sensing, adding 39 land covers to the eight from our initial desk assessment. They also provided additional information on drivers of land use and land cover change, resource areas, territory claims and land status, which we were able to correlate to understand changes in forest cover. Incorporating participatory mapping in the REDD+ MRV protocol would help with initial remotely sensed land classifications, stratify an area for ground checks and measurement plots, and add other valuable social data not visible at the RS scale. Ultimately, it would provide a forum for local communities to discuss REDD+ activities and develop a better understanding of REDD+. PMID:27977685

Large scale land acquisitions and REDD+: a synthesis of conflicts and opportunities

NASA Astrophysics Data System (ADS)

Carter, Sarah; Manceur, Ameur M.; Seppelt, Ralf; Hermans-Neumann, Kathleen; Herold, Martin; Verchot, Lou

2017-03-01

Large scale land acquisitions (LSLA), and Reducing Emissions from Deforestation and forest Degradation (REDD+) are both land based phenomena which when occurring in the same area, can compete with each other for land. A quantitative analysis of country characteristics revealed that land available for agriculture, accessibility, and political stability are key explanatory factors for a country being targeted for LSLA. Surprisingly LSLA occur in countries with lower accessibility. Countries with good land availability, poor accessibility and political stability may become future targets if they do not already have LSLA. Countries which high levels of agriculture-driven deforestation and LSLA, should develop interventions which reduce forest loss driven either directly or indirectly by LSLA as part of their REDD+ strategies. Both host country and investor-side policies have been identified which could be used more widely to reduce conflicts between LSLA and REDD+. Findings from this research highlight the need for and can inform the development of national and international policies on land acquisitions including green acquisitions such as REDD+. Land management must be considered with all its objectives—including food security, biodiversity conservation, and climate change mitigation—in a coherent strategy which engages relevant stakeholders. This is not currently occurring and might be a key ingredient to achieve the targets under the Sustainable Development Goals 2 and 15 and 16 (related to food security and sustainable agriculture and the protection of forests) among others.

EVALUATING PROBABILITY SAMPLING STRATEGIES FOR ESTIMATING REDD COUNTS: AN EXAMPLE WITH CHINOOK SALMON (Oncorhynchus tshawytscha)

EPA Science Inventory

Precise, unbiased estimates of population size are an essential tool for fisheries management. For a wide variety of salmonid fishes, redd counts from a sample of reaches are commonly used to monitor annual trends in abundance. Using a 9-year time series of georeferenced censuses...

Migratory salmonid redd habitat characteristics in the Salmon River, New York

USGS Publications Warehouse

Johnson, James H.; Nack, Christopher C.; McKenna, James E.

2010-01-01

Non-native migratory salmonids ascend tributaries to spawn in all the Great Lakes. In Lake Ontario, these species include Chinook salmon (Oncorhynchus tshawytscha), coho salmon (O. kisutch), steelhead (O. mykiss), and brown trout (Salmo trutta). Although successful natural reproduction has been documented for many of these species, little research has been conducted on their spawning habitat. We examined the spawning habitat of these four species in the Salmon River, New York. Differences in fish size among the species were significantly correlated with spawning site selection. In the Salmon River, the larger species spawned in deeper areas with larger size substrate and made the largest redds. Discriminant function analysis correctly classified redds by species 64–100% of the time. The size of substrate materials below Lighthouse Hill Dam is within the preferred ranges for spawning for these four species indicating that river armoring has not negatively impacted salmonid production. Intra-specific and inter-specific competition for spawning sites may influence redd site selection for smaller salmonids and could be an impediment for Atlantic salmon (S. salar) restoration.

Participatory Carbon Monitoring System in Community Forests of Nepal

NASA Astrophysics Data System (ADS)

Karki, S.

2016-12-01

With the adoption of climate change agreement, Reducing emissions from deforestation and forest degradation (REDD) has advanced as a performance based policy instruments to curtailing the deforestation and forest degradation. Developing countries are working to get REDD ready. However, the readiness assessment process entails criteria such as REDD+ Safeguards are met, monitoring and reporting of emission reductions are verified (MRV). For counties to have MRV in place, technical know-how on measuring forest carbon and capacity of the human resources are limited. International Centre for Integrated Mountain Development (ICIMOD) together with its national partners implemented REDD+ pilot project from 2009-2013 in 105 community forests (CF) of three watersheds namely Charnawati, Kayarkhola and Ludikhola in Nepal. This paper discuss prototype of the participatory carbon monitoring and measurement approach tested in these105 CFs that is systematic, transparent, and cost effective. Additionally it will demonstrate the enhanced carbon stock data from 2010-2013 assembled at ICIMOD Regional Database Initiative are made freely available. Such application can be scaled up or considered in decision making for performance based payment schemes.

Forest Carbon Monitoring and Reporting for REDD+: What Future for Africa?

PubMed

Gizachew, Belachew; Duguma, Lalisa A

2016-11-01

A climate change mitigation mechanism for emissions reduction from reduced deforestation and forest degradation, plus forest conservation, sustainable management of forest, and enhancement of carbon stocks (REDD+), has received an international political support in the climate change negotiations. The mechanism will require, among others, an unprecedented technical capacity for monitoring, reporting and verification of carbon emissions from the forest sector. A functional monitoring, reporting and verification requires inventories of forest area, carbon stock and changes, both for the construction of forest reference emissions level and compiling the report on the actual emissions, which are essentially lacking in developing countries, particularly in Africa. The purpose of this essay is to contribute to a better understanding of the state and prospects of forest monitoring and reporting in the context of REDD+ in Africa. We argue that monitoring and reporting capacities in Africa fall short of the stringent requirements of the methodological guidance for monitoring, reporting and verification for REDD+, and this may weaken the prospects for successfully implementing REDD+ in the continent. We presented the challenges and prospects in the national forest inventory, remote sensing and reporting infrastructures. A North-South, South-South collaboration as well as governments own investments in monitoring, reporting and verification system could help Africa leapfrog in monitoring and reporting. These could be delivered through negotiations for the transfer of technology, technical capacities, and experiences that exist among developed countries that traditionally compile forest carbon reports in the context of the Kyoto protocol.

Assessment of the potential REDD+ as a new international support measure for GHG reduction

NASA Astrophysics Data System (ADS)

Kim, Y.; Ahn, J.; Kim, H.

2016-12-01

As part of the Paris Agreement, the mechanism for reducing emissions from deforestation and forest degradation in developing countries (REDD+) has high potential to simultaneously contribute to greenhouse gas (GHG) mitigation through forest conservation and poverty alleviation. Some of 162 Intended Nationally Determined Contributions (INDCs) submitted by 189 countries representing approximately 98.8% of global GHG emissions include not only unconditional mitigation goals but also conditional goals based on the condition of the provision of international support such as finance, technology transfer and capacity building. Considering REDD+ as one of the main mechanisms to support such work, this study selected ten countries from among Korea's 24 ODA priority partners, taking into consideration their conditional INDC targets alongside sectoral quantified targets such as land use, land-use change and forestry (LULUCF). The ten selected countries are Indonesia, Cambodia, Vietnam, Bangladesh, Sri Lanka, Ghana, Senegal, Colombia, Peru and Paraguay. Of these countries, most REDD+ projects have been conducted in Indonesia mainly due to the fact that 85% of the country's total GHG emissions are caused by forest conversion and peatland degradation. Therefore, GHG reduction rates and associated projected costs of the Indonesia's REDD+ projects were analyzed in order to offer guidance on the potential of REDD+ to contribute to other INDCs' conditional goals. The result showed that about 0.9 t CO2 ha-1 could be reduced at a cost of USD 23 per year. Applying this estimation to the Cambodian case, which has submitted a conditional INDC target of increasing its forest coverage by 60% (currently 57%) by 2030, suggests that financial support of USD 12.8 million would reduce CO2 emissions by about 5.1 million tones by increasing forest coverage. As there is currently no consideration of LULUCF in Cambodia's INDC, this result represents the opportunity for an additional contribution to achieving the country's conditional mitigation goals.

The abiotic environment of the interstitial of a small Swiss river in the foothills of the Alps and its influence on gravel spawning brown trout (Salmo trutta L.)

NASA Astrophysics Data System (ADS)

Schindler, Yael; Michel, Christian; Holm, Patricia; Alewell, Christine

2010-05-01

The hyporheic zone can be characterized by multiple abiotic parameters (e.g. bulk density, texture, temperature, oxygen, ammonium, nitrate) which are all influenced directly or indirectly by the exchange processes between surface water and groundwater. These processes can vary both in time and space and are mainly driven by river discharge, ground water level and flow patterns. The input of fine sediment particles can change water-riverbed interactions through river bed clogging potentially affecting the embryonal development and survival of gravel spawning fish, such as brown trout (Salmo trutta L.). With our investigations we aim to understand these complex interactions spatially and temporally on a relevant small scale, i.e. within individual artificial brown trout redds. We designed an experimental field setup to directly investigate i) the influence of the abiotic river and redd environment on brown trout embryo development and ii) the hydrological dynamics affecting the abiotic environment in artificial brown trout. Additionally, our setup allows investigating the temporal dynamics of i) fine-sediment infiltration into the artificial redds and ii) embryo survival to two distinct developmental stages (i.e. eyed stage and hatch) The experiment was conducted in three sites of a typical Swiss river (Enziwigger, Canton of Luzern) with a strongly modified morphology. Individual sites represented a high, medium and low fine-sediment load. In each site, six artificial redds (18 in total) were built and data were collected during the entire incubation phase. Redds were located in places where natural spawning of brown trout is present. We adapted multiple established methods to the smaller scale of our river to study the dynamics of the most relevant abiotic parameters potentially affecting embryo development: Oxygen content and temperature was monitored continuously in different depths, fine sediment (bedload, suspended sediment load and its input in the river bed) was measured weekly and water samples for DOC and nitrogen components analysis were collected regularly. In addition, all redds were equipped with mini piezometers to measure the hydraulic gradient through the redds. Finally, water stage and turbidity were monitored continuously. Results of the first spawning season will be presented. Dynamic of abiotic parameters and their influence on spawning of brown trout will be discussed.

Monitoring and Modeling Carbon Dynamics at a Network of Intensive Sites in the USA and Mexico

NASA Astrophysics Data System (ADS)

Birdsey, R.; Wayson, C.; Johnson, K. D.; Pan, Y.; Angeles, G.; De Jong, B. H.; Andrade, J. L.; Dai, Z.

2013-05-01

The Forest Services of the USA and Mexico, supported by NASA and USAID, have begun to establish a network of intensive forest carbon monitoring sites. These sites are used for research and teaching, developing forest management practices, and forging links to the needs of communities. Several of the sites have installed eddy flux towers to basic meteorology data and daily estimates of forest carbon uptake and release, the processes that determine forest growth. Field sampling locations at each site provide estimates of forest biomass and carbon stocks, and monitor forest dynamic processes such as growth and mortality rates. Remote sensing facilitates scaling up to the surrounding landscapes. The sites support information requirements for implementing programs such as Reducing Emissions from Deforestation and Forest Degradation (REDD+), enabling communities to receive payments for ecosystem services such as reduced carbon emissions or improved forest management. In addition to providing benchmark data for REDD+ projects, the sites are valuable for validating state and national estimates from satellite remote sensing and the national forest inventory. Data from the sites provide parameters for forest models that support strategic management analysis, and support student training and graduate projects. The intensive monitoring sites may be a model for other countries in Latin America. Coordination among sites in the USA, Mexico and other Latin American countries can ensure harmonization of approaches and data, and share experiences and knowledge among countries with emerging opportunities for implementing REDD+ and other conservation programs.

Modeling predicts that redd trampling by cattle may contribute to population declines of native trout

Treesearch

Douglas P. Peterson; Bruce E. Rieman; Michael K. Young; James A. Brammer

2010-01-01

Unrestricted livestock grazing can degrade aquatic ecosystems, and its effects on native vertebrate species are generally mediated by changes to physical habitat. Recently, high estimated rates of cattle trampling on artificial redds within federal grazing allotments in southwestern Montana, USA, has raised concern that direct mortality from trampling may contribute to...

Avoiding treatment bias of REDD+ monitoring by sampling with partial replacement

Treesearch

Michael Kohl; Charles T Scott; Andrew J Lister; Inez Demon; Daniel Plugge

2015-01-01

Implementing REDD+ renders the development of a measurement, reporting and verification (MRV) system necessary to monitor carbon stock changes. MRV systems generally apply a combination of remote sensing techniques and in-situ field assessments. In-situ assessments can be based on 1) permanent plots, which are assessed on all successive occasions, 2) temporary plots,...

Design and Rationale for a Randomized Controlled Trial to Reduce Readmissions among Patients with Depressive Symptoms

PubMed Central

Mitchell, Suzanne E.; Martin, Jessica M.; Krizman, Katherine; Sadikova, Ekaterina; Culpepper, Larry; Stewart, Sabrina K.; Brown, Jennifer Rose; Jack, Brian W.

2016-01-01

Background The Re-Engineered Discharge (Project RED) reduces 30-day readmission rates by 30 percent. However, our data indicates that for patients displaying depressive symptoms during hospitalization, Project RED is less effective in preventing unplanned readmission. We aim to examine the effectiveness of RED-D, a modified brief Cognitive behavioral therapy (CBT) protocol delivered as a post-discharge extension of the Re-Engineered Discharge, in reducing 30-day readmissions rates and emergency department (ED) use as well as depressive symptoms for medical patients with comorbid depressive symptoms. Methods This paper details the study design and implementation of an ongoing, federally funded randomized controlled trial of our post-discharge mental health intervention, RED-D, compared to the RED plus usual care. This research has two primary objectives: (1) to determine whether RED-D delivered telephonically by a mental health professional immediately following discharge is effective in reducing hospital readmission and emergency department use for patients displaying depressive symptoms during their inpatient stay, and (2) to examine whether this approach yields a clinically significant reduction in depressive symptoms. We intend to recruit 1200 participants randomized to our intervention, RED-D (n=600), and to RED plus usual care (n=600). Conclusions Hospitalized patients with depressive symptoms are at increased risk for 30-day readmission. We aim to conduct a randomized clinical trial to evaluate the comparative effectiveness of RED-D, our post-discharge modified brief CBT intervention compared to RED alone in reducing readmissions and depressive symptoms for this at-risk population. PMID:26343332

Design and rationale for a randomized controlled trial to reduce readmissions among patients with depressive symptoms.

PubMed

Mitchell, Suzanne E; Martin, Jessica M; Krizman, Katherine; Sadikova, Ekaterina; Culpepper, Larry; Stewart, Sabrina K; Brown, Jennifer Rose; Jack, Brian W

2015-11-01

The Re-Engineered Discharge (Project RED) reduces 30-day readmission rates by 30%. However, our data indicates that for patients displaying depressive symptoms during hospitalization, Project RED is less effective in preventing unplanned readmission. We aim to examine the effectiveness of RED-D, a modified brief Cognitive behavioral therapy (CBT) protocol delivered as a post-discharge extension of the Re-Engineered Discharge, in reducing 30-day readmissions rates and emergency department (ED) use as well as depressive symptoms for medical patients with comorbid depressive symptoms. This paper details the study design and implementation of an ongoing, federally funded randomized controlled trial of our post-discharge mental health intervention, RED-D, compared to the RED plus usual care. This research has two primary objectives: (1) to determine whether RED-D delivered telephonically by a mental health professional immediately following discharge is effective in reducing hospital readmission and emergency department use for patients displaying depressive symptoms during their inpatient stay, and (2) to examine whether this approach yields a clinically significant reduction in depressive symptoms. We intend to recruit 1200 participants randomized to our intervention, RED-D (n=600), and to RED plus usual care (n=600). Hospitalized patients with depressive symptoms are at increased risk for 30-day readmission. We aim to conduct a randomized clinical trial to evaluate the comparative effectiveness of RED-D, our post-discharge modified brief CBT intervention compared to RED alone in reducing readmissions and depressive symptoms for this at-risk population. Copyright © 2015 Elsevier Inc. All rights reserved.

Spawning characteristics of redband trout in a headwater stream in Montana

USGS Publications Warehouse

Muhlfeld, Clint C.

2002-01-01

I investigated the spawning characteristics of redband trout Oncorhynchus mykiss gairdneri (a rainbow trout subspecies) during the spring of 1998 in Basin Creek, a third-order headwater stream located in the Kootenai River drainage in northwestern Montana. I examined the timing of spawning as related to discharge and water temperature and analyzed microhabitat selection of 30 completed redds in a low-gradient (0.5–1.5%) reach. Redband trout spawned as flow declined after peak runoff and as mean daily water temperature exceeded 6.0C and maximum daily temperature exceeded 7.0C. Redband trout began spawning on 6 June (mean daily discharge = 2.1 m3/s), 10 d after the peak discharge (8.7 m3/s) occurred. The last redd was completed on 24 June, when discharge was 1.5 m3/s. The mean total redd length was 53 cm (SD = 14; range = 31–91 cm), and the mean total area was 51 cm2 (SD = 8; range= 46– 76 cm2). Eighty percent of the redds were located in pool tailouts, 13% in runs, and 7% in riffles. Spawning redband trout selected redd sites based on substrate size and water depth but not water velocity. Fish selected substrate sizes of 2–6 mm, water depths of 20–30 cm, and water velocities of 40–70 cm/s. My results suggest that redband trout in a low-gradient, third-order mountain stream found suitable spawning habitat in pool tail-outs that contained abundant gravels.

Does small-bodied salmon spawning activity enhance streambed mobility?

NASA Astrophysics Data System (ADS)

Hassan, Marwan A.; Tonina, Daniele; Buxton, Todd H.

2015-09-01

Female salmonids bury and lay their eggs in streambeds by digging a pit, which is then covered with sediment from a second pit that is dug immediately upstream. The spawning process alters streambed topography, winnows fine sediment, and mixes sediment in the active layer. The resulting egg nests (redds) contain coarser and looser sediments than those of unspawned streambed areas, and display a dune-like shape with an amplitude and length that vary with fish size, substrate conditions, and flow conditions. Redds increase local bed surface roughness (<10-1 channel width, W), but may reduce the size of macro bedforms by eroding reach-scale topography (100-101W). Research has suggested that spawning may increase flow resistance due to redd form drag, resulting in lower grain shear stress and less particle mobility. Spawning, also prevents streambed armoring by mixing surface and subsurface material, potentially increasing particle mobility. Here we use two-dimensional hydraulic modeling with detailed prespawning and postspawning bathymetries and field observations to test the effect of spawning by small-bodied salmonids on sediment transport. Our results show that topographical roughness from small salmon redds has negligible effects on shear stress at the reach-unit scale, and limited effects at the local scale. Conversely, results indicate sediment mixing reduces armoring and enhances sediment mobility, which increases potential bed load transport by subsequent floods. River restoration in fish-bearing streams should take into consideration the effects of redd excavation on channel stability. This is particularly important for streams that historically supported salmonids and are the focus of habitat restoration actions.

Network-scale spatial and temporal variation in Chinook salmon (Oncorhynchus tshawytscha) redd distributions: patterns inferred from spatially continuous replicate surveys

Treesearch

Daniel J. Isaak; Russell F. Thurow

2006-01-01

Spatially continuous sampling designs, when temporally replicated, provide analytical flexibility and are unmatched in their ability to provide a dynamic system view. We have compiled such a data set by georeferencing the network-scale distribution of Chinook salmon (Oncorhynchus tshawytscha) redds across a large wilderness basin (7330 km2) in...

Temporal variation in synchrony among chinook salmon (Oncorhynchus tshawytscha) redd counts from a wilderness area in central Idaho

Treesearch

D. J. Isaak; R. F. Thurow; B. E. Rieman; J. B. Dunham

2003-01-01

Metapopulation dynamics have emerged as a key consideration in conservation planning for salmonid fishes. Implicit to many models of spatially structured populations is a degree of synchrony, or correlation, among populations. We used a spatially and temporally extensive database of chinook salmon (Oncorhynchus tshawytscha) redd counts from a wilderness area in central...

Considering land tenure in REDD+ participatory measurement, reporting, and verification: A case study from Indonesia

PubMed Central

Bong, Indah Waty; DePuy, Walker Holton; Jihadah, Lina Farida

2017-01-01

Measurement, Reporting, and Verification (MRV) systems are thought to be essential for effective carbon accounting and joint REDD+ carbon, conservation, and social development goals. Community participation in MRV (PMRV) has been shown to be both cost effective and accurate, as well as a method to potentially advance stakeholder empowerment and perceptions of legitimacy. Recognizing land tenure as a long-standing point of tension in REDD+ planning, we argue that its engagement also has a key role to play in developing a legitimate PMRV. Using household surveys, key informant interviews, and participatory mapping exercises, we present three ‘lived’ land tenure contexts in Indonesia to highlight their socially and ecologically situated natures and to consider the role of tenure pluralism in shaping PMRV. We then raise and interrogate three questions for incorporating lived land tenure contexts into a legitimate PMRV system: 1) Who holds the right to conduct PMRV activities?; 2) How are the impacts of PMRV differentially distributed within local communities?; and 3) What is the relationship between tenure security and motivation to participate in PMRV? We conclude with implementation lessons for REDD+ practitioners, including the benefits of collaborative practices, and point to critical areas for further research. PMID:28406908

Considering land tenure in REDD+ participatory measurement, reporting, and verification: A case study from Indonesia.

PubMed

Felker, Mary Elizabeth; Bong, Indah Waty; DePuy, Walker Holton; Jihadah, Lina Farida

2017-01-01

Measurement, Reporting, and Verification (MRV) systems are thought to be essential for effective carbon accounting and joint REDD+ carbon, conservation, and social development goals. Community participation in MRV (PMRV) has been shown to be both cost effective and accurate, as well as a method to potentially advance stakeholder empowerment and perceptions of legitimacy. Recognizing land tenure as a long-standing point of tension in REDD+ planning, we argue that its engagement also has a key role to play in developing a legitimate PMRV. Using household surveys, key informant interviews, and participatory mapping exercises, we present three 'lived' land tenure contexts in Indonesia to highlight their socially and ecologically situated natures and to consider the role of tenure pluralism in shaping PMRV. We then raise and interrogate three questions for incorporating lived land tenure contexts into a legitimate PMRV system: 1) Who holds the right to conduct PMRV activities?; 2) How are the impacts of PMRV differentially distributed within local communities?; and 3) What is the relationship between tenure security and motivation to participate in PMRV? We conclude with implementation lessons for REDD+ practitioners, including the benefits of collaborative practices, and point to critical areas for further research.

Validity and reliability of in-situ air conduction thresholds measured through hearing aids coupled to closed and open instant-fit tips.

PubMed

O'Brien, Anna; Keidser, Gitte; Yeend, Ingrid; Hartley, Lisa; Dillon, Harvey

2010-12-01

Audiometric measurements through a hearing aid ('in-situ') may facilitate provision of hearing services where these are limited. This study investigated the validity and reliability of in-situ air conduction hearing thresholds measured with closed and open domes relative to thresholds measured with insert earphones, and explored sources of variability in the measures. Twenty-four adults with sensorineural hearing impairment attended two sessions in which thresholds and real-ear-to-dial-difference (REDD) values were measured. Without correction, significantly higher low-frequency thresholds in dB HL were measured in-situ than with insert earphones. Differences were due predominantly to differences in ear canal SPL, as measured with the REDD, which were attributed to leaking low-frequency energy. Test-retest data yielded higher variability with the closed dome coupling due to inconsistent seals achieved with this tip. For all three conditions, inter-participant variability in the REDD values was greater than intra-participant variability. Overall, in-situ audiometry is as valid and reliable as conventional audiometry provided appropriate REDD corrections are made and ambient sound in the test environment is controlled.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ford, Michael J.; Williamson, Kevin S.

We investigated differences in the statistical power to assign parentage between an artificially propagated and wild salmon population. The propagated fish were derived from the wild population, and are used to supplement its abundance. Levels of genetic variation were similar between the propagated and wild groups at 11 microsatellite loci, and exclusion probabilities were >0.999999 for both groups. The ability to unambiguously identify a pair of parents for each sampled progeny was much lower than expected, however. Simulations demonstrated that the proportion of cases the most likely pair of parents were the true parents was lower for propagated parents thanmore » for wild parents. There was a clear relationship between parentage assignment ability and the degree of linkage disequilibrium, the estimated effective number of breeders that produced the parents, and the size of the largest family within the potential parents. If a stringent threshold for parentage assignment was used, estimates of relative fitness were biased downward for the propagated fish. The bias appeared to be largely eliminated by either fractionally assigning progeny among parents in proportion to their likelihood of parentage, or by assigning progeny to the most likely set of parents without using a statistical threshold. We used a DNA-based parentage analysis to measure the relative reproductive success of hatchery- and natural-origin spring Chinook salmon in the natural environment. Both male and female hatchery-origin fish produced far fewer juvenile progeny per parent when spawning naturally than did natural origin fish. Differences in age structure, spawning location, weight and run timing were responsible for some of the difference in fitness. Male size and age had a large influence on fitness, with larger and older males producing more offspring than smaller or younger individuals. Female size had a significant effect on fitness, but the effect was much smaller than the effect of size on male fitness. For both sexes, run time had a smaller but still significant effect on fitness, with earlier returning fish favored. Spawning location within the river had a significant effect on fitness for both males and females, and for females explained most of the reduced fitness observed for hatchery fish in this population. While differences have been reported in the relative reproductive success of hatchery and naturally produced salmonids Oncorhynchus spp., factors explaining the differences are often confounded. We examined the spawning site habitat and redd structure variables of hatchery and naturally produced spring Chinook salmon O. tshawytscha of known size that spawned in two tributaries of the Wenatchee River. We controlled for variability in spawning habitat by limiting our analysis to redds found within four selected reaches. No difference in the instantaneous spawner density or location of the redd in the stream channel was detected between reaches. Within each reach, no difference in the fork length or weight of hatchery and naturally produced fish was detected. While most variables differed between reaches, we found no difference in redd characteristics within a reach between hatchery and naturally produced females. Correlation analysis of fish size and redd characteristics found several weak but significant relationships suggesting larger fish contract larger redds in deeper water. Spawner density was inversely related to several redd structure variables suggesting redd size may decrease as spawner density increases. Results should be considered preliminary until samples size and statistical power goals are reached in future years. Trends in relative reproductive success of hatchery and naturally produced spring Chinook salmon Oncorhynchus tshawytscha in the Wenatchee Basins suggest females that spawn in the upper reaches of the tributaries produced a great number of offspring compared to females that spawn in the lower reaches of the tributaries. To better understand this trend, redd microhabitat data was collected from spring Chinook salmon that spawned in the Chiwawa River and Nason Creek, the primary spawning tributaries in the Wenatchee Basin. The objective of the study was to examine the influence of habitat and spawner density on spawning site and redd structure characteristics. We analyzed 27 variables of redd microhabitat data collected from the upper and lower most reaches of each study stream. In both streams, we found redds in the upper most reaches to be significantly larger (length and width) and deeper (bowl depth). Spawner density was significantly greater in the lower Chiwawa River compared to the upper reach. No difference in spawner density was detected between reaches in Nason Creek (P = 0.54). Data should be considered preliminary until sample size goals are achieved.« less

Kootenai River Fisheries Investigations; Rainbow and Bull Trout Recruitment, 2002-2003 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walters, Jody P.

Rainbow trout Oncorhynchus mykiss provide the most important sport fishery in the Kootenai River, Idaho, but densities and catch rates are low. Low recruitment is one possible factor limiting the rainbow trout population. Bull trout Salvelinus confluentus also exist in the Kootenai River, but little is known about this population. Research reported here addresses the following objectives for the Kootenai River, Idaho: increase rainbow trout recruitment, identify rainbow and bull trout spawning tributaries and migration timing, establish baseline data on bull trout redd numbers in tributaries, and improve the rainbow trout population size structure. Six adult rainbow trout were movedmore » to spawning habitat upstream of a potential migration barrier on Caboose Creek, but numbers of redds and age-0 out-migrants did not appear to increase relative to a reference stream. Measurements taken on the Moyie River indicated the gradient is inadequate to deliver suitable flows to a proposed rainbow trout spawning channel. Summer water temperatures measured in the Deep Creek drainage sometimes exceeded 24 C, higher than those reported as suitable for rainbow trout. Radio-tagged rainbow trout were located in Boulder Creek during the spring spawning season, and bull trout were located in the Moyie River and O'Brien Creek, Montana in the fall. Bull trout spawning migration timing was related to increases in Kootenai River flows. Bull trout redd surveys documented 19 redds on Boulder Creek and North and South Callahan creeks. Fall 2002 electrofishing showed that the Kootenai River rainbow trout proportional stock density was 54, higher than prior years when more liberal fishing regulations were in effect. Boulder Creek produces the highest number of age-0 rainbow trout out-migrants upstream of Bonners Ferry, but the survival rate of these out-migrants upon reaching the Kootenai River is unknown. Determining juvenile survival rates and sources of mortality could aid management efforts to increase rainbow trout recruitment. North and South Callahan creeks support the largest spawning population of bull trout in the Kootenai River drainage, Idaho, so management of the watershed should consider bull trout as high priority.« less

Use of the 'real-ear to dial difference' to derive real-ear SPL from hearing level obtained with insert earphones.

PubMed

Munro, K J; Lazenby, A

2001-10-01

The electroacoustic characteristics of a hearing instrument are normally selected for individuals using data obtained during audiological assessment. The precise inter-relationship between the electroacoustic and audiometric variables is most readily appreciated when they have been measured at the same reference point, such as the tympanic membrane. However, it is not always possible to obtain the real-ear sound pressure level (SPL) directly if this is below the noise floor of the probe-tube microphone system or if the subject is unco-operative. The real-ear SPL may be derived by adding the subject's real-ear to dial difference (REDD) acoustic transform to the audiometer dial setting. The aim of the present study was to confirm the validity of the Audioscan RM500 to measure the REDD with the ER-3A insert earphone. A probe-tube microphone was used to measure the real-ear SPL and REDD from the right ears of 16 adult subjects ranging in age from 22 to 41 years (mean age 27 years). Measurements were made from 0.25 kHz to 6 kHz at a dial setting of 70 dB with an ER-3A insert earphone and two earmould configurations: the EAR-LINK foam ear-tip and the subjects' customized skeleton earmoulds. Mean REDD varied as a function of frequency but was typically approximately 12 dB with a standard deviation (SD) of +/- 1.7 dB and +/- 2.7 dB for the foam ear-tip and customized earmould, respectively. The mean test-retest difference of the REDD varied with frequency but was typically 0.5 dB (SD 1 dB). Over the frequency range 0.5-4 kHz, the derived values were found to be within 5 dB of the measured values in 95% of subjects when using the EAR-LINK foam ear-tip and within 4 dB when using the skeleton earmould. The individually measured REDD transform can be used in clinical practice to derive a valid estimate of real-ear SPL when it has not been possible to measure this directly.

Characteristics of the Remote Sensing Data Used in the Proposed Unfccc REDD+ Forest Reference Emission Levels (frels)

NASA Astrophysics Data System (ADS)

Johnson, B. A.; Scheyvens, H.; Samejima, H.; Onoda, M.

2016-06-01

Developing countries must submit forest reference emission levels (FRELs) to the UNFCCC to receive incentives for REDD+ activities (e.g. reducing emissions from deforestation/forest degradation, sustainable management of forests, forest carbon stock conservation/enhancement). These FRELs are generated based on historical CO2 emissions in the land use, land use change, and forestry sector, and are derived using remote sensing (RS) data and in-situ forest carbon measurements. Since the quality of the historical emissions estimates is affected by the quality and quantity of the RS data used, in this study we calculated five metrics (i-v below) to assess the quality and quantity of the data that has been used thus far. Countries could focus on improving on one or more of these metrics for the submission of future FRELs. Some of our main findings were: (i) the median percentage of each country mapped was 100%, (ii) the median historical timeframe for which RS data was used was 11.5 years, (iii) the median interval of forest map updates was 4.5 years, (iv) the median spatial resolution of the RS data was 30m, and (v) the median number of REDD+ activities that RS data was used for operational monitoring of was 1 (typically deforestation). Many new sources of RS data have become available in recent years, so complementary or alternative RS data sets for generating future FRELs can potentially be identified based on our findings; e.g. alternative RS data sets could be considered if they have similar or higher quality/quantity than the currently-used data sets.

Historic Emissions from Deforestation and Forest Degradation in Mato Grosso, Brazil: 1. Source Data Uncertainties

NASA Technical Reports Server (NTRS)

Morton, Douglas C.; Sales, Marcio H.; Souza, Carlos M., Jr.; Griscom, Bronson

2011-01-01

Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008. Results: Deforestation estimates showed good agreement for multi-year trends of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by >20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C/ha, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas. Conclusions: Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions.

Multiscale hydrogeomorphic influences on bull trout (Salvelinus confluentus) spawning habitat

USGS Publications Warehouse

Bean, Jared R; Wilcox, Andrew C.; Woessner, William W.; Muhlfeld, Clint C.

2015-01-01

We investigated multiscale hydrogeomorphic influences on the distribution and abundance of bull trout (Salvelinus confluentus) spawning in snowmelt-dominated streams of the upper Flathead River basin, northwestern Montana. Within our study reaches, bull trout tended to spawn in the finest available gravel substrates. Analysis of the mobility of these substrates, based on one-dimensional hydraulic modeling and calculation of dimensionless shear stresses, indicated that bed materials in spawning reaches would be mobilized at moderate (i.e., 2-year recurrence interval) high-flow conditions, although the asynchronous timing of the fall–winter egg incubation period and typical late spring – early summer snowmelt high flows in our study area may limit susceptibility to redd scour under current hydrologic regimes. Redd occurrence also tended to be associated with concave-up bedforms (pool tailouts) with downwelling intragravel flows. Streambed temperatures tracked stream water diurnal temperature cycles to a depth of at least 25 cm, averaging 6.1–8.1 °C in different study reaches during the spawning period. Ground water provided thermal moderation of stream water for several high-density spawning reaches. Bull trout redds were more frequent in unconfined alluvial valley reaches (8.5 versus 5.0 redds·km−1 in confined valley reaches), which were strongly influenced by hyporheic and groundwater – stream water exchange. A considerable proportion of redds were patchily distributed in confined valley reaches, however, emphasizing the influence of local physical conditions in supporting bull trout spawning habitat. Moreover, narrowing or “bounding” of these alluvial valley segments did not appear to be important. Our results suggest that geomorphic, thermal, and hydrological factors influence bull trout spawning occurrence at multiple spatial scales.

Enhanced incubation success for kokanee spawning in groundwater upwelling sites in a small Idaho stream

Treesearch

James W. Garrett; David H. Bennett; Frank O. Frost; Russell F. Thurow

1998-01-01

Kokanee (Oncorhynchus nerka lacustrine sockeye salmon) spawned in groundwater upwelling in the North Fork of the Payette River, Idaho. Intragravel water temperatures in groundwater-influenced redds exceeded surface flow water temperature by 2.4–2.6°C. In redds without groundwater influence, intragravel and water column temperatures did not differ by more than 0.2°C....

Motivation Matters: Lessons for REDD+ Participatory Measurement, Reporting and Verification from Three Decades of Child Health Participatory Monitoring in Indonesia.

PubMed

Ekowati, Dian; Hofstee, Carola; Praputra, Andhika Vega; Sheil, Douglas

2016-01-01

Participatory Measurement, Reporting and Verification (PMRV), in the context of reducing emissions from deforestation and forest degradation with its co-benefits (REDD+) requires sustained monitoring and reporting by community members. This requirement appears challenging and has yet to be achieved. Other successful, long established, community self-monitoring and reporting systems may provide valuable lessons. The Indonesian integrated village healthcare program (Posyandu) was initiated in the 1980s and still provides effective and successful participatory measurement and reporting of child health status across the diverse, and often remote, communities of Indonesia. Posyandu activities focus on the growth and development of children under the age of five by recording their height and weight and reporting these monthly to the Ministry of Health. Here we focus on the local Posyandu personnel (kaders) and their motivations and incentives for contributing. While Posyandu and REDD+ measurement and reporting activities differ, there are sufficient commonalities to draw useful lessons. We find that the Posyandu kaders are motivated by their interests in health care, by their belief that it benefits the community, and by encouragement by local leaders. Recognition from the community, status within the system, training opportunities, competition among communities, and small payments provide incentives to sustain participation. We examine these lessons in the context of REDD+.

Community assessment of tropical tree biomass: challenges and opportunities for REDD.

PubMed

Theilade, Ida; Rutishauser, Ervan; Poulsen, Michael K

2015-12-01

REDD+ programs rely on accurate forest carbon monitoring. Several REDD+ projects have recently shown that local communities can monitor above ground biomass as well as external professionals, but at lower costs. However, the precision and accuracy of carbon monitoring conducted by local communities have rarely been assessed in the tropics. The aim of this study was to investigate different sources of error in tree biomass measurements conducted by community monitors and determine the effect on biomass estimates. Furthermore, we explored the potential of local ecological knowledge to assess wood density and botanical identification of trees. Community monitors were able to measure tree DBH accurately, but some large errors were found in girth measurements of large and odd-shaped trees. Monitors with experience from the logging industry performed better than monitors without previous experience. Indeed, only experienced monitors were able to discriminate trees with low wood densities. Local ecological knowledge did not allow consistent tree identification across monitors. Future REDD+ programmes may benefit from the systematic training of local monitors in tree DBH measurement, with special attention given to large and odd-shaped trees. A better understanding of traditional classification systems and concepts is required for local tree identifications and wood density estimates to become useful in monitoring of biomass and tree diversity.

EDITORIAL: Tropical deforestation and greenhouse gas emissions

NASA Astrophysics Data System (ADS)

Gibbs, Holly K.; Herold, Martin

2007-10-01

Carbon emissions from tropical deforestation have long been recognized as a key component of the global carbon budget, and more recently of our global climate system. Tropical forest clearing accounts for roughly 20% of anthropogenic carbon emissions and destroys globally significant carbon sinks (IPCC 2007). Global climate policy initiatives are now being proposed to address these emissions and to more actively include developing countries in greenhouse gas mitigation (e.g. Santilli et al 2005, Gullison et al 2007). In 2005, at the Conference of the Parties (COP) in Montreal, the United Nations Framework Convention on Climate Change (UNFCCC) launched a new initiative to assess the scientific and technical methods and issues for developing policy approaches and incentives to reduce emissions from deforestation and degradation (REDD) in developing countries (Gullison et al 2007). Over the last two years the methods and tools needed to estimate reductions in greenhouse gas emissions from deforestation have quickly evolved, as the scientific community responded to the UNFCCC policy needs. This focus issue highlights those advancements, covering some of the most important technical issues for measuring and monitoring emissions from deforestation and forest degradation and emphasizing immediately available methods and data, as well as future challenges. Elements for effective long-term implementation of a REDD mechanism related to both environmental and political concerns are discussed in Mollicone et al. Herold and Johns synthesize viewpoints of national parties to the UNFCCC on REDD and expand upon key issues for linking policy requirements and forest monitoring capabilities. In response to these expressed policy needs, they discuss a remote-sensing-based observation framework to start REDD implementation activities and build historical deforestation databases on the national level. Achard et al offer an assessment of remote sensing measurements across the world's tropical forests that can provide key consistency and prioritization for national-level efforts. Gibbs et al calculate a range of national-level forest carbon stock estimates that can be used immediately, and also review ground-based and remote sensing approaches to estimate national-level tropical carbon stocks with increased accuracy. These papers help illustrate that methodologies and tools are indeed available to estimate emissions from deforestation. Clearly, important technical challenges remain (e.g. quantifying degradation, assessing uncertainty, verification procedures, capacity building, and Landsat data continuity) but we now have a sufficient technical base to support REDD early actions and readiness mechanisms for building national monitoring systems. Thus, we enter the COP 13 in Bali, Indonesia with great hope for a more inclusive climate policy encompassing all countries and emissions sources from both land-use and energy sectors. Our understanding of tropical deforestation and carbon emissions is improving and with that, opportunities to conserve tropical forests and the host of ecosystem services they provide while also increasing revenue streams in developing countries through economic incentives to avoid deforestation and degradation. References Gullison R E et al 2007 Tropical forests and climate policy Science 316 985 6 Intergovernmental Panel on Climate Change (IPCC) 2007 Climate Change 2007: The Physical Science Basis: Summary for Policymakers http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-spm.pdf Santilli M et al 2005 Tropical deforestation and the Kyoto Protocol: an editorial essay Clim. Change 71 267 76 Focus on Tropical Deforestation and Greenhouse Gas Emissions Contents The articles below represent the first accepted contributions and further additions will appear in the near future. Pan-tropical monitoring of deforestation F Achard, R DeFries, H Eva, M Hansen, P Mayaux and H-J Stibig Monitoring and estimating tropical forest carbon stocks: making REDD a reality Holly K Gibbs, Sandra Brown, John O Niles and Jonathan A Foley Elements for the expected mechanisms on 'reduced emissions from deforestation and degradation, REDD' under UNFCCC D Mollicone, A Freibauer, E D Schulze, S Braatz, G Grassi and S Federici

Coupling hydrodynamic modeling and empirical measures of bed mobility to assess the risk of redd scour on a large regulated river

Treesearch

Christine L. May; Bonnie S. Pryor; Thomas E. Lisle; Margaret M. Lang

2009-01-01

n order to assess the risk of scour and fill of spawning redds during floods, an understanding of the relations among river discharge, bed mobility, and scour and fill depths in areas of the streambed heavily utilized by spawning salmon is needed. Our approach coupled numerical flow modeling and empirical data from the Trinity River, California, to quantify spatially...

SAR For REDD+ in the Mai Ndombe District (DRC)

NASA Astrophysics Data System (ADS)

Haarpaintner, Jorg

2016-08-01

The overall goal of the project "SAR for REDD" is to provide cloud-penetrating satellite synthetic aperture radar (SAR) pre-processing and analysing capabilities and tools to support operational tropical forest monitoring in REDD countries and primarily in Africa. The project's end-user is the Observatoir Satellitale des Forêts d'Afrique Centrale (OSFAC).This paper presents an overall summary of the project and shows first results of the satellite products, that will be delivered to the user in addition to software tools to enhance the user's own technical capacity.The products shown here are SAR mosaics and derived forest-land cover maps based on C-band Sentinel-1A data for 2015, ALOS-PALSAR data for the period 2007-2010 and ALOS-2 PALSAR-2 for 2015. In addition, a forest cover change map from 2007 to 2010 based on ALOS PALSAR has been produced and is compared to results from the Global Forest Cover project [1].

Fine-scale natal homing and localized movement as shaped by sex and spawning habitat in chinook salmon

USGS Publications Warehouse

Neville, Helen; Isaak, Daniel; Dunham, J.B.; Thurow, Russel; Rieman, B.

2006-01-01

Natal homing is a hallmark of the life history of salmonid fishes, but the spatial scale of homing within local, naturally reproducing salmon populations is still poorly understood. Accurate homing (paired with restricted movement) should lead to the existence of fine-scale genetic structuring due to the spatial clustering of related individuals on spawning grounds. Thus, we explored the spatial resolution of natal homing using genetic associations among individual Chinook salmon (Oncorhynchus tshawytscha) in an interconnected stream network. We also investigated the relationship between genetic patterns and two factors hypothesized to influence natal homing and localized movements at finer scales in this species, localized patterns in the distribution of spawning gravels and sex. Spatial autocorrelation analyses showed that spawning locations in both sub-basins of our study site were spatially clumped, but the upper sub-basin generally had a larger spatial extent and continuity of redd locations than the lower sub-basin, where the distribution of redds and associated habitat conditions were more patchy. Male genotypes were not autocorrelated at any spatial scale in either sub-basin. Female genotypes showed significant spatial autocorrelation and genetic patterns for females varied in the direction predicted between the two sub-basins, with much stronger autocorrelation in the sub-basin with less continuity in spawning gravels. The patterns observed here support predictions about differential constraints and breeding tactics between the two sexes and the potential for fine-scale habitat structure to influence the precision of natal homing and localized movements of individual Chinook salmon on their breeding grounds.

Breaking the vicious circle of illegal logging in Indonesia.

PubMed

Linkie, Matthew; Sloan, Sean; Kasia, Rahmad; Kiswayadi, Dedy; Azmi, Wahdi

2014-08-01

The government of Indonesia, which presides over 10% of the world's tropical forests, has set ambitious targets to cut its high deforestation rates through an REDD+ scheme (Reducing Emissions from Deforestation and forest Degradation). This will require strong law enforcement to succeed. Yet, strategies that have accomplished this are rare and, along with past failures, tend not to be documented. We evaluated a multistakeholder approach that seeks to tackle illegal logging in the carbon-rich province of Aceh, Sumatra. From 2008 to 2009, Fauna & Flora International established and supported a community-based informant network for the 738,000 ha Ulu Masen ecosystem. The network reported 190 forest offenses to local law enforcement agencies, which responded with 86 field operations that confiscated illicit vehicles, equipment, and timber, and arrested 138 illegal logging suspects. From 45 cases subsequently monitored, 64.4% proceeded to court, from which 90.0% of defendants received a prison sentence or a verbal warning for a first offense. Spatial analyses of illegal logging and timber storage incidents predicted that illegal activities would be more effectively deterred by law enforcement operations that targeted the storage sites. Although numerous clusters of incidents were identified, they were still widespread reflecting the ubiquity of illegal activities. The multistakeholder results were promising, but illegal logging still persisted at apparently similar levels at the project's end, indicating that efforts need to be further strengthened. Nevertheless, several actions contributed to the law enforcement achievements: strong political will; strong stakeholder support; and funding that could be promptly accessed. These factors are highlighted as prerequisites for achieving Indonesia's ambitious REDD+ goals. © 2014 Society for Conservation Biology.

Motivation Matters: Lessons for REDD+ Participatory Measurement, Reporting and Verification from Three Decades of Child Health Participatory Monitoring in Indonesia

PubMed Central

Ekowati, Dian; Hofstee, Carola; Praputra, Andhika Vega; Sheil, Douglas

2016-01-01

Participatory Measurement, Reporting and Verification (PMRV), in the context of reducing emissions from deforestation and forest degradation with its co-benefits (REDD+) requires sustained monitoring and reporting by community members. This requirement appears challenging and has yet to be achieved. Other successful, long established, community self-monitoring and reporting systems may provide valuable lessons. The Indonesian integrated village healthcare program (Posyandu) was initiated in the 1980s and still provides effective and successful participatory measurement and reporting of child health status across the diverse, and often remote, communities of Indonesia. Posyandu activities focus on the growth and development of children under the age of five by recording their height and weight and reporting these monthly to the Ministry of Health. Here we focus on the local Posyandu personnel (kaders) and their motivations and incentives for contributing. While Posyandu and REDD+ measurement and reporting activities differ, there are sufficient commonalities to draw useful lessons. We find that the Posyandu kaders are motivated by their interests in health care, by their belief that it benefits the community, and by encouragement by local leaders. Recognition from the community, status within the system, training opportunities, competition among communities, and small payments provide incentives to sustain participation. We examine these lessons in the context of REDD+. PMID:27806053

Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements?

PubMed

Zhao, Mingxu; Brofeldt, Søren; Li, Qiaohong; Xu, Jianchu; Danielsen, Finn; Læssøe, Simon Bjarke Lægaard; Poulsen, Michael Køie; Gottlieb, Anna; Maxwell, James Franklin; Theilade, Ida

2016-01-01

Biodiversity conservation is a required co-benefit of REDD+. Biodiversity monitoring is therefore needed, yet in most areas it will be constrained by limitations in the available human professional and financial resources. REDD+ programs that use forest plots for biomass monitoring may be able to take advantage of the same data for detecting changes in the tree diversity, using the richness and abundance of canopy trees as a proxy for biodiversity. If local community members are already assessing the above-ground biomass in a representative network of forest vegetation plots, it may require minimal further effort to collect data on the diversity of trees. We compare community members and trained scientists' data on tree diversity in permanent vegetation plots in montane forest in Yunnan, China. We show that local community members here can collect tree diversity data of comparable quality to trained botanists, at one third the cost. Without access to herbaria, identification guides or the Internet, community members could provide the ethno-taxonomical names for 95% of 1071 trees in 60 vegetation plots. Moreover, we show that the community-led survey spent 89% of the expenses at village level as opposed to 23% of funds in the monitoring by botanists. In participatory REDD+ programs in areas where community members demonstrate great knowledge of forest trees, community-based collection of tree diversity data can be a cost-effective approach for obtaining tree diversity information.

Nuclear factor of activated T-cells 5 increases intestinal goblet cell differentiation through an mTOR/Notch signaling pathway

PubMed Central

Zhou, Yuning; Wang, Qingding; Weiss, Heidi L.; Evers, B. Mark

2014-01-01

The intestinal mucosa undergoes a continual process of proliferation, differentiation, and apoptosis that is regulated by multiple signaling pathways. Previously, we have shown that the nuclear factor of activated T-cells 5 (NFAT5) is involved in the regulation of intestinal enterocyte differentiation. Here we show that treatment with sodium chloride (NaCl), which activates NFAT5 signaling, increased mTORC1 repressor regulated in development and DNA damage response 1 (REDD1) protein expression and inhibited mTOR signaling; these alterations were attenuated by knockdown of NFAT5. Knockdown of NFAT5 activated mammalian target of rapamycin (mTOR) signaling and significantly inhibited REDD1 mRNA expression and protein expression. Consistently, overexpression of NFAT5 increased REDD1 expression. In addition, knockdown of REDD1 activated mTOR and Notch signaling, whereas treatment with mTOR inhibitor rapamycin repressed Notch signaling and increased the expression of the goblet cell differentiation marker mucin 2 (MUC2). Moreover, knockdown of NFAT5 activated Notch signaling and decreased MUC2 expression, while overexpression of NFAT5 inhibited Notch signaling and increased MUC2 expression. Our results demonstrate a role for NFAT5 in the regulation of mTOR signaling in intestinal cells. Importantly, these data suggest that NFAT5 participates in the regulation of intestinal homeostasis via the suppression of mTORC1/Notch signaling pathway. PMID:25057011

Spatially explicit estimates of forest carbon emissions, mitigation costs and REDD+ opportunities in Indonesia

NASA Astrophysics Data System (ADS)

Graham, Victoria; Laurance, Susan G.; Grech, Alana; Venter, Oscar

2017-04-01

Carbon emissions from the conversion and degradation of tropical forests contribute to anthropogenic climate change. Implementing programs to reduce emissions from tropical forest loss in Southeast Asia are perceived to be expensive due to high opportunity costs of avoided deforestation. However, these costs are not representative of all REDD+ opportunities as they are typically based on average costs across large land areas and are primarily for reducing deforestation from oil palm or pulp concessions. As mitigation costs and carbon benefits can vary according to site characteristics, spatially-explicit information should be used to assess cost-effectiveness and to guide the allocation of scarce REDD+ resources. We analyzed the cost-effectiveness of the following REDD+ strategies in Indonesia, one of the world’s largest sources of carbon emissions from deforestation: halting additional deforestation in protected areas, timber and oil palm concessions, reforesting degraded land and employing reduced-impact logging techniques in logging concessions. We discover that when spatial variation in costs and benefits is considered, low-cost options emerged even for the two most expensive strategies: protecting forests from conversion to oil palm and timber plantations. To achieve a low emissions reduction target of 25%, we suggest funding should target deforestation in protected areas, and oil palm and timber concessions to maximize emissions reductions at the lowest cumulative cost. Low-cost opportunities for reducing emissions from oil palm are where concessions have been granted on deep peat deposits or unproductive land. To achieve a high emissions reduction target of 75%, funding is allocated across all strategies, emphasizing that no single strategy can reduce emissions cost-effectively across all of Indonesia. These findings demonstrate that by using a spatially-targeted approach to identify high priority locations for reducing emissions from deforestation and forest degradation, REDD+ resources can be allocated cost-effectively across Indonesia.

Annual variation of spawning Cutthroat Trout in a small Western USA stream: A case study with implications for the conservation of potamodromous trout life history diversity

USGS Publications Warehouse

Bennett, Stephen; Al-Chokhachy, Robert K.; Roper, Brett B.; Budy, Phaedra

2014-01-01

Little is known about the variability in the spatial and temporal distribution of spawning potamodromous trout despite decades of research directed at salmonid spawning ecology and the increased awareness that conserving life history diversity should be a focus of management. We monitored a population of fluvial–resident Bonneville Cutthroat Trout Oncorhynchus clarkii utah in a tributary to the Logan River, Utah, from 2006 to 2012 to gain insight into the distribution and timing of spawning and what factors may influence these spawning activities. We monitored Bonneville Cutthroat Trout using redd surveys with multiple observers and georeferenced redd locations. We documented an extended spawning period that lasted from late April to mid-July. The onset, median, and end of spawning was best predicted by the mean maximum water temperature during the first 13 weeks of the year (F = 130. 4, df = 5, R2 = 0.96, P < 0.0001) with spawning beginning and ending earlier in years that had warmer water temperatures prior to spawning. The distribution of redds was clumped each year and the relative density of redds was greater in a reach dominated by dams constructed by beavers Castor canadensis. Both dam failure and construction appeared to be responsible for creating new spawning habitat that was quickly occupied, demonstrating rapid temporal response to local habitat changes. Bonneville Cutthroat Trout appeared to establish and defend a redd for up to 2 d, and spawning most often occurred between similar-sized individuals. Spawning surveys for potamodromous trout are an underutilized tool that could be used to better understand the distribution and timing of spawning as well as determine the size and trends of the reproducing portion of populations of management concern. Without efforts to document the diversity of this important aspect of potamodromous trout life history, prioritization of conservation will be problematic.

Annual variation of spawning cutthroat trout in a small western USA stream: a case study with implications for the conservation of potamodromous trout life history diversity

USGS Publications Warehouse

Bennett, Stephen; Al-Chokhachy, Robert; Roper, Brett B.; Budy, Phaedra

2014-01-01

Little is known about the variability in the spatial and temporal distribution of spawning potamodromous trout despite decades of research directed at salmonid spawning ecology and the increased awareness that conserving life history diversity should be a focus of management. We monitored a population of fluvial–resident Bonneville Cutthroat Trout Oncorhynchus clarkii utah in a tributary to the Logan River, Utah, from 2006 to 2012 to gain insight into the distribution and timing of spawning and what factors may influence these spawning activities. We monitored Bonneville Cutthroat Trout using redd surveys with multiple observers and georeferenced redd locations. We documented an extended spawning period that lasted from late April to mid-July. The onset, median, and end of spawning was best predicted by the mean maximum water temperature during the first 13 weeks of the year (F = 130. 4, df = 5, R2 = 0.96, P < 0.0001) with spawning beginning and ending earlier in years that had warmer water temperatures prior to spawning. The distribution of redds was clumped each year and the relative density of redds was greater in a reach dominated by dams constructed by beavers Castor canadensis. Both dam failure and construction appeared to be responsible for creating new spawning habitat that was quickly occupied, demonstrating rapid temporal response to local habitat changes. Bonneville Cutthroat Trout appeared to establish and defend a redd for up to 2 d, and spawning most often occurred between similar-sized individuals. Spawning surveys for potamodromous trout are an underutilized tool that could be used to better understand the distribution and timing of spawning as well as determine the size and trends of the reproducing portion of populations of management concern. Without efforts to document the diversity of this important aspect of potamodromous trout life history, prioritization of conservation will be problematic.

Increased natural reproduction and genetic diversity one generation after cessation of a steelhead trout (Oncorhynchus mykiss) conservation hatchery program.

PubMed

Berejikian, Barry A; Van Doornik, Donald M

2018-01-01

Spatial and temporal fluctuations in productivity and abundance confound assessments of captive propagation programs aimed at recovery of Threatened and Endangered populations. We conducted a 17 year before-after-control-impact experiment to determine the effects of a captive rearing program for anadromous steelhead trout (Oncorhynchus mykiss) on a key indicator of natural spawner abundance (naturally produced nests or 'redds'). The supplemented population exhibited a significant (2.6-fold) increase in redd abundance in the generation following supplementation. Four non-supplemented (control) populations monitored over the same 17 year period exhibited stable or decreasing trends in redd abundance. Expected heterozygosity in the supplemented population increased significantly. Allelic richness increased, but to a lesser (non-significant) degree. Estimates of the effective number of breeders increased from a harmonic mean of 24.4 in the generation before supplementation to 38.9 after supplementation. Several non-conventional aspects of the captive rearing program may have contributed to the positive response in the natural population.

Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements?

PubMed Central

Zhao, Mingxu; Brofeldt, Søren; Li, Qiaohong; Xu, Jianchu; Danielsen, Finn; Læssøe, Simon Bjarke Lægaard; Poulsen, Michael Køie; Gottlieb, Anna

2016-01-01

Biodiversity conservation is a required co-benefit of REDD+. Biodiversity monitoring is therefore needed, yet in most areas it will be constrained by limitations in the available human professional and financial resources. REDD+ programs that use forest plots for biomass monitoring may be able to take advantage of the same data for detecting changes in the tree diversity, using the richness and abundance of canopy trees as a proxy for biodiversity. If local community members are already assessing the above-ground biomass in a representative network of forest vegetation plots, it may require minimal further effort to collect data on the diversity of trees. We compare community members and trained scientists’ data on tree diversity in permanent vegetation plots in montane forest in Yunnan, China. We show that local community members here can collect tree diversity data of comparable quality to trained botanists, at one third the cost. Without access to herbaria, identification guides or the Internet, community members could provide the ethno-taxonomical names for 95% of 1071 trees in 60 vegetation plots. Moreover, we show that the community-led survey spent 89% of the expenses at village level as opposed to 23% of funds in the monitoring by botanists. In participatory REDD+ programs in areas where community members demonstrate great knowledge of forest trees, community-based collection of tree diversity data can be a cost-effective approach for obtaining tree diversity information. PMID:27814370

How Well Can We Predict Salmonid Spawning Habitat with LiDAR?

NASA Astrophysics Data System (ADS)

Pfeiffer, A.; Finnegan, N. J.; Hayes, S.

2013-12-01

Suitable salmonid spawning habitat is, to a great extent, determined by physical, landscape driven characteristics such as channel morphology and grain size. Identifying reaches with high-quality spawning habitat is essential to restoration efforts in areas where salmonid species are endangered or threatened. While both predictions of suitable habitat and observations of utilized habitat are common in the literature, they are rarely combined. Here we exploit a unique combination of high-resolution LiDAR data and seven years of 387 individually surveyed Coho and Steelhead redds in Scott Creek, a 77 km2 un-glaciated coastal California drainage in the Santa Cruz Mountains, to both make and test predictions of spawning habitat. Using a threshold channel assumption, we predict grain size throughout Scott Creek via a shear stress model that incorporates channel width, instead of height, using Manning's equation (Snyder et al., 2013). Slope and drainage area are computed from a LiDAR-derived DEM, and channel width is calculated via hydraulic modeling. Our results for median grain size predictions closely match median grain sizes (D50) measured in the field, with the majority of sites having predicted D50's within a factor of two of the observed values, especially for reaches with D50 > 0.02m. This success suggests that the threshold model used to predict grain size is appropriate for un-glaciated alluvial channel systems. However, it appears that grain size alone is not a strong predictor of salmon spawning. Reaches with a high (>0.1m) average predicted D50 do have lower redd densities, as expected based on spawning gravel sizes in the literature. However, reaches with lower (<0.1m) predicted D50 have a wide range of redd densities, suggesting that reach-average grain size alone cannot explain spawning site selection in the finer-grained reaches of Scott Creek. We turn to analysis of bedform morphology in order to explain the variation in redd density in the low-slope, finer-grained reaches of Lower Scott Creek. Because spawning is strongly correlated with riffle locations, we use a LiDAR-derived longitudinal profile to predict where riffle habitat is located within the watershed. To accomplish this, we use previous studies that constrain pool-riffle habitat to slopes <1.5%, then use wavelet analysis of the longitudinal profile within these pool-riffle reaches to investigate the spacing of drops in water surface slope, with the goal of identifying reaches with high riffle density. Our slope-based predictions of pool-riffle morphology closely match the extent of pool-riffle reaches observed in the field. Average redd density in pool-riffle reaches is more than double the average redd density in reaches of other channel morphologies. Initial wavelet analysis suggests that riffle spacing may be longer in the lower reaches of Scott Creek and shorter in the high-redd density upper reaches, a finding that agrees with the hypothesis that spawning habitat is limited by riffle density. Our results suggest that high resolution topographic data can be successfully used to identify reaches of utilized spawning habitat based on grain size predictions and wavelet analysis of bedform spacing.

The community resource management area mechanism: a strategy to manage African forest resources for REDD+.

PubMed

Asare, Rebecca A; Kyei, Andrew; Mason, John J

2013-01-01

Climate change poses a significant threat to Africa, and deforestation rates have increased in recent years. Mitigation initiatives such as REDD+ are widely considered as potentially efficient ways to generate emission reductions (or removals), conserve or sustainably manage forests, and bring benefits to communities, but effective implementation models are lacking. This paper presents the case of Ghana's Community Resource Management Area (CREMA) mechanism, an innovative natural resource governance and landscape-level planning tool that authorizes communities to manage their natural resources for economic and livelihood benefits. This paper argues that while the CREMA was originally developed to facilitate community-based wildlife management and habitat protection, it offers a promising community-based structure and process for managing African forest resources for REDD+. At a theoretical level, it conforms to the ecological, socio-cultural and economic factors that drive resource-users' decision process and practices. And from a practical mitigation standpoint, the CREMA has the potential to help solve many of the key challenges for REDD+ in Africa, including definition of boundaries, smallholder aggregation, free prior and informed consent, ensuring permanence, preventing leakage, clarifying land tenure and carbon rights, as well as enabling equitable benefit-sharing arrangements. Ultimately, CREMA's potential as a forest management and climate change mitigation strategy that generates livelihood benefits for smallholder farmers and forest users will depend upon the willingness of African governments to support the mechanism and give it full legislative backing, and the motivation of communities to adopt the CREMA and integrate democratic decision-making and planning with their traditional values and natural resource management systems.

Optimal reproduction in salmon spawning substrates linked to grain size and fish length

NASA Astrophysics Data System (ADS)

Riebe, Clifford S.; Sklar, Leonard S.; Overstreet, Brandon T.; Wooster, John K.

2014-02-01

Millions of dollars are spent annually on revitalizing salmon spawning in riverbeds where redd building by female salmon is inhibited by sediment that is too big for fish to move. Yet the conditions necessary for productive spawning remain unclear. There is no gauge for quantifying how grain size influences the reproductive potential of coarse-bedded rivers. Hence, managers lack a quantitative basis for optimizing spawning habitat restoration for reproductive value. To overcome this limitation, we studied spawning by Chinook, sockeye, and pink salmon (Oncorhynchus tshawytscha, O. nerka, and O. gorbuscha) in creeks and rivers of California and the Pacific Northwest. Our analysis shows that coarse substrates have been substantially undervalued as spawning habitat in previous work. We present a field-calibrated approach for estimating the number of redds and eggs a substrate can accommodate from measurements of grain size and fish length. Bigger fish can move larger sediment and thus use more riverbed area for spawning. They also tend to have higher fecundity, and so can deposit more eggs per redd. However, because redd area increases with fish length, the number of eggs a substrate can accommodate is maximized for moderate-sized fish. This previously unrecognized tradeoff raises the possibility that differences in grain size help regulate river-to-river differences in salmon size. Thus, population diversity and species resilience may be linked to lithologic, geomorphic, and climatic factors that determine grain size in rivers. Our approach provides a tool for managing grain-size distributions in support of optimal reproductive potential and species resilience.

Mobile devices for community-based REDD+ monitoring: a case study for Central Vietnam.

PubMed

Pratihast, Arun Kumar; Herold, Martin; Avitabile, Valerio; de Bruin, Sytze; Bartholomeus, Harm; Souza, Carlos M; Ribbe, Lars

2012-12-20

Monitoring tropical deforestation and forest degradation is one of the central elements for the Reduced Emissions from Deforestation and Forest Degradation in developing countries (REDD+) scheme. Current arrangements for monitoring are based on remote sensing and field measurements. Since monitoring is the periodic process of assessing forest stands properties with respect to reference data, adopting the current REDD+ requirements for implementing monitoring at national levels is a challenging task. Recently, the advancement in Information and Communications Technologies (ICT) and mobile devices has enabled local communities to monitor their forest in a basic resource setting such as no or slow internet connection link, limited power supply, etc. Despite the potential, the use of mobile device system for community based monitoring (CBM) is still exceptional and faces implementation challenges. This paper presents an integrated data collection system based on mobile devices that streamlines the community-based forest monitoring data collection, transmission and visualization process. This paper also assesses the accuracy and reliability of CBM data and proposes a way to fit them into national REDD+ Monitoring, Reporting and Verification (MRV) scheme. The system performance is evaluated at Tra Bui commune, Quang Nam province, Central Vietnam, where forest carbon and change activities were tracked. The results show that the local community is able to provide data with accuracy comparable to expert measurements (index of agreement greater than 0.88), but against lower costs. Furthermore, the results confirm that communities are more effective to monitor small scale forest degradation due to subsistence fuel wood collection and selective logging, than high resolution remote sensing SPOT imagery.

The community resource management area mechanism: a strategy to manage African forest resources for REDD+

PubMed Central

Asare, Rebecca A.; Kyei, Andrew; Mason, John J.

2013-01-01

Climate change poses a significant threat to Africa, and deforestation rates have increased in recent years. Mitigation initiatives such as REDD+ are widely considered as potentially efficient ways to generate emission reductions (or removals), conserve or sustainably manage forests, and bring benefits to communities, but effective implementation models are lacking. This paper presents the case of Ghana's Community Resource Management Area (CREMA) mechanism, an innovative natural resource governance and landscape-level planning tool that authorizes communities to manage their natural resources for economic and livelihood benefits. This paper argues that while the CREMA was originally developed to facilitate community-based wildlife management and habitat protection, it offers a promising community-based structure and process for managing African forest resources for REDD+. At a theoretical level, it conforms to the ecological, socio-cultural and economic factors that drive resource-users’ decision process and practices. And from a practical mitigation standpoint, the CREMA has the potential to help solve many of the key challenges for REDD+ in Africa, including definition of boundaries, smallholder aggregation, free prior and informed consent, ensuring permanence, preventing leakage, clarifying land tenure and carbon rights, as well as enabling equitable benefit-sharing arrangements. Ultimately, CREMA's potential as a forest management and climate change mitigation strategy that generates livelihood benefits for smallholder farmers and forest users will depend upon the willingness of African governments to support the mechanism and give it full legislative backing, and the motivation of communities to adopt the CREMA and integrate democratic decision-making and planning with their traditional values and natural resource management systems. PMID:23878338

Mapping Biomass for REDD in the Largest Forest of Central Africa: the Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Shapiro, Aurelie; Saatchi, Sassan

2014-05-01

With the support of the International Climate Initiative (ICI) of the Federal Ministry of the Environment, Conservation, and Nuclear Security, the implementation of the German Development Bank KfW, the World Wide Fund for Nature (WWF) Germany, the University of California Los Angeles (UCLA) and local DRC partners will produce a national scale biomass map for the entire forest coverage of the Democratic Republic of Congo (DRC) along with feasibility assessments of different forest protection measures within a framework of a REDD+ model project. The « Carbon Map and Model (CO2M&M) » project will produce a national forest biomass map for the DRC, which will enable quantitative assessments of carbon stocks and emissions in the largest forest of the Congo Basin. This effort will support the national REDD (Reducing Emissions from Deforestation and Degradation) program in DRC, which plays a major role in sustainable development and poverty alleviation. This map will be developed from field data, complemented by airborne LiDAR (Light Detection and Ranging) and aerial photos, systematically sampled throughout the forests of the DRC and up-scaled to satellite images to accurately estimate carbon content in all forested areas. The second component of the project is to develop specific approaches for model REDD projects in key landscapes. This project represents the largest LiDAR-derived mapping effort in Africa, under unprecedented logistical constraints, which will provide one of the poorest nations in the world with the richest airborne and satellites derived datasets for analyzing forest structure, biomass and biodiversity.

Mobile Devices for Community-Based REDD+ Monitoring: A Case Study for Central Vietnam

PubMed Central

Pratihast, Arun Kumar; Herold, Martin; Avitabile, Valerio; de Bruin, Sytze; Bartholomeus, Harm; Souza, Carlos M.; Ribbe, Lars

2013-01-01

Monitoring tropical deforestation and forest degradation is one of the central elements for the Reduced Emissions from Deforestation and Forest Degradation in developing countries (REDD+) scheme. Current arrangements for monitoring are based on remote sensing and field measurements. Since monitoring is the periodic process of assessing forest stands properties with respect to reference data, adopting the current REDD+ requirements for implementing monitoring at national levels is a challenging task. Recently, the advancement in Information and Communications Technologies (ICT) and mobile devices has enabled local communities to monitor their forest in a basic resource setting such as no or slow internet connection link, limited power supply, etc. Despite the potential, the use of mobile device system for community based monitoring (CBM) is still exceptional and faces implementation challenges. This paper presents an integrated data collection system based on mobile devices that streamlines the community-based forest monitoring data collection, transmission and visualization process. This paper also assesses the accuracy and reliability of CBM data and proposes a way to fit them into national REDD+ Monitoring, Reporting and Verification (MRV) scheme. The system performance is evaluated at Tra Bui commune, Quang Nam province, Central Vietnam, where forest carbon and change activities were tracked. The results show that the local community is able to provide data with accuracy comparable to expert measurements (index of agreement greater than 0.88), but against lower costs. Furthermore, the results confirm that communities are more effective to monitor small scale forest degradation due to subsistence fuel wood collection and selective logging, than high resolution remote sensing SPOT imagery. PMID:23344371

Effects of fine sediment, hyporheic flow, and spawning site characteristics on survival and development of bull trout embryos

USGS Publications Warehouse

Bowerman, Tracy; Neilson, Bethany; Budy, Phaedra

2014-01-01

Successful spawning is imperative for the persistence of salmonid populations, but relatively little research has been conducted to evaluate factors affecting early life-stage survival for bull trout (Salvelinus confluentus), a threatened char. We conducted a field experiment to assess the relationship between site-specific environmental factors and bull trout embryo survival and fry emergence timing. Survival from egg to hatch was negatively related to percent fine sediment (<1 mm) in the redd and positively related to the strength of downwelling at spawning sites. Survival of eggs to fry emergence was also negatively related to fine sediment, and the best statistical models included additional variables that described the rate of downwelling and intragravel flow within the incubation environment. Fry emerged at an earlier stage in development from redds with high percentages of fine sediment. Increased hydraulic conductivity via redd construction and selection of spawning sites with strong downwelling appear to enhance hyporheic flow rates and bull trout egg survival, but early life-stage success may ultimately be limited by intrusion of fine sediment into the incubation environment.

High-resolution forest carbon stocks and emissions in the Amazon.

PubMed

Asner, Gregory P; Powell, George V N; Mascaro, Joseph; Knapp, David E; Clark, John K; Jacobson, James; Kennedy-Bowdoin, Ty; Balaji, Aravindh; Paez-Acosta, Guayana; Victoria, Eloy; Secada, Laura; Valqui, Michael; Hughes, R Flint

2010-09-21

Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at 0.1-ha resolution over 4.3 million ha of the Peruvian Amazon, an area twice that of all forests in Costa Rica, to reveal the determinants of forest carbon density and to demonstrate the feasibility of mapping carbon emissions for REDD. We discovered previously unknown variation in carbon storage at multiple scales based on geologic substrate and forest type. From 1999 to 2009, emissions from land use totaled 1.1% of the standing carbon throughout the region. Forest degradation, such as from selective logging, increased regional carbon emissions by 47% over deforestation alone, and secondary regrowth provided an 18% offset against total gross emissions. Very high-resolution monitoring reduces uncertainty in carbon emissions for REDD programs while uncovering fundamental environmental controls on forest carbon storage and their interactions with land-use change.

Knowledge representation and qualitative simulation of salmon redd functioning. Part II: qualitative model of redds.

PubMed

Guerrin, F; Dumas, J

2001-02-01

This paper describes a qualitative model of the functioning of salmon redds (spawning areas of salmon) and its impact on mortality rates of early stages. For this, we use Qsim, a qualitative simulator, which appeared adequate for representing available qualitative knowledge of freshwater ecology experts (see Part I of this paper). Since the number of relevant variables was relatively large, it appeared necessary to decompose the model into two parts, corresponding to processes occurring at separate time-scales. A qualitative clock allows us to submit the simulation of salmon developmental stages to the calculation of accumulated daily temperatures (degree-days), according to the clock ticks and a water temperature regime set by the user. Therefore, this introduces some way of real-time dating and duration in a purely qualitative model. Simulating both sub-models, either separately or by means of alternate transitions, allows us to generate the evolutions of variables of interest, such as the mortality rates according to two factors (flow of oxygenated water and plugging of gravel interstices near the bed surface), under various scenarios.

Escapement and Productivity of Spring Chinook and Summer Steelhead in the John Day River Basin, Technical Report 2004-2005.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, Wayne

The objectives are: (1) Estimate number and distribution of spring Chinook salmon Oncorhynchus tshawytscha redds and spawners in the John Day River subbasin; and (2) Estimate smolt-to-adult survival rates (SAR) and out-migrant abundance for spring Chinook and summer steelhead O. mykiss and life history characteristics of summer steelhead. Spawning ground surveys for spring (stream-type) Chinook salmon were conducted in four main spawning areas (Mainstem, Middle Fork, North Fork, and Granite Creek System) and seven minor spawning areas (South Fork, Camas Creek, Desolation Creek, Trail Creek, Deardorff Creek, Clear Creek, and Big Creek) in the John Day River basin during Augustmore » and September of 2005. Census surveys included 298.2 river kilometers (88.2 rkm within index, 192.4 rkm additional within census, and 17.6 rkm within random survey areas) of spawning habitat. We observed 902 redds and 701 carcasses including 227 redds in the Mainstem, 178 redds in the Middle Fork, 420 redds in the North Fork, 62 redds in the Granite Creek System, and 15 redds in Desolation Creek. Age composition of carcasses sampled for the entire basin was 1.6% age 3, 91.2% age 4, and 7.1% age 5. The sex ratio was 57.4% female and 42.6% male. Significantly more females than males were observed in the Granite Creek System. During 2005, 82.3% of female carcasses sampled had released all of their eggs. Significantly more pre-spawn mortalities were observed in Granite Creek. Nine (1.3%) of 701 carcasses were of hatchery origin. Of 298 carcasses examined, 4.0% were positive for the presence of lesions. A significantly higher incidence of gill lesions was found in the Granite Creek System when compared to the rest of the basin. Of 114 kidney samples tested, two (1.8%) had clinical BKD levels. Both infected fish were age-4 females in the Middle Fork. All samples tested for IHNV were negative. To estimate spring Chinook and summer steelhead smolt-to-adult survival (SAR) we PIT tagged 5,138 juvenile Chinook and 4,913 steelhead during the spring of 2005. We estimated that 130,144 (95% CL's 97,133-168,409) Chinook emigrated from the upper John Day subbasin past our seining area in the Mainstem John Day River (river kilometers 274-296) between February 4 and June 16, 2005. We also estimated that 32,601 (95% CL's 29,651 and 36,264) Chinook and 47,921 (95% CL's 35,025 and 67,366) steelhead migrated past our Mainstem rotary screw trap at river kilometer (rkm) 326 between October 4, 2004 and July 6, 2005. We estimated that 20,193 (95% CL's 17,699 and 22,983) Chinook and 28,980 (95% CL's 19,914 and 43,705) steelhead migrated past our Middle Fork trap (rkm 24) between October 6, 2004 and June 17, 2005. Seventy three percent of PIT tagged steelhead migrants were age-2 fish, 13.8% were age-3, 12.7% were age-2, and 0.3% were age 4. Spring Chinook SAR for the 2002 brood year was estimated at 2.5% (100 returns of 4,000 PIT tagged smolts). Preliminary steelhead SAR (excluding 2-ocean fish) for the 2004 tagging year was estimated at 1.61% (60 returns of 3,732 PIT-tagged migrants).« less

Implications of sampling design and sample size for national carbon accounting systems.

PubMed

Köhl, Michael; Lister, Andrew; Scott, Charles T; Baldauf, Thomas; Plugge, Daniel

2011-11-08

Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources. We compared the cost-efficiency of four different sampling design alternatives (simple random sampling, regression estimators, stratified sampling, 2-phase sampling with regression estimators) that have been proposed in the scope of REDD. Three of the design alternatives provide for a combination of in-situ and earth-observation data. Under different settings of remote sensing coverage, cost per field plot, cost of remote sensing imagery, correlation between attributes quantified in remote sensing and field data, as well as population variability and the percent standard error over total survey cost was calculated. The cost-efficiency of forest carbon stock assessments is driven by the sampling design chosen. Our results indicate that the cost of remote sensing imagery is decisive for the cost-efficiency of a sampling design. The variability of the sample population impairs cost-efficiency, but does not reverse the pattern of cost-efficiency of the individual design alternatives. Our results clearly indicate that it is important to consider cost-efficiency in the development of forest carbon stock assessments and the selection of remote sensing techniques. The development of MRV-systems for REDD need to be based on a sound optimization process that compares different data sources and sampling designs with respect to their cost-efficiency. This helps to reduce the uncertainties related with the quantification of carbon stocks and to increase the financial benefits from adopting a REDD regime.

Salmon Supplementation Studies in Idaho Rivers; Field Activities Conducted on Clear and Pete King Creeks, 2001 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gass, Carrie; Olson, Jim M.

2004-11-01

In 2001 the Idaho Fisheries Resource Office continued as a cooperator on the Salmon Supplementation Studies in Idaho Rivers (ISS) project on Pete King and Clear creeks. Data relating to supplementation treatment releases, juvenile sampling, juvenile PIT tagging, brood stock spawning and rearing, spawning ground surveys, and snorkel surveys were used to evaluate project data points and augment past data. Due to low adult spring Chinook returns to Kooskia National Fish Hatchery (KNFH) in brood year 1999 there was no smolt supplementation treatment release into Clear Creek in 2001. A 17,014 spring Chinook parr supplementation treatment (containing 1000 PIT tags)more » was released into Pete King Creek on July 24, 2001. On Clear Creek, there were 412 naturally produced spring Chinook parr PIT tagged and released. Using juvenile collection methods, Idaho Fisheries Resource Office staff PIT tagged and released 320 naturally produced spring Chinook pre-smolts on Clear Creek, and 16 natural pre-smolts on Pete King Creek, for minimum survival estimates to Lower Granite Dam. There were no PIT tag detections of brood year 1999 smolts from Clear or Pete King creeks. A total of 2261 adult spring Chinook were collected at KNFH. Forty-three females were used for supplementation brood stock, and 45 supplementation (ventral fin-clip), and 45 natural (unmarked) adults were released upstream of KNFH to spawn naturally. Spatial and temporal distribution of 37 adults released above the KNFH weir was determined through the use of radio telemetry. On Clear Creek, a total of 166 redds (8.2 redds/km) were observed and data was collected from 195 carcasses. Seventeen completed redds (2.1 redds/km) were found, and data was collected data from six carcasses on Pete King Creek.« less

Assessing REDD+ performance of countries with low monitoring capacities: the matrix approach

NASA Astrophysics Data System (ADS)

Bucki, M.; Cuypers, D.; Mayaux, P.; Achard, F.; Estreguil, C.; Grassi, G.

2012-03-01

Estimating emissions from deforestation and degradation of forests in many developing countries is so uncertain that the effects of changes in forest management could remain within error ranges (i.e. undetectable) for several years. Meanwhile UNFCCC Parties need consistent time series of meaningful performance indicators to set credible benchmarks and allocate REDD+ incentives to the countries, programs and activities that actually reduce emissions, while providing social and environmental benefits. Introducing widespread measuring of carbon in forest land (which would be required to estimate more accurately changes in emissions from degradation and forest management) will take time and considerable resources. To ensure the overall credibility and effectiveness of REDD+, parties must consider the design of cost-effective systems which can provide reliable and comparable data on anthropogenic forest emissions. Remote sensing can provide consistent time series of land cover maps for most non-Annex-I countries, retrospectively. These maps can be analyzed to identify the forests that are intact (i.e. beyond significant human influence), and whose fragmentation could be a proxy for degradation. This binary stratification of forests biomes (intact/non-intact), a transition matrix and the use of default carbon stock change factors can then be used to provide initial estimates of trends in emission changes. A proof-of-concept is provided for one biome of the Democratic Republic of the Congo over a virtual commitment period (2005-2010). This approach could allow assessment of the performance of the five REDD+ activities (deforestation, degradation, conservation, management and enhancement of forest carbon stocks) in a spatially explicit, verifiable manner. Incentives could then be tailored to prioritize activities depending on the national context and objectives.

Identification of areas in Brazil that optimize conservation of forest carbon, jaguars, and biodiversity.

PubMed

De Barros, Alan E; MacDonald, Ewan A; Matsumoto, Marcelo H; Paula, Rogério C; Nijhawan, Sahil; Malhi, Y; MacDonald, David W

2014-04-01

A major question in global environmental policy is whether schemes to reduce carbon pollution through forest management, such as Reducing Emissions from Deforestation and Degradation (REDD+), can also benefit biodiversity conservation in tropical countries. We identified municipalities in Brazil that are priorities for reducing rates of deforestation and thus preserving carbon stocks that are also conservation targets for the endangered jaguar (Panthera onca) and biodiversity in general. Preliminary statistical analysis showed that municipalities with high biodiversity were positively associated with high forest carbon stocks. We used a multicriteria decision analysis to identify municipalities that offered the best opportunities for the conservation of forest carbon stocks and biodiversity conservation under a range of scenarios with different rates of deforestation and carbon values. We further categorized these areas by their representativeness of the entire country (through measures such as percent forest cover) and an indirect measure of cost (number of municipalities). The municipalities that offered optimal co-benefits for forest carbon stocks and conservation were termed REDDspots (n = 159), and their spatial distribution was compared with the distribution of current and proposed REDD projects (n = 135). We defined REDDspots as the municipalities that offer the best opportunities for co-benefits between the conservation of forest carbon stocks, jaguars, and other wildlife. These areas coincided in 25% (n = 40) of municipalities. We identified a further 95 municipalities that may have the greatest potential to develop additional REDD+ projects while also targeting biodiversity conservation. We concluded that REDD+ strategies could be an efficient tool for biodiversity conservation in key locations, especially in Amazonian and Atlantic Forest biomes. ©2013 Society for Conservation Biology.

A Near Real-time Decision Support System Improving Forest Management in the Tropics

NASA Astrophysics Data System (ADS)

Tabor, K.; Musinsky, J.; Ledezma, J.; Rasolohery, A.; Mendoza, E.; Kistler, H.; Steininger, M.; Morton, D. C.; Melton, F. S.; Manwell, J.; Koenig, K.

2013-12-01

Conservation International (CI) has a decade of experience developing near real-time fire and deforestation monitoring and forecasting systems that channel monitoring information from satellite observations directly to national and sub-national government agencies, Non-Government Organizations (NGOs), and local communities. These systems are used to strengthen forest surveillance and monitoring, fire management and prevention, protected areas management and sustainable land use planning. With support from a NASA Wildland Fires grant, in September 2013 CI will launch a brand new near real-time alert system (FIRECAST) to better meet the outstanding needs and challenges users face in addressing ecosystem degradation from wildland fire and illegal forest activities. Outreach efforts and user feedback have indicated the need for seasonal fire forecasts for effective land use planning, faster alert delivery to enhance response to illegal forest activities, and expanded forest monitoring capabilities that enable proactive responses and that strengthen forest conservation and sustainable development actions. The new FIRECAST system addresses these challenges by integrating the current fire alert and deforestation systems and adding improved ecological forecasting of fire risk; expanding data exchange capabilities with mobile technologies; and delivering a deforestation alert product that can inform policies related to land use management and Reduced Emissions from Deforestation and forest Degradation (REDD+). In addition to demonstrating the capabilities of this new real-time alert system, we also highlight how coordination with host-country institutions enhances the system's capacity to address the implementation needs of REDD+ forest carbon projects, improve tropical forest management, strengthen environmental law enforcement, and facilitate the uptake of near real-time satellite monitoring data into business practices of these national/sub-national institutions.

REDD and PINC: A new policy framework to fund tropical forests as global 'eco-utilities'

NASA Astrophysics Data System (ADS)

Trivedi, M. R.; Mitchell, A. W.; Mardas, N.; Parker, C.; Watson, J. E.; Nobre, A. D.

2009-11-01

Tropical forests are 'eco-utilities' providing critical ecosystem services that underpin food, energy, water and climate security at local to global scales. Currently, these services are unrecognised and unrewarded in international policy and financial frameworks, causing forests to be worth more dead than alive. Much attention is currently focused on REDD (Reducing Emissions from Deforestation and forest Degradation) and A/R (Afforestation and Reforestation) as mitigation options. In this article we propose an additional mechanism - PINC (Proactive Investment in Natural Capital) - that recognises and rewards the value of ecosystem services provided by standing tropical forests, especially from a climate change adaptation perspective. Using Amazonian forests as a case study we show that PINC could improve the wellbeing of rural and forest-dependent populations, enabling them to cope with the impacts associated with climate change and deforestation. By investing pro-actively in areas where deforestation pressures are currently low, the long-term costs of mitigation and adaptation will be reduced. We suggest a number of ways in which funds could be raised through emerging financial mechanisms to provide positive incentives to maintain standing forests. To develop PINC, a new research and capacity-building agenda is needed that explores the interdependence between communities, the forest eco-utility and the wider economy.

Climate change mitigation by carbon stock - the case of semi-arid West Africa

NASA Astrophysics Data System (ADS)

Lykke, A. M.; Barfod, A. S.; Tinggaard Svendsen, G.; Greve, M.; Svenning, J.-C.

2009-11-01

Semi-arid West Africa has not been integrated into the afforestation/reforestation (AR) carbon market. Most projects implemented under the Clean Development Mechanism (CDM) have focused on carbon emission reductions from industry and energy consumption, whereas only few (only one in West Africa) have been certified for AR carbon sequestration. A proposed mechanism, Reducing Emissions from Deforestation and Degradation (REDD) to be discussed under COP15 aims to reduce emissions by conserving already existing forests. REDD has high potential for carbon stocking at low costs, but focuses primarily on rain forest countries and excludes semi-arid West Africa from the preliminary setup. African savannas have potential to store carbon in the present situation with degrading ecosystems and relatively low revenues from crops and cattle, especially if it is possible to combine carbon stocking with promotion of secondary crops such as food resources and traditional medicines harvested on a sustainable basis. Methods for modelling and mapping of potential carbon biomass are being developed, but are still in a preliminary state. Although economic benefits from the sale of carbon credits are likely to be limited, carbon stocking is an interesting option if additional benefits are considered such as improved food security and protection of biodiversity.

Structuring economic incentives to reduce emissions from deforestation within Indonesia.

PubMed

Busch, Jonah; Lubowski, Ruben N; Godoy, Fabiano; Steininger, Marc; Yusuf, Arief A; Austin, Kemen; Hewson, Jenny; Juhn, Daniel; Farid, Muhammad; Boltz, Frederick

2012-01-24

We estimate and map the impacts that alternative national and subnational economic incentive structures for reducing emissions from deforestation (REDD+) in Indonesia would have had on greenhouse gas emissions and national and local revenue if they had been in place from 2000 to 2005. The impact of carbon payments on deforestation is calibrated econometrically from the pattern of observed deforestation and spatial variation in the benefits and costs of converting land to agriculture over that time period. We estimate that at an international carbon price of $10/tCO(2)e, a "mandatory incentive structure," such as a cap-and-trade or symmetric tax-and-subsidy program, would have reduced emissions by 163-247 MtCO(2)e/y (20-31% below the without-REDD+ reference scenario), while generating a programmatic budget surplus. In contrast, a "basic voluntary incentive structure" modeled after a standard payment-for-environmental-services program would have reduced emissions nationally by only 45-76 MtCO(2)e/y (6-9%), while generating a programmatic budget shortfall. By making four policy improvements--paying for net emission reductions at the scale of an entire district rather than site-by-site; paying for reductions relative to reference levels that match business-as-usual levels; sharing a portion of district-level revenues with the national government; and sharing a portion of the national government's responsibility for costs with districts--an "improved voluntary incentive structure" would have been nearly as effective as a mandatory incentive structure, reducing emissions by 136-207 MtCO(2)e/y (17-26%) and generating a programmatic budget surplus.

Responding to climate change and the global land crisis: REDD+, market transformation and low-emissions rural development

PubMed Central

Nepstad, Daniel C.; Boyd, William; Stickler, Claudia M.; Bezerra, Tathiana; Azevedo, Andrea A.

2013-01-01

Climate change and rapidly escalating global demand for food, fuel, fibre and feed present seemingly contradictory challenges to humanity. Can greenhouse gas (GHG) emissions from land-use, more than one-fourth of the global total, decline as growth in land-based production accelerates? This review examines the status of two major international initiatives that are designed to address different aspects of this challenge. REDD+ is an emerging policy framework for providing incentives to tropical nations and states that reduce their GHG emissions from deforestation and forest degradation. Market transformation, best represented by agricultural commodity roundtables, seeks to exclude unsustainable farmers from commodity markets through international social and environmental standards for farmers and processors. These global initiatives could potentially become synergistically integrated through (i) a shared approach for measuring and favouring high environmental and social performance of land use across entire jurisdictions and (ii) stronger links with the domestic policies, finance and laws in the jurisdictions where agricultural expansion is moving into forests. To achieve scale, the principles of REDD+ and sustainable farming systems must be embedded in domestic low-emission rural development models capable of garnering support across multiple constituencies. We illustrate this potential with the case of Mato Grosso State in the Brazilian Amazon. PMID:23610173

Responding to climate change and the global land crisis: REDD+, market transformation and low-emissions rural development.

PubMed

Nepstad, Daniel C; Boyd, William; Stickler, Claudia M; Bezerra, Tathiana; Azevedo, Andrea A

2013-06-05

Climate change and rapidly escalating global demand for food, fuel, fibre and feed present seemingly contradictory challenges to humanity. Can greenhouse gas (GHG) emissions from land-use, more than one-fourth of the global total, decline as growth in land-based production accelerates? This review examines the status of two major international initiatives that are designed to address different aspects of this challenge. REDD+ is an emerging policy framework for providing incentives to tropical nations and states that reduce their GHG emissions from deforestation and forest degradation. Market transformation, best represented by agricultural commodity roundtables, seeks to exclude unsustainable farmers from commodity markets through international social and environmental standards for farmers and processors. These global initiatives could potentially become synergistically integrated through (i) a shared approach for measuring and favouring high environmental and social performance of land use across entire jurisdictions and (ii) stronger links with the domestic policies, finance and laws in the jurisdictions where agricultural expansion is moving into forests. To achieve scale, the principles of REDD+ and sustainable farming systems must be embedded in domestic low-emission rural development models capable of garnering support across multiple constituencies. We illustrate this potential with the case of Mato Grosso State in the Brazilian Amazon.

Spawning habitat and behavior of Gila trout, a rare salmonid of the southwestern United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rinne, J.N.

1980-01-01

The spawning season of Gila trout, Salmo gilae Miller, in three streams in the Gila National Forest, New Mexico, began in early April at the lowest elevation and continued through June at the highest elevation. Water temperature and stream flow interacted to induce spawning; however, the former was more important. Spawning commenced at water temperatures near 8 C. Redds were normally in 6 to 15 cm deep water, about a quarter of the stream width from one bank and within 5 m of cover. The substrate was predominantly gravel and small pebble (0.2 to 3.8 cm). Spawning fish selected reddmore » sites based on depth of water and substrate rather than on water velocity. Redds ranged in area from less than 0.1 m/sup 2/ to nearly 2.0 m/sup 2/ and averaged 3 to 4 cm in structural depth. Normally a single fish or a pair of fish occupied a redd, but occupancy by three to four fish was common. Most spawning activity occurred between 1300 and 1600 hours. Fry (15 to 20 mm long) emerged in 8 to 10 weeks and inhibited riffle areas. Absence of fry from pools occupied by adults indicated that cannibalism may occur.« less

Froude Number is the Single Most Important Hydraulic Parameter for Salmonid Spawning Habitat.

NASA Astrophysics Data System (ADS)

Gillies, E.; Moir, H. J.

2015-12-01

Many gravel-bed rivers exhibit historic straightening or embanking, reducing river complexity and the available habitat for key species such as salmon. A defensible method for predicting salmonid spawning habitat is an important tool for anyone engaged in assessing a river restoration. Most empirical methods to predict spawning habitat use lookup tables of depth, velocity and substrate. However, natural site selection is different: salmon must pick a location where they can successfully build a redd, and where eggs have a sufficient survival rate. Also, using dimensional variables, such as depth and velocity, is problematic: spawning occurs in rivers of differing size, depth and velocity range. Non-dimensional variables have proven useful in other branches of fluid dynamics, and instream habitat is no different. Empirical river data has a high correlation between observed salmon redds and Froude number, without insight into why. Here we present a physics based model of spawning and bedform evolution, which shows that Froude number is indeed a rational choice for characterizing the bedform, substrate, and flow necessary for spawning. It is familiar for Froude to characterize surface waves, but Froude also characterizes longitudinal bedform in a mobile bed river. We postulate that these bedforms and their hydraulics perform two roles in salmonid spawning: allowing transport of clasts during redd building, and oxygenating eggs. We present an example of this Froude number and substrate based habitat characterization on a Scottish river for which we have detailed topography at several stages during river restoration and subsequent evolution of natural processes. We show changes to the channel Froude regime as a result of natural process and validate habitat predictions against redds observed during 2014 and 2015 spawning seasons, also relating this data to the Froude regime in other, nearby, rivers. We discuss the use of the Froude spectrum in providing an indicator of salmonid spawning and the success of river restoration.

Would protecting tropical forest fragments provide carbon and biodiversity cobenefits under REDD+?

PubMed

Magnago, Luiz Fernando S; Magrach, Ainhoa; Laurance, William F; Martins, Sebastião V; Meira-Neto, João Augusto A; Simonelli, Marcelo; Edwards, David P

2015-09-01

Tropical forests store vast amounts of carbon and are the most biodiverse terrestrial habitats, yet they are being converted and degraded at alarming rates. Given global shortfalls in the budgets required to prevent carbon and biodiversity loss, we need to seek solutions that simultaneously address both issues. Of particular interest are carbon-based payments under the Reducing Emissions from Deforestation and Forest Degradation (REDD+) mechanism to also conserve biodiversity at no additional cost. One potential is for REDD+ to protect forest fragments, especially within biomes where contiguous forest cover has diminished dramatically, but we require empirical tests of the strength of any carbon and biodiversity cobenefits in such fragmented systems. Using the globally threatened Atlantic Forest landscape, we measured above-ground carbon stocks within forest fragments spanning 13 to 23 442 ha in area and with different degrees of isolation. We related these stocks to tree community structure and to the richness and abundance of endemic and IUCN Red-listed species. We found that increasing fragment size has a positive relationship with above-ground carbon stock and with abundance of IUCN Red-listed species and tree community structure. We also found negative relationships between distance from large forest block and tree community structure, endemic species richness and abundance, and IUCN Red-listed species abundance. These resulted in positive congruence between carbon stocks and Red-listed species, and the abundance and richness of endemic species, demonstrating vital cobenefits. As such, protecting forest fragments in hotspots of biodiversity, particularly larger fragments and those closest to sources, offers important carbon and biodiversity cobenefits. More generally, our results suggest that macroscale models of cobenefits under REDD+ have likely overlooked key benefits at small scales, indicating the necessity to apply models that include finer-grained assessments in fragmented landscapes rather than using averaged coarse-grained cells. © 2015 John Wiley & Sons Ltd.

Identifying areas of deforestation risk for REDD+ using a species modeling tool

PubMed Central

Riveros, Juan Carlos; Forrest, Jessica L

2014-01-01

Background To implement the REDD+ mechanism (Reducing Emissions for Deforestation and Forest Degradation, countries need to prioritize areas to combat future deforestation CO2 emissions, identify the drivers of deforestation around which to develop mitigation actions, and quantify and value carbon for financial mechanisms. Each comes with its own methodological challenges, and existing approaches and tools to do so can be costly to implement or require considerable technical knowledge and skill. Here, we present an approach utilizing a machine learning technique known as Maximum Entropy Modeling (Maxent) to identify areas at high deforestation risk in the study area in Madre de Dios, Peru under a business-as-usual scenario in which historic deforestation rates continue. We link deforestation risk area to carbon density values to estimate future carbon emissions. We quantified area deforested and carbon emissions between 2000 and 2009 as the basis of the scenario. Results We observed over 80,000 ha of forest cover lost from 2000-2009 (0.21% annual loss), representing over 39 million Mg CO2. The rate increased rapidly following the enhancement of the Inter Oceanic Highway in 2005. Accessibility and distance to previous deforestation were strong predictors of deforestation risk, while land use designation was less important. The model performed consistently well (AUC > 0.9), significantly better than random when we compared predicted deforestation risk to observed. If past deforestation rates continue, we estimate that 132,865 ha of forest could be lost by the year 2020, representing over 55 million Mg CO2. Conclusions Maxent provided a reliable method for identifying areas at high risk of deforestation and the major explanatory variables that could draw attention for mitigation action planning under REDD+. The tool is accessible, replicable and easy to use; all necessary for producing good risk estimates and adapt models after potential landscape change. We propose this approach for developing countries planning to meet requirements under REDD+. PMID:25489336

Investigating the Geomorphic and Ecologic Functions of Wood in Relationship to Habitat Type and Salmonid Redds on a Regulated California River

NASA Astrophysics Data System (ADS)

Senter, A. E.; Pasternack, G. B.

2006-12-01

Most river rehabilitation projects incorporate little to no wood in current designs, and those that do have little science to guide them. The overall goal of this research is to investigate the role of wood in a regulated, mid- sized (where river width is greater than most tree heights), Mediterranean-climate (where smaller, softer-wood trees dominate the landscape) river in order to provide a scientific foundation for the potential use of wood in rehabilitation projects within such systems. Wood structures in the active salmonid spawning reach of the Lower Mokelumne River in Central California were measured, mapped, and described during summer and fall 2006. Digital photos and GPS coordinates were used to establish wood location within the stream channel. Structural morphology was determined by measuring physical properties such as individual diameter and length, orientation to stream flow, and jam dimensions. In addition, qualitative attributes were recorded such as decay class and leaf, limb, bark, and root characteristics. A GIS wood layer will be created and added to a database of existing Mokelumne River GIS layers containing salmonid redd (salmon egg nests) densities, hydraulic conditions associated with individual redds, and sub-reach habitat types. An analysis of wood properties, redd locations and conditions, and habitat types will be used to develop a conceptual model of wood dynamics in relation to salmonid habitat on the Lower Mokelumne River. The primary products of this study will be (1) a scientific conceptual model of the role of wood in regulated gravel reaches of mid-size rivers in Mediterranean California and (2) a decision-making framework that will enable river managers to include scientifically based wood structures into rehabilitation designs, thereby enhancing spawning habitat, stream complexity, and biological diversity. These tools will be developed in collaboration with East Bay Municipal Utilities District to aid in the continuing rehabilitation of the Lower Mokelumne River.

Monitoring forest carbon in a Tanzanian woodland using interferometric SAR: a novel methodology for REDD.

PubMed

Solberg, Svein; Gizachew, Belachew; Næsset, Erik; Gobakken, Terje; Bollandsås, Ole Martin; Mauya, Ernest William; Olsson, Håkan; Malimbwi, Rogers; Zahabu, Eliakimu

2015-12-01

REDD+ implementation requires establishment of a system for measuring, reporting and verification (MRV) of forest carbon changes. A challenge for MRV is the lack of satellite based methods that can track not only deforestation, but also degradation and forest growth, as well as a lack of historical data that can serve as a basis for a reference emission level. Working in a miombo woodland in Tanzania, we here aim at demonstrating a novel 3D satellite approach based on interferometric processing of radar imagery (InSAR). Forest carbon changes are derived from changes in the forest canopy height obtained from InSAR, i.e. decreases represent carbon loss from logging and increases represent carbon sequestration through forest growth. We fitted a model of above-ground biomass (AGB) against InSAR height, and used this to convert height changes to biomass and carbon changes. The relationship between AGB and InSAR height was weak, as the individual plots were widely scattered around the model fit. However, we consider the approach to be unique and feasible for large-scale MRV efforts in REDD+ because the low accuracy was attributable partly to small plots and other limitations in the data set, and partly to a random pixel-to-pixel variation in trunk forms. Further processing of the InSAR data provides data on the categories of forest change. The combination of InSAR data from the Shuttle RADAR Topography Mission (SRTM) and the TanDEM-X satellite mission provided both historic baseline of change for the period 2000-2011, as well as annual change 2011-2012. A 3D data set from InSAR is a promising tool for MRV in REDD+. The temporal changes seen by InSAR data corresponded well with, but largely supplemented, the changes derived from Landsat data.

Identifying areas of deforestation risk for REDD+ using a species modeling tool.

PubMed

Aguilar-Amuchastegui, Naikoa; Riveros, Juan Carlos; Forrest, Jessica L

2014-01-01

To implement the REDD+ mechanism (Reducing Emissions for Deforestation and Forest Degradation, countries need to prioritize areas to combat future deforestation CO2 emissions, identify the drivers of deforestation around which to develop mitigation actions, and quantify and value carbon for financial mechanisms. Each comes with its own methodological challenges, and existing approaches and tools to do so can be costly to implement or require considerable technical knowledge and skill. Here, we present an approach utilizing a machine learning technique known as Maximum Entropy Modeling (Maxent) to identify areas at high deforestation risk in the study area in Madre de Dios, Peru under a business-as-usual scenario in which historic deforestation rates continue. We link deforestation risk area to carbon density values to estimate future carbon emissions. We quantified area deforested and carbon emissions between 2000 and 2009 as the basis of the scenario. We observed over 80,000 ha of forest cover lost from 2000-2009 (0.21% annual loss), representing over 39 million Mg CO2. The rate increased rapidly following the enhancement of the Inter Oceanic Highway in 2005. Accessibility and distance to previous deforestation were strong predictors of deforestation risk, while land use designation was less important. The model performed consistently well (AUC > 0.9), significantly better than random when we compared predicted deforestation risk to observed. If past deforestation rates continue, we estimate that 132,865 ha of forest could be lost by the year 2020, representing over 55 million Mg CO2. Maxent provided a reliable method for identifying areas at high risk of deforestation and the major explanatory variables that could draw attention for mitigation action planning under REDD+. The tool is accessible, replicable and easy to use; all necessary for producing good risk estimates and adapt models after potential landscape change. We propose this approach for developing countries planning to meet requirements under REDD+.

The NASA Carbon Monitoring System

NASA Astrophysics Data System (ADS)

Hurtt, G. C.

2015-12-01

Greenhouse gas emission inventories, forest carbon sequestration programs (e.g., Reducing Emissions from Deforestation and Forest Degradation (REDD and REDD+), cap-and-trade systems, self-reporting programs, and their associated monitoring, reporting and verification (MRV) frameworks depend upon data that are accurate, systematic, practical, and transparent. A sustained, observationally-driven carbon monitoring system using remote sensing data has the potential to significantly improve the relevant carbon cycle information base for the U.S. and world. Initiated in 2010, NASA's Carbon Monitoring System (CMS) project is prototyping and conducting pilot studies to evaluate technological approaches and methodologies to meet carbon monitoring and reporting requirements for multiple users and over multiple scales of interest. NASA's approach emphasizes exploitation of the satellite remote sensing resources, computational capabilities, scientific knowledge, airborne science capabilities, and end-to-end system expertise that are major strengths of the NASA Earth Science program. Through user engagement activities, the NASA CMS project is taking specific actions to be responsive to the needs of stakeholders working to improve carbon MRV frameworks. The first phase of NASA CMS projects focused on developing products for U.S. biomass/carbon stocks and global carbon fluxes, and on scoping studies to identify stakeholders and explore other potential carbon products. The second phase built upon these initial efforts, with a large expansion in prototyping activities across a diversity of systems, scales, and regions, including research focused on prototype MRV systems and utilization of COTS technologies. Priorities for the future include: 1) utilizing future satellite sensors, 2) prototyping with commercial off-the-shelf technology, 3) expanding the range of prototyping activities, 4) rigorous evaluation, uncertainty quantification, and error characterization, 5) stakeholder engagement, 6) partnerships with other U.S. agencies and international partners, and 7) modeling and data assimilation.

ALOS2-Indonesia REDD+ Experiment (AIREX): Soil Pool Carbon Application

NASA Astrophysics Data System (ADS)

Raimadoya, M.; Kristijono, A.; Sudiana, N.; Sumawinata, B.; Suwardi; Santoso, E.; Mahargo, D.; Sudarman, S.; Mattikainen, M.

2015-04-01

The bilateral REDD+ agreement between Indonesia and Norway [1] has scheduled that performance based result phase will be started in 2014. Therefore, a transparent and reliable Monitoring, Reporting and V erification (MRV) system for the following carbon pools: (1) biomass, (2) dead organic matter (DOM), and (3) soil, is required to be ready prior to the performance based phase. While the biomass pool could be acquired by space-borne radar (SAR) application i.e. SAR Interferometry (In-SAR) and Polarimetric SAR Interferometry (Pol-InSAR), the method for soil pool is still needed to be developed.A study was implemented in a test site located in the pulp plantation concession of Teluk Meranti Estate, Riau Andalan Pulp and Paper (RAPP), Pelalawan District, Riau Province, Indonesia. The study was intended to evaluate the possibility to estimate soil pool carbon with radar technology. For this purpose, a combination of spaceborne SAR (ALOS/PALSAR) and Ground Penetrating Radar (200 MHz IDS 200 MHz IDS GPR) were used in this exercise.The initial result this study provides a promising outcome for improved soil pool carbon estimation in tropical peat forest condition. The volume estimation of peat soil could be measured from the combination of spaceborne SAR and GPR. Based on this volume, total carbon content can be generated. However, the application of this approach has several limitation such as: (1) GPR survey can only be implemented during the dry season, (2) Rugged Terrain Antenna (RTA) type of GPR should be used for smooth GPR survey in the surface of peat soil which covered by DOM, and (3) the map of peat soil extent by spaceborne SAR need to be improved.

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

NASA Technical Reports Server (NTRS)

Naesset, Erik; Gobakken, Terje; Bollandsas, Ole Martin; Gregoire, Timothy G.; Nelson, Ross; Stahl, Goeran

2013-01-01

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Moving from Measuring, Reporting, Verification (MRV) of Forest Carbon to Community Mapping, Measuring, Monitoring (MMM): Perspectives from Mexico

PubMed Central

Chutz, Noah; Skutsch, Margaret

2016-01-01

There have been many calls for community participation in MRV (measuring, reporting, verification) for REDD+. This paper examines whether community involvement in MRV is a requirement, why it appears desirable to REDD+ agencies and external actors, and under what conditions communities might be interested in participating. It asks What’s in it for communities? What might communities gain from such an involvement? What could they lose? It embraces a broader approach which we call community MMM which involves mapping, measuring and monitoring of forest and other natural resources for issues which are of interest to the community itself. We focus on cases in México because the country has an unusually high proportion of forests under community communal ownership. In particular, we refer to a recent REDD+ initiative—CONAFOR-LAIF, in which local communities select and approve local people to participate in community-based monitoring activities. From these local initiatives we identify the specific and the general drivers for communities to be involved in mapping, measuring and monitoring of their own territories and their natural resources. We present evidence that communities are more interested in this wider approach than in a narrow focus on carbon monitoring. Finally we review what the challenges to reconciling MMM with MRV requirements are likely to be. PMID:27300439

Agricultural intensification escalates future conservation costs.

PubMed

Phelps, Jacob; Carrasco, Luis Roman; Webb, Edward L; Koh, Lian Pin; Pascual, Unai

2013-05-07

The supposition that agricultural intensification results in land sparing for conservation has become central to policy formulations across the tropics. However, underlying assumptions remain uncertain and have been little explored in the context of conservation incentive schemes such as policies for Reducing Emissions from Deforestation and forest Degradation, conservation, sustainable management, and enhancement of carbon stocks (REDD+). Incipient REDD+ forest carbon policies in a number of countries propose agricultural intensification measures to replace extensive "slash-and-burn" farming systems. These may result in conservation in some contexts, but will also increase future agricultural land rents as productivity increases, creating new incentives for agricultural expansion and deforestation. While robust governance can help to ensure land sparing, we propose that conservation incentives will also have to increase over time, tracking future agricultural land rents, which might lead to runaway conservation costs. We present a conceptual framework that depicts these relationships, supported by an illustrative model of the intensification of key crops in the Democratic Republic of Congo, a leading REDD+ country. A von Thünen land rent model is combined with geographic information systems mapping to demonstrate how agricultural intensification could influence future conservation costs. Once postintensification agricultural land rents are considered, the cost of reducing forest sector emissions could significantly exceed current and projected carbon credit prices. Our analysis highlights the importance of considering escalating conservation costs from agricultural intensification when designing conservation initiatives.

Agricultural intensification escalates future conservation costs

PubMed Central

Phelps, Jacob; Carrasco, Luis Roman; Webb, Edward L.; Koh, Lian Pin; Pascual, Unai

2013-01-01

The supposition that agricultural intensification results in land sparing for conservation has become central to policy formulations across the tropics. However, underlying assumptions remain uncertain and have been little explored in the context of conservation incentive schemes such as policies for Reducing Emissions from Deforestation and forest Degradation, conservation, sustainable management, and enhancement of carbon stocks (REDD+). Incipient REDD+ forest carbon policies in a number of countries propose agricultural intensification measures to replace extensive “slash-and-burn” farming systems. These may result in conservation in some contexts, but will also increase future agricultural land rents as productivity increases, creating new incentives for agricultural expansion and deforestation. While robust governance can help to ensure land sparing, we propose that conservation incentives will also have to increase over time, tracking future agricultural land rents, which might lead to runaway conservation costs. We present a conceptual framework that depicts these relationships, supported by an illustrative model of the intensification of key crops in the Democratic Republic of Congo, a leading REDD+ country. A von Thünen land rent model is combined with geographic information systems mapping to demonstrate how agricultural intensification could influence future conservation costs. Once postintensification agricultural land rents are considered, the cost of reducing forest sector emissions could significantly exceed current and projected carbon credit prices. Our analysis highlights the importance of considering escalating conservation costs from agricultural intensification when designing conservation initiatives. PMID:23589860

Kootenai River Fisheries Investigations; Rainbow and Bull Trout Recruitment, 2003-2004 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walters, Jody P.

2005-08-01

Rainbow trout Oncorhynchus mykiss provide the most important sport fishery in the Kootenai River, Idaho, but densities and catch rates are low. Low recruitment is one possible factor limiting the rainbow trout population. Bull trout Salvelinus confluentus also exist in the Kootenai River, but little is known about this population. Research reported here addresses the following objectives for the Kootenai River, Idaho: identify sources of rainbow and bull trout recruitment, monitor the rainbow trout population size structure to evaluate regulation changes initiated in 2002, and identify factors potentially limiting rainbow trout recruitment. A screw trap was used to estimate juvenilemore » redband and bull trout out-migration from the Callahan Creek drainage, and electrofishing was conducted to estimate summer densities of bull trout rearing in the Idaho portion of the drainage. An estimated 1,132 juvenile redband trout and 68 juvenile bull trout out-migrated from Callahan Creek to the Kootenai River from April 7 through July 15, 2003. Densities of bull trout {ge} age-1 in North and South Callahan creeks ranged from 1.6 to 7.7 fish/100m{sup 2} in August. Bull trout redd surveys were conducted in North and South Callahan creeks, Boulder Creek, and Myrtle Creek. Thirty-two bull trout redds were located in North Callahan Creek, while 10 redds were found in South Callahan Creek. No redds were found in the other two streams. Modeling of culverts in the Deep Creek drainage identified two as upstream migration barriers, preventing rainbow trout from reaching spawning and rearing habitat. Water temperature monitoring in Deep Creek identified two sites where maximum temperatures exceeded those suitable for rainbow trout. Boulder Creek produces the most rainbow trout recruits to the Kootenai River in Idaho upstream of Deep Creek, but may be below carrying capacity for rearing rainbow trout due to nutrient limitations. Monthly water samples indicate Boulder Creek is nutrient limited as soluble reactive and total dissolved phosphorus were typically at or below detection limits, and dissolved inorganic nitrogen concentrations were <30 {micro}/L. A fall 2003 electrofishing survey of the Kootenai River rainbow trout population showed that the proportional stock density (55) and quality stock density (6) increased for the second year in a row following implementation of more conservative harvest regulations. North and South Callahan creeks support the largest spawning population of bull trout in the Kootenai River drainage, Idaho, so management of the watershed should consider bull trout as high priority. Monitoring of the Kootenai River rainbow trout population size structure should continue for at least two to three years to help evaluate the conservative harvest regulations. Finally, options to improve or increase access to rainbow trout spawning and rearing habitat in the Deep Creek drainage should be investigated.« less

Redd Site Selection and Spawning Habitat Use by Fall Chinook Salmon: The Importance of Geomorphic Features in Large Rivers

PubMed

Geist; Dauble

1998-09-01

/ Knowledge of the three-dimensional connectivity between rivers and groundwater within the hyporheic zone can be used to improve the definition of fall chinook salmon (Oncorhynchus tshawytscha) spawning habitat. Information exists on the microhabitat characteristics that define suitable salmon spawning habitat. However, traditional spawning habitat models that use these characteristics to predict available spawning habitat are restricted because they can not account for the heterogeneous nature of rivers. We present a conceptual spawning habitat model for fall chinook salmon that describes how geomorphic features of river channels create hydraulic processes, including hyporheic flows, that influence where salmon spawn in unconstrained reaches of large mainstem alluvial rivers. Two case studies based on empirical data from fall chinook salmon spawning areas in the Hanford Reach of the Columbia River are presented to illustrate important aspects of our conceptual model. We suggest that traditional habitat models and our conceptual model be combined to predict the limits of suitable fall chinook salmon spawning habitat. This approach can incorporate quantitative measures of river channel morphology, including general descriptors of geomorphic features at different spatial scales, in order to understand the processes influencing redd site selection and spawning habitat use. This information is needed in order to protect existing salmon spawning habitat in large rivers, as well as to recover habitat already lost.KEY WORDS: Hyporheic zone; Geomorphology; Spawning habitat; Large rivers; Fall chinook salmon; Habitat management

Options for monitoring and estimating historical carbon emissions from forest degradation in the context of REDD+

PubMed Central

2011-01-01

Measuring forest degradation and related forest carbon stock changes is more challenging than measuring deforestation since degradation implies changes in the structure of the forest and does not entail a change in land use, making it less easily detectable through remote sensing. Although we anticipate the use of the IPCC guidance under the United Framework Convention on Climate Change (UNFCCC), there is no one single method for monitoring forest degradation for the case of REDD+ policy. In this review paper we highlight that the choice depends upon a number of factors including the type of degradation, available historical data, capacities and resources, and the potentials and limitations of various measurement and monitoring approaches. Current degradation rates can be measured through field data (i.e. multi-date national forest inventories and permanent sample plot data, commercial forestry data sets, proxy data from domestic markets) and/or remote sensing data (i.e. direct mapping of canopy and forest structural changes or indirect mapping through modelling approaches), with the combination of techniques providing the best options. Developing countries frequently lack consistent historical field data for assessing past forest degradation, and so must rely more on remote sensing approaches mixed with current field assessments of carbon stock changes. Historical degradation estimates will have larger uncertainties as it will be difficult to determine their accuracy. However improving monitoring capacities for systematic forest degradation estimates today will help reduce uncertainties even for historical estimates. PMID:22115360

Evaluation of Salmon Spawning Below Bonneville Dam Annual Report October 2006 - September 2007.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arntzen, Evan V.; Mueller, Robert P.; Murray, Katherine J.

2008-08-08

From 1999 through 2007, the Fish and Wildlife Program of the Bonneville Power Administration funded a project to determine the number of fall Chinook and chum salmon spawning downstream of Bonneville Dam, the characteristics of their spawning areas, and the flows necessary to ensure their long-term survival. Data were collected to ensure that established flow guidelines are appropriate and provide adequate protection for the species of concern. The projects objectives are consistent with the high priority placed by the Northwest Power and Conservation Council Independent Scientific Advisory Board and the salmon managers on determining the importance of mainstem habitats tomore » the production of salmon in the Columbia River Basin. Because of the influence of mainstem habitat on salmon production, there is a continued need to better understand the physical habitat variables used by mainstem fall Chinook and chum salmon populations and the effects of hydropower project operations on spawning and incubation. During FY 2007, Pacific Northwest National Laboratory focused on (1) locating and mapping deep-water fall Chinook salmon and chum salmon spawning areas, (2) investigating the interaction between groundwater and surface water near fall Chinook and chum salmon spawning areas, and (3) providing in-season hyporheic temperature and water surface elevation data to assist state agencies with emergence timing and redd dewatering estimates. This report documents the studies and tasks performed by PNNL during FY 2007. Chapter 1 provides a description of the searches conducted for deepwater redds-adjacent to Pierce and Ives islands for fall Chinook salmon and near the Interstate 205 bridge for chum salmon. The chapter also provides data on redd location, information about habitat associations, and estimates of total spawning populations. Chapter 2 documents the collection of data on riverbed and river temperatures and water surface elevations, from the onset of spawning to the end of emergence, and the provision of those data in-season to fisheries management agencies to assist with emergence timing estimates and evaluations of redd dewatering.« less

A cost effective and operational methodology for wall to wall Above Ground Biomass (AGB) and carbon stocks estimation and mapping: Nepal REDD+

NASA Astrophysics Data System (ADS)

Gilani, H., Sr.; Ganguly, S.; Zhang, G.; Koju, U. A.; Murthy, M. S. R.; Nemani, R. R.; Manandhar, U.; Thapa, G. J.

2015-12-01

Nepal is a landlocked country with 39% forest cover of the total land area (147,181 km2). Under the Forest Carbon Partnership Facility (FCPF) and implemented by the World Bank (WB), Nepal chosen as one of four countries best suitable for results-based payment system for Reducing Emissions from Deforestation and Forest Degradation (REDD and REDD+) scheme. At the national level Landsat based, from 1990 to 2000 the forest area has declined by 2%, i.e. by 1467 km2, whereas from 2000 to 2010 it has declined only by 0.12% i.e. 176 km2. A cost effective monitoring and evaluation system for REDD+ requires a balanced approach of remote sensing and ground measurements. This paper provides, for Nepal a cost effective and operational 30 m Above Ground Biomass (AGB) estimation and mapping methodology using freely available satellite data integrated with field inventory. Leaf Area Index (LAI) generated based on propose methodology by Ganguly et al. (2012) using Landsat-8 the OLI cloud free images. To generate tree canopy height map, a density scatter graph between the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat) estimated maximum height and Landsat LAI nearest to the center coordinates of the GLAS shots show a moderate but significant exponential correlation (31.211*LAI0.4593, R2= 0.33, RMSE=13.25 m). From the field well distributed circular (750m2 and 500m2), 1124 field plots (0.001% representation of forest cover) measured which were used for estimation AGB (ton/ha) using Sharma et al. (1990) proposed equations for all tree species of Nepal. A satisfactory linear relationship (AGB = 8.7018*Hmax-101.24, R2=0.67, RMSE=7.2 ton/ha) achieved between maximum canopy height (Hmax) and AGB (ton/ha). This cost effective and operational methodology is replicable, over 5-10 years with minimum ground samples through integration of satellite images. Developed AGB used to produce optimum fuel wood scenarios using population and road accessibility datasets.

Vietnam's forest transition in retrospect: demonstrating weaknesses in business-as-usual scenarios for REDD.

PubMed

Ankersen, Jeppe; Grogan, Kenneth; Mertz, Ole; Fensholt, Rasmus; Castella, Jean-Christophe; Lestrelin, Guillaume; Nguyen, Dinh Tien; Danielsen, Finn; Brofeldt, Søren; Rasmussen, Kjeld

2015-05-01

One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.

Vietnam's Forest Transition in Retrospect: Demonstrating Weaknesses in Business-as-Usual Scenarios for REDD+

NASA Astrophysics Data System (ADS)

Ankersen, Jeppe; Grogan, Kenneth; Mertz, Ole; Fensholt, Rasmus; Castella, Jean-Christophe; Lestrelin, Guillaume; Nguyen, Dinh Tien; Danielsen, Finn; Brofeldt, Søren; Rasmussen, Kjeld

2015-05-01

One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.

Estimating terrestrial aboveground biomass estimation using lidar remote sensing: a meta-analysis

NASA Astrophysics Data System (ADS)

Zolkos, S. G.; Goetz, S. J.; Dubayah, R.

2012-12-01

Estimating biomass of terrestrial vegetation is a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD). The accuracy of biomass estimates is important in the context carbon markets emerging under REDD, since areas with more accurate estimates command higher prices, but also for characterizing uncertainty in estimates of carbon cycling and the global carbon budget. There is particular interest in mapping biomass so that carbon stocks and stock changes can be monitored consistently across a range of scales - from relatively small projects (tens of hectares) to national or continental scales - but also so that other benefits of forest conservation can be factored into decision making (e.g. biodiversity and habitat corridors). We conducted an analysis of reported biomass accuracy estimates from more than 60 refereed articles using different remote sensing platforms (aircraft and satellite) and sensor types (optical, radar, lidar), with a particular focus on lidar since those papers reported the greatest efficacy (lowest errors) when used in the a synergistic manner with other coincident multi-sensor measurements. We show systematic differences in accuracy between different types of lidar systems flown on different platforms but, perhaps more importantly, differences between forest types (biomes) and plot sizes used for field calibration and assessment. We discuss these findings in relation to monitoring, reporting and verification under REDD, and also in the context of more systematic assessment of factors that influence accuracy and error estimation.

Enhanced systems for measuring and monitoring REDD+: Opportunities to improve the accuracy of emission factor and activity data in Indonesia

NASA Astrophysics Data System (ADS)

Solichin

The importance of accurate measurement of forest biomass in Indonesia has been growing ever since climate change mitigation schemes, particularly the reduction of emissions from deforestation and forest degradation scheme (known as REDD+), were constitutionally accepted by the government of Indonesia. The need for an accurate system of historical and actual forest monitoring has also become more pronounced, as such a system would afford a better understanding of the role of forests in climate change and allow for the quantification of the impact of activities implemented to reduce greenhouse gas emissions. The aim of this study was to enhance the accuracy of estimations of carbon stocks and to monitor emissions in tropical forests. The research encompassed various scales (from trees and stands to landscape-sized scales) and a wide range of aspects, from evaluation and development of allometric equations to exploration of the potential of existing forest inventory databases and evaluation of cutting-edge technology for non-destructive sampling and accurate forest biomass mapping over large areas. In this study, I explored whether accuracy--especially regarding the identification and reduction of bias--of forest aboveground biomass (AGB) estimates in Indonesia could be improved through (1) development and refinement of allometric equations for major forest types, (2) integration of existing large forest inventory datasets, (3) assessing nondestructive sampling techniques for tree AGB measurement, and (4) landscape-scale mapping of AGB and forest cover using lidar. This thesis provides essential foundations to improve the estimation of forest AGB at tree scale through development of new AGB equations for several major forest types in Indonesia. I successfully developed new allometric equations using large datasets from various forest types that enable us to estimate tree aboveground biomass for both forest type specific and generic equations. My models outperformed the existing local equations, with lower bias and higher precision of the AGB estimates. This study also highlights the potential advantages and challenges of using terrestrial lidar and the acoustic velocity tool for non-destructive sampling of tree biomass to enable more sample collection without the felling of trees. Further, I explored whether existing forest inventories and permanent sample plot datasets can be integrated into Indonesia's existing carbon accounting system. My investigation of these existing datasets found that through quality assurance tests these datasets are essential to be integrated into national and provincial forest monitoring and carbon accounting systems. Integration of this information would eventually improve the accuracy of the estimates of forest carbon stocks, biomass growth, mortality and emission factors from deforestation and forest degradation. At landscape scale, this study demonstrates the capability of airborne lidar for forest monitoring and forest cover classification in tropical peat swamp ecosystems. The mapping application using airborne lidar showed a more accurate and precise classification of land and forest cover when compared with mapping using optical and active sensors. To reduce the cost of lidar acquisition, this study assessed the optimum lidar return density for forest monitoring. I found that the density of lidar return could be reduced to at least 1 return per 4 m2. Overall, this study provides essential scientific background to improve the accuracy of forest AGB estimates. Therefore, the described results and techniques should be integrated into the existing monitoring systems to assess emission reduction targets and the impact of REDD+ implementation.

Improved estimation of forest area in tropical Africa through ALOS/PALSAR 50-m orthorectified mosaic images

NASA Astrophysics Data System (ADS)

Dong, J.; Xiao, X.; Li, L.; Tenku, S. N.; Zhang, G.; Biradar, C. M.

2013-12-01

Tropical and moist Africa has one of the largest rainforests in the world. However, our knowledge about its forest area and spatial extent is still very limited. Forest area datasets from the Food and Agriculture Organization (FAO) Forest Resource Assessment (FRA) and the analyses of optical images (e.g., MODIS and MERIS) had a significant discrepancy, and they cannot meet the requirements to support the studies of forest carbon cycle and biodiversity, as well as the implementation of reducing emissions from deforestation and forest degradation (REDD+). The reasons for the large data discrepancy are complex and may attribute to the frequent cloud cover, coarse spatial resolution of images (MODIS, MERIS), diverse forest definition and classification approaches. In this study we generated a forest cover map in central Africa at 50-m resolution through the use of the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) 50-m orthorectified mosaic imagery in 2009. The resultant forest map was evaluated by the ground-reference data collected from the Geo-referenced Field Photo Library and Google Earth, and it has a reasonably high accuracy (producer's accuracy 83% and user's accuracy 94%). We also compared the PALSAR-based forest map with other three forest cover products (MCD12Q1 2009, GlobCover 2009 and VCF tree cover 2009) at the scales of (1) entire study domain and (2) selected sample regions. This new PALSAR-based 50-m forest cover map is likely to help reduce the uncertainty in forest area estimation, and better quantify and track deforestation, REDD+ implementation, and biodiversity conservation in central Africa.

Spatial variability of Chinook salmon spawning distribution and habitat preferences

USGS Publications Warehouse

Cram, Jeremy M.; Torgersen, Christian E.; Klett, Ryan S.; Pess, George R.; May, Darran; Pearsons, Todd N.; Dittman, Andrew H.

2017-01-01

We investigated physical habitat conditions associated with the spawning sites of Chinook Salmon Oncorhynchus tshawytscha and the interannual consistency of spawning distribution across multiple spatial scales using a combination of spatially continuous and discrete sampling methods. We conducted a census of aquatic habitat in 76 km of the upper main-stem Yakima River in Washington and evaluated spawning site distribution using redd survey data from 2004 to 2008. Interannual reoccupation of spawning areas was high, ranging from an average Pearson’s correlation of 0.62 to 0.98 in channel subunits and 10-km reaches, respectively. Annual variance in the interannual correlation of spawning distribution was highest in channel units and subunits, but it was low at reach scales. In 13 of 15 models developed for individual years (2004–2008) and reach lengths (800 m, 3 km, 6 km), stream power and depth were the primary predictors of redd abundance. Multiple channels and overhead cover were patchy but were important secondary and tertiary predictors of reach-scale spawning site selection. Within channel units and subunits, pool tails and thermal variability, which may be associated with hyporheic exchange, were important predictors of spawning. We identified spawning habitat preferences within reaches and channel units that are relevant for salmonid habitat restoration planning. We also identified a threshold (i.e., 2-km reaches) beyond which interannual spawning distribution was markedly consistent, which may be informative for prioritizing habitat restoration or conservation. Management actions may be improved through enhanced understanding of spawning habitat preferences and the consistency with which Chinook Salmon reoccupy spawning areas at different spatial scales.

Climate Mitigation Versus Agriculture in the Tropics

NASA Astrophysics Data System (ADS)

McAfee, K.

2011-12-01

Significant new drivers of land-use change in the tropics are market-based strategies for climate-change mitigation and biodiversity conservation. These strategies are based on the putative monetary values of new commodities: genetic resources and ecosystem services, especially carbon sequestration services by forests. Payments for Ecosystem Services projects are expanding in Latin America, Asia, and some parts of Africa, promising a 'triple-win' for nature, the private sector, and the poor. Analysis of Mexico's national PES program and review of a growing body of PES case studies, however, reveal a pattern of conflict between poverty alleviation and other social goals, on the one hand, and the market-efficiency criteria that frame many PES projects, on the other hand. This poses a warning for more ambitious, global schemes based on similar principles, such as Reduced Emissions from Deforestation and Degradation (REDD). Additionally, transnational trade in carbon offsets, seen as a source of finance for PES and for REDD, puts climate policy on a collision course with agriculture, particularly given the context of closing land frontiers and international 'land-grabbing' claims on land for food-export plantations. Because market-based PES and REDD tend to target small- and medium-scale farmers, they are likely to constrain agriculture for domestic needs in regions where food security is already weak. Land-use governance based on conservation-by-commercialization can be compared to alternative approaches that link greening, food production, and social equity in a more integrated way, by combining scientific and local ecological and agroecological knowledge with strategies for rural revitalization and development.

Dealing with locally-driven degradation: A quick start option under REDD+.

PubMed

Skutsch, Margaret M; Torres, Arturo Balderas; Mwampamba, Tuyeni H; Ghilardi, Adrian; Herold, Martin

2011-12-28

The paper reviews a number of challenges associated with reducing degradation and its related emissions through national approaches to REDD+ under UNFCCC policy. It proposes that in many countries, it may in the short run be easier to deal with the kinds of degradation that result from locally driven community over-exploitation of forest for livelihoods, than from selective logging or fire control. Such degradation is low-level, but chronic, and is experienced over very large forest areas. Community forest management programmes tend to result not only in reduced degradation, but also in forest enhancement; moreover they are often popular, and do not require major political shifts. In principle these approaches therefore offer a quick start option for REDD+. Developing reference emissions levels for low-level locally driven degradation is difficult however given that stock losses and gains are too small to be identified and measured using remote sensing, and that in most countries there is little or no forest inventory data available. We therefore propose that forest management initiatives at the local level, such as those promoted by community forest management programmes, should monitor, and be credited for, only the net increase in carbon stock over the implementation period, as assessed by ground level surveys at the start and end of the period. This would also resolve the problem of nesting (ensuring that all credits are accounted for against the national reference emission level), since communities and others at the local level would be rewarded only for increased sequestration, while the national reference emission level would deal only with reductions in emissions from deforestation and degradation.

Making biodiversity-friendly cocoa pay: combining yield, certification, and REDD for shade management.

PubMed

Waldron, A; Justicia, R; Smith, L E

2015-03-01

The twin United Nations' Millennium Development Goals of biodiversity preservation and poverty reduction both strongly depend on actions in the tropics. In particular, traditional agroforestry could be critical to both biological conservation and human livelihoods in human-altered rainforest areas. However, traditional agroforestry is rapidly disappearing, because the system itself is economically precarious, and because the forest trees that shade traditional crops are now perceived to be overly detrimental to agricultural yield. Here, we show a case where the commonly used agroforestry shade metric, canopy cover, would indeed suggest complete removal of shade trees to maximize yield, with strongly negative biodiversity and climate implications. However, a yield over 50% higher was achievable if approximately 100 shade trees per hectare were planted in a spatially organized fashion, a win-win for biodiversity and the smallholder. The higher yield option was detected by optimizing simultaneously for canopy cover, and a second shade metric, neighboring tree density, which was designed to better capture the yield value of ecological services flowing from forest trees. Nevertheless, even a 50% yield increase may prove insufficient to stop farmers converting away from traditional agroforestry. To further increase agroforestry rents, we apply our results to the design of a sustainable certification (eco-labelling) scheme for cocoa-based products in a biodiversity hotspot, and consider their implications for the use of the United Nations REDD (reducing emissions from deforestation and forest degradation) program in agroforestry systems. Combining yield boost, certification, and REDD has the potential to incentivize eco-friendly agroforestry and lift smallholders out of poverty, simultaneously.

Effects of Experimental High Flow Releases and Increased Fluctuations in Flow from Glen Canyon Dam on Abundance, Growth, and Survival Rates of Early Life Stages of Rainbow Trout in the Lee's Ferry Reach of the Colorado River

NASA Astrophysics Data System (ADS)

Korman, Josh

2010-05-01

The abundance of adult fish populations is controlled by the growth and survival rates of early life stages. Evaluating the effects of flow regimes on early life stages is therefore critical to determine how these regimes affect the abundance of adult populations. Experimental high flow releases from Glen Canyon Dam, primarily intended to conserve fine sediment and improve habitat conditions for native fish in the Colorado River in Grand Canyon, AZ, have been conducted in 1996, 2004, and 2008. These flows potentially affect the Lee's Ferry reach rainbow trout population, located immediately downstream of the dam, which supports a highly valued fishery and likely influences the abundance of rainbow trout in Grand Canyon. Due to concerns about negative effects of high trout abundance on endangered native fish, hourly variation in flow from Glen Canyon Dam was experimentally increased between 2003 and 2005 to reduce trout abundance. This study reports on the effects of experimental high flow releases and fluctuating flows on early life stages of rainbow trout in the Lee's Ferry reach based on monthly sampling of redds (egg nests) and the abundance and growth of age-0 trout between 2003 and 2009. Data on spawn timing, spawning elevations, and intergravel temperatures were integrated in a model to estimate the magnitude and seasonal trend in incubation mortality resulting from redd dewatering due to fluctuations in flow. Experimental fluctuations from January through March promoted spawning at higher elevations where the duration of dewatering was longer and intergravel temperatures exceeded lethal thresholds. Flow-dependent incubation mortality rates were 24% (2003) and 50% (2004) in years with higher flow fluctuations, compared to 5-11% under normal operations (2006-2009). Spatial and temporal predictions of mortality were consistent with direct observations of egg mortality determined from the excavation of 125 redds. The amount of variation in backcalculated hatch date distributions predicted by flow-independent (84-93%) and flow-dependent (82-91%) incubation loss models were similar. Age-0 abundance was generally independent of viable egg deposition, except in one year when egg deposition was 10-fold lower due to reduced spawning activity. There was no evidence from the hatch date or stock-recruitment analysis that flow-dependent incubation losses, although large in experimental years, affected the abundance of the age-0 population. The data indicate that strong compensation in survival rates shortly after emergence mitigated the impact of flow-dependent losses. Multiple lines of evidence demonstrated that the March 2008 high flow experiment (HFE) resulted in a large increase in early survival rates (fertilization to ~1-2 months from emergence) of age-0 trout due an improvement in habitat conditions. A stock-recruitment analysis indicated that age-0 abundance in July 2008 was over four-fold higher than expected given the number of viable redds that produced these fish. A hatch date analysis indicated that early survival rates were much higher for cohorts that emerged about two months after the HFE. These cohorts, which were fertilized after the HFE, were not exposed to high flows and emerged into better quality habitat. Inter annual differences in growth of age-0 trout based on otolith microstructure support this hypothesis. Growth rates in the summer and fall of 2008 (0.44 mm·day-1) were virtually the same as in 2006 (0.46 mm·day-1), the highest recorded over six years, even though abundance was eight-fold greater in 2008. I speculate that high flows in 2008 increased interstitial spaces in the substrate and food availability or quality, leading to higher early survival of recently emerged trout and better growth during summer and fall. Abundance in 2009 was over two-fold higher than expected, possibly indicating that the effect of the HFE on early life stages was somewhat persistent.

Snake River Sockeye Salmon Captive Broodstock Program Research Elements : 2007 Annual Project Progess Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Mike; Plaster, Kurtis; Redfield, Laura

2008-12-17

On November 20, 1991, the National Oceanic Atmospheric Administration listed Snake River sockeye salmon Oncorhynchus nerka as endangered under the Endangered Species Act of 1973. In 1991, the Shoshone-Bannock Tribes (SBT) and Idaho Department of Fish and Game (IDFG) initiated the Snake River Sockeye Salmon Captive Broodstock Program to conserve and rebuild populations in Idaho. Restoration efforts are focused on Redfish, Pettit, and Alturas lakes within the Sawtooth Valley. The first release of hatchery-produced adults occurred in 1993. The first release of juvenile sockeye salmon from the captive broodstock program occurred in 1994. In 1999, the first anadromous adult returnsmore » from the captive broodstock program were recorded when six jacks and one jill were captured at the IDFG Sawtooth Fish Hatchery. In 2007, progeny from the captive broodstock program were released using four strategies: (1) eyed-eggs were planted in Pettit Lake in November; (2) age-0 presmolts were released to Alturas, Pettit, and Redfish lakes in October; (3) age-1 smolts were released into Redfish Lake Creek and the upper Salmon River in May; and (4) hatchery-produced adult sockeye salmon were released to Redfish Lake for volitional spawning in September. Oncorhynchus nerka population monitoring was conducted on Redfish, Alturas, and Pettit lakes using a midwater trawl in September 2007. Population abundances were estimated at 73,702 fish for Redfish Lake, 124,073 fish for Alturas Lake, and 14,746 fish for Pettit Lake. Angler surveys were conducted from May 26 through August 7, 2007 on Redfish Lake to estimate kokanee harvest. On Redfish Lake, we interviewed 102 anglers and estimated that 56 kokanee were harvested. The calculated kokanee catch rate was 0.03 fish/hour for each kokanee kept. The juvenile out-migrant trap on Redfish Lake Creek was operated from April 14 to June 13, 2007. We estimated that 5,280 natural origin and 14,256 hatchery origin sockeye salmon smolts out-migrated from Redfish Lake in 2007. The hatchery origin component originated from a 2006 fall presmolt direct-release. The juvenile out-migrant traps on Alturas Lake Creek and Pettit Lake Creek were operated by the SBT from April 19 to May 23, 2007 and April 18 to May 29, 2007, respectively. The SBT estimated 1,749 natural origin and 4,695 hatchery origin sockeye salmon smolts out-migrated from Pettit Lake and estimated 8,994 natural origin and 6,897 hatchery origin sockeye salmon smolts out-migrated from Alturas Lake in 2007. The hatchery origin component of sockeye salmon out-migrants originated from fall presmolt direct-releases made to Pettit and Alturas lakes in 2006. In 2007, the Stanley Basin Sockeye Technical Oversight Committee (SBSTOC) chose to have all Snake River sockeye salmon juveniles (tagged and untagged) transported due to potential enhanced survival. Therefore, mainstem survival evaluations were only conducted to Lower Granite Dam. Unique PIT tag interrogations from Sawtooth Valley juvenile out-migrant traps to Lower Granite Dam were utilized to estimate survival rates for out-migrating sockeye salmon smolts. Survival rate comparisons were made between smolts originating from Redfish, Alturas, and Pettit lakes and the various release strategies. Alturas Lake hatchery origin smolts tagged at the out-migrant trap recorded the highest survival rate of 78.0%. In 2007, 494 hatchery origin adult sockeye salmon were released to Redfish Lake for natural spawning. We observed 195 areas of excavation in the lake from spawning events. This was the highest number of redds observed in Redfish Lake since the program was initiated. Suspected redds were approximately 3 m x 3 m in size and were constructed by multiple pairs of adults. To monitor the predator population found within the lakes, we monitored bull trout spawning in Fishhook Creek, a tributary to Redfish Lake; and in Alpine Creek, a tributary to Alturas Lake. This represented the tenth consecutive year that the index reaches have been surveyed on these two streams. Adult counts (41 adults) and redd counts (22 redds) in Fishhook Creek increased compared to counts conducted since monitoring began in 1998. Beginning in 2007, we also surveyed an additional trend site in Fishhook Creek resulting in observing 43 adult bull trout and 30 additional redds. Bull trout numbers (13 adults) and the number of redds observed (18 redds) have gradually increased in Alpine Creek compared to counts from initial monitoring.« less

How coarse is too coarse for salmon spawning substrates?

NASA Astrophysics Data System (ADS)

Wooster, J. K.; Riebe, C. S.; Ligon, F. K.; Overstreet, B. T.

2009-12-01

Populations of Pacific salmon species have declined sharply in many rivers of the western US. Reversing these declines is a top priority and expense of many river restoration projects. To help restore salmon populations, managers often inject gravel into rivers, to supplement spawning habitat that has been depleted by gravel mining and the effects of dams—which block sediment and thus impair habitat downstream by coarsening the bed where salmon historically spawned. However, there is little quantitative understanding nor a methodology for determining when a river bed has become too coarse for salmon spawning. Hence there is little scientific basis for selecting sites that would optimize the restoration benefits of gravel injection (e.g., sites where flow velocities are suitable but bed materials are too coarse for spawning). To develop a quantitative understanding of what makes river beds too coarse for salmon spawning, we studied redds and spawning use in a series of California and Washington rivers where salmon spawning ability appears to be affected by coarse bed material. Our working hypothesis is that for a given flow condition, there is a maximum “threshold” particle size that a salmon of a given size is able to excavate and/or move as she builds her redd. A second, related hypothesis is that spawning use should decrease and eventually become impossible with increasing percent coverage by immovable particles. To test these hypotheses, we quantified the sizes and spatial distributions of immovably coarse particles in a series of salmon redds in each river during the peak of spawning. We also quantified spawning use and how it relates to percent coverage by immovable particles. Results from our studies of fall-run chinook salmon (Oncorhynchus tshawytsha) in the Feather River suggest that immovable particle size varies as a function of flow velocity over the redd, implying that faster water helps fish move bigger particles. Our Feather River study also suggests that the immovable particle size varies as a function of particle shape. Results from our study of fall run chinook salmon in the Sacramento River suggest that spawning is not possible when the bed is more than 40% covered by immovable particles, consistent with our second hypotheses. We will explore these relationships further in fall 2009, when we collect data on threshold particle sizes and spawning use for both pink salmon (O. gorbuscha) in the Puyallup River, and chinook salmon in the Trinity River. Because pink salmon are significantly smaller than chinook salmon, we expect that their redd building success is constrained by a lower average threshold particle size. We expect that there will be a range of threshold sizes for each run, depending on intra-run variability in fish size and variations in flow velocity. Taken together we expect that our results will demonstrate the feasibility of a new methodology for determining when a bed has become too coarse, thus contributing to more effective management of rivers where monitoring of spawning suitability of natural gravels is a priority.

Education Highlights: Food-Energy-Water Nexus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Redd, Shanterell; Zvolanek, Emily

Argonne intern Shanterell Redd from Tougaloo College worked with Argonne mentor Emily Zvolanek in studying the food-energy-water-women nexus in Egypt and Jordan. This research will help scientists determine sustainable ways in which women in developing countries gather and use non-renewable resources.

A biomass representative land cover classification for the Democratic Republic of Congo derived from the Forets D'Afrique Central Evaluee par Teledetection (FACET) data set

NASA Astrophysics Data System (ADS)

Molinario, G.; Hansen, M.; Potapov, P.; Altstatt, A. L.; Justice, C. O.

2012-12-01

The FACET forest cover and forest cover loss 2000-2005-2010 data set has been produced by South Dakota State University, the University of Maryland and the Kinshasa-based Observatoire Satellital des Forets D'Afrique Central (OSFAC) with funding from the USAID Central African Regional Program for the Environment (CARPE). The product is now available or being finalized for the DRC, the ROC and Gabon with plans to complete all Congo Basin countries. While FACET provides unprecedented synoptic detail in the extent of Congo Basin forest and the forest cover loss, additional information is required to stratify land cover into types indicative of biomass content. Analysis of the FACET patterns of deforestation, more detailed remote sensing analysis of biophysical attributes within the FACET land cover classes and GIS-derived classes of degradation obtained through variable distance buffers based on relevant literature and ground truth data are combined with the existing FACET classes to produce a ranking of land cover from low biomass to high biomass for the Democratic Republic of Congo. The resulting classification can be used in all Reduced Emissions from Degradation and Deforestation (REDD) pre-inventory phases when baseline forest cover needs to be known and the location and amount of forest biomass inventory plots needs to be designed. FACET cover loss classes were kept in the classification and can provide the Monitoring, Reporting and Verification tools needed for REDD projects. The project will be demonstrated for the Maringa Lopori Wamba Landscape of the DRC where this work was funded by the African Wildlife Foundation to support the design of a REDD pilot project.

Fall Chinook Salmon Spawning Ground Surveys in the Snake River Basin Upriver of Lower Granite Dam, 2005 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia, A.P.; Bradbury, S.; Arnsberg, B.D.

2006-10-01

Redd counts are routinely used to document the spawning distribution of fall Chinook salmon (Oncorhynchus tshawytscha) in the Snake River basin upriver of Lower Granite Dam. The first reported redd counts were from aerial searches conducted intermittently between 1959 and 1978 (Irving and Bjornn 1981, Witty 1988; Groves and Chandler 1996)(Appendix 1). In 1986, the Washington Department of Fish and Wildlife began an annual monitoring program that, in addition to the Snake River, included aerial searches of the Grande Ronde River the first year (Seidel and Bugert 1987), and the Imnaha River in subsequent years (Seidel et al. 1988; Bugertmore » et al. 1989-1991; Mendel et al. 1992). The U. S. Fish and Wildlife Service and Idaho Power Company began contributing to this effort in 1991 by increasing the number of aerial searches conducted each year and adding underwater searches in areas of the Snake River that were too deep to be searched from the air (Connor et al. 1993; Garcia et al. 1994a, 1994b, 1996-2005; Groves 1993; Groves and Chandler 1996). The Nez Perce Tribe added aerial searches in the Clearwater River basin beginning in 1988 (Arnsberg et. al 1992), and the Salmon River beginning in 1992. Currently searches are conducted cooperatively by the Nez Perce Tribe, Idaho Power Company, and U.S. Fish and Wildlife Service. Our objective for this report was to consolidate the findings from annual redd searches into a single document, containing detailed information about the searches from the most recent spawning season, and summary information from previous years. The work conducted in 2005 was funded by the Bonneville Power Administration and Idaho Power Company.« less

Fall Chinook Salmon Spawning Ground Surveys in the Snake River Basin Upriver of Lower Granite Dam, Annual Report 2002.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia, Aaron P.; Bradbury, S.M.; Arnsberg, Billy D.

2003-09-01

Redd counts were used to document the spawning distribution of fall chinook salmon (Oncorhynchus tshawytscha) in the Snake River basin upriver of Lower Granite Dam. The first reported redd counts were from aerial searches conducted intermittently between 1959 and 1978 (Irving and Bjornn 1981, Witty 1988; Groves and Chandler 1996)(Appendix 1). In 1986, the Washington Department of Fish and Wildlife began an annual monitoring program that, in addition to the Snake River, included aerial searches of the Grande Ronde River the first year (Seidel and Bugert 1987), and the Imnaha River in subsequent years (Seidel et al. 1988; Bugert etmore » al. 1989-1991; Mendel et al. 1992). The U. S. Fish and Wildlife Service and Idaho Power Company began contributing to this effort in 1991 by increasing the number of aerial searches conducted each year and adding underwater searches in areas of the Snake River that were too deep to be searched from the air (Connor et al. 1993; Garcia et al. 1994a, 1994b, 1996-2001; Groves 1993; Groves and Chandler 1996). The Nez Perce Tribe added aerial searches in the Clearwater River basin beginning in 1988 (Arnsberg et. al 1992) and the Salmon River beginning in 1992. Currently searches are conducted cooperatively by the Nez Perce Tribe, Idaho Power Company, and U. S. Fish and Wildlife Service. Our objective for this report was to consolidate the findings from annual redd searches into a single document containing detailed information about the searches from the most recent spawning season, and summary information from previous years. The work conducted in 2002 was funded by the Bonneville Power Administration (Projects 1998-01-003 and 1994-03-400) and the Idaho Power Company.« less

Fall Chinook Salmon Spawning Ground Surveys in the Snake River Basin Upriver of Lower Granite Dam, 2007 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia, A.P.; Bradbury, S.; Arnsberg, B.D.

2008-11-25

Redd counts are routinely used to document the spawning distribution of fall Chinook salmon (Oncorhynchus tshawytscha) in the Snake River basin upriver of Lower Granite Dam. The first reported redd counts were from aerial searches conducted intermittently between 1959 and 1978 (Irving and Bjornn 1981, Witty 1988; Groves and Chandler 1996)(Appendix 1). In 1986, the Washington Department of Fish and Wildlife began an annual monitoring program that, in addition to the Snake River, included aerial searches of the Grande Ronde River the first year (Seidel and Bugert 1987), and the Imnaha River in subsequent years (Seidel et al. 1988; Bugertmore » et al. 1989-1991; Mendel et al. 1992). The U. S. Fish and Wildlife Service and Idaho Power Company began contributing to this effort in 1991 by increasing the number of aerial searches conducted each year and adding underwater searches in areas of the Snake River that were too deep to be searched from the air (Connor et al. 1993; Garcia et al. 1994a, 1994b, 1996-2007; Groves 1993; Groves and Chandler 1996). The Nez Perce Tribe added aerial searches in the Clearwater River basin beginning in 1988 (Arnsberg et. al 1992), and the Salmon River beginning in 1992. Currently searches are conducted cooperatively by the Nez Perce Tribe, Idaho Power Company, and U. S. Fish and Wildlife Service. Our objective for this report was to consolidate the findings from annual redd searches counted upstream of Lower Granite Dam into a single document, containing detailed information about the searches from the most recent spawning season, and summary information from previous years. The work conducted in 2007 was funded by the Bonneville Power Administration and Idaho Power Company.« less

Fall Chinook Salmon Spawning Ground Surveys in the Snake River Basin Upriver of Lower Granite Dam, Annual Report 2003.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia, A.P.; Bradbury, S.M.; Arnsberg, B.D.

2004-08-01

Redd counts were used to document the spawning distribution of fall chinook salmon (Oncorhynchus tshawytscha) in the Snake River basin upriver of Lower Granite Dam. The first reported redd counts were from aerial searches conducted intermittently between 1959 and 1978 (Irving and Bjornn 1981, Witty 1988; Groves and Chandler 1996)(Appendix 1). In 1986, the Washington Department of Fish and Wildlife began an annual monitoring program that, in addition to the Snake River, included aerial searches of the Grande Ronde River the first year (Seidel and Bugert 1987), and the Imnaha River in subsequent years (Seidel et al. 1988; Bugert etmore » al. 1989-1991; Mendel et al. 1992). The U. S. Fish and Wildlife Service and Idaho Power Company began contributing to this effort in 1991 by increasing the number of aerial searches conducted each year and adding underwater searches in areas of the Snake River that were too deep to be searched from the air (Connor et al. 1993; Garcia et al. 1994a, 1994b, 1996-2003; Groves 1993; Groves and Chandler 1996). The Nez Perce Tribe added aerial searches in the Clearwater River basin beginning in 1988 (Arnsberg et. al 1992) and the Salmon River beginning in 1992. Currently searches are conducted cooperatively by the Nez Perce Tribe, Idaho Power Company, and U. S. Fish and Wildlife Service. Our objective for this report was to consolidate the findings from annual redd searches into a single document containing detailed information about the searches from the most recent spawning season, and summary information from previous years. The work conducted in 2003 was funded by the Bonneville Power Administration (Projects 199801003, 199801004, 199403400, 198335003), Idaho Power Company, and Bureau of Land Management.« less

Fall Chinook Salmon Spawning Ground Surveys in the Snake River Basin Upriver of Lower Granite Dam, 2004 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia, A.P.; Bradbury, S.; Arnsberg, B.D.

2005-10-01

Redd counts were used to document the spawning distribution of fall Chinook salmon (Oncorhynchus tshawytscha) in the Snake River basin upriver of Lower Granite Dam. The first reported redd counts were from aerial searches conducted intermittently between 1959 and 1978 (Irving and Bjornn 1981, Witty 1988; Groves and Chandler 1996)(Appendix 1). In 1986, the Washington Department of Fish and Wildlife began an annual monitoring program that, in addition to the Snake River, included aerial searches of the Grande Ronde River the first year (Seidel and Bugert 1987), and the Imnaha River in subsequent years (Seidel et al. 1988; Bugert etmore » al. 1989-1991; Mendel et al. 1992). The U.S. Fish and Wildlife Service and Idaho Power Company began contributing to this effort in 1991 by increasing the number of aerial searches conducted each year and adding underwater searches in areas of the Snake River that were too deep to be searched from the air (Connor et al. 1993; Garcia et al. 1994a, 1994b, 1996-2004; Groves 1993; Groves and Chandler 1996). The Nez Perce Tribe added aerial searches in the Clearwater River basin beginning in 1988 (Arnsberg et. al 1992), and the Salmon River beginning in 1992. Currently searches are conducted cooperatively by the Nez Perce Tribe, Idaho Power Company, and U. S. Fish and Wildlife Service. Our objective for this report was to consolidate the findings from annual redd searches into a single document, containing detailed information about the searches from the most recent spawning season, and summary information from previous years. The work conducted in 2004 was funded by the Bonneville Power Administration, Idaho Power Company, and Bureau of Land Management.« less

Shade tree diversity and aboveground carbon stocks in Theobroma cacao agroforestry systems: implications for REDD+ implementation in a West African cacao landscape.

PubMed

Dawoe, Evans; Asante, Winston; Acheampong, Emmanuel; Bosu, Paul

2016-12-01

The promotion of cacao agroforestry is one of the ways of diversifying farmer income and creating incentives through their inclusion in REDD+ interventions. We estimated the aboveground carbon stocks in cacao and shade trees, determined the floristic diversity of shade trees and explored the possibility of implementing REDD+ interventions in cacao landscapes. Using replicated multi-site transect approach, data were collected from nine 1-ha plots established on 5 km long transects in ten cacao growing districts in Ghana West Africa. Biomass of cacao and shade trees was determined using allometric equations. One thousand four hundred and one (1401) shade trees comprising 109 species from 33 families were recorded. Total number of species ranged from 34 to 49. Newbouldia laevis (Bignoniacea) was the most frequently occurring specie and constituted 43.2 % of all shade trees. The most predominant families were Sterculiaceae and Moraceae (10 species each), followed by Meliaceae and Mimosaceae (8 species each) and Caesalpiniacaea (6 species). Shannon diversity indices (H', H max and J') and species richness were low compared to other similar studies. Shade tree densities ranged from 16.2 ± 3.0 to 22.8 ± 1.7 stems ha -1 and differed significantly between sites. Carbon stocks of shade trees differed between sites but were similar in cacao trees. The average C stock in cacao trees was 7.45 ± 0.41 Mg C ha -1 compared with 8.32 ± 1.15 Mg C ha -1 in the shade trees. Cacao landscapes in Ghana have the potential of contributing to forest carbon stocks enhancement by increasing the stocking density of shade trees to recommended levels.

Dealing with locally-driven degradation: A quick start option under REDD+

PubMed Central

2011-01-01

The paper reviews a number of challenges associated with reducing degradation and its related emissions through national approaches to REDD+ under UNFCCC policy. It proposes that in many countries, it may in the short run be easier to deal with the kinds of degradation that result from locally driven community over-exploitation of forest for livelihoods, than from selective logging or fire control. Such degradation is low-level, but chronic, and is experienced over very large forest areas. Community forest management programmes tend to result not only in reduced degradation, but also in forest enhancement; moreover they are often popular, and do not require major political shifts. In principle these approaches therefore offer a quick start option for REDD+. Developing reference emissions levels for low-level locally driven degradation is difficult however given that stock losses and gains are too small to be identified and measured using remote sensing, and that in most countries there is little or no forest inventory data available. We therefore propose that forest management initiatives at the local level, such as those promoted by community forest management programmes, should monitor, and be credited for, only the net increase in carbon stock over the implementation period, as assessed by ground level surveys at the start and end of the period. This would also resolve the problem of nesting (ensuring that all credits are accounted for against the national reference emission level), since communities and others at the local level would be rewarded only for increased sequestration, while the national reference emission level would deal only with reductions in emissions from deforestation and degradation. PMID:22204698

Aging Reduces the Activation of the mTORC1 Pathway after Resistance Exercise and Protein Intake in Human Skeletal Muscle: Potential Role of REDD1 and Impaired Anabolic Sensitivity.

PubMed

Francaux, Marc; Demeulder, Bénédicte; Naslain, Damien; Fortin, Raphael; Lutz, Olivier; Caty, Gilles; Deldicque, Louise

2016-01-15

This study was designed to better understand the molecular mechanisms involved in the anabolic resistance observed in elderly people. Nine young (22 ± 0.1 years) and 10 older (69 ± 1.7 years) volunteers performed a one-leg extension exercise consisting of 10 × 10 repetitions at 70% of their 3-RM, immediately after which they ingested 30 g of whey protein. Muscle biopsies were taken from the vastus lateralis at rest in the fasted state and 30 min after protein ingestion in the non-exercised (Pro) and exercised (Pro+ex) legs. Plasma insulin levels were determined at the same time points. No age difference was measured in fasting insulin levels but the older subjects had a 50% higher concentration than the young subjects in the fed state (p < 0.05). While no difference was observed in the fasted state, in response to exercise and protein ingestion, the phosphorylation state of PKB (p < 0.05 in Pro and Pro+ex) and S6K1 (p = 0.059 in Pro; p = 0.066 in Pro+ex) was lower in the older subjects compared with the young subjects. After Pro+ex, REDD1 expression tended to be higher (p = 0.087) in the older group while AMPK phosphorylation was not modified by any condition. In conclusion, we show that the activation of the mTORC1 pathway is reduced in skeletal muscle of older subjects after resistance exercise and protein ingestion compared with young subjects, which could be partially due to an increased expression of REDD1 and an impaired anabolic sensitivity.

The density dilemma: limitations on juvenile production in threatened salmon populations

USGS Publications Warehouse

Walters, Annika W.; Copeland, Timothy; Venditti, David A.

2013-01-01

Density-dependent processes have repeatedly been shown to have a central role in salmonid population dynamics, but are often assumed to be negligible for populations at low abundances relative to historical records. Density dependence has been observed in overall spring/summer Snake River Chinook salmon Oncorhynchus tshawytscha production, but it is not clear how patterns observed at the aggregate level relate to individual populations within the basin. We used a Bayesian hierarchical modelling approach to explore the degree of density dependence in juvenile production for nine Idaho populations. Our results indicate that density dependence is ubiquitous, although its strength varies between populations. We also investigated the processes driving the population-level pattern and found density-dependent growth and mortality present for both common life-history strategies, but no evidence of density-dependent movement. Overwinter mortality, spatial clustering of redds and limited resource availability were identified as potentially important limiting factors contributing to density dependence. The ubiquity of density dependence for these threatened populations is alarming as stability at present low abundance levels suggests recovery may be difficult without major changes. We conclude that density dependence at the population level is common and must be considered in demographic analysis and management.

Getting REDD-y: conservation and climate change in Latin America.

PubMed

Hall, Anthony

2011-01-01

Deforestation in Latin America, especially in the Amazon basin, is a major source of greenhouse gases such as carbon dioxide that contribute to global warming. Protected areas play a vital role in minimizing forest loss and in supplying key environmental services, including carbon sequestration and rainfall regulation, which mitigate the adverse impacts of climate change amid a rising tide of economic development in the region. The area of protected forest has expanded rapidly since 1980 to cover one-fifth of Latin America and more than two-fifths of Amazonia, a region whose rain forest captures some 40 percent of Latin America's carbon emissions. The reserve sector has traditionally suffered from severe underfunding, but the possibility of new resources being generated through financial compensation for "reduced emissions from deforestation and forest degradation" (REDD) or "avoided deforestation" under a new Kyoto protocol after 2012 could help strengthen the environmental and social roles of protected areas. However, a number of major implementation and governance challenges will need to be addressed.

Improvement of Anadromous Fish Habitat and Passage in Omak Creek, 2008 Annual Report : February 1, 2008 to January 31, 2009.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasher, Rhonda; Fisher, Christopher

2009-06-09

During the 2008 season, projects completed under BPA project 2000-100-00 included installation of riparian fencing, maintenance of existing riparian fencing, monitoring of at-risk culverts and installation of riparian vegetation along impacted sections of Omak Creek. Redd and snorkel surveys were conducted in Omak Creek to determine steelhead production. Canopy closure surveys were conducted to monitor riparian vegetation recovery after exclusion of cattle since 2000 from a study area commonly known as the Moomaw property. Additional redd and fry surveys were conducted above Mission Falls and in the lower portion of Stapaloop Creek to try and determine whether there has beenmore » successful passage at Mission Falls. Monitoring adult steelhead trying to navigate the falls resulted in the discovery of shallow pool depth at an upper pool that is preventing many fish from successfully navigating the entire falls. The Omak Creek Habitat and Passage Project has worked with NRCS to obtain additional funds to implement projects in 2009 that will address passage at Mission Falls, culvert replacement, as well as additional riparian planting. The Omak Creek Technical Advisory Group (TAG) is currently revising the Omak Creek Watershed Assessment. In addition, the group is revising strategy to focus efforts in targeted areas to provide a greater positive impact within the watershed. In 2008 the NRCS Riparian Technical Team was supposed to assess areas within the watershed that have unique problems and require special treatments to successfully resolve the issues involved. The technical team will be scheduled for 2009 to assist the TAG in developing strategies for these special areas.« less

Structuring economic incentives to reduce emissions from deforestation within Indonesia

PubMed Central

Busch, Jonah; Lubowski, Ruben N.; Godoy, Fabiano; Steininger, Marc; Yusuf, Arief A.; Austin, Kemen; Hewson, Jenny; Juhn, Daniel; Farid, Muhammad; Boltz, Frederick

2012-01-01

We estimate and map the impacts that alternative national and subnational economic incentive structures for reducing emissions from deforestation (REDD+) in Indonesia would have had on greenhouse gas emissions and national and local revenue if they had been in place from 2000 to 2005. The impact of carbon payments on deforestation is calibrated econometrically from the pattern of observed deforestation and spatial variation in the benefits and costs of converting land to agriculture over that time period. We estimate that at an international carbon price of $10/tCO2e, a “mandatory incentive structure,” such as a cap-and-trade or symmetric tax-and-subsidy program, would have reduced emissions by 163–247 MtCO2e/y (20–31% below the without-REDD+ reference scenario), while generating a programmatic budget surplus. In contrast, a “basic voluntary incentive structure” modeled after a standard payment-for-environmental-services program would have reduced emissions nationally by only 45–76 MtCO2e/y (6–9%), while generating a programmatic budget shortfall. By making four policy improvements—paying for net emission reductions at the scale of an entire district rather than site-by-site; paying for reductions relative to reference levels that match business-as-usual levels; sharing a portion of district-level revenues with the national government; and sharing a portion of the national government's responsibility for costs with districts—an “improved voluntary incentive structure” would have been nearly as effective as a mandatory incentive structure, reducing emissions by 136–207 MtCO2e/y (17–26%) and generating a programmatic budget surplus. PMID:22232665

Section summary: Integration of monitoring techniques

Treesearch

Yoshiyuki Kiyono; Rick Turner

2013-01-01

Techniques for monitoring deforestation and associated changes to forest carbon stocks are widespread and well published. In contrast, techniques for monitoring forest degradation are relatively untested in developing countries despite their inclusion in UNFCCC REDD+ negotiations. In the Mekong countries, forest degradation may contribute a substantial portion of the...

78 FR 42062 - Columbia Gas Transmission, LLC; Notice of Intent to Prepare an Environmental Assessment and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-15

... facilities: New compressor station (Redd Farm Compressor Station) on Columbia's existing Line 1570 in... setting; Modifications to the Smithfield Compressor Station consisting of upgrades to the existing... coolers; Modifications to the Glenville Compressor Station by installing two gas-fired turbines, each...

A permeability study on salmonid spawning areas in northern Humboldt County, California

Treesearch

Claire Knopf

2012-01-01

This research was conducted to determine if local salmonid, specifically coho salmon (Oncorhynchus kisutch), Chinook salmon (O. tshawytscha), and the steelhead trout (O. mykiss), redd location is dependent upon the permeability of the streambed. The study took place at four study sites in two coastal...

RS Application for conducting change detection within the Sundarban Mangrove Forest, Bangladesh to meet REDD+ initiatives

NASA Astrophysics Data System (ADS)

Biswas, T.; Maus, P.; Megown, K.

2011-12-01

The U.S. Forest Service (USFS) provided technical support to the Resource Information Management System (RIMS) unit of the Forest Department (FD) of Bangladesh in developing a method to monitor changes within the Sundarbans Reserve Forest using remote sensing and GIS technology to meet the Reducing Emissions from Deforestation and Degradation (REDD+) initiatives within Bangladesh. It included comparing the simple image differencing method with the Z-score outlier change detection method to examine changes within the mangroves of Bangladesh. Landsat data from three time periods (1989, 1999, 2009) were used to quantify change within four canopy cover classes (High, Medium, Low, and Very Low) within Sundarbans. The Z-score change analysis and image differencing was done for all the 6 reflective bands obtained from Landsat and two spectral indices NDVI and NDMI, derived from these bands for each year. Our results indicated very subtle changes in the mangrove forest within the past twenty years and the Z-score analysis was found to be more useful in capturing these subtle changes than the simple image difference method. Percent change in Z-score of NDVI provided the most meaningful index of vegetation change. It was used to summarize change for the entire study area by pixel, by canopy cover classes and the management compartment during this analysis. Our analysis showed less than 5% overall change in area within the mangroves for the entire study period. Percent change in forest canopy cover reduced from 4% in 1989-99 to 2% by 1999-2009 indicating an increase in forest canopy cover. Percent change in NDVI Z-score of each pixel was used to compute the overall percent change in z-score within the entire study area, mean percent change within each canopy cover class and management compartments from 1989 to 1999 and from 1999 to 2009. The above analysis provided insight to the spatial distribution of percent change in NDVI between the study periods and helped in identifying potential area for management intervention. The mean distribution of change from both study periods was observed within ± 20% SD.Our results were in agreement with the independent field study conducted by the US Forest Service earlier the same year for biomass and carbon stock estimation. The 10m field plots that showed a decline in carbon stock between 1995 and 2010 overall coincided with the compartments or region that showed a decline in forest canopy cover between 1999 and 2009 from the present analysis. These results led us to believe that the Z-score analysis can be a potential quantitatively rigorous tool to quantify change in ecosystems that are mostly stable and do not undergo drastic land use or land cover change. The field and remote sensing study together provided important scientific information and direction for future management of the forest resources, baseline information for long term monitoring of the forest, and identifying potential REDD+ Carbon financing projects in Sundarbans, as well as other potential REDD+ sites within forested area of Bangladesh. Given the rising concern and interest in REDD+ initiative we consider the Z-score analysis to be a potential tool in monitoring and providing a quick spatial assessment of change using remote sensing technology.

Near real-time monitoring systems for adaptive management and improved forest governance

NASA Astrophysics Data System (ADS)

Musinsky, J.; Tabor, K.; Cano, A.

2012-12-01

The destruction and degradation of the world's forests from deforestation, illegal logging and fire has wide-ranging environmental and economic impacts, including biodiversity loss, the degradation of ecosystem services and the emission of greenhouse gases. In an effort to strengthen local capacity to respond to these threats, Conservation International has developed a suite of near real-time satellite monitoring systems generating daily alerts, maps and reports of forest fire, fire risk, deforestation and degradation that are used by national and sub-national government agencies, NGO's, scientists, communities, and the media to respond to and report on threats to forest resources. Currently, the systems support more than 1000 subscribers from 45 countries, focusing on Madagascar, Indonesia, Bolivia and Peru. This presentation will explore the types of innovative applications users have found for these data, challenges they've encountered in data acquisition and accuracy, and feedback they've given on the usefulness of these systems for REDD+ implementation, protected areas management and improved forest governance.;

Population viability of the Snake River chinook salmon (Oncorhynchus tshawytscha)

USGS Publications Warehouse

Emlen, John M.

1995-01-01

In the presence of historical data, population viability models of intermediate complexity can be parameterized and utilized to project the consequences of various management actions for endangered species. A general stochastic population dynamics model with density feedback, age structure, and autocorrelated environmental fluctuations was constructed and parameterized for best fit over 36 years of spring chinook salmon (Oncorhynchus tshawytscha) redd count data in five Idaho index streams. Simulations indicate that persistence of the Snake River spring chinook salmon population depends primarily on density-independent mortality. Improvement of rearing habitat, predator control, reduced fishing pressure, and improved dam passage all would alleviate density-independent mortality. The current value of the Ricker α should provide for a continuation of the status quo. A recovery of the population to 1957–1961 levels within 100 years would require an approximately 75% increase in survival and (or) fecundity. Manipulations of the Ricker β are likely to have little or no effect on persistence versus extinction, but considerable influence on population size.

Forest degradation sub-national assessments: Monitoring options for Cambodia, Lao PDR, and Vietnam

Treesearch

Rick Turner; James Halperin; Patricia Manley; Leif Mortenson

2013-01-01

Techniques for monitoring deforestation and associated changes to forest carbon stocks are widespread and well published. In contrast, techniques for monitoring forest degradation are relatively untested in developing countries despite their inclusion in UNFCCC REDD+ negotiations. The Lowering Emissions in Asia's Forests (LEAF) program of the United States Agency...

29 CFR 1910.145 - Specifications for accident prevention signs and tags.

Code of Federal Regulations, 2011 CFR

2011-07-01

... apply to the design, application, and use of signs or symbols (as included in paragraphs (c) through (e.... The reflective border defines the shape of the fluorescent color in daylight and creates a hollow red....D. and Collins, B.L., The Assessment of Safety Symbol Understandability by Different Testing Methods...

29 CFR 1910.145 - Specifications for accident prevention signs and tags.

Code of Federal Regulations, 2010 CFR

2010-07-01

... apply to the design, application, and use of signs or symbols (as included in paragraphs (c) through (e.... The reflective border defines the shape of the fluorescent color in daylight and creates a hollow red....D. and Collins, B.L., The Assessment of Safety Symbol Understandability by Different Testing Methods...

Section summary: Ground-based field measurements

Treesearch

Nophea Sasaki

2013-01-01

Although deforestation has been the main focus of international debate in REDD+, forest degradation could emit even more carbon emissions because forest degradation can take place in any accessible forest. Accounting for emission factors requires the use of stockchange or gain-loss approach depending on the forests in questions. Ground based field measurements are a...

High-resolution carbon mapping on the million-hectare Island of Hawaii

Treesearch

Gregory P. Asner; R. Flint Hughes; Joseph Mascaro; Amanda L. Uowolo; David E. Knapp; James Jacobson; Ty Kennedy-Bowdoin; John K . Clark

2011-01-01

Current markets and international agreements for reducing emissions from deforestation and forest degradation (REDD) rely on carbon (C) monitoring techniques. Combining field measurements, airborne light detection and ranging (LiDAR)-based observations, and satellite-based imagery, we developed a 30-meter-resolution map of aboveground C density spanning 40 vegetation...

Sustainable Landscapes Assessment for the Philippines

Treesearch

Oliver Agoncillo; Jennifer Conje; Susan Cordell; James Halperin; Roopa Karia; Beth Lebow

2011-01-01

As part of their development of a new Country Development Strategy, and with potential for incoming Sustainable Landscapes funding, USAID/Philippines commissioned the U.S. Forest Service to work with them on an assessment of efforts aimed at Reducing Emissions from Deforestation and Forest Degradation (REDD+) in the Philippines, including the role of conservation,...

Mexican Americans Acquiring Bachelor's Degrees: Whose Opportunity?

ERIC Educational Resources Information Center

Evans, Carol

2009-01-01

This study offers a small, highly contextualized counter-example to several recent large-scale analyses depicting Latino underachievement in higher education (R. Fry, 2002; J. Immerwahr, 2003; S. Miller & E. Garcia, 2004; W. Swail, A. Cabrera, & C. Lee, 2004; W. S. Swail, K. E. Redd, & L. W. Perna, 2003). The purpose is to analyze…

Opportunity costs of carbon sequestration in a forest concession in central Africa.

PubMed

Ndjondo, Michel; Gourlet-Fleury, Sylvie; Manlay, Raphaël J; Engone Obiang, Nestor Laurier; Ngomanda, Alfred; Romero, Claudia; Claeys, Florian; Picard, Nicolas

2014-12-01

A large proportion of the tropical rain forests of central Africa undergo periodic selective logging for timber harvesting. The REDD+ mechanism could promote less intensive logging if revenue from the additional carbon stored in the forest compensates financially for the reduced timber yield. Carbon stocks, and timber yields, and their associated values, were predicted at the scale of a forest concession in Gabon over a project scenario of 40 yr with reduced logging intensity. Considering that the timber contribution margin (i.e. the selling price of timber minus its production costs) varies between 10 and US$40 m -3 , the minimum price of carbon that enables carbon revenues to compensate forgone timber benefits ranges between US$4.4 and US$25.9/tCO 2 depending on the management scenario implemented. Where multiple suppliers of emission reductions compete in a REDD+ carbon market, tropical timber companies are likely to change their management practices only if very favourable conditions are met, namely if the timber contribution margin remains low enough and if alternative management practices and associated incentives are appropriately chosen.

The antidepressant sertraline inhibits translation initiation by curtailing mammalian target of rapamycin signaling.

PubMed

Lin, Chen-Ju; Robert, Francis; Sukarieh, Rami; Michnick, Stephen; Pelletier, Jerry

2010-04-15

Sertraline, a selective serotonin reuptake inhibitor, is a widely used antidepressant agent. Here, we show that sertraline also exhibits antiproliferative activity. Exposure to sertraline leads to a concentration-dependent decrease in protein synthesis. Moreover, polysome profile analysis of sertraline-treated cells shows a reduction in polysome content and a concomitant increase in 80S ribosomes. The inhibition in translation caused by sertraline is associated with decreased levels of the eukaryotic initiation factor (eIF) 4F complex, altered localization of eIF4E, and increased eIF2alpha phosphorylation. The latter event leads to increased REDD1 expression, which in turn impinges on the mammalian target of rapamycin (mTOR) pathway by affecting TSC1/2 signaling. Sertraline also independently targets the mTOR signaling pathway downstream of Rheb. In the Emu-myc murine lymphoma model where carcinogenesis is driven by phosphatase and tensin homologue (PTEN) inactivation, sertraline is able to enhance chemosensitivity to doxorubicin. Our results indicate that sertraline exerts antiproliferative activity by targeting the mTOR signaling pathway in a REDD1-dependent manner. (c) 2010 AACR.

Brazilian Amazon Roads and Parks: Temporal & Spatial Deforestation Dynamics

NASA Astrophysics Data System (ADS)

Pfaff, A.; Robalino, J.

2011-12-01

Heterogeneous Forest Impacts of Transport Infrastructure: spatial frontier dynamics & impacts of Brazilian Amazon road changes Prior research on road impacts has almost completely ignored heterogeneity of impacts and as a result both empirically understated potential impact and missed policy potential. We note von Thunen's model suggests not only heterogeneity with distance from market but also specifically road impacts rising then falling with distance ('non-monoThunicity') Endogenous development and partial adjustment dynamics support this for the short run. Causal effects result from studying Brazilian Amazon deforestation (1976-87, 2000-04) using matching for short-run responses to lagged new roads changes (1968-75, 1985-00). We show the critical role of prior development, proxied by 1968 and 1985 road distances, for which exact matching addresses development trends and transforms impact estimates. Splitting the sample on this measure finds confirmation of the nonmonotonic predictions: new road impacts are relatively low if a prior road was close, such that prior transport access and endogenous development dynamics compete with the new road for influence, but also if a prior road was far, since first-decade adjustment in pristine areas is limited; yet in between these bounds, investments immediately raise deforestation significantly. This pattern helps to explain lower estimates within research on a single average impact. It suggests potential for REDD if a country chooses to shift its spatial transport networks. Protected Areas & Brazilian Amazon Deforestation: modeling and testing the impacts of varied PA strategies We model and then estimate the impacts of multiple types of protected areas upon 2000 - 2004 deforestation in the Brazilian Amazon. Our modeling starts with federal versus state objectives and predicts differences in both choice and implementation of each PA strategy that we examine. Our empirical examination brings not only breakdowns sufficient to test the model's implications but also, critically, explicit controls for the influences of the characteristics of protected lands. Controlling for how PAs differ from unprotected lands cuts impact estimates roughly in half, implying that accounting for and planning around site characteristics should be a part of REDD. For instance, we highlight differences among the improved impacts estimates across PA subsets: Federal vs. State vs. Indigenous; 1980s vs. 1990s; and Integral Protection vs. Sustainable Use. Without correcting for the differences in land characteristics, each of the subsets we examine is estimated to cause significant reduction in deforestation. Corrections find Federal and Indigenous prevented more clearing than did State, while Sustainable Use areas blocked more deforestation than Integral Protection. The reason for these unequal shifts in estimates is that the different PA subsets were allocated to different types of locations. That protection's impact is not uniform is important for REDD and those designing institutions should note what local planners may favor.

Annual Carbon Emissions from Deforestation in the Amazon Basin between 2000 and 2010.

PubMed

Song, Xiao-Peng; Huang, Chengquan; Saatchi, Sassan S; Hansen, Matthew C; Townshend, John R

2015-01-01

Reducing emissions from deforestation and forest degradation (REDD+) is considered one of the most cost-effective strategies for mitigating climate change. However, historical deforestation and emission rates-critical inputs for setting reference emission levels for REDD+-are poorly understood. Here we use multi-source, time-series satellite data to quantify carbon emissions from deforestation in the Amazon basin on a year-to-year basis between 2000 and 2010. We first derive annual deforestation indicators by using the Moderate Resolution Imaging Spectroradiometer Vegetation Continuous Fields (MODIS VCF) product. MODIS indicators are calibrated by using a large sample of Landsat data to generate accurate deforestation rates, which are subsequently combined with a spatially explicit biomass dataset to calculate committed annual carbon emissions. Across the study area, the average deforestation and associated carbon emissions were estimated to be 1.59 ± 0.25 M ha•yr(-1) and 0.18 ± 0.07 Pg C•yr(-1) respectively, with substantially different trends and inter-annual variability in different regions. Deforestation in the Brazilian Amazon increased between 2001 and 2004 and declined substantially afterwards, whereas deforestation in the Bolivian Amazon, the Colombian Amazon, and the Peruvian Amazon increased over the study period. The average carbon density of lost forests after 2005 was 130 Mg C•ha(-1), ~11% lower than the average carbon density of remaining forests in year 2010 (144 Mg C•ha(-1)). Moreover, the average carbon density of cleared forests increased at a rate of 7 Mg C•ha(-1)•yr(-1) from 2005 to 2010, suggesting that deforestation has been progressively encroaching into high-biomass lands in the Amazon basin. Spatially explicit, annual deforestation and emission estimates like the ones derived in this study are useful for setting baselines for REDD+ and other emission mitigation programs, and for evaluating the performance of such efforts.

Annual Carbon Emissions from Deforestation in the Amazon Basin between 2000 and 2010

PubMed Central

Song, Xiao-Peng; Huang, Chengquan; Saatchi, Sassan S.; Hansen, Matthew C.; Townshend, John R.

2015-01-01

Reducing emissions from deforestation and forest degradation (REDD+) is considered one of the most cost-effective strategies for mitigating climate change. However, historical deforestation and emission rates―critical inputs for setting reference emission levels for REDD+―are poorly understood. Here we use multi-source, time-series satellite data to quantify carbon emissions from deforestation in the Amazon basin on a year-to-year basis between 2000 and 2010. We first derive annual deforestation indicators by using the Moderate Resolution Imaging Spectroradiometer Vegetation Continuous Fields (MODIS VCF) product. MODIS indicators are calibrated by using a large sample of Landsat data to generate accurate deforestation rates, which are subsequently combined with a spatially explicit biomass dataset to calculate committed annual carbon emissions. Across the study area, the average deforestation and associated carbon emissions were estimated to be 1.59 ± 0.25 M ha•yr−1 and 0.18 ± 0.07 Pg C•yr−1 respectively, with substantially different trends and inter-annual variability in different regions. Deforestation in the Brazilian Amazon increased between 2001 and 2004 and declined substantially afterwards, whereas deforestation in the Bolivian Amazon, the Colombian Amazon, and the Peruvian Amazon increased over the study period. The average carbon density of lost forests after 2005 was 130 Mg C•ha−1, ~11% lower than the average carbon density of remaining forests in year 2010 (144 Mg C•ha−1). Moreover, the average carbon density of cleared forests increased at a rate of 7 Mg C•ha−1•yr−1 from 2005 to 2010, suggesting that deforestation has been progressively encroaching into high-biomass lands in the Amazon basin. Spatially explicit, annual deforestation and emission estimates like the ones derived in this study are useful for setting baselines for REDD+ and other emission mitigation programs, and for evaluating the performance of such efforts. PMID:25951328

Strong Predictability Of Spatially Distributed Physical Habitat Preferences For O. Mykiss Spawning Across Three Spatial Scales

NASA Astrophysics Data System (ADS)

Kammel, L.; Pasternack, G. B.; Wyrick, J. R.; Massa, D.; Bratovich, P.; Johnson, T.

2012-12-01

Currently accepted perception assumes Oncorhynchus mykiss prefer different ranges of similar physical habitat elements for spawning than Chinook salmon (Oncorhynchus tshawytscha), taking into account their difference in size. While there is increasing research interest regarding O. mykiss habitat use and migratory behavior, research conducted to date distinguishing the physical habitat conditions utilized for O. mykiss spawning has not provided quantified understanding of their spawning habitat preferences. The purpose of this study was to use electivity indices and other measures to assess the physical habitat characteristics preferred for O. mykiss spawning in terms of both 1-m scale microhabitat attributes, and landforms at different spatial scales from 0.1-100 times channel width. The testbed for this study was the 37.5-km regulated gravel-cobble Lower Yuba River (LYR). Using spatially distributed 2D hydrodynamic model results, substrate mapping, and a census of O. mykiss redds from two years of observation, micro- and meso-scale representations of physical habitat were tested for their ability to predict spawning habitat preference and avoidance. Overall there was strong stratification of O. mykiss redd occurrence for all representation types of physical habitat. A strong preference of hydraulic conditions was shown for mean water column velocities of 1.18-2.25 ft/s, and water depths of 1.25-2.76 ft. There was a marked preference for the two most upstream alluvial reaches of the LYR (out of 8 total reaches), accounting for 92% of all redds observed. The preferred morphological units (MUs) for O. mykiss spawning were more variable than for Chinook salmon and changed with increasing discharge, demonstrating that O. mykiss shift spawning to different MUs in order to utilize their preferred hydraulic conditions. The substrate range preferred for O. mykiss spawning was within 32-90 mm. Overall, O. mykiss spawning behavior was highly predictable and required a holistic blend of hydraulic and geomorphic representations to explain.

PIT-tagged particle study of bed mobility in a Maine salmon river impacted by logging activities

NASA Astrophysics Data System (ADS)

Thompson, D. M.; Fixler, S. A.; Roberts, K. E.; McKenna, M.; Marshall, A. E.; Koenig, S.

2017-12-01

Presenting an interim report on a study on the Narraguagus River in Maine, which utilizes laser total stations cross-sectional surveys and tracking of passive integrated transponder (PIT) tags embedded in glass spheres to document changes in channel-bed characteristics associated with large wood (LW) additions and natural spawning activities. In 2016, work was initiated to monitor changes in bed elevation and sediment mobility with the addition of LW to the Narraguagus River as part of a restoration effort. Ten cross-sections, spaced 5-m apart, were established and surveyed with a laser total station in each of three different study reaches. The study sites include a control reach, a section with anticipated spawning activities and a site with ongoing LW placement. A grid of 200 glass spheres embedded with PIT tags, with twenty alternating 25-mm and 40-mm size particles equally spaced along each of the ten transects, were placed to serve as point sensors to detect sediment mobilization within each reach. In 2017, the site was revisited to determine if differences in PIT-tagged tracer particle mobilization reflect locations were LW was added and places where Atlantic salmon (Salmo salar) and sea lamprey (Petromyzon marinus) construct spawning redds. The positions of PIT-tagged tracer particles was recorded, but particles were not disturbed or uncovered to permit study of potential reworking of buried tracer particles the following year. Full tracer particle recovery will be determined in 2018 to determine if depths of tracer burial and changes in bed elevation vary among places near redds, LW and main channel locations. The data will be used to determine if salmon redds are preferentially located in either places with greater evidence of sediment reworking or alternatively in stable areas? The study will help determine the degree of bed disruption associated with spawning activities and whether LW placement encourages similar sediment mobilization processes.

Age-related differences in lean mass, protein synthesis and skeletal muscle markers of proteolysis after bed rest and exercise rehabilitation

PubMed Central

Tanner, Ruth E; Brunker, Lucille B; Agergaard, Jakob; Barrows, Katherine M; Briggs, Robert A; Kwon, Oh Sung; Young, Laura M; Hopkins, Paul N; Volpi, Elena; Marcus, Robin L; LaStayo, Paul C; Drummond, Micah J

2015-01-01

Abstract Bed rest-induced muscle loss and impaired muscle recovery may contribute to age-related sarcopenia. It is unknown if there are age-related differences in muscle mass and muscle anabolic and catabolic responses to bed rest. A secondary objective was to determine if rehabilitation could reverse bed rest responses. Nine older and fourteen young adults participated in a 5-day bed rest challenge (BED REST). This was followed by 8 weeks of high intensity resistance exercise (REHAB). Leg lean mass (via dual-energy X-ray absorptiometry; DXA) and strength were determined. Muscle biopsies were collected during a constant stable isotope infusion in the postabsorptive state and after essential amino acid (EAA) ingestion on three occasions: before (PRE), after bed rest and after rehabilitation. Samples were assessed for protein synthesis, mTORC1 signalling, REDD1/2 expression and molecular markers related to muscle proteolysis (MURF1, MAFBX, AMPKα, LC3II/I, Beclin1). We found that leg lean mass and strength decreased in older but not younger adults after bedrest (P < 0.05) and was restored after rehabilitation. EAA-induced mTORC1 signalling and protein synthesis increased before bed rest in both age groups (P < 0.05). Although both groups had blunted mTORC1 signalling, increased REDD2 and MURF1 mRNA after bedrest, only older adults had reduced EAA-induced protein synthesis rates and increased MAFBX mRNA, p-AMPKα and the LC3II/I ratio (P < 0.05). We conclude that older adults are more susceptible than young persons to muscle loss after short-term bed rest. This may be partially explained by a combined suppression of protein synthesis and a marginal increase in proteolytic markers. Finally, rehabilitation restored bed rest-induced deficits in lean mass and strength in older adults. Key points Five days of bed rest resulted in a reduction in leg lean mass and strength in older adults. After bed rest, older (but not younger) adults had reduced amino acid-induced anabolic sensitivity (blunted muscle protein synthesis; MPS) and enhanced markers associated with the ubiquitin proteasome and autophagy–lysosomal systems (increase in molecular markers related to muscle proteolysis). Younger adults did not lose leg lean mass (via DXA) after 5 days of bed rest despite blunted amino acid-induced mTORC1 signalling and increased skeletal muscle REDD1, REDD2 and MURF1 mRNA expression. Exercise rehabilitation restored bed rest-induced deficits in lean mass, strength, nutrient-induced protein anabolism (protein synthesis and mTORC1 signalling) and select muscle proteolytic markers in older adults. PMID:26173027

Implications of sampling design and sample size for national carbon accounting systems

Treesearch

Michael Köhl; Andrew Lister; Charles T. Scott; Thomas Baldauf; Daniel Plugge

2011-01-01

Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of...

Remote sensing application challenges in the Mekong region

Treesearch

Jeffrey Himel

2013-01-01

Forest degradation is not just one of the cornerstones of "REDD+", it is a critical element for Lao PDR and other countries where the primary driver of forest carbon loss is selective logging and small-scale conversion of forest for agriculture rather than deforestation. Unless we can reliably and accurately quantify the area of degradation using remote...

Developing and evaluating rapid field methods to estimate peat carbon

Treesearch

Rodney A. Chimner; Cassandra A. Ott; Charles H. Perry; Randall K. Kolka

2014-01-01

Many international protocols (e.g., REDD+) are developing inventories of ecosystem carbon stocks and fluxes at country and regional scales, which can include peatlands. As the only nationally implemented field inventory and remeasurement of forest soils in the US, the USDA Forest Service Forest Inventory and Analysis Program (FIA) samples the top 20 cm of organic soils...

Detecting and monitoring deforestation and forest degradation: Issues and obstacles for Southeast Asia

Treesearch

Douglas Muchoney; Sharon Hamann

2013-01-01

Forest degradation can be defined as the loss of forest volume, biomass and/or forest productivity caused by natural or human influences. Achieving Reduced Emissions from Deforestation and Forest Degradation (REDD+) requires that deforestation and degradation can be efficiently, reliably, and cost-effectively detected and quantified, often where ground and aerial...

Sustainable forest management of tropical forests can reduce carbon emissions and stabilize timber production

Treesearch

N. Sasaki; G.P. Asner; Yude Pan; W. Knorr; P.B. Durst; H.O. Ma; I. Abe; A.J. Lowe; L.P. Koh

2016-01-01

The REDD+ scheme of the United Nations Framework Conventionon Climate Change has provided opportunities to manage tropical forests for timber production and carbon emission reductions. To determine the appropriate loggingtechniques, we analyzed potential timber production and carbon emission reductions under two logging techniques over a 40-year period of selective...

High-resolution forest carbon stocks and emissions in the Amazon

Treesearch

G. P. Asner; George V. N. Powell; Joseph Mascaro; David E. Knapp; John K. Clark; James Jacobson; Ty Kennedy-Bowdoin; Aravindh Balaji; Guayana Paez-Acosta; Eloy Victoria; Laura Secada; Michael Valqui; R. Flint. Hughes

2010-01-01

Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at...

Assessing the effect of climate change on carbon sequestration in a Mexican dry forest in the Yucatan Peninsula

Treesearch

Z. Dai; K.D. Johnson; R.A. Birdsey; J.L. Hernandez-Stefanoni; J.M. Dupuy

2015-01-01

Assessing the effect of climate change on carbon sequestration in tropical forest ecosystems is important to inform monitoring, reporting, and verification (MRV) for reducing deforestation and forest degradation (REDD), and to effectively assess forest management options under climate change. Two process-based models, Forest-DNDC and Biome-BGC, with different spatial...

Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

Treesearch

Veronika Leitold; Michael Keller; Douglas C Morton; Bruce D Cook; Yosio E Shimabukuro

2015-01-01

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas...

Opportunities and capacity for community-based forest carbon sequestration and monitoring in Ghana

Treesearch

J. Schelhas; S. Samar; Cassandra Johnson; K. Asumadu; F. Tease; J. Stanturf; D. Blay

2010-01-01

International efforts to address global climate change will certainly include Africa’s forests, for example through efforts to reduce emissions from deforestation and forest degradation (REDD)(Sandker et al. 2010). Whether these efforts harm or provide new opportunities for rural people will depend on how programs are designed. In Ghana, as in many developing countries...

Assessing forest degradation in Guyana with GeoEye, Quickbird and Landsat

Treesearch

Bobby Braswell; Steve Hagen; William Salas; Michael Palace; Sandra Brown; Felipe Casarim; Nancy Harris

2013-01-01

Forest degradation is defined as a change in forest quality and condition (e.g. reduction in biomass), while deforestation is a change in forest area. This pilot study evaluated several image processing approaches to map degradation and estimate carbon removals from logging. From the Joint Concept Note on REDD+ cooperation between Guyana and Norway carbon loss as...

Sustainable landscapes in a world of change: tropical forests, land use and implementation of REDD+: Part I

Treesearch

Richard Birdsey; Yude Pan; Richard Houghton

2013-01-01

Tropical forests play a critical role in the Earth system; however, tropical landscapes have changed greatly in recent decades because of increasing demand for land to support agriculture and timber production, fuel wood, and other pressures of population and human economics. The observable results are a legacy of persistent deforestation, forest degradation, increased...

Advancing reference emission levels in subnational and national REDD+ initiatives: a CLASlite approach

PubMed Central

Asner, Gregory P; Joseph, Shijo

2015-01-01

Conservation and monitoring of tropical forests requires accurate information on their extent and change dynamics. Cloud cover, sensor errors and technical barriers associated with satellite remote sensing data continue to prevent many national and sub-national REDD+ initiatives from developing their reference deforestation and forest degradation emission levels. Here we present a framework for large-scale historical forest cover change analysis using free multispectral satellite imagery in an extremely cloudy tropical forest region. The CLASlite approach provided highly automated mapping of tropical forest cover, deforestation and degradation from Landsat satellite imagery. Critically, the fractional cover of forest photosynthetic vegetation, non-photosynthetic vegetation, and bare substrates calculated by CLASlite provided scene-invariant quantities for forest cover, allowing for systematic mosaicking of incomplete satellite data coverage. A synthesized satellite-based data set of forest cover was thereby created, reducing image incompleteness caused by clouds, shadows or sensor errors. This approach can readily be implemented by single operators with highly constrained budgets. We test this framework on tropical forests of the Colombian Pacific Coast (Chocó) – one of the cloudiest regions on Earth, with successful comparison to the Colombian government’s deforestation map and a global deforestation map. PMID:25678933

Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System.

PubMed

Pratihast, Arun Kumar; DeVries, Ben; Avitabile, Valerio; de Bruin, Sytze; Herold, Martin; Bergsma, Aldo

2016-01-01

This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications.

Current remote sensing approaches to monitoring forest degradation in support of countries measurement, reporting and verification (MRV) systems for REDD.

PubMed

Mitchell, Anthea L; Rosenqvist, Ake; Mora, Brice

2017-12-01

Forest degradation is a global phenomenon and while being an important indicator and precursor to further forest loss, carbon emissions due to degradation should also be accounted for in national reporting within the frame of UN REDD+. At regional to country scales, methods have been progressively developed to detect and map forest degradation, with these based on multi-resolution optical, synthetic aperture radar (SAR) and/or LiDAR data. However, there is no one single method that can be applied to monitor forest degradation, largely due to the specific nature of the degradation type or process and the timeframe over which it is observed. The review assesses two main approaches to monitoring forest degradation: first, where detection is indicated by a change in canopy cover or proxies, and second, the quantification of loss (or gain) in above ground biomass (AGB). The discussion only considers degradation that has a visible impact on the forest canopy and is thus detectable by remote sensing. The first approach encompasses methods that characterise the type of degradation and track disturbance, detect gaps in, and fragmentation of, the forest canopy, and proxies that provide evidence of forestry activity. Progress in these topics has seen the extension of methods to higher resolution (both spatial and temporal) data to better capture the disturbance signal, distinguish degraded and intact forest, and monitor regrowth. Improvements in the reliability of mapping methods are anticipated by SAR-optical data fusion and use of very high resolution data. The second approach exploits EO sensors with known sensitivity to forest structure and biomass and discusses monitoring efforts using repeat LiDAR and SAR data. There has been progress in the capacity to discriminate forest age and growth stage using data fusion methods and LiDAR height metrics. Interferometric SAR and LiDAR have found new application in linking forest structure change to degradation in tropical forests. Estimates of AGB change have been demonstrated at national level using SAR and LiDAR-assisted approaches. Future improvements are anticipated with the availability of next generation LiDAR sensors. Improved access to relevant satellite data and best available methods are key to operational forest degradation monitoring. Countries will need to prioritise their monitoring efforts depending on the significance of the degradation, balanced against available resources. A better understanding of the drivers and impacts of degradation will help guide monitoring and restoration efforts. Ultimately we want to restore ecosystem service and function in degraded forests before the change is irreversible.

Captive Rearing Program for Salmon River Chinook Salmon, 2002 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Venditti, David; Willard, Catherine; James, Chris

2003-11-01

During 2002, the Idaho Department of Fish and Game continued to develop techniques to rear Chinook salmon Oncorhynchus tshawytscha to sexual maturity in captivity and to monitor their reproductive performance under natural conditions. Eyed-eggs were hydraulically collected from redds in the East Fork Salmon River (EFSR; N = 328) and the West Fork Yankee Fork Salmon River (WFYF; N = 308) to establish brood year 2002 culture cohorts. The eyed-eggs were incubated and reared at the Eagle Fish Hatchery, Eagle, Idaho (Eagle). Juveniles collected in 2000 were PIT and elastomer tagged and vaccinated against vibrio Vibrio spp. and bacterial kidneymore » disease prior to being transferred to the NOAA Fisheries, Manchester Marine Experimental Station, Manchester, Washington (Manchester) for saltwater rearing through maturity. Smolt transfers included 203 individuals from the WFYF and 379 from the EFSR. Maturing fish transfers from Manchester to Eagle included 107 individuals from the LEM, 167 from the WFYF, and 82 from the EFSR. This was the second year maturing adults were held on chilled water at Eagle to test if water temperature manipulations could advance spawn timing. Adults from the LEM and WFYF were divided into chilled ({approx} 9 C) and ambient ({approx} 13.5 C) temperature groups while at Eagle. Forty-seven mature females from the LEM (19 chilled, 16 ambient, and 12 ambient not included in the temperature study) were spawned at Eagle with 42 males in 2002. Water temperature group was not shown to affect the spawn timing of these females, but males did mature earlier. Egg survival to the eyed stage averaged 66.5% and did not differ significantly between the temperature groups. Personnel from the Shoshone-Bannock Tribe placed a total of 47,977 eyed-eggs from these crosses in in-stream incubators. Mature adults (N = 215 including 56 precocial males) were released into the WFYF to evaluate their reproductive performance. After release, fish distributed themselves throughout the study section and displayed a progression of habitat associations and behavior consistent with progressing maturation and the onset of spawning. Twenty-six captive-reared females constructed 33 redds in the WFYF in 2002. Eighteen of these were hydraulically sampled, and eggs were collected from 17. The percentage of live eggs ranged from 0-100% and averaged 34.6%. No live eggs were found in redds spawned by brood year 1997 females. Expanding these results to the remaining redds gives an estimate of 22,900 eyed-eggs being produced by captive-reared fish in the WFYF. Additionally, 130 mature adults (including 41 precocial males) were released into the EFSR. Almost all of these fish moved out of the areas shoreline observers had access to, so no spawning behavior was observed. Radio-telemetry indicated that most of these fish initially moved downstream (although three females moved upstream as far as 7 km) and then held position.« less

An improved clustering algorithm based on reverse learning in intelligent transportation

NASA Astrophysics Data System (ADS)

Qiu, Guoqing; Kou, Qianqian; Niu, Ting

2017-05-01

With the development of artificial intelligence and data mining technology, big data has gradually entered people's field of vision. In the process of dealing with large data, clustering is an important processing method. By introducing the reverse learning method in the clustering process of PAM clustering algorithm, to further improve the limitations of one-time clustering in unsupervised clustering learning, and increase the diversity of clustering clusters, so as to improve the quality of clustering. The algorithm analysis and experimental results show that the algorithm is feasible.

An historically consistent and broadly applicable MRV system based on LiDAR sampling and Landsat time-series

Treesearch

W. Cohen; H. Andersen; S. Healey; G. Moisen; T. Schroeder; C. Woodall; G. Domke; Z. Yang; S. Stehman; R. Kennedy; C. Woodcock; Z. Zhu; J. Vogelmann; D. Steinwand; C. Huang

2014-01-01

The authors are developing a REDD+ MRV system that tests different biomass estimation frameworks and components. Design-based inference from a costly fi eld plot network was compared to sampling with LiDAR strips and a smaller set of plots in combination with Landsat for disturbance monitoring. Biomass estimation uncertainties associated with these different data sets...

Accountability across resources [Salmon and Wilderness: Sharing the responsibility, sharing the benefits

Treesearch

Russell F. Thurow

2015-01-01

On a cool August morning, Chinook salmon (Oncorhynchus tshawytscha) fulfill an ancient ritual in the wilderness. Despite the rigors of an 850-mile journey, the female excavates a redd (nest) by moving stream gravels with her tail while males spar for a place beside her. In an ultimate act of nurturing, these salmon spawn and die, their bodies providing essential...

Forest biodiversity, carbon and other ecosystem services: relationships and impacts of deforestation and forest degradation

Treesearch

Ian D. Thompson; Joice Ferreira; Toby Gardner; Manuel Guariguata; Lian Pin Koh; Kimiko Okabe; Yude Pan; Christine B. Schmitt; Jason Tylianakis; Jos Barlow; Valerie Kapos; Werner A. Kurz; John A. Parrotta; Mark D. Spalding; Nathalie van Vliet

2012-01-01

REDD+ actions should be based on the best science and on the understanding that forests can provide more than a repository for carbon but also offer a wide range of services beneficial to people. Biodiversity underpins many ecosystem services, one of which is carbon sequestration, and individual species’ functional traits play an important role in determining...

Definitions in the context of the United Nations Framework Convention on Climate Change

Treesearch

Sandra Brown

2013-01-01

In relation to REDD+ implementation, two key steps are needed: (1) establishing a reference emission level or reference level (RL) and (2) monitoring performance against the RL. The RL is based on historic emissions and this can serve as a key starting point for designing any system for future monitoring. A monitoring system must be able to monitor the performance of...

Effects of increased discharge on spawning and age-0 recruitment of rainbow trout in the Colorado River at Lees Ferry, Arizona

USGS Publications Warehouse

Avery, Luke A.; Korman, Josh; Persons, William R.

2015-01-01

Negative interactions of Rainbow Trout Oncorhynchus mykiss with endangered Humpback Chub Gila cypha pose challenges to the operation of Glen Canyon Dam (GCD) to manage for both species in the Colorado River. Operations to enhance the Rainbow Trout tailwater fishery may lead to an increase in downstream movement of the trout to areas where they are likely to interact with Humpback Chub. We evaluated the effects of dam operations on age-0 Rainbow Trout in the tailwater fishery to inform managers about how GCD operations could benefit a tailwater fishery for Rainbow Trout; although this could affect a Humpback Chub population farther downstream. A near year-long increase in discharge at GCD in 2011 enabled us to evaluate whether high and stable flows led to increased spawning and production of age-0 Rainbow Trout compared with other years. Rainbow Trout spawning was monitored by fitting a model to observed redd counts to estimate the number of redds created over a spawning season. Data collected during electrofishing trips in July–September and November were used to acquire age-0 trout population and mortality rate estimates. We found that high and stable flows in 2011 resulted in 3,062 redds (1.7 times the mean of all survey years) and a population estimate of 686,000 age-0 Rainbow Trout (second highest on record). Despite high initial abundance, mortality remained low through the year (0.0043%/d) resulting in significant recruitment with a record high November population estimate of 214,000 age-0 Rainbow Trout. Recent monitoring indicates this recruitment event was followed by an increase in downstream migration, which may lead to increased interactions with downstream populations of Humpback Chub. Consequently, while our results indicate that manipulating flow at GCD can be used to manage Rainbow Trout spawning and recruitment, fisheries managers should use flow manipulation in moderation to minimize downstream migration in order to reduce negative interactions with other species in the Colorado River.

[Contribution of tropical upland forests to carbon storage in Colombia].

PubMed

Yepes, Adriana; Herrera, Johana; Phillips, Juan; Galindo, Gustavo; Granados, Edwin; Duque, Alvaro; Barbosa, Adriana; Olarte, Claudia; Cardona, María

2015-03-01

The tropical montane forests in the Colombian Andean region are located above 1500 m, and have been heavily deforested. Despite the general presumption that productivity and hence carbon stocks in these ecosystems are low, studies in this regard are scarce. This study aimed to (i) to estimate Above Ground Biomass (AGB) in forests located in the South of the Colombian Andean region, (ii) to identify the carbon storage potential of tropical montane forests dominated by the black oak Colombobalanus excelsa and to identify the relationship between AGB and altitude, and (iii) to analyze the role of tropical mountain forests in conservation mechanisms such as Payment for Environmental Services (PES) and Reducing Emissions from Deforestation and Degradation (REDD+). Twenty six 0.25 ha plots were randomly distributed in the forests and all trees with D > or =10 cm were measured. The results provided important elements for understanding the role of tropical montane forests as carbon sinks. The information produced can be used in subnational initiatives, which seek to mitigate or reduce the effects of deforestation through management or conservation of these ecosystems, like REDD+ or PES. The AGB and carbon stocks results obtained were similar to those reported for lowland tropical forests. These could be explained by the dominance and abundance of C. excelsa, which accounted for over 81% of AGB/carbon. The error associated with the estimates of AGB/carbon was 10.58%. We found a negative and significant relationship between AGB and altitude, but the higher AGB values were in middle altitudes (approximatly = 700-1800 m), where the environmental conditions could be favorable to their growth. The carbon storage potential of these forests was higher. However, if the historical rate of the deforestation in the study area continues, the gross emissions of CO2e to the atmosphere could turn these forests in to an important emissions source. Nowadays, it is clear that tropical montane forests are vulnerable to deforestation, especially black Oak forests due to their commercial value. Given their high carbon storage potential, the presence of endemic species and the strategic functions of these ecosystems, we recommend that they should be considered relevant during REDD+, PES or any other conservation assessment.

Upstream Passage, Spawning, and Stock Identification of Fall Chinook in the Snake River, 1992 and 1993 : Final Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blankenship, H. Lee; Mendel, Glen W.

This final report of the 3-year study summarizes activities and results for 1993. Study objectives were to: (1) determine the source of losses (or accounting errors) for adult chinook salmon between Ice Harbor Dam (IHR) and Lower Granite Dam (LGR), and upstream of LGR in the Snake River; (2) identify spawning locations upstream of LGR for calibration of aerial redd surveys, redd habitat mapping, carcass recovery for genetic stock profile analysis, and correction of estimated adult/redd ratios; and (3) estimate passage and migration times at Snake River. 200 fall chinook salmon were radio tagged and tracked with aerial, fixed-site, andmore » ground mobile tracking. Fish were released upstream of IHR at Charbonneau Park (CHAR). 190 of the fish were tracked or relocated away from CHAR. 59 fish descended to below IHR without crossing Lower Monumental Dam (LMO). Another 128 salmon passed upstream of LMO without falling back at IHR. Only 80 salmon passed Little Goose Dam (LGO) without falling back at a downstream dam; 66 of these fish passed LGR. Many fish that fell back reascended the dams. A total of 72 salmon released at CHAR passed upstream of LGR, including fish that had fallen back and reascended a dam. Over 80 percent of the salmon that entered Lyons Ferry Hatchery each year had reached LGO before descending to the hatchery. Extensive wandering was documented between LMO and upstream of LGR before salmon entered Lyons Ferry Hatchery or the Tucannon River. In 1993, 41 salmon were found to be of hatchery origin when recovered. These fish entered Lyons Ferry Hatchery with similar movements to unmarked salmon. Each year a few salmon have remained near the hatchery without entering, which suggests the hatchery may have inadequate attraction flows. Fall chinook passed lower Snake River dams in 2-5 days each on average. Median travel times through LMO and LGO were 1.0-1.3 days each, which was slower than for spring chinook or steelhead in 1993. 5 refs., 21 figs., 20 tabs.« less

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

PubMed

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-09-25

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

PubMed Central

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-01-01

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

EMERGE: Engineered Materials that Create Environments for ReGeneration via Electric Field

DTIC Science & Technology

2016-10-01

Recruitment of multiple cell lines by collagen-synthetic copolymer matrices in corneal regeneration ,” Biomaterials (2004). A) B) REDD-2016-537...AWARD NUMBER: W81XWH-14-1-0542 TITLE: EMERGE: Engineered Materials that Create Environments for ReGeneration via Electric Field PRINCIPAL...23 Sep 2016 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER EMERGE: Engineered Materials that Create Environments for ReGeneration via Electric Field

Central African detail experience: what US FIA field staff can teach and learn through short term assignments—Democratic Republic of Congo and Cameroon

Treesearch

Josh Feinberg

2015-01-01

REDD+, Reduction of Emissions from Deforestation and Forest Degradation is a United Nations initiative targeted to combat atmospheric carbon dioxide and global warming by providing monetary incentives to developing countries to preserve their forested land as effective carbon sinks. In order for these countries to receive this monetary benefit, they must develop and...

Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System

PubMed Central

Pratihast, Arun Kumar; DeVries, Ben; Avitabile, Valerio; de Bruin, Sytze; Herold, Martin; Bergsma, Aldo

2016-01-01

This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications. PMID:27031694

Detailed maps of tropical forest types are within reach: forest tree communities for Trinidad and Tobago mapped with multiseason Landsat and multiseason fine-resolution imagery

Treesearch

Eileen H. Helmer; Thomas S. Ruzycki; Jay Benner; Shannon M. Voggesser; Barbara P. Scobie; Courtenay Park; David W. Fanning; Seepersad Ramnarine

2012-01-01

Tropical forest managers need detailed maps of forest types for REDD+, but spectral similarity among forest types; cloud and scan-line gaps; and scarce vegetation ground plots make producing such maps with satellite imagery difficult. How can managers map tropical forest tree communities with satellite imagery given these challenges? Here we describe a case study of...

Quantification of forest carbon degradation in Nicaragua using RapidEye remote sensing data: El Cuá and Wiwili case studies

NASA Astrophysics Data System (ADS)

Argoty, F. N.; Cifuentes, M.; Imbach, P. A.; Vilchez, S.; Casanoves, F.; Ibrahim, M.; Vierling, L. A.

2012-12-01

Forest degradation and deforestation affect ecosystem function and climate regulation services such as carbon storage. Historically, Central America has been a deforestation and forest degradation hotspot. Wiwili and El Cuá municipalities in northern Nicaragua are no exception, where subsistence agriculture and cattle ranch expansion have driven deforestation and other wood extraction activities, leading to various levels of forest degradation. Reduction of Emissions from forest Degradation and Deforestation (REDD) projects are proposed as a tool to slow the degradation and loss of carbon stocks by restoring carbon to its natural levels in order to mitigate carbon dioxide emissions that cause global warming. REDD projects require baseline estimations of current carbon stocks and forest degradation status. We estimated carbon stocks across a forest degradation gradient based on common biophysical variables and commercially available (RapidEye) remote sensing data. We measured 80 temporary forest plots (50x20m) for aboveground biomass to sample a gradient of forest degradation at two municipalities (El Cuá and Wiwili) in northern Nicaragua. We measured biomass in trees (≥10 cm DBH), saplings (5-9.9 cm DBH), other growth forms (ferns, palms and woody vines), and large detritus (snags and downed wood). Biomass was estimated by a range of allometric models and a constant conversion factor (0.47) was applied to calculate aboveground carbon stocks. Remote sensing data from a RapidEye scene for 02/2010 provided data for 5 spectral bands and 19 vegetation indexes at 6 m spatial resolution. Precipitation, temperature, altitude, slope, canopy cover, and aspect were also used as input variables for carbon modeling. We tested linear mixed models, generalized additive mixed models and regression tree approaches to explain carbon stocks based on vegetation indexes and biophysical variables. Additionally, we grouped plots into low (17-168 Mg C ha-1), medium (168-302 Mg C ha-1) and high (302-418 Mg C ha-1) carbon stocks (with conglomerate analysis) to test for a categorical classification approach based on discriminant analysis. Results show a gradient of total aboveground carbon between 17.78 - 379.2 Mg C ha-1. Models predicting carbon stock had an R2 that ranged between 0.32-0.52 (p<0.0001) across the three methods evaluated. Linear mixed models using the MCARI-MTVI2 vegetation index, based on the red-edge band (690-730 nm), showed the best performance. Categorical classification showed improved performance, with a 17% mean classification error, using 20 predictors (MCARI-MTVI2 was the most important). Our results show the importance of the red-edge band and the potential of multi-spectral high-resolution imagery to quantify tropical forest degradation. Although model performance for prediction of continuous biomass values is somewhat constrained, there is potential for coarser applications in the context of developing REDD baselines and monitoring using categorical mapping of forest degradation (with a trade-off in inference power) by means of relatively low-cost remote sensing and ancillary data.

Geographic overlaps between priority areas for forest carbon-storage efforts and those for delivering peacebuilding programs: implications for policy design

NASA Astrophysics Data System (ADS)

Castro-Nunez, Augusto; Mertz, Ole; Sosa, Chrystian C.

2017-05-01

Of the countries considering national-level policies for incentivizing reductions in forest-based greenhouse gas emissions (REDD+), some 25 are experiencing (or are emerging from) armed-conflicts. It has been hypothesized that the outcomes of the interactions between carbon-storage and peacebuilding efforts could result in either improved or worsened forest conservation and likewise increased or decreased conflict. Hence, for this study we explore potential interactions between forest carbon-storage and peacebuilding efforts, with Colombia as a case study. Spatial associations between biomass carbon and three conflict-related variables suggest that such interactions may exist. Nonetheless, while priority areas for carbon-focused conservation are presumably those at highest risks of deforestation, our research indicates that forests with lower risk of deforestation are typically those affected by armed-conflict. Our findings moreover highlight three possible roles played by Colombian forested municipalities in armed groups’ military strategies: venues for battle, hideouts, and sources of natural resources to finance war.

How to Address a Global Problem with Earth Observations? Developing Best Practices to Monitor Forests Around the World

NASA Technical Reports Server (NTRS)

Flores Cordova, Africa I.; Cherrington, Emil A.; Vadrevu, Krishna; Thapa, Rajesh Bahadur; Odour, Phoebe; Mehmood, Hamid; Quyen, Nguyen Hanh; Saah, David; Yero, Kadidia; Mamane, Bako;

Using Remote Sensing and Synthetic Controls to Understand Deforestation Drivers and their Moderation by Forest Use in Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Gray, J. M.; Sills, E. O.; Amanatides, M. M.

2017-12-01

Tropical forests offer valuable ecosystem services at multiple scales, from the local hydrological cycle to the global carbon cycle. This has motivated significant international attention and funding for efforts to reduce emissions from deforestation and forest degradation (REDD+), especially where they account for most greenhouse gas emissions, as in Indonesia. Indonesia holds 39% of Southeast Asian forest, experiences the second highest rate of deforestation after Brazil, and has the potential to earn high profits both from logging native forests and from clearing forests for oil palm and pulp plantations. In Indonesia, REDD+ initiatives have taken a wide variety of forms, with some interventions focused on encouraging sustainable forest management and others focused on reducing demand for cleared land. Evaluating the efficacy of these interventions is critical but challenging because exogenous factors may affect both placement of the interventions and deforestation trends. Overcoming this limitation requires an in-depth understanding of the drivers of deforestation and how they vary with context. One barrier to improved understanding has been that existing deforestation datasets are largely binary (e.g. forested/deforested). Recent developments in mapping land-use change from time series of remotely sensed images may offer a path towards obtaining longer times series with more detail on land use. Such data would enable use of the synthetic control method (SCM), which allows for heterogenous impacts across units and over time. Here, we use this approach to answer the question: How has the designation and active use of logging concessions affected deforestation rates in East Kalimantan province, Indonesia since 2000? That is, we ask whether, where, and how using forests for timber production affects the probability of deforestation. We used an image time-series approach (YATSM/CCDC) to classify Landsat imagery from 2000 to 2017 for East Kalimantan, and SCM to evaluate the effect of allocating forest to logging concessions, controlling for a large variety of covariates such as proximity to pulp and palm oil mills and topography to construct our synthetic controls. By mapping land use in previously forested areas, we are able to interrogate the primary drivers of deforestation in different contexts.

Improvements in Ionized Cluster-Beam Deposition

NASA Technical Reports Server (NTRS)

Fitzgerald, D. J.; Compton, L. E.; Pawlik, E. V.

1986-01-01

Lower temperatures result in higher purity and fewer equipment problems. In cluster-beam deposition, clusters of atoms formed by adiabatic expansion nozzle and with proper nozzle design, expanding vapor cools sufficiently to become supersaturated and form clusters of material deposited. Clusters are ionized and accelerated in electric field and then impacted on substrate where films form. Improved cluster-beam technique useful for deposition of refractory metals.

Measuring Environmental and Socio-economic Impact of Deforestation at Kalimantan Island

NASA Astrophysics Data System (ADS)

Nahib, Irmadi; Trenggana, Soma; Turmudi; Suryanta, Jaka; Lestari Munajati, Sri; Windiastuti, Rizka

2018-05-01

Indonesia’s forests in the period of 2000-2009 has been deforested by about 15.158 million ha out of 103.309 milion ha. Deforestation caused carbon emissions. One method for measuring emissions from deforestation and forest degradation is GeOSIRIS model. A modeled GeOSIRIS policy used a carbon payment system to incentivize emission reductions. Data used in this study were maps of forest cover in 2005 and 2010, map of deforestation 2005-2010, carbon and agricultural price and driver variables for deforestation such as slope, elevation, logarithmic distance to the nearest road or provincial capital, or the amount of area per pixel included in a national park, or a timber plantation. The result of this study showed rate of deforestation was 1.417 million ha/5 years (observed). The REDD policy could decrease deforestation in Kalimantan Island by 0.170 million ha (16.70%), with assumption that international carbon price of US 10/tCO2e. The change of emissions due to REDD was 22.29%, or reduced emissions by 245.03 million tCO2e/5 years. Finally, Gross National Revenue from carbon payments (NPV 5 years) was US 2,450.34 billion, where incentivize emission reductions to sub-national entities (NPV, 5 years) was US 2,150.07 million and net central government surplus from carbon payments was US 300.26 million (NPV, 5 years).

Reducing uncertainty for estimating forest carbon stocks and dynamics using integrated remote sensing, forest inventory and process-based modeling

NASA Astrophysics Data System (ADS)

Poulter, B.; Ciais, P.; Joetzjer, E.; Maignan, F.; Luyssaert, S.; Barichivich, J.

2015-12-01

Accurately estimating forest biomass and forest carbon dynamics requires new integrated remote sensing, forest inventory, and carbon cycle modeling approaches. Presently, there is an increasing and urgent need to reduce forest biomass uncertainty in order to meet the requirements of carbon mitigation treaties, such as Reducing Emissions from Deforestation and forest Degradation (REDD+). Here we describe a new parameterization and assimilation methodology used to estimate tropical forest biomass using the ORCHIDEE-CAN dynamic global vegetation model. ORCHIDEE-CAN simulates carbon uptake and allocation to individual trees using a mechanistic representation of photosynthesis, respiration and other first-order processes. The model is first parameterized using forest inventory data to constrain background mortality rates, i.e., self-thinning, and productivity. Satellite remote sensing data for forest structure, i.e., canopy height, is used to constrain simulated forest stand conditions using a look-up table approach to match canopy height distributions. The resulting forest biomass estimates are provided for spatial grids that match REDD+ project boundaries and aim to provide carbon estimates for the criteria described in the IPCC Good Practice Guidelines Tier 3 category. With the increasing availability of forest structure variables derived from high-resolution LIDAR, RADAR, and optical imagery, new methodologies and applications with process-based carbon cycle models are becoming more readily available to inform land management.

Post-crackdown effectiveness of field-based forest law enforcement in the Brazilian Amazon.

PubMed

Börner, Jan; Kis-Katos, Krisztina; Hargrave, Jorge; König, Konstantin

2015-01-01

Regulatory enforcement of forest conservation laws is often dismissed as an ineffective approach to reducing tropical forest loss. Yet, effective enforcement is often a precondition for alternative conservation measures, such as payments for environmental services, to achieve desired outcomes. Fair and efficient policies to reducing emissions from deforestation and forest degradation (REDD) will thus crucially depend on understanding the determinants and requirements of enforcement effectiveness. Among potential REDD candidate countries, Brazil is considered to possess the most advanced deforestation monitoring and enforcement infrastructure. This study explores a unique dataset of over 15 thousand point coordinates of enforcement missions in the Brazilian Amazon during 2009 and 2010, after major reductions of deforestation in the region. We study whether local deforestation patterns have been affected by field-based enforcement and to what extent these effects vary across administrative boundaries. Spatial matching and regression techniques are applied at different spatial resolutions. We find that field-based enforcement operations have not been universally effective in deterring deforestation during our observation period. Inspections have been most effective in reducing large-scale deforestation in the states of Mato Grosso and Pará, where average conservation effects were 4.0 and 9.9 hectares per inspection, respectively. Despite regional and actor-specific heterogeneity in inspection effectiveness, field-based law enforcement is highly cost-effective on average and might be enhanced by closer collaboration between national and state-level authorities.

Post-Crackdown Effectiveness of Field-Based Forest Law Enforcement in the Brazilian Amazon

PubMed Central

Börner, Jan; Kis-Katos, Krisztina; Hargrave, Jorge; König, Konstantin

2015-01-01

Regulatory enforcement of forest conservation laws is often dismissed as an ineffective approach to reducing tropical forest loss. Yet, effective enforcement is often a precondition for alternative conservation measures, such as payments for environmental services, to achieve desired outcomes. Fair and efficient policies to reducing emissions from deforestation and forest degradation (REDD) will thus crucially depend on understanding the determinants and requirements of enforcement effectiveness. Among potential REDD candidate countries, Brazil is considered to possess the most advanced deforestation monitoring and enforcement infrastructure. This study explores a unique dataset of over 15 thousand point coordinates of enforcement missions in the Brazilian Amazon during 2009 and 2010, after major reductions of deforestation in the region. We study whether local deforestation patterns have been affected by field-based enforcement and to what extent these effects vary across administrative boundaries. Spatial matching and regression techniques are applied at different spatial resolutions. We find that field-based enforcement operations have not been universally effective in deterring deforestation during our observation period. Inspections have been most effective in reducing large-scale deforestation in the states of Mato Grosso and Pará, where average conservation effects were 4.0 and 9.9 hectares per inspection, respectively. Despite regional and actor-specific heterogeneity in inspection effectiveness, field-based law enforcement is highly cost-effective on average and might be enhanced by closer collaboration between national and state-level authorities. PMID:25875656

Assessment of capacity-building activities for forest measurement, reporting, and verification, 2011–15

USGS Publications Warehouse

Peneva-Reed, Elitsa I.; Romijn, J. Erika

2018-05-31

This report was written as a collaborative effort between the U.S. Geological Survey, SilvaCarbon, and Wageningen University with funding provided by the U.S. Agency for International Development and the European Space Agency, respectively, to address a pressing need for enhanced result-based monitoring and evaluation of delivered capacity-building activities. For this report, the capacity-building activities delivered by capacity-building providers (referred to as “providers” hereafter) during 2011–15 (the study period) to support countries in building measurement, reporting, and verification (MRV) systems for reducing emissions from deforestation and forest degradation (REDD+) were assessed and evaluated.Summarizing capacity-building activities and outcomes across multiple providers was challenging. Many of the providers did not have information readily available, which precluded them from participating in this study despite the usefulness of their information. This issue led to a key proposed future action: Capacity-building providers could establish a central repository within the Global Forestry Observation Initiative (GFOI; http://www.gfoi.org/) where data from past, current, and future activities of all capacity-building providers could be stored. The repository could be maintained in a manner to continually learn from previous lessons.Although various providers monitored and evaluated the success of their capacity-building activities, such evaluations only assessed the success of immediate outcomes and not the overarching outcomes and impacts of activities implemented by multiple providers. Good monitoring and evaluation should continuously monitor and periodically evaluate all factors affecting the outcomes of a provided capacity-building activity.The absence of a methodology to produce quantitative evidence of a causal link between multiple capacity-building activities delivered and successful outcomes left only a plausible association. A previous publication argued that plausible association, although not a precise measurement of cause and effect, was a realistic tool. Our review of the available literature on this subject did not find another similar assessment to assess capacity-building activities for supporting the countries in building MRV system for REDD+.Four countries from the main forested regions of Africa, the Americas, and Asia were chosen as subjects for this report based on the length of time SilvaCarbon and other providers have provided capacity-building activities toward MRV system for REDD+: Colombia (the Americas), the Democratic Republic of the Congo (DRC; Africa), Peru (the Americas), and the Republic of the Philippines (referred to as “the Philippines” hereafter; Asia).Several providers were contacted for information to include in this report, but, because of various constraints, only SilvaCarbon, the Food and Agriculture Organization of the United Nations (FAO), and the World Wildlife Fund (WWF) participated in this study. These three providers supported various targeted capacity-building activities through-out Africa, the Americas, and Asia, including the following: technical workshops at national and regional levels (referred to as “workshops” hereafter), hands on training, study tours, technical details by experts, technical consultation between providers and recipients, sponsorship for travel, organizing network meetings, developing sampling protocols, assessing deforestation and degradation drivers, estimating carbon stock and flow, designing monitoring systems for multiple uses, promoting public-private partnerships to scale up investments on MRV system for REDD+, and assisting with the design of national forest monitoring systems.Their activities were planned in coordination with key partners in each country and region and with the support and assistance of other providers. Note that several other organizations and institutions assisted the providers to deliver capacity-building activities, including Boston University, Conservation International, Stanford University, University of Maryland, and Wageningen University & Research.

An effective fuzzy kernel clustering analysis approach for gene expression data.

PubMed

Sun, Lin; Xu, Jiucheng; Yin, Jiaojiao

2015-01-01

Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First of all, to optimize characteristic differences and estimate optimal cluster number, Gaussian kernel function is introduced to improve spectrum analysis method (SAM). By combining subtractive clustering with max-min distance mean, maximum distance method (MDM) is proposed to determine cluster centers. Then, the corresponding steps of improved SAM (ISAM) and MDM are given respectively, whose superiority and stability are illustrated through performing experimental comparisons on gene expression data. Finally, by introducing ISAM and MDM into FKCA, an effective improved FKCA algorithm is proposed. Experimental results from public gene expression data and UCI database show that the proposed algorithms are feasible for cluster analysis, and the clustering accuracy is higher than the other related clustering algorithms.

An improved method to detect correct protein folds using partial clustering.

PubMed

Zhou, Jianjun; Wishart, David S

2013-01-16

Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient "partial" clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods. We propose a new scheme that performs rapid but incomplete clustering on protein decoys. Our method detects structurally similar decoys (measured using either C(α) RMSD or GDT-TS score) and extracts representatives from them without assigning every decoy to a cluster. We integrated our new clustering strategy with several different scoring functions to assess both the performance and speed in identifying correct or near-correct folds. Experimental results on 35 Rosetta decoy sets and 40 I-TASSER decoy sets show that our method can improve the correct fold detection rate as assessed by two different quality criteria. This improvement is significantly better than two recently published clustering methods, Durandal and Calibur-lite. Speed and efficiency testing shows that our method can handle much larger decoy sets and is up to 22 times faster than Durandal and Calibur-lite. The new method, named HS-Forest, avoids the computationally expensive task of clustering every decoy, yet still allows superior correct-fold selection. Its improved speed, efficiency and decoy-selection performance should enable structure prediction researchers to work with larger decoy sets and significantly improve their ab initio structure prediction performance.

An improved method to detect correct protein folds using partial clustering

PubMed Central

2013-01-01

Background Structure-based clustering is commonly used to identify correct protein folds among candidate folds (also called decoys) generated by protein structure prediction programs. However, traditional clustering methods exhibit a poor runtime performance on large decoy sets. We hypothesized that a more efficient “partial“ clustering approach in combination with an improved scoring scheme could significantly improve both the speed and performance of existing candidate selection methods. Results We propose a new scheme that performs rapid but incomplete clustering on protein decoys. Our method detects structurally similar decoys (measured using either Cα RMSD or GDT-TS score) and extracts representatives from them without assigning every decoy to a cluster. We integrated our new clustering strategy with several different scoring functions to assess both the performance and speed in identifying correct or near-correct folds. Experimental results on 35 Rosetta decoy sets and 40 I-TASSER decoy sets show that our method can improve the correct fold detection rate as assessed by two different quality criteria. This improvement is significantly better than two recently published clustering methods, Durandal and Calibur-lite. Speed and efficiency testing shows that our method can handle much larger decoy sets and is up to 22 times faster than Durandal and Calibur-lite. Conclusions The new method, named HS-Forest, avoids the computationally expensive task of clustering every decoy, yet still allows superior correct-fold selection. Its improved speed, efficiency and decoy-selection performance should enable structure prediction researchers to work with larger decoy sets and significantly improve their ab initio structure prediction performance. PMID:23323835

Identification and Localization of Genes Which Restore Senescence in Breast Cancer Cells.

DTIC Science & Technology

1999-08-01

transformation await cloning and sequencing of this gene. Deepthi E. Redd) DAMD17-96-1-60. REFERENCES 1. Hayflick , L. (1965). The limited in vitro life time... LIMITATION OF ABSTRACT Unlimited Standard Fprm 298 (Rev. 2-89) Praacribad by ANSI Std. Z39-18 298-102 U5APPC vi.OO t FOREWORD Opinions...is quoted, permission has been obtained to use such material. ft/1A Where material from documents designated for limited distribution is quoted

EMERGE: Engineered Materials that Create Environments for ReGeneration via Electric Field

DTIC Science & Technology

2015-10-01

lactic  co-­‐glycolic   acid )  (PLGA)   Injury   Aminophylline  REDD-­‐2015-­‐424   6   3. Accomplishments...laboratories.  Previously,  we  used  specific   pharmacological  activators  (aminophylline,  ascorbic   acid *)  or...electric   signal  and  wound  healing  (shallow  epithelial  wounds).  Aminophylline  and  ascorbic   acid  (10  mM)

A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method.

PubMed

Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol

2007-11-27

A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries.

A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method

PubMed Central

Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol

2007-01-01

Background A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Results Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Conclusion Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries. PMID:18047705

A roadmap of clustering algorithms: finding a match for a biomedical application.

PubMed

Andreopoulos, Bill; An, Aijun; Wang, Xiaogang; Schroeder, Michael

2009-05-01

Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means partitioning being the most popular methods. Numerous improvements of these two clustering methods have been introduced, as well as completely different approaches such as grid-based, density-based and model-based clustering. For improved bioinformatics analysis of data, it is important to match clusterings to the requirements of a biomedical application. In this article, we present a set of desirable clustering features that are used as evaluation criteria for clustering algorithms. We review 40 different clustering algorithms of all approaches and datatypes. We compare algorithms on the basis of desirable clustering features, and outline algorithms' benefits and drawbacks as a basis for matching them to biomedical applications.

Partially oxidized iridium clusters within dendrimers: size-controlled synthesis and selective hydrogenation of 2-nitrobenzaldehyde

NASA Astrophysics Data System (ADS)

Higaki, Tatsuya; Kitazawa, Hirokazu; Yamazoe, Seiji; Tsukuda, Tatsuya

2016-06-01

Iridium clusters nominally composed of 15, 30 or 60 atoms were size-selectively synthesized within OH-terminated poly(amidoamine) dendrimers of generation 6. Spectroscopic characterization revealed that the Ir clusters were partially oxidized. All the Ir clusters efficiently converted 2-nitrobenzaldehyde to anthranil and 2-aminobenzaldehyde under atmospheric hydrogen at room temperature in toluene via selective hydrogenation of the NO2 group. The selectivity toward 2-aminobenzaldehyde over anthranil was improved with the reduction of the cluster size. The improved selectivity is ascribed to more efficient reduction than intramolecular heterocyclization of a hydroxylamine intermediate on smaller clusters that have a higher Ir(0)-phase population on the surface.Iridium clusters nominally composed of 15, 30 or 60 atoms were size-selectively synthesized within OH-terminated poly(amidoamine) dendrimers of generation 6. Spectroscopic characterization revealed that the Ir clusters were partially oxidized. All the Ir clusters efficiently converted 2-nitrobenzaldehyde to anthranil and 2-aminobenzaldehyde under atmospheric hydrogen at room temperature in toluene via selective hydrogenation of the NO2 group. The selectivity toward 2-aminobenzaldehyde over anthranil was improved with the reduction of the cluster size. The improved selectivity is ascribed to more efficient reduction than intramolecular heterocyclization of a hydroxylamine intermediate on smaller clusters that have a higher Ir(0)-phase population on the surface. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr01460g

Fire patterns in the Amazonian biome

NASA Astrophysics Data System (ADS)

Aragao, Luiz E. O. C.; Shimabukuro, Yosio E.; Lima, Andre; Anderson, Liana O.; Barbier, Nicolas; Saatchi, Sassan

2010-05-01

This paper aims to provide an overview of our recent findings on the interplay between climate and land use dynamics in defining fire patterns in Amazonia. Understanding these relationships is currently a fundamental concern for assessing the vulnerability of Amazonia to climate change and its potential for mitigating current increases in atmospheric greenhouse gases. Reducing carbon emissions from tropical deforestation and forest degradation (REDD), for instance, could contribute to a cumulative emission reduction of 13-50 billion tons of carbon (GtC) by 2100. In Amazonia, though, forest fires can release similar quantities of carbon to the atmosphere (~0.2 GtC yr-1) as deforestation alone. Therefore, to achieve carbon savings through REDD mechanism there is an urgent need of understanding and subsequently restraining related Amazonian fire drivers. In this study, we analyze satellite-derived monthly and annual time-series of fires, rainfall and deforestation in Amazonia to: (1) quantify the seasonal patterns and relationships between these variables; (2) quantify fire and rainfall anomalies to evaluate the impact of recent drought on fire patterns; (3) quantify recent trends in fire and deforestation to understand how land use affects fire patterns in Amazonia. Our results demonstrate a marked seasonality of fires. The majority of fires occurs along the Arc of Deforestation, the expanding agricultural frontier in southern and eastern Amazonia, indicating humans are the major ignition sources determining fire seasonality, spatial distribution and long-term patterns. There is a marked seasonality of fires, which is highly correlated (p<0.05) with monthly rainfall and deforestation rates. Deforestation and fires reach their highest values three and six months, respectively, after the peak of the rainy season. This result clearly describes the impact of major human activities on fire incidence, which is generally characterized by the slash-and-burn of Amazonian vegetation for implementation of pastures and agricultural fields. The cumulative number of hot pixels is exponentially related to the monthly rainfall, which ultimately defines where and when fire can potentially strike. During the 2005 Amazonian drought, the number of hot pixels increased 33% in relation to mean 1998-2005. However, even with a large fraction of the basin experiencing considerable water deficits, fires have only affect areas with extensive human activity. Our spatially explicit trend analysis on deforestation and fire data revealed that more than half of the area experiencing increased fire occurrence have reduced deforestation rates. This reverse pattern is likely to be associated with the slash-and-burn of secondary forests and the increase of fragmentation and forest edges, favouring the leakage of fires from deforested lands into forests. Finally, our analysis points towards a reduction of fire incidence due to land use intensification in this region. In this study, we demonstrated that anthropogenic forcing, such as deforestation rates, is decisive in determining the seasonality and annual patterns of fire occurrence. Moreover, droughts can significantly increase the number of fires in the region exacerbating human impacts in Amazonia. Due to ongoing deforestation and the predicted intensification of climate change induced droughts, it is anticipated that a large area of forest edge will be under increased risk of fires and carbon savings from REDD may be partially offset by increased emissions following fire events. Improved fire-free land management practices may provide a sustainable solution for reducing emissions from the world's largest rainforest. Acknowledges The first author would like to thank the financial support of the Natural Environment Research Council (NERC-UK/grant NE/F015356/1).

DUE GlobBiomass - Estimates of Biomass on a Global Scale

NASA Astrophysics Data System (ADS)

Eberle, J.; Schmullius, C.

2017-12-01

For the last three years, a new ESA Data User Element (DUE) project had focussed on creating improved knowledge about the Essential Climate Variable Biomass. The main purpose of the DUE GlobBiomass project is to better characterize and to reduce uncertainties of AGB estimates by developing an innovative synergistic mapping approach in five regional sites (Sweden, Poland, Mexico, Kalimantan, South Africa) for the epochs 2005, 2010 and 2015 and for one global map for the year 2010. The project team includes leading Earth Observation experts of Europe and is linked through Partnership Agreements with further national bodies from Brazil, Canada, China, Russia and South Africa. GlobBiomass has demonstrated how EO observation data can be integrated with in situ measurements and ecological understanding to provide improved biomass estimates that can be effectively exploited by users. The target users had mainly be drawn from the climate and carbon cycle modelling communities and included users concerned with carbon emissions and uptake due to biomass changes within initiatives such as REDD+. GlobBiomass provided a harmonised structure that can be exploited to address user needs for biomass information, but will be capable of being progressively refined as new data and methods become available. This presentation will give an overview of the technical prerequisites and final results of the GlobBiomass project.

Nonintrusive Load Monitoring Based on Advanced Deep Learning and Novel Signature.

PubMed

Kim, Jihyun; Le, Thi-Thu-Huong; Kim, Howon

2017-01-01

Monitoring electricity consumption in the home is an important way to help reduce energy usage. Nonintrusive Load Monitoring (NILM) is existing technique which helps us monitor electricity consumption effectively and costly. NILM is a promising approach to obtain estimates of the electrical power consumption of individual appliances from aggregate measurements of voltage and/or current in the distribution system. Among the previous studies, Hidden Markov Model (HMM) based models have been studied very much. However, increasing appliances, multistate of appliances, and similar power consumption of appliances are three big issues in NILM recently. In this paper, we address these problems through providing our contributions as follows. First, we proposed state-of-the-art energy disaggregation based on Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) model and additional advanced deep learning. Second, we proposed a novel signature to improve classification performance of the proposed model in multistate appliance case. We applied the proposed model on two datasets such as UK-DALE and REDD. Via our experimental results, we have confirmed that our model outperforms the advanced model. Thus, we show that our combination between advanced deep learning and novel signature can be a robust solution to overcome NILM's issues and improve the performance of load identification.

The carbon footprint of traditional woodfuels

NASA Astrophysics Data System (ADS)

Bailis, Robert; Drigo, Rudi; Ghilardi, Adrian; Masera, Omar

2015-03-01

Over half of all wood harvested worldwide is used as fuel, supplying ~9% of global primary energy. By depleting stocks of woody biomass, unsustainable harvesting can contribute to forest degradation, deforestation and climate change. However, past efforts to quantify woodfuel sustainability failed to provide credible results. We present a spatially explicit assessment of pan-tropical woodfuel supply and demand, calculate the degree to which woodfuel demand exceeds regrowth, and estimate woodfuel-related greenhouse-gas emissions for the year 2009. We estimate 27-34% of woodfuel harvested was unsustainable, with large geographic variations. Our estimates are lower than estimates from carbon offset projects, which are probably overstating the climate benefits of improved stoves. Approximately 275 million people live in woodfuel depletion `hotspots’--concentrated in South Asia and East Africa--where most demand is unsustainable. Emissions from woodfuels are 1.0-1.2 Gt CO2e yr-1 (1.9-2.3% of global emissions). Successful deployment and utilization of 100 million improved stoves could reduce this by 11-17%. At US$11 per tCO2e, these reductions would be worth over US$1 billion yr-1 in avoided greenhouse-gas emissions if black carbon were integrated into carbon markets. By identifying potential areas of woodfuel-driven degradation or deforestation, we inform the ongoing discussion about REDD-based approaches to climate change mitigation.

Nonintrusive Load Monitoring Based on Advanced Deep Learning and Novel Signature

PubMed Central

Le, Thi-Thu-Huong; Kim, Howon

2017-01-01

Monitoring electricity consumption in the home is an important way to help reduce energy usage. Nonintrusive Load Monitoring (NILM) is existing technique which helps us monitor electricity consumption effectively and costly. NILM is a promising approach to obtain estimates of the electrical power consumption of individual appliances from aggregate measurements of voltage and/or current in the distribution system. Among the previous studies, Hidden Markov Model (HMM) based models have been studied very much. However, increasing appliances, multistate of appliances, and similar power consumption of appliances are three big issues in NILM recently. In this paper, we address these problems through providing our contributions as follows. First, we proposed state-of-the-art energy disaggregation based on Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) model and additional advanced deep learning. Second, we proposed a novel signature to improve classification performance of the proposed model in multistate appliance case. We applied the proposed model on two datasets such as UK-DALE and REDD. Via our experimental results, we have confirmed that our model outperforms the advanced model. Thus, we show that our combination between advanced deep learning and novel signature can be a robust solution to overcome NILM's issues and improve the performance of load identification. PMID:29118809

Improved optical mass tracer for galaxy clusters calibrated using weak lensing measurements

NASA Astrophysics Data System (ADS)

Reyes, R.; Mandelbaum, R.; Hirata, C.; Bahcall, N.; Seljak, U.

2008-11-01

We develop an improved mass tracer for clusters of galaxies from optically observed parameters, and calibrate the mass relation using weak gravitational lensing measurements. We employ a sample of ~13000 optically selected clusters from the Sloan Digital Sky Survey (SDSS) maxBCG catalogue, with photometric redshifts in the range 0.1-0.3. The optical tracers we consider are cluster richness, cluster luminosity, luminosity of the brightest cluster galaxy (BCG) and combinations of these parameters. We measure the weak lensing signal around stacked clusters as a function of the various tracers, and use it to determine the tracer with the least amount of scatter. We further use the weak lensing data to calibrate the mass normalization. We find that the best mass estimator for massive clusters is a combination of cluster richness, N200, and the luminosity of the BCG, LBCG: , where is the observed mean BCG luminosity at a given richness. This improved mass tracer will enable the use of galaxy clusters as a more powerful tool for constraining cosmological parameters.

Benchmark map of forest carbon stocks in tropical regions across three continents.

PubMed

Saatchi, Sassan S; Harris, Nancy L; Brown, Sandra; Lefsky, Michael; Mitchard, Edward T A; Salas, William; Zutta, Brian R; Buermann, Wolfgang; Lewis, Simon L; Hagen, Stephen; Petrova, Silvia; White, Lee; Silman, Miles; Morel, Alexandra

2011-06-14

Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a "benchmark" map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ± 6% to ± 53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ± 5% and ca. ± 1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete.

Predicting pan-tropical climate change induced forest stock gains and losses—implications for REDD

NASA Astrophysics Data System (ADS)

Gumpenberger, Marlies; Vohland, Katrin; Heyder, Ursula; Poulter, Benjamin; Macey, Kirsten; Rammig, Anja; Popp, Alexander; Cramer, Wolfgang

2010-01-01

Deforestation is a major threat to tropical forests worldwide, contributing up to one-fifth of global carbon emissions into the atmosphere. Despite protection efforts, deforestation of tropical forests has continued in recent years. Providing incentives to reducing deforestation has been proposed in the United Nations Framework Convention on Climate Change (UNFCCC) Bali negotiations in 2007 to decelerate emissions from deforestation (REDD—reduced emissions from deforestation and forest degradation). A number of methodological issues such as ensuring permanence, establishing reference emissions levels that do not reward business-as-usual and having a measuring, reporting and verification system in place are essential elements in implementing successful REDD schemes. To assess the combined impacts of climate and land-use change on tropical forest carbon stocks in the 21st century, we use a dynamic global vegetation model (LPJ DGVM) driven by five different climate change projections under a given greenhouse gas emission scenario (SRES A2) and two contrasting land-use change scenarios. We find that even under a complete stop of deforestation after the period of the Kyoto Protocol (post-2012) some countries may continue to lose carbon stocks due to climate change. Especially at risk is tropical Latin America, although the presence and magnitude of the risk depends on the climate change scenario. By contrast, strong protection of forests could increase carbon uptake in many tropical countries, due to CO2 fertilization effects, even under altered climate regimes.

A clustering approach to segmenting users of internet-based risk calculators.

PubMed

Harle, C A; Downs, J S; Padman, R

2011-01-01

Risk calculators are widely available Internet applications that deliver quantitative health risk estimates to consumers. Although these tools are known to have varying effects on risk perceptions, little is known about who will be more likely to accept objective risk estimates. To identify clusters of online health consumers that help explain variation in individual improvement in risk perceptions from web-based quantitative disease risk information. A secondary analysis was performed on data collected in a field experiment that measured people's pre-diabetes risk perceptions before and after visiting a realistic health promotion website that provided quantitative risk information. K-means clustering was performed on numerous candidate variable sets, and the different segmentations were evaluated based on between-cluster variation in risk perception improvement. Variation in responses to risk information was best explained by clustering on pre-intervention absolute pre-diabetes risk perceptions and an objective estimate of personal risk. Members of a high-risk overestimater cluster showed large improvements in their risk perceptions, but clusters of both moderate-risk and high-risk underestimaters were much more muted in improving their optimistically biased perceptions. Cluster analysis provided a unique approach for segmenting health consumers and predicting their acceptance of quantitative disease risk information. These clusters suggest that health consumers were very responsive to good news, but tended not to incorporate bad news into their self-perceptions much. These findings help to quantify variation among online health consumers and may inform the targeted marketing of and improvements to risk communication tools on the Internet.

Improved Ant Colony Clustering Algorithm and Its Performance Study

PubMed Central

Gao, Wei

2016-01-01

Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533

Applications of cluster analysis to satellite soundings

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Jakubowicz, O.; Kalnay, E.; Piraino, P.

1984-01-01

The advantages of the use of cluster analysis in the improvement of satellite temperature retrievals were evaluated since the use of natural clusters, which are associated with atmospheric temperature soundings characteristic of different types of air masses, has the potential for improving stratified regression schemes in comparison with currently used methods which stratify soundings based on latitude, season, and land/ocean. The method of discriminatory analysis was used. The correct cluster of temperature profiles from satellite measurements was located in 85% of the cases. Considerable improvement was observed at all mandatory levels using regression retrievals derived in the clusters of temperature (weighted and nonweighted) in comparison with the control experiment and with the regression retrievals derived in the clusters of brightness temperatures of 3 MSU and 5 IR channels.

Enhanced hepatic insulin signaling in the livers of high altitude native rats under basal conditions and in the livers of low altitude native rats under insulin stimulation: a mechanistic study.

PubMed

Al Dera, Hussain; Eleawa, Samy M; Al-Hashem, Fahaid H; Mahzari, Moeber M; Hoja, Ibrahim; Al Khateeb, Mahmoud

2017-07-01

This study was designed to investigate the role of the liver in lowering fasting blood glucose levels (FBG) in rats native to high (HA) and low altitude (LA) areas. As compared with LA natives, besides the improved insulin and glucose tolerance, HA native rats had lower FBG, at least mediated by inhibition of hepatic gluconeogenesis and activation of glycogen synthesis. An effect that is mediated by the enhancement of hepatic insulin signaling mediated by the decreased phosphorylation of TSC induced inhibition of mTOR function. Such effect was independent of activation of AMPK nor stabilization of HIF1α, but most probably due to oxidative stress induced REDD1 expression. However, under insulin stimulation, and in spite of the less activated mTOR function in HA native rats, LA native rats had higher glycogen content and reduced levels of gluconeogenic enzymes with a more enhanced insulin signaling, mainly due to higher levels of p-IRS1 (tyr612).

Towards a System Combining SAR and Optical Sentinel Data to Monitor Gold Mining in the Guiana Shield

NASA Astrophysics Data System (ADS)

Rahm, Mathieu; Lardeux, Cedric; Frison, Pierre-Louis; Bedeau, Caroline; Crabbe, Sarah; Svensson, Sara; Hardjoprajitno, Mercedes; Moe soe Let, Valentien; Miranda, Pricilla; Paloeng, Consuela; Kasanpawiro, Cindyrella; Smartt, Towana; Totaram, Jasmin; Funi, Claudia; Farias, Patrick; Lauger, Anthony

2016-08-01

Included in the Guiana Shield ecosystem which is one of the largest blocks of intact tropical forest worldwide, Guyana, Suriname, French Guiana and the Brazilian state of Amapá play a critical role in mitigating climate change, preserving biodiversity and regulating water of the Amazon basin. Under low pressure in the past, degradation of this fragile ecosystem is growing, especially driven by gold mining activities.The REDD+ for the Guiana Shield project developed a method involving each country in data production to monitor the impact of this activity on the forest cover and freshwater at the regional level. This paper presents the data and methodology that were used to quantify the impact on the forest cover. It discusses the results of three reference years (2001, 2008 and 2014) which confirmed the alarming expansion of gold mining in the region. Furthermore, the paper shows the results of innovative methods combining the use of optical and Synthetic Aperture Radar (SAR) satellite data on pilot sites to improve the efficiency of future monitoring.

Long-term affects of experimental flows on riverine biota below a reservoir

NASA Astrophysics Data System (ADS)

Robinson, Chris; Ortlepp, Johannes

2010-05-01

Large dams have altered the flow regime of most rivers on the globe with consequent effects on riverine biota. Experimental flows (multiple floods per year) have been used on the regulated Spöl River below Livigno Reservoir for over 9 years to enhance the ecological condition of the river. The flow program has improved the brown trout fishery in the river as indicated by an increased number of redds. Floods have reset periphyton assemblages from a moss-dominated streambed to one dominated by diatoms and patches of filamentous algae. Zoobenthic assemblages have shown dramatic shifts in benthic structure in line with predictions from altered state models. Ecosystem regime shifts have been characterized with increases in parameter variances followed by periods of stable states. The system appears to be entering a second zoobenthic regime shift after year 8, perhaps in response to biotic interactions due to changes in the fishery. The response patterns clearly show that a long-term perspective must be in place when assessing biotic responses to changes in physical habitat properties resulting from flow experiments.

Construction and application of Red5 cluster based on OpenStack

NASA Astrophysics Data System (ADS)

Wang, Jiaqing; Song, Jianxin

2017-08-01

With the application and development of cloud computing technology in various fields, the resource utilization rate of the data center has been improved obviously, and the system based on cloud computing platform has also improved the expansibility and stability. In the traditional way, Red5 cluster resource utilization is low and the system stability is poor. This paper uses cloud computing to efficiently calculate the resource allocation ability, and builds a Red5 server cluster based on OpenStack. Multimedia applications can be published to the Red5 cloud server cluster. The system achieves the flexible construction of computing resources, but also greatly improves the stability of the cluster and service efficiency.

Breast Cancer Symptom Clusters Derived from Social Media and Research Study Data Using Improved K-Medoid Clustering.

PubMed

Ping, Qing; Yang, Christopher C; Marshall, Sarah A; Avis, Nancy E; Ip, Edward H

2016-06-01

Most cancer patients, including patients with breast cancer, experience multiple symptoms simultaneously while receiving active treatment. Some symptoms tend to occur together and may be related, such as hot flashes and night sweats. Co-occurring symptoms may have a multiplicative effect on patients' functioning, mental health, and quality of life. Symptom clusters in the context of oncology were originally described as groups of three or more related symptoms. Some authors have suggested symptom clusters may have practical applications, such as the formulation of more effective therapeutic interventions that address the combined effects of symptoms rather than treating each symptom separately. Most studies that have sought to identify clusters in breast cancer survivors have relied on traditional research studies. Social media, such as online health-related forums, contain a bevy of user-generated content in the form of threads and posts, and could be used as a data source to identify and characterize symptom clusters among cancer patients. The present study seeks to determine patterns of symptom clusters in breast cancer survivors derived from both social media and research study data using improved K-Medoid clustering. A total of 50,426 publicly available messages were collected from Medhelp.com and 653 questionnaires were collected as part of a research study. The network of symptoms built from social media was sparse compared to that of the research study data, making the social media data easier to partition. The proposed revised K-Medoid clustering helps to improve the clustering performance by re-assigning some of the negative-ASW (average silhouette width) symptoms to other clusters after initial K-Medoid clustering. This retains an overall non-decreasing ASW and avoids the problem of trapping in local optima. The overall ASW, individual ASW, and improved interpretation of the final clustering solution suggest improvement. The clustering results suggest that some symptom clusters are consistent across social media data and clinical data, such as gastrointestinal (GI) related symptoms, menopausal symptoms, mood-change symptoms, cognitive impairment and pain-related symptoms. We recommend an integrative approach taking advantage of both data sources. Social media data could provide context for the interpretation of clustering results derived from research study data, while research study data could compensate for the risk of lower precision and recall found using social media data.

Breast Cancer Symptom Clusters Derived from Social Media and Research Study Data Using Improved K-Medoid Clustering

PubMed Central

Ping, Qing; Yang, Christopher C.; Marshall, Sarah A.; Avis, Nancy E.; Ip, Edward H.

2017-01-01

Most cancer patients, including patients with breast cancer, experience multiple symptoms simultaneously while receiving active treatment. Some symptoms tend to occur together and may be related, such as hot flashes and night sweats. Co-occurring symptoms may have a multiplicative effect on patients’ functioning, mental health, and quality of life. Symptom clusters in the context of oncology were originally described as groups of three or more related symptoms. Some authors have suggested symptom clusters may have practical applications, such as the formulation of more effective therapeutic interventions that address the combined effects of symptoms rather than treating each symptom separately. Most studies that have sought to identify clusters in breast cancer survivors have relied on traditional research studies. Social media, such as online health-related forums, contain a bevy of user-generated content in the form of threads and posts, and could be used as a data source to identify and characterize symptom clusters among cancer patients. The present study seeks to determine patterns of symptom clusters in breast cancer survivors derived from both social media and research study data using improved K-Medoid clustering. A total of 50,426 publicly available messages were collected from Medhelp.com and 653 questionnaires were collected as part of a research study. The network of symptoms built from social media was sparse compared to that of the research study data, making the social media data easier to partition. The proposed revised K-Medoid clustering helps to improve the clustering performance by re-assigning some of the negative-ASW (average silhouette width) symptoms to other clusters after initial K-Medoid clustering. This retains an overall non-decreasing ASW and avoids the problem of trapping in local optima. The overall ASW, individual ASW, and improved interpretation of the final clustering solution suggest improvement. The clustering results suggest that some symptom clusters are consistent across social media data and clinical data, such as gastrointestinal (GI) related symptoms, menopausal symptoms, mood-change symptoms, cognitive impairment and pain-related symptoms. We recommend an integrative approach taking advantage of both data sources. Social media data could provide context for the interpretation of clustering results derived from research study data, while research study data could compensate for the risk of lower precision and recall found using social media data. PMID:29152536

Hungry Horse Dam Fisheries Mitigation, 1992-1993 Progress Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

DosSantos, Joe; Vashro, Jim; Lockard, Larry

1994-06-01

In February of 1900, over forty agency representatives and interested citizens began development of the 1991 Mitigation Plan. This effort culminated in the 1993 Implementation Plan for mitigation of fish losses attributable to the construction and operation of Hungry Horse Dam. The primary purpose of this biennial report is to inform the public of the status of ongoing mitigation activities resulting from those planning efforts. A habitat improvement project is underway to benefit bull trout in Big Creek in the North Fork drainage of the Flathead River and work is planned in Hay Creek, another North Fork tributary. Bull troutmore » redd counts have been expanded and experimental programs involving genetic evaluation, outmigrant monitoring, and hatchery studies have been initiated, Cutthroat mitigation efforts have focused on habitat improvements in Elliott Creek and Taylor`s Outflow and improvements have been followed by imprint plants of hatchery fish and/or eyed eggs in those streams. Rogers Lake west of Kalispell and Lion Lake, near Hungry Horse, were chemically rehabilitated. Cool and warm water fish habitat has been improved in Halfmoon Lake and Echo Lake. Public education and public interest is important to the future success of mitigation activities. As part of the mitigation team`s public awareness responsibility we have worked with numerous volunteer groups, public agencies, and private landowners to stimulate interest and awareness of mitigation activities and the aquatic ecosystem. The purpose of this biennial report is to foster public awareness of, and support for, mitigation activities as we move forward in implementing the Hungry Horse Dam Fisheries Mitigation Implementation Plan.« less

An improved K-means clustering method for cDNA microarray image segmentation.

PubMed

Wang, T N; Li, T J; Shao, G F; Wu, S X

2015-07-14

Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

Improving performance through concept formation and conceptual clustering

NASA Technical Reports Server (NTRS)

Fisher, Douglas H.

1992-01-01

Research from June 1989 through October 1992 focussed on concept formation, clustering, and supervised learning for purposes of improving the efficiency of problem-solving, planning, and diagnosis. These projects resulted in two dissertations on clustering, explanation-based learning, and means-ends planning, and publications in conferences and workshops, several book chapters, and journals; a complete Bibliography of NASA Ames supported publications is included. The following topics are studied: clustering of explanations and problem-solving experiences; clustering and means-end planning; and diagnosis of space shuttle and space station operating modes.

A Differential Evolution-Based Routing Algorithm for Environmental Monitoring Wireless Sensor Networks

PubMed Central

Li, Xiaofang; Xu, Lizhong; Wang, Huibin; Song, Jie; Yang, Simon X.

2010-01-01

The traditional Low Energy Adaptive Cluster Hierarchy (LEACH) routing protocol is a clustering-based protocol. The uneven selection of cluster heads results in premature death of cluster heads and premature blind nodes inside the clusters, thus reducing the overall lifetime of the network. With a full consideration of information on energy and distance distribution of neighboring nodes inside the clusters, this paper proposes a new routing algorithm based on differential evolution (DE) to improve the LEACH routing protocol. To meet the requirements of monitoring applications in outdoor environments such as the meteorological, hydrological and wetland ecological environments, the proposed algorithm uses the simple and fast search features of DE to optimize the multi-objective selection of cluster heads and prevent blind nodes for improved energy efficiency and system stability. Simulation results show that the proposed new LEACH routing algorithm has better performance, effectively extends the working lifetime of the system, and improves the quality of the wireless sensor networks. PMID:22219670

Improving local clustering based top-L link prediction methods via asymmetric link clustering information

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

2018-02-01

Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

The improvement and simulation for LEACH clustering routing protocol

NASA Astrophysics Data System (ADS)

Ji, Ai-guo; Zhao, Jun-xiang

2017-01-01

An energy-balanced unequal multi-hop clustering routing protocol LEACH-EUMC is proposed in this paper. The candidate cluster head nodes are elected firstly, then they compete to be formal cluster head nodes by adding energy and distance factors, finally the date are transferred to sink through multi-hop. The results of simulation show that the improved algorithm is better than LEACH in network lifetime, energy consumption and the amount of data transmission.

Improving clustering with metabolic pathway data.

PubMed

Milone, Diego H; Stegmayer, Georgina; López, Mariana; Kamenetzky, Laura; Carrari, Fernando

2014-04-10

It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.The algorithm is available as a web-demo at http://fich.unl.edu.ar/sinc/web-demo/bsom-lite/. The source code and the data sets supporting the results of this article are available at http://sourceforge.net/projects/sourcesinc/files/bsom.

Forest carbon stocks and fluxes in physiographic zones of India.

PubMed

Sheikh, Mehraj A; Kumar, Munesh; Bussman, Rainer W; Todaria, Np

2011-12-25

Reducing carbon Emissions from Deforestation and Degradation (REDD+) is of central importance to combat climate change. Foremost among the challenges is quantifying nation's carbon emissions from deforestation and degradation, which requires information on forest carbon storage. Here we estimated carbon storage in India's forest biomass for the years 2003, 2005 and 2007 and the net flux caused by deforestation and degradation, between two assessment periods i.e., Assessment Period first (ASP I), 2003-2005 and Assessment Period second (ASP II), 2005-2007. The total estimated carbon stock in India's forest biomass varied from 3325 to 3161 Mt during the years 2003 to 2007 respectively. There was a net flux of 372 Mt of CO2 in ASP I and 288 Mt of CO2 in ASP II, with an annual emission of 186 and 114 Mt of CO2 respectively. The carbon stock in India's forest biomass decreased continuously from 2003 onwards, despite slight increase in forest cover. The rate of carbon loss from the forest biomass in ASP II has dropped by 38.27% compared to ASP I. With the Copenhagen Accord, India along with other BASIC countries China, Brazil and South Africa is voluntarily going to cut emissions. India will voluntary reduce the emission intensity of its GDP by 20-25% by 2020 in comparison to 2005 level, activities like REDD+ can provide a relatively cost-effective way of offsetting emissions, either by increasing the removals of greenhouse gases from the atmosphere by afforestation programmes, managing forests, or by reducing emissions through deforestation and degradation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Maoyi; Asner, Gregory P.

Amazon deforestation contributes significantly to global carbon (C) emissions. In comparison, the contribution from selective logging to atmospheric CO2 emissions, and its impact on regional C dynamics, is highly uncertain. Using a new geographically-based modeling approach in combination with high resolution remote sensing data from 1999-2002, we estimate that C emissions were 0.04 – 0.05 Pg C yr-1 due to selective logging from a ~2,664,960 km2 region of the Brazilian Amazon. Selective logging was responsible for 15-19% higher carbon emissions than reported from deforestation (clear-cutting) alone. Our simulations indicated that forest carbon lost via selective logging lasts two to threemore » decades following harvest, and that the original live biomass takes up to a century to recover, if the forests are not subsequently cleared. The two- to three-decade loss of carbon results from the biomass damaged by logging activities, including leaves, wood, and roots, estimated to be 89.1 Tg C yr-1 from 1999-2002 over the study region, leaving 70.0 Tg C yr-1 and 7.9 Tg C yr-1 to accumulate as coarse woody debris and soil C, respectively. While avoided deforestation is central to crediting rainforest nations for reduced carbon emissions, the extent and intensity of selective logging are also critical to determining carbon emissions in the context of Reduced Emissions from Deforestation and Forest Degradation (REDD). We show that a combination of automated high-resolution satellite monitoring and detailed forest C modeling can yield spatially explicit estimates of harvest related C losses and subsequent recovery in support of REDD and other international carbon market mechanisms.« less

Benchmark map of forest carbon stocks in tropical regions across three continents

PubMed Central

Saatchi, Sassan S.; Harris, Nancy L.; Brown, Sandra; Lefsky, Michael; Mitchard, Edward T. A.; Salas, William; Zutta, Brian R.; Buermann, Wolfgang; Lewis, Simon L.; Hagen, Stephen; Petrova, Silvia; White, Lee; Silman, Miles; Morel, Alexandra

2011-01-01

Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a “benchmark” map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ±6% to ±53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ±5% and ca. ±1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete. PMID:21628575

Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach

USGS Publications Warehouse

Meredith, Christy S.; Budy, Phaedra; Hooten, Mevin B.; Oliveira Prates, Marcos

2017-01-01

Trout species often segregate along elevational gradients, yet the mechanisms driving this pattern are not fully understood. On the Logan River, Utah, USA, exotic brown trout (Salmo trutta) dominate at low elevations but are near-absent from high elevations with native Bonneville cutthroat trout (Onchorhynchus clarkii utah). We used a spatially-explicit Bayesian modeling approach to evaluate how abiotic conditions (describing mechanisms related to temperature and physical habitat) as well as propagule pressure explained the distribution of brown trout in this system. Many covariates strongly explained redd abundance based on model performance and coefficient strength, including average annual temperature, average summer temperature, gravel availability, distance from a concentrated stocking area, and anchor ice-impeded distance from a concentrated stocking area. In contrast, covariates that exhibited low performance in models and/or a weak relationship to redd abundance included reach-average water depth, stocking intensity to the reach, average winter temperature, and number of days with anchor ice. Even if climate change creates more suitable summer temperature conditions for brown trout at high elevations, our findings suggest their success may be limited by other conditions. The potential role of anchor ice in limiting movement upstream is compelling considering evidence suggesting anchor ice prevalence on the Logan River has decreased significantly over the last several decades, likely in response to climatic changes. Further experimental and field research is needed to explore the role of anchor ice, spawning gravel availability, and locations of historical stocking in structuring brown trout distributions on the Logan River and elsewhere.

REDD+ and climate smart agriculture in landscapes: A case study in Vietnam using companion modelling.

PubMed

Salvini, G; Ligtenberg, A; van Paassen, A; Bregt, A K; Avitabile, V; Herold, M

2016-05-01

Finding land use strategies that merge land-based climate change mitigation measures and adaptation strategies is still an open issue in climate discourse. This article explores synergies and trade-offs between REDD+, a scheme that focuses mainly on mitigation through forest conservation, with "Climate Smart Agriculture", an approach that emphasizes adaptive agriculture. We introduce a framework for ex-ante assessment of the impact of land management policies and interventions and for quantifying their impacts on land-based mitigation and adaptation goals. The framework includes a companion modelling (ComMod) process informed by interviews with policymakers, local experts and local farmers. The ComMod process consists of a Role-Playing Game with local farmers and an Agent Based Model. The game provided a participatory means to develop policy and climate change scenarios. These scenarios were then used as inputs to the Agent Based Model, a spatially explicit model to simulate landscape dynamics and the associated carbon emissions over decades. We applied the framework using as case study a community in central Vietnam, characterized by deforestation for subsistence agriculture and cultivation of acacias as a cash crop. The main findings show that the framework is useful in guiding consideration of local stakeholders' goals, needs and constraints. Additionally the framework provided beneficial information to policymakers, pointing to ways that policies might be re-designed to make them better tailored to local circumstances and therefore more effective in addressing synergistically climate change mitigation and adaptation objectives. Copyright © 2015 Elsevier Ltd. All rights reserved.

Forest carbon stocks and fluxes in physiographic zones of India

PubMed Central

2011-01-01

Background Reducing carbon Emissions from Deforestation and Degradation (REDD+) is of central importance to combat climate change. Foremost among the challenges is quantifying nation's carbon emissions from deforestation and degradation, which requires information on forest carbon storage. Here we estimated carbon storage in India's forest biomass for the years 2003, 2005 and 2007 and the net flux caused by deforestation and degradation, between two assessment periods i.e., Assessment Period first (ASP I), 2003-2005 and Assessment Period second (ASP II), 2005-2007. Results The total estimated carbon stock in India's forest biomass varied from 3325 to 3161 Mt during the years 2003 to 2007 respectively. There was a net flux of 372 Mt of CO2 in ASP I and 288 Mt of CO2 in ASP II, with an annual emission of 186 and 114 Mt of CO2 respectively. The carbon stock in India's forest biomass decreased continuously from 2003 onwards, despite slight increase in forest cover. The rate of carbon loss from the forest biomass in ASP II has dropped by 38.27% compared to ASP I. Conclusion With the Copenhagen Accord, India along with other BASIC countries China, Brazil and South Africa is voluntarily going to cut emissions. India will voluntary reduce the emission intensity of its GDP by 20-25% by 2020 in comparison to 2005 level, activities like REDD+ can provide a relatively cost-effective way of offsetting emissions, either by increasing the removals of greenhouse gases from the atmosphere by afforestation programmes, managing forests, or by reducing emissions through deforestation and degradation. PMID:22196920

Selection of the Maximum Spatial Cluster Size of the Spatial Scan Statistic by Using the Maximum Clustering Set-Proportion Statistic.

PubMed

Ma, Yue; Yin, Fei; Zhang, Tao; Zhou, Xiaohua Andrew; Li, Xiaosong

2016-01-01

Spatial scan statistics are widely used in various fields. The performance of these statistics is influenced by parameters, such as maximum spatial cluster size, and can be improved by parameter selection using performance measures. Current performance measures are based on the presence of clusters and are thus inapplicable to data sets without known clusters. In this work, we propose a novel overall performance measure called maximum clustering set-proportion (MCS-P), which is based on the likelihood of the union of detected clusters and the applied dataset. MCS-P was compared with existing performance measures in a simulation study to select the maximum spatial cluster size. Results of other performance measures, such as sensitivity and misclassification, suggest that the spatial scan statistic achieves accurate results in most scenarios with the maximum spatial cluster sizes selected using MCS-P. Given that previously known clusters are not required in the proposed strategy, selection of the optimal maximum cluster size with MCS-P can improve the performance of the scan statistic in applications without identified clusters.

Selection of the Maximum Spatial Cluster Size of the Spatial Scan Statistic by Using the Maximum Clustering Set-Proportion Statistic

PubMed Central

Ma, Yue; Yin, Fei; Zhang, Tao; Zhou, Xiaohua Andrew; Li, Xiaosong

2016-01-01

Spatial scan statistics are widely used in various fields. The performance of these statistics is influenced by parameters, such as maximum spatial cluster size, and can be improved by parameter selection using performance measures. Current performance measures are based on the presence of clusters and are thus inapplicable to data sets without known clusters. In this work, we propose a novel overall performance measure called maximum clustering set–proportion (MCS-P), which is based on the likelihood of the union of detected clusters and the applied dataset. MCS-P was compared with existing performance measures in a simulation study to select the maximum spatial cluster size. Results of other performance measures, such as sensitivity and misclassification, suggest that the spatial scan statistic achieves accurate results in most scenarios with the maximum spatial cluster sizes selected using MCS-P. Given that previously known clusters are not required in the proposed strategy, selection of the optimal maximum cluster size with MCS-P can improve the performance of the scan statistic in applications without identified clusters. PMID:26820646

An improved K-means clustering algorithm in agricultural image segmentation

NASA Astrophysics Data System (ADS)

Cheng, Huifeng; Peng, Hui; Liu, Shanmei

Image segmentation is the first important step to image analysis and image processing. In this paper, according to color crops image characteristics, we firstly transform the color space of image from RGB to HIS, and then select proper initial clustering center and cluster number in application of mean-variance approach and rough set theory followed by clustering calculation in such a way as to automatically segment color component rapidly and extract target objects from background accurately, which provides a reliable basis for identification, analysis, follow-up calculation and process of crops images. Experimental results demonstrate that improved k-means clustering algorithm is able to reduce the computation amounts and enhance precision and accuracy of clustering.

Under What Circumstances Does External Knowledge about the Correlation Structure Improve Power in Cluster Randomized Designs?

ERIC Educational Resources Information Center

Rhoads, Christopher

2014-01-01

Recent publications have drawn attention to the idea of utilizing prior information about the correlation structure to improve statistical power in cluster randomized experiments. Because power in cluster randomized designs is a function of many different parameters, it has been difficult for applied researchers to discern a simple rule explaining…

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling.

PubMed

Sefuba, Maria; Walingo, Tom; Takawira, Fambirai

2015-09-18

This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols.

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling

PubMed Central

Sefuba, Maria; Walingo, Tom; Takawira, Fambirai

2015-01-01

This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols. PMID:26393608

Photosensitized Reduction of Carbon Dioxide in Solution Using Noble-Metal Clusters for Electron Transfer

NASA Astrophysics Data System (ADS)

Toshima, Naoki; Yamaji, Yumi; Teranishi, Toshiharu; Yonezawa, Tetsu

1995-03-01

Carbon dioxide was reduced to methane by visible-light irradiation of a solution composed of tris(bipyridine)ruthenium(III) as photosensitizer, ethylenediaminetetraacetic acid disodium salt as sacrificial reagent, methyl viologen as electron relay, and a colloidal dispersion of polymer-protected noble-metal clusters, prepared by alcohol-reduction, as catalyst. Among the noble-metal clusters examined, Pt clusters showed the highest activity for the formation of methane as well as hydrogen. In order to improve the activity, oxidized clusters and bimetallic clusters were also applied. For example, the CH4 yield in 3-h irradiation increased from 51 x 10-3 μmol with unoxidized Pt clusters to 72 x 10-3 μmol with partially oxidized ones. In the case of Pt/Ru bimetalic systems, the improvement of the catalytic activity by air treatment was much greater than in case of monometallic clusters.

An optimal autonomous microgrid cluster based on distributed generation droop parameter optimization and renewable energy sources using an improved grey wolf optimizer

NASA Astrophysics Data System (ADS)

Moazami Goodarzi, Hamed; Kazemi, Mohammad Hosein

2018-05-01

Microgrid (MG) clustering is regarded as an important driver in improving the robustness of MGs. However, little research has been conducted on providing appropriate MG clustering. This article addresses this shortfall. It proposes a novel multi-objective optimization approach for finding optimal clustering of autonomous MGs by focusing on variables such as distributed generation (DG) droop parameters, the location and capacity of DG units, renewable energy sources, capacitors and powerline transmission. Power losses are minimized and voltage stability is improved while virtual cut-set lines with minimum power transmission for clustering MGs are obtained. A novel chaotic grey wolf optimizer (CGWO) algorithm is applied to solve the proposed multi-objective problem. The performance of the approach is evaluated by utilizing a 69-bus MG in several scenarios.

The stoneroller, Campostoma anomalum (Rafinesque), in Great Smoky Mountains National Park

USGS Publications Warehouse

Lennon, R.E.; Parker, P.S.

1960-01-01

The stoneroller (Campostoma anomalum) is one of the more important fish in Great Smoky Mountains National Park because of its abundance and habits. Although esteemed locally as a food and a bait fish, the stoneroller is exploited but little since the fishing regulations which govern the utilization of game fishes afford it a large measure of protection. Distribution is controlled by gradient with an upper limit of 4.4 percent. Stonerollers limit reproduction of rainbow trout (Salmo gairdneri) by destroying trout redds. Artificial reduction of stoneroller populations is not considered a necessary management procedure.

Better Redd than Dead: Optimizing Reservoir Operations for Wild Fish Survival During Drought

NASA Astrophysics Data System (ADS)

Adams, L. E.; Lund, J. R.; Quiñones, R.

2014-12-01

Extreme droughts are difficult to predict and may incur large economic and ecological costs. Dam operations in drought usually consider minimizing economic costs. However, dam operations also offer an opportunity to increase wild fish survival under difficult conditions. Here, we develop a probabilistic optimization approach to developing reservoir release schedules to maximize fish survival in regulated rivers. A case study applies the approach to wild Fall-run Chinook Salmon below Folsom Dam on California's American River. Our results indicate that releasing more water early in the drought will, on average, save more wild fish over the long term.

Security clustering algorithm based on reputation in hierarchical peer-to-peer network

NASA Astrophysics Data System (ADS)

Chen, Mei; Luo, Xin; Wu, Guowen; Tan, Yang; Kita, Kenji

2013-03-01

For the security problems of the hierarchical P2P network (HPN), the paper presents a security clustering algorithm based on reputation (CABR). In the algorithm, we take the reputation mechanism for ensuring the security of transaction and use cluster for managing the reputation mechanism. In order to improve security, reduce cost of network brought by management of reputation and enhance stability of cluster, we select reputation, the historical average online time, and the network bandwidth as the basic factors of the comprehensive performance of node. Simulation results showed that the proposed algorithm improved the security, reduced the network overhead, and enhanced stability of cluster.

Energy efficient strategy for throughput improvement in wireless sensor networks.

PubMed

Jabbar, Sohail; Minhas, Abid Ali; Imran, Muhammad; Khalid, Shehzad; Saleem, Kashif

2015-01-23

Network lifetime and throughput are one of the prime concerns while designing routing protocols for wireless sensor networks (WSNs). However, most of the existing schemes are either geared towards prolonging network lifetime or improving throughput. This paper presents an energy efficient routing scheme for throughput improvement in WSN. The proposed scheme exploits multilayer cluster design for energy efficient forwarding node selection, cluster heads rotation and both inter- and intra-cluster routing. To improve throughput, we rotate the role of cluster head among various nodes based on two threshold levels which reduces the number of dropped packets. We conducted simulations in the NS2 simulator to validate the performance of the proposed scheme. Simulation results demonstrate the performance efficiency of the proposed scheme in terms of various metrics compared to similar approaches published in the literature.

Energy Efficient Strategy for Throughput Improvement in Wireless Sensor Networks

PubMed Central

Jabbar, Sohail; Minhas, Abid Ali; Imran, Muhammad; Khalid, Shehzad; Saleem, Kashif

2015-01-01

Network lifetime and throughput are one of the prime concerns while designing routing protocols for wireless sensor networks (WSNs). However, most of the existing schemes are either geared towards prolonging network lifetime or improving throughput. This paper presents an energy efficient routing scheme for throughput improvement in WSN. The proposed scheme exploits multilayer cluster design for energy efficient forwarding node selection, cluster heads rotation and both inter- and intra-cluster routing. To improve throughput, we rotate the role of cluster head among various nodes based on two threshold levels which reduces the number of dropped packets. We conducted simulations in the NS2 simulator to validate the performance of the proposed scheme. Simulation results demonstrate the performance efficiency of the proposed scheme in terms of various metrics compared to similar approaches published in the literature. PMID:25625902

Formation of Education Clusters as a Way to Improve Education

ERIC Educational Resources Information Center

Aitbayeva, Gul'zamira D.; Zhubanova, Mariyash K.; Kulgildinova, Tulebike A.; Tusupbekova, Gulsum M.; Uaisova, Gulnar I.

2016-01-01

The purpose of this research is to analyze basic prerequisites formation and development factors of educational clusters of the world's leading nations for studying the possibility of cluster policy introduction and creating educational clusters in the Republic of Kazakhstan. The authors of this study concluded that educational cluster could be…

Cluster management.

PubMed

Katz, R

1992-11-01

Cluster management is a management model that fosters decentralization of management, develops leadership potential of staff, and creates ownership of unit-based goals. Unlike shared governance models, there is no formal structure created by committees and it is less threatening for managers. There are two parts to the cluster management model. One is the formation of cluster groups, consisting of all staff and facilitated by a cluster leader. The cluster groups function for communication and problem-solving. The second part of the cluster management model is the creation of task forces. These task forces are designed to work on short-term goals, usually in response to solving one of the unit's goals. Sometimes the task forces are used for quality improvement or system problems. Clusters are groups of not more than five or six staff members, facilitated by a cluster leader. A cluster is made up of individuals who work the same shift. For example, people with job titles who work days would be in a cluster. There would be registered nurses, licensed practical nurses, nursing assistants, and unit clerks in the cluster. The cluster leader is chosen by the manager based on certain criteria and is trained for this specialized role. The concept of cluster management, criteria for choosing leaders, training for leaders, using cluster groups to solve quality improvement issues, and the learning process necessary for manager support are described.

Mindfulness-Based Stress Reduction in Post-treatment Breast Cancer Patients: Immediate and Sustained Effects Across Multiple Symptom Clusters.

PubMed

Reich, Richard R; Lengacher, Cecile A; Alinat, Carissa B; Kip, Kevin E; Paterson, Carly; Ramesar, Sophia; Han, Heather S; Ismail-Khan, Roohi; Johnson-Mallard, Versie; Moscoso, Manolete; Budhrani-Shani, Pinky; Shivers, Steve; Cox, Charles E; Goodman, Matthew; Park, Jong

2017-01-01

Breast cancer survivors (BCS) face adverse physical and psychological symptoms, often co-occurring. Biologic and psychological factors may link symptoms within clusters, distinguishable by prevalence and/or severity. Few studies have examined the effects of behavioral interventions or treatment of symptom clusters. The aim of this study was to identify symptom clusters among post-treatment BCS and determine symptom cluster improvement following the Mindfulness-Based Stress Reduction for Breast Cancer (MBSR(BC)) program. Three hundred twenty-two Stage 0-III post-treatment BCS were randomly assigned to either a six-week MBSR(BC) program or usual care. Psychological (depression, anxiety, stress, and fear of recurrence), physical (fatigue, pain, sleep, and drowsiness), and cognitive symptoms and quality of life were assessed at baseline, six, and 12 weeks, along with demographic and clinical history data at baseline. A three-step analytic process included the error-accounting models of factor analysis and structural equation modeling. Four symptom clusters emerged at baseline: pain, psychological, fatigue, and cognitive. From baseline to six weeks, the model demonstrated evidence of MBSR(BC) effectiveness in both the psychological (anxiety, depression, perceived stress and QOL, emotional well-being) (P = 0.007) and fatigue (fatigue, sleep, and drowsiness) (P < 0.001) clusters. Results between six and 12 weeks showed sustained effects, but further improvement was not observed. Our results provide clinical effectiveness evidence that MBSR(BC) works to improve symptom clusters, particularly for psychological and fatigue symptom clusters, with the greatest improvement occurring during the six-week program with sustained effects for several weeks after MBSR(BC) training. Name and URL of Registry: ClinicalTrials.gov. Registration number: NCT01177124. Copyright © 2016. Published by Elsevier Inc.

Network-based spatial clustering technique for exploring features in regional industry

NASA Astrophysics Data System (ADS)

Chou, Tien-Yin; Huang, Pi-Hui; Yang, Lung-Shih; Lin, Wen-Tzu

2008-10-01

In the past researches, industrial cluster mainly focused on single or particular industry and less on spatial industrial structure and mutual relations. Industrial cluster could generate three kinds of spillover effects, including knowledge, labor market pooling, and input sharing. In addition, industrial cluster indeed benefits industry development. To fully control the status and characteristics of district industrial cluster can facilitate to improve the competitive ascendancy of district industry. The related researches on industrial spatial cluster were of great significance for setting up industrial policies and promoting district economic development. In this study, an improved model, GeoSOM, that combines DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and SOM (Self-Organizing Map) was developed for analyzing industrial cluster. Different from former distance-based algorithm for industrial cluster, the proposed GeoSOM model can calculate spatial characteristics between firms based on DBSCAN algorithm and evaluate the similarity between firms based on SOM clustering analysis. The demonstrative data sets, the manufacturers around Taichung County in Taiwan, were analyzed for verifying the practicability of the proposed model. The analyzed results indicate that GeoSOM is suitable for evaluating spatial industrial cluster.

Topology control algorithm for wireless sensor networks based on Link forwarding

NASA Astrophysics Data System (ADS)

Pucuo, Cairen; Qi, Ai-qin

2018-03-01

The research of topology control could effectively save energy and increase the service life of network based on wireless sensor. In this paper, a arithmetic called LTHC (link transmit hybrid clustering) based on link transmit is proposed. It decreases expenditure of energy by changing the way of cluster-node’s communication. The idea is to establish a link between cluster and SINK node when the cluster is formed, and link-node must be non-cluster. Through the link, cluster sends information to SINK nodes. For the sake of achieving the uniform distribution of energy on the network, prolongate the network survival time, and improve the purpose of communication, the communication will cut down much more expenditure of energy for cluster which away from SINK node. In the two aspects of improving the traffic and network survival time, we find that the LTCH is far superior to the traditional LEACH by experiments.

Development of a two-fluid drag law for clustered particles using direct numerical simulation and validation through experiments

NASA Astrophysics Data System (ADS)

Abbasi Baharanchi, Ahmadreza

This dissertation focused on development and utilization of numerical and experimental approaches to improve the CFD modeling of fluidization flow of cohesive micron size particles. The specific objectives of this research were: (1) Developing a cluster prediction mechanism applicable to Two-Fluid Modeling (TFM) of gas-solid systems (2) Developing more accurate drag models for Two-Fluid Modeling (TFM) of gas-solid fluidization flow with the presence of cohesive interparticle forces (3) using the developed model to explore the improvement of accuracy of TFM in simulation of fluidization flow of cohesive powders (4) Understanding the causes and influential factor which led to improvements and quantification of improvements (5) Gathering data from a fast fluidization flow and use these data for benchmark validations. Simulation results with two developed cluster-aware drag models showed that cluster prediction could effectively influence the results in both the first and second cluster-aware models. It was proven that improvement of accuracy of TFM modeling using three versions of the first hybrid model was significant and the best improvements were obtained by using the smallest values of the switch parameter which led to capturing the smallest chances of cluster prediction. In the case of the second hybrid model, dependence of critical model parameter on only Reynolds number led to the fact that improvement of accuracy was significant only in dense section of the fluidized bed. This finding may suggest that a more sophisticated particle resolved DNS model, which can span wide range of solid volume fraction, can be used in the formulation of the cluster-aware drag model. The results of experiment suing high speed imaging indicated the presence of particle clusters in the fluidization flow of FCC inside the riser of FIU-CFB facility. In addition, pressure data was successfully captured along the fluidization column of the facility and used as benchmark validation data for the second hybrid model developed in the present dissertation. It was shown the second hybrid model could predict the pressure data in the dense section of the fluidization column with better accuracy.

Organic dairy farmers put more emphasis on production traits than conventional farmers.

PubMed

Slagboom, M; Kargo, M; Edwards, D; Sørensen, A C; Thomasen, J R; Hjortø, L

2016-12-01

The overall aim of this research was to characterize the preferences of Danish dairy farmers for improvements in breeding goal traits. The specific aims were (1) to investigate the presence of heterogeneity in farmers' preferences by means of cluster analysis, and (2) to associate these clusters with herd characteristics and production systems (organic or conventional). We established a web-based survey to characterize the preferences of farmers for improvements in 10 traits, by means of pairwise rankings. We also collected a considerable number of herd characteristics. Overall, 106 organic farmers and 290 conventional farmers answered the survey, all with Holstein cows. The most preferred trait improvement was cow fertility, and the least preferred was calving difficulty. By means of cluster analysis, we identified 4 distinct clusters of farmers and named them according to the trait improvements that were most preferred: Health and Fertility, Production and Udder Health, Survival, and Fertility and Production. Some herd characteristics differed between clusters; for example, farmers in the Survival cluster had twice the percentage of dead cows in their herds compared with the other clusters, and farmers that gave the highest ranking to cow and heifer fertility had the lowest conception rate in their herds. This finding suggests that farmers prefer to improve traits that are more problematic in their herd. The proportion of organic and conventional farmers also differed between clusters; we found a higher proportion of organic farmers in the production-based clusters. When we analyzed organic and conventional data separately, we found that organic farmers ranked production traits higher than conventional farmers. The herds of organic farmers had lower milk yields and lower disease incidences, which might explain the high ranking of milk production and the low ranking of disease traits. This study shows that heterogeneity exists in farmers' preferences for improvements in breeding goal traits, that organic and conventional farmers differ in their preferences, and that herd characteristics can be linked to different farmer clusters. The results of this study could be used for the future development of breeding goals in Danish Holstein cows and for the development of customized total merit indices based on farmer preferences. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Snake River Sockeye Salmon Captive Broodstock Program; Research Element, 2003 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Willard, Catherine; Plaster, Kurtis; Castillo, Jason

2005-01-01

On November 20, 1991, the National Oceanic Atmospheric Administration listed Snake River sockeye salmon Oncorhynchus nerka as endangered under the Endangered Species Act of 1973. In 1991, the Shoshone-Bannock Tribes (SBT) and Idaho Department of Fish and Game (IDFG) initiated the Snake River Sockeye Salmon Captive Broodstock Program to conserve and rebuild populations in Idaho. Restoration efforts are focused on Redfish, Pettit, and Alturas lakes within the Sawtooth Valley. The first release of hatchery-produced adults occurred in 1993. The first release of juvenile sockeye salmon from the captive broodstock program occurred in 1994. In 1999, the first anadromous adult returnsmore » from the captive broodstock program were recorded when six jacks and one jill were captured at the IDFG Sawtooth Fish Hatchery. In 2003, progeny from the captive broodstock program were released using three strategies: eyed-eggs were planted in Pettit and Alturas lakes in November and December, age-0 presmolts were released to Alturas, Pettit, and Redfish lakes in October, and hatchery-produced adult sockeye salmon were released to Redfish Lake for volitional spawning in September. Oncorhynchus nerka population monitoring was conducted on Redfish, Alturas, and Pettit lakes using a midwater trawl in September 2003. Age-0 through age-4 O. nerka were captured in Redfish Lake, and population abundance was estimated at 81,727 fish. Age-0 through age-3 O. nerka were captured in Alturas Lake, and population abundance was estimated at 46,234 fish. Age-0 through age-3 O. nerka were captured in Pettit Lake, and population abundance was estimated at 11,961 fish. Angler surveys were conducted from May 25 through August 7, 2003 on Redfish Lake to estimate kokanee harvest. On Redfish Lake, we interviewed 179 anglers and estimated that 424 kokanee were harvested. The calculated kokanee catch rate was 0.09 fish/hour. The juvenile out-migrant trap on Redfish Lake Creek was operated from April 15 to May 29, 2003. We estimated that 4,637 wild/natural and 12,226 hatchery-produced sockeye salmon smolts out-migrated from Redfish Lake in 2003. The hatchery-produced component included an estimated 5,352 out-migrants produced from a summer direct-release made to Redfish Lake in 2002 and 6,874 out-migrants produced from a fall direct-release made in 2002. The juvenile out-migrant traps on Alturas Lake Creek and Pettit Lake Creek were operated by the SBT from April 23 to June 5, 2003 and April 25 to June 4, 2003, respectively. The SBT enumerated 28 wild/natural and 13,329 hatchery-produced sockeye salmon smolts that outmigrated from Pettit Lake and estimated 286 wild/natural and 553 hatchery-produced sockeye salmon smolts out-migrated from Alturas Lake in 2003. The hatchery-produced component of sockeye salmon out-migrants originated from presmolt releases made directly to Pettit and Alturas lakes in 2002. Median travel times for passive integrated transponder (PIT) tagged smolts from the Redfish Lake Creek trap site to Lower Granite Dam were estimated for wild/natural smolts and hatchery-produced smolts. Median travel times for smolts originating from the Redfish Lake Creek trap were 10.6 d for wild/natural smolts, 6.2 d for summer direct-released smolts, and 7.1 d for fall direct-released smolts. Median travel times for PIT-tagged smolts from the Pettit Lake Creek trap site to Lower Granite Dam were estimated for hatchery-produced smolts. Median travel times for smolts originating from the Pettit Lake Creek trap were 14.1 d for fall direct released smolts and 13.6 d for fall direct released smolts. Cumulative unique PIT tag interrogations from Sawtooth Valley juvenile out-migrant traps to mainstem Snake and Columbia river dams were utilized to estimate detection rates for out-migrating sockeye salmon smolts. Detection rate comparisons were made between smolts originating from Redfish, Alturas, and Pettit lakes and the various release strategies. Pettit Lake fall direct released smolts recorded the highest detection rate of 37.14%. In 2003, 312 hatchery-produced adult sockeye salmon were released to Redfish Lake for natural spawning. We observed 42 areas of excavation in the lake from spawning events. Suspected redds were approximately 3 m x 3 m in size and were constructed by multiple pairs of adults. We monitored bull trout spawning in Fishhook Creek, a tributary to Redfish Lake, and in Alpine Creek, a tributary to Alturas Lake. This represented the sixth consecutive year that the index reaches have been surveyed on these two streams. Adult counts (40 adults) and redd counts (17 redds) in Fishhook Creek were similar to counts conducted since monitoring began in 1998. Bull trout numbers (27 adults) and the number of redds observed (14 redds) have gradually increased in Alpine Creek compared to counts from initial monitoring.« less

An Improved Clustering Algorithm of Tunnel Monitoring Data for Cloud Computing

PubMed Central

Zhong, Luo; Tang, KunHao; Li, Lin; Yang, Guang; Ye, JingJing

2014-01-01

With the rapid development of urban construction, the number of urban tunnels is increasing and the data they produce become more and more complex. It results in the fact that the traditional clustering algorithm cannot handle the mass data of the tunnel. To solve this problem, an improved parallel clustering algorithm based on k-means has been proposed. It is a clustering algorithm using the MapReduce within cloud computing that deals with data. It not only has the advantage of being used to deal with mass data but also is more efficient. Moreover, it is able to compute the average dissimilarity degree of each cluster in order to clean the abnormal data. PMID:24982971

VizieR Online Data Catalog: Clusters of galaxies in SDSS-III (Wen+, 2012)

NASA Astrophysics Data System (ADS)

Wen, Z. L.; Han, J. L.; Liu, F. S.

2012-06-01

Wen et al. (2009, Cat. J/ApJS/183/197) identified 39668 galaxy clusters from the SDSS DR6 by the discrimination of member galaxies of clusters using photometric redshifts of galaxies. Wen & Han (2011ApJ...734...68W) improved the method and successfully identified the high-redshift clusters from the deep fields of the Canada-France-Hawaii Telescope (CFHT) Wide survey, the CHFT Deep survey, the Cosmic Evolution Survey, and the Spitzer Wide-area InfraRed Extragalactic survey. Here, we follow and improve the algorithm to identify clusters from SDSS-III (SDSS Data Release 8; Aihara et al. 2011ApJS..193...29A, see Cat. II/306). (1 data file).

Stabilizing ultrasmall Au clusters for enhanced photoredox catalysis.

PubMed

Weng, Bo; Lu, Kang-Qiang; Tang, Zichao; Chen, Hao Ming; Xu, Yi-Jun

2018-04-18

Recently, loading ligand-protected gold (Au) clusters as visible light photosensitizers onto various supports for photoredox catalysis has attracted considerable attention. However, the efficient control of long-term photostability of Au clusters on the metal-support interface remains challenging. Herein, we report a simple and efficient method for enhancing the photostability of glutathione-protected Au clusters (Au GSH clusters) loaded on the surface of SiO 2 sphere by utilizing multifunctional branched poly-ethylenimine (BPEI) as a surface charge modifying, reducing and stabilizing agent. The sequential coating of thickness controlled TiO 2 shells can further significantly improve the photocatalytic efficiency, while such structurally designed core-shell SiO 2 -Au GSH clusters-BPEI@TiO 2 composites maintain high photostability during longtime light illumination conditions. This joint strategy via interfacial modification and composition engineering provides a facile guideline for stabilizing ultrasmall Au clusters and rational design of Au clusters-based composites with improved activity toward targeting applications in photoredox catalysis.

Using Complementary Learning Clusters in Studying Literature to Enhance Students' Medical Humanities Literacy, Critical Thinking, and English Proficiency.

PubMed

Liao, Hung-Chang; Wang, Ya-Huei

2016-04-01

This study examined whether students studying literature in complementary learning clusters would show more improvement in medical humanities literacy, critical thinking skills, and English proficiency compared to those in conventional learning clusters. Ninety-three students participated in the study (M age = 18.2 years, SD = 0.4; 36 men, 57 women). A quasi-experimental design was used over 16 weeks, with the control group (n = 47) working in conventional learning clusters and the experimental group (n = 46) working in complementary learning clusters. Complementary learning clusters were those in which individuals had complementary strengths enabling them to learn from and offer assistance to other cluster members, hypothetically facilitating the learning process. Measures included the Medical Humanities Literacy Scale, Critical Thinking Disposition Assessment, English proficiency tests, and Analytic Critical Thinking Scoring Rubric. The results showed that complementary learning clusters have the potential to improve students' medical humanities literacy, critical thinking skills, and English proficiency. © The Author(s) 2016.

A smart checkpointing scheme for improving the reliability of clustering routing protocols.

PubMed

Min, Hong; Jung, Jinman; Kim, Bongjae; Cho, Yookun; Heo, Junyoung; Yi, Sangho; Hong, Jiman

2010-01-01

In wireless sensor networks, system architectures and applications are designed to consider both resource constraints and scalability, because such networks are composed of numerous sensor nodes with various sensors and actuators, small memories, low-power microprocessors, radio modules, and batteries. Clustering routing protocols based on data aggregation schemes aimed at minimizing packet numbers have been proposed to meet these requirements. In clustering routing protocols, the cluster head plays an important role. The cluster head collects data from its member nodes and aggregates the collected data. To improve reliability and reduce recovery latency, we propose a checkpointing scheme for the cluster head. In the proposed scheme, backup nodes monitor and checkpoint the current state of the cluster head periodically. We also derive the checkpointing interval that maximizes reliability while using the same amount of energy consumed by clustering routing protocols that operate without checkpointing. Experimental comparisons with existing non-checkpointing schemes show that our scheme reduces both energy consumption and recovery latency.

A Smart Checkpointing Scheme for Improving the Reliability of Clustering Routing Protocols

PubMed Central

Min, Hong; Jung, Jinman; Kim, Bongjae; Cho, Yookun; Heo, Junyoung; Yi, Sangho; Hong, Jiman

2010-01-01

In wireless sensor networks, system architectures and applications are designed to consider both resource constraints and scalability, because such networks are composed of numerous sensor nodes with various sensors and actuators, small memories, low-power microprocessors, radio modules, and batteries. Clustering routing protocols based on data aggregation schemes aimed at minimizing packet numbers have been proposed to meet these requirements. In clustering routing protocols, the cluster head plays an important role. The cluster head collects data from its member nodes and aggregates the collected data. To improve reliability and reduce recovery latency, we propose a checkpointing scheme for the cluster head. In the proposed scheme, backup nodes monitor and checkpoint the current state of the cluster head periodically. We also derive the checkpointing interval that maximizes reliability while using the same amount of energy consumed by clustering routing protocols that operate without checkpointing. Experimental comparisons with existing non-checkpointing schemes show that our scheme reduces both energy consumption and recovery latency. PMID:22163389

Identification of symptom and functional domains that fibromyalgia patients would like to see improved: a cluster analysis.

PubMed

Bennett, Robert M; Russell, Jon; Cappelleri, Joseph C; Bushmakin, Andrew G; Zlateva, Gergana; Sadosky, Alesia

2010-06-28

The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters. Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain > or =40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships. Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions). Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.

A legacy of divergent fishery management regimes and the resilience of rainbow and cutthroat trout populations in Lake Crescent, Olympic National Park, Washington

USGS Publications Warehouse

Brenkman, Samuel J.; Duda, Jeffrey J.; Kennedy, Philip R.; Baker, Bruce M.

2014-01-01

As a means to increase visitation, early fisheries management in the National Park Service (NPS) promoted sport harvest and hatchery supplementation. Today, NPS management objectives focus on the preservation of native fish. We summarized management regimes of Olympic National Park's Lake Crescent, which included decades of liberal sport harvest and hatchery releases of 14.3 million salmonids. Notably, nonnative species failed to persist in the lake. Complementary analyses of annual redd counts (1989–2012) and genetics data delineated three sympatric trout (one rainbow; two cutthroat) populations that exhibited distinct spatial and temporal spawning patterns, variable emergence timings, and genetic distinctiveness. Allacustrine rainbow trout spawned in the lake outlet from January to May. Cutthroat trout spawned in the major inlet tributary (Barnes Creek) from February to June and in the outlet river (Lyre) from September to March, an unusual timing for coastal cutthroat trout. Redd counts for each species were initially low (rainbow = mean 89; range 37–159; cutthroat = mean 93; range 18–180), and significantly increased for rainbow trout (mean 306; range 254–352) after implementation of catch-and-release regulations. Rainbow and cutthroat trout reached maximum sizes of 10.4 kg and 5.4 kg, respectively, and are among the largest throughout their native ranges. Morphometric analyses revealed interspecific differences but no intraspecific differences between the two cutthroat populations. Genetic analyses identified three distinct populations and low levels (9–17%) of interspecific hybridization. Lake Crescent rainbow trout were genetically divergent from 24 nearby Oncorhynchus mykiss populations, and represented a unique evolutionary legacy worthy of protection. The indigenous and geographically isolated Lake Crescent trout populations were resilient to overharvest and potential interactions with introduced fish species.

Mapping High Biomass Corridors for Climate and Biodiversity Co-Benefits

NASA Astrophysics Data System (ADS)

Jantz, P.; Goetz, S. J.; Laporte, N. T.

2013-12-01

A key issue in global conservation is how climate mitigation activities can secure biodiversity co-benefits. Tropical deforestation releases significant amounts of CO2 to the atmosphere and results in widespread biodiversity loss. The dominant strategy for forest conservation has been protected area designation. However, maintaining biodiversity in protected areas requires ecological exchange with ecosystems in which they are embedded. At current funding levels, existing conservation strategies are unlikely to prevent further loss of connectivity between protected areas and surrounding landscapes. The emergence of REDD+, a mechanism for funding carbon emissions reductions from deforestation in developing countries, suggests an alignment of goals and financial resources for protecting forest carbon, maintaining biodiversity in protected areas, and minimizing loss of forest ecosystem services. Identifying, protecting and sustainably managing vegetation carbon stocks between protected areas can provide both climate mitigation benefits through avoided CO2 emissions from deforestation and biodiversity benefits through the targeted protection of forests that maintain connectivity between protected areas and surrounding ecosystems. We used a high resolution, pan-tropical map of vegetation carbon stocks derived from MODIS, GLAS lidar and field measurements to map corridors that traverse areas of highest aboveground biomass between protected areas. We mapped over 13,000 corridors containing 49 GtC, accounting for 14% of unprotected vegetation carbon stock in the tropics. In the majority of cases, carbon density in corridors was commensurate with that of the protected areas they connect, suggesting significant opportunities for achieving climate mitigation and biodiversity co-benefits. To further illustrate the utility of this approach, we conducted a multi-criteria analysis of corridors in the Brazilian Amazon, identifying high biodiversity, high vegetation carbon stock corridors with low opportunity costs which may be good candidates for inclusion in climate mitigation activities like those being considered under REDD+.

Salmon Supplementation Studies in Idaho Rivers; Field Activities Conducted on Clear and Pete King Creeks, 2002 Annual Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bretz, Justin K.; Olson, Jill M.

2003-03-01

In 2002 the Idaho Fisheries Resource Office continued working as a cooperator on the Salmon Supplementation Studies in Idaho Rivers (ISS) project on Pete King and Clear creeks. Data relating to supplementation treatment releases, juvenile sampling, juvenile PIT tagging, broodstock spawning and rearing, spawning ground surveys, and snorkel surveys were used to evaluate the project data points and augment past data. Supplementation treatments included the release of 51,329 left ventral-clipped smolts into Clear Creek (750 were PIT tagged), and 12,000 unmarked coded-wire tagged parr into Pete King Creek (998 were PIT tagged). Using juvenile collection methods, Idaho Fisheries Resource Officemore » staff PIT tagged and released 579 naturally produced spring chinook juveniles in Clear Creek, and 54 on Pete King Creek, for minimum survival estimates to Lower Granite Dam. For Clear Creek, minimum survival estimates to Lower Granite Dam of hatchery produced supplementation and naturally produced PIT tagged smolts, were 36.0%, and 53.1%, respectively. For Pete King Creek, minimum survival estimates to Lower Granite Dam, of hatchery produced supplementation smolts and naturally produced smolts PIT tagged as parr and presmolts, were 18.8%, and 8.3%, respectively. Adults collected for broodstock in 2002 represented the final adult broodstock group collected for the ISS project. Twenty-six ventral clipped, and 28 natural adult spring chinook were transported above the weir. Monitoring and evaluation of spawning success was continued on Clear and Pete King creeks. A total of 69 redds were counted and 79 carcasses were recovered on Clear Creek. Two redds were observed and no carcasses were collected on Pete King Creek.« less

Mangrove and Freshwater Wetland Conservation Through Carbon Offsets: A Cost-Benefit Analysis for Establishing Environmental Policies

NASA Astrophysics Data System (ADS)

Vázquez-González, César; Moreno-Casasola, Patricia; Hernández, María Elizabeth; Campos, Adolfo; Espejel, Ileana; Fermán-Almada, José Luis

2017-02-01

Mexico has extensive coastal wetlands (4,243,137 ha), and one of its most important sites is the Alvarado Lagoon System, located in the Papaloapan River Basin on the Gulf of Mexico. The land cover dedicated to livestock and sugarcane has increased: by 25 % in 2005 and 50 % in 2010, with a loss of wetland vegetation and the carbon that it stores. We found that the Net Present Value of mangrove carbon offsets profit is equal to 5822.71, that of broad-leaved marshes is 7958.86, cattail marshes 5250.33, and forested wetlands 8369.41 per hectare, during a 30-year-carbonoffset contract. However, the opportunity cost from conserving wetland instead of growing sugarcane is positive according to REDD+ methodology, e.g., broad-leaved marsh conservation ranged from 6.73 to 20 USD/t CO2e, that of cattail marshes from 12.20 to 32.65 USD/t CO2e, and forested wetlands from 7.15 to 20.60 USD/t CO2e, whereas the opportunity cost between conservation and livestock was negative, it means that conservation is more profitable. The cost-benefit analysis for assessing investment projects from a governmental perspective is useful to determine the viability of conserving coastal wetlands through carbon offset credits. It also shows why in some areas it is not possible to conserve ecosystems due to the opportunity cost of changing from one economic activity (livestock and sugarcane) to carbon offsets for protecting wetlands. Furthermore, it allows for a comparison of carbon markets and assessment in terms of REDD+ and its methods for determining the social cost per ton of carbon avoided.

Using preoperative unsupervised cluster analysis of chronic rhinosinusitis to inform patient decision and endoscopic sinus surgery outcome.

PubMed

Adnane, Choaib; Adouly, Taoufik; Khallouk, Amine; Rouadi, Sami; Abada, Redallah; Roubal, Mohamed; Mahtar, Mohamed

2017-02-01

The purpose of this study is to use unsupervised cluster methodology to identify phenotype and mucosal eosinophilia endotype subgroups of patients with medical refractory chronic rhinosinusitis (CRS), and evaluate the difference in quality of life (QOL) outcomes after endoscopic sinus surgery (ESS) between these clusters for better surgical case selection. A prospective cohort study included 131 patients with medical refractory CRS who elected ESS. The Sino-Nasal Outcome Test (SNOT-22) was used to evaluate QOL before and 12 months after surgery. Unsupervised two-step clustering method was performed. One hundred and thirteen subjects were retained in this study: 46 patients with CRS without nasal polyps and 67 patients with nasal polyps. Nasal polyps, gender, mucosal eosinophilia profile, and prior sinus surgery were the most discriminating factors in the generated clusters. Three clusters were identified. A significant clinical improvement was observed in all clusters 12 months after surgery with a reduction of SNOT-22 scores. There was a significant difference in QOL outcomes between clusters; cluster 1 had the worst QOL improvement after FESS in comparison with the other clusters 2 and 3. All patients in cluster 1 presented CRSwNP with the highest mucosal eosinophilia endotype. Clustering method is able to classify CRS phenotypes and endotypes with different associated surgical outcomes.

Information Filtering via Clustering Coefficients of User-Object Bipartite Networks

NASA Astrophysics Data System (ADS)

Guo, Qiang; Leng, Rui; Shi, Kerui; Liu, Jian-Guo

The clustering coefficient of user-object bipartite networks is presented to evaluate the overlap percentage of neighbors rating lists, which could be used to measure interest correlations among neighbor sets. The collaborative filtering (CF) information filtering algorithm evaluates a given user's interests in terms of his/her friends' opinions, which has become one of the most successful technologies for recommender systems. In this paper, different from the object clustering coefficient, users' clustering coefficients of user-object bipartite networks are introduced to improve the user similarity measurement. Numerical results for MovieLens and Netflix data sets show that users' clustering effects could enhance the algorithm performance. For MovieLens data set, the algorithmic accuracy, measured by the average ranking score, can be improved by 12.0% and the diversity could be improved by 18.2% and reach 0.649 when the recommendation list equals to 50. For Netflix data set, the accuracy could be improved by 14.5% at the optimal case and the popularity could be reduced by 13.4% comparing with the standard CF algorithm. Finally, we investigate the sparsity effect on the performance. This work indicates the user clustering coefficients is an effective factor to measure the user similarity, meanwhile statistical properties of user-object bipartite networks should be investigated to estimate users' tastes.

Heterogeneous Clustering: Operational and User Impacts

NASA Technical Reports Server (NTRS)

Salm, Saita Wood

1999-01-01

Heterogeneous clustering can improve overall utilization of multiple hosts and can provide better turnaround to users by balancing workloads across hosts. Building a cluster requires both operational changes and revisions in user scripts.

When is Constrained Clustering Beneficial, and Why?

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Basu, Sugato; Davidson, Ian

2006-01-01

Several researchers have shown that constraints can improve the results of a variety of clustering algorithms. However, there can be a large variation in this improvement, even for a fixed number of constraints for a given data set. We present the first attempt to provide insight into this phenomenon by characterizing two constraint set properties: informativeness and coherence. We show that these measures can help explain why some constraint sets are more beneficial to clustering algorithms than others. Since they can be computed prior to clustering, these measures can aid in deciding which constraints to use in practice.

AN EMPIRICAL METHOD FOR IMPROVING THE QUALITY OF RXTE HEXTE SPECTRA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia, Javier A.; Steiner, James F.; McClintock, Jeffrey E.

2016-03-01

We have developed a correction tool to improve the quality of Rossi X-ray Timing Explorer (RXTE) High Energy X-ray Timing Experiment (HEXTE) spectra by employing the same method we used earlier to improve the quality of RXTE Proportional Counter Array (PCA) spectra. We fit all of the hundreds of HEXTE spectra of the Crab individually to a simple power-law model, some 37 million counts in total for Cluster A and 39 million counts for Cluster B, and we create for each cluster a combined spectrum of residuals. We find that the residual spectrum of Cluster A is free of instrumental artifacts while that of Clustermore » B contains significant features with amplitudes ∼1%; the most prominent is in the energy range 30–50 keV, which coincides with the iodine K edge. Starting with the residual spectrum for Cluster B, via an iterative procedure we created the calibration tool hexBcorr for correcting any Cluster B spectrum of interest. We demonstrate the efficacy of the tool by applying it to Cluster B spectra of two bright black holes, which contain several million counts apiece. For these spectra, application of the tool significantly improves the goodness of fit, while affecting only slightly the broadband fit parameters. The tool may be important for the study of spectral features, such as cyclotron lines, a topic that is beyond the scope of this paper.« less

Hybrid Tracking Algorithm Improvements and Cluster Analysis Methods.

DTIC Science & Technology

1982-02-26

UPGMA ), and Ward’s method. Ling’s papers describe a (k,r) clustering method. Each of these methods have individual characteristics which make them...Reference 7), UPGMA is probably the most frequently used clustering strategy. UPGMA tries to group new points into an existing cluster by using an

SAIL: Summation-bAsed Incremental Learning for Information-Theoretic Text Clustering.

PubMed

Cao, Jie; Wu, Zhiang; Wu, Junjie; Xiong, Hui

2013-04-01

Information-theoretic clustering aims to exploit information-theoretic measures as the clustering criteria. A common practice on this topic is the so-called Info-Kmeans, which performs K-means clustering with KL-divergence as the proximity function. While expert efforts on Info-Kmeans have shown promising results, a remaining challenge is to deal with high-dimensional sparse data such as text corpora. Indeed, it is possible that the centroids contain many zero-value features for high-dimensional text vectors, which leads to infinite KL-divergence values and creates a dilemma in assigning objects to centroids during the iteration process of Info-Kmeans. To meet this challenge, in this paper, we propose a Summation-bAsed Incremental Learning (SAIL) algorithm for Info-Kmeans clustering. Specifically, by using an equivalent objective function, SAIL replaces the computation of KL-divergence by the incremental computation of Shannon entropy. This can avoid the zero-feature dilemma caused by the use of KL-divergence. To improve the clustering quality, we further introduce the variable neighborhood search scheme and propose the V-SAIL algorithm, which is then accelerated by a multithreaded scheme in PV-SAIL. Our experimental results on various real-world text collections have shown that, with SAIL as a booster, the clustering performance of Info-Kmeans can be significantly improved. Also, V-SAIL and PV-SAIL indeed help improve the clustering quality at a lower cost of computation.

Operational multi-sensor design for forest carbon monitoring to support REDD+ in Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Braswell, B. H.; Hagen, S. C.; Harris, N.; Saatchi, S. S.

2013-12-01

Parties to the United Nations Framework Convention on Climate Change (UNFCCC) have been requested to establish robust and transparent national forest monitoring systems (NFMS) that use a combination of remote sensing and ground-based forest carbon inventory approaches to estimate anthropogenic forest-related greenhouse gas emissions and removals, reducing uncertainties as far as possible. A country's NFMS should also be used for data collection to inform the assessment of national or subnational forest reference emission levels and/or forest reference levels (RELs/RLs). In this way, the NFMS forms the link between historical assessments and current/future assessments, enabling consistency in the data and information to support the implementation of REDD+ activities in countries. The creation of a reliable, transparent, and comprehensive NFMS is currently limited by a dearth of relevant data that are accurate, low-cost, and spatially resolved at subnational scales. We are developing, evaluating, and validating several critical components of an NFMS in Kalimantan, Indonesia, focusing on the use of LiDAR and radar imagery for improved carbon stock and forest degradation information. Our goal is to evaluate sensor and platform tradeoffs systematically against in situ investments, as well as provide detailed tracking and characterization of uncertainty in a cost-benefit framework. Kalimantan is an ideal area to evaluate the use of remote sensing methods because measuring forest carbon stocks and their human caused changes with a high degree of certainty in areas of dense tropical forests has proven to be difficult. While the proposed NFMS components are being developed at the subnational scale for Kalimantan, we are targeting these methods for applicability across broader geographies and for implementation at various scales. Our intention is for this research to advance the state of the art of Measuring, Reporting, and Verification (MRV) system methodologies in ways that are both technical and operational. First, because a primary focus of carbon monitoring systems, especially in developing countries, is on cost-effectiveness, our analysis of optimal inputs of information from various satellite, airborne, and in situ measurements will provide practical information that countries can use to consider the tradeoffs. Second, because quantifying and understanding uncertainty is critical both in an Earth science research context and with regard to payment for ecosystem services, our development of reusable methods for tracking and evaluating uncertainty within a carbon monitoring system will provide a framework for stakeholders and researchers to understand and minimize errors across MRV components.

A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

PubMed Central

Liu, Jingxian; Wu, Kefeng

2017-01-01

The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with traditional spectral clustering and fast affinity propagation clustering. Experimental results have illustrated its superior performance in terms of quantitative and qualitative evaluations. PMID:28777353

Multi-Optimisation Consensus Clustering

NASA Astrophysics Data System (ADS)

Li, Jian; Swift, Stephen; Liu, Xiaohui

Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.

Label-free high-throughput detection and quantification of circulating melanoma tumor cell clusters by linear-array-based photoacoustic tomography

NASA Astrophysics Data System (ADS)

Hai, Pengfei; Zhou, Yong; Zhang, Ruiying; Ma, Jun; Li, Yang; Shao, Jin-Yu; Wang, Lihong V.

2017-04-01

Circulating tumor cell (CTC) clusters, arising from multicellular groupings in a primary tumor, greatly elevate the metastatic potential of cancer compared with single CTCs. High-throughput detection and quantification of CTC clusters are important for understanding the tumor metastatic process and improving cancer therapy. Here, we applied a linear-array-based photoacoustic tomography (LA-PAT) system and improved the image reconstruction for label-free high-throughput CTC cluster detection and quantification in vivo. The feasibility was first demonstrated by imaging CTC cluster ex vivo. The relationship between the contrast-to-noise ratios (CNRs) and the number of cells in melanoma tumor cell clusters was investigated and verified. Melanoma CTC clusters with a minimum of four cells could be detected, and the number of cells could be computed from the CNR. Finally, we demonstrated imaging of injected melanoma CTC clusters in rats in vivo. Similarly, the number of cells in the melanoma CTC clusters could be quantified. The data showed that larger CTC clusters had faster clearance rates in the bloodstream, which agreed with the literature. The results demonstrated the capability of LA-PAT to detect and quantify melanoma CTC clusters in vivo and showed its potential for tumor metastasis study and cancer therapy.

Effects of levomilnacipran ER on noradrenergic symptoms, anxiety symptoms, and functional impairment in adults with major depressive disorder: Post hoc analysis of 5 clinical trials.

PubMed

Blier, Pierre; Gommoll, Carl; Chen, Changzheng; Kramer, Kenneth

2017-03-01

To evaluate the effects of levomilnacipran extended-release (LVM-ER; 40-120mg/day) on noradrenergic (NA) and anxiety-related symptoms in adults with major depressive disorder (MDD) and explore the relationship between these symptoms and functional impairment. Data were pooled from 5 randomized, double-blind, placebo-controlled trials (N=2598). Anxiety and NA Cluster scores were developed by adding selected item scores from the Montgomery-Åsberg Depression Rating Scale (MADRS) and 17-item Hamilton Depression Rating Scale (HAMD 17 ). A path analysis was conducted to estimate the direct effects of LVM-ER on functional impairment (Sheehan Disability Scale [SDS] total score) and the indirect effects through changes in NA and Anxiety Cluster scores. Mean improvements from baseline in NA and Anxiety Cluster scores were significantly greater with LVM-ER versus placebo (both P<0.001), as were the response rates (≥50% score improvement): NA Cluster (44% vs 34%; odds ratio=1.56; P<0.0001); Anxiety Cluster (39% vs 36%; odds ratio=1.19; P=0.041). Mean improvement in SDS total score was also significantly greater with LVM-ER versus placebo (-7.3 vs -5.6; P<0.0001). LVM-ER had an indirect effect on change in SDS total score that was mediated more strongly through NA Cluster score change (86%) than Anxiety Cluster score change (18%); the direct effect was negligible. NA and Anxiety Cluster scores, developed based on the face validity of individual MADRS and HAMD 17 items, were not predefined as efficacy outcomes in any of the studies. In adults with MDD, LVM-ER indirectly improved functional impairment mainly through improvements in NA symptoms and less so via anxiety symptoms. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Development of a Conceptual Chum Salmon Emergence Model for Ives Island

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murray, Christopher J.; Geist, David R.; Arntzen, Evan V.

2011-02-09

The objective of the study described herein was to develop a conceptual model of chum salmon emergence that was based on empirical water temperature of the riverbed and river in specific locations where chum salmon spawn in the Ives Island area. The conceptual model was developed using water temperature data that have been collected in the past and are currently being collected in the Ives Island area. The model will be useful to system operators who need to estimate the complete distribution of chum salmon emergence (first emergence through final emergence) in order to balance chum salmon redd protection andmore » power system operation.« less

CASA Forest Cover Change Data Sets

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2012-01-01

Deforestation and forest fires are global land cover changes that can be caused by both natural and human factors. Although monitoring forest fires in near-real time is critical for operational wildfire management, mapping historical wildfires in a spatially explicit fashion is also important for a number of reasons, including climate change studies (e.g., examining the relationship between rising temperatures and frequency of fires), fuel load management (e.g., deciding when and where to conduct controlled burns), and carbon cycle studies (e.g., quantifying how much CO2 is emitted by fires and for emissions reduction efforts under the United Nations programs for Reducing Emissions from Deforestation and Degradation -- REDD).

Effects of Dexamethasone and Placebo on Symptom Clusters in Advanced Cancer Patients: A Preliminary Report.

PubMed

Yennurajalingam, Sriram; Williams, Janet L; Chisholm, Gary; Bruera, Eduardo

2016-03-01

Advanced cancer patients frequently experience debilitating symptoms that occur in clusters, but few pharmacological studies have targeted symptom clusters. Our objective was to examine the effects of dexamethasone on symptom clusters in patients with advanced cancer. We reviewed the data from a previous randomized clinical trial to determine the effects of dexamethasone on cancer symptoms. Symptom clusters were identified according to baseline symptoms by using principal component analysis. Correlations and change in the severity of symptom clusters were analyzed after study treatment. A total of 114 participants were included in this study. Three clusters were identified: fatigue/anorexia-cachexia/depression (FAD), sleep/anxiety/drowsiness (SAD), and pain/dyspnea (PD). Changes in severity of FAD and PD significantly correlated over time (at baseline, day 8, and day 15). The FAD cluster was associated with significant improvement in severity at day 8 and day 15, whereas no significant change was observed with the SAD cluster or PD cluster after dexamethasone treatment. The results of this preliminary study suggest significant correlation over time and improvement in the FAD cluster at day 8 and day 15 after treatment with dexamethasone. These findings suggest that fatigue, anorexia-cachexia, and depression may share a common pathophysiologic basis. Further studies are needed to investigate this cluster and target anti-inflammatory therapies. ©AlphaMed Press.

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

Generalized fuzzy C-means clustering algorithm with improved fuzzy partitions.

PubMed

Zhu, Lin; Chung, Fu-Lai; Wang, Shitong

2009-06-01

The fuzziness index m has important influence on the clustering result of fuzzy clustering algorithms, and it should not be forced to fix at the usual value m = 2. In view of its distinctive features in applications and its limitation in having m = 2 only, a recent advance of fuzzy clustering called fuzzy c-means clustering with improved fuzzy partitions (IFP-FCM) is extended in this paper, and a generalized algorithm called GIFP-FCM for more effective clustering is proposed. By introducing a novel membership constraint function, a new objective function is constructed, and furthermore, GIFP-FCM clustering is derived. Meanwhile, from the viewpoints of L(p) norm distance measure and competitive learning, the robustness and convergence of the proposed algorithm are analyzed. Furthermore, the classical fuzzy c-means algorithm (FCM) and IFP-FCM can be taken as two special cases of the proposed algorithm. Several experimental results including its application to noisy image texture segmentation are presented to demonstrate its average advantage over FCM and IFP-FCM in both clustering and robustness capabilities.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

NASA Astrophysics Data System (ADS)

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-04-01

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra.

PubMed

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-03-13

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models' performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Flow-Mediated Stem Cell Labeling with Superparamagnetic Iron Oxide Nanoparticle Clusters

PubMed Central

Shkumatov, Artem; Lai, Mei-Hsiu; Smith, Cartney E.; Rich, Max; Kong, Hyunjoon

2013-01-01

This study presents a strategy to enhance the uptake of superparamagnetic iron oxide nanoparticle (SPIO) clusters by manipulating the cellular mechanical environment. Specifically, stem cells exposed to an orbital flow ingested almost two-fold greater amount of SPIO clusters than those cultured statically. Improvements in MR contrast were subsequently achieved for labeled cells in collagen gels and a mouse model. Overall, this strategy will serve to improve the efficiency of cell tracking and therapies. PMID:24033276

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure.

PubMed

Zhang, Wen; Xiao, Fan; Li, Bin; Zhang, Siguang

2016-01-01

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods.

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure

PubMed Central

Xiao, Fan; Li, Bin; Zhang, Siguang

2016-01-01

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods. PMID:27579031

Cancer Cluster Investigations: Review of the Past and Proposals for the Future

PubMed Central

Goodman, Michael; LaKind, Judy S.; Fagliano, Jerald A.; Lash, Timothy L.; Wiemels, Joseph L.; Winn, Deborah M.; Patel, Chirag; Van Eenwyk, Juliet; Kohler, Betsy A.; Schisterman, Enrique F.; Albert, Paul; Mattison, Donald R.

2014-01-01

Residential clusters of non-communicable diseases are a source of enduring public concern, and at times, controversy. Many clusters reported to public health agencies by concerned citizens are accompanied by expectations that investigations will uncover a cause of disease. While goals, methods and conclusions of cluster studies are debated in the scientific literature and popular press, investigations of reported residential clusters rarely provide definitive answers about disease etiology. Further, it is inherently difficult to study a cluster for diseases with complex etiology and long latency (e.g., most cancers). Regardless, cluster investigations remain an important function of local, state and federal public health agencies. Challenges limiting the ability of cluster investigations to uncover causes for disease include the need to consider long latency, low statistical power of most analyses, uncertain definitions of cluster boundaries and population of interest, and in- and out-migration. A multi-disciplinary Workshop was held to discuss innovative and/or under-explored approaches to investigate cancer clusters. Several potentially fruitful paths forward are described, including modern methods of reconstructing residential history, improved approaches to analyzing spatial data, improved utilization of electronic data sources, advances using biomarkers of carcinogenesis, novel concepts for grouping cases, investigations of infectious etiology of cancer, and “omics” approaches. PMID:24477211

Prediction, Detection, and Validation of Isotope Clusters in Mass Spectrometry Data

PubMed Central

Treutler, Hendrik; Neumann, Steffen

2016-01-01

Mass spectrometry is a key analytical platform for metabolomics. The precise quantification and identification of small molecules is a prerequisite for elucidating the metabolism and the detection, validation, and evaluation of isotope clusters in LC-MS data is important for this task. Here, we present an approach for the improved detection of isotope clusters using chemical prior knowledge and the validation of detected isotope clusters depending on the substance mass using database statistics. We find remarkable improvements regarding the number of detected isotope clusters and are able to predict the correct molecular formula in the top three ranks in 92% of the cases. We make our methodology freely available as part of the Bioconductor packages xcms version 1.50.0 and CAMERA version 1.30.0. PMID:27775610

Digital Signal Processing Based on a Clustering Algorithm for Ir/Au TES Microcalorimeter

NASA Astrophysics Data System (ADS)

Zen, N.; Kunieda, Y.; Takahashi, H.; Hiramoto, K.; Nakazawa, M.; Fukuda, D.; Ukibe, M.; Ohkubo, M.

2006-02-01

In recent years, cryogenic microcalorimeters using their superconducting transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy resolution of superconducting transition edge sensors (TES), several correction methods have been developed. Among them, a clustering method based on digital signal processing has recently been proposed. In this paper, we applied the clustering method to Ir/Au bilayer TES. This method resulted in almost a 10% improvement in the energy resolution. Conversely, from the point of view of imaging X-ray spectroscopy, we applied the clustering method to pixellated Ir/Au-TES devices. We will thus show how a clustering method which sorts signals by their shapes is also useful for position identification

Dual organism design cycle reveals small subunit substitutions that improve [NiFe] hydrogenase hydrogen evolution.

PubMed

Yonemoto, Isaac T; Matteri, Christopher W; Nguyen, Thao Amy; Smith, Hamilton O; Weyman, Philip D

2013-07-02

Photosynthetic microorganisms that directly channel solar energy to the production of molecular hydrogen are a potential future biofuel system. Building such a system requires installation of a hydrogenase in the photosynthetic organism that is both tolerant to oxygen and capable of hydrogen production. Toward this end, we have identified the [NiFe] hydrogenase from the marine bacterium Alteromonas macleodii "Deep ecotype" that is able to be heterologously expressed in cyanobacteria and has tolerance to partial oxygen. The A. macleodii enzyme shares sequence similarity with the uptake hydrogenases that favor hydrogen uptake activity over hydrogen evolution. To improve hydrogen evolution from the A. macleodii hydrogenase, we examined the three Fe-S clusters found in the small subunit of many [NiFe] uptake hydrogenases that presumably act as a molecular wire to guide electrons to or from the active site of the enzyme. Studies by others altering the medial cluster of a Desulfovibrio fructosovorans hydrogenase from 3Fe-4S to 4Fe-4S resulted in two-fold improved hydrogen evolution activity. We adopted a strategy of screening for improved hydrogenase constructs using an Escherichia coli expression system before testing in slower growing cyanobacteria. From the A. macleodii enzyme, we created a mutation in the gene encoding the hydrogenase small subunit that in other systems is known to convert the 3Fe-4S medial cluster to 4Fe-4S. The medial cluster substitution did not improve the hydrogen evolution activity of our hydrogenase. However, modifying both the medial cluster and the ligation of the distal Fe-S cluster improved in vitro hydrogen evolution activity relative to the wild type hydrogenase by three- to four-fold. Other properties of the enzyme including thermostability and tolerance to partial oxygen did not appear to be affected by the substitutions. Our results show that substitution of amino acids altering the ligation of Fe-S clusters in the A. macleodii [NiFe] uptake hydrogenase resulted in increased hydrogen evolution activity. This activity can be recapitulated in multiple host systems and with purified protein. These results validate the approach of using an E. coli-cyanobacteria shuttle system for enzyme expression and improvement.

Cluster Analysis of Vulnerable Groups in Acute Traumatic Brain Injury Rehabilitation.

PubMed

Kucukboyaci, N Erkut; Long, Coralynn; Smith, Michelle; Rath, Joseph F; Bushnik, Tamara

2018-01-06

To analyze the complex relation between various social indicators that contribute to socioeconomic status and health care barriers. Cluster analysis of historical patient data obtained from inpatient visits. Inpatient rehabilitation unit in a large urban university hospital. Adult patients (N=148) receiving acute inpatient care, predominantly for closed head injury. Not applicable. We examined the membership of patients with traumatic brain injury in various "vulnerable group" clusters (eg, homeless, unemployed, racial/ethnic minority) and characterized the rehabilitation outcomes of patients (eg, duration of stay, changes in FIM scores between admission to inpatient stay and discharge). The cluster analysis revealed 4 major clusters (ie, clusters A-D) separated by vulnerable group memberships, with distinct durations of stay and FIM gains during their stay. Cluster B, the largest cluster and also consisting of mostly racial/ethnic minorities, had the shortest duration of hospital stay and one of the lowest FIM improvements among the 4 clusters despite higher FIM scores at admission. In cluster C, also consisting of mostly ethnic minorities with multiple socioeconomic status vulnerabilities, patients were characterized by low cognitive FIM scores at admission and the longest duration of stay, and they showed good improvement in FIM scores. Application of clustering techniques to inpatient data identified distinct clusters of patients who may experience differences in their rehabilitation outcome due to their membership in various "at-risk" groups. The results identified patients (ie, cluster B, with minority patients; and cluster D, with elderly patients) who attain below-average gains in brain injury rehabilitation. The results also suggested that systemic (eg, duration of stay) or clinical service improvements (eg, staff's language skills, ability to offer substance abuse therapy, provide appropriate referrals, liaise with intensive social work services, or plan subacute rehabilitation phase) could be beneficial for acute settings. Stronger recruitment, training, and retention initiatives for bilingual and multiethnic professionals may also be considered to optimize gains from acute inpatient rehabilitation after traumatic brain injury. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Improved efficiency in amplification of Escherichia coli o-antigen gene clusters using genome-wide sequence comparison

USDA-ARS?s Scientific Manuscript database

Background: In many bacteria including E. coli, genes encoding O-antigens are clustered in the chromosome, with a 39-bp JUMPstart sequence and gnd gene located upstream and downstream of the cluster, respectively. For determining the DNA sequence of the E. coli O-antigen gene cluster, one set of P...

Improved Gravitation Field Algorithm and Its Application in Hierarchical Clustering

PubMed Central

Zheng, Ming; Sun, Ying; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

2012-01-01

Background Gravitation field algorithm (GFA) is a new optimization algorithm which is based on an imitation of natural phenomena. GFA can do well both for searching global minimum and multi-minima in computational biology. But GFA needs to be improved for increasing efficiency, and modified for applying to some discrete data problems in system biology. Method An improved GFA called IGFA was proposed in this paper. Two parts were improved in IGFA. The first one is the rule of random division, which is a reasonable strategy and makes running time shorter. The other one is rotation factor, which can improve the accuracy of IGFA. And to apply IGFA to the hierarchical clustering, the initial part and the movement operator were modified. Results Two kinds of experiments were used to test IGFA. And IGFA was applied to hierarchical clustering. The global minimum experiment was used with IGFA, GFA, GA (genetic algorithm) and SA (simulated annealing). Multi-minima experiment was used with IGFA and GFA. The two experiments results were compared with each other and proved the efficiency of IGFA. IGFA is better than GFA both in accuracy and running time. For the hierarchical clustering, IGFA is used to optimize the smallest distance of genes pairs, and the results were compared with GA and SA, singular-linkage clustering, UPGMA. The efficiency of IGFA is proved. PMID:23173043

Optimization of wireless sensor networks based on chicken swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Wang, Qingxi; Zhu, Lihua

2017-05-01

In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.

A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

PubMed

Mascaro, Joseph; Asner, Gregory P; Knapp, David E; Kennedy-Bowdoin, Ty; Martin, Roberta E; Anderson, Christopher; Higgins, Mark; Chadwick, K Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

A Tale of Two “Forests”: Random Forest Machine Learning Aids Tropical Forest Carbon Mapping

PubMed Central

Mascaro, Joseph; Asner, Gregory P.; Knapp, David E.; Kennedy-Bowdoin, Ty; Martin, Roberta E.; Anderson, Christopher; Higgins, Mark; Chadwick, K. Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including—in the latter case—x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called “out-of-bag”), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha−1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation. PMID:24489686

An adaptive clustering algorithm for image matching based on corner feature

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-04-01

The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.

A high-significance measurement of correlation between unresolved IRAS sources and optically-selected galaxy clusters

NASA Astrophysics Data System (ADS)

Hincks, Adam D.; Hajian, Amir; Addison, Graeme E.

2013-05-01

We cross-correlate the 100 μm Improved Reprocessing of the IRAS Survey (IRIS) map and galaxy clusters at 0.1 < z < 0.3 in the maxBCG catalogue taken from the Sloan Digital Sky Survey, measuring an angular cross-power spectrum over multipole moments 150 < l < 3000 at a total significance of over 40σ. The cross-spectrum, which arises from the spatial correlation between unresolved dusty galaxies that make up the cosmic infrared background (CIB) in the IRIS map and the galaxy clusters, is well-fit by a single power law with an index of -1.28±0.12, similar to the clustering of unresolved galaxies from cross-correlating far-infrared and submillimetre maps at longer wavelengths. Using a recent, phenomenological model for the spectral and clustering properties of the IRIS galaxies, we constrain the large-scale bias of the maxBCG clusters to be 2.6±1.4, consistent with existing analyses of the real-space cluster correlation function. The success of our method suggests that future CIB-optical cross-correlations using Planck and Herschel data will significantly improve our understanding of the clustering and redshift distribution of the faint CIB sources.

Synchronous Firefly Algorithm for Cluster Head Selection in WSN.

PubMed

Baskaran, Madhusudhanan; Sadagopan, Chitra

2015-01-01

Wireless Sensor Network (WSN) consists of small low-cost, low-power multifunctional nodes interconnected to efficiently aggregate and transmit data to sink. Cluster-based approaches use some nodes as Cluster Heads (CHs) and organize WSNs efficiently for aggregation of data and energy saving. A CH conveys information gathered by cluster nodes and aggregates/compresses data before transmitting it to a sink. However, this additional responsibility of the node results in a higher energy drain leading to uneven network degradation. Low Energy Adaptive Clustering Hierarchy (LEACH) offsets this by probabilistically rotating cluster heads role among nodes with energy above a set threshold. CH selection in WSN is NP-Hard as optimal data aggregation with efficient energy savings cannot be solved in polynomial time. In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. Extensive simulation shows the proposed technique to perform well compared to LEACH and energy-efficient hierarchical clustering. Simulations show the effectiveness of the proposed method in decreasing the packet loss ratio by an average of 9.63% and improving the energy efficiency of the network when compared to LEACH and EEHC.

Obstructive Sleep Apnea: A Cluster Analysis at Time of Diagnosis

PubMed Central

Grillet, Yves; Richard, Philippe; Stach, Bruno; Vivodtzev, Isabelle; Timsit, Jean-Francois; Lévy, Patrick; Tamisier, Renaud; Pépin, Jean-Louis

2016-01-01

Background The classification of obstructive sleep apnea is on the basis of sleep study criteria that may not adequately capture disease heterogeneity. Improved phenotyping may improve prognosis prediction and help select therapeutic strategies. Objectives: This study used cluster analysis to investigate the clinical clusters of obstructive sleep apnea. Methods An ascending hierarchical cluster analysis was performed on baseline symptoms, physical examination, risk factor exposure and co-morbidities from 18,263 participants in the OSFP (French national registry of sleep apnea). The probability for criteria to be associated with a given cluster was assessed using odds ratios, determined by univariate logistic regression. Results: Six clusters were identified, in which patients varied considerably in age, sex, symptoms, obesity, co-morbidities and environmental risk factors. The main significant differences between clusters were minimally symptomatic versus sleepy obstructive sleep apnea patients, lean versus obese, and among obese patients different combinations of co-morbidities and environmental risk factors. Conclusions Our cluster analysis identified six distinct clusters of obstructive sleep apnea. Our findings underscore the high degree of heterogeneity that exists within obstructive sleep apnea patients regarding clinical presentation, risk factors and consequences. This may help in both research and clinical practice for validating new prevention programs, in diagnosis and in decisions regarding therapeutic strategies. PMID:27314230

Treatment of intractable chronic cluster headache by occipital nerve stimulation: a cohort of 51 patients.

PubMed

Miller, S; Watkins, L; Matharu, M

2017-02-01

Chronic cluster headache is a rare, highly disabling primary headache condition. When medically intractable, occipital nerve stimulation can offer effective treatment. Open-label series have provided data on small cohorts only. We analyzed 51 subjects to evaluate the long-term outcomes of highly intractable chronic cluster headache with occipital nerve stimulation. Patients with intractable chronic cluster headache were implanted with occipital nerve stimulators during the period 2007-2014. The primary endpoint was improvement in daily attack frequency. Secondary endpoints included attack severity, attack duration, quality-of-life measures, headache disability scores and adverse events. We studied 51 patients [35 males; mean age at implant 47.78 (range 31-70) years; mean follow-up 39.17 (range 2-81) months]. Nineteen patients had other chronic headache types in addition in chronic cluster headache. At final follow-up, there was a 46.1% improvement in attack frequency (P < 0001) across all patients, 49.5% (P < 0.001) in those with cluster headache alone and 40.3% (P = 0.036) in those with multiple phenotypes. There were no significant differences in response in those with or without multiple headache types. The overall response rate (defined as at least a 50% improvement in attack frequency) was 52.9%. Significant reductions were also seen in attack duration and severity. Improvements were noted in headache disability scores and quality-of-life measures. Triptan use of responders dropped by 62.56%, resulting in significant cost savings. Adverse event rates were highly favorable. Occipital nerve stimulation appears to be a safe and efficacious treatment for highly intractable chronic cluster headache even after a mean follow-up of over 3 years. © 2016 EAN.

Effects of cluster vs. traditional plyometric training sets on maximal-intensity exercise performance.

PubMed

Asadi, Abbas; Ramírez-Campillo, Rodrigo

2016-01-01

The aim of this study was to compare the effects of 6-week cluster versus traditional plyometric training sets on jumping ability, sprint and agility performance. Thirteen college students were assigned to a cluster sets group (N=6) or traditional sets group (N=7). Both training groups completed the same training program. The traditional group completed five sets of 20 repetitions with 2min of rest between sets each session, while the cluster group completed five sets of 20 [2×10] repetitions with 30/90-s rest each session. Subjects were evaluated for countermovement jump (CMJ), standing long jump (SLJ), t test, 20-m and 40-m sprint test performance before and after the intervention. Both groups had similar improvements (P<0.05) in CMJ, SLJ, t test, 20-m, and 40-m sprint. However, the magnitude of improvement in CMJ, SLJ and t test was greater for the cluster group (effect size [ES]=1.24, 0.81 and 1.38, respectively) compared to the traditional group (ES=0.84, 0.60 and 0.55). Conversely, the magnitude of improvement in 20-m and 40-m sprint test was greater for the traditional group (ES=1.59 and 0.96, respectively) compared to the cluster group (ES=0.94 and 0.75, respectively). Although both plyometric training methods improved lower body maximal-intensity exercise performance, the traditional sets methods resulted in greater adaptations in sprint performance, while the cluster sets method resulted in greater jump and agility adaptations. Copyright © 2016 The Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

A nationwide hospital survey on patient safety culture in Belgian hospitals: setting priorities at the launch of a 5-year patient safety plan.

PubMed

Vlayen, Annemie; Hellings, Johan; Claes, Neree; Peleman, Hilde; Schrooten, Ward

2012-09-01

To measure patient safety culture in Belgian hospitals and to examine the homogeneous grouping of underlying safety culture dimensions. The Hospital Survey on Patient Safety Culture was distributed organisation-wide in 180 Belgian hospitals participating in the federal program on quality and safety between 2007 and 2009. Participating hospitals were invited to submit their data to a comparative database. Homogeneous groups of underlying safety culture dimensions were sought by hierarchical cluster analysis. 90 acute, 42 psychiatric and 11 long-term care hospitals submitted their data for comparison to other hospitals. The benchmark database included 55 225 completed questionnaires (53.7% response rate). Overall dimensional scores were low, although scores were found to be higher for psychiatric and long-term care hospitals than for acute hospitals. The overall perception of patient safety was lower in French-speaking hospitals. Hierarchical clustering of dimensions resulted in two distinct clusters. Cluster I grouped supervisor/manager expectations and actions promoting safety, organisational learning-continuous improvement, teamwork within units and communication openness, while Cluster II included feedback and communication about error, overall perceptions of patient safety, non-punitive response to error, frequency of events reported, teamwork across units, handoffs and transitions, staffing and management support for patient safety. The nationwide safety culture assessment confirms the need for a long-term national initiative to improve patient safety culture and provides each hospital with a baseline patient safety culture profile to direct an intervention plan. The identification of clusters of safety culture dimensions indicates the need for a different approach and context towards the implementation of interventions aimed at improving the safety culture. Certain clusters require unit level improvements, whereas others demand a hospital-wide policy.

Hydrogen evolution reaction catalyst

DOEpatents

Subbaraman, Ram; Stamenkovic, Vojislav; Markovic, Nenad; Tripkovic, Dusan

2016-02-09

Systems and methods for a hydrogen evolution reaction catalyst are provided. Electrode material includes a plurality of clusters. The electrode exhibits bifunctionality with respect to the hydrogen evolution reaction. The electrode with clusters exhibits improved performance with respect to the intrinsic material of the electrode absent the clusters.

Onto-clust--a methodology for combining clustering analysis and ontological methods for identifying groups of comorbidities for developmental disorders.

PubMed

Peleg, Mor; Asbeh, Nuaman; Kuflik, Tsvi; Schertz, Mitchell

2009-02-01

Children with developmental disorders usually exhibit multiple developmental problems (comorbidities). Hence, such diagnosis needs to revolve on developmental disorder groups. Our objective is to systematically identify developmental disorder groups and represent them in an ontology. We developed a methodology that combines two methods (1) a literature-based ontology that we created, which represents developmental disorders and potential developmental disorder groups, and (2) clustering for detecting comorbid developmental disorders in patient data. The ontology is used to interpret and improve clustering results and the clustering results are used to validate the ontology and suggest directions for its development. We evaluated our methodology by applying it to data of 1175 patients from a child development clinic. We demonstrated that the ontology improves clustering results, bringing them closer to an expert generated gold-standard. We have shown that our methodology successfully combines an ontology with a clustering method to support systematic identification and representation of developmental disorder groups.

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms.

PubMed

Sammond, Deanne W; Kastelowitz, Noah; Himmel, Michael E; Yin, Hang; Crowley, Michael F; Bomble, Yannick J

2016-01-01

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms

PubMed Central

Sammond, Deanne W.; Kastelowitz, Noah; Himmel, Michael E.; Yin, Hang; Crowley, Michael F.; Bomble, Yannick J.

2016-01-01

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions. PMID:26741367

Superframe Duration Allocation Schemes to Improve the Throughput of Cluster-Tree Wireless Sensor Networks

PubMed Central

Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco

2017-01-01

The use of Wireless Sensor Network (WSN) technologies is an attractive option to support wide-scale monitoring applications, such as the ones that can be found in precision agriculture, environmental monitoring and industrial automation. The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable topology to build wide-scale WSNs. Despite some of its known advantages, including timing synchronisation and duty-cycle operation, cluster-tree networks may suffer from severe network congestion problems due to the convergecast pattern of its communication traffic. Therefore, the careful adjustment of transmission opportunities (superframe durations) allocated to the cluster-heads is an important research issue. This paper proposes a set of proportional Superframe Duration Allocation (SDA) schemes, based on well-defined protocol and timing models, and on the message load imposed by child nodes (Load-SDA scheme), or by number of descendant nodes (Nodes-SDA scheme) of each cluster-head. The underlying reasoning is to adequately allocate transmission opportunities (superframe durations) and parametrize buffer sizes, in order to improve the network throughput and avoid typical problems, such as: network congestion, high end-to-end communication delays and discarded messages due to buffer overflows. Simulation assessments show how proposed allocation schemes may clearly improve the operation of wide-scale cluster-tree networks. PMID:28134822

Elucidation of the Pattern of the Onset of Male Lower Urinary Tract Symptoms Using Cluster Analysis: Efficacy of Tamsulosin in Each Symptom Group.

PubMed

Aikawa, Ken; Kataoka, Masao; Ogawa, Soichiro; Akaihata, Hidenori; Sato, Yuichi; Yabe, Michihiro; Hata, Junya; Koguchi, Tomoyuki; Kojima, Yoshiyuki; Shiragasawa, Chihaya; Kobayashi, Toshimitsu; Yamaguchi, Osamu

2015-08-01

To present a new grouping of male patients with lower urinary tract symptoms (LUTS) based on symptom patterns and clarify whether the therapeutic effect of α1-blocker differs among the groups. We performed secondary analysis of anonymous data from 4815 patients enrolled in a postmarketing surveillance study of tamsulosin in Japan. Data on 7 International Prostate Symptom Score (IPSS) items at the initial visit were used in the cluster analysis. IPSS and quality of life (QOL) scores before and after tamsulosin treatment for 12 weeks were assessed in each cluster. Partial correlation coefficients were also obtained for IPSS and QOL scores based on changes before and after treatment. Five symptom groups were identified by cluster analysis of IPSS. On their symptom profile, each cluster was labeled as minimal type (cluster 1), multiple severe type (cluster 2), weak stream type (cluster 3), storage type (cluster 4), and voiding type (cluster 5). Prevalence and the mean symptom score were significantly improved in almost all symptoms in all clusters by tamsulosin treatment. Nocturia and weak stream had the strongest effect on QOL in clusters 1, 2, and 4 and clusters 3 and 5, respectively. The study clarified that 5 characteristic symptom patterns exist by cluster analysis of IPSS in male patients with LUTS. Tamsulosin improved various symptoms and QOL in each symptom group. The study reports many male patients with LUTS being satisfied with monotherapy using tamsulosin and suggests the usefulness of α1-blockers as a drug of first choice. Copyright © 2015 Elsevier Inc. All rights reserved.

Genetic diversity analysis of Gossypium arboreum germplasm accessions using genotyping-by-sequencing.

PubMed

Li, Ruijuan; Erpelding, John E

2016-10-01

The diploid cotton species Gossypium arboreum possesses many favorable agronomic traits such as drought tolerance and disease resistance, which can be utilized in the development of improved upland cotton cultivars. The USDA National Plant Germplasm System maintains more than 1600 G. arboreum accessions. Little information is available on the genetic diversity of the collection thereby limiting the utilization of this cotton species. The genetic diversity and population structure of the G. arboreum germplasm collection were assessed by genotyping-by-sequencing of 375 accessions. Using genome-wide single nucleotide polymorphism sequence data, two major clusters were inferred with 302 accessions in Cluster 1, 64 accessions in Cluster 2, and nine accessions unassigned due to their nearly equal membership to each cluster. These two clusters were further evaluated independently resulting in the identification of two sub-clusters for the 302 Cluster 1 accessions and three sub-clusters for the 64 Cluster 2 accessions. Low to moderate genetic diversity between clusters and sub-clusters were observed indicating a narrow genetic base. Cluster 2 accessions were more genetically diverse and the majority of the accessions in this cluster were landraces. In contrast, Cluster 1 is composed of varieties or breeding lines more recently added to the collection. The majority of the accessions had kinship values ranging from 0.6 to 0.8. Eight pairs of accessions were identified as potential redundancies due to their high kinship relatedness. The genetic diversity and genotype data from this study are essential to enhance germplasm utilization to identify genetically diverse accessions for the detection of quantitative trait loci associated with important traits that would benefit upland cotton improvement.

E-learning or educational leaflet: does it make a difference in oral health promotion? A clustered randomized trial.

PubMed

Al Bardaweel, Susan; Dashash, Mayssoon

2018-05-10

The early recognition of technology together with great ability to use computers and smart systems have promoted researchers to investigate the possibilities of utilizing technology for improving health care in children. The aim of this study was to compare between the traditional educational leaflets and E-applications in improving oral health knowledge, oral hygiene and gingival health in schoolchildren of Damascus city, Syria. A clustered randomized controlled trial at two public primary schools was performed. About 220 schoolchildren aged 10-11 years were included in this study and grouped into two clusters. Children in Leaflet cluster received oral health education through leaflets, while children in E-learning cluster received oral health education through an E-learning program. A questionnaire was designed to register information related to oral health knowledge and to record Plaque and Gingival indices. Questionnaire administration and clinical assessment were undertaken at baseline, 6 and at 12 weeks of oral health education. Data was analysed using one way repeated measures ANOVA, post hoc Bonferroni test and independent samples t-test. Leaflet cluster (107 participants) had statistically significant better oral health knowledge than E-learning cluster (104 participants) at 6 weeks (P < 0.05) and at 12 weeks (P < 0.05) (Leaflet cluster:100 participants, E-learning cluster:100 participants). The mean knowledge gain compared to baseline was higher in Leaflet cluster than in E-learning cluster. A significant reduction in the PI means at 6 weeks and 12 weeks was observed in both clusters (P < 0.05) when compared to baseline. Children in Leaflet cluster had significantly less plaque than those in E-learning cluster at 6 weeks (P < 0.05) and at 12 weeks (P < 0.05). Similarly, a significant reduction in the GI means at 6 weeks and 12 weeks was observed in both clusters when compared to baseline (P < 0.05). Children in Leaflet cluster had statistically significant better gingival health than E-learning cluster at 6 weeks (P < 0.05) and 12 weeks (P < 0.05). Traditional educational leaflets are an effective tool in the improvement of both oral health knowledge as well as clinical indices of oral hygiene and care among Syrian children. Leaflets can be used in school-based oral health education for a positive outcome. Australian New Zealand Clinical Trials Registry ( ACTRN12618000395235 ), Date registered: 16/03/2018, retrospectively registered.

Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?

PubMed

Kent, Peter; Stochkendahl, Mette Jensen; Christensen, Henrik Wulff; Kongsted, Alice

2015-01-01

Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role participation, psychological factors, biomarkers and imaging. However, such 'whole person' research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may improve the clinical interpretability of derived subgroups and reduce sample size requirements. This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it.

Grassland management regimens reduce small-scale heterogeneity and species diversity of beta-proteobacterial ammonia pxidizer populations.

PubMed

Webster, Gordon; Embley, T Martin; Prosser, James I

2002-01-01

The impact of soil management practices on ammonia oxidizer diversity and spatial heterogeneity was determined in improved (addition of N fertilizer), unimproved (no additions), and semi-improved (intermediate management) grassland pastures at the Sourhope Research Station in Scotland. Ammonia oxidizer diversity within each grassland soil was assessed by PCR amplification of microbial community DNA with both ammonia oxidizer-specific, 16S rRNA gene (rDNA) and functional, amoA, gene primers. PCR products were analysed by denaturing gradient gel electrophoresis, phylogenetic analysis of partial 16S rDNA and amoA sequences, and hybridization with ammonia oxidizer-specific oligonucleotide probes. Ammonia oxidizer populations in unimproved soils were more diverse than those in improved soils and were dominated by organisms representing Nitrosospira clusters 1 and 3 and Nitrosomonas cluster 7 (closely related phylogenetically to Nitrosomonas europaea). Improved soils were only dominated by Nitrosospira cluster 3 and Nitrosomonas cluster 7. These differences were also reflected in functional gene (amoA) diversity, with amoA gene sequences of both Nitrosomonas and Nitrosospira species detected. Replicate 0.5-g samples of unimproved soil demonstrated significant spatial heterogeneity in 16S rDNA-defined ammonia oxidizer clusters, which was reflected in heterogeneity in ammonium concentration and pH. Heterogeneity in soil characteristics and ammonia oxidizer diversity were lower in improved soils. The results therefore demonstrate significant effects of soil management on diversity and heterogeneity of ammonia oxidizer populations that are related to similar changes in relevant soil characteristics.

Applying the conservativeness principle to REDD to deal with the uncertainties of the estimates

NASA Astrophysics Data System (ADS)

Grassi, Giacomo; Monni, Suvi; Federici, Sandro; Achard, Frederic; Mollicone, Danilo

2008-07-01

A common paradigm when the reduction of emissions from deforestations is estimated for the purpose of promoting it as a mitigation option in the context of the United Nations Framework Convention on Climate Change (UNFCCC) is that high uncertainties in input data—i.e., area change and C stock change/area—may seriously undermine the credibility of the estimates and therefore of reduced deforestation as a mitigation option. In this paper, we show how a series of concepts and methodological tools—already existing in UNFCCC decisions and IPCC guidance documents—may greatly help to deal with the uncertainties of the estimates of reduced emissions from deforestation.

Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

NASA Astrophysics Data System (ADS)

Hoomod, Haider K.; Kareem Jebur, Tuka

2018-05-01

Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

Proximity effect assisted absorption enhancement in thin film with locally clustered nanoholes.

PubMed

Wu, Shaolong; Zhang, Cheng; Li, Xiaofeng; Zhan, Yaohui

2015-03-01

We focus on the light-trapping characteristics of a thin film with locally clustered nanoholes (NHs), considering that the clustering effect is usually encountered in preparing the nanostructures. Our full-wave finite-element simulation indicates that an intentionally introduced clustering effect could be employed for improving the light-trapping performance of the nanostructured thin film. For a 100 nm thick amorphous silicon film, an optimal clustering design with NH diameter of 100 nm is able to double the integrated optical absorption over the solar spectrum, compared to the planar counterpart, as well as show much improved optical performance over that of the nonclustered setup. A further insight into the underlying physics explains the outstanding light-trapping capability in terms of the increased available modes, a stronger power coupling efficiency, a higher fraction of electric field concentrated in absorbable material, and a higher density of photon states.

Dual organism design cycle reveals small subunit substitutions that improve [NiFe] hydrogenase hydrogen evolution

PubMed Central

2013-01-01

Background Photosynthetic microorganisms that directly channel solar energy to the production of molecular hydrogen are a potential future biofuel system. Building such a system requires installation of a hydrogenase in the photosynthetic organism that is both tolerant to oxygen and capable of hydrogen production. Toward this end, we have identified the [NiFe] hydrogenase from the marine bacterium Alteromonas macleodii “Deep ecotype” that is able to be heterologously expressed in cyanobacteria and has tolerance to partial oxygen. The A. macleodii enzyme shares sequence similarity with the uptake hydrogenases that favor hydrogen uptake activity over hydrogen evolution. To improve hydrogen evolution from the A. macleodii hydrogenase, we examined the three Fe-S clusters found in the small subunit of many [NiFe] uptake hydrogenases that presumably act as a molecular wire to guide electrons to or from the active site of the enzyme. Studies by others altering the medial cluster of a Desulfovibrio fructosovorans hydrogenase from 3Fe-4S to 4Fe-4S resulted in two-fold improved hydrogen evolution activity. Results We adopted a strategy of screening for improved hydrogenase constructs using an Escherichia coli expression system before testing in slower growing cyanobacteria. From the A. macleodii enzyme, we created a mutation in the gene encoding the hydrogenase small subunit that in other systems is known to convert the 3Fe-4S medial cluster to 4Fe-4S. The medial cluster substitution did not improve the hydrogen evolution activity of our hydrogenase. However, modifying both the medial cluster and the ligation of the distal Fe-S cluster improved in vitro hydrogen evolution activity relative to the wild type hydrogenase by three- to four-fold. Other properties of the enzyme including thermostability and tolerance to partial oxygen did not appear to be affected by the substitutions. Conclusions Our results show that substitution of amino acids altering the ligation of Fe-S clusters in the A. macleodii [NiFe] uptake hydrogenase resulted in increased hydrogen evolution activity. This activity can be recapitulated in multiple host systems and with purified protein. These results validate the approach of using an E. coli-cyanobacteria shuttle system for enzyme expression and improvement. PMID:23819621

Local-world and cluster-growing weighted networks with controllable clustering

NASA Astrophysics Data System (ADS)

Yang, Chun-Xia; Tang, Min-Xuan; Tang, Hai-Qiang; Deng, Qiang-Qiang

2014-12-01

We constructed an improved weighted network model by introducing local-world selection mechanism and triangle coupling mechanism based on the traditional BBV model. The model gives power-law distributions of degree, strength and edge weight and presents the linear relationship both between the degree and strength and between the degree and the clustering coefficient. Particularly, the model is equipped with an ability to accelerate the speed increase of strength exceeding that of degree. Besides, the model is more sound and efficient in tuning clustering coefficient than the original BBV model. Finally, based on our improved model, we analyze the virus spread process and find that reducing the size of local-world has a great inhibited effect on virus spread.

Clinical Implications of Cluster Analysis-Based Classification of Acute Decompensated Heart Failure and Correlation with Bedside Hemodynamic Profiles.

PubMed

Ahmad, Tariq; Desai, Nihar; Wilson, Francis; Schulte, Phillip; Dunning, Allison; Jacoby, Daniel; Allen, Larry; Fiuzat, Mona; Rogers, Joseph; Felker, G Michael; O'Connor, Christopher; Patel, Chetan B

2016-01-01

Classification of acute decompensated heart failure (ADHF) is based on subjective criteria that crudely capture disease heterogeneity. Improved phenotyping of the syndrome may help improve therapeutic strategies. To derive cluster analysis-based groupings for patients hospitalized with ADHF, and compare their prognostic performance to hemodynamic classifications derived at the bedside. We performed a cluster analysis on baseline clinical variables and PAC measurements of 172 ADHF patients from the ESCAPE trial. Employing regression techniques, we examined associations between clusters and clinically determined hemodynamic profiles (warm/cold/wet/dry). We assessed association with clinical outcomes using Cox proportional hazards models. Likelihood ratio tests were used to compare the prognostic value of cluster data to that of hemodynamic data. We identified four advanced HF clusters: 1) male Caucasians with ischemic cardiomyopathy, multiple comorbidities, lowest B-type natriuretic peptide (BNP) levels; 2) females with non-ischemic cardiomyopathy, few comorbidities, most favorable hemodynamics; 3) young African American males with non-ischemic cardiomyopathy, most adverse hemodynamics, advanced disease; and 4) older Caucasians with ischemic cardiomyopathy, concomitant renal insufficiency, highest BNP levels. There was no association between clusters and bedside-derived hemodynamic profiles (p = 0.70). For all adverse clinical outcomes, Cluster 4 had the highest risk, and Cluster 2, the lowest. Compared to Cluster 4, Clusters 1-3 had 45-70% lower risk of all-cause mortality. Clusters were significantly associated with clinical outcomes, whereas hemodynamic profiles were not. By clustering patients with similar objective variables, we identified four clinically relevant phenotypes of ADHF patients, with no discernable relationship to hemodynamic profiles, but distinct associations with adverse outcomes. Our analysis suggests that ADHF classification using simultaneous considerations of etiology, comorbid conditions, and biomarker levels, may be superior to bedside classifications.

Contributions to "k"-Means Clustering and Regression via Classification Algorithms

ERIC Educational Resources Information Center

Salman, Raied

2012-01-01

The dissertation deals with clustering algorithms and transforming regression problems into classification problems. The main contributions of the dissertation are twofold; first, to improve (speed up) the clustering algorithms and second, to develop a strict learning environment for solving regression problems as classification tasks by using…

Inference from clustering with application to gene-expression microarrays.

PubMed

Dougherty, Edward R; Barrera, Junior; Brun, Marcel; Kim, Seungchan; Cesar, Roberto M; Chen, Yidong; Bittner, Michael; Trent, Jeffrey M

2002-01-01

There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.

Function Clustering Self-Organization Maps (FCSOMs) for mining differentially expressed genes in Drosophila and its correlation with the growth medium.

PubMed

Liu, L L; Liu, M J; Ma, M

2015-09-28

The central task of this study was to mine the gene-to-medium relationship. Adequate knowledge of this relationship could potentially improve the accuracy of differentially expressed gene mining. One of the approaches to differentially expressed gene mining uses conventional clustering algorithms to identify the gene-to-medium relationship. Compared to conventional clustering algorithms, self-organization maps (SOMs) identify the nonlinear aspects of the gene-to-medium relationships by mapping the input space into another higher dimensional feature space. However, SOMs are not suitable for huge datasets consisting of millions of samples. Therefore, a new computational model, the Function Clustering Self-Organization Maps (FCSOMs), was developed. FCSOMs take advantage of the theory of granular computing as well as advanced statistical learning methodologies, and are built specifically for each information granule (a function cluster of genes), which are intelligently partitioned by the clustering algorithm provided by the DAVID_6.7 software platform. However, only the gene functions, and not their expression values, are considered in the fuzzy clustering algorithm of DAVID. Compared to the clustering algorithm of DAVID, these experimental results show a marked improvement in the accuracy of classification with the application of FCSOMs. FCSOMs can handle huge datasets and their complex classification problems, as each FCSOM (modeled for each function cluster) can be easily parallelized.

The shape of galaxy dark matter halos in massive galaxy clusters: Insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-04-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and VLT/MUSE spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z=0.397, M(R < 200 kpc)=1.6×1014M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar halos are allowed, the model improves by 35%. This technique may provide a new way to investigate the processes and timescales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

PubMed Central

Blin, Kai; Duddela, Srikanth; Krug, Daniel; Kim, Hyun Uk; Bruccoleri, Robert; Lee, Sang Yup; Fischbach, Michael A; Müller, Rolf; Wohlleben, Wolfgang; Breitling, Rainer; Takano, Eriko

2015-01-01

Abstract Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software. PMID:25948579

The shape of galaxy dark matter haloes in massive galaxy clusters: insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-07-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and Very Large Telescope/Multi Unit Spectroscopic Explorer spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z = 0.397, M(R < 200 kpc) = 1.6 × 1014 M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar haloes are allowed, the model improves by 35 per cent. This technique may provide a new way to investigate the processes and time-scales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

Convalescing Cluster Configuration Using a Superlative Framework

PubMed Central

Sabitha, R.; Karthik, S.

2015-01-01

Competent data mining methods are vital to discover knowledge from databases which are built as a result of enormous growth of data. Various techniques of data mining are applied to obtain knowledge from these databases. Data clustering is one such descriptive data mining technique which guides in partitioning data objects into disjoint segments. K-means algorithm is a versatile algorithm among the various approaches used in data clustering. The algorithm and its diverse adaptation methods suffer certain problems in their performance. To overcome these issues a superlative algorithm has been proposed in this paper to perform data clustering. The specific feature of the proposed algorithm is discretizing the dataset, thereby improving the accuracy of clustering, and also adopting the binary search initialization method to generate cluster centroids. The generated centroids are fed as input to K-means approach which iteratively segments the data objects into respective clusters. The clustered results are measured for accuracy and validity. Experiments conducted by testing the approach on datasets from the UC Irvine Machine Learning Repository evidently show that the accuracy and validity measure is higher than the other two approaches, namely, simple K-means and Binary Search method. Thus, the proposed approach proves that discretization process will improve the efficacy of descriptive data mining tasks. PMID:26543895

Using Targeted Active-Learning Exercises and Diagnostic Question Clusters to Improve Students' Understanding of Carbon Cycling in Ecosystems

ERIC Educational Resources Information Center

Maskiewicz, April Cordero; Griscom, Heather Peckham; Welch, Nicole Turrill

2012-01-01

In this study, we used targeted active-learning activities to help students improve their ways of reasoning about carbon flow in ecosystems. The results of a validated ecology conceptual inventory (diagnostic question clusters [DQCs]) provided us with information about students' understanding of and reasoning about transformation of inorganic and…

WFPC2 Observations of Star Clusters in the Magellanic Clouds. Report 2; The Oldest Star Clusters in the Small Magellanic Cloud

NASA Technical Reports Server (NTRS)

Mighell, Kenneth J.; Sarajedini, Ata; French, Rica S.

1998-01-01

We present our analysis of archival Hubble Space Telescope Wide Field Planetary Camera 2 (WFPC2) observations in F45OW ( approximately B) and F555W (approximately V) of the intermediate-age populous star clusters NGC 121, NGC 339, NGC 361, NGC 416, and Kron 3 in the Small Magellanic Cloud. We use published photometry of two other SMC populous star clusters, Lindsay 1 and Lindsay 113, to investigate the age sequence of these seven populous star clusters in order to improve our understanding of the formation chronology of the SMC. We analyzed the V vs B-V and M(sub V) vs (B-V)(sub 0) color-magnitude diagrams of these populous Small Magellanic Cloud star clusters using a variety of techniques and determined their ages, metallicities, and reddenings. These new data enable us to improve the age-metallicity relation of star clusters in the Small Magellanic Cloud. In particular, we find that a closed-box continuous star-formation model does not reproduce the age-metallicity relation adequately. However, a theoretical model punctuated by bursts of star formation is in better agreement with the observational data presented herein.

Synchronous Firefly Algorithm for Cluster Head Selection in WSN

PubMed Central

Baskaran, Madhusudhanan; Sadagopan, Chitra

2015-01-01

Wireless Sensor Network (WSN) consists of small low-cost, low-power multifunctional nodes interconnected to efficiently aggregate and transmit data to sink. Cluster-based approaches use some nodes as Cluster Heads (CHs) and organize WSNs efficiently for aggregation of data and energy saving. A CH conveys information gathered by cluster nodes and aggregates/compresses data before transmitting it to a sink. However, this additional responsibility of the node results in a higher energy drain leading to uneven network degradation. Low Energy Adaptive Clustering Hierarchy (LEACH) offsets this by probabilistically rotating cluster heads role among nodes with energy above a set threshold. CH selection in WSN is NP-Hard as optimal data aggregation with efficient energy savings cannot be solved in polynomial time. In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. Extensive simulation shows the proposed technique to perform well compared to LEACH and energy-efficient hierarchical clustering. Simulations show the effectiveness of the proposed method in decreasing the packet loss ratio by an average of 9.63% and improving the energy efficiency of the network when compared to LEACH and EEHC. PMID:26495431

Performance of Extended Local Clustering Organization (LCO) for Large Scale Job-Shop Scheduling Problem (JSP)

NASA Astrophysics Data System (ADS)

Konno, Yohko; Suzuki, Keiji

This paper describes an approach to development of a solution algorithm of a general-purpose for large scale problems using “Local Clustering Organization (LCO)” as a new solution for Job-shop scheduling problem (JSP). Using a performance effective large scale scheduling in the study of usual LCO, a solving JSP keep stability induced better solution is examined. In this study for an improvement of a performance of a solution for JSP, processes to a optimization by LCO is examined, and a scheduling solution-structure is extended to a new solution-structure based on machine-division. A solving method introduced into effective local clustering for the solution-structure is proposed as an extended LCO. An extended LCO has an algorithm which improves scheduling evaluation efficiently by clustering of parallel search which extends over plural machines. A result verified by an application of extended LCO on various scale of problems proved to conduce to minimizing make-span and improving on the stable performance.

Country clustering applied to the water & sanitation sector: a new tool with potential applications in research & policy

PubMed Central

Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

2013-01-01

The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were unique from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. PMID:24054545

Exploring the IMF of star clusters: a joint SLUG and LEGUS effort

NASA Astrophysics Data System (ADS)

Ashworth, G.; Fumagalli, M.; Krumholz, M. R.; Adamo, A.; Calzetti, D.; Chandar, R.; Cignoni, M.; Dale, D.; Elmegreen, B. G.; Gallagher, J. S., III; Gouliermis, D. A.; Grasha, K.; Grebel, E. K.; Johnson, K. E.; Lee, J.; Tosi, M.; Wofford, A.

2017-08-01

We present the implementation of a Bayesian formalism within the Stochastically Lighting Up Galaxies (slug) stellar population synthesis code, which is designed to investigate variations in the initial mass function (IMF) of star clusters. By comparing observed cluster photometry to large libraries of clusters simulated with a continuously varying IMF, our formalism yields the posterior probability distribution function (PDF) of the cluster mass, age and extinction, jointly with the parameters describing the IMF. We apply this formalism to a sample of star clusters from the nearby galaxy NGC 628, for which broad-band photometry in five filters is available as part of the Legacy ExtraGalactic UV Survey (LEGUS). After allowing the upper-end slope of the IMF (α3) to vary, we recover PDFs for the mass, age and extinction that are broadly consistent with what is found when assuming an invariant Kroupa IMF. However, the posterior PDF for α3 is very broad due to a strong degeneracy with the cluster mass, and it is found to be sensitive to the choice of priors, particularly on the cluster mass. We find only a modest improvement in the constraining power of α3 when adding Hα photometry from the companion Hα-LEGUS survey. Conversely, Hα photometry significantly improves the age determination, reducing the frequency of multi-modal PDFs. With the aid of mock clusters, we quantify the degeneracy between physical parameters, showing how constraints on the cluster mass that are independent of photometry can be used to pin down the IMF properties of star clusters.

Towards semantically sensitive text clustering: a feature space modeling technology based on dimension extension.

PubMed

Liu, Yuanchao; Liu, Ming; Wang, Xin

2015-01-01

The objective of text clustering is to divide document collections into clusters based on the similarity between documents. In this paper, an extension-based feature modeling approach towards semantically sensitive text clustering is proposed along with the corresponding feature space construction and similarity computation method. By combining the similarity in traditional feature space and that in extension space, the adverse effects of the complexity and diversity of natural language can be addressed and clustering semantic sensitivity can be improved correspondingly. The generated clusters can be organized using different granularities. The experimental evaluations on well-known clustering algorithms and datasets have verified the effectiveness of our approach.

The composite sequential clustering technique for analysis of multispectral scanner data

NASA Technical Reports Server (NTRS)

Su, M. Y.

1972-01-01

The clustering technique consists of two parts: (1) a sequential statistical clustering which is essentially a sequential variance analysis, and (2) a generalized K-means clustering. In this composite clustering technique, the output of (1) is a set of initial clusters which are input to (2) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by traditional supervised maximum likelihood classification techniques. The mathematical algorithms for the composite sequential clustering program and a detailed computer program description with job setup are given.

Towards Semantically Sensitive Text Clustering: A Feature Space Modeling Technology Based on Dimension Extension

PubMed Central

Liu, Yuanchao; Liu, Ming; Wang, Xin

2015-01-01

The objective of text clustering is to divide document collections into clusters based on the similarity between documents. In this paper, an extension-based feature modeling approach towards semantically sensitive text clustering is proposed along with the corresponding feature space construction and similarity computation method. By combining the similarity in traditional feature space and that in extension space, the adverse effects of the complexity and diversity of natural language can be addressed and clustering semantic sensitivity can be improved correspondingly. The generated clusters can be organized using different granularities. The experimental evaluations on well-known clustering algorithms and datasets have verified the effectiveness of our approach. PMID:25794172

Improving Performance for Gifted Students in a Cluster Grouping Model

ERIC Educational Resources Information Center

Brulles, Dina; Saunders, Rachel; Cohn, Sanford J.

2010-01-01

Although experts in gifted education widely promote cluster grouping gifted students, little empirical evidence is available to attest to its effectiveness. This study is an example of comparative action research in the form of a quantitative case study that focused on the mandated cluster grouping practices for gifted students in an urban…

Shortest-path constraints for 3D multiobject semiautomatic segmentation via clustering and Graph Cut.

PubMed

Kéchichian, Razmig; Valette, Sébastien; Desvignes, Michel; Prost, Rémy

2013-11-01

We derive shortest-path constraints from graph models of structure adjacency relations and introduce them in a joint centroidal Voronoi image clustering and Graph Cut multiobject semiautomatic segmentation framework. The vicinity prior model thus defined is a piecewise-constant model incurring multiple levels of penalization capturing the spatial configuration of structures in multiobject segmentation. Qualitative and quantitative analyses and comparison with a Potts prior-based approach and our previous contribution on synthetic, simulated, and real medical images show that the vicinity prior allows for the correct segmentation of distinct structures having identical intensity profiles and improves the precision of segmentation boundary placement while being fairly robust to clustering resolution. The clustering approach we take to simplify images prior to segmentation strikes a good balance between boundary adaptivity and cluster compactness criteria furthermore allowing to control the trade-off. Compared with a direct application of segmentation on voxels, the clustering step improves the overall runtime and memory footprint of the segmentation process up to an order of magnitude without compromising the quality of the result.

Comparing residue clusters from thermophilic and mesophilic enzymes reveals adaptive mechanisms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sammond, Deanne W.; Kastelowitz, Noah; Himmel, Michael E.

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research.more » Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. As a result, the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.« less

Comparing residue clusters from thermophilic and mesophilic enzymes reveals adaptive mechanisms

DOE PAGES

Sammond, Deanne W.; Kastelowitz, Noah; Himmel, Michael E.; ...

2016-01-07

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research.more » Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. As a result, the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.« less

Carbon outcomes of major land-cover transitions in SE Asia: great uncertainties and REDD+ policy implications.

PubMed

Ziegler, Alan D; Phelps, Jacob; Yuen, Jia Qi; Webb, Edward L; Lawrence, Deborah; Fox, Jeff M; Bruun, Thilde B; Leisz, Stephen J; Ryan, Casey M; Dressler, Wolfram; Mertz, Ole; Pascual, Unai; Padoch, Christine; Koh, Lian Pin

2012-10-01

Policy makers across the tropics propose that carbon finance could provide incentives for forest frontier communities to transition away from swidden agriculture (slash-and-burn or shifting cultivation) to other systems that potentially reduce emissions and/or increase carbon sequestration. However, there is little certainty regarding the carbon outcomes of many key land-use transitions at the center of current policy debates. Our meta-analysis of over 250 studies reporting above- and below-ground carbon estimates for different land-use types indicates great uncertainty in the net total ecosystem carbon changes that can be expected from many transitions, including the replacement of various types of swidden agriculture with oil palm, rubber, or some other types of agroforestry systems. These transitions are underway throughout Southeast Asia, and are at the heart of REDD+ debates. Exceptions of unambiguous carbon outcomes are the abandonment of any type of agriculture to allow forest regeneration (a certain positive carbon outcome) and expansion of agriculture into mature forest (a certain negative carbon outcome). With respect to swiddening, our meta-analysis supports a reassessment of policies that encourage land-cover conversion away from these [especially long-fallow] systems to other more cash-crop-oriented systems producing ambiguous carbon stock changes - including oil palm and rubber. In some instances, lengthening fallow periods of an existing swidden system may produce substantial carbon benefits, as would conversion from intensely cultivated lands to high-biomass plantations and some other types of agroforestry. More field studies are needed to provide better data of above- and below-ground carbon stocks before informed recommendations or policy decisions can be made regarding which land-use regimes optimize or increase carbon sequestration. As some transitions may negatively impact other ecosystem services, food security, and local livelihoods, the entire carbon and noncarbon benefit stream should also be taken into account before prescribing transitions with ambiguous carbon benefits. © 2012 Blackwell Publishing Ltd.

Estimating the effective number of breeders from single parr samples for conservation monitoring of wild populations of Atlantic salmon Salmo salar.

PubMed

Bacles, C F E; Bouchard, C; Lange, F; Manicki, A; Tentelier, C; Lepais, O

2018-03-01

This study assesses whether the effective number of breeders (N b ) can be estimated using a time and cost-effective protocol using genetic sibship reconstruction from a single sample of young-of-the-year (YOY) for the purposes of Atlantic salmon Salmo salar population monitoring. N b was estimated for 10 consecutive reproductive seasons for S. salar in the River Nivelle, a small population located at the rear-edge of the species distribution area in France, chronically under its conservation limit and subjected to anthropogenic and environmental changes. Subsampling of real and simulated data showed that accurate estimates of N b can be obtained from YOY genotypes, collected at moderate random sampling intensity, achievable using routine juvenile electrofishing protocols. Spatial bias and time elapsed since spawning were found to affect estimates, which must be accounted for in sampling designs. N b estimated in autumn for S. salar in the River Nivelle was low and variable across years from 23 (95% C.I. 14-41) to 75 (53-101) and was not statistically correlated with the estimated number of returning adults, but it was positively correlated with the estimated number of YOY at age 9 months. N b was found to be lower for intermediate levels of redd aggregation, suggesting that the strength of the competition between males to access females affects reproductive success variance depending on redd spatial configuration. Thus, environmental factors such as habitat availability and quality for spawning and YOY development predominate over demographic ones (number of returning adults) in driving long-term population viability for S. salar in the River Nivelle. This study showcases N b as an integrated parameter, encompassing demographic and ecological information about a reproductive event, relevant to the assessment of both short-term effects of management practices and long-term population conservation status. © 2018 The Fisheries Society of the British Isles.

Age-related differences in lean mass, protein synthesis and skeletal muscle markers of proteolysis after bed rest and exercise rehabilitation.

PubMed

Tanner, Ruth E; Brunker, Lucille B; Agergaard, Jakob; Barrows, Katherine M; Briggs, Robert A; Kwon, Oh Sung; Young, Laura M; Hopkins, Paul N; Volpi, Elena; Marcus, Robin L; LaStayo, Paul C; Drummond, Micah J

2015-09-15

Bed rest-induced muscle loss and impaired muscle recovery may contribute to age-related sarcopenia. It is unknown if there are age-related differences in muscle mass and muscle anabolic and catabolic responses to bed rest. A secondary objective was to determine if rehabilitation could reverse bed rest responses. Nine older and fourteen young adults participated in a 5-day bed rest challenge (BED REST). This was followed by 8 weeks of high intensity resistance exercise (REHAB). Leg lean mass (via dual-energy X-ray absorptiometry; DXA) and strength were determined. Muscle biopsies were collected during a constant stable isotope infusion in the postabsorptive state and after essential amino acid (EAA) ingestion on three occasions: before (PRE), after bed rest and after rehabilitation. Samples were assessed for protein synthesis, mTORC1 signalling, REDD1/2 expression and molecular markers related to muscle proteolysis (MURF1, MAFBX, AMPKα, LC3II/I, Beclin1). We found that leg lean mass and strength decreased in older but not younger adults after bedrest (P < 0.05) and was restored after rehabilitation. EAA-induced mTORC1 signalling and protein synthesis increased before bed rest in both age groups (P < 0.05). Although both groups had blunted mTORC1 signalling, increased REDD2 and MURF1 mRNA after bedrest, only older adults had reduced EAA-induced protein synthesis rates and increased MAFBX mRNA, p-AMPKα and the LC3II/I ratio (P < 0.05). We conclude that older adults are more susceptible than young persons to muscle loss after short-term bed rest. This may be partially explained by a combined suppression of protein synthesis and a marginal increase in proteolytic markers. Finally, rehabilitation restored bed rest-induced deficits in lean mass and strength in older adults. © 2015 The Authors. The Journal of Physiology © 2015 The Physiological Society.

Integration of carbon conservation into sustainable forest management using high resolution satellite imagery: A case study in Sabah, Malaysian Borneo

NASA Astrophysics Data System (ADS)

Langner, Andreas; Samejima, Hiromitsu; Ong, Robert C.; Titin, Jupiri; Kitayama, Kanehiro

2012-08-01

Conservation of tropical forests is of outstanding importance for mitigation of climate change effects and preserving biodiversity. In Borneo most of the forests are classified as permanent forest estates and are selectively logged using conventional logging techniques causing high damage to the forest ecosystems. Incorporation of sustainable forest management into climate change mitigation measures such as Reducing Emissions from Deforestation and Forest Degradation (REDD+) can help to avert further forest degradation by synergizing sustainable timber production with the conservation of biodiversity. In order to evaluate the efficiency of such initiatives, monitoring methods for forest degradation and above-ground biomass in tropical forests are urgently needed. In this study we developed an index using Landsat satellite data to describe the crown cover condition of lowland mixed dipterocarp forests. We showed that this index combined with field data can be used to estimate above-ground biomass using a regression model in two permanent forest estates in Sabah, Malaysian Borneo. Tangkulap represented a conventionally logged forest estate while Deramakot has been managed in accordance with sustainable forestry principles. The results revealed that conventional logging techniques used in Tangkulap during 1991 and 2000 decreased the above-ground biomass by an annual amount of average -6.0 t C/ha (-5.2 to -7.0 t C/ha, 95% confidential interval) whereas the biomass in Deramakot increased by 6.1 t C/ha per year (5.3-7.2 t C/ha, 95% confidential interval) between 2000 and 2007 while under sustainable forest management. This indicates that sustainable forest management with reduced-impact logging helps to protect above-ground biomass. In absolute terms, a conservative amount of 10.5 t C/ha per year, as documented using the methodology developed in this study, can be attributed to the different management systems, which will be of interest when implementing REDD+ that rewards the enhancement of carbon stocks.

An unsupervised classification technique for multispectral remote sensing data.

NASA Technical Reports Server (NTRS)

Su, M. Y.; Cummings, R. E.

1973-01-01

Description of a two-part clustering technique consisting of (a) a sequential statistical clustering, which is essentially a sequential variance analysis, and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by traditional supervised maximum-likelihood classification techniques.

Unsupervised classification of earth resources data.

NASA Technical Reports Server (NTRS)

Su, M. Y.; Jayroe, R. R., Jr.; Cummings, R. E.

1972-01-01

A new clustering technique is presented. It consists of two parts: (a) a sequential statistical clustering which is essentially a sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by existing supervised maximum liklihood classification technique.

Automated cloud screening of AVHRR imagery using split-and-merge clustering

NASA Technical Reports Server (NTRS)

Gallaudet, Timothy C.; Simpson, James J.

1991-01-01

Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.

Water oxidation by size selected Co 27 clusters supported on Fe 2O 3

DOE PAGES

Pellin, Michael J.; Riha, Shannon C.; Tyo, Eric C.; ...

2016-09-22

The complexity of the water oxidation reaction makes understanding the role of individual catalytic sites critical to improving the process. Here, size-selected 27-atom cobalt clusters (Co 27) deposited on hematite (Fe 2O 3) anodes were tested for water oxidation activity. The uniformity of these anodes allows measurement of the activity of catalytic sites of well-defined nuclearity and known density. Grazing incidence X-ray absorption near-edge spectroscopy (GIXANES) characterization of the anodes before and after electrochemical cycling demonstrates that these Co 27 clusters are stable to dissolution even in the harsh water oxidation electrochemical environment. They are also stable under illumination atmore » the equivalent of 0.4suns irradiation. The clusters show turnover rates for water oxidation that are comparable or higher than those reported for Pd- and Co-based materials or for hematite. The support for the Co 27 clusters is Fe 2O 3 grown by atomic layer deposition on a Si chip. We have chosen to deposit a Fe2O3 layer that is only a few unit cells thick (2nm), to remove complications related to exciton diffusion. We find that the electrocatalytic and the photoelectrocatalytic activity of the Co 27/Fe 2O 3 material is significantly improved when the samples are annealed (with the clusters already deposited). Lastly, given that the support is thin and that the cluster deposition density is equivalent to approximately 5% of an atomic monolayer, we suggest that annealing may significantly improve the exciton diffusion from the support to the catalytic moiety.« less

Effects of quality improvement in health facilities and community mobilization through women's groups on maternal, neonatal and perinatal mortality in three districts of Malawi: MaiKhanda, a cluster randomized controlled effectiveness trial.

PubMed

Colbourn, Tim; Nambiar, Bejoy; Bondo, Austin; Makwenda, Charles; Tsetekani, Eric; Makonda-Ridley, Agnes; Msukwa, Martin; Barker, Pierre; Kotagal, Uma; Williams, Cassie; Davies, Ros; Webb, Dale; Flatman, Dorothy; Lewycka, Sonia; Rosato, Mikey; Kachale, Fannie; Mwansambo, Charles; Costello, Anthony

2013-09-01

Maternal, perinatal and neonatal mortality remains high in low-income countries. We evaluated community and facility-based interventions to reduce deaths in three districts of Malawi. We evaluated a rural participatory women's group community intervention (CI) and a quality improvement intervention at health centres (FI) via a two-by-two factorial cluster randomized controlled trial. Consenting pregnant women were followed-up to 2 months after birth using key informants. Primary outcomes were maternal, perinatal and neonatal mortality. Clusters were health centre catchment areas assigned using stratified computer-generated randomization. Following exclusions, including non-birthing facilities, 61 clusters were analysed: control (17 clusters, 4912 births), FI (15, 5335), CI (15, 5080) and FI + CI (14, 5249). This trial was registered as International Standard Randomised Controlled Trial [ISRCTN18073903]. Outcomes for 14,576 and 20,576 births were recorded during baseline (June 2007-September 2008) and intervention (October 2008-December 2010) periods. For control, FI, CI and FI + CI clusters neonatal mortality rates were 34.0, 28.3, 29.9 and 27.0 neonatal deaths per 1000 live births and perinatal mortality rates were 56.2, 55.1, 48.0 and 48.4 per 1000 births, during the intervention period. Adjusting for clustering and stratification, the neonatal mortality rate was 22% lower in FI + CI than control clusters (OR = 0.78, 95% CI 0.60-1.01), and the perinatal mortality rate was 16% lower in CI clusters (OR = 0.84, 95% CI 0.72-0.97). We did not observe any intervention effects on maternal mortality. Despite implementation problems, a combined community and facility approach using participatory women's groups and quality improvement at health centres reduced newborn mortality in rural Malawi.

Effects of quality improvement in health facilities and community mobilization through women’s groups on maternal, neonatal and perinatal mortality in three districts of Malawi: MaiKhanda, a cluster randomized controlled effectiveness trial

PubMed Central

Colbourn, Tim; Nambiar, Bejoy; Bondo, Austin; Makwenda, Charles; Tsetekani, Eric; Makonda-Ridley, Agnes; Msukwa, Martin; Barker, Pierre; Kotagal, Uma; Williams, Cassie; Davies, Ros; Webb, Dale; Flatman, Dorothy; Lewycka, Sonia; Rosato, Mikey; Kachale, Fannie; Mwansambo, Charles; Costello, Anthony

2016-01-01

Background Maternal, perinatal and neonatal mortality remains high in low-income countries. We evaluated community and facility-based interventions to reduce deaths in three districts of Malawi. Methods We evaluated a rural participatory women’s group community intervention (CI) and a quality improvement intervention at health centres (FI) via a two-by-two factorial cluster randomized controlled trial. Consenting pregnant women were followed-up to 2 months after birth using key informants. Primary outcomes were maternal, perinatal and neonatal mortality. Clusters were health centre catchment areas assigned using stratified computer-generated randomization. Following exclusions, including non-birthing facilities, 61 clusters were analysed: control (17 clusters, 4912 births), FI (15, 5335), CI (15, 5080) and FI + CI (14, 5249). This trial was registered as International Standard Randomised Controlled Trial [ISRCTN18073903]. Outcomes for 14 576 and 20 576 births were recorded during baseline (June 2007–September 2008) and intervention (October 2008–December 2010) periods. Results For control, FI, CI and FI + CI clusters neonatal mortality rates were 34.0, 28.3, 29.9 and 27.0 neonatal deaths per 1000 live births and perinatal mortality rates were 56.2, 55.1, 48.0 and 48.4 per 1000 births, during the intervention period. Adjusting for clustering and stratification, the neonatal mortality rate was 22% lower in FI + CI than control clusters (OR = 0.78, 95% CI 0.60–1.01), and the perinatal mortality rate was 16% lower in CI clusters (OR = 0.84, 95% CI 0.72–0.97). We did not observe any intervention effects on maternal mortality. Conclusions Despite implementation problems, a combined community and facility approach using participatory women’s groups and quality improvement at health centres reduced newborn mortality in rural Malawi. PMID:24030269

MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Young, M; Craft, D

Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchicalmore » clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve cancer classification using biological pathways. Patients are classified with greater specificity and physiological relevance as compared to current gene-specific approaches. Focus now moves to utilizing PICS for pan-cancer patient-specific treatment response prediction.« less

Machine Learning for Discriminating Quantum Measurement Trajectories and Improving Readout.

PubMed

Magesan, Easwar; Gambetta, Jay M; Córcoles, A D; Chow, Jerry M

2015-05-22

Current methods for classifying measurement trajectories in superconducting qubit systems produce fidelities systematically lower than those predicted by experimental parameters. Here, we place current classification methods within the framework of machine learning (ML) algorithms and improve on them by investigating more sophisticated ML approaches. We find that nonlinear algorithms and clustering methods produce significantly higher assignment fidelities that help close the gap to the fidelity possible under ideal noise conditions. Clustering methods group trajectories into natural subsets within the data, which allows for the diagnosis of systematic errors. We find large clusters in the data associated with T1 processes and show these are the main source of discrepancy between our experimental and ideal fidelities. These error diagnosis techniques help provide a path forward to improve qubit measurements.

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

NASA Astrophysics Data System (ADS)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

GALAXY CLUSTERS DISCOVERED VIA THE SUNYAEV-ZEL'DOVICH EFFECT IN THE FIRST 720 SQUARE DEGREES OF THE SOUTH POLE TELESCOPE SURVEY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reichardt, C. L.; Stalder, B.; Ashby, M. L. N.

2013-02-15

We present a catalog of galaxy cluster candidates, selected through their Sunyaev-Zel'dovich (SZ) effect signature in the first 720 deg{sup 2} of the South Pole Telescope (SPT) survey. This area was mapped with the SPT in the 2008 and 2009 austral winters to a depth of {approx}18 {mu}K{sub CMB}-arcmin at 150 GHz; 550 deg{sup 2} of it was also mapped to {approx}44 {mu}K{sub CMB}-arcmin at 95 GHz. Based on optical imaging of all 224 candidates and near-infrared imaging of the majority of candidates, we have found optical and/or infrared counterparts for 158, which we then classify as confirmed galaxy clusters.more » Of these 158 clusters, 135 were first identified as clusters in SPT data, including 117 new discoveries reported in this work. This catalog triples the number of confirmed galaxy clusters discovered through the SZ effect. We report photometrically derived (and in some cases spectroscopic) redshifts for confirmed clusters and redshift lower limits for the remaining candidates. The catalog extends to high redshift with a median redshift of z = 0.55 and maximum confirmed redshift of z = 1.37. Forty-five of the clusters have counterparts in the ROSAT bright or faint source catalogs from which we estimate X-ray fluxes. Based on simulations, we expect the catalog to be nearly 100% complete above M {sub 500} Almost-Equal-To 5 Multiplication-Sign 10{sup 14} M {sub Sun} h {sup -1} {sub 70} at z {approx}> 0.6. There are 121 candidates detected at signal-to-noise ratio greater than five, at which the catalog purity is measured to be 95%. From this high-purity subsample, we exclude the z < 0.3 clusters and use the remaining 100 candidates to improve cosmological constraints following the method presented by Benson et al. Adding the cluster data to CMB + BAO + H {sub 0} data leads to a preference for non-zero neutrino masses while only slightly reducing the upper limit on the sum of neutrino masses to {Sigma}m {sub {nu}} < 0.38 eV (95% CL). For a spatially flat wCDM cosmological model, the addition of this catalog to the CMB + BAO + H {sub 0} + SNe results yields {sigma}{sub 8} = 0.807 {+-} 0.027 and w = -1.010 {+-} 0.058, improving the constraints on these parameters by a factor of 1.4 and 1.3, respectively. The larger cluster catalog presented in this work leads to slight improvements in cosmological constraints from those presented by Benson et al. These cosmological constraints are currently limited by uncertainty in the cluster mass calibration, not the size or quality of the cluster catalog. A multi-wavelength observation program to improve the cluster mass calibration will make it possible to realize the full potential of the final 2500 deg{sup 2} SPT cluster catalog to constrain cosmology.« less

A Simple Model for the Earthquake Cycle Combining Self-Organized Criticality with Critical Point Behavior

NASA Astrophysics Data System (ADS)

Newman, W. I.; Turcotte, D. L.

2002-12-01

We have studied a hybrid model combining the forest-fire model with the site-percolation model in order to better understand the earthquake cycle. We consider a square array of sites. At each time step, a "tree" is dropped on a randomly chosen site and is planted if the site is unoccupied. When a cluster of "trees" spans the site (a percolating cluster), all the trees in the cluster are removed ("burned") in a "fire." The removal of the cluster is analogous to a characteristic earthquake and planting "trees" is analogous to increasing the regional stress. The clusters are analogous to the metastable regions of a fault over which an earthquake rupture can propagate once triggered. We find that the frequency-area statistics of the metastable regions are power-law with a negative exponent of two (as in the forest-fire model). This is analogous to the Gutenberg-Richter distribution of seismicity. This "self-organized critical behavior" can be explained in terms of an inverse cascade of clusters. Individual trees move from small to larger clusters until they are destroyed. This inverse cascade of clusters is self-similar and the power-law distribution of cluster sizes has been shown to have an exponent of two. We have quantified the forecasting of the spanning fires using error diagrams. The assumption that "fires" (earthquakes) are quasi-periodic has moderate predictability. The density of trees gives an improved degree of predictability, while the size of the largest cluster of trees provides a substantial improvement in forecasting a "fire."

Identification of an unusual type II thioesterase in the dithiolopyrrolone antibiotics biosynthetic pathway

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhai, Ying; Bai, Silei; Liu, Jingjing

Dithiolopyrrolone group antibiotics characterized by an electronically unique dithiolopyrrolone heterobicyclic core are known for their antibacterial, antifungal, insecticidal and antitumor activities. Recently the biosynthetic gene clusters for two dithiolopyrrolone compounds, holomycin and thiomarinol, have been identified respectively in different bacterial species. Here, we report a novel dithiolopyrrolone biosynthetic gene cluster (aut) isolated from Streptomyces thioluteus DSM 40027 which produces two pyrrothine derivatives, aureothricin and thiolutin. By comparison with other characterized dithiolopyrrolone clusters, eight genes in the aut cluster were verified to be responsible for the assembly of dithiolopyrrolone core. The aut cluster was further confirmed by heterologous expression and in-framemore » gene deletion experiments. Intriguingly, we found that the heterogenetic thioesterase HlmK derived from the holomycin (hlm) gene cluster in Streptomyces clavuligerus significantly improved heterologous biosynthesis of dithiolopyrrolones in Streptomyces albus through coexpression with the aut cluster. In the previous studies, HlmK was considered invalid because it has a Ser to Gly point mutation within the canonical Ser-His-Asp catalytic triad of thioesterases. However, gene inactivation and complementation experiments in our study unequivocally demonstrated that HlmK is an active distinctive type II thioesterase that plays a beneficial role in dithiolopyrrolone biosynthesis. - Highlights: • Cloning of the aureothricin biosynthetic gene cluster from Streptomyces thioluteus DSM 40027. • Identification of the aureothricin gene cluster by heterologous expression and in-frame gene deletion. • The heterogenetic thioesterase HlmK significantly improved dithiolopyrrolones production of the aureothricin gene cluster. • Identification of HlmK as an unusual type II thioesterase.« less

MetaCAA: A clustering-aided methodology for efficient assembly of metagenomic datasets.

PubMed

Reddy, Rachamalla Maheedhar; Mohammed, Monzoorul Haque; Mande, Sharmila S

2014-01-01

A key challenge in analyzing metagenomics data pertains to assembly of sequenced DNA fragments (i.e. reads) originating from various microbes in a given environmental sample. Several existing methodologies can assemble reads originating from a single genome. However, these methodologies cannot be applied for efficient assembly of metagenomic sequence datasets. In this study, we present MetaCAA - a clustering-aided methodology which helps in improving the quality of metagenomic sequence assembly. MetaCAA initially groups sequences constituting a given metagenome into smaller clusters. Subsequently, sequences in each cluster are independently assembled using CAP3, an existing single genome assembly program. Contigs formed in each of the clusters along with the unassembled reads are then subjected to another round of assembly for generating the final set of contigs. Validation using simulated and real-world metagenomic datasets indicates that MetaCAA aids in improving the overall quality of assembly. A software implementation of MetaCAA is available at https://metagenomics.atc.tcs.com/MetaCAA. Copyright © 2014 Elsevier Inc. All rights reserved.

The observed clustering of damaging extra-tropical cyclones in Europe

NASA Astrophysics Data System (ADS)

Cusack, S.

2015-12-01

The clustering of severe European windstorms on annual timescales has substantial impacts on the re/insurance industry. Management of the risk is impaired by large uncertainties in estimates of clustering from historical storm datasets typically covering the past few decades. The uncertainties are unusually large because clustering depends on the variance of storm counts. Eight storm datasets are gathered for analysis in this study in order to reduce these uncertainties. Six of the datasets contain more than 100~years of severe storm information to reduce sampling errors, and the diversity of information sources and analysis methods between datasets sample observational errors. All storm severity measures used in this study reflect damage, to suit re/insurance applications. It is found that the shortest storm dataset of 42 years in length provides estimates of clustering with very large sampling and observational errors. The dataset does provide some useful information: indications of stronger clustering for more severe storms, particularly for southern countries off the main storm track. However, substantially different results are produced by removal of one stormy season, 1989/1990, which illustrates the large uncertainties from a 42-year dataset. The extended storm records place 1989/1990 into a much longer historical context to produce more robust estimates of clustering. All the extended storm datasets show a greater degree of clustering with increasing storm severity and suggest clustering of severe storms is much more material than weaker storms. Further, they contain signs of stronger clustering in areas off the main storm track, and weaker clustering for smaller-sized areas, though these signals are smaller than uncertainties in actual values. Both the improvement of existing storm records and development of new historical storm datasets would help to improve management of this risk.

Object-Oriented Image Clustering Method Using UAS Photogrammetric Imagery

NASA Astrophysics Data System (ADS)

Lin, Y.; Larson, A.; Schultz-Fellenz, E. S.; Sussman, A. J.; Swanson, E.; Coppersmith, R.

2016-12-01

Unmanned Aerial Systems (UAS) have been used widely as an imaging modality to obtain remotely sensed multi-band surface imagery, and are growing in popularity due to their efficiency, ease of use, and affordability. Los Alamos National Laboratory (LANL) has employed the use of UAS for geologic site characterization and change detection studies at a variety of field sites. The deployed UAS equipped with a standard visible band camera to collect imagery datasets. Based on the imagery collected, we use deep sparse algorithmic processing to detect and discriminate subtle topographic features created or impacted by subsurface activities. In this work, we develop an object-oriented remote sensing imagery clustering method for land cover classification. To improve the clustering and segmentation accuracy, instead of using conventional pixel-based clustering methods, we integrate the spatial information from neighboring regions to create super-pixels to avoid salt-and-pepper noise and subsequent over-segmentation. To further improve robustness of our clustering method, we also incorporate a custom digital elevation model (DEM) dataset generated using a structure-from-motion (SfM) algorithm together with the red, green, and blue (RGB) band data for clustering. In particular, we first employ an agglomerative clustering to create an initial segmentation map, from where every object is treated as a single (new) pixel. Based on the new pixels obtained, we generate new features to implement another level of clustering. We employ our clustering method to the RGB+DEM datasets collected at the field site. Through binary clustering and multi-object clustering tests, we verify that our method can accurately separate vegetation from non-vegetation regions, and are also able to differentiate object features on the surface.

Country clustering applied to the water and sanitation sector: a new tool with potential applications in research and policy.

PubMed

Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

2014-03-01

The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were distinct from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. Copyright © 2013 Elsevier GmbH. All rights reserved.

Clustering of adherence to personalised dietary recommendations and changes in healthy eating index within the Food4Me study.

PubMed

Livingstone, Katherine M; Celis-Morales, Carlos; Lara, Jose; Woolhead, Clara; O'Donovan, Clare B; Forster, Hannah; Marsaux, Cyril Fm; Macready, Anna L; Fallaize, Rosalind; Navas-Carretero, Santiago; San-Cristobal, Rodrigo; Kolossa, Silvia; Tsirigoti, Lydia; Lambrinou, Christina P; Moschonis, George; Surwiłło, Agnieszka; Drevon, Christian A; Manios, Yannis; Traczyk, Iwona; Gibney, Eileen R; Brennan, Lorraine; Walsh, Marianne C; Lovegrove, Julie A; Martinez, J Alfredo; Saris, Wim Hm; Daniel, Hannelore; Gibney, Mike; Mathers, John C

2016-12-01

To characterise clusters of individuals based on adherence to dietary recommendations and to determine whether changes in Healthy Eating Index (HEI) scores in response to a personalised nutrition (PN) intervention varied between clusters. Food4Me study participants were clustered according to whether their baseline dietary intakes met European dietary recommendations. Changes in HEI scores between baseline and month 6 were compared between clusters and stratified by whether individuals received generalised or PN advice. Pan-European, Internet-based, 6-month randomised controlled trial. Adults aged 18-79 years (n 1480). Individuals in cluster 1 (C1) met all recommended intakes except for red meat, those in cluster 2 (C2) met two recommendations, and those in cluster 3 (C3) and cluster 4 (C4) met one recommendation each. C1 had higher intakes of white fish, beans and lentils and low-fat dairy products and lower percentage energy intake from SFA (P<0·05). C2 consumed less chips and pizza and fried foods than C3 and C4 (P<0·05). C1 were lighter, had lower BMI and waist circumference than C3 and were more physically active than C4 (P<0·05). More individuals in C4 were smokers and wanted to lose weight than in C1 (P<0·05). Individuals who received PN advice in C4 reported greater improvements in HEI compared with C3 and C1 (P<0·05). The cluster where the fewest recommendations were met (C4) reported greater improvements in HEI following a 6-month trial of PN whereas there was no difference between clusters for those randomised to the Control, non-personalised dietary intervention.

Towards Development of Clustering Applications for Large-Scale Comparative Genotyping and Kinship Analysis Using Y-Short Tandem Repeats.

PubMed

Seman, Ali; Sapawi, Azizian Mohd; Salleh, Mohd Zaki

2015-06-01

Y-chromosome short tandem repeats (Y-STRs) are genetic markers with practical applications in human identification. However, where mass identification is required (e.g., in the aftermath of disasters with significant fatalities), the efficiency of the process could be improved with new statistical approaches. Clustering applications are relatively new tools for large-scale comparative genotyping, and the k-Approximate Modal Haplotype (k-AMH), an efficient algorithm for clustering large-scale Y-STR data, represents a promising method for developing these tools. In this study we improved the k-AMH and produced three new algorithms: the Nk-AMH I (including a new initial cluster center selection), the Nk-AMH II (including a new dominant weighting value), and the Nk-AMH III (combining I and II). The Nk-AMH III was the superior algorithm, with mean clustering accuracy that increased in four out of six datasets and remained at 100% in the other two. Additionally, the Nk-AMH III achieved a 2% higher overall mean clustering accuracy score than the k-AMH, as well as optimal accuracy for all datasets (0.84-1.00). With inclusion of the two new methods, the Nk-AMH III produced an optimal solution for clustering Y-STR data; thus, the algorithm has potential for further development towards fully automatic clustering of any large-scale genotypic data.

antiSMASH 3.0-a comprehensive resource for the genome mining of biosynthetic gene clusters.

PubMed

Weber, Tilmann; Blin, Kai; Duddela, Srikanth; Krug, Daniel; Kim, Hyun Uk; Bruccoleri, Robert; Lee, Sang Yup; Fischbach, Michael A; Müller, Rolf; Wohlleben, Wolfgang; Breitling, Rainer; Takano, Eriko; Medema, Marnix H

2015-07-01

Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Optimizing weak lensing mass estimates for cluster profile uncertainty

DOE PAGES

Gruen, D.; Bernstein, G. M.; Lam, T. Y.; ...

2011-09-11

Weak lensing measurements of cluster masses are necessary for calibrating mass-observable relations (MORs) to investigate the growth of structure and the properties of dark energy. However, the measured cluster shear signal varies at fixed mass M 200m due to inherent ellipticity of background galaxies, intervening structures along the line of sight, and variations in the cluster structure due to scatter in concentrations, asphericity and substructure. We use N-body simulated halos to derive and evaluate a weak lensing circular aperture mass measurement M ap that minimizes the mass estimate variance <(M ap - M 200m) 2> in the presence of allmore » these forms of variability. Depending on halo mass and observational conditions, the resulting mass estimator improves on M ap filters optimized for circular NFW-profile clusters in the presence of uncorrelated large scale structure (LSS) about as much as the latter improve on an estimator that only minimizes the influence of shape noise. Optimizing for uncorrelated LSS while ignoring the variation of internal cluster structure puts too much weight on the profile near the cores of halos, and under some circumstances can even be worse than not accounting for LSS at all. As a result, we discuss the impact of variability in cluster structure and correlated structures on the design and performance of weak lensing surveys intended to calibrate cluster MORs.« less

Fuzzy C-mean clustering on kinetic parameter estimation with generalized linear least square algorithm in SPECT

NASA Astrophysics Data System (ADS)

Choi, Hon-Chit; Wen, Lingfeng; Eberl, Stefan; Feng, Dagan

2006-03-01

Dynamic Single Photon Emission Computed Tomography (SPECT) has the potential to quantitatively estimate physiological parameters by fitting compartment models to the tracer kinetics. The generalized linear least square method (GLLS) is an efficient method to estimate unbiased kinetic parameters and parametric images. However, due to the low sensitivity of SPECT, noisy data can cause voxel-wise parameter estimation by GLLS to fail. Fuzzy C-Mean (FCM) clustering and modified FCM, which also utilizes information from the immediate neighboring voxels, are proposed to improve the voxel-wise parameter estimation of GLLS. Monte Carlo simulations were performed to generate dynamic SPECT data with different noise levels and processed by general and modified FCM clustering. Parametric images were estimated by Logan and Yokoi graphical analysis and GLLS. The influx rate (K I), volume of distribution (V d) were estimated for the cerebellum, thalamus and frontal cortex. Our results show that (1) FCM reduces the bias and improves the reliability of parameter estimates for noisy data, (2) GLLS provides estimates of micro parameters (K I-k 4) as well as macro parameters, such as volume of distribution (Vd) and binding potential (BP I & BP II) and (3) FCM clustering incorporating neighboring voxel information does not improve the parameter estimates, but improves noise in the parametric images. These findings indicated that it is desirable for pre-segmentation with traditional FCM clustering to generate voxel-wise parametric images with GLLS from dynamic SPECT data.

Salmonella enterica Pulsed-Field Gel Electrophoresis Clusters, Minnesota, USA, 2001–2007

PubMed Central

Hedberg, Craig W.; Meyer, Stephanie; Boxrud, David J.; Smith, Kirk E.

2010-01-01

We determined characteristics of Salmonella enterica pulsed-field gel electrophoresis clusters that predict their being solved (i.e., that result in identification of a confirmed outbreak). Clusters were investigated by the Minnesota Department of Health by using a dynamic iterative model. During 2001–2007, a total of 43 (12.5%) of 344 clusters were solved. Clusters of >4 isolates were more likely to be solved than clusters of 2 isolates. Clusters in which the first 3 case isolates were received at the Minnesota Department of Health within 7 days were more likely to be solved than were clusters in which the first 3 case isolates were received over a period >14 days. If resources do not permit investigation of all S. enterica pulsed-field gel electrophoresis clusters, investigation of clusters of >4 cases and clusters in which the first 3 case isolates were received at a public health laboratory within 7 days may improve outbreak investigations. PMID:21029524

ICAP - An Interactive Cluster Analysis Procedure for analyzing remotely sensed data

NASA Technical Reports Server (NTRS)

Wharton, S. W.; Turner, B. J.

1981-01-01

An Interactive Cluster Analysis Procedure (ICAP) was developed to derive classifier training statistics from remotely sensed data. ICAP differs from conventional clustering algorithms by allowing the analyst to optimize the cluster configuration by inspection, rather than by manipulating process parameters. Control of the clustering process alternates between the algorithm, which creates new centroids and forms clusters, and the analyst, who can evaluate and elect to modify the cluster structure. Clusters can be deleted, or lumped together pairwise, or new centroids can be added. A summary of the cluster statistics can be requested to facilitate cluster manipulation. The principal advantage of this approach is that it allows prior information (when available) to be used directly in the analysis, since the analyst interacts with ICAP in a straightforward manner, using basic terms with which he is more likely to be familiar. Results from testing ICAP showed that an informed use of ICAP can improve classification, as compared to an existing cluster analysis procedure.

Open source clustering software.

PubMed

de Hoon, M J L; Imoto, S; Nolan, J; Miyano, S

2004-06-12

We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C. The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.

MODEL-FREE MULTI-PROBE LENSING RECONSTRUCTION OF CLUSTER MASS PROFILES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Umetsu, Keiichi

2013-05-20

Lens magnification by galaxy clusters induces characteristic spatial variations in the number counts of background sources, amplifying their observed fluxes and expanding the area of sky, the net effect of which, known as magnification bias, depends on the intrinsic faint-end slope of the source luminosity function. The bias is strongly negative for red galaxies, dominated by the geometric area distortion, whereas it is mildly positive for blue galaxies, enhancing the blue counts toward the cluster center. We generalize the Bayesian approach of Umetsu et al. for reconstructing projected cluster mass profiles, by incorporating multiple populations of background sources for magnification-biasmore » measurements and combining them with complementary lens-distortion measurements, effectively breaking the mass-sheet degeneracy and improving the statistical precision of cluster mass measurements. The approach can be further extended to include strong-lensing projected mass estimates, thus allowing for non-parametric absolute mass determinations in both the weak and strong regimes. We apply this method to our recent CLASH lensing measurements of MACS J1206.2-0847, and demonstrate how combining multi-probe lensing constraints can improve the reconstruction of cluster mass profiles. This method will also be useful for a stacked lensing analysis, combining all lensing-related effects in the cluster regime, for a definitive determination of the averaged mass profile.« less

Unlocking the secrets of Lake Clark sockeye salmon

USGS Publications Warehouse

Woody, Carol Ann

2003-01-01

Sockeye salmon are a cornerstone species in many Alaska watersheds. Each summer, adults lay eggs in rocky nests called “redds,” and they die soon after. In spring, their fry emerge from gravels and then rear in a nearby freshwater lake for one year or more before migrating as smolt to the sea. During this smolt phase, an olfactory map of their route is imprinted on their memories. Sockeye salmon spend one to four years in the ocean feeding and growing. Then, some innate cue sends them back in a mass migration to their natal lake systems, which they find using the olfactory map made years before. They complete their life cycle by spawning, then dying in habitats of their birth.

Hypnosis as sole anesthesia for major surgeries: historical & contemporary perspectives.

PubMed

Hammond, D Corydon

2008-10-01

Hypnosis is a well validated treatment for acute and chronic pain (Montgomery, DuHamel, & Redd, 2000). It has been found capable of reducing inflammation, altering blood flow, and producing beneficial effects when hypnotic suggestions are provided during and prior to surgery (Frederick, 2001) and other painful medical procedures. This paper quotes extensively from historical examples of the use of hypnosis (mesmerism) as the sole anesthesia for major surgeries in the 1800's. These historic examples by themselves provide powerful documentation of the ability of the mind to influence the body, but they are then followed by a review of contemporary literature and controlled research on the use in hypnosis in relation to surgery and prior to medical procedures.

Topic modeling for cluster analysis of large biological and medical datasets

PubMed Central

2014-01-01

Background The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. Results In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Conclusion Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets. PMID:25350106

Topic modeling for cluster analysis of large biological and medical datasets.

PubMed

Zhao, Weizhong; Zou, Wen; Chen, James J

2014-01-01

The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting that topic model-based methods could provide an analytic advancement in the analysis of large biological or medical datasets.

The structure of deposited metal clusters generated by laser evaporation

NASA Astrophysics Data System (ADS)

Faust, P.; Brandstättner, M.; Ding, A.

1991-09-01

Metal clusters have been produced using a laser evaporation source. A Nd-YAG laser beam focused onto a solid silver rod was used to evaporate the material, which was then cooled to form clusters with the help of a pulsed high pressure He beam. TOF mass spectra of these clusters reveal a strong occurrence of small and medium sized clusters ( n<100). Clusters were also deposited onto grid supported thin layers of carbon-films which were investigated by transmission electron microscopy. Very high resolution pictures of these grids were used to analyze the size distribution and the structure of the deposited clusters. The diffraction pattern caused by crystalline structure of the clusters reveals 3-and 5-fold symmetries as well as fcc bulk structure. This can be explained in terms of icosahedron and cuboctahedron type clusters deposited on the surface of the carbon layer. There is strong evidence that part of these cluster geometries had already been formed before the depostion process. The non-linear dependence of the cluster size and the cluster density on the generating conditions is discussed. Therefore the samples were observed in HREM in the stable DEEKO 100 microscope of the Fritz-Haber-Institut operating at 100 KV with the spherical aberration c S =0.5 mm. The quality of the pictures was improved by using the conditions of minimum phase contrast hollow cone illumination. This procedure led to a minimum of phase contrast artefacts. Among the well-crystallized particles were a great amount of five- and three-fold symmetries, icosahedra and cuboctahedra respectively. The largest clusters with five- and three-fold symmetries have been found with diameters of 7 nm; the smallest particles displaying the same undistorted symmetries were of about 2 mm. Even smaller ones with strong distortions could be observed although their classification is difficult. The quality of the images was improved by applying Fourier filtering techniques.

Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

NASA Astrophysics Data System (ADS)

Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

2017-11-01

In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

GLASS: The Grism Lens-Amplified Survey From Space. HST Grism Spectroscopy of the Frontier Fields

NASA Astrophysics Data System (ADS)

Schmidt, Kasper B.; Schmidt

The Grism Lens-Amplified Survey From Space (GLASS) is a 140 orbit spectroscopic survey of 10 massive galaxy clusters, including the six Hubble Frontier Fields. GLASS has observed the cluster cores with the HST-WFC3 G102 and G141 grisms providing a wide wavelength coverage in the near-infrared from roughly 0.8-1.7μm. The parallel fields were observed through the optical ACS G800L grism. Taking advantage of the lensing magnification of the clusters, GLASS reaches intrinsic spectroscopic 1σ flux limits of roughly 10-18erg/s/cm2 and improved spatial resolution for lensed sources behind the clusters. These features are particularly useful for the three main science drivers of GLASS which are, I) exploring the universe at the epoch of reionization, II) describe how metals cycle in and out of galaxies, and III) asses the environmental dependence of galaxy evolution. The former two benefit highly from the improved depth and increased resolution provided by the cluster lensing. Apart from the main science drivers, a slew of ancillary science has been enabled by the survey, including improving cluster lens modeling and searches for supernovae. Here we present the survey and the GLASS data releases, which are continuously being made available to the community through https://archive.stsci.edu/prepds/glass/. For further information we refer to Schmidt et al. (2014), Treu et al. (2015), and http://glass.physics.ucsb.edu.

Fast large-scale clustering of protein structures using Gauss integrals.

PubMed

Harder, Tim; Borg, Mikael; Boomsma, Wouter; Røgen, Peter; Hamelryck, Thomas

2012-02-15

Clustering protein structures is an important task in structural bioinformatics. De novo structure prediction, for example, often involves a clustering step for finding the best prediction. Other applications include assigning proteins to fold families and analyzing molecular dynamics trajectories. We present Pleiades, a novel approach to clustering protein structures with a rigorous mathematical underpinning. The method approximates clustering based on the root mean square deviation by first mapping structures to Gauss integral vectors--which were introduced by Røgen and co-workers--and subsequently performing K-means clustering. Compared to current methods, Pleiades dramatically improves on the time needed to perform clustering, and can cluster a significantly larger number of structures, while providing state-of-the-art results. The number of low energy structures generated in a typical folding study, which is in the order of 50,000 structures, can be clustered within seconds to minutes.

Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

PubMed

Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2013-07-01

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design and implementation of streaming media server cluster based on FFMpeg.

PubMed

Zhao, Hong; Zhou, Chun-long; Jin, Bao-zhao

2015-01-01

Poor performance and network congestion are commonly observed in the streaming media single server system. This paper proposes a scheme to construct a streaming media server cluster system based on FFMpeg. In this scheme, different users are distributed to different servers according to their locations and the balance among servers is maintained by the dynamic load-balancing algorithm based on active feedback. Furthermore, a service redirection algorithm is proposed to improve the transmission efficiency of streaming media data. The experiment results show that the server cluster system has significantly alleviated the network congestion and improved the performance in comparison with the single server system.

Design and Implementation of Streaming Media Server Cluster Based on FFMpeg

PubMed Central

Zhao, Hong; Zhou, Chun-long; Jin, Bao-zhao

2015-01-01

Poor performance and network congestion are commonly observed in the streaming media single server system. This paper proposes a scheme to construct a streaming media server cluster system based on FFMpeg. In this scheme, different users are distributed to different servers according to their locations and the balance among servers is maintained by the dynamic load-balancing algorithm based on active feedback. Furthermore, a service redirection algorithm is proposed to improve the transmission efficiency of streaming media data. The experiment results show that the server cluster system has significantly alleviated the network congestion and improved the performance in comparison with the single server system. PMID:25734187

Cluster-void degeneracy breaking: Modified gravity in the balance

NASA Astrophysics Data System (ADS)

Sahlén, Martin; Silk, Joseph

2018-05-01

Combining galaxy cluster and void abundances is a novel, powerful way to constrain deviations from general relativity and the Λ CDM model. For a flat w CDM model with growth of large-scale structure parametrized by the redshift-dependent growth index γ (z )=γ0+γ1z /(1 +z ) of linear matter perturbations, combining void and cluster abundances in future surveys with Euclid and the four-meter multiobject spectroscopic telescope could improve the figure of merit for (w ,γ0,γ1) by a factor of 20 compared to individual abundances. In an ideal case, improvement on current cosmological data is a figure of merit factor 600 or more.

Application of Fuzzy c-Means and Joint-Feature-Clustering to Detect Redundancies of Image-Features in Drug Combinations Studies of Breast Cancer

NASA Astrophysics Data System (ADS)

Brandl, Miriam B.; Beck, Dominik; Pham, Tuan D.

2011-06-01

The high dimensionality of image-based dataset can be a drawback for classification accuracy. In this study, we propose the application of fuzzy c-means clustering, cluster validity indices and the notation of a joint-feature-clustering matrix to find redundancies of image-features. The introduced matrix indicates how frequently features are grouped in a mutual cluster. The resulting information can be used to find data-derived feature prototypes with a common biological meaning, reduce data storage as well as computation times and improve the classification accuracy.

Observing Globular Cluster RR Lyrae Variables with the BYU West Mountain Observatory

NASA Astrophysics Data System (ADS)

Jeffery, E. J.; Joner, M. D.

2016-06-01

We have utilized the 0.9-meter telescope of the Brigham Young University West Mountain Observatory to secure data on six northern hemisphere globular clusters. Here we present representative observations of RR Lyrae stars located in these clusters, including light curves. We compare light curves produced using both DAOPHOT and ISIS software packages. Light curve fitting is done with FITLC. We find that for well-separated stars, DAOPHOT and ISIS provide comparable results. However, for stars within the cluster core, ISIS provides superior results. These improved techniques will allow us to better measure the properties of cluster variable stars.

An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

PubMed

Botía, Juan A; Vandrovcova, Jana; Forabosco, Paola; Guelfi, Sebastian; D'Sa, Karishma; Hardy, John; Lewis, Cathryn M; Ryten, Mina; Weale, Michael E

2017-04-12

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn ). We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.

Clustering cancer gene expression data by projective clustering ensemble

PubMed Central

Yu, Xianxue; Yu, Guoxian

2017-01-01

Gene expression data analysis has paramount implications for gene treatments, cancer diagnosis and other domains. Clustering is an important and promising tool to analyze gene expression data. Gene expression data is often characterized by a large amount of genes but with limited samples, thus various projective clustering techniques and ensemble techniques have been suggested to combat with these challenges. However, it is rather challenging to synergy these two kinds of techniques together to avoid the curse of dimensionality problem and to boost the performance of gene expression data clustering. In this paper, we employ a projective clustering ensemble (PCE) to integrate the advantages of projective clustering and ensemble clustering, and to avoid the dilemma of combining multiple projective clusterings. Our experimental results on publicly available cancer gene expression data show PCE can improve the quality of clustering gene expression data by at least 4.5% (on average) than other related techniques, including dimensionality reduction based single clustering and ensemble approaches. The empirical study demonstrates that, to further boost the performance of clustering cancer gene expression data, it is necessary and promising to synergy projective clustering with ensemble clustering. PCE can serve as an effective alternative technique for clustering gene expression data. PMID:28234920

Density-based clustering of small peptide conformations sampled from a molecular dynamics simulation.

PubMed

Kim, Minkyoung; Choi, Seung-Hoon; Kim, Junhyoung; Choi, Kihang; Shin, Jae-Min; Kang, Sang-Kee; Choi, Yun-Jaie; Jung, Dong Hyun

2009-11-01

This study describes the application of a density-based algorithm to clustering small peptide conformations after a molecular dynamics simulation. We propose a clustering method for small peptide conformations that enables adjacent clusters to be separated more clearly on the basis of neighbor density. Neighbor density means the number of neighboring conformations, so if a conformation has too few neighboring conformations, then it is considered as noise or an outlier and is excluded from the list of cluster members. With this approach, we can easily identify clusters in which the members are densely crowded in the conformational space, and we can safely avoid misclustering individual clusters linked by noise or outliers. Consideration of neighbor density significantly improves the efficiency of clustering of small peptide conformations sampled from molecular dynamics simulations and can be used for predicting peptide structures.

Attitudes of local communities towards conservation of mangrove forests: A case study from the east coast of India

NASA Astrophysics Data System (ADS)

Badola, Ruchi; Barthwal, Shivani; Hussain, Syed Ainul

2012-01-01

The ecological and economic importance of mangrove ecosystems is well established and highlighted by studies establishing a correlation between the protective function of mangroves and the loss of lives and property caused by coastal hazards. Nevertheless, degradation of this ecosystem remains a matter of concern, emphasizing the fact that effective conservation of natural resources is possible only with an understanding of the attitudes and perceptions of local communities. In the present study, we examined the attitudes and perceptions of local communities towards mangrove forests through questionnaire surveys in 36 villages in the Bhitarkanika Conservation Area, India. The sample villages were selected from 336 villages using hierarchical cluster analysis. The study revealed that local communities in the area had positive attitudes towards conservation and that their demographic and socio-economic conditions influenced people's attitudes. Local communities valued those functions of mangrove forests that were directly linked to their wellbeing. Despite human-wildlife conflict, the attitudes of the local communities were not altogether negative, and they were willing to participate in mangrove restoration. People agreed to adopt alternative resources if access to forest resources were curtailed. Respondents living near the forests, who could not afford alternatives, admitted that they would resort to pilfering. Hence, increasing their livelihood options may reduce the pressure on mangrove forests. In contrast with other ecosystems, the linkages of mangrove ecosystem services with local livelihoods and security are direct and tangible. It is therefore possible to develop strong local support for sustainable management of mangrove forests in areas where a positive attitude towards mangrove conservation prevails. The current debates on Reducing Emissions from Deforestation and Forest Degradation (REDD) and payment for ecosystem services provide ample scope for development of sustainable livelihood options for local communities from the conservation of critical ecosystems such as mangroves.

The Antenatal Corticosteroids Trial (ACT): a secondary analysis to explore site differences in a multi-country trial.

PubMed

Klein, Karen; McClure, Elizabeth M; Colaci, Daniela; Thorsten, Vanessa; Hibberd, Patricia L; Esamai, Fabian; Garces, Ana; Patel, Archana; Saleem, Sarah; Pasha, Omrana; Chomba, Elwyn; Carlo, Waldemar A; Krebs, Nancy F; Goudar, Shivaprasad; Derman, Richard J; Liechty, Edward A; Koso-Thomas, Marion; Buekens, Pierre M; Belizán, José M; Goldenberg, Robert L; Althabe, Fernando

2016-05-24

The Antenatal Corticosteroid Trial (ACT) assessed the feasibility, effectiveness, and safety of a multifaceted intervention to increase the use of antenatal corticosteroids (ACS) in mothers at risk of preterm birth at all levels of care in low and middle-income countries. The intervention effectively increased the use of ACS but had no overall impact on neonatal mortality in the targeted <5(th) percentile birth weight infants. Being in the intervention clusters was also associated with an overall increase in neonatal deaths. We sought to explore plausible pathways through which this intervention increased neonatal mortality. We conducted secondary analyses to assess site differences in outcome and potential explanations for the differences in outcomes if found. By site, and in the intervention and control clusters, we evaluated characteristics of the mothers and care systems, the proportion of the <5(th) percentile infants and the overall population that received ACS, the rates of possible severe bacterial infection (pSBI), determined from clinical signs, and neonatal mortality rates. There were substantial differences between the sites in both participant and health system characteristics, with Guatemala and Argentina generally having the highest levels of care. In some sites there were substantial differences in the health system characteristics between the intervention and control clusters. The increase in ACS in the intervention clusters was similar among the sites. While overall, there was no difference in neonatal mortality among <5(th) percentile births between the intervention and control clusters, Guatemala and Pakistan both had significant reductions in neonatal mortality in the <5(th) percentile infants in the intervention clusters. The improvement in neonatal mortality in the Guatemalan site in the <5(th) percentile infants was associated with a higher level of care at the site and an improvement in care in the intervention clusters. There was a significant increase overall in neonatal mortality in the intervention clusters compared to the control. Across sites, this increase in neonatal mortality was statistically significant and most apparent in the African sites. This increase in neonatal mortality was accompanied by a significant increase in pSBI in the African sites. The improvement in neonatal mortality in the Guatemalan site in the <5(th) percentile infants was associated with a higher level of care and an improvement in care in the intervention clusters. The increase in neonatal mortality in the intervention clusters across all sites was largely driven by the poorer outcomes in the African sites, which also had an increase in pSBI in the intervention clusters. We emphasize that these results come from secondary analyses. Additional prospective studies are needed to assess the effectiveness and safety of ACS on neonatal health in low resource settings. clinicaltrials.gov (NCT01084096).

Probing potential Li-ion battery electrolyte through first principles simulation of atomic clusters

NASA Astrophysics Data System (ADS)

Kushwaha, Anoop Kumar; Sahoo, Mihir Ranjan; Nayak, Saroj

2018-04-01

Li-ion battery has wide area of application starting from low power consumer electronics to high power electric vehicles. However, their large scale application in electric vehicles requires further improvement due to their low specific power density which is an essential parameter and is closely related to the working potential windows of the battery system. Several studies have found that these parameters can be taken care of by considering different cathode/anode materials and electrolytes. Recently, a unique approach has been reported on the basis of cluster size in which the use of Li3 cluster has been suggested as a potential component of the battery electrode material. The cluster based approach significantly enhances the working electrode potential up to 0.6V in the acetonitrile solvent. In the present work, using ab-initio quantum chemical calculation and the dielectric continuum model, we have investigated various dielectric solvent medium for the suitable electrolyte for the potential component Li3 cluster. This study suggests that high dielectric electrolytic solvent (ethylene carbonate and propylene carbonate) could be better for lithium cluster due to improvement in the total electrode potential in comparison to the other dielectric solvent.

Discrete Wavelet Transform-Based Whole-Spectral and Subspectral Analysis for Improved Brain Tumor Clustering Using Single Voxel MR Spectroscopy.

PubMed

Yang, Guang; Nawaz, Tahir; Barrick, Thomas R; Howe, Franklyn A; Slabaugh, Greg

2015-12-01

Many approaches have been considered for automatic grading of brain tumors by means of pattern recognition with magnetic resonance spectroscopy (MRS). Providing an improved technique which can assist clinicians in accurately identifying brain tumor grades is our main objective. The proposed technique, which is based on the discrete wavelet transform (DWT) of whole-spectral or subspectral information of key metabolites, combined with unsupervised learning, inspects the separability of the extracted wavelet features from the MRS signal to aid the clustering. In total, we included 134 short echo time single voxel MRS spectra (SV MRS) in our study that cover normal controls, low grade and high grade tumors. The combination of DWT-based whole-spectral or subspectral analysis and unsupervised clustering achieved an overall clustering accuracy of 94.8% and a balanced error rate of 7.8%. To the best of our knowledge, it is the first study using DWT combined with unsupervised learning to cluster brain SV MRS. Instead of dimensionality reduction on SV MRS or feature selection using model fitting, our study provides an alternative method of extracting features to obtain promising clustering results.

Improved nonorthogonal tight-binding Hamiltonian for molecular-dynamics simulations of silicon clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ordejon, P.; Lebedenko, D.; Menon, M.

1994-08-15

We present an improvement over the nonorthogonal tight-binding molecular-dynamics scheme recently proposed by Menon and Subbaswamy [Phys. Rev. B 47, 12 754 (1993)]. The proper treatment of the nonorthogonality and its effect on the Hamiltonian matrix elements has been found to obviate the need for a bond-counting term, leaving only two adjustable parameters in the formalism. With the improved parametrization we obtain values of the energies and bonding distances which are in better agreement with the available [ital ab] [ital initio] results for clusters of size up to [ital N]=10. Additionally, we have identified a lowest energy structure for themore » Si[sub 9] cluster, which to our knowledge has not been considered to date. We show that this structure (a distorted tricapped trigonal prism with [ital C][sub 2[ital v

Visual cluster analysis and pattern recognition methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

2001-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Suppression of vacancy cluster growth in concentrated solid solution alloys

DOE PAGES

Zhao, Shijun; Velisa, Gihan; Xue, Haizhou; ...

2016-12-13

Large vacancy clusters, such as stacking-fault tetrahedra, are detrimental vacancy-type defects in ion-irradiated structural alloys. Suppression of vacancy cluster formation and growth is highly desirable to improve the irradiation tolerance of these materials. In this paper, we demonstrate that vacancy cluster growth can be inhibited in concentrated solid solution alloys by modifying cluster migration pathways and diffusion kinetics. The alloying effects of Fe and Cr on the migration of vacancy clusters in Ni concentrated alloys are investigated by molecular dynamics simulations and ion irradiation experiment. While the diffusion coefficients of small vacancy clusters in Ni-based binary and ternary solid solutionmore » alloys are higher than in pure Ni, they become lower for large clusters. This observation suggests that large clusters can easily migrate and grow to very large sizes in pure Ni. In contrast, cluster growth is suppressed in solid solution alloys owing to the limited mobility of large vacancy clusters. Finally, the differences in cluster sizes and mobilities in Ni and in solid solution alloys are consistent with the results from ion irradiation experiments.« less

A Review of Subsequence Time Series Clustering

PubMed Central

Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

A review of subsequence time series clustering.

PubMed

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

An improved initialization center k-means clustering algorithm based on distance and density

NASA Astrophysics Data System (ADS)

Duan, Yanling; Liu, Qun; Xia, Shuyin

2018-04-01

Aiming at the problem of the random initial clustering center of k means algorithm that the clustering results are influenced by outlier data sample and are unstable in multiple clustering, a method of central point initialization method based on larger distance and higher density is proposed. The reciprocal of the weighted average of distance is used to represent the sample density, and the data sample with the larger distance and the higher density are selected as the initial clustering centers to optimize the clustering results. Then, a clustering evaluation method based on distance and density is designed to verify the feasibility of the algorithm and the practicality, the experimental results on UCI data sets show that the algorithm has a certain stability and practicality.

Performance of cancer cluster Q-statistics for case-control residential histories

PubMed Central

Sloan, Chantel D.; Jacquez, Geoffrey M.; Gallagher, Carolyn M.; Ward, Mary H.; Raaschou-Nielsen, Ole; Nordsborg, Rikke Baastrup; Meliker, Jaymie R.

2012-01-01

Few investigations of health event clustering have evaluated residential mobility, though causative exposures for chronic diseases such as cancer often occur long before diagnosis. Recently developed Q-statistics incorporate human mobility into disease cluster investigations by quantifying space- and time-dependent nearest neighbor relationships. Using residential histories from two cancer case-control studies, we created simulated clusters to examine Q-statistic performance. Results suggest the intersection of cases with significant clustering over their life course, Qi, with cases who are constituents of significant local clusters at given times, Qit, yielded the best performance, which improved with increasing cluster size. Upon comparison, a larger proportion of true positives were detected with Kulldorf’s spatial scan method if the time of clustering was provided. We recommend using Q-statistics to identify when and where clustering may have occurred, followed by the scan method to localize the candidate clusters. Future work should investigate the generalizability of these findings. PMID:23149326

Microseismic Monitoring of Stimulating Shale Gas Reservoir in SW China: 2. Spatial Clustering Controlled by the Preexisting Faults and Fractures

NASA Astrophysics Data System (ADS)

Chen, Haichao; Meng, Xiaobo; Niu, Fenglin; Tang, Youcai; Yin, Chen; Wu, Furong

2018-02-01

Microseismic monitoring is crucial to improving stimulation efficiency of hydraulic fracturing treatment, as well as to mitigating potential induced seismic hazard. We applied an improved matching and locating technique to the downhole microseismic data set during one treatment stage along a horizontal well within the Weiyuan shale gas play inside Sichuan Basin in SW China, resulting in 3,052 well-located microseismic events. We employed this expanded catalog to investigate the spatiotemporal evolution of the microseismicity in order to constrain migration of the injected fluids and the associated dynamic processes. The microseismicity is generally characterized by two distinctly different clusters, both of which are highly correlated with the injection activity spatially and temporarily. The distant and well-confined cluster (cluster A) is featured by relatively large-magnitude events, with 40 events of M -1 or greater, whereas the cluster in the immediate vicinity of the wellbore (cluster B) includes two apparent lineations of seismicity with a NE-SW trending, consistent with the predominant orientation of natural fractures. We calculated the b-value and D-value, an index of fracture complexity, and found significant differences between the two seismicity clusters. Particularly, the distant cluster showed an extremely low b-value ( 0.47) and D-value ( 1.35). We speculate that the distant cluster is triggered by reactivation of a preexisting critically stressed fault, whereas the two lineations are induced by shear failures of optimally oriented natural fractures associated with fluid diffusion. In both cases, the spatially clustered microseismicity related to hydraulic stimulation is strongly controlled by the preexisting faults and fractures.

An energy-efficient and compact clustering scheme with temporary support nodes for cognitive radio sensor networks.

PubMed

Salim, Shelly; Moh, Sangman; Choi, Dongmin; Chung, Ilyong

2014-08-11

A cognitive radio sensor network (CRSN) is a wireless sensor network whose sensor nodes are equipped with cognitive radio capability. Clustering is one of the most challenging issues in CRSNs, as all sensor nodes, including the cluster head, have to use the same frequency band in order to form a cluster. However, due to the nature of heterogeneous channels in cognitive radio, it is difficult for sensor nodes to find a cluster head. This paper proposes a novel energy-efficient and compact clustering scheme named clustering with temporary support nodes (CENTRE). CENTRE efficiently achieves a compact cluster formation by adopting two-phase cluster formation with fixed duration. By introducing a novel concept of temporary support nodes to improve the cluster formation, the proposed scheme enables sensor nodes in a network to find a cluster head efficiently. The performance study shows that not only is the clustering process efficient and compact but it also results in remarkable energy savings that prolong the overall network lifetime. In addition, the proposed scheme decreases both the clustering overhead and the average distance between cluster heads and their members.

An Energy-Efficient and Compact Clustering Scheme with Temporary Support Nodes for Cognitive Radio Sensor Networks

PubMed Central

Salim, Shelly; Moh, Sangman; Choi, Dongmin; Chung, Ilyong

2014-01-01

A cognitive radio sensor network (CRSN) is a wireless sensor network whose sensor nodes are equipped with cognitive radio capability. Clustering is one of the most challenging issues in CRSNs, as all sensor nodes, including the cluster head, have to use the same frequency band in order to form a cluster. However, due to the nature of heterogeneous channels in cognitive radio, it is difficult for sensor nodes to find a cluster head. This paper proposes a novel energy-efficient and compact clustering scheme named clustering with temporary support nodes (CENTRE). CENTRE efficiently achieves a compact cluster formation by adopting two-phase cluster formation with fixed duration. By introducing a novel concept of temporary support nodes to improve the cluster formation, the proposed scheme enables sensor nodes in a network to find a cluster head efficiently. The performance study shows that not only is the clustering process efficient and compact but it also results in remarkable energy savings that prolong the overall network lifetime. In addition, the proposed scheme decreases both the clustering overhead and the average distance between cluster heads and their members. PMID:25116905

Integrin Clustering Matters: A Review of Biomaterials Functionalized with Multivalent Integrin-Binding Ligands to Improve Cell Adhesion, Migration, Differentiation, Angiogenesis, and Biomedical Device Integration.

PubMed

Karimi, Fatemeh; O'Connor, Andrea J; Qiao, Greg G; Heath, Daniel E

2018-03-25

Material systems that exhibit tailored interactions with cells are a cornerstone of biomaterial and tissue engineering technologies. One method of achieving these tailored interactions is to biofunctionalize materials with peptide ligands that bind integrin receptors present on the cell surface. However, cell biology research has illustrated that both integrin binding and integrin clustering are required to achieve a full adhesion response. This biophysical knowledge has motivated researchers to develop material systems biofunctionalized with nanoscale clusters of ligands that promote both integrin occupancy and clustering of the receptors. These materials have improved a wide variety of biological interactions in vitro including cell adhesion, proliferation, migration speed, gene expression, and stem cell differentiation; and improved in vivo outcomes including increased angiogenesis, tissue healing, and biomedical device integration. This review first introduces the techniques that enable the fabrication of these nanopatterned materials, describes the improved biological effects that have been achieved, and lastly discusses the current limitations of the technology and where future advances may occur. Although this technology is still in its nascency, it will undoubtedly play an important role in the future development of biomaterials and tissue engineering scaffolds for both in vitro and in vivo applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Surgeon-Specific Reports in General Surgery: Establishing Benchmarks for Peer Comparison Within a Single Hospital.

PubMed

Hatfield, Mark D; Ashton, Carol M; Bass, Barbara L; Shirkey, Beverly A

2016-02-01

Methods to assess a surgeon's individual performance based on clinically meaningful outcomes have not been fully developed, due to small numbers of adverse outcomes and wide variation in case volumes. The Achievable Benchmark of Care (ABC) method addresses these issues by identifying benchmark-setting surgeons with high levels of performance and greater case volumes. This method was used to help surgeons compare their surgical practice to that of their peers by using merged National Surgical Quality Improvement Program (NSQIP) and Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) data to generate surgeon-specific reports. A retrospective cohort study at a single institution's department of surgery was conducted involving 107 surgeons (8,660 cases) over 5.5 years. Stratification of more than 32,000 CPT codes into 16 CPT clusters served as the risk adjustment. Thirty-day outcomes of interest included surgical site infection (SSI), acute kidney injury (AKI), and mortality. Performance characteristics of the ABC method were explored by examining how many surgeons were identified as benchmark-setters in view of volume and outcome rates within CPT clusters. For the data captured, most surgeons performed cases spanning a median of 5 CPT clusters (range 1 to 15 clusters), with a median of 26 cases (range 1 to 776 cases) and a median of 2.8 years (range 0 to 5.5 years). The highest volume surgeon for that CPT cluster set the benchmark for 6 of 16 CPT clusters for SSIs, 8 of 16 CPT clusters for AKIs, and 9 of 16 CPT clusters for mortality. The ABC method appears to be a sound and useful approach to identifying benchmark-setting surgeons within a single institution. Such surgeons may be able to help their peers improve their performance. Copyright © 2016 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Improving estimation of kinetic parameters in dynamic force spectroscopy using cluster analysis

NASA Astrophysics Data System (ADS)

Yen, Chi-Fu; Sivasankar, Sanjeevi

2018-03-01

Dynamic Force Spectroscopy (DFS) is a widely used technique to characterize the dissociation kinetics and interaction energy landscape of receptor-ligand complexes with single-molecule resolution. In an Atomic Force Microscope (AFM)-based DFS experiment, receptor-ligand complexes, sandwiched between an AFM tip and substrate, are ruptured at different stress rates by varying the speed at which the AFM-tip and substrate are pulled away from each other. The rupture events are grouped according to their pulling speeds, and the mean force and loading rate of each group are calculated. These data are subsequently fit to established models, and energy landscape parameters such as the intrinsic off-rate (koff) and the width of the potential energy barrier (xβ) are extracted. However, due to large uncertainties in determining mean forces and loading rates of the groups, errors in the estimated koff and xβ can be substantial. Here, we demonstrate that the accuracy of fitted parameters in a DFS experiment can be dramatically improved by sorting rupture events into groups using cluster analysis instead of sorting them according to their pulling speeds. We test different clustering algorithms including Gaussian mixture, logistic regression, and K-means clustering, under conditions that closely mimic DFS experiments. Using Monte Carlo simulations, we benchmark the performance of these clustering algorithms over a wide range of koff and xβ, under different levels of thermal noise, and as a function of both the number of unbinding events and the number of pulling speeds. Our results demonstrate that cluster analysis, particularly K-means clustering, is very effective in improving the accuracy of parameter estimation, particularly when the number of unbinding events are limited and not well separated into distinct groups. Cluster analysis is easy to implement, and our performance benchmarks serve as a guide in choosing an appropriate method for DFS data analysis.

See Change: the Supernova Sample from the Supernova Cosmology Project High Redshift Cluster Supernova Survey

NASA Astrophysics Data System (ADS)

Hayden, Brian; Perlmutter, Saul; Boone, Kyle; Nordin, Jakob; Rubin, David; Lidman, Chris; Deustua, Susana E.; Fruchter, Andrew S.; Aldering, Greg Scott; Brodwin, Mark; Cunha, Carlos E.; Eisenhardt, Peter R.; Gonzalez, Anthony H.; Jee, James; Hildebrandt, Hendrik; Hoekstra, Henk; Santos, Joana; Stanford, S. Adam; Stern, Daniel; Fassbender, Rene; Richard, Johan; Rosati, Piero; Wechsler, Risa H.; Muzzin, Adam; Willis, Jon; Boehringer, Hans; Gladders, Michael; Goobar, Ariel; Amanullah, Rahman; Hook, Isobel; Huterer, Dragan; Huang, Xiaosheng; Kim, Alex G.; Kowalski, Marek; Linder, Eric; Pain, Reynald; Saunders, Clare; Suzuki, Nao; Barbary, Kyle H.; Rykoff, Eli S.; Meyers, Joshua; Spadafora, Anthony L.; Sofiatti, Caroline; Wilson, Gillian; Rozo, Eduardo; Hilton, Matt; Ruiz-Lapuente, Pilar; Luther, Kyle; Yen, Mike; Fagrelius, Parker; Dixon, Samantha; Williams, Steven

2017-01-01

The Supernova Cosmology Project has finished executing a large (174 orbits, cycles 22-23) Hubble Space Telescope program, which has measured ~30 type Ia Supernovae above z~1 in the highest-redshift, most massive galaxy clusters known to date. Our SN Ia sample closely matches our pre-survey predictions; this sample will improve the constraint by a factor of 3 on the Dark Energy equation of state above z~1, allowing an unprecedented probe of Dark Energy time variation. When combined with the improved cluster mass calibration from gravitational lensing provided by the deep WFC3-IR observations of the clusters, See Change will triple the Dark Energy Task Force Figure of Merit. With the primary observing campaign completed, we present the preliminary supernova sample and our path forward to the supernova cosmology results. We also compare the number of SNe Ia discovered in each cluster with our pre-survey expectations based on cluster mass and SFR estimates. Our extensive HST and ground-based campaign has already produced unique results; we have confirmed several of the highest redshift cluster members known to date, confirmed the redshift of one of the most massive galaxy clusters at z~1.2 expected across the entire sky, and characterized one of the most extreme starburst environments yet known in a z~1.7 cluster. We have also discovered a lensed SN Ia at z=2.22 magnified by a factor of ~2.7, which is the highest spectroscopic redshift SN Ia currently known.

Cognitive-behavioral conjoint therapy for PTSD improves various PTSD symptoms and trauma-related cognitions: Results from a randomized controlled trial.

PubMed

Macdonald, Alexandra; Pukay-Martin, Nicole D; Wagner, Anne C; Fredman, Steffany J; Monson, Candice M

2016-02-01

Numerous studies document an association between posttraumatic stress disorder (PTSD) and impairments in intimate relationship functioning, and there is evidence that PTSD symptoms and associated impairments are improved by cognitive-behavioral conjoint therapy for PTSD (CBCT for PTSD; Monson & Fredman, 2012). The present study investigated changes across treatment in clinician-rated PTSD symptom clusters and patient-rated trauma-related cognitions in a randomized controlled trial comparing CBCT for PTSD with waitlist in a sample of 40 individuals with PTSD and their partners (N = 40; Monson et al., 2012). Compared with waitlist, patients who received CBCT for PTSD immediately demonstrated greater improvements in all PTSD symptom clusters, trauma-related beliefs, and guilt cognitions (Hedge's gs -.33 to -1.51). Results suggest that CBCT for PTSD improves all PTSD symptom clusters and trauma-related cognitions among individuals with PTSD and further supports the value of utilizing a couple-based approach to the treatment of PTSD. (c) 2016 APA, all rights reserved).

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

1999-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Accurate Grid-based Clustering Algorithm with Diagonal Grid Searching and Merging

NASA Astrophysics Data System (ADS)

Liu, Feng; Ye, Chengcheng; Zhu, Erzhou

2017-09-01

Due to the advent of big data, data mining technology has attracted more and more attentions. As an important data analysis method, grid clustering algorithm is fast but with relatively lower accuracy. This paper presents an improved clustering algorithm combined with grid and density parameters. The algorithm first divides the data space into the valid meshes and invalid meshes through grid parameters. Secondly, from the starting point located at the first point of the diagonal of the grids, the algorithm takes the direction of “horizontal right, vertical down” to merge the valid meshes. Furthermore, by the boundary grid processing, the invalid grids are searched and merged when the adjacent left, above, and diagonal-direction grids are all the valid ones. By doing this, the accuracy of clustering is improved. The experimental results have shown that the proposed algorithm is accuracy and relatively faster when compared with some popularly used algorithms.

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

Size-guided multi-seed heuristic method for geometry optimization of clusters: Application to benzene clusters.

PubMed

Takeuchi, Hiroshi

2018-05-08

Since searching for the global minimum on the potential energy surface of a cluster is very difficult, many geometry optimization methods have been proposed, in which initial geometries are randomly generated and subsequently improved with different algorithms. In this study, a size-guided multi-seed heuristic method is developed and applied to benzene clusters. It produces initial configurations of the cluster with n molecules from the lowest-energy configurations of the cluster with n - 1 molecules (seeds). The initial geometries are further optimized with the geometrical perturbations previously used for molecular clusters. These steps are repeated until the size n satisfies a predefined one. The method locates putative global minima of benzene clusters with up to 65 molecules. The performance of the method is discussed using the computational cost, rates to locate the global minima, and energies of initial geometries. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Influence of the Hyporheic Zone on Supersaturated Gas Exposure to Incubating Chum Salmon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arntzen, Evan V.; Geist, David R.; Murray, Katherine J.

2009-12-01

Supersaturated total dissolved gas (TDG) is elevated seasonally in the lower Columbia River, with surface water concentrations approaching 120% saturation of TDG. Chum salmon (Oncorhynchus keta) embryos incubating in nearby spawning areas could be affected if depth-compensated TDG concentrations within the hyporheic zone exceed 103% TDG. The objective of this study was to determine if TDG of the hyporheic zone in two chum salmon spawning areas -- one in a side channel near Ives Island, Washington, and another on the mainstem Columbia River near Multnomah Falls, Oregon -- was affected by the elevated TDG of the surface water. Depth-compensated hyporheicmore » TDG did not exceed 103% at the Multnomah Falls site. However, in the Ives Island area, chum salmon redds were exposed to TDG greater than 103% for more than 600 hours. In response to river depth fluctuations, TDG varied significantly in the Ives Island area, suggesting increased interaction between the hyporheic zone and surface water at that site. We conclude from this study that the interaction between surface water and the hyporheic zone affects the concentration of TDG within the hyporheic zone directly via physical mixing as well as indirectly by altering water chemistry and thus dissolved gas solubility. These interactions are important considerations when estimating TDG exposure within egg pocket environments, facilitating improved exposure estimates, and enabling managers to optimize recovery strategies.« less

Depth-dependent hydraulic roughness and its impact on the assessment of hydropeaking.

PubMed

Kopecki, Ianina; Schneider, Matthias; Tuhtan, Jeffrey A

2017-01-01

Hydrodynamic river models in combination with physical habitat modelling serve as the basis for a wide spectrum of environmental studies. Larvae, juvenile and spawning fish, redds and benthic invertebrates belong to the biological groups most heavily affected by rapid flow variations as a consequence of peaking energy production, or "hydropeaking". As these species find their preferential habitat to a great extent in shallow regions, high prediction accuracy for these areas is essential to substantiate the use of hydrodynamic models. In this paper, a new formulation for the depth-dependent roughness originating from the boundary layer theory is derived. The modelling approach is based on the concept of a dynamic, spatio-temporal Manning's roughness which allows for considerable improvement in the accuracy of stationary and highly transient hydrodynamic simulations in shallow river areas. In addition, the approach facilitates more effective model calibration, as it allows for the preservation of the roughness sublayer thickness as a single calibration parameter for the entire range of hydropeaking discharges. The approach is tested and validated on a 7.5km long stretch of a middle-size gravel river affected by hydropeaking. Model results using conventional constant roughness and the proposed dynamic roughness approaches are compared. The implications for the stationary habitat assessment and calculation of dynamic hydropeaking parameters are analysed as well. Copyright © 2016 Elsevier B.V. All rights reserved.

Implementation of client versus care-provider strategies to improve external cephalic version rates: a cluster randomized controlled trial.

PubMed

Vlemmix, Floortje; Rosman, Ageeth N; Rijnders, Marlies E; Beuckens, Antje; Opmeer, Brent C; Mol, Ben W J; Kok, Marjolein; Fleuren, Margot A H

2015-05-01

To determine the effectiveness of a client or care-provider strategy to improve the implementation of external cephalic version. Cluster randomized controlled trial. Twenty-five clusters; hospitals and their referring midwifery practices randomly selected in the Netherlands. Singleton breech presentation from 32 weeks of gestation onwards. We randomized clusters to a client strategy (written information leaflets and decision aid), a care-provider strategy (1-day counseling course focused on knowledge and counseling skills), a combined client and care-provider strategy and care-as-usual strategy. We performed an intention-to-treat analysis. Rate of external cephalic version in various strategies. Secondary outcomes were the percentage of women counseled and opting for a version attempt. The overall implementation rate of external cephalic version was 72% (1169 of 1613 eligible clients) with a range between clusters of 8-95%. Neither the client strategy (OR 0.8, 95% CI 0.4-1.5) nor the care-provider strategy (OR 1.2, 95% CI 0.6-2.3) showed significant improvements. Results were comparable when we limited the analysis to those women who were actually offered intervention (OR 0.6, 95% CI 0.3-1.4 and OR 2.0, 95% CI 0.7-4.5). Neither a client nor a care-provider strategy improved the external cephalic version implementation rate for breech presentation, neither with regard to the number of version attempts offered nor the number of women accepting the procedure. © 2015 Nordic Federation of Societies of Obstetrics and Gynecology.

Novel multiresolution mammographic density segmentation using pseudo 3D features and adaptive cluster merging

NASA Astrophysics Data System (ADS)

He, Wenda; Juette, Arne; Denton, Erica R. E.; Zwiggelaar, Reyer

2015-03-01

Breast cancer is the most frequently diagnosed cancer in women. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective ways to overcome the disease. Successful mammographic density segmentation is a key aspect in deriving correct tissue composition, ensuring an accurate mammographic risk assessment. However, mammographic densities have not yet been fully incorporated with non-image based risk prediction models, (e.g. the Gail and the Tyrer-Cuzick model), because of unreliable segmentation consistency and accuracy. This paper presents a novel multiresolution mammographic density segmentation, a concept of stack representation is proposed, and 3D texture features were extracted by adapting techniques based on classic 2D first-order statistics. An unsupervised clustering technique was employed to achieve mammographic segmentation, in which two improvements were made; 1) consistent segmentation by incorporating an optimal centroids initialisation step, and 2) significantly reduced the number of missegmentation by using an adaptive cluster merging technique. A set of full field digital mammograms was used in the evaluation. Visual assessment indicated substantial improvement on segmented anatomical structures and tissue specific areas, especially in low mammographic density categories. The developed method demonstrated an ability to improve the quality of mammographic segmentation via clustering, and results indicated an improvement of 26% in segmented image with good quality when compared with the standard clustering approach. This in turn can be found useful in early breast cancer detection, risk-stratified screening, and aiding radiologists in the process of decision making prior to surgery and/or treatment.

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-07-01

In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed yielding an explict cluster attribution for each particle, improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Multiscale visual quality assessment for cluster analysis with self-organizing maps

NASA Astrophysics Data System (ADS)

Bernard, Jürgen; von Landesberger, Tatiana; Bremm, Sebastian; Schreck, Tobias

2011-01-01

Cluster analysis is an important data mining technique for analyzing large amounts of data, reducing many objects to a limited number of clusters. Cluster visualization techniques aim at supporting the user in better understanding the characteristics and relationships among the found clusters. While promising approaches to visual cluster analysis already exist, these usually fall short of incorporating the quality of the obtained clustering results. However, due to the nature of the clustering process, quality plays an important aspect, as for most practical data sets, typically many different clusterings are possible. Being aware of clustering quality is important to judge the expressiveness of a given cluster visualization, or to adjust the clustering process with refined parameters, among others. In this work, we present an encompassing suite of visual tools for quality assessment of an important visual cluster algorithm, namely, the Self-Organizing Map (SOM) technique. We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar-valued quality scores up to the structural comparison of a given SOM clustering with output of additional supportive clustering methods. The suite of methods allows the user to assess the SOM quality on the appropriate abstraction level, and arrive at improved clustering results. We implement our tools in an integrated system, apply it on experimental data sets, and show its applicability.

An Energy Centric Cluster-Based Routing Protocol for Wireless Sensor Networks.

PubMed

Hosen, A S M Sanwar; Cho, Gi Hwan

2018-05-11

Clustering is an effective way to prolong the lifetime of a wireless sensor network (WSN). The common approach is to elect cluster heads to take routing and controlling duty, and to periodically rotate each cluster head's role to distribute energy consumption among nodes. However, a significant amount of energy dissipates due to control messages overhead, which results in a shorter network lifetime. This paper proposes an energy-centric cluster-based routing mechanism in WSNs. To begin with, cluster heads are elected based on the higher ranks of the nodes. The rank is defined by residual energy and average distance from the member nodes. With the role of data aggregation and data forwarding, a cluster head acts as a caretaker for cluster-head election in the next round, where the ranks' information are piggybacked along with the local data sending during intra-cluster communication. This reduces the number of control messages for the cluster-head election as well as the cluster formation in detail. Simulation results show that our proposed protocol saves the energy consumption among nodes and achieves a significant improvement in the network lifetime.

An Energy Centric Cluster-Based Routing Protocol for Wireless Sensor Networks

PubMed Central

Hosen, A. S. M. Sanwar; Cho, Gi Hwan

2018-01-01

Clustering is an effective way to prolong the lifetime of a wireless sensor network (WSN). The common approach is to elect cluster heads to take routing and controlling duty, and to periodically rotate each cluster head’s role to distribute energy consumption among nodes. However, a significant amount of energy dissipates due to control messages overhead, which results in a shorter network lifetime. This paper proposes an energy-centric cluster-based routing mechanism in WSNs. To begin with, cluster heads are elected based on the higher ranks of the nodes. The rank is defined by residual energy and average distance from the member nodes. With the role of data aggregation and data forwarding, a cluster head acts as a caretaker for cluster-head election in the next round, where the ranks’ information are piggybacked along with the local data sending during intra-cluster communication. This reduces the number of control messages for the cluster-head election as well as the cluster formation in detail. Simulation results show that our proposed protocol saves the energy consumption among nodes and achieves a significant improvement in the network lifetime. PMID:29751663

Photo-induced transformation process at gold clusters-semiconductor interface: Implications for the complexity of gold clusters-based photocatalysis

NASA Astrophysics Data System (ADS)

Liu, Siqi; Xu, Yi-Jun

2016-03-01

The recent thrust in utilizing atomically precise organic ligands protected gold clusters (Au clusters) as photosensitizer coupled with semiconductors for nano-catalysts has led to the claims of improved efficiency in photocatalysis. Nonetheless, the influence of photo-stability of organic ligands protected-Au clusters at the Au/semiconductor interface on the photocatalytic properties remains rather elusive. Taking Au clusters-TiO2 composites as a prototype, we for the first time demonstrate the photo-induced transformation of small molecular-like Au clusters to larger metallic Au nanoparticles under different illumination conditions, which leads to the diverse photocatalytic reaction mechanism. This transformation process undergoes a diffusion/aggregation mechanism accompanied with the onslaught of Au clusters by active oxygen species and holes resulting from photo-excited TiO2 and Au clusters. However, such Au clusters aggregation can be efficiently inhibited by tuning reaction conditions. This work would trigger rational structural design and fine condition control of organic ligands protected-metal clusters-semiconductor composites for diverse photocatalytic applications with long-term photo-stability.

Application of adaptive cluster sampling to low-density populations of freshwater mussels

USGS Publications Warehouse

Smith, D.R.; Villella, R.F.; Lemarie, D.P.

2003-01-01

Freshwater mussels appear to be promising candidates for adaptive cluster sampling because they are benthic macroinvertebrates that cluster spatially and are frequently found at low densities. We applied adaptive cluster sampling to estimate density of freshwater mussels at 24 sites along the Cacapon River, WV, where a preliminary timed search indicated that mussels were present at low density. Adaptive cluster sampling increased yield of individual mussels and detection of uncommon species; however, it did not improve precision of density estimates. Because finding uncommon species, collecting individuals of those species, and estimating their densities are important conservation activities, additional research is warranted on application of adaptive cluster sampling to freshwater mussels. However, at this time we do not recommend routine application of adaptive cluster sampling to freshwater mussel populations. The ultimate, and currently unanswered, question is how to tell when adaptive cluster sampling should be used, i.e., when is a population sufficiently rare and clustered for adaptive cluster sampling to be efficient and practical? A cost-effective procedure needs to be developed to identify biological populations for which adaptive cluster sampling is appropriate.

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

PubMed Central

Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

2015-01-01

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

PubMed

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

Social and Behavioral Risk Marker Clustering Associated with Biological Risk Factors for Coronary Heart Disease: NHANES 2001–2004

PubMed Central

Everage, Nicholas J.; Linkletter, Crystal D.; Gjelsvik, Annie; McGarvey, Stephen T.; Loucks, Eric B.

2014-01-01

Background. Social and behavioral risk markers (e.g., physical activity, diet, smoking, and socioeconomic position) cluster; however, little is known whether clustering is associated with coronary heart disease (CHD) risk. Objectives were to determine if sociobehavioral clustering is associated with biological CHD risk factors (total cholesterol, HDL cholesterol, systolic blood pressure, body mass index, waist circumference, and diabetes) and whether associations are independent of individual clustering components. Methods. Participants included 4,305 males and 4,673 females aged ≥20 years from NHANES 2001–2004. Sociobehavioral Risk Marker Index (SRI) included a summary score of physical activity, fruit/vegetable consumption, smoking, and educational attainment. Regression analyses evaluated associations of SRI with aforementioned biological CHD risk factors. Receiver operator curve analyses assessed independent predictive ability of SRI. Results. Healthful clustering (SRI = 0) was associated with improved biological CHD risk factor levels in 5 of 6 risk factors in females and 2 of 6 risk factors in males. Adding SRI to models containing age, race, and individual SRI components did not improve C-statistics. Conclusions. Findings suggest that healthful sociobehavioral risk marker clustering is associated with favorable CHD risk factor levels, particularly in females. These findings should inform social ecological interventions that consider health impacts of addressing social and behavioral risk factors. PMID:24719858

Relating anomaly correlation to lead time: Clustering analysis of CFSv2 forecasts of summer precipitation in China

NASA Astrophysics Data System (ADS)

Zhao, Tongtiegang; Liu, Pan; Zhang, Yongyong; Ruan, Chengqing

2017-09-01

Global climate model (GCM) forecasts are an integral part of long-range hydroclimatic forecasting. We propose to use clustering to explore anomaly correlation, which indicates the performance of raw GCM forecasts, in the three-dimensional space of latitude, longitude, and initialization time. Focusing on a certain period of the year, correlations for forecasts initialized at different preceding periods form a vector. The vectors of anomaly correlation across different GCM grid cells are clustered to reveal how GCM forecasts perform as time progresses. Through the case study of Climate Forecast System Version 2 (CFSv2) forecasts of summer precipitation in China, we observe that the correlation at a certain cell oscillates with lead time and can become negative. The use of clustering reveals two meaningful patterns that characterize the relationship between anomaly correlation and lead time. For some grid cells in Central and Southwest China, CFSv2 forecasts exhibit positive correlations with observations and they tend to improve as time progresses. This result suggests that CFSv2 forecasts tend to capture the summer precipitation induced by the East Asian monsoon and the South Asian monsoon. It also indicates that CFSv2 forecasts can potentially be applied to improving hydrological forecasts in these regions. For some other cells, the correlations are generally close to zero at different lead times. This outcome implies that CFSv2 forecasts still have plenty of room for further improvement. The robustness of the patterns has been tested using both hierarchical clustering and k-means clustering and examined with the Silhouette score.

Efficient Deployment of Key Nodes for Optimal Coverage of Industrial Mobile Wireless Networks

PubMed Central

Li, Xiaomin; Li, Di; Dong, Zhijie; Hu, Yage; Liu, Chengliang

2018-01-01

In recent years, industrial wireless networks (IWNs) have been transformed by the introduction of mobile nodes, and they now offer increased extensibility, mobility, and flexibility. Nevertheless, mobile nodes pose efficiency and reliability challenges. Efficient node deployment and management of channel interference directly affect network system performance, particularly for key node placement in clustered wireless networks. This study analyzes this system model, considering both industrial properties of wireless networks and their mobility. Then, static and mobile node coverage problems are unified and simplified to target coverage problems. We propose a novel strategy for the deployment of clustered heads in grouped industrial mobile wireless networks (IMWNs) based on the improved maximal clique model and the iterative computation of new candidate cluster head positions. The maximal cliques are obtained via a double-layer Tabu search. Each cluster head updates its new position via an improved virtual force while moving with full coverage to find the minimal inter-cluster interference. Finally, we develop a simulation environment. The simulation results, based on a performance comparison, show the efficacy of the proposed strategies and their superiority over current approaches. PMID:29439439

Amplification of the entire kanamycin biosynthetic gene cluster during empirical strain improvement of Streptomyces kanamyceticus.

PubMed

Yanai, Koji; Murakami, Takeshi; Bibb, Mervyn

2006-06-20

Streptomyces kanamyceticus 12-6 is a derivative of the wild-type strain developed for industrial kanamycin (Km) production. Southern analysis and DNA sequencing revealed amplification of a large genomic segment including the entire Km biosynthetic gene cluster in the chromosome of strain 12-6. At 145 kb, the amplifiable unit of DNA (AUD) is the largest AUD reported in Streptomyces. Striking repetitive DNA sequences belonging to the clustered regularly interspaced short palindromic repeats family were found in the AUD and may play a role in its amplification. Strain 12-6 contains a mixture of different chromosomes with varying numbers of AUDs, sometimes exceeding 36 copies and producing an amplified region >5.7 Mb. The level of Km production depended on the copy number of the Km biosynthetic gene cluster, suggesting that DNA amplification occurred during strain improvement as a consequence of selection for increased Km resistance. Amplification of DNA segments including entire antibiotic biosynthetic gene clusters might be a common mechanism leading to increased antibiotic production in industrial strains.

The Canadian Preterm Birth Network: a study protocol for improving outcomes for preterm infants and their families

PubMed Central

Shah, Prakesh S.; McDonald, Sarah D.; Barrett, Jon; Synnes, Anne; Robson, Kate; Foster, Jonathan; Pasquier, Jean-Charles; Joseph, K.S.; Piedboeuf, Bruno; Lacaze-Masmonteil, Thierry; O'Brien, Karel; Shivananda, Sandesh; Chaillet, Nils; Pechlivanoglou, Petros

2018-01-01

Background: Preterm birth (birth before 37 wk of gestation) occurs in about 8% of pregnancies in Canada and is associated with high mortality and morbidity rates that substantially affect infants, their families and the health care system. Our overall goal is to create a transdisciplinary platform, the Canadian Preterm Birth Network (CPTBN), where investigators, stakeholders and families will work together to improve childhood outcomes of preterm neonates. Methods: Our national cohort will include 24 maternal-fetal/obstetrical units, 31 neonatal intensive care units and 26 neonatal follow-up programs across Canada with planned linkages to provincial health information systems. Three broad clusters of projects will be undertaken. Cluster 1 will focus on quality-improvement efforts that use the Evidence-based Practice for Improving Quality method to evaluate information from the CPTBN database and review the current literature, then identify potentially better health care practices and implement identified strategies. Cluster 2 will assess the impact of current practices and practice changes in maternal, perinatal and neonatal care on maternal, neonatal and neurodevelopmental outcomes. Cluster 3 will evaluate the effect of preterm birth on babies, their families and the health care system by integrating CPTBN data, parent feedback, and national and provincial database information in order to identify areas where more parental support is needed, and also generate robust estimates of resource use, cost and cost-effectiveness around preterm neonatal care. Interpretation: These collaborative efforts will create a flexible, transdisciplinary, evaluable and informative research and quality-improvement platform that supports programs, projects and partnerships focused on improving outcomes of preterm neonates. PMID:29348260

Critical Analysis of Cluster Models and Exchange-Correlation Functionals for Calculating Magnetic Shielding in Molecular Solids.

PubMed

Holmes, Sean T; Iuliucci, Robbie J; Mueller, Karl T; Dybowski, Cecil

2015-11-10

Calculations of the principal components of magnetic-shielding tensors in crystalline solids require the inclusion of the effects of lattice structure on the local electronic environment to obtain significant agreement with experimental NMR measurements. We assess periodic (GIPAW) and GIAO/symmetry-adapted cluster (SAC) models for computing magnetic-shielding tensors by calculations on a test set containing 72 insulating molecular solids, with a total of 393 principal components of chemical-shift tensors from 13C, 15N, 19F, and 31P sites. When clusters are carefully designed to represent the local solid-state environment and when periodic calculations include sufficient variability, both methods predict magnetic-shielding tensors that agree well with experimental chemical-shift values, demonstrating the correspondence of the two computational techniques. At the basis-set limit, we find that the small differences in the computed values have no statistical significance for three of the four nuclides considered. Subsequently, we explore the effects of additional DFT methods available only with the GIAO/cluster approach, particularly the use of hybrid-GGA functionals, meta-GGA functionals, and hybrid meta-GGA functionals that demonstrate improved agreement in calculations on symmetry-adapted clusters. We demonstrate that meta-GGA functionals improve computed NMR parameters over those obtained by GGA functionals in all cases, and that hybrid functionals improve computed results over the respective pure DFT functional for all nuclides except 15N.

Graph Based Models for Unsupervised High Dimensional Data Clustering and Network Analysis

DTIC Science & Technology

2015-01-01

ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for...algorithms we proposed improve the time e ciency signi cantly for large scale datasets. In the last chapter, we also propose an incremental reseeding...plume detection in hyper-spectral video data. These graph based clustering algorithms we proposed improve the time efficiency significantly for large

New output improvements for CLASSY

NASA Technical Reports Server (NTRS)

Rassbach, M. E. (Principal Investigator)

1981-01-01

Additional output data and formats for the CLASSY clustering algorithm were developed. Four such aids to the CLASSY user are described. These are: (1) statistical measures; (2) special map types; (3) formats for standard output; and (4) special cluster display method.

Stochastic coupled cluster theory: Efficient sampling of the coupled cluster expansion

NASA Astrophysics Data System (ADS)

Scott, Charles J. C.; Thom, Alex J. W.

2017-09-01

We consider the sampling of the coupled cluster expansion within stochastic coupled cluster theory. Observing the limitations of previous approaches due to the inherently non-linear behavior of a coupled cluster wavefunction representation, we propose new approaches based on an intuitive, well-defined condition for sampling weights and on sampling the expansion in cluster operators of different excitation levels. We term these modifications even and truncated selections, respectively. Utilising both approaches demonstrates dramatically improved calculation stability as well as reduced computational and memory costs. These modifications are particularly effective at higher truncation levels owing to the large number of terms within the cluster expansion that can be neglected, as demonstrated by the reduction of the number of terms to be sampled when truncating at triple excitations by 77% and hextuple excitations by 98%.

Factors influencing the quality of life of haemodialysis patients according to symptom cluster.

PubMed

Shim, Hye Yeung; Cho, Mi-Kyoung

2018-05-01

To identify the characteristics in each symptom cluster and factors influencing the quality of life of haemodialysis patients in Korea according to cluster. Despite developments in renal replacement therapy, haemodialysis still restricts the activities of daily living due to pain and impairs physical functioning induced by the disease and its complications. Descriptive survey. Two hundred and thirty dialysis patients aged >18 years. They completed self-administered questionnaires of Dialysis Symptom Index and Kidney Disease Quality of Life instrument-Short Form 1.3. To determine the optimal number of clusters, the collected data were analysed using polytomous variable latent class analysis in R software (poLCA) to estimate the latent class models and the latent class regression models for polytomous outcome variables. Differences in characteristics, symptoms and QOL according to the symptom cluster of haemodialysis patients were analysed using the independent t test and chi-square test. The factors influencing the QOL according to symptom cluster were identified using hierarchical multiple regression analysis. Physical and emotional symptoms were significantly more severe, and the QOL was significantly worse in Cluster 1 than in Cluster 2. The factors influencing the QOL were spouse, job, insurance type and physical and emotional symptoms in Cluster 1, with these variables having an explanatory power of 60.9%. Physical and emotional symptoms were the only influencing factors in Cluster 2, and they had an explanatory power of 37.4%. Mitigating the symptoms experienced by haemodialysis patients and improving their QOL require educational and therapeutic symptom management interventions that are tailored according to the characteristics and symptoms in each cluster. The findings of this study are expected to lead to practical guidelines for addressing the symptoms experienced by haemodialysis patients, and they provide basic information for developing nursing interventions to manage these symptoms and improve the QOL of these patients. © 2017 John Wiley & Sons Ltd.

Improvement of the ab initio embedded cluster method for luminescence properties of doped materials by taking into account impurity induced distortions: the example of Y2O3:Bi(3+).

PubMed

Réal, Florent; Ordejón, Belén; Vallet, Valérie; Flament, Jean-Pierre; Schamps, Joël

2009-11-21

New ab initio embedded-cluster calculations devoted to simulating the electronic spectroscopy of Bi(3+) impurities in Y(2)O(3) sesquioxide for substitutions in either S(6) or C(2) cationic sites have been carried out taking special care of the quality of the environment. A considerable quantitative improvement with respect to previous studies [F. Real et al. J. Chem. Phys. 125, 174709 (2006); F. Real et al. J. Chem. Phys. 127, 104705 (2007)] is brought by using environments of the impurities obtained via supercell techniques that allow the whole (pseudo) crystal to relax (WCR geometries) instead of environments obtained from local relaxation of the first coordination shell only (FSR geometries) within the embedded cluster approach, as was done previously. In particular the uniform 0.4 eV discrepancy of absorption energies found previously with FSR environments disappears completely when the new WCR environments of the impurities are employed. Moreover emission energies and hence Stokes shifts are in much better agreement with experiment. These decisive improvements are mainly due to a lowering of the local point-group symmetry (S(6)-->C(3) and C(2)-->C(1)) when relaxing the geometry of the emitting (lowest) triplet state. This symmetry lowering was not observed in FSR embedded cluster relaxations because the crystal field of the embedding frozen at the genuine pure crystal positions seems to be a more important driving force than the interactions within the cluster, thus constraining the overall symmetry of the system. Variations of the doping rate are found to have negligible influence on the spectra. In conclusion, the use of WCR environments may be crucial to render the structural distortions occurring in a doped crystal and it may help to significantly improve the embedded-cluster methodology to reach the quantitative accuracy necessary to interpret and predict luminescence properties of doped materials of this type.

Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

PubMed Central

Liu, Wenfen

2017-01-01

Constrained spectral clustering (CSC) method can greatly improve the clustering accuracy with the incorporation of constraint information into spectral clustering and thus has been paid academic attention widely. In this paper, we propose a fast CSC algorithm via encoding landmark-based graph construction into a new CSC model and applying random sampling to decrease the data size after spectral embedding. Compared with the original model, the new algorithm has the similar results with the increase of its model size asymptotically; compared with the most efficient CSC algorithm known, the new algorithm runs faster and has a wider range of suitable data sets. Meanwhile, a scalable semisupervised cluster ensemble algorithm is also proposed via the combination of our fast CSC algorithm and dimensionality reduction with random projection in the process of spectral ensemble clustering. We demonstrate by presenting theoretical analysis and empirical results that the new cluster ensemble algorithm has advantages in terms of efficiency and effectiveness. Furthermore, the approximate preservation of random projection in clustering accuracy proved in the stage of consensus clustering is also suitable for the weighted k-means clustering and thus gives the theoretical guarantee to this special kind of k-means clustering where each point has its corresponding weight. PMID:29312447

Reexamine structures and relative stability of medium-sized silicon clusters: Low-lying endohedral fullerene-like clusters Si 30-Si 38

NASA Astrophysics Data System (ADS)

Yoo, Soohaeng; Shao, Nan; Zeng, X. C.

2009-10-01

We report improved results of lowest-lying silicon clusters Si 30-Si 38. A large population of low-energy clusters are collected from previous searches by several research groups and the binding energies of these clusters are computed using density-functional theory (DFT) methods. Best candidates (isomers with high binding energies) are identified from the screening calculations. Additional constrained search is then performed for the best candidates using the basin-hopping method combined with DFT geometry optimization. The obtained low-lying clusters are classified according to binding energies computed using either the Perdew-Burke-Ernzerhof (PBE) functional or the Becke exchange and Lee-Yang-Parr correlation (BLYP) functional. We propose to rank low-lying clusters according to the mean PBE/BLYP binding energies in view that the PBE functional tends to give greater binding energies for more compact clusters whereas the BLYP functional tends to give greater binding energies for less compact clusters or clusters composed of small-sized magic-number clusters. Except for Si 30, the new search confirms again that medium-size silicon clusters Si 31-Si 38 constructed with proper fullerene cage motifs are most promising to be the lowest-energy structures.

A spatial scan statistic for multiple clusters.

PubMed

Li, Xiao-Zhou; Wang, Jin-Feng; Yang, Wei-Zhong; Li, Zhong-Jie; Lai, Sheng-Jie

2011-10-01

Spatial scan statistics are commonly used for geographical disease surveillance and cluster detection. While there are multiple clusters coexisting in the study area, they become difficult to detect because of clusters' shadowing effect to each other. The recently proposed sequential method showed its better power for detecting the second weaker cluster, but did not improve the ability of detecting the first stronger cluster which is more important than the second one. We propose a new extension of the spatial scan statistic which could be used to detect multiple clusters. Through constructing two or more clusters in the alternative hypothesis, our proposed method accounts for other coexisting clusters in the detecting and evaluating process. The performance of the proposed method is compared to the sequential method through an intensive simulation study, in which our proposed method shows better power in terms of both rejecting the null hypothesis and accurately detecting the coexisting clusters. In the real study of hand-foot-mouth disease data in Pingdu city, a true cluster town is successfully detected by our proposed method, which cannot be evaluated to be statistically significant by the standard method due to another cluster's shadowing effect. Copyright © 2011 Elsevier Inc. All rights reserved.

Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach.

PubMed

Julie, E Golden; Selvi, S Tamil

2016-01-01

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach

PubMed Central

Julie, E. Golden; Selvi, S. Tamil

2016-01-01

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes. PMID:26881269

Novel density-based and hierarchical density-based clustering algorithms for uncertain data.

PubMed

Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

2017-09-01

Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing algorithms in accuracy and efficiency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Open-Source Sequence Clustering Methods Improve the State Of the Art.

PubMed

Kopylova, Evguenia; Navas-Molina, Jose A; Mercier, Céline; Xu, Zhenjiang Zech; Mahé, Frédéric; He, Yan; Zhou, Hong-Wei; Rognes, Torbjørn; Caporaso, J Gregory; Knight, Rob

2016-01-01

Sequence clustering is a common early step in amplicon-based microbial community analysis, when raw sequencing reads are clustered into operational taxonomic units (OTUs) to reduce the run time of subsequent analysis steps. Here, we evaluated the performance of recently released state-of-the-art open-source clustering software products, namely, OTUCLUST, Swarm, SUMACLUST, and SortMeRNA, against current principal options (UCLUST and USEARCH) in QIIME, hierarchical clustering methods in mothur, and USEARCH's most recent clustering algorithm, UPARSE. All the latest open-source tools showed promising results, reporting up to 60% fewer spurious OTUs than UCLUST, indicating that the underlying clustering algorithm can vastly reduce the number of these derived OTUs. Furthermore, we observed that stringent quality filtering, such as is done in UPARSE, can cause a significant underestimation of species abundance and diversity, leading to incorrect biological results. Swarm, SUMACLUST, and SortMeRNA have been included in the QIIME 1.9.0 release. IMPORTANCE Massive collections of next-generation sequencing data call for fast, accurate, and easily accessible bioinformatics algorithms to perform sequence clustering. A comprehensive benchmark is presented, including open-source tools and the popular USEARCH suite. Simulated, mock, and environmental communities were used to analyze sensitivity, selectivity, species diversity (alpha and beta), and taxonomic composition. The results demonstrate that recent clustering algorithms can significantly improve accuracy and preserve estimated diversity without the application of aggressive filtering. Moreover, these tools are all open source, apply multiple levels of multithreading, and scale to the demands of modern next-generation sequencing data, which is essential for the analysis of massive multidisciplinary studies such as the Earth Microbiome Project (EMP) (J. A. Gilbert, J. K. Jansson, and R. Knight, BMC Biol 12:69, 2014, http://dx.doi.org/10.1186/s12915-014-0069-1).