Science.gov

Sample records for abundance biomass estimates

  1. Use of Droplet Digital PCR for Estimation of Fish Abundance and Biomass in Environmental DNA Surveys

    PubMed Central

    Doi, Hideyuki; Uchii, Kimiko; Takahara, Teruhiko; Matsuhashi, Saeko; Yamanaka, Hiroki; Minamoto, Toshifumi

    2015-01-01

    An environmental DNA (eDNA) analysis method has been recently developed to estimate the distribution of aquatic animals by quantifying the number of target DNA copies with quantitative real-time PCR (qPCR). A new quantitative PCR technology, droplet digital PCR (ddPCR), partitions PCR reactions into thousands of droplets and detects the amplification in each droplet, thereby allowing direct quantification of target DNA. We evaluated the quantification accuracy of qPCR and ddPCR to estimate species abundance and biomass by using eDNA in mesocosm experiments involving different numbers of common carp. We found that ddPCR quantified the concentration of carp eDNA along with carp abundance and biomass more accurately than qPCR, especially at low eDNA concentrations. In addition, errors in the analysis were smaller in ddPCR than in qPCR. Thus, ddPCR is better suited to measure eDNA concentration in water, and it provides more accurate results for the abundance and biomass of the target species than qPCR. We also found that the relationship between carp abundance and eDNA concentration was stronger than that between biomass and eDNA by using both ddPCR and qPCR; this suggests that abundance can be better estimated by the analysis of eDNA for species with fewer variations in body mass. PMID:25799582

  2. Seasonal variations in species composition, abundance, biomass and estimated production rates of tintinnids at tropical estuarine and mangrove waters, Parangipettai, southeast coast of India

    NASA Astrophysics Data System (ADS)

    Godhantaraman, N.

    2002-10-01

    Seasonal varaitions in species composition, abundance, biomass and production rates of tintinnids (Protozoa: Ciliata) were investigated in the tropical estuarine and mangrove systems of Parangipettai, South India, monthly from January to December 1994. There were remarkable seasonal variations in environmental parameters, chlorophyll a concentrations and abundance, biomass and production rates of tintinnids: highest in postmosoon/summer and lowest in monsoon. The total abundance and biomass of tintinnids were in the range of 2-420 indiv. l -1 and 0.02 3.01 μg C l -1, respectively, with the peak appearing in the estuarine waters. A total of 47 species of tintinnids belonging to 14 genera was identified. Of which, Tintinnopsis was the most abundant genus in terms of number of species (20), followed by Codonellopsis (4), Stenosemella (4), Favella (3), Eutintinnus (3), and the remaining genus, number of species are one or two. Most of the tintinnid species occurred on distinct seasonal pattern and closely associated to species-specific environmental conditions. Due to large thermal gradients (range: 22.5-33.8 °C), the overall mean biomass was highest (mean: 1.64 μg C l -1) during summer than the remaining seasons. Estimated production rates of tintinnids ranged from 0.02 to 2.5 μg C l -1 day -1, with peak in summer. The trophodynamic role of tintinnids was assessed by estimating their grazing impact as expressed by daily removal of phytoplankton biomass. The grazing impact also demonstrated a seasonal pattern and ranged from 0.03% to 1.24% removal day -1. The higher grazing impact estimated during summer could be related to high concentrations of food supply. Due to significant positive relationship between the total biomass of tintinnids and chlorophyll a concentrations, food supply is not a problem for tintinnids harboring in this estuarine and mangrove systems. Hence, predation loss by meso- and macrozooplankton might be the possible reasons for the estimated

  3. Lakewide estimates of alewife biomass and Chinook salmon abundance and consumption in Lake Ontario, 1989–2005: implications for prey fish sustainability

    USGS Publications Warehouse

    Murry, Brent A.; Connerton, Michael J.; O'Gorman, Robert; Stewart, Donald J.; Ringlerd, Neil H.

    2010-01-01

    Stocking levels of Chinook salmon Oncorhynchus tshawytscha for Lake Ontario have been highly controversial since the early 1990s, largely because of uncertainties about lakewide abundance and rates of prey consumption. Previous estimates have focused on years before 1995; since then, however, the Lake Ontario ecosystem has undergone substantial changes, and there is new evidence of extensive natural recruitment. Presented here are new abundance estimates of Chinook salmon and alewives Alosa pseudoharengus in Lake Ontario and a reevaluation of the potential risk of alewife population collapse. We found that Lake Ontario has been supporting, on average (1989–2005), 1.83 × 106 (range, 1.08 × 106 to 3.24 × 106) Chinook salmon of ages 1–4, amounting to a mean annual biomass of 11.33 × 103 metric tons (range, 5.83 × 103 to 23.04 × 103 metric tons). During the same period (1989–2005), the lake supported an alewife biomass of 173.66 × 103 metric tons (range, 62.37 × 103 to 345.49 × 103 metric tons); Chinook salmon of ages 1–4 consumed, on average, 22% (range, 11–44%) of the alewife biomass annually. Because our estimates probably underestimate total consumption and because Chinook salmon are only one of several salmonine species that depend on alewives, predation pressure on the Lake Ontario alewife population may be high enough to raise concerns about long-term stability of this predator–prey system.

  4. Global distribution of microbial abundance and biomass in subseafloor sediment

    PubMed Central

    Kallmeyer, Jens; Pockalny, Robert; Adhikari, Rishi Ram; Smith, David C.; D’Hondt, Steven

    2012-01-01

    The global geographic distribution of subseafloor sedimentary microbes and the cause(s) of that distribution are largely unexplored. Here, we show that total microbial cell abundance in subseafloor sediment varies between sites by ca. five orders of magnitude. This variation is strongly correlated with mean sedimentation rate and distance from land. Based on these correlations, we estimate global subseafloor sedimentary microbial abundance to be 2.9⋅1029 cells [corresponding to 4.1 petagram (Pg) C and ∼0.6% of Earth’s total living biomass]. This estimate of subseafloor sedimentary microbial abundance is roughly equal to previous estimates of total microbial abundance in seawater and total microbial abundance in soil. It is much lower than previous estimates of subseafloor sedimentary microbial abundance. In consequence, we estimate Earth’s total number of microbes and total living biomass to be, respectively, 50–78% and 10–45% lower than previous estimates. PMID:22927371

  5. Global Distribution of Microbial Abundance and Biomass in Subseafloor Sediment

    NASA Astrophysics Data System (ADS)

    Kallmeyer, J.; Pockalny, R. A.; Adhikari, R. R.; Smith, D. C.; D'Hondt, S. L.

    2012-12-01

    Previously published cell counts were mostly from ocean margins and the eastern equatorial Pacific. Cell counts from these environments are generally similar from site to site and decrease logarithmically with sediment depth, although there can be sharp peaks of high cell densities in zones of anaerobic methane-oxidation. Recent counts from the South Pacific Gyre and the North Pacific Gyre are several orders of magnitude lower and show a more rapid decrease with depth than all previously published datasets. With these new data available, total microbial cell abundance in subseafloor sediment varies between sites by ca. five orders of magnitude. The differences between cell counts from ocean margins and upwelling areas and cell counts from oceanic gyres raise three questions. First, how does the abundance of microbes in subseafloor sediment vary throughout the world ocean? Second, what property or properties are likely to control that variation? Third, how does this variation affect estimates of total subseafloor sedimentary biomass and Earth's total biomass? To address these questions, we compiled our cell counts from the South Pacific Gyre, the North Pacific Gyre and the eastern equatorial Pacific Ocean with previously published counts and parameterized the cell distribution at each site and determined two parameters, (i) cell concentration at 1 mbsf and (ii) rate of decrease in cell counts with depth. Both parameters are strongly correlated with mean sedimentation rate and distance to shore. Based on these correlations, we estimate global subseafloor sedimentary microbial abundance to be 2.9*1029 cells (corresponding to 4.1 Pg C and ~0.6% of Earth's total living biomass). This estimate of subseafloor sedimentary microbial abundance is roughly equal to previous estimates of total microbial abundance in seawater and total microbial abundance in soil. It is much lower than previous estimates of subseafloor sedimentary microbial abundance. In consequence, we estimate

  6. Hydroacoustic estimates of fish abundance

    SciTech Connect

    Wilson, W.K.

    1992-06-01

    Mobile hydroacoustic surveys are a recent addition to the sampling techniques available to fisheries biologists. Hydroacoustic techniques for fish stock assessment and monitoring are efficient in providingquantitative biomass estimates, absolute population estimates, fish distribution patterns, and size structure statistics. Other advantages of hydroacoustic surveys include a better method of sampling reservoir pelagic (open water) zones than is available with other techniques, collection of large amounts of data in a relatively short time allowing improved statistical interpretation and data comparisons, and non-destructive, non-invasive sampling that neither destroys the sampled fish nor disturbs the environment. The objective of this study is to use hydroacoustic techniques to estimate fish standing stocks (i.e., numbersand biomass) in several areas of selected Tennessee Valley Reservoirs as part of a base level monitoring program to assess long-term changes in reservoir water quality.

  7. Hydroacoustic estimates of fish abundance

    SciTech Connect

    Wilson, W.K.

    1991-03-01

    Hydroacoustics, as defined in the context of this report, is the use of a scientific sonar system to determine fish densities with respect to numbers and biomass. These two parameters provide a method of monitoring reservoir fish populations and detecting gross changes in the ecosystem. With respect to southeastern reservoirs, hydroacoustic surveys represent a new method of sampling open water areas and the best technology available. The advantages of this technology are large amounts of data can be collected in a relatively short period of time allowing improved statistical interpretation and data comparison, the pelagic (open water) zone can be sampled efficiently regardless of depth, and sampling is nondestructive and noninvasive with neither injury to the fish nor alteration of the environment. Hydroacoustics cannot provide species identification and related information on species composition or length/weight relationships. Also, sampling is limited to a minimum depth of ten feet which precludes the use of this equipment for sampling shallow shoreline areas. The objective of this study is to use hydroacoustic techniques to estimate fish standing stocks (i.e., numbers and biomass) in several areas of selected Tennessee Valley Reservoirs as part of a base level monitoring program to assess long-term changes in reservoir water quality.

  8. Distribution of known macrozooplankton abundance and biomass in the global ocean

    NASA Astrophysics Data System (ADS)

    Moriarty, R.; Buitenhuis, E. T.; Le Quéré, C.; Gosselin, M.-P.

    2013-07-01

    Macrozooplankton are an important link between higher and lower trophic levels in the oceans. They serve as the primary food for fish, reptiles, birds and mammals in some regions, and play a role in the export of carbon from the surface to the intermediate and deep ocean. Little, however, is known of their global distribution and biomass. Here we compiled a dataset of macrozooplankton abundance and biomass observations for the global ocean from a collection of four datasets. We harmonise the data to common units, calculate additional carbon biomass where possible, and bin the dataset in a global 1 × 1 degree grid. This dataset is part of a wider effort to provide a global picture of carbon biomass data for key plankton functional types, in particular to support the development of marine ecosystem models. Over 387 700 abundance data and 1330 carbon biomass data have been collected from pre-existing datasets. A further 34 938 abundance data were converted to carbon biomass data using species-specific length frequencies or using species-specific abundance to carbon biomass data. Depth-integrated values are used to calculate known epipelagic macrozooplankton biomass concentrations and global biomass. Global macrozooplankton biomass, to a depth of 350 m, has a mean of 8.4 μg C L-1, median of 0.2 μg C L-1 and a standard deviation of 63.5 μg C L-1. The global annual average estimate of macrozooplankton biomass in the top 350 m, based on the median value, is 0.02 Pg C. There are, however, limitations on the dataset; abundance observations have good coverage except in the South Pacific mid-latitudes, but biomass observation coverage is only good at high latitudes. Biomass is restricted to data that is originally given in carbon or to data that can be converted from abundance to carbon. Carbon conversions from abundance are restricted by the lack of information on the size of the organism and/or the absence of taxonomic information. Distribution patterns of global

  9. Distribution of known macrozooplankton abundance and biomass in the global ocean

    NASA Astrophysics Data System (ADS)

    Moriarty, R.; Buitenhuis, E. T.; Le Quéré, C.; Gosselin, M.-P.

    2012-04-01

    Macrozooplankton are an important link between higher and lower trophic levels in the oceans. They serve as the primary food for fish, reptiles, birds and mammals in some regions, and play a role in the export of carbon from the surface to the intermediate and deep ocean. Little, however, is known of their global distribution and biomass. Here we compiled a dataset of macrozooplankton abundance and biomass observations for the global ocean from a collection of four datasets. We harmonise the data to common units, calculate additional carbon biomass where possible, and bin the dataset in a global 1 × 1 degree grid. This dataset is part of a wider effort to provide a global picture of carbon biomass data for key plankton functional types, in particular to support the development of marine ecosystem models. Over 387 700 abundance data and 1330 carbon biomass data have been collected from pre-existing datasets. A further 34 938 abundance data were converted to carbon biomass data using species-specific length frequencies or using species-specific abundance to carbon biomass data. Depth-integrated values are used to calculate known epipelagic macrozooplankton biomass concentrations and global biomass. Global macrozooplankton biomass has a mean of 8.4 μg C l-1, median of 0.15 μg C l-1 and a standard deviation of 63.46 μg C l-1. The global annual average estimate of epipelagic macrozooplankton, based on the median value, is 0.02 Pg C. Biomass is highest in the tropics, decreasing in the sub-tropics and increasing slightly towards the poles. There are, however, limitations on the dataset; abundance observations have good coverage except in the South Pacific mid latitudes, but biomass observation coverage is only good at high latitudes. Biomass is restricted to data that is originally given in carbon or to data that can be converted from abundance to carbon. Carbon conversions from abundance are restricted in the most part by the lack of information on the size of the

  10. Estimates of US biomass energy consumption 1992

    SciTech Connect

    Not Available

    1994-05-06

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  11. Estimates of US biomass energy consumption 1992

    NASA Astrophysics Data System (ADS)

    1994-05-01

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the U.S. economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  12. ESTIMATES OF BIOMASS DENSITY FOR TROPICAL FORESTS

    EPA Science Inventory

    An accurate estimation of the biomass density in forests is a necessary step in understanding the global carbon cycle and production of other atmospheric trace gases from biomass burning. n this paper the authors summarize the various approaches that have developed for estimating...

  13. Vertical distribution and diel patterns of zooplankton abundance and biomass at Conch Reef, Florida Keys (USA).

    PubMed

    Heidelberg, Karla B; O'Neil, Keri L; Bythell, John C; Sebens, Kenneth P

    2010-01-01

    Zooplankton play an important role in the trophic dynamics of coral reef ecosystems. Detailed vertical and temporal distribution and biomass of zooplankton were evaluated at four heights off the bottom and at six times throughout the diel cycle over a coral reef in the Florida Keys (USA). Zooplankton abundance averaged 4396 +/- 1949 SD individuals m(-3), but temporal and spatial distributions varied for individual zooplankton taxa by time of day and by height off the bottom. Copepods comprised 93-96% of the abundance in the samples. Taxon-based zooplankton CHN values paired with abundance data were used to estimate biomass. Average daily biomass ranged from 3.1 to 21.4 mg C m(-3) and differed by both height off the bottom and by time of day. While copepods were the numerically dominant organisms, their contribution to biomass was only 35% of the total zooplankton biomass. Our findings provide important support for the new emerging paradigm of how zooplankton are distributed over reefs. PMID:20046854

  14. Vertical distribution and diel patterns of zooplankton abundance and biomass at Conch Reef, Florida Keys (USA)

    PubMed Central

    Heidelberg, Karla B.; O'Neil, Keri L.; Bythell, John C.; Sebens, Kenneth P.

    2010-01-01

    Zooplankton play an important role in the trophic dynamics of coral reef ecosystems. Detailed vertical and temporal distribution and biomass of zooplankton were evaluated at four heights off the bottom and at six times throughout the diel cycle over a coral reef in the Florida Keys (USA). Zooplankton abundance averaged 4396 ± 1949 SD individuals m−3, but temporal and spatial distributions varied for individual zooplankton taxa by time of day and by height off the bottom. Copepods comprised 93–96% of the abundance in the samples. Taxon-based zooplankton CHN values paired with abundance data were used to estimate biomass. Average daily biomass ranged from 3.1 to 21.4 mg C m−3 and differed by both height off the bottom and by time of day. While copepods were the numerically dominant organisms, their contribution to biomass was only 35% of the total zooplankton biomass. Our findings provide important support for the new emerging paradigm of how zooplankton are distributed over reefs. PMID:20046854

  15. UNCERTAINTIES IN COUNTRYWIDE FOREST BIOMASS ESTIMATES

    EPA Science Inventory

    Country-wide estimates of forest biomass are the major driver for estimating and understanding carbon pools and flux, a critical component of global change research. mportant determinants in making these estimates include the areal extend of forested lands and their associated bi...

  16. Aerial survey estimates of fallow deer abundance

    USGS Publications Warehouse

    Gogan, Peter J.; Gates, Natalie B.; Lubow, Bruce C.; Pettit, Suzanne

    2012-01-01

    Reliable estimates of the distribution and abundance of an ungulate species is essential prior to establishing and implementing a management program. We used ground surveys to determine distribution and ground and aerial surveys and individually marked deer to estimate the abundance of fallow deer (Dama dama) in north-coastal California. Fallow deer had limited distribution and heterogeneous densities. Estimated post-rut densities across 4 annual surveys ranged from a low of 1.4 (SE=0.2) deer/km2 to a high of 3.3 (se=0.5) deer/km2 in a low density stratum and from 49.0 (SE=8.3) deer/km2 to 111.6 deer/km2 in a high density stratum. Sightability was positively influenced by the presence of white color-phase deer in a group and group size, and varied between airial and ground-based observers and by density strata. Our findings underscore the utility of double-observer surveys and aerial surveys with individually marked deer, both incorporating covariates to model sightability, to estimate deer abundance.

  17. Community composition, abundance and biomass of tintinnids (Ciliata: Protozoa) in the Western Harbour, south-eastern Mediterranean Sea, Egypt.

    PubMed

    Heneash, Ahmed M M; Abdel-Rahman, Nasser S; Gharib, Samiha M

    2015-08-01

    Seasonal variations in species composition, abundance and biomass of tintinnids (Protozoa: Ciliata) were investigated in the Western Harbour, seasonally during 2012. There were remarkable seasonal variations in environmental parameters, phytoplankton concentrations and abundance and biomass of tintinnids: highest in spring and lowest in autumn. Annual average abundance and biomass of tintinnids were 8.435 ind. l(-1) and 3.725 μg C l(-1), respectively. A total of 29 species of tintinnids belonging to 11 genera was identified. Of which, Tintinnopsis was the most abundant genus in terms of number of species (9), but Favella was the best quantitatively (89% of the total tintinnids). The overall mean abundance and biomass were highest (mean 24.415 ind. l(-1) and 10.355 μg C l(-1), respectively) during spring than the remaining seasons. Due to significant positive relationship between the total biomass of tintinnids and phytoplankton concentrations, food supply is not a problem for tintinnids harbouring in the Western Harbour. Hence, predation loss by meso- and macrozooplankton might be the possible reasons for the estimated low biomass of tintinnids in the present study. Some of the seasonal environmental factors as water salinity, nitrite, dissolved oxygen and pH values exert an influence on the species composition, abundance and biomass of tintinnids. PMID:26202815

  18. Macroinvertebrate Abundance and Biomass: 2007 Data, BPA-51; Preliminary Report, February 10, 2009..

    SciTech Connect

    Holderman, Charles

    2009-02-10

    Four Excel files containing information on the 2007 macroinvertebrate data were initially provided to Statistical Consulting Services (SCS) by EcoAnalysts on 1/27/2009. These data files contained information on abundance and biomass data at the level of taxonomic groups. The data were subsequently reformatted and compiled, and aggregated for analysis by SCS. All descriptions and analyses below relate to this compiled data. Computations were carried out separately for each site over all sample periods. Basic summary information for both the abundance and biomass data is presented in Print Out No.2. The 14 sites varied widely in their minimum, mean, maximum and variance values. The number of observations ranged from 10 to 18. Some large abundance values (abundance > 40,000) were noted for sites KR6 and KR13. A more detailed summary of each site is given in Print Out No.3. Site KR3, for example, had a mean abundance of 6914 with a sample size of 17. The variance was 4591991 and the standard error of the mean was 1643. The skewness value, a measure of symmetry for the frequency distribution, was moderately large at 1.29 indicating an asymmetric distribution. Biomass for KR3 had a mean value of 0.87 g/m{sup 2} with 17 observations. The variance was 0.8872 and the standard error was 0.228 g/m{sup 2}. Skewness for biomass was also high at 1.29. Further examination of the quantiles and frequency plots for abundance and biomass also indicate considerable skewness. The stem and leaf diagram (frequency plot) for abundance in KR3 shows most of the data centered on smaller values with a few very large counts. The distribution for biomass has a similar pattern. Statistical tests for normality are significant for both response variables in KR3, thus, the hypothesis that the data originates from a symmetric normal distribution is rejected. Because sample size estimation and statistical inference assume normally distributed data, a transformation of the data is required prior to

  19. Occupancy as a surrogate for abundance estimation

    USGS Publications Warehouse

    MacKenzie, D.I.; Nichols, J.D.

    2004-01-01

    In many monitoring programmes it may be prohibitively expensive to estimate the actual abundance of a bird species in a defined area, particularly at large spatial scales, or where birds occur at very low densities. Often it may be appropriate to consider the proportion of area occupied by the species as an alternative state variable. However, as with abundance estimation, issues of detectability must be taken into account in order to make accurate inferences: the non?detection of the species does not imply the species is genuinely absent. Here we review some recent modelling developments that permit unbiased estimation of the proportion of area occupied, colonization and local extinction probabilities. These methods allow for unequal sampling effort and enable covariate information on sampling locations to be incorporated. We also describe how these models could be extended to incorporate information from marked individuals, which would enable finer questions of population dynamics (such as turnover rate of nest sites by specific breeding pairs) to be addressed. We believe these models may be applicable to a wide range of bird species and may be useful for investigating various questions of ecological interest. For example, with respect to habitat quality, we might predict that a species is more likely to have higher local extinction probabilities, or higher turnover rates of specific breeding pairs, in poor quality habitats.

  20. Spectral procedures for estimating crop biomass

    SciTech Connect

    Wanjura, D.F.; Hatfield, J.L.

    1985-05-01

    Spectral reflectance was measured semi-weekly and used to estimate leaf area and plant dry weight accumulation in cotton, soybeans, and sunflower. Integration of spectral crop growth cycle curves explained up to 95 and 91%, respectively, of the variation in cotton lint yield and dry weight. A theoretical relationship for dry weight accumulation, in which only intercepted radiation or intercepted radiation and solar energy to biomass conversion efficiency were spectrally estimated, explained 99 and 96%, respectively, of the observed plant dry weight variation of the three crops. These results demonstrate the feasibility of predicting crop biomass from spectral measurements collected frequently during the growing season. 15 references.

  1. Rangeland biomass estimation demonstration. [Texas Experimenta Ranch

    NASA Technical Reports Server (NTRS)

    Newton, R. W. (Principal Investigator); Boyd, W. E.; Clark, B. V.

    1982-01-01

    Because of their sensitivity to chlorophyll density, green leaf density, and leaf water density, two hand-held radiometers which have sensor bands coinciding with thematic mapper bands 3, 4, and 5 were used to calibrate green biomass to LANDSAT spectral ratios as a step towards using portable radiometers to speed up ground data acquisition. Two field reflectance panels monitored incoming radiation concurrently with sampling. Software routines were developed and used to extract data from uncorrected tapes of MSS data provided in NASA LANDSAT universal format. A LANDSAT biomass calibration curve estimated the range biomass over a four scene area and displayed this information spatially as a product in a format of use to ranchers. The regional biomass contour map is discussed.

  2. Efficient Methods of Estimating Switchgrass Biomass Supplies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Switchgrass (Panicum virgatum L.) is being developed as a biofuel feedstock for the United States. Efficient and accurate methods to estimate switchgrass biomass feedstock supply within a production area will be required by biorefineries. Our main objective was to determine the effectiveness of in...

  3. Accurate Biomass Estimation via Bayesian Adaptive Sampling

    NASA Technical Reports Server (NTRS)

    Wheeler, Kevin R.; Knuth, Kevin H.; Castle, Joseph P.; Lvov, Nikolay

    2005-01-01

    The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.

  4. SPECIES-ABUNDANCE-BIOMASS RESPONSES BY ESTUARINE MACROBENTHOS TO SEDIMENT CHEMICAL CONTAMINATION.

    EPA Science Inventory

    Macrobenthic community responses can be measured through concerted changes in univariate metrics, including species richness, total abundance, and total biomass. The classic model of pollution effects on marine macroinvertebrate communities recognizes that species/abundance/bioma...

  5. Abundance, biomass and growth rates of Synechococcus sp. in a tropical coastal ecosystem (Philippines, South China Sea)

    NASA Astrophysics Data System (ADS)

    Agawin, N. S. R.; Duarte, C. M.; Agustí, S.; McManus, L.

    2003-03-01

    The abundance, biomass and growth rates of Synechococcus sp. were estimated in a tropical coastal ecosystem (Philippines, South China Sea). The patterns of change of these parameters were further examined in relation to human-derived disturbance such as siltation, and by short-term episodic disturbances such as the typhoons, which are frequent in the region. The average abundance and biomass of Synechococcus sp. in the coastal ecosystem ranged from 0.13 to 21×10 6 cells l -1, and from 0.01 to l.6 mg C m -3, respectively, with higher biomass occurring near river sources rich in inorganic nutrients. There was, however, a significant decline of specific growth rates and maximum frequency of cells in division with increasing siltation, which suggests a deterioration of the environmental conditions to support picocyanobacterial populations. The low biomass of Synechococcus sp. in more pristine sites, in spite of relatively high growth rates there suggests that loss factors (i.e. grazing) are important in controlling the biomass in the area. The temporal pattern of picocyanobacterial abundance in the tropical ecosystem studied was tightly coupled with their temporal patterns of growth indicating that changes in abundance may result from changes in growth rate. There was not, however, a clear annual pattern of Synechococcus sp. abundance in the study site but there was some evidence for effects of storms on Synechococcus sp. abundance.

  6. Robust Abundance Estimation in Animal Abundance Surveys with Imperfect Detection

    EPA Science Inventory

    Surveys of animal abundance are central to the conservation and management of living natural resources. However, detection uncertainty complicates the sampling process of many species. One sampling method employed to deal with this problem is depletion (or removal) surveys in whi...

  7. Estimating slash pine biomass using radar backscatter

    NASA Technical Reports Server (NTRS)

    Hussin, Yousif Ali; Reich, Robin M.; Hoffer, Roger M.

    1991-01-01

    L-band HV multiple-incidence-angle aircraft synthetic aperture radar (SAR) data were analyzed in relation to average stand biomass, basal area, and tree height for 55 slash pine plantations located in northern Florida. This information was used to develop a system of equations to predict average stand biomass as a function of L-band (24.5-cm) radar backscatter. The system of equations developed in this study using three-stage least-squares and combinatorial screening accounted for 97 percent of the variability observed in average stand biomass per hectare. When applied to an independent data set, the biomass equations had an average bias of less than 1 percent with a standard error of approximately 3 percent. These results indicate that future Shuttle Imaging Radar Systems (e.g., SIR-C, which will have cross-polarized radar sensors) should be able to obtain better estimates of forest biomass than were obtained with previous satellite radar missions, which utilized only HH-polarized SAR data.

  8. Hydroacoustic estimates of abundance and spatial distribution of pelagic prey fishes in western Lake Superior

    USGS Publications Warehouse

    Mason, Doran M.; Johnson, Timothy B.; Harvey, Chris J.; Kitchell, James F.; Schram, Stephen T.; Bronte, Charles R.; Hoff, MIchael H.; Lozano, Stephen J.; Trebitz, Anett S.; Schreiner, Donald R.; Lamon, E. Conrad; Hrabik, Thomas R.

    2005-01-01

    Lake herring (Coregonus artedi) and rainbow smelt (Osmerus mordax) are a valuable prey resource for the recovering lake trout (Salvelinus namaycush) in Lake Superior. However, prey biomass may be insufficient to support the current predator demand. In August 1997, we assessed the abundance and spatial distribution of pelagic coregonines and rainbow smelt in western Lake Superior by combining a 120 kHz split beam acoustics system with midwater trawls. Coregonines comprised the majority of the midwater trawl catches and the length distributions for trawl caught fish coincided with estimated sizes of acoustic targets. Overall mean pelagic prey fish biomass was 15.56 kg ha−1 with the greatest fish biomass occurring in the Apostle Islands region (27.98 kg ha−1), followed by the Duluth Minnesota region (20.22 kg ha−1), and with the lowest biomass occurring in the open waters of western Lake Superior (9.46 kg ha−1). Biomass estimates from hydroacoustics were typically 2–134 times greater than estimates derived from spring bottom trawl surveys. Prey fish biomass for Lake Superior is about order of magnitude less than acoustic estimates for Lakes Michigan and Ontario. Discrepancies observed between bioenergetics-based estimates of predator consumption of coregonines and earlier coregonine biomass estimates may be accounted for by our hydroacoustic estimates.

  9. Biomass and Abundance Biases in European Standard Gillnet Sampling

    PubMed Central

    Prchalová, Marie; Říha, Milan; Muška, Milan; Blabolil, Petr; Čech, Martin; Vašek, Mojmír; Jůza, Tomáš; Monteoliva Herreras, Agustín; Encina, Lourdes; Peterka, Jiří; Kubečka, Jan

    2015-01-01

    The European Standard EN 14757 recommends gillnet mesh sizes that range from 5 to 55mm (knot-to-knot) for the standard monitoring of fish assemblages and suggests adding gillnets with larger mesh sizes if necessary. Our research showed that the recommended range of mesh sizes did not provide a representative picture of fish sizes for larger species that commonly occur in continental Europe. We developed a novel, large mesh gillnet which consists of mesh sizes 70, 90, 110 and 135mm (knot to knot, 10m panels) and assessed its added value for monitoring purposes. From selectivity curves obtained by sampling with single mesh size gillnets (11 mesh sizes 6 – 55mm) and large mesh gillnets, we identified the threshold length of bream (Abramis brama) above which this widespread large species was underestimated by European standard gillnet catches. We tested the European Standard gillnet by comparing its size composition with that obtained during concurrent pelagic trawling and purse seining in a cyprinid-dominated reservoir and found that the European Standard underestimated fish larger than 292mm by 26 times. The inclusion of large mesh gillnets in the sampling design removed this underestimation. We analysed the length-age relationship of bream in the Římov Reservoir, and concluded that catches of bream larger than 292mm and older than five years were seriously underrepresented in European Standard gillnet catches. The Římov Reservoir is a typical cyprinid-dominated water body where the biomass of bream > 292mm formed 70% of the pelagic trawl and purse seine catch. The species-specific relationships between the large mesh gillnet catch and European Standard catch suggested that the presence of carp (Cyprinus carpio), European catfish (Silurus glanis), tench (Tinca tinca) or bream warrants the use of both gillnet types. We suggest extending the gillnet series in the European Standard to avoid misinterpretation of fish community biomass estimates. PMID:25793776

  10. Biomass and abundance biases in European standard gillnet sampling.

    PubMed

    Šmejkal, Marek; Ricard, Daniel; Prchalová, Marie; Říha, Milan; Muška, Milan; Blabolil, Petr; Čech, Martin; Vašek, Mojmír; Jůza, Tomáš; Monteoliva Herreras, Agustín; Encina, Lourdes; Peterka, Jiří; Kubečka, Jan

    2015-01-01

    The European Standard EN 14757 recommends gillnet mesh sizes that range from 5 to 55mm (knot-to-knot) for the standard monitoring of fish assemblages and suggests adding gillnets with larger mesh sizes if necessary. Our research showed that the recommended range of mesh sizes did not provide a representative picture of fish sizes for larger species that commonly occur in continental Europe. We developed a novel, large mesh gillnet which consists of mesh sizes 70, 90, 110 and 135mm (knot to knot, 10m panels) and assessed its added value for monitoring purposes. From selectivity curves obtained by sampling with single mesh size gillnets (11 mesh sizes 6 - 55mm) and large mesh gillnets, we identified the threshold length of bream (Abramis brama) above which this widespread large species was underestimated by European standard gillnet catches. We tested the European Standard gillnet by comparing its size composition with that obtained during concurrent pelagic trawling and purse seining in a cyprinid-dominated reservoir and found that the European Standard underestimated fish larger than 292mm by 26 times. The inclusion of large mesh gillnets in the sampling design removed this underestimation. We analysed the length-age relationship of bream in the Římov Reservoir, and concluded that catches of bream larger than 292mm and older than five years were seriously underrepresented in European Standard gillnet catches. The Římov Reservoir is a typical cyprinid-dominated water body where the biomass of bream > 292mm formed 70% of the pelagic trawl and purse seine catch. The species-specific relationships between the large mesh gillnet catch and European Standard catch suggested that the presence of carp (Cyprinus carpio), European catfish (Silurus glanis), tench (Tinca tinca) or bream warrants the use of both gillnet types. We suggest extending the gillnet series in the European Standard to avoid misinterpretation of fish community biomass estimates. PMID:25793776

  11. Non-destructive lichen biomass estimation in northwestern Alaska: a comparison of methods.

    PubMed

    Rosso, Abbey; Neitlich, Peter; Smith, Robert J

    2014-01-01

    Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa "community" samples, n = 144) at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume) as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4%) using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m-2). Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska. PMID:25079228

  12. Non-Destructive Lichen Biomass Estimation in Northwestern Alaska: A Comparison of Methods

    PubMed Central

    Rosso, Abbey; Neitlich, Peter; Smith, Robert J.

    2014-01-01

    Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa “community” samples, n = 144) at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume) as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4%) using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m−2). Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska. PMID:25079228

  13. Toward Reliable Estimates of Abundance: Comparing Index Methods to Assess the Abundance of a Mammalian Predator

    PubMed Central

    Güthlin, Denise; Storch, Ilse; Küchenhoff, Helmut

    2014-01-01

    Due to time and financial constraints indices are often used to obtain landscape-scale estimates of relative species abundance. Using two different field methods and comparing the results can help to detect possible bias or a non monotonic relationship between the index and the true abundance, providing more reliable results. We used data obtained from camera traps and feces counts to independently estimate relative abundance of red foxes in the Black Forest, a forested landscape in southern Germany. Applying negative binomial regression models, we identified landscape parameters that influence red fox abundance, which we then used to predict relative red fox abundance. We compared the estimated regression coefficients of the landscape parameters and the predicted abundance of the two methods. Further, we compared the costs and the precision of the two field methods. The predicted relative abundances were similar between the two methods, suggesting that the two indices were closely related to the true abundance of red foxes. For both methods, landscape diversity and edge density best described differences in the indices and had positive estimated effects on the relative fox abundance. In our study the costs of each method were of similar magnitude, but the sample size obtained from the feces counts (262 transects) was larger than the camera trap sample size (88 camera locations). The precision of the camera traps was lower than the precision of the feces counts. The approach we applied can be used as a framework to compare and combine the results of two or more different field methods to estimate abundance and by this enhance the reliability of the result. PMID:24743565

  14. Forest Above Ground Biomass Estimation in China

    NASA Astrophysics Data System (ADS)

    Zhao, D.; Zeng, Y.; Wu, B.; Li, X.

    2013-12-01

    In order to study the carbon cycling in China deeply, a forest above ground biomass (AGB) estimation research is carried out under the support of 'Strategic Priority Research Program - Climate Change: Carbone Budget and Related Issues' of the Chinese Academy of Sciences (Carbon Project). The research aims to estimate the forest AGB in 2000, 2005 and 2010 in China, and analyzes its dynamic changes. The overall thinking of the research is using field works and airborne LiDAR data as basis to estimate the AGB in GLAS footprints, and then extrapolating discrete AGB to continuous results with optical and auxiliary data. Due to the large area of China, totally 8 sub-areas are marked out based on the different forest ecosystems and some other factors (Table 1 and Fig. 1). Here, a latest China's land cover product (the background of Fig 1), named 'ChinaCover', and also supported by the 'Carbon Project', is imported to classify the forest types. There are around 5000 sample plots (Table 1) surveyed by the 'Carbon Project'. It can provide a large number of training and validation data. At the same time, the research sets 6 other typical sample areas, which have areas of 60 to 200 km2, and airborne LiDAR flights are carried out to obtain high accuracy AGB in these areas. With the sample plots and 6 typical sample areas, the AGB in GLAS footprint is estimated. Since the sample plots and LiDAR flights were carried out in 2012, the height and area parameters extracted from GLAS footprint are corrected by tree growth model of different forest types. In a further step, extrapolation models are built together with time-series MODIS and auxiliary data. These models fully consider the time-series features and propose several long time-series indices to minimize the influence of spectral saturation. Results are validated by samples and compared to the result of some other researches. At last, the models are applied to the data of 2000, 2005 and 2010 to get the corresponding AGB maps

  15. Biomass Estimates for Five Western States.

    SciTech Connect

    Howard, James O.

    1990-10-01

    The purpose of this report is to describe the woody biomass resource within US Department of Energy's Pacific Northwest and Alaska Regional Biomass Program, comprised of southeast Alaska, Idaho, Montana, Oregon, and Washington. In addition to the regional forest biomass assessment, information will be presented for logging residue, which represents current energy conversion opportunities. The information presented in the report is based on data and relationships already published. Regionally applicable biomass equations are generally not available for species occurring in the west. Because of this, a number of assumptions were made to develop whole-tree biomass tables. These assumptions are required to link algorithms from biomass studies to regional timber inventory data published by the Forest Inventory and Analysis Research Units (FIA), of the Pacific Northwest and Intermountain Research Stations, US Forest Service. These sources and assumptions will be identified later in this report. Tabular biomass data will be presented for 11 resource areas, identified in the FS inventory publications. This report does not include information for the vast area encompassing interior Alaska. Total tress biomass as defined in the report refers to the above ground weight of a tree above a 1.0 foot stump, and exclusive of foliage. A glossary is included that defines specific terms as used in the report. Inventory terminology is derived from forest inventory reports from Forest Inventory and Analysis units at the Intermountain and Pacific Northwest Research Stations. 39 refs., 15 figs., 23 tabs.

  16. Evaluation of Methods to Estimate Understory Fruit Biomass

    PubMed Central

    Lashley, Marcus A.; Thompson, Jeffrey R.; Chitwood, M. Colter; DePerno, Christopher S.; Moorman, Christopher E.

    2014-01-01

    Fleshy fruit is consumed by many wildlife species and is a critical component of forest ecosystems. Because fruit production may change quickly during forest succession, frequent monitoring of fruit biomass may be needed to better understand shifts in wildlife habitat quality. Yet, designing a fruit sampling protocol that is executable on a frequent basis may be difficult, and knowledge of accuracy within monitoring protocols is lacking. We evaluated the accuracy and efficiency of 3 methods to estimate understory fruit biomass (Fruit Count, Stem Density, and Plant Coverage). The Fruit Count method requires visual counts of fruit to estimate fruit biomass. The Stem Density method uses counts of all stems of fruit producing species to estimate fruit biomass. The Plant Coverage method uses land coverage of fruit producing species to estimate fruit biomass. Using linear regression models under a censored-normal distribution, we determined the Fruit Count and Stem Density methods could accurately estimate fruit biomass; however, when comparing AIC values between models, the Fruit Count method was the superior method for estimating fruit biomass. After determining that Fruit Count was the superior method to accurately estimate fruit biomass, we conducted additional analyses to determine the sampling intensity (i.e., percentage of area) necessary to accurately estimate fruit biomass. The Fruit Count method accurately estimated fruit biomass at a 0.8% sampling intensity. In some cases, sampling 0.8% of an area may not be feasible. In these cases, we suggest sampling understory fruit production with the Fruit Count method at the greatest feasible sampling intensity, which could be valuable to assess annual fluctuations in fruit production. PMID:24819253

  17. The weight of nations: an estimation of adult human biomass

    PubMed Central

    2012-01-01

    Background The energy requirement of species at each trophic level in an ecological pyramid is a function of the number of organisms and their average mass. Regarding human populations, although considerable attention is given to estimating the number of people, much less is given to estimating average mass, despite evidence that average body mass is increasing. We estimate global human biomass, its distribution by region and the proportion of biomass due to overweight and obesity. Methods For each country we used data on body mass index (BMI) and height distribution to estimate average adult body mass. We calculated total biomass as the product of population size and average body mass. We estimated the percentage of the population that is overweight (BMI > 25) and obese (BMI > 30) and the biomass due to overweight and obesity. Results In 2005, global adult human biomass was approximately 287 million tonnes, of which 15 million tonnes were due to overweight (BMI > 25), a mass equivalent to that of 242 million people of average body mass (5% of global human biomass). Biomass due to obesity was 3.5 million tonnes, the mass equivalent of 56 million people of average body mass (1.2% of human biomass). North America has 6% of the world population but 34% of biomass due to obesity. Asia has 61% of the world population but 13% of biomass due to obesity. One tonne of human biomass corresponds to approximately 12 adults in North America and 17 adults in Asia. If all countries had the BMI distribution of the USA, the increase in human biomass of 58 million tonnes would be equivalent in mass to an extra 935 million people of average body mass, and have energy requirements equivalent to that of 473 million adults. Conclusions Increasing population fatness could have the same implications for world food energy demands as an extra half a billion people living on the earth. PMID:22709383

  18. Latitudinal variation in invertebrate megafaunal abundance and biomass in the North Atlantic Ocean Abyss

    NASA Astrophysics Data System (ADS)

    Thurston, M. H.; Rice, A. L.; Bett, B. J.

    1998-01-01

    Megafauna was collected by otter trawl at two widely separated abyssal sites in the eastern North Atlantic Ocean. The northern site, on the Porcupine Abyssal Plain (PAP, 4850 m), is subject to strong seasonal pulses of phytodetritus deposition, whereas the southern site, on the Madeira Abyssal Plain (OLIGO, 4500-4650 m), showed no indication of such deposition. Data from these two sites were compared with those from a third site (GME), also apparently not affected by phytodetritus, but on the Madeira Abyssal Plain 1200 km from OLIGO. Mean abundance and biomass of invertebrate megafauna at PAP were 72.6 individuals ha -1 and 1974 g ha -1 respectively. The corresponding values for OLIGO were 10.2 individuals ha -1 and 63.4 g ha -1 and for GME 21.7 individuals ha -1 and 112.9 g ha -1. Size-spectral curves of abundance and biomass based on PAP samples showed peaks in the 40-80 g wet weight class, thus confirming the megafauna as a functional entity. No evidence for seasonal variation of abundance or biomass was found. At OLIGO, abundance declined more or less regularly over the organism size range sampled, and biomass was spread fairly evenly across the larger size classes. Major differences in trophic structure among the three sites were evident, with OLIGO and GME more similar to one another than either were to PAP, with much of the higher biomass at PAP represented by particle-selective detritivorous holothurians. The contribution of invertebrates to overall megafaunal biomass at OLIGO (8%) and GME (30%) was lower than at PAP (48%), but a high proportion of fish biomass at OLIGO and GME, and almost all at PAP, belonged to macrophagous species trophically independent of benthic production.

  19. Estimating vegetative biomass from LANDSAT-1 imagery for range management

    NASA Technical Reports Server (NTRS)

    Seevers, P. M.; Drew, J. V.; Carlson, M. P.

    1975-01-01

    Evaluation of LANDSAT-1, band 5 data for use in estimation of vegetative biomass for range management decisions was carried out for five selected range sites in the Sandhills region of Nebraska. Analysis of sets of optical density-vegetative biomass data indicated that comparisons of biomass estimation could be made within one frame but not between frames without correction factors. There was high correlation among sites within sets of radiance value-vegetative biomass data and also between sets, indicating comparisons of biomass could be made within and between frames. Landsat-1 data are shown to be a viable alternative to currently used methods of determining vegetative biomass production and stocking rate recommendations for Sandhills rangeland.

  20. Biomass Estimation of Dry Tropical Woody Species at Juvenile Stage

    PubMed Central

    Chaturvedi, R. K.; Raghubanshi, A. S.; Singh, J. S.

    2012-01-01

    Accurate characterization of biomass in different forest components is important to estimate their contribution to total carbon stock. Due to lack of allometric equations for biomass estimation of woody species at juvenile stage, the carbon stored in this forest component is ignored. We harvested 47 woody species at juvenile stage in a dry tropical forest and developed regression models for the estimation of above-ground biomass (AGB). The models including wood-specific gravity (ρ) exhibited higher R2 than those without ρ. The model consisting of ρ, stem diameter (D), and height (H) not only exhibited the highest R2 value but also had the lowest standard error of estimate. We suggest that ρ-based regression model is a viable option for nondestructive estimation of biomass of forest trees at juvenile stage. PMID:22448139

  1. Mnemiopsis leidyi (Ctenophora) in Narragansett Bay, 1975-1979: Abundance, size composition and estimation of grazing

    NASA Astrophysics Data System (ADS)

    Deason, Ellen E.

    1982-08-01

    Surveys of the distribution, abundance and size of the ctenophore Mnemiopsis leidyi were carried out in Narragansett Bay, R.I. over a 5-year period, 1975-1979. Yearly variations were observed in time of initiation of the ctenophore increase and maximum abundance. Biomass maxima ranged from 0·2 to 3 g dry weight m -3 at Station 2 in lower Narragansett Bay while maximum abundance varied from 20 to 100 animals m -3. Ctenophores less than 1 cm in length generally composed up to 50% of the biomass and 95% of the numerical abundance during the peak of the M. leidyi pulse. During the 1978 maxima and the declining stages of the pulse each year, 100% of the population was composed of small animals. M. leidyi populations increased earlier, reached greater maximum abundances, and were more highly dominated by small animals in the upper bay than toward the mouth of the bay. The averageclearance rate of M. leidyi larvae feeding on A. tonsa at 22°C was 0·36 l mg -1 dry weight day -1, with apparent selection for nauplii relative to copepodites. Predation and excretion rates applied to ctenophore biomass estimated for Narragansett Bay indicated that M. leidyi excretion is minor but predation removed a bay-wide mean of 20% of the zooplankton standing stock daily during August of 1975 and 1976. Variation in M. leidyi predation at Station 2 was inversely related to mean zooplankton biomass during August and September, which increased 4-fold during the 5-year period.

  2. MODIS Based Estimation of Forest Aboveground Biomass in China

    PubMed Central

    Sun, Yan; Wang, Tao; Zeng, Zhenzhong; Piao, Shilong

    2015-01-01

    Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha−1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y−1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y−1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y−1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests. PMID:26115195

  3. MODIS Based Estimation of Forest Aboveground Biomass in China.

    PubMed

    Yin, Guodong; Zhang, Yuan; Sun, Yan; Wang, Tao; Zeng, Zhenzhong; Piao, Shilong

    2015-01-01

    Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests. PMID:26115195

  4. Relative contributions of sampling effort, measuring, and weighing to precision of larval sea lamprey biomass estimates

    USGS Publications Warehouse

    Slade, J.W.; Adams, J.V.; Cuddy, D.W.; Neave, F.B.; Sullivan, W.P.; Young, R.J.; Fodale, M.F.; Jones, M.L.

    2003-01-01

    We developed two weight-length models from 231 populations of larval sea lampreys (Petromyzon marinus) collected from tributaries of the Great Lakes: Lake Ontario (21), Lake Erie (6), Lake Huron (67), Lake Michigan (76), and Lake Superior (61). Both models were mixed models, which used population as a random effect and additional environmental factors as fixed effects. We resampled weights and lengths 1,000 times from data collected In each of 14 other populations not used to develop the models, obtaining a weight and length distribution from reach resampling. To test model performance, we applied the two weight-length models to the resampled length distributions and calculated the predicted mean weights. We also calculated the observed mean weight for each resampling and for each of the original 14 data sets. When the average of predicted means was compared to means from the original data in each stream, inclusion of environmental factors did not consistently improve the performance of the weight-length model. We estimated the variance associated with measures of abundance and mean weight for each of the 14 selected populations and determined that a conservative estimate of the proportional contribution to variance associated with estimating abundance accounted for 32% to 95% of the variance (mean = 66%). Variability in the biomass estimate appears more affected by variability in estimating abundance than in converting length to weight. Hence, efforts to improve the precision of biomass estimates would be aided most by reducing the variability associated with estimating abundance.

  5. Relative contributions of sampling effort, measuring, and weighing to precision of larval sea lamprey biomass estimates

    USGS Publications Warehouse

    Slade, Jeffrey W.; Adams, Jean V.; Cuddy, Douglas W.; Neave, Fraser B.; Sullivan, W. Paul; Young, Robert J.; Fodale, Michael F.; Jones, Michael L.

    2003-01-01

    We developed two weight-length models from 231 populations of larval sea lampreys (Petromyzon marinus) collected from tributaries of the Great Lakes: Lake Ontario (21), Lake Erie (6), Lake Huron (67), Lake Michigan (76), and Lake Superior (61). Both models were mixed models, which used population as a random effect and additional environmental factors as fixed effects. We resampled weights and lengths 1,000 times from data collected in each of 14 other populations not used to develop the models, obtaining a weight and length distribution from reach resampling. To test model performance, we applied the two weight-length models to the resampled length distributions and calculated the predicted mean weights. We also calculated the observed mean weight for each resampling and for each of the original 14 data sets. When the average of predicted means was compared to means from the original data in each stream, inclusion of environmental factors did not consistently improve the performance of the weight-length model. We estimated the variance associated with measures of abundance and mean weight for each of the 14 selected populations and determined that a conservative estimate of the proportional contribution to variance associated with estimating abundance accounted for 32% to 95% of the variance (mean = 66%). Variability in the biomass estimate appears more affected by variability in estimating abundance than in converting length to weight. Hence, efforts to improve the precision of biomass estimates would be aided most by reducing the variability associated with estimating abundance.

  6. Quantitative abundance estimates from bidirectional reflectance measurements. [for planetary surfaces

    NASA Technical Reports Server (NTRS)

    Mustard, John F.; Pieters, Carle M.

    1987-01-01

    A simplified approach for estimating mineral abundances in mineral mixtures from bidirectional reflectance measurements is presented. Fundamental to this approach is a priori information concerning reflectance spectra of the individual minerals and an estimate of the particle sizes of the components. Simplified equations for bidirectional reflectance are used to linearize the systematics of spectral mixing. The method was used to determine the relative proportions of olivine, magnetite, enstatite, and anorthite in a mixture; the mass fractions of mixture components were calculated on the basis of known particle diameters. The results indicate that for materials without strongly adsorbing components, the accuracy of abundance determinations is better than 5 percent.

  7. [Interannual Variations in Abundance and Biomass of Planktonic Copepods Oithona in the Barents Sea].

    PubMed

    Dvoretsky, V G; Dvoretsky, A G

    2015-01-01

    The distribution patterns of the common arctic zooplankton species Oithona similis and Oithona atlantica were investigated in the Barents Sea during warm and temperate years. The maximum abundance and biomass of Oithona spp. (159 x 10(3) ind./m2 and 38.8 mgC/m2, respectively) were recorded in the waters of Atlantic origin. O. atlantica occurred in Arctic waters only during anomalously warm years. It has been found that the quantitative characteristics of O. similis were negatively correlated with salinity and the winter NAO index, whereas the abundance of O. atlantica in Atlantic waters was positively correlated with the temperature anomaly. It is found that the abundance and biomass of Oithona pp. were comparable with the values recorded in other Arctic regions. PMID:26638241

  8. Global patterns in sandy beach macrofauna: Species richness, abundance, biomass and body size

    NASA Astrophysics Data System (ADS)

    Defeo, Omar; McLachlan, Anton

    2013-10-01

    Global patterns in species richness in sandy beach ecosystems have been poorly understood until comparatively recently, because of the difficulty of compiling high-resolution databases at continental scales. We analyze information from more than 200 sandy beaches around the world, which harbor hundreds of macrofauna species, and explore latitudinal trends in species richness, abundance and biomass. Species richness increases from temperate to tropical sites. Abundance follows contrasting trends depending on the slope of the beach: in gentle slope beaches, it is higher at temperate sites, whereas in steep-slope beaches it is higher at the tropics. Biomass follows identical negative trends for both climatic regions at the whole range of beach slopes, suggesting decreasing rates in carrying capacity of the environment towards reflective beaches. Various morphodynamic variables determine global trends in beach macrofauna. Species richness, abundance and biomass are higher at dissipative than at reflective beaches, whereas a body size follows the reverse pattern. A generalized linear model showed that large tidal range (which determines the vertical dimension of the intertidal habitat), small size of sand particles and flat beach slope (a product of the interaction among wave energy, tidal range and grain size) are correlated with high species richness, suggesting that these parameters represent the most parsimonious variables for modelling patterns in sandy beach macrofauna. Large-scale patterns indicate a scaling of abundance to a body size, suggesting that dissipative beaches harbor communities with highest abundance and species with the smallest body sizes. Additional information for tropical and northern hemisphere sandy beaches (underrepresented in our compilation) is required to decipher more conclusive trends, particularly in abundance, biomass and body size. Further research should integrate meaningful oceanographic variables, such as temperature and primary

  9. Estimating abundance in the presence of species uncertainty

    USGS Publications Warehouse

    Chambert, Thierry A; Hossack, Blake R.; Fishback, LeeAnn; Davenport, Jon M.

    2016-01-01

    1.N-mixture models have become a popular method for estimating abundance of free-ranging animals that are not marked or identified individually. These models have been used on count data for single species that can be identified with certainty. However, co-occurring species often look similar during one or more life stages, making it difficult to assign species for all recorded captures. This uncertainty creates problems for estimating species-specific abundance and it can often limit life stages to which we can make inference. 2.We present a new extension of N-mixture models that accounts for species uncertainty. In addition to estimating site-specific abundances and detection probabilities, this model allows estimating probability of correct assignment of species identity. We implement this hierarchical model in a Bayesian framework and provide all code for running the model in BUGS-language programs. 3.We present an application of the model on count data from two sympatric freshwater fishes, the brook stickleback (Culaea inconstans) and the ninespine stickleback (Pungitius pungitius), ad illustrate implementation of covariate effects (habitat characteristics). In addition, we used a simulation study to validate the model and illustrate potential sample size issues. We also compared, for both real and simulated data, estimates provided by our model to those obtained by a simple N-mixture model when captures of unknown species identification were discarded. In the latter case, abundance estimates appeared highly biased and very imprecise, while our new model provided unbiased estimates with higher precision. 4.This extension of the N-mixture model should be useful for a wide variety of studies and taxa, as species uncertainty is a common issue. It should notably help improve investigation of abundance and vital rate characteristics of organisms’ early life stages, which are sometimes more difficult to identify than adults.

  10. A collaborative approach for estimating terrestrial wildlife abundance

    USGS Publications Warehouse

    Ransom, Jason I.; Kaczensky, Petra; Lubow, Bruce C.; Ganbaatar, Oyunsaikhan; Altansukh, Nanjid

    2012-01-01

    Accurately estimating abundance of wildlife is critical for establishing effective conservation and management strategies. Aerial methodologies for estimating abundance are common in developed countries, but they are often impractical for remote areas of developing countries where many of the world's endangered and threatened fauna exist. The alternative terrestrial methodologies can be constrained by limitations on access, technology, and human resources, and have rarely been comprehensively conducted for large terrestrial mammals at landscape scales. We attempted to overcome these problems by incorporating local peoples into a simultaneous point count of Asiatic wild ass (Equus hemionus) and goitered gazelle (Gazella subgutturosa) across the Great Gobi B Strictly Protected Area, Mongolia. Paired observers collected abundance and covariate metrics at 50 observation points and we estimated population sizes using distance sampling theory, but also assessed individual observer error to examine potential bias introduced by the large number of minimally trained observers. We estimated 5671 (95% CI = 3611–8907) wild asses and 5909 (95% CI = 3762–9279) gazelle inhabited the 11,027 km2 study area at the time of our survey and found that the methodology developed was robust at absorbing the logistical challenges and wide range of observer abilities. This initiative serves as a functional model for estimating terrestrial wildlife abundance while integrating local people into scientific and conservation projects. This, in turn, creates vested interest in conservation by the people who are most influential in, and most affected by, the outcomes.

  11. Estimates of U.S. Biomass Energy Consumption 1992

    EIA Publications

    1994-01-01

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass derived primary energy used by the U.S. economy. It presents estimates of 1991 and 1992 consumption.

  12. Lidar point cloud representation of canopy structure for biomass estimation

    NASA Astrophysics Data System (ADS)

    Neuenschwander, A. L.; Krofcheck, D. J.; Litvak, M. E.

    2014-12-01

    Laser mapping systems (lidar) have become an essential remote sensing tool for determining local and regional estimates of biomass. Lidar data (possibly in conjunction with optical imagery) can be used to segment the landscape into either individual trees or clusters of trees. Canopy characteristics (i.e. max, mean height) for a segmented tree are typically derived from a rasterized canopy height model (CHM) and subsequently used in a regression model to estimate biomass. The process of rasterizing the lidar point cloud into a CHM, however, reduces the amount information about the tree structure. Here, we compute statistics for each segmented tree from the raw lidar point cloud rather than a rasterized CHM. Working directly from the lidar point cloud enables a more accurate representation of the canopy structure. Biomass estimates from the point cloud method are compared against biomass estimates derived from a CHM for a Juniper savanna in New Mexico.

  13. USING DIRICHLET TESSELLATION TO HELP ESTIMATE MICROBIAL BIOMASS CONCENTRATIONS

    EPA Science Inventory

    Dirichlet tessellation was applied to estimate microbial concentrations from microscope well slides. The use of microscopy/Dirichlet tessellation to quantify biomass was illustrated with two species of morphologically distinct cyanobacteria, and validated empirically by compariso...

  14. Linking Gap Model with MODIS Biophysical Products for Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Wang, D.; Sun, G.; Cai, Y.; Guo, Z.; Fu, A.; Ni, W.; Liu, D.

    With the development of earth observation technology and data processing technology biophysical data from remote sensing means such as MODIS LAI and NPP are accessible now However it is still difficult for direct measurement of biomass from remote sensors One possibility for overcoming this problem is using ecological models to link the vegetation parameters currently available from remote sensing to biomass In this paper a combined work is done for estimating forest biomass A calibrated gap model ZELIG was run to simulate the forest development in a temperate forested area in NE China The output relationship between age and biomass was linked to registered MODIS LAI NPP and land cover type images of the same area From the above work forest age or biomass was estimated from existing remote sensed data Obviously there is a lot of work to be done such as optimal combination of biophysical parameters to improve the linkage between MODIS product and ecological modeling

  15. [Abundance and biomass of meiobenthos in Lingdingyang Bay of Pearl River Estuary].

    PubMed

    Zhang, Jing-huai; Gao, Yang; Fang, Hong-da

    2011-10-01

    An investigation was conducted on the meiobenthic abundance and biomass in the Lingdingyang Bay of Pearl River Estuary in July-August 2006 (summer), April 2007 (spring), and October 2007 (autumn). A total of 15 meiobenthic groups were recorded, including Nematoda, Copepoda, Polychaeta, Ostracoda, Kinorhyncha, Amphipoda, Cumacea, Tanaidacea, Gnathostomulida, Nemertea, Gastropoda, Bivalvia, Sipuncula, Echiura, and other unidentified taxa. The average abundance of the meiobenthos in spring, summer, and autumn was 272.1 +/- 281.9, 165.1 +/- 147.1 and 246. 4 +/- 369.3 ind 10 cm(-2), and Nematoda was the most dominant group in abundance, accounting for 86.8%, 83.5%, and 93.4% of the total, respectively, followed by Polychaeta, and benthic Copepoda. The meiobenthic abundance had an uneven vertical distribution. 54.1% of the meibenthos were in 0-2 cm sediments, 35.2% were in 2-5 cm sediments, and 10.8% were in 5-10 cm sediments. 87.4% of nematodes were distributed in 0-5 cm sediments. The average biomass of the meiobenthos in spring, summer, and autumn was 374.6 +/- 346.9, 274.1 +/- 352.2, and 270.8 +/- 396.0 microg 10 cm(-2), and Polychaeta was the most dominant group in biomass, accounting for 30.1%, 46.7% and 46.0%, respectively, followed by Nematoda (25.2%, 20.1%, and 34.0%), and Ostracoda (20.6%, 15.3%, and 14.8%). The horizontal distribution of the meiobenthos had a trend of increasing from north to south, and being higher at east than at west. The meiobenthic abundance and biomass had significant positive correlations with water depth. PMID:22263483

  16. Evaluating noninvasive genetic sampling techniques to estimate large carnivore abundance.

    PubMed

    Mumma, Matthew A; Zieminski, Chris; Fuller, Todd K; Mahoney, Shane P; Waits, Lisette P

    2015-09-01

    Monitoring large carnivores is difficult because of intrinsically low densities and can be dangerous if physical capture is required. Noninvasive genetic sampling (NGS) is a safe and cost-effective alternative to physical capture. We evaluated the utility of two NGS methods (scat detection dogs and hair sampling) to obtain genetic samples for abundance estimation of coyotes, black bears and Canada lynx in three areas of Newfoundland, Canada. We calculated abundance estimates using program capwire, compared sampling costs, and the cost/sample for each method relative to species and study site, and performed simulations to determine the sampling intensity necessary to achieve abundance estimates with coefficients of variation (CV) of <10%. Scat sampling was effective for both coyotes and bears and hair snags effectively sampled bears in two of three study sites. Rub pads were ineffective in sampling coyotes and lynx. The precision of abundance estimates was dependent upon the number of captures/individual. Our simulations suggested that ~3.4 captures/individual will result in a < 10% CV for abundance estimates when populations are small (23-39), but fewer captures/individual may be sufficient for larger populations. We found scat sampling was more cost-effective for sampling multiple species, but suggest that hair sampling may be less expensive at study sites with limited road access for bears. Given the dependence of sampling scheme on species and study site, the optimal sampling scheme is likely to be study-specific warranting pilot studies in most circumstances. PMID:25693632

  17. [Optimized Spectral Indices Based Estimation of Forage Grass Biomass].

    PubMed

    An, Hai-bo; Li, Fei; Zhao, Meng-li; Liu, Ya-jun

    2015-11-01

    As an important indicator of forage production, aboveground biomass will directly illustrate the growth of forage grass. Therefore, Real-time monitoring biomass of forage grass play a crucial role in performing suitable grazing and management in artificial and natural grassland. However, traditional sampling and measuring are time-consuming and labor-intensive. Recently, development of hyperspectral remote sensing provides the feasibility in timely and nondestructive deriving biomass of forage grass. In the present study, the main objectives were to explore the robustness of published and optimized spectral indices in estimating biomass of forage grass in natural and artificial pasture. The natural pasture with four grazing density (control, light grazing, moderate grazing and high grazing) was designed in desert steppe, and different forage cultivars with different N rate were conducted in artificial forage fields in Inner Mongolia. The canopy reflectance and biomass in each plot were measured during critical stages. The result showed that, due to the influence in canopy structure and biomass, the canopy reflectance have a great difference in different type of forage grass. The best performing spectral index varied in different species of forage grass with different treatments (R² = 0.00-0.69). The predictive ability of spectral indices decreased under low biomass of desert steppe, while red band based spectral indices lost sensitivity under moderate-high biomass of forage maize. When band combinations of simple ratio and normalized difference spectral indices were optimized in combined datasets of natural and artificial grassland, optimized spectral indices significant increased predictive ability and the model between biomass and optimized spectral indices had the highest R² (R² = 0.72) compared to published spectral indices. Sensitive analysis further confirmed that the optimized index had the lowest noise equivalent and were the best performing index in

  18. Biomass Estimation for Individual Trees using Waveform LiDAR

    NASA Astrophysics Data System (ADS)

    Wang, K.; Kumar, P.; Dutta, D.

    2015-12-01

    Vegetation biomass information is important for many ecological models that include terrestrial vegetation in their simulations. Biomass has strong influences on carbon, water, and nutrient cycles. Traditionally biomass estimation requires intensive, and often destructive, field measurements. However, with advances in technology, airborne LiDAR has become a convenient tool for acquiring such information on a large scale. In this study, we use infrared full waveform LiDAR to estimate biomass information for individual trees in the Sangamon River basin in Illinois, USA. During this process, we also develop automated geolocation calibration algorithms for raw waveform LiDAR data. In the summer of 2014, discrete and waveform LiDAR data were collected over the Sangamon River basin. Field measurements commonly used in biomass equations such as diameter at breast height and total tree height were also taken for four sites across the basin. Using discrete LiDAR data, individual trees are delineated. For each tree, a voxelization methods is applied to all waveforms associated with the tree to result in a pseudo-waveform. By relating biomass extrapolated using field measurements from a training set of trees to waveform metrics for each corresponding tree, we are able to estimate biomass on an individual tree basis. The results can be especially useful as current models increase in resolution.

  19. Estimating vegetation biomass using synthetic aperture radar

    NASA Astrophysics Data System (ADS)

    Baronti, Stefano; Luciani, S.; Paloscia, Simonetta; Schiavon, G.; Sigismondi, S.; Solimini, Domenico

    1994-12-01

    A significant experiment for evaluating the potential of Synthetic Aperture Radar (SAR) in monitoring soil and vegetation parameters is being carried out on an agricultural area located in Central Italy. The site has been imaged in 1991 by NASA/JPL AIRSAR during the MAC-91 Campaign and subsequently by ESA/ERS-1 and NASDA JERS-1 in 1992. The sensitivity to vegetation biomass of backscattering coefficient measured by ERS-1 and JERS-1 radars is discussed and compared with the best results achieved using the multifrequency polarimetric AIRSAR data.

  20. Lincoln estimates of mallard (Anas platyrhynchos) abundance in North America

    PubMed Central

    Alisauskas, Ray T; Arnold, Todd W; Leafloor, James O; Otis, David L; Sedinger, James S

    2014-01-01

    Estimates of range-wide abundance, harvest, and harvest rate are fundamental for sound inferences about the role of exploitation in the dynamics of free-ranging wildlife populations, but reliability of existing survey methods for abundance estimation is rarely assessed using alternative approaches. North American mallard populations have been surveyed each spring since 1955 using internationally coordinated aerial surveys, but population size can also be estimated with Lincoln's method using banding and harvest data. We estimated late summer population size of adult and juvenile male and female mallards in western, midcontinent, and eastern North America using Lincoln's method of dividing (i) total estimated harvest, , by estimated harvest rate, , calculated as (ii) direct band recovery rate, , divided by the (iii) band reporting rate, . Our goal was to compare estimates based on Lincoln's method with traditional estimates based on aerial surveys. Lincoln estimates of adult males and females alive in the period June–September were 4.0 (range: 2.5–5.9), 1.8 (range: 0.6–3.0), and 1.8 (range: 1.3–2.7) times larger than respective aerial survey estimates for the western, midcontinent, and eastern mallard populations, and the two population estimates were only modestly correlated with each other (western: r = 0.70, 1993–2011; midcontinent: r = 0.54, 1961–2011; eastern: r = 0.50, 1993–2011). Higher Lincoln estimates are predictable given that the geographic scope of inference from Lincoln estimates is the entire population range, whereas sampling frames for aerial surveys are incomplete. Although each estimation method has a number of important potential biases, our review suggests that underestimation of total population size by aerial surveys is the most likely explanation. In addition to providing measures of total abundance, Lincoln's method provides estimates of fecundity and population sex ratio and could be used in integrated population

  1. Evaluation of SPOT imagery for the estimation of grassland biomass

    NASA Astrophysics Data System (ADS)

    Dusseux, P.; Hubert-Moy, L.; Corpetti, T.; Vertès, F.

    2015-06-01

    In many regions, a decrease in grasslands and change in their management, which are associated with agricultural intensification, have been observed in the last half-century. Such changes in agricultural practices have caused negative environmental effects that include water pollution, soil degradation and biodiversity loss. Moreover, climate-driven changes in grassland productivity could have serious consequences for the profitability of agriculture. The aim of this study was to assess the ability of remotely sensed data with high spatial resolution to estimate grassland biomass in agricultural areas. A vegetation index, namely the Normalized Difference Vegetation Index (NDVI), and two biophysical variables, the Leaf Area Index (LAI) and the fraction of Vegetation Cover (fCOVER) were computed using five SPOT images acquired during the growing season. In parallel, ground-based information on grassland growth was collected to calculate biomass values. The analysis of the relationship between the variables derived from the remotely sensed data and the biomass observed in the field shows that LAI outperforms NDVI and fCOVER to estimate biomass (R2 values of 0.68 against 0.30 and 0.50, respectively). The squared Pearson correlation coefficient between observed and estimated biomass using LAI derived from SPOT images reached 0.73. Biomass maps generated from remotely sensed data were then used to estimate grass reserves at the farm scale in the perspective of operational monitoring and forecasting.

  2. Secondary Forest Age and Tropical Forest Biomass Estimation Using TM

    NASA Technical Reports Server (NTRS)

    Nelson, R. F.; Kimes, D. S.; Salas, W. A.; Routhier, M.

    1999-01-01

    The age of secondary forests in the Amazon will become more critical with respect to the estimation of biomass and carbon budgets as tropical forest conversion continues. Multitemporal Thematic Mapper data were used to develop land cover histories for a 33,000 Square kM area near Ariquemes, Rondonia over a 7 year period from 1989-1995. The age of the secondary forest, a surrogate for the amount of biomass (or carbon) stored above-ground, was found to be unimportant in terms of biomass budget error rates in a forested TM scene which had undergone a 20% conversion to nonforest/agricultural cover types. In such a situation, the 80% of the scene still covered by primary forest accounted for over 98% of the scene biomass. The difference between secondary forest biomass estimates developed with and without age information were inconsequential relative to the estimate of biomass for the entire scene. However, in futuristic scenarios where all of the primary forest has been converted to agriculture and secondary forest (55% and 42% respectively), the ability to age secondary forest becomes critical. Depending on biomass accumulation rate assumptions, scene biomass budget errors on the order of -10% to +30% are likely if the age of the secondary forests are not taken into account. Single-date TM imagery cannot be used to accurately age secondary forests into single-year classes. A neural network utilizing TM band 2 and three TM spectral-texture measures (bands 3 and 5) predicted secondary forest age over a range of 0-7 years with an RMSE of 1.59 years and an R(Squared) (sub actual vs predicted) = 0.37. A proposal is made, based on a literature review, to use satellite imagery to identify general secondary forest age groups which, within group, exhibit relatively constant biomass accumulation rates.

  3. Estimating forest biomass and volume using airborne laser data

    NASA Technical Reports Server (NTRS)

    Nelson, Ross; Krabill, William; Tonelli, John

    1988-01-01

    An airborne pulsed laser system was used to obtain canopy height data over a southern pine forest in Georgia in order to predict ground-measured forest biomass and timber volume. Although biomass and volume estimates obtained from the laser data were variable when compared with the corresponding ground measurements site by site, the present models are found to predict mean total tree volume within 2.6 percent of the ground value, and mean biomass within 2.0 percent. The results indicate that species stratification did not consistently improve regression relationships for four southern pine species.

  4. Generalized estimators of avian abundance from count survey data

    USGS Publications Warehouse

    Royle, J. Andrew

    2004-01-01

    I consider modeling avian abundance from spatially referenced bird count data collected according to common protocols such as capture?recapture, multiple observer, removal sampling and simple point counts. Small sample sizes and large numbers of parameters have motivated many analyses that disregard the spatial indexing of the data, and thus do not provide an adequate treatment of spatial structure. I describe a general framework for modeling spatially replicated data that regards local abundance as a random process, motivated by the view that the set of spatially referenced local populations (at the sample locations) constitute a metapopulation. Under this view, attention can be focused on developing a model for the variation in local abundance independent of the sampling protocol being considered. The metapopulation model structure, when combined with the data generating model, define a simple hierarchical model that can be analyzed using conventional methods. The proposed modeling framework is completely general in the sense that broad classes of metapopulation models may be considered, site level covariates on detection and abundance may be considered, and estimates of abundance and related quantities may be obtained for sample locations, groups of locations, unsampled locations. Two brief examples are given, the first involving simple point counts, and the second based on temporary removal counts. Extension of these models to open systems is briefly discussed.

  5. Evaluating lidar point densities for effective estimation of aboveground biomass

    USGS Publications Warehouse

    Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.

    2016-01-01

    The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.

  6. Hydrogen Production Cost Estimate Using Biomass Gasification: Independent Review

    SciTech Connect

    Ruth, M.

    2011-10-01

    This independent review is the conclusion arrived at from data collection, document reviews, interviews and deliberation from December 2010 through April 2011 and the technical potential of Hydrogen Production Cost Estimate Using Biomass Gasification. The Panel reviewed the current H2A case (Version 2.12, Case 01D) for hydrogen production via biomass gasification and identified four principal components of hydrogen levelized cost: CapEx; feedstock costs; project financing structure; efficiency/hydrogen yield. The panel reexamined the assumptions around these components and arrived at new estimates and approaches that better reflect the current technology and business environments.

  7. [Abundance and biomass of meiobenthos in Southern Yellow Sea in winter].

    PubMed

    Zhang, Yan; Zhang, Zhi-nan; Huang, Yong; Hua, Er

    2007-02-01

    A two cruises investigation on the meiobenthos in the continental shelf of Southern Yellow Sea was made in January 2003 and January 2004. The results showed that the average abundance of meiobenthos was (954.20 +/- 269.47) ind x 10 cm(-2) and ( 1 186.12+/- 486.07) ind x 10 cm(-2), and the biomass was (954.38+/-403.93) microg x10 cm(-2) and (1 120.72+/-487.21 ) mg x 10 cm(-2) in January 2003 and January 2004, respectively, with no significant difference observed. A total of twenty meiobenthic groups were identified. Free-living marine nematodes was the most dominant group in abundance, with a relative dominance of 87% in 2003 and 90% in 2004, followed by benthic harpacticoids copepoda, polychaeta and kinorhyncha. In terms of biomass, the dominant groups were nematoda (34% -38%), polychaeta (25% -33%), ostracoda (9% -22%) and copepoda (8%). 96. 64% of the meiobenthos distributed in the top 0-5 cm of sediment, while 72. 48% of nematode and 89. 46% of copepoda were in the top 0-2 cm of the sediment. Meiobenthos biomass had significant correlation with the sand and silt contents of sediment and the content of Chl-a. The species composition and biodiversity analyses of six representative stations indicated that there were three meiobenthos communities in the study area, i. e. , inshore, cold waters mass, and transitional communities. PMID:17450749

  8. Comparative study of above ground biomass estimates for conterminous US

    NASA Astrophysics Data System (ADS)

    Neeti, N.; Kennedy, R. E.

    2013-12-01

    Accurate estimates of forest biomass are important for carbon accounting at both regional and national scale. There are four above ground biomass (AGB) maps available for conterminous US, one from the National Aeronautics and Space Administration (NASA), two from the United States Forest Service (USFS) (Blackard and Wilson) and one from the Woods Hole Research Center (WHRC). Although all four maps are meant to represent similar quantities, spatial patterns of AGB vary considerably from map to map. To use any of these AGB maps for carbon accounting, it is important to understand sources of uncertainty in individual maps and agreement and disagreement among them. Therefore, we compared the four AGB maps at ecoregion and state level to gain understanding of map consistency, leveraging discrepancies among maps to gain insight into the method and data sources. We also developed statewide summaries to compare with FIA forest AGB estimates, which are typically reported at the state level. We examined both absolute differences among these aggregated maps, and relative differences among regions within each map. The result shows that NASA biomass estimates are highest and Blackard estimates are lowest compared to other maps at both ecoregion and state level. The AGB for WHRC and Wilson are very similar at both ecoregion and state level specifically in the lower biomass regions compared to higher biomass regions. This could be associated with the differences in the spatial resolution of the data sources uses to generate these maps. At state level, WHRC map is found to be most similar and NASA biomass estimates least similar to FIA plot data. We discuss these differences in light of the different methods and data sources used to generate the maps.

  9. Estimating abundance of mountain lions from unstructured spatial sampling

    USGS Publications Warehouse

    Russell, Robin E.; Royle, J. Andrew; Desimone, Richard; Schwartz, Michael K.; Edwards, Victoria L.; Pilgrim, Kristy P.; Mckelvey, Kevin S.

    2012-01-01

    Mountain lions (Puma concolor) are often difficult to monitor because of their low capture probabilities, extensive movements, and large territories. Methods for estimating the abundance of this species are needed to assess population status, determine harvest levels, evaluate the impacts of management actions on populations, and derive conservation and management strategies. Traditional mark–recapture methods do not explicitly account for differences in individual capture probabilities due to the spatial distribution of individuals in relation to survey effort (or trap locations). However, recent advances in the analysis of capture–recapture data have produced methods estimating abundance and density of animals from spatially explicit capture–recapture data that account for heterogeneity in capture probabilities due to the spatial organization of individuals and traps. We adapt recently developed spatial capture–recapture models to estimate density and abundance of mountain lions in western Montana. Volunteers and state agency personnel collected mountain lion DNA samples in portions of the Blackfoot drainage (7,908 km2) in west-central Montana using 2 methods: snow back-tracking mountain lion tracks to collect hair samples and biopsy darting treed mountain lions to obtain tissue samples. Overall, we recorded 72 individual capture events, including captures both with and without tissue sample collection and hair samples resulting in the identification of 50 individual mountain lions (30 females, 19 males, and 1 unknown sex individual). We estimated lion densities from 8 models containing effects of distance, sex, and survey effort on detection probability. Our population density estimates ranged from a minimum of 3.7 mountain lions/100 km2 (95% Cl 2.3–5.7) under the distance only model (including only an effect of distance on detection probability) to 6.7 (95% Cl 3.1–11.0) under the full model (including effects of distance, sex, survey effort, and

  10. Methyl halide emission estimates from domestic biomass burning in Africa

    NASA Astrophysics Data System (ADS)

    Mead, M. I.; Khan, M. A. H.; White, I. R.; Nickless, G.; Shallcross, D. E.

    Inventories of methyl halide emissions from domestic burning of biomass in Africa, from 1950 to the present day and projected to 2030, have been constructed. By combining emission factors from Andreae and Merlet [2001. Emission of trace gases and aerosols from biomass burning. Global Biogeochemical Cycles 15, 955-966], the biomass burning estimates from Yevich and Logan [2003. An assessment of biofuel use and burning of agricultural waste in the developing world. Global Biogeochemical Cycles 17(4), 1095, doi:10.1029/2002GB001952] and the population data from the UN population division, the emission of methyl halides from domestic biomass usage in Africa has been estimated. Data from this study suggest that methyl halide emissions from domestic biomass burning have increased by a factor of 4-5 from 1950 to 2005 and based on the expected population growth could double over the next 25 years. This estimated change has a non-negligible impact on the atmospheric budgets of methyl halides.

  11. Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems

    NASA Technical Reports Server (NTRS)

    Saatchi, Sassan; Moghaddam, Mahta

    1995-01-01

    In this paper, we report on the use of a semiempirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy. of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.

  12. Tropical Africa: Land use, biomass, and carbon estimates for 1980

    SciTech Connect

    Brown, S.; Gaston, G.; Daniels, R.C.

    1996-06-01

    This document describes the contents of a digital database containing maximum potential aboveground biomass, land use, and estimated biomass and carbon data for 1980 and describes a methodology that may be used to extend this data set to 1990 and beyond based on population and land cover data. The biomass data and carbon estimates are for woody vegetation in Tropical Africa. These data were collected to reduce the uncertainty associated with the possible magnitude of historical releases of carbon from land use change. Tropical Africa is defined here as encompassing 22.7 x 10{sup 6} km{sup 2} of the earth`s land surface and includes those countries that for the most part are located in Tropical Africa. Countries bordering the Mediterranean Sea and in southern Africa (i.e., Egypt, Libya, Tunisia, Algeria, Morocco, South Africa, Lesotho, Swaziland, and Western Sahara) have maximum potential biomass and land cover information but do not have biomass or carbon estimate. The database was developed using the GRID module in the ARC/INFO{sup TM} geographic information system. Source data were obtained from the Food and Agriculture Organization (FAO), the U.S. National Geophysical Data Center, and a limited number of biomass-carbon density case studies. These data were used to derive the maximum potential and actual (ca. 1980) aboveground biomass-carbon values at regional and country levels. The land-use data provided were derived from a vegetation map originally produced for the FAO by the International Institute of Vegetation Mapping, Toulouse, France.

  13. The cryptofauna of Zostera marina (L.): Abundance, biomass and population dynamics

    NASA Astrophysics Data System (ADS)

    Pihl Baden, Susanne

    Cryptofauna (epifauna passing a 2-mm but retained on a 0.2-mm mesh sieve) of Zostera marina on the Swedish west coast (58°N, 11°E) is dominated by crustaceans, mainly detritivorous tube-building amphipods and harpacticoids. Abundance and biomass of amphipods in two relatively unpolluted Z. marina beds were higher than any data from the literature, with maximum abundance of 80·10 3 ind·m -2 and 1 g AFDW·m -2 bottom. This is at least partly due to the small mesh size used in this investigation. The recruitment of the crustaceans started in late June and was continuous through the rest of the season, whereas the recruitment of the molluscs peaked in late June and July. In a Z. marina bed (Rixö) located 2 km from an oil refinery, the seasonal abundance of amphipods was 15% of the abundance in the other beds, whereas the remaining fauna had about the same density. In Rixö the percentage of female amphipod with empty brood pouches increased during the season. It is suggested that low abundances and fecundity of amphipods in Rixö could result from oil pollution.

  14. Research of a new model for abundance estimation

    NASA Astrophysics Data System (ADS)

    Xie, Hong-ye; Song, Mei-ping; Lin, Bin; An, Ju-bai

    2013-08-01

    Hyperspectral remote sensing has been widely used in more and more fields nowadays, such as the oil spill analysis and chlorophyll estimation in green plants. To decompose the mixed pixels people always turns to the traditional method of Least Squares Method now. But its main drawback is that it involves a large amount of matrix operations, especially regarding to the huge dimension of hyperspectral images. So it will take much time. Motivated by this, in this paper we have developed a new model of endmember abundance estimate which is referred to as Spectral Characteristic Based Abundance Estimation Model (SCBAEM). The model is based on the fitted curve in which spectral characteristic were considered. To establish the model, Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) were utilized between endmember and mixed pixels. The main contributions of the paper are summarized as follows: Firstly, we build the model by calculating normalized SAM (NSAM) and normalized SID (NSID). Secondly, to test and verify the accuracy of the model, oil slick experiment is carried out. Finally, we further conduct its application in the real hyperspectral oil spill images which is from Peng-lai 19-3C platform. The results of simulation experiments and real hyperspectral image demonstrate that the proposed model could achieve the efficiency of LSM. At the same time, the time cost can be reduced greatly. So it can satisfy the real-time need.

  15. Evaluation of marked-recapture for estimating striped skunk abundance

    USGS Publications Warehouse

    Greenwood, R.J.; Sargeant, A.B.; Johnson, D.H.

    1985-01-01

    The mark-recapture method for estimating striped skunk (Mephitis mephitis) abundance was evaluated by systematically livetrapping a radio-equipped population on a 31.4-km2 study area in North Dakota during late April of 1977 and 1978. The study population was 10 females and 13 males in 1977 and 20 females and 8 males in 1978. Skunks were almost exclusively nocturnal. Males traveled greater nightly distances than females (3.3 vs. 2.6 km, P < 0.05) and had larger home ranges (308 vs. 242 ha) although not significantly so. Increased windchill reduced night-time activity. The population was demographically but not geographically closed. Frequency of capture was positively correlated with time skunks spent on the study area. Little variation in capture probabilities was found among trap-nights. Skunks exhibited neither trap-proneness nor shyness. Capture rates in 1977 were higher for males than for females; the reverse occurred in 1978. Variation in individual capture rates was indicated among males in 1977 and among females in 1978. Ten estimators produced generally similar results, but all underestimated true population size. Underestimation was a function of the number of untrapped skunks, primarily those that spent limited time on the study area. The jackknife method produced the best estimates of skunk abundance.

  16. Survey estimates of fishable biomass following a mass mortality in an Australian molluscan fishery.

    PubMed

    Mayfield, S; McGarvey, R; Gorfine, H K; Peeters, H; Burch, P; Sharma, S

    2011-04-01

    Mass mortality events are relatively uncommon in commercially fished populations, but when they occur, they reduce production and degrade ecosystems. Observing and documenting mass mortalities is simpler than quantifying the impact on stocks, monitoring or predicting recovery, and re-establishing commercial fishing. Direct survey measures of abundance, distribution and harvestable biomass provide the most tenable approach to informing decisions about future harvests in cases where stock collapses have occurred because conventional methods have been disrupted and are less applicable. Abalone viral ganglioneuritis (AVG) has resulted in high levels of mortality across all length classes of blacklip abalone, Haliotis rubra Leach, off western Victoria, Australia, since May 2006. Commercial catches in this previously valuable fishery were reduced substantially. This paper describes the integration of research surveys with commercial fishermen's knowledge to estimate the biomass of abalone on AVG-impacted reefs. Experienced commercial abalone divers provided credible information on the precise locations of historical fishing grounds within which fishery-independent surveys were undertaken. Abalone density estimates remained low relative to pre-AVG levels, and total biomass estimates were similar to historical annual catch levels, indicating that the abalone populations have yet to adequately recover. Survey biomass estimates were incorporated into harvest decision tables and used with prior accumulated knowledge of the populations to determine a conservative harvest strategy for the fishery. PMID:21382050

  17. Bacterial abundance, biomass and production during spring blooms in the northern Barents Sea

    NASA Astrophysics Data System (ADS)

    Sturluson, Maria; Gissel Nielsen, Torkel; Wassmann, Paul

    2008-10-01

    To evaluate importance of bacterioplankton in the Barents Sea, we investigated the spatial and temporal distribution of bacterial abundance, biomass and production in relation to spring-bloom stages. During three cruises in 2003-2005, 12 stations were investigated. Average bacterial abundance (±S.D.) in the photic zone was 3.6±3.0×10 5 cells ml -1, corresponding to 7.1±6.1 mg C m -3. Bacterial production in the photic zone was measured using dual labelling technique with 3H-thymidine and 14C-leucine, resulting in average production rates (±S.D.) of 1.5±1.0 and 6.9±4.8 mg C m -3 d -1, respectively. In spite of low water temperature, the bacterial community was well developed and active. Similarity analysis of stations resulted in four distinct spring-bloom stages, covering pre- early-, late- and post-bloom stages. In the photic zone, bacterial biomass on average corresponded to 6±2% of phytoplankton biomass. Highest integrated bacterial biomass was observed at mid- to late-bloom stages. Average bacterial production equalled 32±6% (±S.E., n=24) of particulate primary production. The bacterial production to primary production ratio tended to increase at late-bloom stages. The observed bacterial activity illustrates the importance of the bacterial pathway for channelling carbon from DOC through the microbial food web back into the classical food web, which previously has not been adequately considered in plankton ecosystem models of the Barents Sea.

  18. First-order estimate of the planktic foraminifer biomass in the modern ocean

    NASA Astrophysics Data System (ADS)

    Schiebel, R.; Movellan, A.

    2012-09-01

    Planktic foraminifera are heterotrophic mesozooplankton of global marine abundance. The position of planktic foraminifers in the marine food web is different compared to other protozoans and ranges above the base of heterotrophic consumers. Being secondary producers with an omnivorous diet, which ranges from algae to small metazoans, planktic foraminifers are not limited to a single food source, and are assumed to occur at a balanced abundance displaying the overall marine biological productivity at a regional scale. With a new non-destructive protocol developed from the bicinchoninic acid (BCA) method and nano-photospectrometry, we have analysed the protein-biomass, along with test size and weight, of 754 individual planktic foraminifers from 21 different species and morphotypes. From additional CHN analysis, it can be assumed that protein-biomass equals carbon-biomass. Accordingly, the average individual planktic foraminifer protein- and carbon-biomass amounts to 0.845 μg. Samples include symbiont bearing and symbiont-barren species from the sea surface down to 2500 m water depth. Conversion factors between individual biomass and assemblage-biomass are calculated for test sizes between 72 and 845 μm (minimum test diameter). Assemblage-biomass data presented here include 1128 sites and water depth intervals. The regional coverage of data includes the North Atlantic, Arabian Sea, Red Sea, and Caribbean as well as literature data from the eastern and western North Pacific, and covers a wide range of oligotrophic to eutrophic waters over six orders of magnitude of planktic-foraminifer assemblage-biomass (PFAB). A first order estimate of the average global planktic foraminifer biomass production (>125 μm) ranges from 8.2-32.7 Tg C yr-1 (i.e. 0.008-0.033 Gt C yr-1), and might be more than three times as high including neanic and juvenile individuals adding up to 25-100 Tg C yr-1. However, this is a first estimate of regional PFAB extrapolated to the global scale

  19. First-order estimate of the planktic foraminifer biomass in the modern global oceans

    NASA Astrophysics Data System (ADS)

    Schiebel, R.; Movellan, A.

    2012-04-01

    Planktic foraminifera are heterotrophic mesozooplankton of global marine abundance. The position of planktic foraminifers in the marine food web is different compared to other protozoans and ranges above the base of heterotrophic consumers. Being secondary producers with an omnivorous diet, which ranges from algae to small metazoans, planktic foraminifers are not limited to a single food source, and are assumed to occur at a balanced abundance displaying the overall marine biological productivity at a regional scale. We have calculated the assemblage carbon biomass from data on standing stocks between the sea surface and 2500 m water depth, based on 754 protein-biomass data of 21 planktic foraminifer species and morphotypes, produced with a newly developed method to analyze the protein biomass of single planktic foraminifer specimens. Samples include symbiont bearing and symbiont barren species, characteristic of surface and deep-water habitats. Conversion factors between individual protein-biomass and assemblage-biomass are calculated for test sizes between 72 and 845 μm (minimum diameter). The calculated assemblage biomass data presented here include 1057 sites and water depth intervals. Although the regional coverage of database is limited to the North Atlantic, Arabian Sea, Red Sea, and Caribbean, our data include a wide range of oligotrophic to eutrophic waters covering six orders of magnitude of assemblage biomass. A first order estimate of the global planktic foraminifer biomass from average standing stocks (>125 μm) ranges at 8.5-32.7 Tg C yr-1 (i.e. 0.008-0.033 Gt C yr-1), and might be more than three time as high including the entire fauna including neanic and juvenile individuals adding up to 25-100 Tg C yr-1. However, this is a first estimate of regional planktic-foraminifer assemblage-biomass (PFAB) extrapolated to the global scale, and future estimates based on larger data-sets might considerably deviate from the one presented here. This paper is

  20. Hydroacoustic estimates of fish abundance. Reservoir vital signs monitoring, 1990

    SciTech Connect

    Wilson, W.K.

    1991-03-01

    Hydroacoustics, as defined in the context of this report, is the use of a scientific sonar system to determine fish densities with respect to numbers and biomass. These two parameters provide a method of monitoring reservoir fish populations and detecting gross changes in the ecosystem. With respect to southeastern reservoirs, hydroacoustic surveys represent a new method of sampling open water areas and the best technology available. The advantages of this technology are large amounts of data can be collected in a relatively short period of time allowing improved statistical interpretation and data comparison, the pelagic (open water) zone can be sampled efficiently regardless of depth, and sampling is nondestructive and noninvasive with neither injury to the fish nor alteration of the environment. Hydroacoustics cannot provide species identification and related information on species composition or length/weight relationships. Also, sampling is limited to a minimum depth of ten feet which precludes the use of this equipment for sampling shallow shoreline areas. The objective of this study is to use hydroacoustic techniques to estimate fish standing stocks (i.e., numbers and biomass) in several areas of selected Tennessee Valley Reservoirs as part of a base level monitoring program to assess long-term changes in reservoir water quality.

  1. Spectral abundance fraction estimation of materials using Kalman filters

    NASA Astrophysics Data System (ADS)

    Wang, Su; Chang, Chein; Jensen, Janet L.; Jensen, James O.

    2004-12-01

    Kalman filter has been widely used in statistical signal processing for parameter estimation. Although a Kalman filter approach has been recently developed for spectral unmixing, referred to as Kalman filter-based linear unmixing (KFLU), its applicability to spectral characterization within a single pixel vector has not been explored. This paper presents a new application of Kalman filtering in spectral estimation and quantification. It develops a Kalman filter-based spectral signature esimator (KFSSE) which is different from the KFLU in the sense that the former performs a Kalman filter wavelength by wavelength across a spectral signature as opposed to the latter which implements a Kalman filter pixel vector by pixel vector in an image cube. The idea of the KFSSE is to implement the state equation to characterize the true spectral signature, while the measurement equation is being used to describe the spectral signature to be processed. Additionally, since a Kalman filter can accurately estimate spectral abundance fraction of a signature, our proposed KFSSE can further used for spectral quantification for subpixel targets and mixed pixel vectors, called Kalman filter-based spectral quantifier (KFSQ). Such spectral quantification is particularly important for chemical/biological defense which requires quantification of detected agents for damage control assessment. Several different types of hyperspectral data are used for experiments to demonstrate the ability of the KFSSE in estimation of spectral signature and the utility of the KFSQ in spectral quantification.

  2. Negative binomial models for abundance estimation of multiple closed populations

    USGS Publications Warehouse

    Boyce, Mark S.; MacKenzie, Darry I.; Manly, Bryan F.J.; Haroldson, Mark A.; Moody, David W.

    2001-01-01

    Counts of uniquely identified individuals in a population offer opportunities to estimate abundance. However, for various reasons such counts may be burdened by heterogeneity in the probability of being detected. Theoretical arguments and empirical evidence demonstrate that the negative binomial distribution (NBD) is a useful characterization for counts from biological populations with heterogeneity. We propose a method that focuses on estimating multiple populations by simultaneously using a suite of models derived from the NBD. We used this approach to estimate the number of female grizzly bears (Ursus arctos) with cubs-of-the-year in the Yellowstone ecosystem, for each year, 1986-1998. Akaike's Information Criteria (AIC) indicated that a negative binomial model with a constant level of heterogeneity across all years was best for characterizing the sighting frequencies of female grizzly bears. A lack-of-fit test indicated the model adequately described the collected data. Bootstrap techniques were used to estimate standard errors and 95% confidence intervals. We provide a Monte Carlo technique, which confirms that the Yellowstone ecosystem grizzly bear population increased during the period 1986-1998.

  3. Heterogeneity of macrozoobenthic assemblages within a Zostera noltii seagrass bed: diversity, abundance, biomass and structuring factors

    NASA Astrophysics Data System (ADS)

    Blanchet, Hugues; de Montaudouin, Xavier; Lucas, Aurélien; Chardy, Pierre

    2004-09-01

    The macrobenthic fauna community of a 70-km 2Zostera noltii seagrass bed (Arcachon bay, France) was studied by sampling 49 stations systematically. A total of 126 taxa were identified. Cluster Analysis based on χ2 distance showed that in this apparently homogeneous habitat, four distinct macrobenthic communities could be identified. Multiple Discriminant Analysis highlighted the major contribution of the overlying water mass as a forcing variable, and, to a lesser extent, of tidal level and Z. noltii's below-ground parts. Seven stations did not constitute any conspicuous group, and were characterized by a low biomass of leaf (<28 g DW m -2), considered as the lowest value to constitute a Z. noltii community. Less than 24% of the seagrass bed was situated in more oceanic waters and at a quite low tidal level. In this relatively stable environment, the macrofauna community was characterized by a high species richness (mean = 39) and a moderate density and high biomass (12 638 individuals m -2 and 25 g AFDW m -2, respectively). Annelids dominated, particularly the oligochaetes. When physical constraints increased (emersion or brackish water conditions), diversity decreased, abundance and biomass increased. The seagrass bed (55%) was flooded with highly fluctuating waters in term of temperature and salinity, here species richness was low (mean = 27) but abundance and biomass were high (24 384 individuals m -2 and 28 g AFDW m -2, respectively), with a dominance of molluscs. The meadow (7%) was in external waters but at a higher tidal level (2.4 m vs 1.8 m above medium low tide level). This community was characterized by the particularly high density (41 826 individuals m -2) and dominance of oligochaetes (79% of total abundance). Species richness was high (mean = 37) here. A fourth community, extending over 12% of the meadow was dominated by the gastropod Hydrobia ulvae but could not be linked to a specific forcing variable. This study confirmed the almost

  4. Wavelet analysis for aboveground biomass estimate in temperate deciduous forests

    NASA Astrophysics Data System (ADS)

    Wei, Xiao-Fang

    2008-10-01

    The ever-increasing concentration of anthropogenic greenhouse gases (CO2, CH4, and CFCs) has been identified as a likely (greater than 90% confidence) cause of the observed increase of global mean temperatures since the mid-20th century (IPCC, 2007). The effect of human-induced climate change could be unprecedented and far-reaching. Carbon sequestration into trees and forests is an effective and inexpensive way for mitigating the CO2 level in the atmosphere. Hence, accurate measurement of biomass will be of great importance to global carbon cycle and climate change. This study performed a wavelet-based forest aboveground biomass estimation approach in a temperate deciduous forest, the Hoosier National Forest, in Indiana. Wavelet analysis, specifically two-dimensional discrete wavelet transform (DWT) was applied to ASTER images to obtain wavelet coefficients (WCs), which were correlated with forest inventory data using multiple linear regression analysis to investigate the relationship. Different mother wavelets and level of decomposition were tested. Moreover, vegetation indices, RATIO, normalized difference vegetation index (NDVI), and principal component analyses (PCA) were computed and correlated with field biomass measurements. The results indicate that wavelet coefficients correlate better with field biomass data than vegetation indices. For level one decomposition, the correlation coefficients are 0.3 to 0.5, while 0.1-0.3 for vegetation indices; for level two decomposition, the overall R value increased by 0.2, and for level three, the R value can be increased to 0.6-0.7. Meanwhile, tree per acre and basal area were also examined and correlated with field measurements. This study demonstrates that wavelet-based biomass estimation could be a very promising approach for solving the uncertainty between reflectance value from satellite images and forest biomass and therefore providing better biomass estimation; however, further research is needed for identifying

  5. Biomass estimation to support pasture management in Niger

    NASA Astrophysics Data System (ADS)

    Schucknecht, A.; Meroni, M.; Kayitakire, F.; Rembold, F.; Boureima, A.

    2015-04-01

    Livestock plays a central economic role in Niger, but it is highly vulnerable due to the high inter-annual variability of rain and hence pasture production. This study aims to develop an approach for mapping pasture biomass production to support activities of the Niger Ministry of Livestock for effective pasture management. Our approach utilises the observed spatiotemporal variability of biomass production to build a predictive model based on ground and remote sensing data for the period 1998-2012. Measured biomass (63 sites) at the end of the growing season was used for the model parameterisation. The seasonal cumulative Fraction of Absorbed Photosynthetically Active Radiation (CFAPAR), calculated from 10-day image composites of SPOT-VEGETATION FAPAR, was computed as a phenology-tuned proxy of biomass production. A linear regression model was tested aggregating field data at different levels (global, department, agro-ecological zone, and intersection of agro-ecological and department units) and subjected to a cross validation (cv) by leaving one full year out. An increased complexity (i.e. spatial detail) of the model increased the estimation performances indicating the potential relevance of additional and spatially heterogeneous agro-ecological characteristics for the relationship between herbaceous biomass at the end of the season and CFAPAR. The model using the department aggregation yielded the best trade-off between model complexity and predictive power (R2 = 0.55, R2cv = 0.48). The proposed approach can be used to timely produce maps of estimated biomass at the end of the growing season before ground point measurements are made available.

  6. Estimation of old field ecosystem biomass using low altitude imagery

    NASA Technical Reports Server (NTRS)

    Nor, S. M.; Safir, G.; Burton, T. M.; Hook, J. E.; Schultink, G.

    1977-01-01

    Color-infrared photography was used to evaluate the biomass of experimental plots in an old-field ecosystem that was treated with different levels of waste water from a sewage treatment facility. Cibachrome prints at a scale of approximately 1:1,600 produced from 35 mm color infrared slides were used to analyze density patterns using prepared tonal density scales and multicell grids registered to ground panels shown on the photograph. Correlation analyses between tonal density and vegetation biomass obtained from ground samples and harvests were carried out. Correlations between mean tonal density and harvest biomass data gave consistently high coefficients ranging from 0.530 to 0.896 at the 0.001 significance level. Corresponding multiple regression analysis resulted in higher correlation coefficients. The results of this study indicate that aerial infrared photography can be used to estimate standing crop biomass on waste water irrigated old field ecosystems. Combined with minimal ground truth data, this technique could enable managers of wastewater irrigation projects to precisely time harvest of such systems for maximal removal of nutrients in harvested biomass.

  7. Stratified aboveground forest biomass estimation by remote sensing data

    NASA Astrophysics Data System (ADS)

    Latifi, Hooman; Fassnacht, Fabian E.; Hartig, Florian; Berger, Christian; Hernández, Jaime; Corvalán, Patricio; Koch, Barbara

    2015-06-01

    Remote sensing-assisted estimates of aboveground forest biomass are essential for modeling carbon budgets. It has been suggested that estimates can be improved by building species- or strata-specific biomass models. However, few studies have attempted a systematic analysis of the benefits of such stratification, especially in combination with other factors such as sensor type, statistical prediction method and sampling design of the reference inventory data. We addressed this topic by analyzing the impact of stratifying forest data into three classes (broadleaved, coniferous and mixed forest). We compare predictive accuracy (a) between the strata (b) to a case without stratification for a set of pre-selected predictors from airborne LiDAR and hyperspectral data obtained in a managed mixed forest site in southwestern Germany. We used 5 commonly applied algorithms for biomass predictions on bootstrapped subsamples of the data to obtain cross validated RMSE and r2 diagnostics. Those values were analyzed in a factorial design by an analysis of variance (ANOVA) to rank the relative importance of each factor. Selected models were used for wall-to-wall mapping of biomass estimates and their associated uncertainty. The results revealed marginal advantages for the strata-specific prediction models over the unstratified ones, which were more obvious on the wall-to-wall mapped area-based predictions. Yet further tests are necessary to establish the generality of these results. Input data type and statistical prediction method are concluded to remain the two most crucial factors for the quality of remote sensing-assisted biomass models.

  8. Metagenomic abundance estimation and diagnostic testing on species level

    PubMed Central

    Lindner, Martin S.; Renard, Bernhard Y.

    2013-01-01

    One goal of sequencing-based metagenomic community analysis is the quantitative taxonomic assessment of microbial community compositions. In particular, relative quantification of taxons is of high relevance for metagenomic diagnostics or microbial community comparison. However, the majority of existing approaches quantify at low resolution (e.g. at phylum level), rely on the existence of special genes (e.g. 16S), or have severe problems discerning species with highly similar genome sequences. Yet, problems as metagenomic diagnostics require accurate quantification on species level. We developed Genome Abundance Similarity Correction (GASiC), a method to estimate true genome abundances via read alignment by considering reference genome similarities in a non-negative LASSO approach. We demonstrate GASiC’s superior performance over existing methods on simulated benchmark data as well as on real data. In addition, we present applications to datasets of both bacterial DNA and viral RNA source. We further discuss our approach as an alternative to PCR-based DNA quantification. PMID:22941661

  9. Optimizing Sampling Efficiency for Biomass Estimation Across NEON Domains

    NASA Astrophysics Data System (ADS)

    Abercrombie, H. H.; Meier, C. L.; Spencer, J. J.

    2013-12-01

    Over the course of 30 years, the National Ecological Observatory Network (NEON) will measure plant biomass and productivity across the U.S. to enable an understanding of terrestrial carbon cycle responses to ecosystem change drivers. Over the next several years, prior to operational sampling at a site, NEON will complete construction and characterization phases during which a limited amount of sampling will be done at each site to inform sampling designs, and guide standardization of data collection across all sites. Sampling biomass in 60+ sites distributed among 20 different eco-climatic domains poses major logistical and budgetary challenges. Traditional biomass sampling methods such as clip harvesting and direct measurements of Leaf Area Index (LAI) involve collecting and processing plant samples, and are time and labor intensive. Possible alternatives include using indirect sampling methods for estimating LAI such as digital hemispherical photography (DHP) or using a LI-COR 2200 Plant Canopy Analyzer. These LAI estimations can then be used as a proxy for biomass. The biomass estimates calculated can then inform the clip harvest sampling design during NEON operations, optimizing both sample size and number so that standardized uncertainty limits can be achieved with a minimum amount of sampling effort. In 2011, LAI and clip harvest data were collected from co-located sampling points at the Central Plains Experimental Range located in northern Colorado, a short grass steppe ecosystem that is the NEON Domain 10 core site. LAI was measured with a LI-COR 2200 Plant Canopy Analyzer. The layout of the sampling design included four, 300 meter transects, with clip harvests plots spaced every 50m, and LAI sub-transects spaced every 10m. LAI was measured at four points along 6m sub-transects running perpendicular to the 300m transect. Clip harvest plots were co-located 4m from corresponding LAI transects, and had dimensions of 0.1m by 2m. We conducted regression analyses

  10. Error propagation and scaling for tropical forest biomass estimates.

    PubMed Central

    Chave, Jerome; Condit, Richard; Aguilar, Salomon; Hernandez, Andres; Lao, Suzanne; Perez, Rolando

    2004-01-01

    The above-ground biomass (AGB) of tropical forests is a crucial variable for ecologists, biogeochemists, foresters and policymakers. Tree inventories are an efficient way of assessing forest carbon stocks and emissions to the atmosphere during deforestation. To make correct inferences about long-term changes in biomass stocks, it is essential to know the uncertainty associated with AGB estimates, yet this uncertainty is rarely evaluated carefully. Here, we quantify four types of uncertainty that could lead to statistical error in AGB estimates: (i) error due to tree measurement; (ii) error due to the choice of an allometric model relating AGB to other tree dimensions; (iii) sampling uncertainty, related to the size of the study plot; (iv) representativeness of a network of small plots across a vast forest landscape. In previous studies, these sources of error were reported but rarely integrated into a consistent framework. We estimate all four terms in a 50 hectare (ha, where 1 ha = 10(4) m2) plot on Barro Colorado Island, Panama, and in a network of 1 ha plots scattered across central Panama. We find that the most important source of error is currently related to the choice of the allometric model. More work should be devoted to improving the predictive power of allometric models for biomass. PMID:15212093

  11. Afforestation impacts microbial biomass and its natural (13)C and (15)N abundance in soil aggregates in central China.

    PubMed

    Wu, Junjun; Zhang, Qian; Yang, Fan; Lei, Yao; Zhang, Quanfa; Cheng, Xiaoli

    2016-10-15

    We investigated soil microbial biomass and its natural abundance of δ(13)C and δ(15)N in aggregates (>2000μm, 250-2000μm, 53-250μm and <53μm) of afforested (implementing woodland and shrubland plantations) soils, adjacent croplands and open area (i.e., control) in the Danjiangkou Reservoir area of central China. The afforested soils averaged higher microbial biomass carbon (MBC) and nitrogen (MBN) levels in all aggregates than in open area and cropland, with higher microbial biomass in micro-aggregates (<250μm) than in macro-aggregates (>2000μm). The δ(13)C of soil microbial biomass was more enriched in woodland soils than in other land use types, while δ(15)N of soil microbial biomass was more enriched compared with that of organic soil in all land use types. The δ(13)C and δ(15)N of microbial biomass were positively correlated with the δ(13)C and δ(15)N of organic soil across aggregates and land use types, whereas the (13)C and (15)N enrichment of microbial biomass exhibited linear decreases with the corresponding C:N ratio of organic soil. Our results suggest that shifts in the natural (13)C and (15)N abundance of microbial biomass reflect changes in the stabilization and turnover of soil organic matter (SOM) and thereby imply that afforestation can greatly impact SOM accumulation over the long-term. PMID:27285796

  12. Estimation of old field ecosystem biomass using low altitude imagery

    NASA Technical Reports Server (NTRS)

    Nor, S. M.; Safir, G.; Burton, T. M.; Hook, J. E.; Schultink, G.

    1977-01-01

    Color-infrared photography was used to evaluate the biomass of experimental plots in an old-field ecosystem that was treated with different levels of waste water from a sewage treatment facility. Cibachrome prints at a scale of approximately 1:1,600 produced from 35 mm color infrared slides were used to analyze density patterns using prepared tonal density scales and multicell grids registered to ground panels shown on the photograph. Correlations between mean tonal density and harvest biomass data gave consistently high coefficients ranging from 0.530 to 0.896 at the 0.001 significance level. Corresponding multiple regression analysis resulted in higher correlation coefficients. The results indicate that aerial infrared photography can be used to estimate standing crop biomass on waste water irrigated old field ecosystems. Combined with minimal ground truth data, this technique could enable managers of waste water irrigation projects to precisely time harvest of such systems for maximal removal of nutrients in harvested biomass.

  13. Estimating externalities of biomass fuel cycles, Report 7

    SciTech Connect

    Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.

    1998-01-01

    This report documents the analysis of the biomass fuel cycle, in which biomass is combusted to produce electricity. The major objectives of this study were: (1) to implement the methodological concepts which were developed in the Background Document (ORNL/RFF 1992) as a means of estimating the external costs and benefits of fuel cycles, and by so doing, to demonstrate their application to the biomass fuel cycle; (2) to develop, given the time and resources, a range of estimates of marginal (i.e., the additional or incremental) damages and benefits associated with selected impact-pathways from a new wood-fired power plant, using a representative benchmark technology, at two reference sites in the US; and (3) to assess the state of the information available to support energy decision making and the estimation of externalities, and by so doing, to assist in identifying gaps in knowledge and in setting future research agendas. The demonstration of methods, modeling procedures, and use of scientific information was the most important objective of this study. It provides an illustrative example for those who will, in the future, undertake studies of actual energy options and sites. As in most studies, a more comprehensive analysis could have been completed had budget constraints not been as severe. Particularly affected were the air and water transport modeling, estimation of ecological impacts, and economic valuation. However, the most important objective of the study was to demonstrate methods, as a detailed example for future studies. Thus, having severe budget constraints was appropriate from the standpoint that these studies could also face similar constraints. Consequently, an important result of this study is an indication of what can be done in such studies, rather than the specific numerical estimates themselves.

  14. Single Baseline Tomography SAR for Forest Above Ground Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Li, Wenmei; Chen, Erxue; Li, Zengyuan; Wang, Xinshuang; Feng, Qi

    2013-01-01

    Single baseline tomography SAR is used for forest height estimation as its little restriction on the number of baselines and configurations of tracks in recent years. There existed two kinds of single baseline tomography SAR techniques, the polarimetric coherence tomography (PCT) and the sum of Kronecker product (SKP), algebraic synthesis (AS) and Capon spectral estimator approach (SKP-AS-Capon). Few researches on forest above ground biomass (AGB) estimation are there using single baseline tomography SAR. In this paper, PCT and SKP-AS-Capon approaches are proposed for forest AGB estimation. L-band data set acquired by E-SAR airborne system in 2003 for the forest test site in Traunstein, is used for this experiment. The result shows that single baseline polarimetric tomography SAR can obtain forest AGB in forest stand scale, and SKP-AS-Capon method has better detailed vertical structure information, while the Freeman 3-component combined PCT approach gets a homogenous vertical structure in forest stand.

  15. Polychaete abundance, biomass and diversity patterns at the Mid-Atlantic Ridge, North Atlantic Ocean

    NASA Astrophysics Data System (ADS)

    Shields, Mark A.; Blanco-Perez, Raimundo

    2013-12-01

    Recent studies have revealed that the Mid-Atlantic Ridge (MAR) in the North Atlantic Ocean accounts for a large proportion of available bathyal soft-sediment habitat. When comparing the MAR to the continental margins of the North Atlantic, it is apparent that very little is known about the soft-sediment macrofaunal community associated with the MAR. In the present study, as part of the ECOMAR (Ecosystems of the Mid-Atlantic Ridge at the Sub-Polar Front and Charlie-Gibbs Fracture Zone) project, the polychaete component of the MAR macrofaunal community was investigated. A total of 751 polychaete specimens and 133 species were identified from megacorer samples collected at four MAR sites (48-54°N, depth: 2500-2800 m) sampled during the RRS James Cook 48 cruise in the summer of 2010. Polychaetes were the most abundant member of the macrofaunal community, and there was no significant difference in polychaete abundance, biomass and diversity between any of the MAR sites. In addition, the MAR did not appear to provide a physical barrier to the distribution of bathyal polychaetes either side of the ridge.

  16. Helium abundances on the moon: Assumptions and estimates

    NASA Technical Reports Server (NTRS)

    Taylor, Lawrence A.

    1991-01-01

    Nuclear energy is a highly desirable source of energy, and He-3 is the most prized of the fusion reactants. As the Wisconsin Group has emphasized, He-3 may be the only true economic ore on the Moon. The lack of a shielding atmosphere on the Moon permits solar-wind alpha particles to impinge upon the lunar regolith and become implanted into the various solid components. In particular, large quantities of helium (5 to 50 ppm) are presented. The measured parameter of I(sub s)/FeO, a direct indicator of maturity and exposure age, can be used as a first approximation to predict the abundances of many solar-wind components in the soils. However, because ilmenite has a much higher retentivity for helium than the other phases, the TiO2 contents of the soils are better indicators of helium contents (Taylor, Space 90). High-Ti mare bassalt regions, such as at the Apollo 17 locale, appear to be the best areas for He mining (15 to 50 ppm He(sub T)), versus 3 to 9 ppm in the Highlands. However, the relationships between I(sub s)/FeO, TiO2 and He-3 contents are complicated - e.g., many of the most He-rich soils are immature to submature. The amount of He-3 in the regolith of the moon is estimated at 220,000 tons in the outer 2 m of the Maria.

  17. Bias in acoustic biomass estimates of Euphausia superba due to diel vertical migration

    NASA Astrophysics Data System (ADS)

    Demer, David A.; Hewitt, Roger P.

    1995-04-01

    The diel vertical migration (DVM) of Antarctic krill ( Euphausia superba) can greatly bias the results of qualitative and quantitative hydroacoustic surveys which are conducted with a down-looking sonar and irrespective of the time of day. To demonstrate and quantify these negative biases on both the estimates of biomass distribution and abundance, a time-depth-density analysis was performed. Data were collected, as part of the United States Antarctic Marine Living Resources Program (AMLR), in the vicinities of Elephant Island, Antarctica, during the austral summers of 1992 and 1993. Five surveys were conducted in 1992; two covered a 105 by 105 n.mi. area centered on Elephant Island, two encompassed a 60 by 35 n.mi. area immediately to the north of the Island, and one covered a 1 n.mi. 2 area centered on a large krill swarm to the west of Seal Island. The 1993 data include repetitions of the two small-area and two large-area surveys. Average krill volume densities were calculated for each hour as well as for three daily periods: day, twilight and night. These data were normalized and presented as a probability of daily average density. With spectral analysis to identify the frequencies of migration, a four-term periodic function was fitted to the probability density function of average daily biomass versus local apparent time. This function was transformed to create a temporal compensation function (TCF) for upwardly adjusting acoustic biomass estimates. The TCF was then applied to the original 1992 survey data; the resulting biomass estimates are an average of 49.5% higher than those calculated disregarding biases due to diel vertical migration. The effect of DVM on the estimates of krill distribution are illustrated by a comparison of compensated and uncompensated density maps of two 1992 surveys. Through this technique, high density kril areas are revealed where uncompensated maps indicated low densities.

  18. Estimation of alewife biomass in Lake Michigan, 1967-1978

    USGS Publications Warehouse

    Hatch, Richard W.; Haack, Paul M.; Brown, Edward H., Jr.

    1981-01-01

    The buildup of salmonid populations in Lake Michigan through annual stockings of hatchery-reared fish may become limited by the quantity of forage fish, mainly alewives Alosa pseudoharengus, available for food. As a part of a continuing examination of salmonid predator-prey relations in Lake Michigan, we traced changes in alewife biomass estimated from bottom-trawl surveys conducted in late October and early November 1967–1978. Weight of adult alewives trawled per 0.5 hectare of bottom (10-minute drag) at 16 depths along eight transects between 1973 and 1977 formed a skewed distribution: 72 of 464 drags caught no alewives; 89 drags caught less than 1 kg; and 2 drags caught more than 100 kg (maximum 159 kg). Analysis of variance in normalized catch per tow indicated highly significant differences between the main effects of years and depths, and highly significant differences in the interactions of years and transects, years and depths, and transects and depths. Five geographic and depth strata, formed by combining parts of transects wherein mean catch rate did not differ significantly, were the basis for calculating annual estimates of adult alewife biomass (with 90% confidence intervals). Estimated biomass of alewives (±90% confidence limits) in Lake Michigan proper (Green Bay and Grand Traverse Bay excluded) rose gradually from 46,000 (±9,000) t in 1967 to 114,000 (±17,000) t in 1973, declined to 45,000 (±8,000) t in 1977, and rose to 77,000 (±19,000) t in 1978.

  19. Copepods attain high abundance, biomass and production in the absence of large predators but suffer cannibalistic loss

    NASA Astrophysics Data System (ADS)

    Uye, Shin-ichi; Liang, Dong

    1998-06-01

    Zooplankton samples were collected at intervals of 3-5 days for a year in Fukuyama Harbor, a eutrophic inlet of the Inland Sea of Japan, using a 62-μm-mesh plankton net. The copepod community, which consisted of twelve species, had a very high abundance, biomass and production rate. Acartia omorii, Centropages abdominalis, Oithona davisae and Paracalanus sp. were the most abundant species. The annual average abundance and biomass of adults and copepodites were 1.10×10 5 ind. m -3 and 39.1 mg C m -3, respectively, one of the highest values so far reported in coastal marine waters. The annual average production rate was 6.85 mg C m -3 d -1, of which Paracalanus sp., O. davisae, A. omorii and C. abdominalis accounted for 27, 26, 25 and 13%, respectively. The combination of an abundant food supply and scarce large predators, except for the ctenophore Bolinopsis mikado which was abundant only in mid-summer, allowed the high abundance, biomass and production of copepods. However, predation on copepod eggs and early nauplii by adults and late copepodites reduced the population recruitment rate and copepod production.

  20. [Abundance and biomass of planktonic ciliates in the shelf of East China Sea in spring and autumn].

    PubMed

    Yu, Ying; Zhang, Wu-chang; Zhou, Feng; Liu, Cheng-gang; Feng, Mei-ping; Li, Hai-bo; Zhao, Yuan; Xiao, Tian

    2013-08-01

    An investigation was made on the abundance and biomass of planktonic ciliates in the shelf of East China Sea in May (spring) and November (autumn), 2011. The abundance of the ciliates in spring and autumn was averagely (614 +/- 861) and (934 +/- 809) ind x L(-1), and the biomass was averagely (1.70 +/- 3.91) and (0.93 +/- 0.99) microg C x L(-1), respectively. The high abundance and biomass in spring were found in coastal and offshore areas, and those in autumn were in offshore only. In the two seasons, the ciliates tended to accumulate in the waters upper layer, and sometimes flocked in the bottom. In the spring, aloricate ciliate species were larger than those in the autumn. Tintinnids occupied (26.9% +/- 34.3)% and (44.9% +/- 25.2)% of the total ciliates abundance in spring and autumn, respectively. In taxonomy, 52 tintinnid species of 27 genera were identified. The most dominant species were Tintinnidium primitivum, Stenosemella oliva, and Tintinnopsis tubulosoides in spring, and Tintinnidium primitivum, Stenosemella parvicollis, and Tintinnopsis nana in autumn. The ciliates abundance showed significant positive correlations with water temperature and Chl a concentration, the tintinnids abundance showed significant negative correlation with water salinity, and the tintinnids community was significantly related to water temperature. PMID:24380353

  1. Testing the sensitivity of terrestrial carbon models using remotely sensed biomass estimates

    NASA Astrophysics Data System (ADS)

    Hashimoto, H.; Saatchi, S. S.; Meyer, V.; Milesi, C.; Wang, W.; Ganguly, S.; Zhang, G.; Nemani, R. R.

    2010-12-01

    There is a large uncertainty in carbon allocation and biomass accumulation in forest ecosystems. With the recent availability of remotely sensed biomass estimates, we now can test some of the hypotheses commonly implemented in various ecosystem models. We used biomass estimates derived by integrating MODIS, GLAS and PALSAR data to verify above-ground biomass estimates simulated by a number of ecosystem models (CASA, BIOME-BGC, BEAMS, LPJ). This study extends the hierarchical framework (Wang et al., 2010) for diagnosing ecosystem models by incorporating independent estimates of biomass for testing and calibrating respiration, carbon allocation, turn-over algorithms or parameters.

  2. Uav-Based Automatic Tree Growth Measurement for Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Karpina, M.; Jarząbek-Rychard, M.; Tymków, P.; Borkowski, A.

    2016-06-01

    Manual in-situ measurements of geometric tree parameters for the biomass volume estimation are time-consuming and economically non-effective. Photogrammetric techniques can be deployed in order to automate the measurement procedure. The purpose of the presented work is an automatic tree growth estimation based on Unmanned Aircraft Vehicle (UAV) imagery. The experiment was conducted in an agriculture test field with scots pine canopies. The data was collected using a Leica Aibotix X6V2 platform equipped with a Nikon D800 camera. Reference geometric parameters of selected sample plants were measured manually each week. In situ measurements were correlated with the UAV data acquisition. The correlation aimed at the investigation of optimal conditions for a flight and parameter settings for image acquisition. The collected images are processed in a state of the art tool resulting in a generation of dense 3D point clouds. The algorithm is developed in order to estimate geometric tree parameters from 3D points. Stem positions and tree tops are identified automatically in a cross section, followed by the calculation of tree heights. The automatically derived height values are compared to the reference measurements performed manually. The comparison allows for the evaluation of automatic growth estimation process. The accuracy achieved using UAV photogrammetry for tree heights estimation is about 5cm.

  3. Twenty-eight Years of Stream Invertebrate Abundance, Biomass, and Secondary Production From Three Headwater Streams

    NASA Astrophysics Data System (ADS)

    Wallace, J.; Eggert, S. L.; Cross, W. F.; Rosemond, A. D.; Meyer, J. L.

    2005-05-01

    We analyzed 28 years of abundance, biomass and secondary production data from 3 headwater streams at the Coweeta Hydrologic Laboratory, NC, USA. These data include years of extreme drought and precipitation (78-y record) and 8 years of reduced litter inputs (litter exclusion) and wood removal for one stream. Analysis of functional feeding group (FFG) proportions revealed strong habitat-specific preferences for either mixed substrates or bedrock outcrop habitats, with remarkable between year similarities. For both reference streams and litter reduction streams there was a significant relationship between annual CPOM standing crop and secondary production for the dominant mixed substrate habitats. Habitat-weighted production across reference streams averaged 8.2 g AFDM/m2/y (range = 4.6 to 13.2) versus 1.7 g AFDM/m2/y (range = 0.9 to 3.5) for litter exclusion years. Predator production was strongly correlated (P<0.001) with total secondary production over all years, and based on known bioenergetic efficiencies, indicate the importance of predators in these streams. Our study suggests that trophic interactions, including standing crop of CPOM as a food source, strongly influence secondary production in these headwater streams.

  4. A database of marine phytoplankton abundance, biomass and species composition in Australian waters

    PubMed Central

    Davies, Claire H.; Coughlan, Alex; Hallegraeff, Gustaaf; Ajani, Penelope; Armbrecht, Linda; Atkins, Natalia; Bonham, Prudence; Brett, Steve; Brinkman, Richard; Burford, Michele; Clementson, Lesley; Coad, Peter; Coman, Frank; Davies, Diana; Dela-Cruz, Jocelyn; Devlin, Michelle; Edgar, Steven; Eriksen, Ruth; Furnas, Miles; Hassler, Christel; Hill, David; Holmes, Michael; Ingleton, Tim; Jameson, Ian; Leterme, Sophie C.; Lønborg, Christian; McLaughlin, James; McEnnulty, Felicity; McKinnon, A. David; Miller, Margaret; Murray, Shauna; Nayar, Sasi; Patten, Renee; Pritchard, Tim; Proctor, Roger; Purcell-Meyerink, Diane; Raes, Eric; Rissik, David; Ruszczyk, Jason; Slotwinski, Anita; Swadling, Kerrie M.; Tattersall, Katherine; Thompson, Peter; Thomson, Paul; Tonks, Mark; Trull, Thomas W.; Uribe-Palomino, Julian; Waite, Anya M.; Yauwenas, Rouna; Zammit, Anthony; Richardson, Anthony J.

    2016-01-01

    There have been many individual phytoplankton datasets collected across Australia since the mid 1900s, but most are unavailable to the research community. We have searched archives, contacted researchers, and scanned the primary and grey literature to collate 3,621,847 records of marine phytoplankton species from Australian waters from 1844 to the present. Many of these are small datasets collected for local questions, but combined they provide over 170 years of data on phytoplankton communities in Australian waters. Units and taxonomy have been standardised, obviously erroneous data removed, and all metadata included. We have lodged this dataset with the Australian Ocean Data Network (http://portal.aodn.org.au/) allowing public access. The Australian Phytoplankton Database will be invaluable for global change studies, as it allows analysis of ecological indicators of climate change and eutrophication (e.g., changes in distribution; diatom:dinoflagellate ratios). In addition, the standardised conversion of abundance records to biomass provides modellers with quantifiable data to initialise and validate ecosystem models of lower marine trophic levels. PMID:27328409

  5. A database of marine phytoplankton abundance, biomass and species composition in Australian waters.

    PubMed

    Davies, Claire H; Coughlan, Alex; Hallegraeff, Gustaaf; Ajani, Penelope; Armbrecht, Linda; Atkins, Natalia; Bonham, Prudence; Brett, Steve; Brinkman, Richard; Burford, Michele; Clementson, Lesley; Coad, Peter; Coman, Frank; Davies, Diana; Dela-Cruz, Jocelyn; Devlin, Michelle; Edgar, Steven; Eriksen, Ruth; Furnas, Miles; Hassler, Christel; Hill, David; Holmes, Michael; Ingleton, Tim; Jameson, Ian; Leterme, Sophie C; Lønborg, Christian; McLaughlin, James; McEnnulty, Felicity; McKinnon, A David; Miller, Margaret; Murray, Shauna; Nayar, Sasi; Patten, Renee; Pritchard, Tim; Proctor, Roger; Purcell-Meyerink, Diane; Raes, Eric; Rissik, David; Ruszczyk, Jason; Slotwinski, Anita; Swadling, Kerrie M; Tattersall, Katherine; Thompson, Peter; Thomson, Paul; Tonks, Mark; Trull, Thomas W; Uribe-Palomino, Julian; Waite, Anya M; Yauwenas, Rouna; Zammit, Anthony; Richardson, Anthony J

    2016-01-01

    There have been many individual phytoplankton datasets collected across Australia since the mid 1900s, but most are unavailable to the research community. We have searched archives, contacted researchers, and scanned the primary and grey literature to collate 3,621,847 records of marine phytoplankton species from Australian waters from 1844 to the present. Many of these are small datasets collected for local questions, but combined they provide over 170 years of data on phytoplankton communities in Australian waters. Units and taxonomy have been standardised, obviously erroneous data removed, and all metadata included. We have lodged this dataset with the Australian Ocean Data Network (http://portal.aodn.org.au/) allowing public access. The Australian Phytoplankton Database will be invaluable for global change studies, as it allows analysis of ecological indicators of climate change and eutrophication (e.g., changes in distribution; diatom:dinoflagellate ratios). In addition, the standardised conversion of abundance records to biomass provides modellers with quantifiable data to initialise and validate ecosystem models of lower marine trophic levels. PMID:27328409

  6. Developing a generalized allometric equation for aboveground biomass estimation

    NASA Astrophysics Data System (ADS)

    Xu, Q.; Balamuta, J. J.; Greenberg, J. A.; Li, B.; Man, A.; Xu, Z.

    2015-12-01

    A key potential uncertainty in estimating carbon stocks across multiple scales stems from the use of empirically calibrated allometric equations, which estimate aboveground biomass (AGB) from plant characteristics such as diameter at breast height (DBH) and/or height (H). The equations themselves contain significant and, at times, poorly characterized errors. Species-specific equations may be missing. Plant responses to their local biophysical environment may lead to spatially varying allometric relationships. The structural predictor may be difficult or impossible to measure accurately, particularly when derived from remote sensing data. All of these issues may lead to significant and spatially varying uncertainties in the estimation of AGB that are unexplored in the literature. We sought to quantify the errors in predicting AGB at the tree and plot level for vegetation plots in California. To accomplish this, we derived a generalized allometric equation (GAE) which we used to model the AGB on a full set of tree information such as DBH, H, taxonomy, and biophysical environment. The GAE was derived using published allometric equations in the GlobAllomeTree database. The equations were sparse in details about the error since authors provide the coefficient of determination (R2) and the sample size. A more realistic simulation of tree AGB should also contain the noise that was not captured by the allometric equation. We derived an empirically corrected variance estimate for the amount of noise to represent the errors in the real biomass. Also, we accounted for the hierarchical relationship between different species by treating each taxonomic level as a covariate nested within a higher taxonomic level (e.g. species < genus). This approach provides estimation under incomplete tree information (e.g. missing species) or blurred information (e.g. conjecture of species), plus the biophysical environment. The GAE allowed us to quantify contribution of each different

  7. Estimating relative abundances of proteins from shotgun proteomics data

    PubMed Central

    2012-01-01

    Background Spectral counting methods provide an easy means of identifying proteins with differing abundances between complex mixtures using shotgun proteomics data. The crux spectral-counts command, implemented as part of the Crux software toolkit, implements four previously reported spectral counting methods, the spectral index (SIN), the exponentially modified protein abundance index (emPAI), the normalized spectral abundance factor (NSAF), and the distributed normalized spectral abundance factor (dNSAF). Results We compared the reproducibility and the linearity relative to each protein’s abundance of the four spectral counting metrics. Our analysis suggests that NSAF yields the most reproducible counts across technical and biological replicates, and both SIN and NSAF achieve the best linearity. Conclusions With the crux spectral-counts command, Crux provides open-source modular methods to analyze mass spectrometry data for identifying and now quantifying peptides and proteins. The C++ source code, compiled binaries, spectra and sequence databases are available at http://noble.gs.washington.edu/proj/crux-spectral-counts. PMID:23164367

  8. Comparison of carbon and biomass estimation methods for European forests

    NASA Astrophysics Data System (ADS)

    Neumann, Mathias; Mues, Volker; Harkonen, Sanna; Mura, Matteo; Bouriaud, Olivier; Lang, Mait; Achten, Wouter; Thivolle-Cazat, Alain; Bronisz, Karol; Merganicova, Katarina; Decuyper, Mathieu; Alberdi, Iciar; Astrup, Rasmus; Schadauer, Klemens; Hasenauer, Hubert

    2015-04-01

    National and international reporting systems as well as research, enterprises and political stakeholders require information on carbon stocks of forests. Terrestrial assessment systems like forest inventory data in combination with carbon calculation methods are often used for this purpose. To assess the effect of the calculation method used, a comparative analysis was done using the carbon calculation methods from 13 European countries and the research plots from ICP Forests (International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests). These methods are applied for five European tree species (Fagus sylvatica L., Quercus robur L., Betula pendula Roth, Picea abies (L.) Karst. and Pinus sylvestris L.) using a standardized theoretical tree dataset to avoid biases due to data collection and sample design. The carbon calculation methods use allometric biomass and volume functions, carbon and biomass expansion factors or a combination thereof. The results of the analysis show a high variation in the results for total tree carbon as well as for carbon in the single tree compartments. The same pattern is found when comparing the respective volume estimates. This is consistent for all five tree species and the variation remains when the results are grouped according to the European forest regions. Possible explanations are differences in the sample material used for the biomass models, the model variables or differences in the definition of tree compartments. The analysed carbon calculation methods have a strong effect on the results both for single trees and forest stands. To avoid misinterpretation the calculation method has to be chosen carefully along with quality checks and the calculation method needs consideration especially in comparative studies to avoid biased and misleading conclusions.

  9. Estimation of Methanogen Biomass by Quantitation of Coenzyme M

    PubMed Central

    Elias, Dwayne A.; Krumholz, Lee R.; Tanner, Ralph S.; Suflita, Joseph M.

    1999-01-01

    Determination of the role of methanogenic bacteria in an anaerobic ecosystem often requires quantitation of the organisms. Because of the extreme oxygen sensitivity of these organisms and the inherent limitations of cultural techniques, an accurate biomass value is very difficult to obtain. We standardized a simple method for estimating methanogen biomass in a variety of environmental matrices. In this procedure we used the thiol biomarker coenzyme M (CoM) (2-mercaptoethanesulfonic acid), which is known to be present in all methanogenic bacteria. A high-performance liquid chromatography-based method for detecting thiols in pore water (A. Vairavamurthy and M. Mopper, Anal. Chim. Acta 78:363–370, 1990) was modified in order to quantify CoM in pure cultures, sediments, and sewage water samples. The identity of the CoM derivative was verified by using liquid chromatography-mass spectroscopy. The assay was linear for CoM amounts ranging from 2 to 2,000 pmol, and the detection limit was 2 pmol of CoM/ml of sample. CoM was not adsorbed to sediments. The methanogens tested contained an average of 19.5 nmol of CoM/mg of protein and 0.39 ± 0.07 fmol of CoM/cell. Environmental samples contained an average of 0.41 ± 0.17 fmol/cell based on most-probable-number estimates. CoM was extracted by using 1% tri-(N)-butylphosphine in isopropanol. More than 90% of the CoM was recovered from pure cultures and environmental samples. We observed no interference from sediments in the CoM recovery process, and the method could be completed aerobically within 3 h. Freezing sediment samples resulted in 46 to 83% decreases in the amounts of detectable CoM, whereas freezing had no effect on the amounts of CoM determined in pure cultures. The method described here provides a quick and relatively simple way to estimate methanogenic biomass. PMID:10584015

  10. Biomass burning emissions estimates in the boreal forests of Siberia

    NASA Astrophysics Data System (ADS)

    Kukavskaya, E. A.; Ivanova, G. A.; Soja, A. J.; Conard, S. G.

    2012-04-01

    Wildfire is the main boreal forest disturbance and can burn 10-30 million hectares annually, thus modifying the global carbon budget through direct fire emissions, postfire biogenic emissions, and by maintaining or altering ecosystems through establishing the beginning and end of successional processes. Fires in the Russian boreal forest range from low-severity surface fires to high-severity crown fires. Estimates of carbon emissions from fires in Russian boreal forests vary substantially due to differences in ecosystems types, burned area calculations, and the amount of fuel consumed. There is an urgent need to obtain more accurate and impartial fire carbon loss estimates in the boreal forests of Siberia due to their considerable contribution to the regional and global carbon balance. We examined uncertainties in estimates of carbon emissions. Area burned in the Siberian region was analyzed and compared using distinct methodologies. Differences between mapped ecosystems were also compared and contrasted to evaluate the potential for error resulting from disparate vegetation structure and fuel consumption estimates. Accurate fuel consumption estimates are obtained in the course of fire experiments with pre- and post-fire biomass measuring. Our large-scale experiments carried out in the course of the FIRE BEAR (Fire Effects in the Boreal Eurasia Region) Project provided quantitative and qualitative data on ecosystem state and carbon emissions due to fires of known behavior in major forest types of Siberia that could be used to verify large-scale carbon emissions estimates. Carbon emissions from fires vary annually and interannually and can increase several times in extreme fire years in comparison to normal fire years. Climate change and increasing drought length have increased the probability of high-severity fire occurrences. This would result in greater carbon losses and efflux to the atmosphere. This research was supported by NASA LCLUC Program, Fulbright

  11. Estimating occupancy and abundance of stream amphibians using environmental DNA from filtered water samples

    USGS Publications Warehouse

    Pilliod, David S.; Goldberg, Caren S.; Arkle, Robert S.; Waits, Lisette P.

    2013-01-01

    Environmental DNA (eDNA) methods for detecting aquatic species are advancing rapidly, but with little evaluation of field protocols or precision of resulting estimates. We compared sampling results from traditional field methods with eDNA methods for two amphibians in 13 streams in central Idaho, USA. We also evaluated three water collection protocols and the influence of sampling location, time of day, and distance from animals on eDNA concentration in the water. We found no difference in detection or amount of eDNA among water collection protocols. eDNA methods had slightly higher detection rates than traditional field methods, particularly when species occurred at low densities. eDNA concentration was positively related to field-measured density, biomass, and proportion of transects occupied. Precision of eDNA-based abundance estimates increased with the amount of eDNA in the water and the number of replicate subsamples collected. eDNA concentration did not vary significantly with sample location in the stream, time of day, or distance downstream from animals. Our results further advance the implementation of eDNA methods for monitoring aquatic vertebrates in stream habitats.

  12. "Capture" Me if You Can: Estimating Abundance of Dolphin Populations

    ERIC Educational Resources Information Center

    Thompson, Jessica; Curran, Mary Carla; Cox, Tara

    2016-01-01

    Animal populations are monitored over time to assess the effects of environmental disaster and disease, as well as the efficacy of laws designed to protect them. Determining the abundance of a species within a defined area is one method of monitoring a population. In "Capture" Me if You Can, middle school students will use data collected…

  13. Robust Abundance Estimation in Animal Surveys with Imperfect Detection

    EPA Science Inventory

    Surveys of animal abundance are central to the conservation and management of living natural resources. However, detection uncertainty complicates the sampling process of many species. One sampling method employed to deal with this problem is depletion (or removal) surveys in whi...

  14. Estimating the abundance of mouse populations of known size: promises and pitfalls of new methods

    USGS Publications Warehouse

    Conn, P.B.; Arthur, A.D.; Bailey, L.L.; Singleton, G.R.

    2006-01-01

    Knowledge of animal abundance is fundamental to many ecological studies. Frequently, researchers cannot determine true abundance, and so must estimate it using a method such as mark-recapture or distance sampling. Recent advances in abundance estimation allow one to model heterogeneity with individual covariates or mixture distributions and to derive multimodel abundance estimators that explicitly address uncertainty about which model parameterization best represents truth. Further, it is possible to borrow information on detection probability across several populations when data are sparse. While promising, these methods have not been evaluated using mark?recapture data from populations of known abundance, and thus far have largely been overlooked by ecologists. In this paper, we explored the utility of newly developed mark?recapture methods for estimating the abundance of 12 captive populations of wild house mice (Mus musculus). We found that mark?recapture methods employing individual covariates yielded satisfactory abundance estimates for most populations. In contrast, model sets with heterogeneity formulations consisting solely of mixture distributions did not perform well for several of the populations. We show through simulation that a higher number of trapping occasions would have been necessary to achieve good estimator performance in this case. Finally, we show that simultaneous analysis of data from low abundance populations can yield viable abundance estimates.

  15. Regional estimation of current and future forest biomass.

    PubMed

    Mickler, R A; Earnhardt, T S; Moore, J A

    2002-01-01

    The 90,674 wildland fires that burned 2.9 million ha at an estimated suppression cost of $1.6 billion in the United States during the 2000 fire season demonstrated that forest fuel loading has become a hazard to life, property, and ecosystem health as a result of past fire exclusion policies and practices. The fire regime at any given location in these regions is a result of complex interactions between forest biomass, topography, ignitions, and weather. Forest structure and biomass are important aspects in determining current and future fire regimes. Efforts to quantify live and dead forest biomass at the local to regional scale has been hindered by the uncertainty surrounding the measurement and modeling of forest ecosystem processes and fluxes. The interaction of elevated CO2 with climate, soil nutrients, and other forest management factors that affect forest growth and fuel loading will play a major role in determining future forest stand growth and the distribution of species across the southern United States. The use of satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of forest carbon. The incorporation of Landsat Thematic Mapper data coupled with a physiologically based productivity model (PnET), soil water holding capacity, and historic and projected climatic data provides an opportunity to enhance field plot based forest inventory and monitoring methodologies. We use periodic forest inventory data from the USDA Forest Service's Forest Inventory and Analysis (FIA) project to obtain estimates of forest area and type to generate estimates of carbon storage for evergreen, deciduous, and mixed forest classes for use in an assessment of remotely sensed forest cover at the regional scale for the southern United States. The displays of net primary productivity (NPP) generated from the PnET model show areas of high and low forest carbon storage

  16. ESTIMATION OF SURPLUS BIOMASS OF CLUPEIDS IN SMITH MOUNTAIN LAKE, VIRGINIA

    EPA Science Inventory

    Mean annual estimates of surplus biomass of alewife Alosa pseudoharengus and gizzard shad Dorosoma cepedianum in Smith Mountain Lake, Virginia, were calculated using data on the biomass, growth, and mortality of each clupeid species. Surplus biomass, defined as production over a...

  17. High-biomass sorghum yield estimate with aerial imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Abstract. To reach the goals laid out by the U.S. Government for displacing fossil fuels with biofuels, agricultural production of dedicated biomass crops is required. High-biomass sorghum is advantageous across wide regions because it requires less water per unit dry biomass and can produce very hi...

  18. Vertical changes in abundance, biomass and community structure of copepods down to 3000 m in the southern Bering Sea

    NASA Astrophysics Data System (ADS)

    Homma, Tomoe; Yamaguchi, Atsushi

    2010-08-01

    Vertical changes in abundance, biomass and community structure of copepods down to 3000 m depth were studied at a single station of the Aleutian Basin of the Bering Sea (53°28'N, 177°00'W, depth 3779 m) on the 14th June 2006. Both abundance and biomass of copepods were greatest near the surface layer and decreased with increase in depth. Abundance and biomass of copepods integrated over 0-3000 m were 1,390,000 inds. m -2 and 5056 mg C m -2, respectively. Copepod carcasses occurred throughout the layer, and the carcass:living specimen ratio was the greatest in the oxygen minimum layer (750-100 m, the ratio was 2.3). A total of 72 calanoid copepod species belonging to 34 genera and 15 families occurred in the 0-3000 m water column (Cyclopoida, Harpacticoida and Poecilostomatoida were not identified to species level). Cluster analysis separated calanoid copepod communities into 5 groups (A-E). Each group was separated by depth, and the depth range of each group was at 0-75 m (A), 75-500 m (B), 500-750 m (C), 750-1500 m (D) and 1500-3000 m (E). Copepods were divided into four types based on the feeding pattern: suspension feeders, suspension feeders in diapause, detritivores and carnivores. In terms of abundance the most dominant group was suspension feeders (mainly Cyclopoida) in the epipelagic zone, and detritivores (mainly Poecilostomatoida) were dominant in the meso- and bathypelagic zones. In terms of biomass, suspension feeders in diapause (calanoid copepods Neocalanus spp. and Eucalanus bungii) were the major component (ca. 10-45%), especially in the 250-3000 m depth. These results are compared with the previous studies in the same region and that down to greater depths in the worldwide oceans.

  19. Seasonal variability of plankton blooms in the Ria de Ferrol (NW Spain): II. Plankton abundance, composition and biomass

    NASA Astrophysics Data System (ADS)

    Bode, Antonio; Álvarez-Ossorio, M. Teresa; González, Nicolás; Lorenzo, Jorge; Rodríguez, Cristina; Varela, Manuel; Varela, Marta M.

    2005-04-01

    The abundance, taxonomic composition and biomass of plankton components were studied in the mostly eutrophic waters of the Ria de Ferrol (Galicia, NW Spain) in contrasting seasons. Three stations arranged in a transect along the main ria axis were sampled during cruises in February, May, July and September 2000. Phytoplankton, bacteria, micro- (40-200 μm) and mesozooplankton (>200 μm) compartments were considered. Phytoplankton blooms (>10 3 cel ml -1) and high total plankton biomass (up to 44 g C m -2) was found at all seasons, except in winter when values were <1 g C m -2. Phytoplankton generally accounted for most of total plankton biomass, particularly in late summer, thus driving most of plankton dynamics. The blooming species were always diatoms, either fast-growing, chain-forming species, well adapted to relatively turbulent conditions (e.g. Chaetoceros socialis), or disturbance-tolerant, estuarine adapted species (e.g. Skeletonema costatum). In addition, microflagellates (<10 μm) reached high abundances, particularly during summer. The influence of shelf waters, where coastal upwelling events are frequent for most of the spring and summer, prevents the establishment of a marked pycnocline and the dominance of dinoflagellates. Microheterotrophs (bacteria, protozoa and larval stages of metazoa) increased their abundance and biomass from winter to late summer, while mesozooplankton peaked in spring and summer. Zooplankton dynamics were characterised by the presence of large numbers of larvae of both planktonic copepods and benthic metazoans, the latter mainly cirripeds and bivalve molluscs. The absence of a definite succession pattern in the mesozooplankton species abundance data, in contrast with phytoplankton data, along with the dominance of estuarine species (e.g. Acartia margalefi), suggest that mesozooplankton communities inside the ria behave differently from communities in shelf waters. Despite its small size and reduced influence of upwelling

  20. Density and Biomass Estimates by Removal for an Amazonian Crocodilian, Paleosuchus palpebrosus

    PubMed Central

    2016-01-01

    Direct counts of crocodilians are rarely feasible and it is difficult to meet the assumptions of mark-recapture methods for most species in most habitats. Catch-out experiments are also usually not logistically or morally justifiable because it would be necessary to destroy the habitat in order to be confident that most individuals had been captured. We took advantage of the draining and filling of a large area of flooded forest during the building of the Santo Antônio dam on the Madeira River to obtain accurate estimates of the density and biomass of Paleosuchus palpebrosus. The density, 28.4 non-hatchling individuals per km2, is one of the highest reported for any crocodilian, except for species that are temporarily concentrated in small areas during dry-season drought. The biomass estimate of 63.15 kg*km-2 is higher than that for most or even all mammalian carnivores in tropical forest. P. palpebrosus may be one of the World´s most abundant crocodilians. PMID:27224473

  1. Density and Biomass Estimates by Removal for an Amazonian Crocodilian, Paleosuchus palpebrosus.

    PubMed

    Campos, Zilca; Magnusson, William E

    2016-01-01

    Direct counts of crocodilians are rarely feasible and it is difficult to meet the assumptions of mark-recapture methods for most species in most habitats. Catch-out experiments are also usually not logistically or morally justifiable because it would be necessary to destroy the habitat in order to be confident that most individuals had been captured. We took advantage of the draining and filling of a large area of flooded forest during the building of the Santo Antônio dam on the Madeira River to obtain accurate estimates of the density and biomass of Paleosuchus palpebrosus. The density, 28.4 non-hatchling individuals per km2, is one of the highest reported for any crocodilian, except for species that are temporarily concentrated in small areas during dry-season drought. The biomass estimate of 63.15 kg*km-2 is higher than that for most or even all mammalian carnivores in tropical forest. P. palpebrosus may be one of the World´s most abundant crocodilians. PMID:27224473

  2. A method for estimating abundance of mobile populations using telemetry and counts of unmarked animals

    USGS Publications Warehouse

    Clement, Matthew; O'Keefe, Joy M; Walters, Brianne

    2015-01-01

    While numerous methods exist for estimating abundance when detection is imperfect, these methods may not be appropriate due to logistical difficulties or unrealistic assumptions. In particular, if highly mobile taxa are frequently absent from survey locations, methods that estimate a probability of detection conditional on presence will generate biased abundance estimates. Here, we propose a new estimator for estimating abundance of mobile populations using telemetry and counts of unmarked animals. The estimator assumes that the target population conforms to a fission-fusion grouping pattern, in which the population is divided into groups that frequently change in size and composition. If assumptions are met, it is not necessary to locate all groups in the population to estimate abundance. We derive an estimator, perform a simulation study, conduct a power analysis, and apply the method to field data. The simulation study confirmed that our estimator is asymptotically unbiased with low bias, narrow confidence intervals, and good coverage, given a modest survey effort. The power analysis provided initial guidance on survey effort. When applied to small data sets obtained by radio-tracking Indiana bats, abundance estimates were reasonable, although imprecise. The proposed method has the potential to improve abundance estimates for mobile species that have a fission-fusion social structure, such as Indiana bats, because it does not condition detection on presence at survey locations and because it avoids certain restrictive assumptions.

  3. The Spatial Distribution of Forest Biomass in the Brazilian Amazon: A Comparison of Estimates

    NASA Technical Reports Server (NTRS)

    Houghton, R. A.; Lawrence, J. L.; Hackler, J. L.; Brown, S.

    2001-01-01

    The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land-use change. We compared several estimates of forest biomass for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. We asked three questions. First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas? Amazonian forests (including dead and below-ground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modeling of forest recovery following observed stand-replacing disturbances (the approach used in this research), and estimation of aboveground biomass from airborne or satellite-based instruments sensitive to the vertical structure plant canopies.

  4. Estimated Rock Abundances at the Apollo and Luna Landing Sites

    NASA Astrophysics Data System (ADS)

    Bauch, Karin E.; Hiesinger, Harald; Weinauer, Julia; Robinson, Mark S.; Scholten, Frank

    2013-04-01

    Diurnal temperature variations can be used to analyze the surface and subsurface thermophysical properties [1, 2]. These properties, namely the bulk density, heat capacity, and thermal conductivity, define the thermal inertia, which represents the ability of the surface and subsurface to conduct and store heat [2]. Materials with a low thermal inertia, such as dust and other fine grained materials, quickly respond to temperature changes, which results in a large temperature amplitude during a complete lunar cycle. Surfaces covered with high thermal inertia materials, e.g., rocks or bedrock, take more time to heat up during the day and reradiate the heat during night. We derived maps of thermal inertia from LRO-Diviner nighttime temperature data [3]. This approach is similar to martian thermal inertia derivations, as described by Mellon et al. (2000) and Putzig et al. (2005) [2, 4]. In addition to studying thermal inertia, we also calculated the relative rock abundances of selected study areas; e.g., the Apollo and Luna Landing Sites. Due to the relatively large footprints of remote sensing data, anisothermal surfaces are observed within the field of view. Consequently, multiple thermal inertia units having variable temperatures are merged to a single observed temperature. However, because the brightness temperature is a function of wavelength, it increases with decreasing wavelength. This nonlinearity of the Planck radiance can be used to determine the rock concentration of the observed surfaces [e.g., 5-7]. Therefore, we used our model surface temperatures for different thermal inertia and rock abundances and compared these results to the LRO-Diviner temperature data at distinct wavelengths. The areas investigated in this study are covered by units of low thermal inertia material with low rock abundances (

  5. Estimating abundance from repeated presence-absence data or point counts

    USGS Publications Warehouse

    Royle, J. Andrew; Nichols, J.D.

    2003-01-01

    We describe an approach for estimating occupancy rate or the proportion of area occupied when heterogeneity in detection probability exists as a result of variation in abundance of the organism under study. The key feature of such problems, which we exploit, is that variation in abundance induces variation in detection probability. Thus, heterogeneity in abundance can be modeled as heterogeneity in detection probability. Moreover, this linkage between heterogeneity in abundance and heterogeneity in detection probability allows one to exploit a heterogeneous detection probability model to estimate the underlying distribution of abundances. Therefore, our method allows estimation of abundance from repeated observations of the presence or absence of animals without having to uniquely mark individuals in the population.

  6. Using counts to simultaneously estimate abundance and detection probabilities in a salamander community

    USGS Publications Warehouse

    Dodd, C.K., Jr.; Dorazio, R.M.

    2004-01-01

    A critical variable in both ecological and conservation field studies is determining how many individuals of a species are present within a defined sampling area. Labor intensive techniques such as capture-mark-recapture and removal sampling may provide estimates of abundance, but there are many logistical constraints to their widespread application. Many studies on terrestrial and aquatic salamanders use counts as an index of abundance, assuming that detection remains constant while sampling. If this constancy is violated, determination of detection probabilities is critical to the accurate estimation of abundance. Recently, a model was developed that provides a statistical approach that allows abundance and detection to be estimated simultaneously from spatially and temporally replicated counts. We adapted this model to estimate these parameters for salamanders sampled over a six vear period in area-constrained plots in Great Smoky Mountains National Park. Estimates of salamander abundance varied among years, but annual changes in abundance did not vary uniformly among species. Except for one species, abundance estimates were not correlated with site covariates (elevation/soil and water pH, conductivity, air and water temperature). The uncertainty in the estimates was so large as to make correlations ineffectual in predicting which covariates might influence abundance. Detection probabilities also varied among species and sometimes among years for the six species examined. We found such a high degree of variation in our counts and in estimates of detection among species, sites, and years as to cast doubt upon the appropriateness of using count data to monitor population trends using a small number of area-constrained survey plots. Still, the model provided reasonable estimates of abundance that could make it useful in estimating population size from count surveys.

  7. Hydrodynamic control of mesozooplankton abundance and biomass in northern Svalbard waters (79-81°N)

    NASA Astrophysics Data System (ADS)

    Blachowiak-Samolyk, Katarzyna; Søreide, Janne E.; Kwasniewski, Slawek; Sundfjord, Arild; Hop, Haakon; Falk-Petersen, Stig; Nøst Hegseth, Else

    2008-10-01

    The spatial variation in mesozooplankton biomass, abundance and species composition in relation to oceanography was studied in different climatic regimes (warm Atlantic vs. cold Arctic) in northern Svalbard waters. Relationships between the zooplankton community and various environmental factors (salinity, temperature, sampling depth, bottom depth, sea-ice concentrations, algal biomass and bloom stage) were established using multivariate statistics. Our study demonstrated that variability in the physical environment around Svalbard had measurable effect on the pelagic ecosystem. Differences in bottom depth and temperature-salinity best explained more than 40% of the horizontal variability in mesozooplankton biomass (DM m -2) after adjusting for seasonal variability. Salinity and temperature also explained much (21% and 15%, respectively) of the variability in mesozooplankton vertical distribution (ind. m -3) in August. Algal bloom stage, chlorophyll- a biomass, and depth stratum accounted for additional 17% of the overall variability structuring vertical zooplankton distribution. Three main zooplankton communities were identified, including Atlantic species Fritillaria borealis, Oithona atlantica, Calanus finmarchicus, Themisto abyssorum and Aglantha digitale; Arctic species Calanus glacialis, Gammarus wilkitzkii, Mertensia ovum and Sagitta elegans; and deeper-water inhabitants Paraeuchaeta spp., Spinocalanus spp., Aetideopsis minor, Mormonilla minor, Scolecithricella minor, Gaetanus ( Gaidius) tenuispinus, Ostracoda, Scaphocalanus brevicornis and Triconia borealis. Zooplankton biomasses in Atlantic- and Arctic-dominated water masses were similar, but biological "hot-spots" were associated with Arctic communities.

  8. Harvesting tree biomass at the stand level to assess the accuracy of field and airborne biomass estimation in savannas.

    PubMed

    Colgan, Matthew S; Asner, Gregory P; Swemmer, Tony

    2013-07-01

    Tree biomass is an integrated measure of net growth and is critical for understanding, monitoring, and modeling ecosystem functions. Despite the importance of accurately measuring tree biomass, several fundamental barriers preclude direct measurement at large spatial scales, including the facts that trees must be felled to be weighed and that even modestly sized trees are challenging to maneuver once felled. Allometric methods allow for estimation of tree mass using structural characteristics, such as trunk diameter. Savanna trees present additional challenges, including limited available allometry and a prevalence of multiple stems per individual. Here we collected airborne lidar data over a semiarid savanna adjacent to the Kruger National Park, South Africa, and then harvested and weighed woody plant biomass at the plot scale to provide a standard against which field and airborne estimation methods could be compared. For an existing airborne lidar method, we found that half of the total error was due to averaging canopy height at the plot scale. This error was eliminated by instead measuring maximum height and crown area of individual trees from lidar data using an object-based method to identify individual tree crowns and estimate their biomass. The best object-based model approached the accuracy of field allometry at both the tree and plot levels, and it more than doubled the accuracy compared to existing airborne methods (17% vs. 44% deviation from harvested biomass). Allometric error accounted for less than one-third of the total residual error in airborne biomass estimates at the plot scale when using allometry with low bias. Airborne methods also gave more accurate predictions at the plot level than did field methods based on diameter-only allometry. These results provide a novel comparison of field and airborne biomass estimates using harvested plots and advance the role of lidar remote sensing in savanna ecosystems. PMID:23967584

  9. A RAPID NON-DESTRUCTIVE METHOD FOR ESTIMATING ABOVEGROUND BIOMASS OF SALT MARSH GRASSES

    EPA Science Inventory

    Understanding the primary productivity of salt marshes requires accurate estimates of biomass. Unfortunately, these estimates vary enough within and among salt marshes to require large numbers of replicates if the averages are to be statistically meaningful. Large numbers of repl...

  10. Large Spatial Scale Variability in Bathyal Macrobenthos Abundance, Biomass, α- and β-Diversity along the Mediterranean Continental Margin

    PubMed Central

    Baldrighi, Elisa; Lavaleye, Marc; Aliani, Stefano; Conversi, Alessandra; Manini, Elena

    2014-01-01

    The large-scale deep-sea biodiversity distribution of the benthic fauna was explored in the Mediterranean Sea, which can be seen as a miniature model of the oceans of the world. Within the framework of the BIOFUN project (“Biodiversity and Ecosystem Functioning in Contrasting Southern European Deep-sea Environments: from viruses to megafauna”), we investigated the large spatial scale variability (over >1,000 km) of the bathyal macrofauna communities that inhabit the Mediterranean basin, and their relationships with the environmental variables. The macrofauna abundance, biomass, community structure and functional diversity were analysed and the α-diversity and β-diversity were estimated across six selected slope areas at different longitudes and along three main depths. The macrobenthic standing stock and α-diversity were lower in the deep-sea sediments of the eastern Mediterranean basin, compared to the western and central basins. The macrofaunal standing stock and diversity decreased significantly from the upper bathyal to the lower bathyal slope stations. The major changes in the community composition of the higher taxa and in the trophic (functional) structure occurred at different longitudes, rather than at increasing water depth. For the β-diversity, very high dissimilarities emerged at all levels: (i) between basins; (ii) between slopes within the same basin; and (iii) between stations at different depths; this therefore demonstrates the high macrofaunal diversity of the Mediterranean basins at large spatial scales. Overall, the food sources (i.e., quantity and quality) that characterised the west, central and eastern Mediterranean basins, as well as sediment grain size, appear to influence the macrobenthic standing stock and the biodiversity along the different slope areas. PMID:25225909

  11. Large spatial scale variability in bathyal macrobenthos abundance, biomass, α- and β-diversity along the Mediterranean continental margin.

    PubMed

    Baldrighi, Elisa; Lavaleye, Marc; Aliani, Stefano; Conversi, Alessandra; Manini, Elena

    2014-01-01

    The large-scale deep-sea biodiversity distribution of the benthic fauna was explored in the Mediterranean Sea, which can be seen as a miniature model of the oceans of the world. Within the framework of the BIOFUN project ("Biodiversity and Ecosystem Functioning in Contrasting Southern European Deep-sea Environments: from viruses to megafauna"), we investigated the large spatial scale variability (over >1,000 km) of the bathyal macrofauna communities that inhabit the Mediterranean basin, and their relationships with the environmental variables. The macrofauna abundance, biomass, community structure and functional diversity were analysed and the α-diversity and β-diversity were estimated across six selected slope areas at different longitudes and along three main depths. The macrobenthic standing stock and α-diversity were lower in the deep-sea sediments of the eastern Mediterranean basin, compared to the western and central basins. The macrofaunal standing stock and diversity decreased significantly from the upper bathyal to the lower bathyal slope stations. The major changes in the community composition of the higher taxa and in the trophic (functional) structure occurred at different longitudes, rather than at increasing water depth. For the β-diversity, very high dissimilarities emerged at all levels: (i) between basins; (ii) between slopes within the same basin; and (iii) between stations at different depths; this therefore demonstrates the high macrofaunal diversity of the Mediterranean basins at large spatial scales. Overall, the food sources (i.e., quantity and quality) that characterised the west, central and eastern Mediterranean basins, as well as sediment grain size, appear to influence the macrobenthic standing stock and the biodiversity along the different slope areas. PMID:25225909

  12. Estimation of Canopy Foliar Biomass with Spectral Reflectance Measurements

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Canopy foliar biomass, defined as the product of leaf dry matter content and leaf area index, is an important measurement for global biogeochemical cycles. This study explores the potential for retrieving foliar biomass in green canopies using a spectral index, the Normalized Dry Matter Index (NDMI)...

  13. An aerial survey method to estimate sea otter abundance

    USGS Publications Warehouse

    Bodkin, J.L.; Udevitz, M.S.

    1999-01-01

    Sea otters (Enhydra lutris) occur in shallow coastal habitats and can be highly visible on the sea surface. They generally rest in groups and their detection depends on factors that include sea conditions, viewing platform, observer technique and skill, distance, habitat and group size. While visible on the surface, they are difficult to see while diving and may dive in response to an approaching survey platform. We developed and tested an aerial survey method that uses intensive searches within portions of strip transects to adjust for availability and sightability biases. Correction factors are estimated independently for each survey and observer. In tests of our method using shore-based observers, we estimated detection probabilities of 0.52-0.72 in standard strip-transects and 0.96 in intensive searches. We used the survey method in Prince William Sound, Alaska to estimate a sea otter population size of 9,092 (SE = 1422). The new method represents an improvement over various aspects of previous methods, but additional development and testing will be required prior to its broad application.

  14. Biomass estimator for NIR image with a few additional spectral band images taken from light UAS

    NASA Astrophysics Data System (ADS)

    Pölönen, Ilkka; Salo, Heikki; Saari, Heikki; Kaivosoja, Jere; Pesonen, Liisa; Honkavaara, Eija

    2012-05-01

    A novel way to produce biomass estimation will offer possibilities for precision farming. Fertilizer prediction maps can be made based on accurate biomass estimation generated by a novel biomass estimator. By using this knowledge, a variable rate amount of fertilizers can be applied during the growing season. The innovation consists of light UAS, a high spatial resolution camera, and VTT's novel spectral camera. A few properly selected spectral wavelengths with NIR images and point clouds extracted by automatic image matching have been used in the estimation. The spectral wavelengths were chosen from green, red, and NIR channels.

  15. Effects of LiDAR point density and landscape context on estimates of urban forest biomass

    NASA Astrophysics Data System (ADS)

    Singh, Kunwar K.; Chen, Gang; McCarter, James B.; Meentemeyer, Ross K.

    2015-03-01

    Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional

  16. Forest biomass estimation with hemispherical photography for multiple forest types and various atmospheric conditions

    NASA Astrophysics Data System (ADS)

    Clark, Joshua Andrew

    The importance of accurately identifying inventories of domestic energy, including forest biomass, has increasingly become a priority of the US government and its citizens as the cost of fossil fuels has risen. It is useful to identify which of these resources can be processed and transported at the lowest cost for both private and public landowners. Accurate spatial inventories of forest biomass can help landowners allocate resources to maximize forest biomass utilization and provide information regarding current forest health (e.g., forest fire potential, insect susceptibility, wildlife habitat range). This research has indicated that hemispherical photography (HP) may be an accurate and low cost sensing technique for forest biomass measurements. In this dissertation: (1) It is shown that HP gap fraction measurements and both above ground biomass and crown biomass have a linear relationship. (2) It is demonstrated that careful manipulation of images improves gap fraction estimates, even under unfavorable atmospheric conditions. (3) It is shown that estimates of Leaf Area Index (LAI), based on transformations of gap fraction measurements, are the best estimator for both above ground forest biomass and crown biomass. (4) It is shown that many factors negatively influence the utility of HP for biomass estimation. (5) It is shown that biomass of forests stands with regular spacing is not modeled well using HP. As researchers continue to explore different methods for forest biomass estimation, HP is likely to remain as a viable technique, especially if LAI can be accurately estimated. However, other methods should be compared with HP, particularly for stands where LAI is poorly estimated by HP.

  17. Effect of Trapping Methods, Weather, and Landscape on Estimates of the Culex Vector Mosquito Abundance.

    PubMed

    Karki, Surendra; Hamer, Gabriel L; Anderson, Tavis K; Goldberg, Tony L; Kitron, Uriel D; Krebs, Bethany L; Walker, Edward D; Ruiz, Marilyn O

    2016-01-01

    The local abundance of Culex mosquitoes is a central factor adding to the risk of West Nile virus transmission, and vector abundance data influence public health decisions. This study evaluated differences in abundance estimates from mosquitoes trapped using two common methods: CO2-baited CDC light traps and infusion-baited gravid traps in suburban, Chicago, Illinois. On a weekly basis, the two methods were modestly correlated (r = 0.219) across 71 weeks over 4 years. Lagged weather conditions of up to four weeks were associated with the number of mosquitoes collected in light and gravid traps. Collections in light traps were higher with higher temperature in the same week, higher precipitation one, two, and four weeks before the week of trapping, and lower maximum average wind speed. Collections in gravid traps were higher with higher temperature in the same week and one week earlier, lower temperature four weeks earlier, and with higher precipitation two and four weeks earlier. Culex abundance estimates from light traps were significantly higher in semi-natural areas compared to residential areas, but abundance estimates from gravid traps did not vary by the landscape type. These results highlight the importance of the surveillance methods used in the assessment of local Culex abundance estimates. Measures of risk of exposure to West Nile virus should assess carefully how mosquito abundance has been estimated and integrated into assessments of transmission risk. PMID:27375359

  18. Effect of Trapping Methods, Weather, and Landscape on Estimates of the Culex Vector Mosquito Abundance

    PubMed Central

    Karki, Surendra; Hamer, Gabriel L.; Anderson, Tavis K.; Goldberg, Tony L.; Kitron, Uriel D.; Krebs, Bethany L.; Walker, Edward D.; Ruiz, Marilyn O.

    2016-01-01

    The local abundance of Culex mosquitoes is a central factor adding to the risk of West Nile virus transmission, and vector abundance data influence public health decisions. This study evaluated differences in abundance estimates from mosquitoes trapped using two common methods: CO2-baited CDC light traps and infusion-baited gravid traps in suburban, Chicago, Illinois. On a weekly basis, the two methods were modestly correlated (r = 0.219) across 71 weeks over 4 years. Lagged weather conditions of up to four weeks were associated with the number of mosquitoes collected in light and gravid traps. Collections in light traps were higher with higher temperature in the same week, higher precipitation one, two, and four weeks before the week of trapping, and lower maximum average wind speed. Collections in gravid traps were higher with higher temperature in the same week and one week earlier, lower temperature four weeks earlier, and with higher precipitation two and four weeks earlier. Culex abundance estimates from light traps were significantly higher in semi-natural areas compared to residential areas, but abundance estimates from gravid traps did not vary by the landscape type. These results highlight the importance of the surveillance methods used in the assessment of local Culex abundance estimates. Measures of risk of exposure to West Nile virus should assess carefully how mosquito abundance has been estimated and integrated into assessments of transmission risk. PMID:27375359

  19. Composition, abundance, biomass, and production of macrofauna in a New England estuary: comparisons among eelgrass meadows and other nursery habitats

    USGS Publications Warehouse

    Heck, K.L., Jr.; Able, K.W.; Roman, C.T.; Fahay, M.P.

    1995-01-01

    Quantitative suction sampling was used to characterize and compare the species composition, abundance, biomass, and secondary production of macrofauna inhabiting intertidal mudflat and sandflat, eelgrass meadow, and saltmarshpool habitats in the Nauset Marsh complex, Cape Cod, Massachusetts (USA). Species richness and abundance were often greatest in eelgrass habitat, as was macroinvertebrate biomass and production. Most striking was the five to fifteen times greater rate of annual macrofaunal production in eelgrass habitat than elsewhere, with values ranging from approximately 23139 g AFDW m super(2) yr super(1). The marsh pool containing widgeon grass (Ruppia maritima) supported surprisingly low numbers of macroinvertebrates, probably due to stressfully low dissolved oxygen levels at night during the summer. Two species of macroinvertebrates, blue mussels (Mytilus edulis) and to a lesser extent bay scallops (Argopecten irradians), used eelgrass as 'nursery habitat.' Calculations showed that macroinvertebrate production is proportionally much greater than the amount of primary production attributable to eelgrass in the Nauset Marsh system, and that dramatic changes at all trophic levels could be expected if large changes in seagrass abundance should occur. This work further underscores the extraordinarily large impact that seagrass can have on both the structure and function of estuarine ecosystems.

  20. Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

    NASA Technical Reports Server (NTRS)

    Nelson, Ross F.

    2010-01-01

    Ice, Cloud, and land Elevation Satellite (ICESat) / Geosciences Laser Altimeter System (GLAS) waveform data are used to estimate biomass and carbon on a 1.27 X 10(exp 6) square km study area in the Province of Quebec, Canada, below the tree line. The same input datasets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include non-stratified and stratified versions of a multiple linear model where either biomass or (biomass)(exp 0.5) serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial dry biomass estimates of up to 0.35 G, with a range of 4.94 +/- 0.28 Gt to 5.29 +/-0.36 Gt. The differences among model estimates are statistically non-significant, however, and the results demonstrate the degree to which carbon estimates vary strictly as a function of the model used to estimate regional biomass. Results also indicate that GLAS measurements become problematic with respect to height and biomass retrievals in the boreal forest when biomass values fall below 20 t/ha and when GLAS 75th percentile heights fall below 7 m.

  1. Goals and strategies for estimating trends in landbird abundance

    USGS Publications Warehouse

    Bart, J.; Burnham, K.P.; Dunn, E.H.; Francis, C.M.; John, Ralph C.

    2004-01-01

    Reliable estimates of trends in population size are critical to effective management of landbirds. We propose a standard for considering that landbird populations are adequately monitored: 80% power to detect a 50% decline occuning within 20 years, using a 2-tailed test and a significance level of 0.10, and incorporating effects of potential bias. Our standard also requires that at least two-thirds of the target region be covered by the monitoring program. We recommend that the standard be achieved for species' entire ranges or for any area one-third the size of the temperate portions of Canada and the United States, whichever is smaller. We applied our approach to North American Breeding Bird Survey (BBS) data. At present, potential annual bias for the BBS is estimated at ??0.008. Further, the BBS achieves the monitoring standard for only about 42% of landbirds for which the BBS is considered the most effective monitoring approach. Achieving the proposed monitoring target for ???80% of these species would require increasing the number of BBS - or similar survey - routes by several-fold, a goal that probably is impractical. We suggest several methods for reducing potential bias and argue that if our methods are implemented, potential bias would fall to ??0.003. The required number of BBS or similar routes would then be 5,106, about 40% more than in the current BBS program. Most of the needed increases are in 15 states or provinces. Developing a comprehensive land-bird monitoring program will require increased support for coordination of the BBS (currently 2 people) and new programs for species that are poorly covered at present. Our results provide a quantitative goal for long-term land-bird monitoring and identify the sample sizes needed, within each state and province, to achieve the monitoring goal for most of the roughly 300 landbird species that are well suited to monitoring with the BBS and similar surveys.

  2. Efficient estimation of abundance for patchily distributed populations via two-phase, adaptive sampling.

    USGS Publications Warehouse

    Conroy, M.J.; Runge, J.P.; Barker, R.J.; Schofield, M.R.; Fonnesbeck, C.J.

    2008-01-01

    Many organisms are patchily distributed, with some patches occupied at high density, others at lower densities, and others not occupied. Estimation of overall abundance can be difficult and is inefficient via intensive approaches such as capture-mark-recapture (CMR) or distance sampling. We propose a two-phase sampling scheme and model in a Bayesian framework to estimate abundance for patchily distributed populations. In the first phase, occupancy is estimated by binomial detection samples taken on all selected sites, where selection may be of all sites available, or a random sample of sites. Detection can be by visual surveys, detection of sign, physical captures, or other approach. At the second phase, if a detection threshold is achieved, CMR or other intensive sampling is conducted via standard procedures (grids or webs) to estimate abundance. Detection and CMR data are then used in a joint likelihood to model probability of detection in the occupancy sample via an abundance-detection model. CMR modeling is used to estimate abundance for the abundance-detection relationship, which in turn is used to predict abundance at the remaining sites, where only detection data are collected. We present a full Bayesian modeling treatment of this problem, in which posterior inference on abundance and other parameters (detection, capture probability) is obtained under a variety of assumptions about spatial and individual sources of heterogeneity. We apply the approach to abundance estimation for two species of voles (Microtus spp.) in Montana, USA. We also use a simulation study to evaluate the frequentist properties of our procedure given known patterns in abundance and detection among sites as well as design criteria. For most population characteristics and designs considered, bias and mean-square error (MSE) were low, and coverage of true parameter values by Bayesian credibility intervals was near nominal. Our two-phase, adaptive approach allows efficient estimation of

  3. Improving removal-based estimates of abundance by sampling a population of spatially distinct subpopulations

    USGS Publications Warehouse

    Dorazio, R.M.; Jelks, H.L.; Jordan, F.

    2005-01-01

     A statistical modeling framework is described for estimating the abundances of spatially distinct subpopulations of animals surveyed using removal sampling. To illustrate this framework, hierarchical models are developed using the Poisson and negative-binomial distributions to model variation in abundance among subpopulations and using the beta distribution to model variation in capture probabilities. These models are fitted to the removal counts observed in a survey of a federally endangered fish species. The resulting estimates of abundance have similar or better precision than those computed using the conventional approach of analyzing the removal counts of each subpopulation separately. Extension of the hierarchical models to include spatial covariates of abundance is straightforward and may be used to identify important features of an animal's habitat or to predict the abundance of animals at unsampled locations.

  4. Spatial-temporal scales of synchrony in marine zooplankton biomass and abundance patterns: A world-wide comparison

    NASA Astrophysics Data System (ADS)

    Batchelder, Harold P.; Mackas, David L.; O'Brien, Todd D.

    2012-05-01

    Large scale synchrony in the fluctuations of abundance or biomass of marine fish populations in regions on opposite sides of an ocean basin or in different oceans have been viewed as externally forced by correlated environmental stochasticity (e.g., common external forcing), most often as atmospheric teleconnections of basin-to-global scale atmospheric forcing, such as the Arctic Oscillation, North Atlantic Oscillation or the Pacific Decadal Oscillation. Specific causal mechanisms have been difficult to unequivocally discover, but possible mechanisms include influences on habitat temperatures, productivity operating through bottom-up (trophodynamic) mechanisms or direct climate influence on the fish populations (top-down mechanisms). For small pelagic fishes (sardines and anchovies) in widely separated large marine ecosystems that lack obvious ocean interconnectivity, it has been argued that the teleconnections may be atmospheric, acting on the fishes directly and propagating to the ecosystem from the middle out (wasp-waist species). Zooplankton biomass or abundance time series data from >100 sites world-wide are used to examine the spatial scales of coherent temporal synchrony. If spatially correlated environmental factors (like climate) are important for creating synchrony in fish populations via bottom-up effects (trophic interactions involving fish prey, e.g., zooplankton), then we would expect to observe synchrony in fluctuations of zooplankton biomass/numbers at spatial scales similar to those found for fish species. Zooplankton biomass/abundance have 50% spatial decorrelation scales of ca. 700-1400 km and scales of significant coherence that extend to separation distances of ca. 3000 km. These are also the spatial scales of environmental (sea surface temperature) synchrony from our global analysis. These scales are slightly greater than the 50% decorrelation scales of ca. 150-700 km for recruitment synchrony in Atlantic marine fish and survival and

  5. Accuracy or precision: Implications of sample design and methodology on abundance estimation

    USGS Publications Warehouse

    Kowalewski, Lucas K.; Chizinski, Christopher J.; Powell, Larkin A.; Pope, Kevin L.; Pegg, Mark A.

    2015-01-01

    Sampling by spatially replicated counts (point-count) is an increasingly popular method of estimating population size of organisms. Challenges exist when sampling by point-count method, and it is often impractical to sample entire area of interest and impossible to detect every individual present. Ecologists encounter logistical limitations that force them to sample either few large-sample units or many small sample-units, introducing biases to sample counts. We generated a computer environment and simulated sampling scenarios to test the role of number of samples, sample unit area, number of organisms, and distribution of organisms in the estimation of population sizes using N-mixture models. Many sample units of small area provided estimates that were consistently closer to true abundance than sample scenarios with few sample units of large area. However, sample scenarios with few sample units of large area provided more precise abundance estimates than abundance estimates derived from sample scenarios with many sample units of small area. It is important to consider accuracy and precision of abundance estimates during the sample design process with study goals and objectives fully recognized, although and with consequence, consideration of accuracy and precision of abundance estimates is often an afterthought that occurs during the data analysis process.

  6. Filling a void: abundance estimation of North American populations of arctic geese using hunter recoveries

    USGS Publications Warehouse

    Alisauskas, R.T.; Drake, K.L.; Nichols, J.D.

    2009-01-01

    We consider use of recoveries of marked birds harvested by hunters, in conjunction with continental harvest estimates, for drawing inferences about continental abundance of a select number of goose species. We review assumptions of this method, a version of the Lincoln?Petersen approach, and consider its utility as a tool for making decisions about harvest management in comparison to current sources of information. Finally, we compare such estimates with existing count data, photographic estimates, or other abundance estimates. In most cases, Lincoln estimates are far higher than abundances assumed or perhaps accepted by many waterfowl biologists and managers. Nevertheless, depending on the geographic scope of inference, we suggest that this approach for abundance estimation of arctic geese may have usefulness for retrospective purposes or to assist with harvest management decisions for some species. Lincoln?s estimates may be as close or closer to truth than count, index, or photo data, and can be used with marking efforts currently in place for estimation of survival and harvest rates. Although there are bias issues associated with estimates of both harvest and harvest rate, some of the latter can be addressed with proper allocation of marks to spatially structured populations if subpopulations show heterogeneity in harvest rates.

  7. Hand-held spectral radiometer to estimate gramineous biomass. [with interfaced pocket calculator solution

    NASA Technical Reports Server (NTRS)

    Pearson, R. L.; Miller, L. D.; Tucker, C. J.

    1976-01-01

    A simple hand-held instrument has been designed and constructed to nondestructively estimate above-ground gramineous biomass using radiometric measurements. The prototype unit consists of a modified two-channel digital radiometer interfaced to a pocket calculator. A digital interface was constructed to join electronically and control the radiometer and calculator to enable the radiometer-calculator system to solve a linear conversion solution from radiometric units to estimated biomass. This instrument has been used to estimate radiometrically gramineous biomass in a more efficient fashion with a high degree of accuracy.

  8. Precision of sugarcane biomass estimates in pot studies using fresh and dry weights

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sugarcane (Saccharum spp.) field studies generally report fresh weight (FW) rather than dry weight (DW) due to logistical difficulties in drying large amounts of biomass. Pot studies often measure biomass of young plants with DW under the assumption that DW provides a more precise estimate of treatm...

  9. Biomass estimation of Douglas fir stands using airborne LiDAR data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Biomass is an important parameter not only for carbon cycle modeling, but also for supporting land management operations (e.g. land use policy, forest fire management). Various remote sensing data have been utilized for biomass estimation, especially in forested areas. LiDAR (Light Detection And Ran...

  10. Estimating Root Biomass and Distribution After Fire in a Great Basin Woodland Using Cores or Pits

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurately estimating root biomass is critically important for understanding how below ground carbon storage is affected by different plant life forms and by fire. We compared a new soil coring technique with traditional quantitative pits for determining root biomass. We conducted the study in an ex...

  11. A study on estimation of aboveground wet biomass based on the microwave vegetation indices

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Vegetation biomass is an important parameter in the carbon cycle study. In this paper, a new technique to estimate aboveground vegetation wet biomass based on the Microwave Vegetation Indices (MVIs), which are computed through the observed brightness temperature of AMSR-E/Aqua under two adjacent fre...

  12. Estimating woody biomass in Sub-Saharan Africa

    SciTech Connect

    Millington, A.C.; Critchley, R.W.; Douglas, T.D.; Ryan, P.

    1994-03-01

    Woody biomass constitutes the main domestic fuel in many parts of Africa. The need for more definitive data on this resource was perceived at a Household Energy Seminar held by the World Bank Energy Sector Management Assistance Program (ESMAP) in Harare, Zimbabwe, in February 1988. The present project was conceived as a result. It is a first attempt to produce an analysis by type of land cover of the woody biomass present in Sub-Saharan. On examining the energy balance for most Sub-Saharan countries, one is struck by the dominance of woodfuel, including fuelwood and charcoal. (Copyright (c) 1994 The International Bank for Reconstruction and Development/The World Bank.)

  13. A comparative study of iron abundance estimation methods: Application to the western nearside of the Moon

    NASA Astrophysics Data System (ADS)

    Bhatt, Megha; Mall, Urs; Wöhler, Christian; Grumpe, Arne; Bugiolacchi, Roberto

    2015-03-01

    The FeO weight percentage (wt.%) abundance of the Moon's western nearside (55°S-55°N and 5°E-40°W) is estimated using data from the InfraRed Spectrometer-2 (SIR-2) and the Moon Mineralogy Mapper (M3). In this study, we modified an FeO abundance estimation algorithm (Bhatt, M., Mall, U., Bugiolacchi, R., McKenna-Lawlor, S., Banaszkiewicz, M., Nathues, A., Ullaland, K. [2012]. Icarus 220, 51-64) which relies exclusively on the 2-μm absorption band parameters. The modified FeO abundance estimation algorithm and the regression-based elemental abundance estimation algorithm (Wöhler, C., Grumpe, A., Berezhnoy, A., Bhatt, M.U., Mall, U. [2014]. Icarus 235, 86-122) which is based on the 1-μm and 2-μm absorption band parameters is applied to the M3 data. We have compared results obtained from these two modified algorithms with a previously published Clementine's FeO wt.% map (Lucey, P.G., Blewett, D.T., Jolliff, B.L. [2000]. J. Geophys. Res. 105, 20297-20306). The effects of topography and space weathering on FeO wt.% estimates have been successfully minimized using the modified algorithm based on the 2-μm absorption band parameters. Thus, this algorithm can be successfully applied at middle to high latitudes. Furthermore, a correction for TiO2 is applied to the FeO abundance estimation algorithm based on the 2-μm absorption band parameters using the M3 data. Our comparative study shows a good correspondence between the three algorithms discussed. There are two locations: the crater Tycho and the region around Rima Bode which show major discrepancies. Our modified algorithm based on the 2-μm absorption parameters predicts 3-4 wt.% less FeO for the ray system of Tycho than for the surrounding region. The average iron abundance for the lunar highlands is about 6 wt.% and for the mare regions is about 16 wt.% using the regression-based elemental abundance estimation algorithm and the algorithm based on the 2-μm absorption parameters. This result is consistent with

  14. Estimating aboveground biomass for broadleaf woody plants and young conifers in Sierra Nevada, California forests.

    USGS Publications Warehouse

    McGinnis, Thomas W.; Shook, Christine D.; Keeley, Jon E.

    2010-01-01

    Quantification of biomass is fundamental to a wide range of research and natural resource management goals. An accurate estimation of plant biomass is essential to predict potential fire behavior, calculate carbon sequestration for global climate change research, assess critical wildlife habitat, and so forth. Reliable allometric equations from simple field measurements are necessary for efficient evaluation of plant biomass. However, allometric equations are not available for many common woody plant taxa in the Sierra Nevada. In this report, we present more than 200 regression equations for the Sierra Nevada western slope that relate crown diameter, plant height, crown volume, stem diameter, and both crown diameter and height to the dry weight of foliage, branches, and entire aboveground biomass. Destructive sampling methods resulted in regression equations that accurately predict biomass from one or two simple, nondestructive field measurements. The tables presented here will allow researchers and natural resource managers to easily choose the best equations to fit their biomass assessment needs.

  15. Estimating aboveground biomass for broadleaf woody plants and young conifers in Sierra Nevada, California, forests

    USGS Publications Warehouse

    McGinnis, T.W.; Shook, C.D.; Keeley, J.E.

    2010-01-01

    Quantification of biomass is fundamental to a wide range of research and natural resource management goals. An accurate estimation of plant biomass is essential to predict potential fire behavior, calculate carbon sequestration for global climate change research, assess critical wildlife habitat, and so forth. Reliable allometric equations from simple field measurements are necessary for efficient evaluation of plant biomass. However, allometric equations are not available for many common woody plant taxa in the Sierra Nevada. In this report, we present more than 200 regression equations for the Sierra Nevada western slope that relate crown diameter, plant height, crown volume, stem diameter, and both crown diameter and height to the dry weight of foliage, branches, and entire aboveground biomass. Destructive sampling methods resulted in regression equations that accurately predict biomass from one or two simple, nondestructive field measurements. The tables presented here will allow researchers and natural resource managers to easily choose the best equations to fit their biomass assessment needs.

  16. A method to estimate the biomass of Spirulina platensis cultivated on a solid medium

    PubMed Central

    Pelizer, Lúcia Helena; Moraes, Iracema de Oliveira

    2014-01-01

    This paper presents a method to estimate the biomass of Spirulina cultivated on solid medium with sugarcane bagasse as a support, in view of the difficulty in determining biomass concentrations in bioprocesses, particularly those conducted in semi-solid or solid media. The genus Spirulina of the family Oscillatoriaceae comprises the group of multicellular filamentous cyanobacteria (blue-green microalgae). Spirulina is used as fish feed in aquaculture, as a food supplement, a source of vitamins, pigments, antioxidants and fatty acids. Therefore, its growth parameters are extremely important in studies of the development and optimization of bioprocesses. For studies of biomass growth, Spirulina platensis was cultured on solid medium using sugarcane bagasse as a support. The biomass thus produced was estimated by determining the protein content of the material grown during the process, based on the ratio of dry weight to protein content obtained in the surface growth experiments. The protein content of the biomass grown in Erlenmeyer flasks on surface medium was examined daily to check the influence of culture time on the protein content of the biomass. The biomass showed an average protein content of 42.2%. This methodology enabled the concentration of biomass adhering to the sugarcane bagasse to be estimated from the indirect measurement of the protein content associated with cell growth. PMID:25477928

  17. A method to estimate the biomass of Spirulina platensis cultivated on a solid medium.

    PubMed

    Pelizer, Lúcia Helena; Moraes, Iracema de Oliveira

    2014-01-01

    This paper presents a method to estimate the biomass of Spirulina cultivated on solid medium with sugarcane bagasse as a support, in view of the difficulty in determining biomass concentrations in bioprocesses, particularly those conducted in semi-solid or solid media. The genus Spirulina of the family Oscillatoriaceae comprises the group of multicellular filamentous cyanobacteria (blue-green microalgae). Spirulina is used as fish feed in aquaculture, as a food supplement, a source of vitamins, pigments, antioxidants and fatty acids. Therefore, its growth parameters are extremely important in studies of the development and optimization of bioprocesses. For studies of biomass growth, Spirulina platensis was cultured on solid medium using sugarcane bagasse as a support. The biomass thus produced was estimated by determining the protein content of the material grown during the process, based on the ratio of dry weight to protein content obtained in the surface growth experiments. The protein content of the biomass grown in Erlenmeyer flasks on surface medium was examined daily to check the influence of culture time on the protein content of the biomass. The biomass showed an average protein content of 42.2%. This methodology enabled the concentration of biomass adhering to the sugarcane bagasse to be estimated from the indirect measurement of the protein content associated with cell growth. PMID:25477928

  18. Estimating total standing herbaceous biomass production with LANDSAT MSS digital data

    NASA Technical Reports Server (NTRS)

    Richardson, A. J.; Everitt, J. H.; Wiegand, C. L. (Principal Investigator)

    1982-01-01

    Rangeland biomass data were correlated with spectral vegetation indices, derived from LANDSAT MSS data. LANDSAT data from five range and three other land use sites in Willacv and Cameron Counties were collected on October 17 and December 10, 1975, and on July 31 and September 23, 1976. The overall linear correlation of total standing herbaceous biomass with the LANDSAT derived perpendicular vegetation index was highly significant (r = 0.90**) for these four dates. The standard error of estimate was 722 kg/ha. Biomass data were recorded for two of these range sites for 8 months (March through October) during the 1976 growing season. Standing green biomass accounted for most of the increase in herbage, starting in June and ending about September and October. These results indicate that satellite data may be useful for the estimation of total standing herbaceous biomass production that could aid range managers in assessing range condition and animal carrying capacities of large and inaccessible range holdings.

  19. Simulations of Forest Structure and Biomass across Russia for Biomass Estimation under a Changing Climate.

    NASA Astrophysics Data System (ADS)

    Shugart, H. H., Jr.; Shuman, J. K.

    2014-12-01

    An important innovation in understanding the interactions among physical of forests and measurement of forest state is the potential deployment of active (RADAR and LiDAR) satellite reconnaissance systems. We investigate the potential gain in predictive capability of structural measures determined by these instruments. Observations and model results have identified climate change as a driver of structural and compositional change in forest of Russia, which may affect climate patterns beyond the region. Using an individual-tree-based model (UVAFME) for forests at 31,000+ grid points of a 22 km×22 km grid across Russia, we inspected the relationships between above-ground biomass and structural measures including maximum tree height and Lorey's height (average height for each tree weighted by basal area). At each of the grid points 200 independent 0.1hectare plots were simulated for 100 years using two climate change scenarios following a 500-year spin-up to produce a mature forest. Other simulations project the change of a forest-landscape mosaic with equal proportions of 0, 25, 50, 75 and 100 year-old stands to mimic a heterogeneous landscape mosaic typical of reoccurring wildfires. Qualitatively, maximum height and Lorey's height seem particularly useful in detecting forest change in the vicinity of forest transitions with other ecosystems. Quantitatively, maximum height and Lorey's height account for a large component of the variability in forest biomass. Results of exponential regression between height measurements and biomass show that r2 values can exceed 0.75. Lorey's height is more capable in this regard. The relationship between these measures of height and biomass can be improved with classification of forests into types. For example, Russian forest dominated by the tall, large diameter pines (Pinus koraiensis, P. sibirica, P. sylvestris) can have exceptional biomass compared to other forests across Russia, and produced biomass and height values higher

  20. Rapid assessment of above-ground biomass of Giant Reed using visibility estimates

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A method for the rapid estimation of biomass and density of giant reed (Arundo donax L.) was developed using estimates of visibility as a predictive tool. Visibility estimates were derived by capturing digital images of a 0.25 m2 polystyrene whiteboard placed a set distance (1m) from the edge of gia...

  1. Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

    NASA Technical Reports Server (NTRS)

    Nelson, Ross

    2008-01-01

    ICESat/GLAS waveform data are used to estimate biomass and carbon on a 1.27 million sq km study area. the Province of Quebec, Canada, below treeline. The same input data sets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include nonstratified and stratified versions of a multiple linear model where either biomass or (square root of) biomass serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial biomass estimates of up to 0.35 Gt (range 4.942+/-0.28 Gt to 5.29+/-0.36 Gt). The results suggest that if different predictive models are used to estimate regional carbon stocks in different epochs, e.g., y2005, y2015, one might mistakenly infer an apparent aboveground carbon "change" of, in this case, 0.18 Gt, or approximately 7% of the aboveground carbon in Quebec, due solely to the use of different predictive models. These findings argue for model consistency in future, LiDAR-based carbon monitoring programs. Regional biomass estimates from the four GLAS models are compared to ground estimates derived from an extensive network of 16,814 ground plots located in southern Quebec. Stratified models proved to be more accurate and precise than either of the two nonstratified models tested.

  2. A first estimate of white shark, Carcharodon carcharias, abundance off Central California

    PubMed Central

    Chapple, Taylor K.; Jorgensen, Salvador J.; Anderson, Scot D.; Kanive, Paul E.; Klimley, A. Peter; Botsford, Louis W.; Block, Barbara A.

    2011-01-01

    The decline of sharks in the global oceans underscores the need for careful assessment and monitoring of remaining populations. The northeastern Pacific is the home range for a genetically distinct clade of white sharks (Carcharodon carcharias). Little is known about the conservation status of this demographically isolated population, concentrated seasonally at two discrete aggregation sites: Central California (CCA) and Guadalupe Island, Mexico. We used photo-identification of dorsal fins in a sequential Bayesian mark–recapture algorithm to estimate white shark abundance off CCA. We collected 321 photographs identifying 130 unique individuals, and estimated the abundance off CCA to be 219 mature and sub-adult individuals ((130, 275) 95% credible intervals), substantially smaller than populations of other large marine predators. Our methods can be readily expanded to estimate shark population abundance at other locations, and over time, to monitor the status, population trends and protection needs of these globally distributed predators. PMID:21389017

  3. Estimations of deciduous forest biomass by analyzing vegetation microwave emission

    NASA Astrophysics Data System (ADS)

    Zhang, Zhongjun; Zhang, Lixin; Zhao, Shaojie; Wang, Huan

    2011-09-01

    Forest is important in global carbon cycle and has potential impact on global climatic change. Whether the soil moisture under forest area can be detected by microwave emission signature is unknown due to the dense forest cover. Also, the relationship between forest biomass and its microwave emissivity and transmissivity is of interest to be studied. The microwave emission contribution received by the radiometer above the forest canopy comes from both the soil surface and vegetation layer. In this study, a high-order emission model, Matrix-Doubling, was employed to simulate the emissivity of a young deciduous forest. A field experiment before and after watering the deciduous tree stand was carried in June 5, 2011 in Baoding, China to verify the model, and to measure the tree transmissivity. A tree was selected to be cut to measure the tree parameters and weighed its biomass. Assuming the forest as a non-scattering medium, the effective single-scattering albedo is obtained for 0th-order model by fitting the same emissivity from Matrix-Doubling model. For lower albedo which could be ignored, transmissivity of trees can be deduced by measured Brightness Temperatures before and after watering the underlying soil. The relationship between forest biomass and its transmissivity is presented in this paper.

  4. Derivation of safety factors for setting harvest quotas on adult walleyes from past estimates of abundance

    USGS Publications Warehouse

    Hansen, Michael J.; Staggs, Michael D.; Hoff, Michael H.

    1991-01-01

    Past population estimates of adult walleyes Stizostedion vitreum can be used to set harvest quotas, provided that temporal variability in abundance of adult walleyes is accounted for. We used a long-term data set from Escanaba Lake, Wisconsin, to evaluate the accuracy of past population estimates for setting current-year quotas for adult walleyes. The results from Escanaba Lake were corroborated by comparison with other lakes where adult walleye abundance was estimated in more than 1 year. The accuracy of estimates of adult walleye abundance declined over time from the year the estimate was obtained to the year it was used to set a harvest quota. We derived safety factors for application to past estimates of population size; these factors limit the occurrence of an exploitation rate exceeding the maximum sustainable rate (35%) to approximately 1 in 40. These safety factors declined from 35% for 1-year-old estimates to less than 20% for 10-year-old estimates.

  5. Potential application of multipolarization SAR for pine-plantation biomass estimation

    NASA Technical Reports Server (NTRS)

    Wu, Shih-Tseng

    1987-01-01

    This paper presents the technique and the potential utility of multipolarization Synthetic Aperture Radar (SAR) data for pine-plantation biomass estimation. Three channels of SAR data, one from the Shuttle Imaging Radar SIR-A and the other two from the aircraft SAR, were acquired over the Baldwin County, Alabama, study area. The SIR-A data were acquired with HH polarization and the aircraft SAR data with VV and VH polarizations. Linear regression techniques are used to estimate the pine-plantation biomass, tree height, and age using 21 test plots. The results indicate that the multipolarization data are highly related to the plantation biomass. The results suggest a potential application of multipolarization SAR for pine-plantation biomass estimation.

  6. Forest Fire Burned Biomass Estimation Using Satellite Images and Reference Data

    NASA Astrophysics Data System (ADS)

    Qin, Xianlin; Zu, Xiaofeng; Deng, Guang; Li, Zengyuan; Zhang, Zihui; Casanova, J. L. Sanz, Julia; Salvador, Pablo

    2014-11-01

    Vegetation biomass burning has been identified as a significant source of aerosols, carbon fluxes, and trace gases, which pollute the atmosphere and contribute to radiative forcing responsible for global climate change. To estimate the total biomass burned by forest fire using satellite images in Dragon 3, basing on the fuel load from reference data,the combustion factor getting from fieldwork at the sub-compartment level, and the results of burned scar mapping by using HJ-1A CCD and the monthly MODIS burned production datasets (MCD45A1), the biomass burned of the selected experiment area has been estimated by combining these data. The result showed that the accuracy of the biomass burned estimation mainly was affected by the accuracy of burned scar edge using the spatial resolution of satellite data.

  7. Dependence of Mercurian Atmospheric Column Abundance Estimations on Surface-Reflectance Modeling

    NASA Technical Reports Server (NTRS)

    Domingue, Deborah L.; Sprague, Ann L.; Hunten, Donald M.

    1997-01-01

    Column abundance estimates of sodium, and analogously, potassium, in Mercury's exosphere are strongly correlated to the surface reflection model used to calibrate the spectral data and the surface reflection model incorporated into the atmospheric radiative transfer solution. Depending on the surface reflection model parameters used, there can be differences in calibration factors of up to +/- 30% and differences in estimated column abundance of up to +/- 35%. Although the surface reflectance may not be used in the calibration of spacecraft measurements, the interaction between the reflected surface light and the atmospheric brightness remains important.

  8. Hierarchical modelling and estimation of abundance and population trends in metapopulation designs.

    PubMed

    Kéry, Marc; Andrew Royle, J

    2010-03-01

    1. Population assessment in changing environments is challenging because factors governing abundance may also affect detectability and thus bias observed counts. We describe a hierarchical modelling framework for estimating abundance corrected for detectability in metapopulation designs, where observations of 'individuals' (e.g. territories) are replicated in space and time. We consider two classes of models; first, we regard the data as independent binomial counts and model abundance and detectability based on a product-binomial likelihood. Secondly, we use the more complex detection-non-detection data for each territory to form encounter history frequencies, and analyse the resulting multinomial/Poisson hierarchical model. Importantly, we extend both models to directly estimate population trends over multiple years. Our models correct for any time trends in detectability when assessing population trends in abundance. 2. We illustrate both models for a farmland and a woodland bird species, skylark Alauda arvensis and willow tit Parus montanus, by applying them to Swiss BBS data, where 268 1 km(2) quadrats were surveyed two to three times during 1999-2003. We fit binomial and multinomial mixture models where log(abundance) depended on year, elevation, forest cover and transect route length, and logit(detection) on year, season and search effort. 3. Parameter estimates were very similar between models with confidence intervals overlapping for most parameters. Trend estimates were similar for skylark (-0.074 +/- 0.041 vs. -0.047 +/- 0.019) and willow tit (0.044 +/- 0.046 vs. 0.047 +/- 0.018). As expected, the multinomial model gave more precise estimates, but also yielded lower abundance estimates for the skylark. This may be due to effects of territory misclassification (lumping error), which do not affect the binomial model. 4. Both models appear useful for estimating abundance and population trends free from distortions by detectability in metapopulation designs

  9. Mid-summer mesozooplankton biomass, its size distribution, and estimated production within a glacial Arctic fjord (Hornsund, Svalbard)

    NASA Astrophysics Data System (ADS)

    Trudnowska, E.; Basedow, S. L.; Blachowiak-Samolyk, K.

    2014-09-01

    The estimation of secondary production constitutes an integrating proxy of pelagic ecosystem status, its functions as well as its responses to environmental stressors. The combination of high-resolution automatic measurements with a Laser Optical Plankton Counter (LOPC) and size spectrum analyses was utilized to estimate the secondary production of a high Arctic fjord during a summer post bloom situation in 2012. The dataset comprised 28 vertical and extensive horizontal hauls of a LOPC-CTD-fluorometer platform plus four zooplankton net sampling stations for taxonomic composition designation. A clear gradient in temperature, salinity, chlorophyll a concentrations as well as mesozooplankton abundance, biomass and production was demonstrated along Hornsund fjord axis. The outer fjord part was under the influence of water advection and had the highest chlorophyll a concentrations, numerous opaque mesozooplankton individuals and flat slopes of size spectra, pointing to long food chains in which biomass is recycled several times. The opposite state was found in the glacial bays, where the glacier meltwater discharge led to low chlorophyll a concentrations but high abundance of small and amorphous particles. It resulted in steep size spectra slopes and high intercepts implying higher potential productivity there. The model of mesozooplankton production demonstrated that Hornsund fjord is a highly productive ecosystem, particularly its upper water layer and its central parts. However, we would like to emphasize that a careful approach is needed before going deeper into ecological interpretations based on size spectra analysis, especially in reservoirs, where non-zooplankton particles contribute to the size spectra.

  10. Fresh Biomass Estimation in Heterogeneous Grassland Using Hyperspectral Measurements and Multivariate Statistical Analysis

    NASA Astrophysics Data System (ADS)

    Darvishzadeh, R.; Skidmore, A. K.; Mirzaie, M.; Atzberger, C.; Schlerf, M.

    2014-12-01

    Accurate estimation of grassland biomass at their peak productivity can provide crucial information regarding the functioning and productivity of the rangelands. Hyperspectral remote sensing has proved to be valuable for estimation of vegetation biophysical parameters such as biomass using different statistical techniques. However, in statistical analysis of hyperspectral data, multicollinearity is a common problem due to large amount of correlated hyper-spectral reflectance measurements. The aim of this study was to examine the prospect of above ground biomass estimation in a heterogeneous Mediterranean rangeland employing multivariate calibration methods. Canopy spectral measurements were made in the field using a GER 3700 spectroradiometer, along with concomitant in situ measurements of above ground biomass for 170 sample plots. Multivariate calibrations including partial least squares regression (PLSR), principal component regression (PCR), and Least-Squared Support Vector Machine (LS-SVM) were used to estimate the above ground biomass. The prediction accuracy of the multivariate calibration methods were assessed using cross validated R2 and RMSE. The best model performance was obtained using LS_SVM and then PLSR both calibrated with first derivative reflectance dataset with R2cv = 0.88 & 0.86 and RMSEcv= 1.15 & 1.07 respectively. The weakest prediction accuracy was appeared when PCR were used (R2cv = 0.31 and RMSEcv= 2.48). The obtained results highlight the importance of multivariate calibration methods for biomass estimation when hyperspectral data are used.

  11. Hankin and Reeves' approach to estimating fish abundance in small streams: Limitations and alternatives

    USGS Publications Warehouse

    Thompson, W.L.

    2003-01-01

    Hankin and Reeves' (1988) approach to estimating fish abundance in small streams has been applied in stream fish studies across North America. However, their population estimator relies on two key assumptions: (1) removal estimates are equal to the true numbers of fish, and (2) removal estimates are highly correlated with snorkel counts within a subset of sampled stream units. Violations of these assumptions may produce suspect results. To determine possible sources of the assumption violations, I used data on the abundance of steelhead Oncorhynchus mykiss from Hankin and Reeves' (1988) in a simulation composed of 50,000 repeated, stratified systematic random samples from a spatially clustered distribution. The simulation was used to investigate effects of a range of removal estimates, from 75% to 100% of true fish abundance, on overall stream fish population estimates. The effects of various categories of removal-estimates-to-snorkel-count correlation levels (r = 0.75-1.0) on fish population estimates were also explored. Simulation results indicated that Hankin and Reeves' approach may produce poor results unless removal estimates exceed at least 85% of the true number of fish within sampled units and unless correlations between removal estimates and snorkel counts are at least 0.90. A potential modification to Hankin and Reeves' approach is the inclusion of environmental covariates that affect detection rates of fish into the removal model or other mark-recapture model. A potential alternative approach is to use snorkeling combined with line transect sampling to estimate fish densities within stream units. As with any method of population estimation, a pilot study should be conducted to evaluate its usefulness, which requires a known (or nearly so) population of fish to serve as a benchmark for evaluating bias and precision of estimators.

  12. Are Inventory Based and Remotely Sensed Above-Ground Biomass Estimates Consistent?

    PubMed Central

    Hill, Timothy C.; Williams, Mathew; Bloom, A. Anthony; Mitchard, Edward T. A.; Ryan, Casey M.

    2013-01-01

    Carbon emissions resulting from deforestation and forest degradation are poorly known at local, national and global scales. In part, this lack of knowledge results from uncertain above-ground biomass estimates. It is generally assumed that using more sophisticated methods of estimating above-ground biomass, which make use of remote sensing, will improve accuracy. We examine this assumption by calculating, and then comparing, above-ground biomass area density (AGBD) estimates from studies with differing levels of methodological sophistication. We consider estimates based on information from nine different studies at the scale of Africa, Mozambique and a 1160 km2 study area within Mozambique. The true AGBD is not known for these scales and so accuracy cannot be determined. Instead we consider the overall precision of estimates by grouping different studies. Since an the accuracy of an estimate cannot exceed its precision, this approach provides an upper limit on the overall accuracy of the group. This reveals poor precision at all scales, even between studies that are based on conceptually similar approaches. Mean AGBD estimates for Africa vary from 19.9 to 44.3 Mg ha−1, for Mozambique from 12.7 to 68.3 Mg ha−1, and for the 1160 km2 study area estimates range from 35.6 to 102.4 Mg ha−1. The original uncertainty estimates for each study, when available, are generally small in comparison with the differences between mean biomass estimates of different studies. We find that increasing methodological sophistication does not appear to result in improved precision of AGBD estimates, and moreover, inadequate estimates of uncertainty obscure any improvements in accuracy. Therefore, despite the clear advantages of remote sensing, there is a need to improve remotely sensed AGBD estimates if they are to provide accurate information on above-ground biomass. In particular, more robust and comprehensive uncertainty estimates are needed. PMID:24069275

  13. [Estimation of Winter Wheat Biomass Using Visible Spectral and BP Based Artificial Neural Networks].

    PubMed

    Cui, Ri-xian; Liu, Ya-dong; Fu, Jin-dong

    2015-09-01

    The objective of this study was to evaluate the feasibility of using color digital image analysis and back propagation (BP) based artificial neural networks (ANN) method to estimate above ground biomass at the canopy level of winter wheat field. Digital color images of winter wheat canopies grown under six levels of nitrogen treatments were taken with a digital camera for four times during the elongation stage and at the same time wheat plants were sampled to measure above ground biomass. Canopy cover (CC) and 10 color indices were calculated from winter wheat canopy images by using image analysis program (developed in Microsoft Visual Basic). Correlation analysis was carried out to identify the relationship between CC, 10 color indices and winter wheat above ground biomass. Stepwise multiple linear regression and BP based ANN methods were used to establish the models to estimate winter wheat above ground biomass. The results showed that CC, and two color indices had a significant cor- relation with above ground biomass. CC revealed the highest correlation with winter wheat above ground biomass. Stepwise multiple linear regression model constituting CC and color indices of NDI and b, and BP based ANN model with four variables (CC, g, b and NDI) for input was constructed to estimate winter wheat above ground biomass. The validation results indicate that the model using BP based ANN method has a better performance with higher R2 (0.903) and lower RMSE (61.706) and RRMSE (18.876) in comparation with the stepwise regression model. PMID:26669174

  14. Estimation of lunar FeO abundance based on imaging by LRO Diviner

    NASA Astrophysics Data System (ADS)

    Tang, Xiao; Luo, Xiao-Xing; Jiang, Yun; Xu, Ao-Ao; Wang, Zhen-Chao; Zhang, Xue-Wei; Chen, Yuan; Zhang, Xiao-Meng; Cai, Wei; Wu, Yun-Zhao

    2016-02-01

    Understanding the abundance and distribution characteristics of FeO on the surface of the Moon is important for investigating its evolution. The current high resolution maps of the global FeO abundance are mostly produced with visible and near infrared reflectance spectra. The Christiansen Feature (CF) in mid-infrared has strong sensitivity to lunar minerals and correlates to major elements composing minerals. This paper investigates the possibility of mapping global FeO abundance using the CF values from the Diviner Lunar Radiometer Experiment aboard the Lunar Reconnaissance Orbiter (LRO) mission. A high correlation between the CF values and FeO abundances from the Apollo samples was found. Based on this high correlation, a new global map (±60°) of FeO was produced using the CF map. The results show that the global FeO average is 8.2 wt.%, the highland average is 4.7 wt.%, the global modal abundance is 5.4 wt.% and the lunar mare mode is 15.7 wt.%. These results are close to those derived from data provided by Clementine, the Lunar Prospector Gamma Ray Spectrometer (LP-GRS) and the Chang'e-1 Interference Imaging Spectrometer (IIM), demonstrating the feasibility of estimating FeO abundance based on the Diviner CF data. The near global FeO abundance map shows an enrichment of lunar major elements.

  15. Estimating species occurrence, abundance, and detection probability using zero-inflated distributions

    USGS Publications Warehouse

    Wenger, S.J.; Freeman, Mary C.

    2008-01-01

    Researchers have developed methods to account for imperfect detection of species with either occupancy (presence-absence) or count data using replicated sampling. We show how these approaches can be combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero-inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete-detection zero-inflated modeling approach yields a superior fit to the data than other models. We propose that zero-inflated abundance models accounting for incomplete detection be considered when replicate count data are available.

  16. How does landscape use influence small mammal diversity, abundance and biomass in hedgerow networks of farming landscapes?

    NASA Astrophysics Data System (ADS)

    Michel, Nadia; Burel, Françoise; Butet, Alain

    2006-07-01

    Over the last decades, profound changes in agricultural practices in the world have led to modifications of land-use as well as landscape structure and composition. Major changes resulted in enlargement of parcel size, increase of cultivated areas and drastic reduction of permanent elements such as woods, hedges or natural meadows. In this context we chose to investigate the composition and structure of small mammal communities in the hedgerow networks of three landscape units of Western France (Brittany) differing by their level of agricultural land-use intensity and hedgerow network density: a slightly intensified dense hedgerow network landscape unit (BOC1), a moderately intensified and fragmented hedgerow network landscape unit (BOC2) and a highly intensified landscape unit on an area reclaimed from the sea (POL). Characterization of small mammal communities was performed using live trapping on permanent habitats (eight hedges per landscape unit). In each of the 24 trapping units, a standardized method was used consisting of a baited 100-m trap-line. Diversity indices were used to compare the three communities. Species richness didn't vary across landscapes whereas Shannon's index of diversity underlined a clear difference between, on the one hand, the most intensified landscape unit (POL) which displayed the lowest diversity and, on the other hand, the two other less intensified units. The abundance of small mammals differed between the three sites: they were significantly more numerous in the hedges of the most intensified site than in hedges of the two other sites. Differences between species also appeared: for example, the Bank vole ( Clethrionomys glareolus) was very characteristic of POL, whereas the Pygmy shrew ( Sorex minutus) was much more associated with BOC sites. Within hedges, like for abundance, small mammal biomass was the highest in the most intensified site (POL > BOC2 = BOC1). On the contrary, at the landscape scale, biomass was the lowest in

  17. A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti

    PubMed Central

    Villela, Daniel A. M.; Codeço, Claudia T.; Figueiredo, Felipe; Garcia, Gabriela A.; Maciel-de-Freitas, Rafael; Struchiner, Claudio J.

    2015-01-01

    Strategies to minimize dengue transmission commonly rely on vector control, which aims to maintain Ae. aegypti density below a theoretical threshold. Mosquito abundance is traditionally estimated from mark-release-recapture (MRR) experiments, which lack proper analysis regarding accurate vector spatial distribution and population density. Recently proposed strategies to control vector-borne diseases involve replacing the susceptible wild population by genetically modified individuals’ refractory to the infection by the pathogen. Accurate measurements of mosquito abundance in time and space are required to optimize the success of such interventions. In this paper, we present a hierarchical probabilistic model for the estimation of population abundance and spatial distribution from typical mosquito MRR experiments, with direct application to the planning of these new control strategies. We perform a Bayesian analysis using the model and data from two MRR experiments performed in a neighborhood of Rio de Janeiro, Brazil, during both low- and high-dengue transmission seasons. The hierarchical model indicates that mosquito spatial distribution is clustered during the winter (0.99 mosquitoes/premise 95% CI: 0.80–1.23) and more homogeneous during the high abundance period (5.2 mosquitoes/premise 95% CI: 4.3–5.9). The hierarchical model also performed better than the commonly used Fisher-Ford’s method, when using simulated data. The proposed model provides a formal treatment of the sources of uncertainty associated with the estimation of mosquito abundance imposed by the sampling design. Our approach is useful in strategies such as population suppression or the displacement of wild vector populations by refractory Wolbachia-infected mosquitoes, since the invasion dynamics have been shown to follow threshold conditions dictated by mosquito abundance. The presence of spatially distributed abundance hotspots is also formally addressed under this modeling framework and

  18. Biomass estimation of wetland vegetation in Poyang Lake area using ENVISAT advanced synthetic aperture radar data

    NASA Astrophysics Data System (ADS)

    Liao, Jingjuan; Shen, Guozhuang; Dong, Lei

    2013-01-01

    Biomass estimation of wetlands plays a role in understanding dynamic changes of the wetland ecosystem. Poyang Lake is the largest freshwater lake in China, with an area of about 3000 km2. The lake's wetland ecosystem has a significant impact on leveraging China's environmental change. Synthetic aperture radar (SAR) data are a good choice for biomass estimation during rainy and dry seasons in this region. In this paper, we discuss the neural network algorithms (NNAs) to retrieve wetland biomass using the alternating-polarization ENVISAT advanced synthetic aperture radar (ASAR) data. Two field measurements were carried out coinciding with the satellite overpasses through the hydrological cycle in April to November. A radiative transfer model of forest canopy, the Michigan Microwave Canopy Scattering (MIMICS) model, was modified to fit to herbaceous wetland ecosystems. With both ASAR and MIMICS simulations as input data, the NNA-estimated biomass was validated with ground-measured data. This study indicates the capability of NNA combined with a modified MIMICS model to retrieve wetland biomass from SAR imagery. Finally, the overall biomass of Poyang Lake wetland vegetation has been estimated. It reached a level of 1.09×109, 1.86×108, and 9.87×108 kg in April, July, and November 2007, respectively.

  19. Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam

    PubMed Central

    Nam, Vu Thanh; van Kuijk, Marijke; Anten, Niels P. R.

    2016-01-01

    Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam. PMID:27309718

  20. Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam.

    PubMed

    Nam, Vu Thanh; van Kuijk, Marijke; Anten, Niels P R

    2016-01-01

    Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam. PMID:27309718

  1. Repeated count surveys help standardize multi-agency estimates of American Oystercatcher (Haematopus palliatus) abundance

    USGS Publications Warehouse

    Hostetter, Nathan J.; Gardner, Beth; Schweitzer, Sara H.; Boettcher, Ruth; Wilke, Alexandra L.; Addison, Lindsay; Swilling, William R.; Pollock, Kenneth H.; Simons, Theodore R.

    2015-01-01

    The extensive breeding range of many shorebird species can make integration of survey data problematic at regional spatial scales. We evaluated the effectiveness of standardized repeated count surveys coordinated across 8 agencies to estimate the abundance of American Oystercatcher (Haematopus palliatus) breeding pairs in the southeastern United States. Breeding season surveys were conducted across coastal North Carolina (90 plots) and the Eastern Shore of Virginia (3 plots). Plots were visited on 1–5 occasions during April–June 2013. N-mixture models were used to estimate abundance and detection probability in relation to survey date, tide stage, plot size, and plot location (coastal bay vs. barrier island). The estimated abundance of oystercatchers in the surveyed area was 1,048 individuals (95% credible interval: 851–1,408) and 470 pairs (384–637), substantially higher than estimates that did not account for detection probability (maximum counts of 674 individuals and 316 pairs). Detection probability was influenced by a quadratic function of survey date, and increased from mid-April (~0.60) to mid-May (~0.80), then remained relatively constant through June. Detection probability was also higher during high tide than during low, rising, or falling tides. Abundance estimates from N-mixture models were validated at 13 plots by exhaustive productivity studies (2–5 surveys wk−1). Intensive productivity studies identified 78 breeding pairs across 13 productivity plots while the N-mixture model abundance estimate was 74 pairs (62–119) using only 1–5 replicated surveys season−1. Our results indicate that standardized replicated count surveys coordinated across multiple agencies and conducted during a relatively short time window (closure assumption) provide tremendous potential to meet both agency-level (e.g., state) and regional-level (e.g., flyway) objectives in large-scale shorebird monitoring programs.

  2. ROOT BIOMASS ALLOCATION IN THE WORLD'S UPLAND FORESTS

    EPA Science Inventory

    Because the world's forests play a major role in regulating nutrient and carbon cycles, there is much interest in estimating their biomass. Estimates of aboveground biomass based on well-established methods are relatively abundant; estimates of root biomass based on standard meth...

  3. Estimating the abundance of clustered animal population by using adaptive cluster sampling and negative binomial distribution

    NASA Astrophysics Data System (ADS)

    Bo, Yizhou; Shifa, Naima

    2013-09-01

    An estimator for finding the abundance of a rare, clustered and mobile population has been introduced. This model is based on adaptive cluster sampling (ACS) to identify the location of the population and negative binomial distribution to estimate the total in each site. To identify the location of the population we consider both sampling with replacement (WR) and sampling without replacement (WOR). Some mathematical properties of the model are also developed.

  4. Using spatiotemporal statistical models to estimate animal abundance and infer ecological dynamics from survey counts

    USGS Publications Warehouse

    Conn, Paul B.; Johnson, Devin S.; Ver Hoef, Jay M.; Hooten, Mevin B.; London, Joshua M.; Boveng, Peter L.

    2015-01-01

    Ecologists often fit models to survey data to estimate and explain variation in animal abundance. Such models typically require that animal density remains constant across the landscape where sampling is being conducted, a potentially problematic assumption for animals inhabiting dynamic landscapes or otherwise exhibiting considerable spatiotemporal variation in density. We review several concepts from the burgeoning literature on spatiotemporal statistical models, including the nature of the temporal structure (i.e., descriptive or dynamical) and strategies for dimension reduction to promote computational tractability. We also review several features as they specifically relate to abundance estimation, including boundary conditions, population closure, choice of link function, and extrapolation of predicted relationships to unsampled areas. We then compare a suite of novel and existing spatiotemporal hierarchical models for animal count data that permit animal density to vary over space and time, including formulations motivated by resource selection and allowing for closed populations. We gauge the relative performance (bias, precision, computational demands) of alternative spatiotemporal models when confronted with simulated and real data sets from dynamic animal populations. For the latter, we analyze spotted seal (Phoca largha) counts from an aerial survey of the Bering Sea where the quantity and quality of suitable habitat (sea ice) changed dramatically while surveys were being conducted. Simulation analyses suggested that multiple types of spatiotemporal models provide reasonable inference (low positive bias, high precision) about animal abundance, but have potential for overestimating precision. Analysis of spotted seal data indicated that several model formulations, including those based on a log-Gaussian Cox process, had a tendency to overestimate abundance. By contrast, a model that included a population closure assumption and a scale prior on total

  5. Estimating Animal Abundance in Ground Beef Batches Assayed with Molecular Markers

    PubMed Central

    Hu, Xin-Sheng; Simila, Janika; Platz, Sindey Schueler; Moore, Stephen S.; Plastow, Graham; Meghen, Ciaran N.

    2012-01-01

    Estimating animal abundance in industrial scale batches of ground meat is important for mapping meat products through the manufacturing process and for effectively tracing the finished product during a food safety recall. The processing of ground beef involves a potentially large number of animals from diverse sources in a single product batch, which produces a high heterogeneity in capture probability. In order to estimate animal abundance through DNA profiling of ground beef constituents, two parameter-based statistical models were developed for incidence data. Simulations were applied to evaluate the maximum likelihood estimate (MLE) of a joint likelihood function from multiple surveys, showing superiority in the presence of high capture heterogeneity with small sample sizes, or comparable estimation in the presence of low capture heterogeneity with a large sample size when compared to other existing models. Our model employs the full information on the pattern of the capture-recapture frequencies from multiple samples. We applied the proposed models to estimate animal abundance in six manufacturing beef batches, genotyped using 30 single nucleotide polymorphism (SNP) markers, from a large scale beef grinding facility. Results show that between 411∼1367 animals were present in six manufacturing beef batches. These estimates are informative as a reference for improving recall processes and tracing finished meat products back to source. PMID:22479559

  6. Estimation of potential maximum biomass of trout in Wyoming streams to assist management decisions

    USGS Publications Warehouse

    Hubert, W.A.; Marwitz, T.D.; Gerow, K.G.; Binns, N.A.; Wiley, R.W.

    1996-01-01

    Fishery managers can benefit from knowledge of the potential maximum biomass (PMB) of trout in streams when making decisions on the allocation of resources to improve fisheries. Resources are most likely to he expended on streams with high PMB and with large differences between PMB and currently measured biomass. We developed and tested a model that uses four easily measured habitat variables to estimate PMB (upper 90th percentile of predicted mean bid mass) of trout (Oncorhynchus spp., Salmo trutta, and Salvelinus fontinalis) in Wyoming streams. The habitat variables were proportion of cover, elevation, wetted width, and channel gradient. The PMB model was constructed from data on 166 stream reaches throughout Wyoming and validated on an independent data set of 50 stream reaches. Prediction of PMB in combination with estimation of current biomass and information on habitat quality can provide managers with insight into the extent to which management actions may enhance trout biomass.

  7. A method for subsampling terrestrial invertebrate samples in the laboratory: estimating abundance and taxa richness.

    PubMed

    Doğramaci, Mahmut; DeBano, Sandra J; Wooster, David E; Kimoto, Chiho

    2010-01-01

    Significant progress has been made in developing subsampling techniques to process large samples of aquatic invertebrates. However, limited information is available regarding subsampling techniques for terrestrial invertebrate samples. Therefore a novel subsampling procedure was evaluated for processing samples of terrestrial invertebrates collected using two common field techniques: pitfall and pan traps. A three-phase sorting protocol was developed for estimating abundance and taxa richness of invertebrates. First, large invertebrates and plant material were removed from the sample using a sieve with a 4 mm mesh size. Second, the sample was poured into a specially designed, gridded sampling tray, and 16 cells, comprising 25% of the sampling tray, were randomly subsampled and processed. Third, the remainder of the sample was scanned for 4-7 min to record rare taxa missed in the second phase. To compare estimated abundance and taxa richness with the true values of these variables for the samples, the remainder of each sample was processed completely. The results were analyzed relative to three sample size categories: samples with less than 250 invertebrates (low abundance samples), samples with 250-500 invertebrates (moderate abundance samples), and samples with more than 500 invertebrates (high abundance samples). The number of invertebrates estimated after subsampling eight or more cells was highly precise for all sizes and types of samples. High accuracy for moderate and high abundance samples was achieved after even as few as six subsamples. However, estimates of the number of invertebrates for low abundance samples were less reliable. The subsampling technique also adequately estimated taxa richness; on average, subsampling detected 89% of taxa found in samples. Thus, the subsampling technique provided accurate data on both the abundance and taxa richness of terrestrial invertebrate samples. Importantly, subsampling greatly decreased the time required to

  8. Estimating aboveground biomass of broadleaved woody plants in the understory of Florida Keys pine forests

    USGS Publications Warehouse

    Sah, J.P.; Ross, M.S.; Koptur, S.; Snyder, J.R.

    2004-01-01

    Species-specific allometric equations that provide estimates of biomass from measured plant attributes are currently unavailable for shrubs common to South Florida pine rocklands, where fire plays an important part in shaping the structure and function of ecosystems. We developed equations to estimate total aboveground biomass and fine fuel of 10 common hardwood species in the shrub layer of pine forests of the lower Florida Keys. Many equations that related biomass categories to crown area and height were significant (p < 0.05), but the form and variables comprising the best model varied among species. We applied the best-fit regression models to structural information from the shrub stratum in 18 plots on Big Pine Key, the most extensive pine forest in the Keys. Estimates based on species-specific equations indicated clearly that total aboveground shrub biomass and shrub fine fuel increased with time since last fire, but the relationships were non-linear. The relative proportion of biomass constituted by the major species also varied with stand age. Estimates based on mixed-species regressions differed slightly from estimates based on species-specific models, but the former could provide useful approximations in similar forests where species-specific regressions are not yet available. ?? 2004 Elsevier B.V. All rights reserved.

  9. Efficacy of generic allometric equations for estimating biomass: a test in Japanese natural forests.

    PubMed

    Ishihara, Masae I; Utsugi, Hajime; Tanouchi, Hiroyuki; Aiba, Masahiro; Kurokawa, Hiroko; Onoda, Yusuke; Nagano, Masahiro; Umehara, Toru; Ando, Makoto; Miyata, Rie; Hiura, Tsutom

    2015-07-01

    Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved

  10. Belowground Biomass Sampling to Estimate Fine Root Mass across NEON Sites

    NASA Astrophysics Data System (ADS)

    Spencer, J. J.; Meier, C. L.; Abercrombie, H.; Everhart, J. C.

    2013-12-01

    Production of belowground biomass is an important and relatively uncharacterized component of the net primary productivity (NPP) of ecosystems. Fine root productivity makes up a significant portion of total belowground production because fine roots turn over rapidly, and therefore contribute disproportionately to annual estimates of belowground net primary productivity (BNPP). One of the major goals of the National Ecological Observatory Network (NEON) is to quantify above- and below-ground NPP at 60 sites within 20 different eco-climactic regions. NEON's Terrestrial Observation System will carry out belowground biomass sampling throughout the life of the observatory to estimate fine root production. However, belowground biomass sampling during NEON operations will be constrained to a maximum depth of 50cm. This limited depth range leaves the question of what proportion of total fine root mass is being collected and how to optimally characterize belowground biomass given sampling depth limitations. During the construction period, NEON is characterizing fine root biomass distribution at depth down to 2m at each site, as well as physical and chemical properties in each soil horizon. Each sampling unit is a pit (2m deep and approximately 1.5m wide), dug in the site's dominant vegetation type where fine root biomass sampling will also occur during Operations. To sample fine root biomass in each pit, soil samples of a known volume are taken from three vertical profiles down the face of the pit. Samples are then wet sieved to extract fine root mass, and roots are dried at 65°C for 48 hours and then weighed. The soil pit data are used to estimate the proportion of total fine root biomass from each site as a function of depth. Non-linear curves are fitted to the data to calculate total fine root mass at depth and to provide estimates of the proportion of the total fine root mass that is sampled at each site during NEON's 30 year operational sampling. The belowground

  11. Estimating Abundances of Interacting Species Using Morphological Traits, Foraging Guilds, and Habitat

    PubMed Central

    Dorazio, Robert M.; Connor, Edward F.

    2014-01-01

    We developed a statistical model to estimate the abundances of potentially interacting species encountered while conducting point-count surveys at a set of ecologically relevant locations – as in a metacommunity of species. In the model we assume that abundances of species with similar traits (e.g., body size) are potentially correlated and that these correlations, when present, may exist among all species or only among functionally related species (such as members of the same foraging guild). We also assume that species-specific abundances vary among locations owing to systematic and stochastic sources of heterogeneity. For example, if abundances differ among locations due to differences in habitat, then measures of habitat may be included in the model as covariates. Naturally, the quantitative effects of these covariates are assumed to differ among species. Our model also accounts for the effects of detectability on the observed counts of each species. This aspect of the model is especially important for rare or uncommon species that may be difficult to detect in community-level surveys. Estimating the detectability of each species requires sampling locations to be surveyed repeatedly using different observers or different visits of a single observer. As an illustration, we fitted models to species-specific counts of birds obtained while sampling an avian community during the breeding season. In the analysis we examined whether species abundances appeared to be correlated due to similarities in morphological measures (body mass, beak length, tarsus length, wing length, tail length) and whether these correlations existed among all species or only among species of the same foraging guild. We also used the model to estimate the effects of forested area on species abundances and the effects of sound power output (as measured by body size) on species detection probabilities. PMID:24727898

  12. Estimating abundances of interacting species using morphological traits, foraging guilds, and habitat

    USGS Publications Warehouse

    Dorazio, Robert M.; Connor, Edward F.

    2014-01-01

    We developed a statistical model to estimate the abundances of potentially interacting species encountered while conducting point-count surveys at a set of ecologically relevant locations - as in a metacommunity of species. In the model we assume that abundances of species with similar traits (e.g., body size) are potentially correlated and that these correlations, when present, may exist among all species or only among functionally related species (such as members of the same foraging guild). We also assume that species-specific abundances vary among locations owing to systematic and stochastic sources of heterogeneity. For example, if abundances differ among locations due to differences in habitat, then measures of habitat may be included in the model as covariates. Naturally, the quantitative effects of these covariates are assumed to differ among species. Our model also accounts for the effects of detectability on the observed counts of each species. This aspect of the model is especially important for rare or uncommon species that may be difficult to detect in community-level surveys. Estimating the detectability of each species requires sampling locations to be surveyed repeatedly using different observers or different visits of a single observer. As an illustration, we fitted models to species-specific counts of birds obtained while sampling an avian community during the breeding season. In the analysis we examined whether species abundances appeared to be correlated due to similarities in morphological measures (body mass, beak length, tarsus length, wing length, tail length) and whether these correlations existed among all species or only among species of the same foraging guild. We also used the model to estimate the effects of forested area on species abundances and the effects of sound power output (as measured by body size) on species detection probabilities.

  13. Development of a Model for Estimation of Acacia Senegal Tree Biomass Using Allometry and Aster Satellite Imagery at Ennuhud, West Kordofan State, Sudan

    NASA Astrophysics Data System (ADS)

    Elamin, Hatim; Elnour Adam, Hassan; Csaplovics, Elmar

    The current paper deals with the development of a biomass model for Acacia senegal trees by applying allometric equations for ground data combined with ASTER satellite data sets. The current study is conducted around Ennuhud area which is located in Ennuhud locality in West Kordofan State, Sudan. Primary data are obtained by application of random sampling around Ennuhud town where Acacia senegal tree species is abundant. Ten sample units are taken. Each unit contains five sample plots (15x15 m), one in the centre and the others in the four directions 100 m away from the centre forming a total of 50 sample plots. The tree coordinates, diameter/diameters (diameter at breast height ≥ 5 cm), height and crown diameters will be recorded. Sensor data were acquired from ASTER remote sensing satellite (29.03.2007 & 26.01.2011) and integrated with the in-situ data. The expected findings allow for the calculation of the mean diameter of trees. The tree above ground biomass (TAGB), tree below ground biomass (TBGB) and the tree total biomass (TTB) of Acacia senegal are computed consequently. Remotely sensed data are integrated with the ground data for creating the data base for calculating the correlation of the relationship between the two methods of data collection. The application of allometric equations is useful as a non-destructive method for biomass estimation by the application of remote sensing is recommended for biomass modelling over large areas. Keywords: Biomass model, Acacia senegal tree, remote sensing, Ennuhud, North Kordofan

  14. Abundance of {sup 14}C in biomass fractions of wastes and solid recovered fuels

    SciTech Connect

    Fellner, Johann Rechberger, Helmut

    2009-05-15

    In recent years thermal utilization of mixed wastes and solid recovered fuels has become of increasing importance in European waste management. Since wastes or solid recovered fuels are generally composed of fossil and biogenic materials, only part of the CO{sub 2} emissions is accounted for in greenhouse gas inventories or emission trading schemes. A promising approach for determining this fraction is the so-called radiocarbon method. It is based on different ratios of the carbon isotopes {sup 14}C and {sup 12}C in fossil and biogenic fuels. Fossil fuels have zero radiocarbon, whereas biogenic materials are enriched in {sup 14}C and reflect the {sup 14}CO{sub 2} abundance of the ambient atmosphere. Due to nuclear weapons tests in the past century, the radiocarbon content in the atmosphere has not been constant, which has resulted in a varying {sup 14}C content of biogenic matter, depending on the period of growth. In the present paper {sup 14}C contents of different biogenic waste fractions (e.g., kitchen waste, paper, wood), as well as mixtures of different wastes (household, bulky waste, and commercial waste), and solid recovered fuels are determined. The calculated {sup 14}C content of the materials investigated ranges between 98 and 135 pMC.

  15. Abundance of (14)C in biomass fractions of wastes and solid recovered fuels.

    PubMed

    Fellner, Johann; Rechberger, Helmut

    2009-05-01

    In recent years thermal utilization of mixed wastes and solid recovered fuels has become of increasing importance in European waste management. Since wastes or solid recovered fuels are generally composed of fossil and biogenic materials, only part of the CO(2) emissions is accounted for in greenhouse gas inventories or emission trading schemes. A promising approach for determining this fraction is the so-called radiocarbon method. It is based on different ratios of the carbon isotopes (14)C and (12)C in fossil and biogenic fuels. Fossil fuels have zero radiocarbon, whereas biogenic materials are enriched in (14)C and reflect the (14)CO(2) abundance of the ambient atmosphere. Due to nuclear weapons tests in the past century, the radiocarbon content in the atmosphere has not been constant, which has resulted in a varying (14)C content of biogenic matter, depending on the period of growth. In the present paper (14)C contents of different biogenic waste fractions (e.g., kitchen waste, paper, wood), as well as mixtures of different wastes (household, bulky waste, and commercial waste), and solid recovered fuels are determined. The calculated (14)C content of the materials investigated ranges between 98 and 135pMC. PMID:19157836

  16. Appendix C: Biomass Program inputs for FY 2008 benefits estimates

    SciTech Connect

    None, None

    2009-01-18

    Document summarizes the results of the benefits analysis of EERE’s programs, as described in the FY 2008 Budget Request. EERE estimates benefits for its overall portfolio and nine Research, Development, Demonstration, and Deployment (RD3) programs.

  17. Finding a Fox: An Evaluation of Survey Methods to Estimate Abundance of a Small Desert Carnivore

    PubMed Central

    Dempsey, Steven J.; Gese, Eric M.; Kluever, Bryan M.

    2014-01-01

    The status of many carnivore species is a growing concern for wildlife agencies, conservation organizations, and the general public. Historically, kit foxes (Vulpes macrotis) were classified as abundant and distributed in the desert and semi-arid regions of southwestern North America, but is now considered rare throughout its range. Survey methods have been evaluated for kit foxes, but often in populations where abundance is high and there is little consensus on which technique is best to monitor abundance. We conducted a 2-year study to evaluate four survey methods (scat deposition surveys, scent station surveys, spotlight survey, and trapping) for detecting kit foxes and measuring fox abundance. We determined the probability of detection for each method, and examined the correlation between the relative abundance as estimated by each survey method and the known minimum kit fox abundance as determined by radio-collared animals. All surveys were conducted on 15 5-km transects during the 3 biological seasons of the kit fox. Scat deposition surveys had both the highest detection probabilities (p = 0.88) and were most closely related to minimum known fox abundance (r2 = 0.50, P = 0.001). The next best method for kit fox detection was the scent station survey (p = 0.73), which had the second highest correlation to fox abundance (r2 = 0.46, P<0.001). For detecting kit foxes in a low density population we suggest using scat deposition transects during the breeding season. Scat deposition surveys have low costs, resilience to weather, low labor requirements, and pose no risk to the study animals. The breeding season was ideal for monitoring kit fox population size, as detections consisted of the resident population and had the highest detection probabilities. Using appropriate monitoring techniques will be critical for future conservation actions for this rare desert carnivore. PMID:25148102

  18. Abundance estimation from multiple photo surveys: confidence distributions and reduced likelihoods for bowhead whales off Alaska.

    PubMed

    Schweder, Tore

    2003-12-01

    Maximum likelihood estimates of abundance are obtained from repeated photographic surveys of a closed stratified population with naturally marked and unmarked individuals. Capture intensities are assumed log-linear in stratum, year, and season. In the chosen model, an approximate confidence distribution for total abundance of bowhead whales, with an accompanying likelihood reduced of nuisance parameters, is found from a parametric bootstrap experiment. The confidence distribution depends on the assumed study protocol. A confidence distribution that is exact (except for the effect of discreteness) is found by conditioning in the unstratified case without unmarked individuals. PMID:14969476

  19. Mangrove Canopy Height and Biomass Estimations by means of Pol-InSAR Techniques

    NASA Astrophysics Data System (ADS)

    Lee, S. K.; Fatoyinbo, T. E.; Trettin, C.; Simard, M.; Bandeira, S.

    2014-12-01

    Mangrove forests cover only about 1% of the Earth's terrestrial surface, but they are amongst the highest carbon-storing and carbon-exporting ecosystems globally. Estimating 3-D mangrove forest parameters has been challenging due to the complex physical environment of the forests. In previous works, remote sensing techniques have proven an excellent tool for the estimation of mangrove forests. Recent experiments have successfully demonstrated the global scale estimation of mangrove structure using spaceborne remote sensing data: SRTM (InSAR), ICESat/GLAS (lidar), Landsat ETM+ (passive optical). However, those systems had relatively low spatial and temporal resolutions. Polarimetric SAR Interferometry (Pol-InSAR) is a Synthetic Aperture Radar (SAR) remote sensing technique based on the coherent combination of both Polarimetric and interferometric observables. The Pol-InSAR has provided a step forward in quantitative 3D forest structure parameter estimation (e.g. forest canopy height and biomass) over a variety of forests. Recent developments of Pol-InSAR technique with TanDEM-X (TDX) data in mangroves have proven that TDX data can be used to produce global-scale mangrove canopy height and biomass maps at accuracies comparable to airborne lidar measurements. In this study we propose to generate 12m-resolution mangrove canopy height and biomass estimates for the coastline of Mozambique using Pol-InSAR techniques from single-/dual-pol TDX data and validated with commercial airborne lidar. To cover all of the mangroves in the costal area of Mozambique, which is about 3000 km, about 200 TDX data sets are selected and processed. The TDX height data are calibrated with commercial airborne lidar data acquired over 150 km2 of mangroves in the Zambezi delta of Mozambique while height and Biomass estimates are validated using in-situ forest inventory measurements and biomass. The results from the study will be the first country-wide, wall-to-wall estimate of mangrove structure

  20. Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass--Sequence Relationships with an Innovative Metabarcoding Protocol.

    PubMed

    Elbrecht, Vasco; Leese, Florian

    2015-01-01

    Metabarcoding is an emerging genetic tool to rapidly assess biodiversity in ecosystems. It involves high-throughput sequencing of a standard gene from an environmental sample and comparison to a reference database. However, no consensus has emerged regarding laboratory pipelines to screen species diversity and infer species abundances from environmental samples. In particular, the effect of primer bias and the detection limit for specimens with a low biomass has not been systematically examined, when processing samples in bulk. We developed and tested a DNA metabarcoding protocol that utilises the standard cytochrome c oxidase subunit I (COI) barcoding fragment to detect freshwater macroinvertebrate taxa. DNA was extracted in bulk, amplified in a single PCR step, and purified, and the libraries were directly sequenced in two independent MiSeq runs (300-bp paired-end reads). Specifically, we assessed the influence of specimen biomass on sequence read abundance by sequencing 31 specimens of a stonefly species with known haplotypes spanning three orders of magnitude in biomass (experiment I). Then, we tested the recovery of 52 different freshwater invertebrate taxa of similar biomass using the same standard barcoding primers (experiment II). Each experiment was replicated ten times to maximise statistical power. The results of both experiments were consistent across replicates. We found a distinct positive correlation between species biomass and resulting numbers of MiSeq reads. Furthermore, we reliably recovered 83% of the 52 taxa used to test primer bias. However, sequence abundance varied by four orders of magnitudes between taxa despite the use of similar amounts of biomass. Our metabarcoding approach yielded reliable results for high-throughput assessments. However, the results indicated that primer efficiency is highly species-specific, which would prevent straightforward assessments of species abundance and biomass in a sample. Thus, PCR-based metabarcoding

  1. An evaluation of multipass electrofishing for estimating the abundance of stream-dwelling salmonids

    USGS Publications Warehouse

    Peterson, J.T.; Thurow, R.F.; Guzevich, J.W.

    2004-01-01

    Failure to estimate capture efficiency, defined as the probability of capturing individual fish, can introduce a systematic error or bias into estimates of fish abundance. We evaluated the efficacy of multipass electrofishing removal methods for estimating fish abundance by comparing estimates of capture efficiency from multipass removal estimates to capture efficiencies measured by the recapture of known numbers of marked individuals for bull trout Salvelinus confluentus and westslope cutthroat trout Oncorhynchus clarki lewisi. Electrofishing capture efficiency measured by the recapture of marked fish was greatest for westslope cutthroat trout and for the largest size-classes of both species. Capture efficiency measured by the recapture of marked fish also was low for the first electrofishing pass (mean, 28%) and decreased considerably (mean, 1.71 times lower) with successive passes, which suggested that fish were responding to the electrofishing procedures. On average, the removal methods overestimated three-pass capture efficiency by 39% and under-estimated fish abundance by 88%, across both species and all size-classes. The overestimates of efficiency were positively related to the cross-sectional area of the stream and the amount of undercut banks and negatively related to the number of removal passes for bull trout, whereas for westslope cutthroat trout, the overestimates were positively related to the amount of cobble substrate. Three-pass capture efficiency measured by the recapture of marked fish was related to the same stream habitat characteristics that influenced (biased) the removal estimates and did not appear to be influenced by our sampling procedures, including fish marking. Simulation modeling confirmed our field observations and indicated that underestimates of fish abundance by the removal method were negatively related to first-pass sampling efficiency and the magnitude of the decrease in capture efficiency with successive passes. Our results

  2. Natural Forest Biomass Estimation Based on Plantation Information Using PALSAR Data

    PubMed Central

    Avtar, Ram; Suzuki, Rikie; Sawada, Haruo

    2014-01-01

    Forests play a vital role in terrestrial carbon cycling; therefore, monitoring forest biomass at local to global scales has become a challenging issue in the context of climate change. In this study, we investigated the backscattering properties of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data in cashew and rubber plantation areas of Cambodia. The PALSAR backscattering coefficient (σ0) had different responses in the two plantation types because of differences in biophysical parameters. The PALSAR σ0 showed a higher correlation with field-based measurements and lower saturation in cashew plants compared with rubber plants. Multiple linear regression (MLR) models based on field-based biomass of cashew (C-MLR) and rubber (R-MLR) plants with PALSAR σ0 were created. These MLR models were used to estimate natural forest biomass in Cambodia. The cashew plant-based MLR model (C-MLR) produced better results than the rubber plant-based MLR model (R-MLR). The C-MLR-estimated natural forest biomass was validated using forest inventory data for natural forests in Cambodia. The validation results showed a strong correlation (R2 = 0.64) between C-MLR-estimated natural forest biomass and field-based biomass, with RMSE  = 23.2 Mg/ha in deciduous forests. In high-biomass regions, such as dense evergreen forests, this model had a weaker correlation because of the high biomass and the multiple-story tree structure of evergreen forests, which caused saturation of the PALSAR signal. PMID:24465908

  3. Quantifying the differences between Amazon forest biomass maps: uncertainty to be tackled in carbon emission estimates

    NASA Astrophysics Data System (ADS)

    Ometto, J.; Soler, L.; Assis, T.; Lapola, D.; Aguiar, A. P.; Meir, P.

    2012-12-01

    The current methods adopted to estimate the spatial variation on above- and below-ground biomass in tropical forests, in particular the Brazilian Amazon, are usually based on remote sensing and coupled with scarce and, generally poorly distributed fieldwork measurements. There are notable differences between the resulting published biomass maps and this results in high uncertainty in calculated carbon emissions from deforestation, forest degradation and other changes in the land cover. These uncertainties are particularly critical when biomass maps are coded into biomass classes referring to a specific range of values. The Brazilian Amazon is the largest continuous tropical broadleaf forest in the globe, containing a substantial amount of carbon above and below the soil surface. Analysis of land use change has shown that deforestation in the region is a patchy process, comprising different intensities and dynamics in separate and adjacent areas, such that even if when characterized by broad patterns estimates of carbon emissions can become a complicated task unless spatially accurate biomass maps are available. In this paper we analyze the differences in recently published biomass maps of the Amazon region, considering as well the official information used by the Brazilian government for its communication to the United Framework on Climate Change Convention of the United Nations. From the average biomass at deforestation areas in two different periods (1997 and 2006), maps varied from +20% to -19% in the first period and from +20% to -15% in the later, highlighting the substantial differences in the overall biomass estimate, with clear reflect on carbon emissions in the region.

  4. Estimating forest and woodland aboveground biomass using active and passive remote sensing

    USGS Publications Warehouse

    Wu, Zhuoting; Dye, Dennis G.; Vogel, John M.; Middleton, Barry R.

    2016-01-01

    Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1. Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States.

  5. Estimating parasitic sea lamprey abundance in Lake Huron from heterogenous data sources

    USGS Publications Warehouse

    Young, Robert J.; Jones, Michael L.; Bence, James R.; McDonald, Rodney B.; Mullett, Katherine M.; Bergstedt, Roger A.

    2003-01-01

    The Great Lakes Fishery Commission uses time series of transformer, parasitic, and spawning population estimates to evaluate the effectiveness of its sea lamprey (Petromyzon marinus) control program. This study used an inverse variance weighting method to integrate Lake Huron sea lamprey population estimates derived from two estimation procedures: 1) prediction of the lake-wide spawning population from a regression model based on stream size and, 2) whole-lake mark and recapture estimates. In addition, we used a re-sampling procedure to evaluate the effect of trading off sampling effort between the regression and mark-recapture models. Population estimates derived from the regression model ranged from 132,000 to 377,000 while mark-recapture estimates of marked recently metamorphosed juveniles and parasitic sea lampreys ranged from 536,000 to 634,000 and 484,000 to 1,608,000, respectively. The precision of the estimates varied greatly among estimation procedures and years. The integrated estimate of the mark-recapture and spawner regression procedures ranged from 252,000 to 702,000 transformers. The re-sampling procedure indicated that the regression model is more sensitive to reduction in sampling effort than the mark-recapture model. Reliance on either the regression or mark-recapture model alone could produce misleading estimates of abundance of sea lampreys and the effect of the control program on sea lamprey abundance. These analyses indicate that the precision of the lakewide population estimate can be maximized by re-allocating sampling effort from marking sea lampreys to trapping additional streams.

  6. A new device to estimate abundance of moist-soil plant seeds

    USGS Publications Warehouse

    Penny, E.J.; Kaminski, R.M.; Reinecke, K.J.

    2006-01-01

    Methods to sample the abundance of moist-soil seeds efficiently and accurately are critical for evaluating management practices and determining food availability. We adapted a portable, gasoline-powered vacuum to estimate abundance of seeds on the surface of a moist-soil wetland in east-central Mississippi and evaluated the sampler by simulating conditions that researchers and managers may experience when sampling moist-soil areas for seeds. We measured the percent recovery of known masses of seeds by the vacuum sampler in relation to 4 experimentally controlled factors (i.e., seed-size class, sample mass, soil moisture class, and vacuum time) with 2-4 levels per factor. We also measured processing time of samples in the laboratory. Across all experimental factors, seed recovery averaged 88.4% and varied little (CV = 0.68%, n = 474). Overall, mean time to process a sample was 30.3 ? 2.5 min (SE, n = 417). Our estimate of seed recovery rate (88%) may be used to adjust estimates for incomplete seed recovery, or project-specific correction factors may be developed by investigators. Our device was effective for estimating surface abundance of moist-soil plant seeds after dehiscence and before habitats were flooded.

  7. Use of near infrared/red radiance ratios for estimating vegetation biomass and physiological status

    NASA Technical Reports Server (NTRS)

    Tucker, C. J.

    1977-01-01

    The application of photographic infrared/red (ir/red) reflectance or radiance ratios for the estimation of vegetation biomass and physiological status were investigated by analyzing in situ spectral reflectance data from experimental grass plots. Canopy biological samples were taken for total wet biomass, total dry biomass, leaf water content, dry green biomass, dry brown biomass, and total chlorophyll content at each sampling date. Integrated red and photographic infrared radiances were regressed against the various canopy or plot variables to determine the relative significance between the red, photographic infrared, and the ir/red ratio and the canopy variables. The ir/red ratio is sensitive to the photosynthetically active or green biomass, the rate of primary production, and actually measures the interaction between the green biomass and the rate of primary production within a given species type. The ir/red ratio resulted in improved regression significance over the red or the ir/radiances taken separately. Only slight differences were found between ir/red ratio, the ir-red difference, the vegetation index, and the transformed vegetation index. The asymptotic spectral radiance properties of the ir, red, ir/red ratio, and the various transformations were evaluated.

  8. Estimation of biomass and canopy height in bermudagrass, alfalfa, and wheat using ultrasonic, laser, and spectral sensors.

    PubMed

    Pittman, Jeremy Joshua; Arnall, Daryl Brian; Interrante, Sindy M; Moffet, Corey A; Butler, Twain J

    2015-01-01

    Non-destructive biomass estimation of vegetation has been performed via remote sensing as well as physical measurements. An effective method for estimating biomass must have accuracy comparable to the accepted standard of destructive removal. Estimation or measurement of height is commonly employed to create a relationship between height and mass. This study examined several types of ground-based mobile sensing strategies for forage biomass estimation. Forage production experiments consisting of alfalfa (Medicago sativa L.), bermudagrass [Cynodon dactylon (L.) Pers.], and wheat (Triticum aestivum L.) were employed to examine sensor biomass estimation (laser, ultrasonic, and spectral) as compared to physical measurements (plate meter and meter stick) and the traditional harvest method (clipping). Predictive models were constructed via partial least squares regression and modeled estimates were compared to the physically measured biomass. Least significant difference separated mean estimates were examined to evaluate differences in the physical measurements and sensor estimates for canopy height and biomass. Differences between methods were minimal (average percent error of 11.2% for difference between predicted values versus machine and quadrat harvested biomass values (1.64 and 4.91 t·ha(-1), respectively), except at the lowest measured biomass (average percent error of 89% for harvester and quad harvested biomass < 0.79 t·ha(-1)) and greatest measured biomass (average percent error of 18% for harvester and quad harvested biomass >6.4 t·ha(-1)). These data suggest that using mobile sensor-based biomass estimation models could be an effective alternative to the traditional clipping method for rapid, accurate in-field biomass estimation. PMID:25635415

  9. Estimation of Biomass and Canopy Height in Bermudagrass, Alfalfa, and Wheat Using Ultrasonic, Laser, and Spectral Sensors

    PubMed Central

    Pittman, Jeremy Joshua; Arnall, Daryl Brian; Interrante, Sindy M.; Moffet, Corey A.; Butler, Twain J.

    2015-01-01

    Non-destructive biomass estimation of vegetation has been performed via remote sensing as well as physical measurements. An effective method for estimating biomass must have accuracy comparable to the accepted standard of destructive removal. Estimation or measurement of height is commonly employed to create a relationship between height and mass. This study examined several types of ground-based mobile sensing strategies for forage biomass estimation. Forage production experiments consisting of alfalfa (Medicago sativa L.), bermudagrass [Cynodon dactylon (L.) Pers.], and wheat (Triticum aestivum L.) were employed to examine sensor biomass estimation (laser, ultrasonic, and spectral) as compared to physical measurements (plate meter and meter stick) and the traditional harvest method (clipping). Predictive models were constructed via partial least squares regression and modeled estimates were compared to the physically measured biomass. Least significant difference separated mean estimates were examined to evaluate differences in the physical measurements and sensor estimates for canopy height and biomass. Differences between methods were minimal (average percent error of 11.2% for difference between predicted values versus machine and quadrat harvested biomass values (1.64 and 4.91 t·ha−1, respectively), except at the lowest measured biomass (average percent error of 89% for harvester and quad harvested biomass < 0.79 t·ha−1) and greatest measured biomass (average percent error of 18% for harvester and quad harvested biomass >6.4 t·ha−1). These data suggest that using mobile sensor-based biomass estimation models could be an effective alternative to the traditional clipping method for rapid, accurate in-field biomass estimation. PMID:25635415

  10. Estimation of sugarcane sucrose and biomass with remote sensing techniques

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing techniques were used to predict sucrose levels (TRS) and gross cane yield in field-grown sugarcane. To estimate sucrose levels, leaves were collected from plant-cane and first-ratoon sugarcane plants from the variety maturity studies conducted at the USDA-ARS-SRRC, Sugarcane Research...

  11. REGIONAL ESTIMATION OF CURRENT AND FUTURE FOREST BIOMASS. (R828785)

    EPA Science Inventory

    The 90,674 wildland fires that burned 2.9 million ha at an estimated suppression cost of $1.6 billion in the United States during the 2000 fire season demonstrated that forest fuel loading has become a hazard to life, property, and ecosystem health as a result of past fire exc...

  12. Range vegetation type mapping and above-ground green biomass estimations using multispectral imagery. [Wyoming

    NASA Technical Reports Server (NTRS)

    Houston, R. S. (Principal Investigator); Gordon, R. C.

    1974-01-01

    The author has identified the following significant results. Range vegetation types have been successfully mapped on a portion of the 68,000 acre study site located west of Baggs, Wyoming, using ERTS-1 imagery. These types have been ascertained from field transects over a five year period. Comparable studies will be made with EREP imagery. Above-ground biomass estimation studies are being conducted utilizing double sampling techniques on two similar study sites. Information obtained will be correlated with percent relative reflectance measurements obtained on the ground which will be related to image brightness levels. This will provide an estimate of above-ground green biomass with multispectral imagery.

  13. Estimating abundance and density of Amur tigers along the Sino-Russian border.

    PubMed

    Xiao, Wenhong; Feng, Limin; Mou, Pu; Miquelle, Dale G; Hebblewhite, Mark; Goldberg, Joshua F; Robinson, Hugh S; Zhao, Xiaodan; Zhou, Bo; Wang, Tianming; Ge, Jianping

    2016-07-01

    As an apex predator the Amur tiger (Panthera tigris altaica) could play a pivotal role in maintaining the integrity of forest ecosystems in Northeast Asia. Due to habitat loss and harvest over the past century, tigers rapidly declined in China and are now restricted to the Russian Far East and bordering habitat in nearby China. To facilitate restoration of the tiger in its historical range, reliable estimates of population size are essential to assess effectiveness of conservation interventions. Here we used camera trap data collected in Hunchun National Nature Reserve from April to June 2013 and 2014 to estimate tiger density and abundance using both maximum likelihood and Bayesian spatially explicit capture-recapture (SECR) methods. A minimum of 8 individuals were detected in both sample periods and the documentation of marking behavior and reproduction suggests the presence of a resident population. Using Bayesian SECR modeling within the 11 400 km(2) state space, density estimates were 0.33 and 0.40 individuals/100 km(2) in 2013 and 2014, respectively, corresponding to an estimated abundance of 38 and 45 animals for this transboundary Sino-Russian population. In a maximum likelihood framework, we estimated densities of 0.30 and 0.24 individuals/100 km(2) corresponding to abundances of 34 and 27, in 2013 and 2014, respectively. These density estimates are comparable to other published estimates for resident Amur tiger populations in the Russian Far East. This study reveals promising signs of tiger recovery in Northeast China, and demonstrates the importance of connectivity between the Russian and Chinese populations for recovering tigers in Northeast China. PMID:27136188

  14. Estimating abundance of the Southern Hudson Bay polar bear subpopulation using aerial surveys, 2011 and 2012

    USGS Publications Warehouse

    Obbard, Martyn E.; Middel, Kevin R.; Stapleton, Seth P.; Thibault, Isabelle; Brodeur, Vincent; Jutras, Charles

    2013-01-01

    The Southern Hudson Bay (SH) polar bear subpopulation occurs at the southern extent of the species’ range. Although capture-recapture studies indicate that abundance remained stable between 1986 and 2005, declines in body condition and survival were documented during the period, possibly foreshadowing a future decrease in abundance. To obtain a current estimate of abundance, we conducted a comprehensive line transect aerial survey of SH during 2011–2012. We stratified the study site by anticipated densities and flew coastal contour transects and systematically spaced inland transects in Ontario and on Akimiski Island and large offshore islands in 2011. Data were collected with double observer and distance sampling protocols. We also surveyed small islands in Hudson Bay and James Bay and flew a comprehensive transect along the Québec coastline in 2012. We observed 667 bears in Ontario and on Akimiski Island and nearby islands in 2011, and we sighted 80 bears on offshore islands during 2012. Mark-recapture distance sampling and sightresight models yielded a model-averaged estimate of 868 (SE: 177) for the 2011 study area. Our estimate of abundance for the entire SH subpopulation (951; SE: 177) suggests that abundance has remained unchanged. However, this result should be interpreted cautiously because of the methodological differences between historical studies (physical capture) and this survey. A conservative management approach is warranted given the previous increases in the duration of the ice-free season, which are predicted to continue in the future, and previously documented declines in body condition and vital rates.

  15. Estimating the abundance of the Southern Hudson Bay polar bear subpopulation with aerial surveys

    USGS Publications Warehouse

    Obbard, Martyn E.; Stapleton, Seth P.; Middel, Kevin R.; Thibault, Isabelle; Brodeur, Vincent; Jutras, Charles

    2015-01-01

    The Southern Hudson Bay (SH) polar bear subpopulation occurs at the southern extent of the species’ range. Although capture–recapture studies indicate abundance was likely unchanged between 1986 and 2005, declines in body condition and survival occurred during the period, possibly foreshadowing a future decrease in abundance. To obtain a current estimate of abundance, we conducted a comprehensive line transect aerial survey of SH during 2011–2012. We stratified the study site by anticipated densities and flew coastal contour transects and systematically spaced inland transects in Ontario and on Akimiski Island and large offshore islands in 2011. Data were collected with double-observer and distance sampling protocols. We surveyed small islands in James Bay and eastern Hudson Bay and flew a comprehensive transect along the Québec coastline in 2012. We observed 667 bears in Ontario and on Akimiski Island and nearby islands in 2011, and we sighted 80 bears on offshore islands during 2012. Mark–recapture distance sampling and sight–resight models yielded an estimate of 860 (SE = 174) for the 2011 study area. Our estimate of abundance for the entire SH subpopulation (943; SE = 174) suggests that abundance is unlikely to have changed significantly since 1986. However, this result should be interpreted cautiously because of the methodological differences between historical studies (physical capture–recapture) and this survey. A conservative management approach is warranted given previous increases in duration of the ice-free season, which are predicted to continue in the future, and previously documented declines in body condition and vital rates.

  16. [A spectral unmixing method of estimating main minerals abundance of lunar soils].

    PubMed

    Yan, Bo-Kun; Li, Jian-Zhong; Gan, Fu-Ping; Yang, Su-Ming; Wang, Run-Sheng

    2012-12-01

    Estimating minerals abundance from reflectance spectra is one of the fundamental goals of remote sensing lunar exploration, and the main difficulties are the complicated mixing law of minerals spectrum and spectral features being sensitive to several kinds of factors such as topography, particle size and roughness etc. A method based on spectral unmixing was put forward and tested in the present paper. Before spectra are unmixed the spectral continuum is removed for clarifying and strengthening spectral features. The absorption features and reflectance features (the upward curving parts of spectra between absorption features) are integrated for unmixing to improve the unmixing performance. The Hapke model was used to correct unmixing error due to nonlinear mixing of minerals spectra. Forty three mixed spectra of olivine, clinopyroxene, hypersthene and plagioclase were used to validate the above method. The four minerals abundance was estimated under the conditions of being unaware of endmember spectra used to mix, granularity and chemical composition of minerals. Residual error, abundance error and correlation coefficient between retrieved and true abundance were 5.0 Vol%, 14.4 Vol% and 0.92 respectively. The method and result of this paper could be referred in the lunar minerals mapping of imaging spectrometer data such as M3. PMID:23427563

  17. iReckon: simultaneous isoform discovery and abundance estimation from RNA-seq data.

    PubMed

    Mezlini, Aziz M; Smith, Eric J M; Fiume, Marc; Buske, Orion; Savich, Gleb L; Shah, Sohrab; Aparicio, Sam; Chiang, Derek Y; Goldenberg, Anna; Brudno, Michael

    2013-03-01

    High-throughput RNA sequencing (RNA-seq) promises to revolutionize our understanding of genes and their role in human disease by characterizing the RNA content of tissues and cells. The realization of this promise, however, is conditional on the development of effective computational methods for the identification and quantification of transcripts from incomplete and noisy data. In this article, we introduce iReckon, a method for simultaneous determination of the isoforms and estimation of their abundances. Our probabilistic approach incorporates multiple biological and technical phenomena, including novel isoforms, intron retention, unspliced pre-mRNA, PCR amplification biases, and multimapped reads. iReckon utilizes regularized expectation-maximization to accurately estimate the abundances of known and novel isoforms. Our results on simulated and real data demonstrate a superior ability to discover novel isoforms with a significantly reduced number of false-positive predictions, and our abundance accuracy prediction outmatches that of other state-of-the-art tools. Furthermore, we have applied iReckon to two cancer transcriptome data sets, a triple-negative breast cancer patient sample and the MCF7 breast cancer cell line, and show that iReckon is able to reconstruct the complex splicing changes that were not previously identified. QT-PCR validations of the isoforms detected in the MCF7 cell line confirmed all of iReckon's predictions and also showed strong agreement (r(2) = 0.94) with the predicted abundances. PMID:23204306

  18. iReckon: Simultaneous isoform discovery and abundance estimation from RNA-seq data

    PubMed Central

    Mezlini, Aziz M.; Smith, Eric J.M.; Fiume, Marc; Buske, Orion; Savich, Gleb L.; Shah, Sohrab; Aparicio, Sam; Chiang, Derek Y.; Goldenberg, Anna; Brudno, Michael

    2013-01-01

    High-throughput RNA sequencing (RNA-seq) promises to revolutionize our understanding of genes and their role in human disease by characterizing the RNA content of tissues and cells. The realization of this promise, however, is conditional on the development of effective computational methods for the identification and quantification of transcripts from incomplete and noisy data. In this article, we introduce iReckon, a method for simultaneous determination of the isoforms and estimation of their abundances. Our probabilistic approach incorporates multiple biological and technical phenomena, including novel isoforms, intron retention, unspliced pre-mRNA, PCR amplification biases, and multimapped reads. iReckon utilizes regularized expectation-maximization to accurately estimate the abundances of known and novel isoforms. Our results on simulated and real data demonstrate a superior ability to discover novel isoforms with a significantly reduced number of false-positive predictions, and our abundance accuracy prediction outmatches that of other state-of-the-art tools. Furthermore, we have applied iReckon to two cancer transcriptome data sets, a triple-negative breast cancer patient sample and the MCF7 breast cancer cell line, and show that iReckon is able to reconstruct the complex splicing changes that were not previously identified. QT-PCR validations of the isoforms detected in the MCF7 cell line confirmed all of iReckon's predictions and also showed strong agreement (r2 = 0.94) with the predicted abundances. PMID:23204306

  19. Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts

    USGS Publications Warehouse

    Dorazio, Robert M.; Martin, Juulien; Edwards, Holly H.

    2013-01-01

    The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

  20. Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts.

    PubMed

    Dorazio, Robert M; Martin, Julien; Edwards, Holly H

    2013-07-01

    The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability. PMID:23951707

  1. Tropical Africa: Land Use, Biomass, and Carbon Estimates for 1980 (NDP-055)

    SciTech Connect

    Brown, S.

    2002-04-16

    This document describes the contents of a digital database containing maximum potential aboveground biomass, land use, and estimated biomass and carbon data for 1980. The biomass data and carbon estimates are associated with woody vegetation in Tropical Africa. These data were collected to reduce the uncertainty associated with estimating historical releases of carbon from land use change. Tropical Africa is defined here as encompassing 22.7 x 10{sup 6} km{sup 2} of the earth's land surface and is comprised of countries that are located in tropical Africa (Angola, Botswana, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Congo, Benin, Equatorial Guinea, Ethiopia, Djibouti, Gabon, Gambia, Ghana, Guinea, Ivory Coast, Kenya, Liberia, Madagascar, Malawi, Mali, Mauritania, Mozambique, Namibia, Niger, Nigeria, Guinea-Bissau, Zimbabwe (Rhodesia), Rwanda, Senegal, Sierra Leone, Somalia, Sudan, Tanzania, Togo, Uganda, Burkina Faso (Upper Volta), Zaire, and Zambia). The database was developed using the GRID module in the ARC/INFO{trademark} geographic information system. Source data were obtained from the Food and Agriculture Organization (FAO), the U.S. National Geophysical Data Center, and a limited number of biomass-carbon density case studies. These data were used to derive the maximum potential and actual (ca. 1980) aboveground biomass values at regional and country levels. The land-use data provided were derived from a vegetation map originally produced for the FAO by the International Institute of Vegetation Mapping, Toulouse, France.

  2. Measuring bulrush culm relationships to estimate plant biomass within a southern California treatment wetland

    USGS Publications Warehouse

    Daniels, Joan S. (Thullen); Cade, Brian S.; Sartoris, James J.

    2010-01-01

    Assessment of emergent vegetation biomass can be time consuming and labor intensive. To establish a less onerous, yet accurate method, for determining emergent plant biomass than by direct measurements we collected vegetation data over a six-year period and modeled biomass using easily obtained variables: culm (stem) diameter, culm height and culm density. From 1998 through 2005, we collected emergent vegetation samples (Schoenoplectus californicus andSchoenoplectus acutus) at a constructed treatment wetland in San Jacinto, California during spring and fall. Various statistical models were run on the data to determine the strongest relationships. We found that the nonlinear relationship: CB=β0DHβ110ε, where CB was dry culm biomass (g m−2), DH was density of culms × average height of culms in a plot, and β0 and β1 were parameters to estimate, proved to be the best fit for predicting dried-live above-ground biomass of the two Schoenoplectus species. The random error distribution, ε, was either assumed to be normally distributed for mean regression estimates or assumed to be an unspecified continuous distribution for quantile regression estimates.

  3. Evaluation of the Environmental DNA Method for Estimating Distribution and Biomass of Submerged Aquatic Plants

    PubMed Central

    Matsuhashi, Saeko; Doi, Hideyuki; Fujiwara, Ayaka; Watanabe, Sonoko; Minamoto, Toshifumi

    2016-01-01

    The environmental DNA (eDNA) method has increasingly been recognized as a powerful tool for monitoring aquatic animal species; however, its application for monitoring aquatic plants is limited. To evaluate eDNA analysis for estimating the distribution of aquatic plants, we compared its estimated distributions with eDNA analysis, visual observation, and past distribution records for the submerged species Hydrilla verticillata. Moreover, we conducted aquarium experiments using H. verticillata and Egeria densa and analyzed the relationships between eDNA concentrations and plant biomass to investigate the potential for biomass estimation. The occurrences estimated by eDNA analysis closely corresponded to past distribution records, and eDNA detections were more frequent than visual observations, indicating that the method is potentially more sensitive. The results of the aquarium experiments showed a positive relationship between plant biomass and eDNA concentration; however, the relationship was not always significant. The eDNA concentration peaked within three days of the start of the experiment in most cases, suggesting that plants do not release constant amounts of DNA. These results showed that eDNA analysis can be used for distribution surveys, and has the potential to estimate the biomass of aquatic plants. PMID:27304876

  4. An improved radiative transfer model for estimating mineral abundance of immature and mature lunar soils

    NASA Astrophysics Data System (ADS)

    Liu, Dawei; Li, Lin; Sun, Ying

    2015-06-01

    An improved Hapke's radiative transfer model (RTM) is presented to estimate mineral abundance for both immature and mature lunar soils from the Lunar Soil Characterization Consortium (LSCC) dataset. Fundamental to this improved Hapke's model is the application of an alternative equation to describe the effects of larger size submicroscopic metallic iron (SMFe) (>50 nm) in the interior of agglutinitic glass that mainly darken the host material, contrasting to the darkening and reddening effects of smaller size SMFe (<50 nm) residing in the rims of mineral grains. Results from applying a nonlinear inversion procedure to the improved Hapke's RTM show that the average mass fraction of smaller and larger size SMFe in lunar soils was estimated to be 0.30% and 0.31% respectively, and the particle size distribution of soil samples is all within their measured range. Based on the derived mass fraction of SMFe and particle size of the soil samples, abundances of end-member components composing lunar soil samples were derived via minimizing the difference between measured and calculated spectra. The root mean square error (RMSE) between the fitted and measured spectra is lower than 0.01 for highland samples and 0.005 for mare samples. This improved Hapke's model accurately estimates abundances of agglutinitic glass (R-squared = 0.88), pyroxene (R-squared = 0.69) and plagioclase (R-squared = 0.95) for all 57 samples used in this study including both immature and mature lunar soils. However, the improved Hapke's RTM shows poor performance for quantifying abundances of olivine, ilmenite and volcanic glass. Improving the model performance for estimation of these three end-member components is the central focus for our future work.

  5. Biomass burning in Asia : annual and seasonal estimates and atmospheric emissions.

    SciTech Connect

    Streets, D. G.; Yarber, K. F.; Woo, J.-H.; Carmichael, G. R.; Decision and Information Sciences; Univ. of Iowa

    2003-10-15

    Estimates of biomass burning in Asia are developed to facilitate the modeling of Asian and global air quality. A survey of national, regional, and international publications on biomass burning is conducted to yield consensus estimates of 'typical' (i.e., non-year-specific) estimates of open burning (excluding biofuels). We conclude that 730 Tg of biomass are burned in a typical year from both anthropogenic and natural causes. Forest burning comprises 45% of the total, the burning of crop residues in the field comprises 34%, and 20% comes from the burning of grassland and savanna. China contributes 25% of the total, India 18%, Indonesia 13%, and Myanmar 8%. Regionally, forest burning in Southeast Asia dominates. National, annual totals are converted to daily and monthly estimates at 1{sup o} x 1{sup o} spatial resolution using distributions based on AVHRR fire counts for 1999--2000. Several adjustment schemes are applied to correct for the deficiencies of AVHRR data, including the use of moving averages, normalization, TOMS Aerosol Index, and masks for dust, clouds, landcover, and other fire sources. Good agreement between the national estimates of biomass burning and adjusted fire counts is obtained (R{sup 2} = 0.71--0.78). Biomass burning amounts are converted to atmospheric emissions, yielding the following estimates: 0.37 Tg of SO{sub 2}, 2.8 Tg of NO{sub x}, 1100 Tg of CO{sub 2}, 67 Tg of CO, 3.1 Tg of CH{sub 4}, 12 Tg of NMVOC, 0.45 Tg of BC, 3.3 Tg of OC, and 0.92 Tg of NH{sub 3}. Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of {+-}65% for CO{sub 2} emissions in Japan to a high of {+-}700% for BC emissions in India.

  6. Biomass burning in Asia: Annual and seasonal estimates and atmospheric emissions

    NASA Astrophysics Data System (ADS)

    Streets, D. G.; Yarber, K. F.; Woo, J.-H.; Carmichael, G. R.

    2003-12-01

    Estimates of biomass burning in Asia are developed to facilitate the modeling of Asian and global air quality. A survey of national, regional, and international publications on biomass burning is conducted to yield consensus estimates of "typical" (i.e., non-year-specific) estimates of open burning (excluding biofuels). We conclude that 730 Tg of biomass are burned in a typical year from both anthropogenic and natural causes. Forest burning comprises 45% of the total, the burning of crop residues in the field comprises 34%, and 20% comes from the burning of grassland and savanna. China contributes 25% of the total, India 18%, Indonesia 13%, and Myanmar 8%. Regionally, forest burning in Southeast Asia dominates. National, annual totals are converted to daily and monthly estimates at 1° × 1° spatial resolution using distributions based on AVHRR fire counts for 1999-2000. Several adjustment schemes are applied to correct for the deficiencies of AVHRR data, including the use of moving averages, normalization, TOMS Aerosol Index, and masks for dust, clouds, landcover, and other fire sources. Good agreement between the national estimates of biomass burning and adjusted fire counts is obtained (R2 = 0.71-0.78). Biomass burning amounts are converted to atmospheric emissions, yielding the following estimates: 0.37 Tg of SO2, 2.8 Tg of NOx, 1100 Tg of CO2, 67 Tg of CO, 3.1 Tg of CH4, 12 Tg of NMVOC, 0.45 Tg of BC, 3.3 Tg of OC, and 0.92 Tg of NH3. Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of ±65% for CO2 emissions in Japan to a high of ±700% for BC emissions in India.

  7. A double-observer approach for estimating detection probability and abundance from point counts

    USGS Publications Warehouse

    Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Fallon, F.W.; Fallon, J.E.; Heglund, P.J.

    2000-01-01

    Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

  8. Free-living plathelminthes in sheep-grazed and ungrazed supralittoral salt marshes of the North Sea: Abundance, biomass, and their significance in food chains

    NASA Astrophysics Data System (ADS)

    Armonies, W.

    The supralittoral salt marshes of the North Sea are marked by high halophyte primary productivity. The environmental factors are strongly fluctuating. Despite these features the metazoan meiofaunal abundance is equal to that found in other littoral habitats. On average 1250 marine metazoans are found per 10 cm 2 in ungrazed and 770 per 10 cm 2 in sheep-grazed supralittoral salt marshes. Nematoda dominate in numerical abundance, Oligochaeta in biomass. Plathelminthes account for 15% of marine metazoans in ungrazed and 5% in grazed salt marshes. Total plathelminth abundance increases with halophyte density, whereas the abundance of diatom-feeding Plathelminthes decreases. In ungrazed marshes on average 104 Plathelminthes are found per 10 cm 2, accounting for a biomass of 0.65 g DW·m -2. In sheep-grazed marshes the average abundance is only 32 individuals per 10 cm 2, accounting for a biomass of 0.1 g DW·m -2. Average individual weight is 3.2 μg DW or 2.5 μg AFDW. In grazed salt marshes, 30% of plathelminthes feed on diatoms, 66% are predators, and 4% feed on bacteria (gut analysis). In ungrazed salt marshes only 3% are diatom-feeders, and 90% are predators feeding on Nematoda, Copepoda, Oligochaeta, and smaller Plathelminthes. Presumably plathelminthes are top predators on the salt marsh meiofauna.

  9. Comparison of visual survey and seining methods for estimating abundance of an endangered, benthic stream fish

    USGS Publications Warehouse

    Jordan, F.; Jelks, H.L.; Bortone, S.A.; Dorazio, R.M.

    2008-01-01

    We compared visual survey and seining methods for estimating abundance of endangered Okaloosa darters, Etheostoma okaloosae, in 12 replicate stream reaches during August 2001. For each 20-m stream reach, two divers systematically located and marked the position of darters and then a second crew of three to five people came through with a small-mesh seine and exhaustively sampled the same area. Visual surveys required little extra time to complete. Visual counts (24.2 ?? 12.0; mean ?? one SD) considerably exceeded seine captures (7.4 ?? 4.8), and counts from the two methods were uncorrelated. Visual surveys, but not seines, detected the presence of Okaloosa darters at one site with low population densities. In 2003, we performed a depletion removal study in 10 replicate stream reaches to assess the accuracy of the visual survey method. Visual surveys detected 59% of Okaloosa darters present, and visual counts and removal estimates were positively correlated. Taken together, our comparisons indicate that visual surveys more accurately and precisely estimate abundance of Okaloosa darters than seining and more reliably detect presence at low population densities. We recommend evaluation of visual survey methods when designing programs to monitor abundance of benthic fishes in clear streams, especially for threatened and endangered species that may be sensitive to handling and habitat disturbance. ?? 2007 Springer Science+Business Media, Inc.

  10. Estimation of Biomass Carbon Stocks over Peat Swamp Forests using Multi-Temporal and Multi-Polratizations SAR Data

    NASA Astrophysics Data System (ADS)

    Wijaya, A.; Liesenberg, V.; Susanti, A.; Karyanto, O.; Verchot, L. V.

    2015-04-01

    The capability of L-band radar backscatter to penetrate through the forest canopy is useful for mapping the forest structure, including above ground biomass (AGB) estimation. Recent studies confirmed that the empirical AGB models generated from the L-band radar backscatter can provide favourable estimation results, especially if the data has dual-polarization configuration. Using dual polarimetry SAR data the backscatter signal is more sensitive to forest biomass and forest structure because of tree trunk scattering, thus showing better discriminations of different forest successional stages. These SAR approaches, however, need to be further studied for the application in tropical peatlands ecosystem We aims at estimating forest carbon stocks and stand biophysical properties using combination of multi-temporal and multi-polarizations (quad-polarimetric) L-band SAR data and focuses on tropical peat swamp forest over Kampar Peninsula at Riau Province, Sumatra, Indonesia which is one of the most peat abundant region in the country. Applying radar backscattering (Sigma nought) to model the biomass we found that co-polarizations (HH and VV) band are more sensitive than cross-polarization channels (HV and VH). Individual HH polarization channel from April 2010 explained > 86% of AGB. Whereas VV polarization showed strong correlation coefficients with LAI, tree height, tree diameter and basal area. Surprisingly, polarimetric anisotropy feature from April 2007 SAR data show relatively high correlations with almost all forest biophysical parameters. Polarimetric anisotropy, which explains the ratio between the second and the first dominant scattering mechanism from a target has reduced at some extent the randomness of scattering mechanism, thus improve the predictability of this particular feature in estimating the forest properties. These results may be influenced by local seasonal variations of the forest as well as moisture, but available quad-pol SAR data were unable to

  11. Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms. [Guyton, Oklahoma and Dalhart, Texas

    NASA Technical Reports Server (NTRS)

    Rosenthal, W. D.; Mcfarland, M. J.; Theis, S. W.; Jones, C. L. (Principal Investigator)

    1982-01-01

    Agricultural crop classification models using two or more spectral regions (visible through microwave) are considered in an effort to estimate biomass at Guymon, Oklahoma Dalhart, Texas. Both grounds truth and aerial data were used. Results indicate that inclusion of C, L, and P band active microwave data, from look angles greater than 35 deg from nadir, with visible and infrared data improve crop discrimination and biomass estimates compared to results using only visible and infrared data. The microwave frequencies were sensitive to different biomass levels. The K and C band were sensitive to differences at low biomass levels, while P band was sensitive to differences at high biomass levels. Two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass. It is implied that inclusion of active microwave sensors with visible and infrared sensors on future satellites could aid in crop discrimination and biomass estimation.

  12. Abundance estimation of long-diving animals using line transect methods.

    PubMed

    Okamura, Hiroshi; Minamikawa, Shingo; Skaug, Hans J; Kishiro, Toshiya

    2012-06-01

    Line transect sampling is one of the most widely used methods for estimating the size of wild animal populations. An assumption in standard line transect sampling is that all the animals on the trackline are detected without fail. This assumption tends to be violated for marine mammals with surfacing/diving behaviors. The detection probability on the trackline is estimated using duplicate sightings from double-platform line transect methods. The double-platform methods, however, are insufficient to estimate the abundance of long-diving animals because these animals can be completely missed while the observers pass. We developed a more flexible hazard probability model that incorporates information on surfacing/diving patterns obtained from telemetry data. The model is based on a stochastic point process and is statistically tractable. A simulation study showed that the new model provides near-unbiased abundance estimates, whereas the traditional hazard rate and hazard probability models produce considerably biased estimates. As an illustration, we applied the model to data on the Baird's beaked whale (Berardius bairdii) in the western North Pacific. PMID:21992225

  13. A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities

    USGS Publications Warehouse

    McClintock, B.T.; White, Gary C.; Burnham, K.P.

    2006-01-01

    This article introduces the beta-binomial estimator (BBE), a closed-population abundance mark-resight model combining the favorable qualities of maximum likelihood theory and the allowance of individual heterogeneity in sighting probability (p). The model may be parameterized for a robust sampling design consisting of multiple primary sampling occasions where closure need not be met between primary occasions. We applied the model to brown bear data from three study areas in Alaska and compared its performance to the joint hypergeometric estimator (JHE) and Bowden's estimator (BOWE). BBE estimates suggest heterogeneity levels were non-negligible and discourage the use of JHE for these data. Compared to JHE and BOWE, confidence intervals were considerably shorter for the AICc model-averaged BBE. To evaluate the properties of BBE relative to JHE and BOWE when sample sizes are small, simulations were performed with data from three primary occasions generated under both individual heterogeneity and temporal variation in p. All models remained consistent regardless of levels of variation in p. In terms of precision, the AICc model-averaged BBE showed advantages over JHE and BOWE when heterogeneity was present and mean sighting probabilities were similar between primary occasions. Based on the conditions examined, BBE is a reliable alternative to JHE or BOWE and provides a framework for further advances in mark-resight abundance estimation. ?? 2006 American Statistical Association and the International Biometric Society.

  14. Assessing small mammal abundance with track-tube indices and mark-recapture population estimates

    USGS Publications Warehouse

    Wiewel, A.S.; Clark, W.R.; Sovada, M.A.

    2007-01-01

    We compared track-tube sampling with mark-recapture livetrapping and evaluated a track-tube index, defined as the number of track tubes with identifiable small mammal tracks during a 4-night period, as a predictor of small mammal abundance estimates in North Dakota grasslands. Meadow voles (Microtus pennsylvanicus) were the most commonly recorded species by both methods, but were underrepresented in track-tube sampling, whereas 13-lined ground squirrels (Spermophilus tridecemlineatus) and Franklin's ground squirrels (S. franklinii) were overrepresented in track-tube sampling. Estimates of average species richness were lower from track tubes than from livetrapping. Regression models revealed that the track-tube index was at best a moderately good predictor of small mammal population estimates because both the form (linear versus curvilinear) and slope of the relationship varied between years. In addition, 95% prediction intervals indicated low precision when predicting population estimates from new track-tube index observations. Track tubes required less time and expense than mark-recapture and eliminated handling of small mammals. Using track tubes along with mark-recapture in a double sampling for regression framework would have potential value when attempting to estimate abundance of small mammals over large areas. ?? 2007 American Society of Mammalogists.

  15. Hankin and Reeves' Approach to Estimating Fish Abundance in Small Streams : Limitations and Potential Options.

    SciTech Connect

    Thompson, William L.

    2000-11-01

    Hankin and Reeves' (1988) approach to estimating fish abundance in small streams has been applied in stream-fish studies across North America. However, as with any method of population estimation, there are important assumptions that must be met for estimates to be minimally biased and reasonably precise. Consequently, I investigated effects of various levels of departure from these assumptions via simulation based on results from an example application in Hankin and Reeves (1988) and a spatially clustered population. Coverage of 95% confidence intervals averaged about 5% less than nominal when removal estimates equaled true numbers within sampling units, but averaged 62% - 86% less than nominal when they did not, with the exception where detection probabilities of individuals were >0.85 and constant across sampling units (95% confidence interval coverage = 90%). True total abundances averaged far (20% - 41%) below the lower confidence limit when not included within intervals, which implies large negative bias. Further, average coefficient of variation was about 1.5 times higher when removal estimates did not equal true numbers within sampling units (C{bar V} = 0.27 [SE = 0.0004]) than when they did (C{bar V} = 0.19 [SE = 0.0002]). A potential modification to Hankin and Reeves' approach is to include environmental covariates that affect detection rates of fish into the removal model or other mark-recapture model. A potential alternative is to use snorkeling in combination with line transect sampling to estimate fish densities. Regardless of the method of population estimation, a pilot study should be conducted to validate the enumeration method, which requires a known (or nearly so) population of fish to serve as a benchmark to evaluate bias and precision of population estimates.

  16. Estimating snow leopard population abundance using photography and capture-recapture techniques

    USGS Publications Warehouse

    Jackson, R.M.; Roe, J.D.; Wangchuk, R.; Hunter, D.O.

    2006-01-01

    Conservation and management of snow leopards (Uncia uncia) has largely relied on anecdotal evidence and presence-absence data due to their cryptic nature and the difficult terrain they inhabit. These methods generally lack the scientific rigor necessary to accurately estimate population size and monitor trends. We evaluated the use of photography in capture-mark-recapture (CMR) techniques for estimating snow leopard population abundance and density within Hemis National Park, Ladakh, India. We placed infrared camera traps along actively used travel paths, scent-sprayed rocks, and scrape sites within 16- to 30-km2 sampling grids in successive winters during January and March 2003-2004. We used head-on, oblique, and side-view camera configurations to obtain snow leopard photographs at varying body orientations. We calculated snow leopard abundance estimates using the program CAPTURE. We obtained a total of 66 and 49 snow leopard captures resulting in 8.91 and 5.63 individuals per 100 trap-nights during 2003 and 2004, respectively. We identified snow leopards based on the distinct pelage patterns located primarily on the forelimbs, flanks, and dorsal surface of the tail. Capture probabilities ranged from 0.33 to 0.67. Density estimates ranged from 8.49 (SE = 0.22; individuals per 100 km2 in 2003 to 4.45 (SE = 0.16) in 2004. We believe the density disparity between years is attributable to different trap density and placement rather than to an actual decline in population size. Our results suggest that photographic capture-mark-recapture sampling may be a useful tool for monitoring demographic patterns. However, we believe a larger sample size would be necessary for generating a statistically robust estimate of population density and abundance based on CMR models.

  17. Intercomparison of Near-Real-Time Biomass Burning Emissions Estimates Constrained by Satellite Fire Data

    EPA Science Inventory

    We compare biomass burning emissions estimates from four different techniques that use satellite based fire products to determine area burned over regional to global domains. Three of the techniques use active fire detections from polar-orbiting MODIS sensors and one uses detec...

  18. Evaluating analytical approaches for estimating pelagic fish biomass using simulated fish communities

    USGS Publications Warehouse

    Yule, Daniel L.; Adams, Jean V.; Warner, David M.; Hrabik, Thomas R.; Kocovsky, Patrick M.; Weidel, Brian C.; Rudstam, Lars G.; Sullivan, Patrick J.

    2013-01-01

    Pelagic fish assessments often combine large amounts of acoustic-based fish density data and limited midwater trawl information to estimate species-specific biomass density. We compared the accuracy of five apportionment methods for estimating pelagic fish biomass density using simulated communities with known fish numbers that mimic Lakes Superior, Michigan, and Ontario, representing a range of fish community complexities. Across all apportionment methods, the error in the estimated biomass generally declined with increasing effort, but methods that accounted for community composition changes with water column depth performed best. Correlations between trawl catch and the true species composition were highest when more fish were caught, highlighting the benefits of targeted trawling in locations of high fish density. Pelagic fish surveys should incorporate geographic and water column depth stratification in the survey design, use apportionment methods that account for species-specific depth differences, target midwater trawling effort in areas of high fish density, and include at least 15 midwater trawls. With relatively basic biological information, simulations of fish communities and sampling programs can optimize effort allocation and reduce error in biomass estimates.

  19. Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data

    USGS Publications Warehouse

    Dorazio, Robert M.

    2013-01-01

    In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar – and often identical – inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.

  20. Estimating biomass of submersed vegetation using a simple rake sampling technique

    USGS Publications Warehouse

    Kenow, K.P.; Lyon, J.E.; Hines, R.K.; Elfessi, A.

    2007-01-01

    We evaluated the use of a simple rake sampling technique for predicting the biomass of submersed aquatic vegetation. Vegetation sampled from impounded areas of the Mississippi River using a rake sampling technique, was compared with vegetation harvested from 0.33-m2 quadrats. The resulting data were used to model the relationship between rake indices and vegetation biomass (total and for individual species). We constructed linear regression models using log-transformed biomass data for sites sampled in 1999 and 2000. Data collected in 2001 were used to validate the resulting models. The coefficient of determination (R 2) for predicting total biomass was 0.82 and ranged from 0.59 (Potamogeton pectinatus) to 0.89 (Ceratophyllum demersum) for individual species. Application of the model to estimate total submersed aquatic vegetation is illustrated using data collected independent of this study. The accuracy and precision of the models tested indicate that the rake method data may be used to predict total vegetation biomass and biomass of selected species; however, the method should be tested in other regions, in other plant communities, and on other species. ?? 2006 Springer Science+Business Media B.V.

  1. Terrestrial laser scanning for plant height measurement and biomass estimation of maize

    NASA Astrophysics Data System (ADS)

    Tilly, N.; Hoffmeister, D.; Schiedung, H.; Hütt, C.; Brands, J.; Bareth, G.

    2014-09-01

    Over the last decades, the role of remote sensing gained in importance for monitoring applications in precision agriculture. A key factor for assessing the development of crops during the growing period is the actual biomass. As non-destructive methods of directly measuring biomass do not exist, parameters like plant height are considered as estimators. In this contribution, first results of multitemporal surveys on a maize field with a terrestrial laser scanner are shown. The achieved point clouds are interpolated to generate Crop Surface Models (CSM) that represent the top canopy. These CSMs are used for visualizing the spatial distribution of plant height differences within the field and calculating plant height above ground with a high resolution of 1 cm. In addition, manual measurements of plant height were carried out corresponding to each TLS campaign to verify the results. The high coefficient of determination (R² = 0.93) between both measurement methods shows the applicability of the presented approach. The established regression model between CSM-derived plant height and destructively measured biomass shows a varying performance depending on the considered time frame during the growing period. This study shows that TLS is a suitable and promising method for measuring plant height of maize. Moreover, it shows the potential of plant height as a non-destructive estimator for biomass in the early growing period. However, challenges are the non-linear development of plant height and biomass over the whole growing period.

  2. Estimating single-tree branch biomass of Norway spruce by airborne laser scanning

    NASA Astrophysics Data System (ADS)

    Hauglin, Marius; Dibdiakova, Janka; Gobakken, Terje; Næsset, Erik

    2013-05-01

    The use of forest biomass for bioenergy purposes, directly or through refinement processes, has increased in the last decade. One example of such use is the utilization of logging residues. Branch biomass constitutes typically a considerable part of the logging residues, and should be quantified and included in future forest inventories. Airborne laser scanning (ALS) is widely used when collecting data for forest inventories, and even methods to derive information at the single-tree level has been described. Procedures for estimation of single-tree branch biomass of Norway spruce using features derived from ALS data are proposed in the present study. As field reference data the dry weight branch biomass of 50 trees were obtained through destructive sampling. Variables were further derived from the ALS echoes from each tree, including crown volume calculated from an interpolated crown surface constructed with a radial basis function. Spatial information derived from the pulse vectors were also incorporated when calculating the crown volume. Regression models with branch biomass as response variable were fit to the data, and the prediction accuracy assessed through a cross-validation procedure. Random forest regression models were compared to stepwise and simple linear least squares models. In the present study branch biomass was estimated with a higher accuracy by the best ALS-based models than by existing allometric biomass equations based on field measurements. An improved prediction accuracy was observed when incorporating information from the laser pulse vectors into the calculation of the crown volume variable, and a linear model with the crown volume as a single predictor gave the best overall results with a root mean square error of 35% in the validation.

  3. Using endmembers in AVIRIS images to estimate changes in vegetative biomass

    NASA Technical Reports Server (NTRS)

    Smith, Milton O.; Adams, John B.; Ustin, Susan L.; Roberts, Dar A.

    1992-01-01

    Field techniques for estimating vegetative biomass are labor intensive, and rarely are used to monitor changes in biomass over time. Remote-sensing offers an attractive alternative to field measurements; however, because there is no simple correspondence between encoded radiance in multispectral images and biomass, it is not possible to measure vegetative biomass directly from AVIRIS images. Ways to estimate vegetative biomass by identifying community types and then applying biomass scalars derived from field measurements are investigated. Field measurements of community-scale vegetative biomass can be made, at least for local areas, but it is not always possible to identify vegetation communities unambiguously using remote measurements and conventional image-processing techniques. Furthermore, even when communities are well characterized in a single image, it typically is difficult to assess the extent and nature of changes in a time series of images, owing to uncertainties introduced by variations in illumination geometry, atmospheric attenuation, and instrumental responses. Our objective is to develop an improved method based on spectral mixture analysis to characterize and identify vegetative communities, that can be applied to multi-temporal AVIRIS and other types of images. In previous studies, multi-temporal data sets (AVIRIS and TM) of Owens Valley, CA were analyzed and vegetation communities were defined in terms of fractions of reference (laboratory and field) endmember spectra. An advantage of converting an image to fractions of reference endmembers is that, although fractions in a given pixel may vary from image to image in a time series, the endmembers themselves typically are constant, thus providing a consistent frame of reference.

  4. A framework for creating and validating a non-linear spectrum-biomass model to estimate the secondary succession biomass in moist tropical forests

    NASA Astrophysics Data System (ADS)

    Li, Hui; Mausel, Paul; Brondizio, Eduardo; Deardorff, David

    Uncertainties remain in the use of remote sensing technologies to provide validated model-derived estimates of the biomass of the secondary succession (SS) forests in the Amazon Basin. The objectives of this study were to develop a modeling framework for creating a valid spectrum-biomass model to estimate the SS biomass, to assess the utility of the framework and the accuracy and validity of the model, and to identify the model's determinants. Data sources for this study include 1992-1993 vegetation inventory data and 1991 Landsat Thematic Mapper (TM) data on the Altamira region of Para, Brazil, and 1994-1995 vegetation inventory data and 1994 Landsat TM data on the nearby Bragantina region. The allometric approach was used to estimate the biomass of the sampled sites based on the vegetation inventory data. A framework for the spectrum-biomass regression model was developed based on the estimated biomass of the sampled sites and the Landsat data. The framework includes (1) the pooling of data from Bragantina and the use of ANCOVA to justify this approach; (2) image calibration; (3) biomass data age-adjustment, (4) selection of independent variables, (5) regression model development, and (6) model assessment and validation. The cubic regression model with TM Band5-related predictors was found to best fit the data as evidenced by an adjusted R-squared value of 0.865, mean square error (MSE) of the model, and the analysis of residuals. Residual analysis showed that the model might yield a better estimation on a lower biomass values than on higher biomass values. In addition, further analyses identified several determinants that can impact the accuracy of the spectrum-biomass model. ANCOVA confirmed that the relationship between the biomass and the spectrum is independent of the Altamira and Bragantina regions, and that it was appropriate to pool sampled data from both regions in the proposed model. The model development methodology and the model produced from this

  5. Abundance-based similarity indices and their estimation when there are unseen species in samples.

    PubMed

    Chao, Anne; Chazdon, Robin L; Colwell, Robert K; Shen, Tsung-Jen

    2006-06-01

    A wide variety of similarity indices for comparing two assemblages based on species incidence (i.e., presence/absence) data have been proposed in the literature. These indices are generally based on three simple incidence counts: the number of species shared by two assemblages and the number of species unique to each of them. We provide a new probabilistic derivation for any incidence-based index that is symmetric (i.e., the index is not affected by the identity ordering of the two assemblages) and homogeneous (i.e., the index is unchanged if all counts are multiplied by a constant). The probabilistic approach is further extended to formulate abundance-based indices. Thus any symmetric and homogeneous incidence index can be easily modified to an abundance-type version. Applying the Laplace approximation formulas, we propose estimators that adjust for the effect of unseen shared species on our abundance-based indices. Simulation results show that the adjusted estimators significantly reduce the biases of the corresponding unadjusted ones when a substantial fraction of species is missing from samples. Data on successional vegetation in six tropical forests are used for illustration. Advantages and disadvantages of some commonly applied indices are briefly discussed. PMID:16918900

  6. A BIOMASS-BASED MODEL TO ESTIMATE THE PLAUSIBILITY OF EXOPLANET BIOSIGNATURE GASES

    SciTech Connect

    Seager, S.; Bains, W.; Hu, R.

    2013-10-01

    Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry and biological thermodynamics. The new framework is intended to liberate predictive atmosphere models from requiring fixed, Earth-like biosignature gas source fluxes. New biosignature gases can be considered with a check that the biomass estimate is physically plausible. We have validated the models on terrestrial production of NO, H{sub 2}S, CH{sub 4}, CH{sub 3}Cl, and DMS. We have applied the models to propose NH{sub 3} as a biosignature gas on a 'cold Haber World', a planet with a N{sub 2}-H{sub 2} atmosphere, and to demonstrate why gases such as CH{sub 3}Cl must have too large of a biomass to be a plausible biosignature gas on planets with Earth or early-Earth-like atmospheres orbiting a Sun-like star. To construct the biomass models, we developed a functional classification of biosignature gases, and found that gases (such as CH{sub 4}, H{sub 2}S, and N{sub 2}O) produced from life that extracts energy from chemical potential energy gradients will always have false positives because geochemistry has the same gases to work with as life does, and gases (such as DMS and CH{sub 3}Cl) produced for secondary metabolic reasons are far less likely to have false positives but because of their highly specialized origin are more likely to be produced in small quantities. The biomass model estimates are valid to one or two orders of magnitude; the goal is an independent approach to testing whether a biosignature gas is plausible rather than a precise quantification of atmospheric biosignature gases and their corresponding biomasses.

  7. A doubling of microphytobenthos biomass coincides with a tenfold increase in denitrifier and total bacterial abundances in intertidal sediments of a temperate estuary.

    PubMed

    Decleyre, Helen; Heylen, Kim; Sabbe, Koen; Tytgat, Bjorn; Deforce, Dieter; Van Nieuwerburgh, Filip; Van Colen, Carl; Willems, Anne

    2015-01-01

    Surface sediments are important systems for the removal of anthropogenically derived inorganic nitrogen in estuaries. They are often characterized by the presence of a microphytobenthos (MPB) biofilm, which can impact bacterial communities in underlying sediments for example by secretion of extracellular polymeric substances (EPS) and competition for nutrients (including nitrogen). Pyrosequencing and qPCR was performed on two intertidal surface sediments of the Westerschelde estuary characterized by a two-fold difference in MPB biomass but no difference in MPB composition. Doubling of MPB biomass was accompanied by a disproportionately (ten-fold) increase in total bacterial abundances while, unexpectedly, no difference in general community structure was observed, despite significantly lower bacterial richness and distinct community membership, mostly for non-abundant taxa. Denitrifier abundances corresponded likewise while community structure, both for nirS and nirK denitrifiers, remained unchanged, suggesting that competition with diatoms for nitrate is negligible at concentrations in the investigated sediments (appr. 1 mg/l NO3-). This study indicates that MPB biomass increase has a general, significantly positive effect on total bacterial and denitrifier abundances, with stimulation or inhibition of specific bacterial groups that however do not result in a re-structured community. PMID:25961719

  8. A Doubling of Microphytobenthos Biomass Coincides with a Tenfold Increase in Denitrifier and Total Bacterial Abundances in Intertidal Sediments of a Temperate Estuary

    PubMed Central

    Decleyre, Helen; Heylen, Kim; Sabbe, Koen; Tytgat, Bjorn; Deforce, Dieter; Van Nieuwerburgh, Filip; Van Colen, Carl; Willems, Anne

    2015-01-01

    Surface sediments are important systems for the removal of anthropogenically derived inorganic nitrogen in estuaries. They are often characterized by the presence of a microphytobenthos (MPB) biofilm, which can impact bacterial communities in underlying sediments for example by secretion of extracellular polymeric substances (EPS) and competition for nutrients (including nitrogen). Pyrosequencing and qPCR was performed on two intertidal surface sediments of the Westerschelde estuary characterized by a two-fold difference in MPB biomass but no difference in MPB composition. Doubling of MPB biomass was accompanied by a disproportionately (ten-fold) increase in total bacterial abundances while, unexpectedly, no difference in general community structure was observed, despite significantly lower bacterial richness and distinct community membership, mostly for non-abundant taxa. Denitrifier abundances corresponded likewise while community structure, both for nirS and nirK denitrifiers, remained unchanged, suggesting that competition with diatoms for nitrate is negligible at concentrations in the investigated sediments (appr. 1 mg/l NO3-). This study indicates that MPB biomass increase has a general, significantly positive effect on total bacterial and denitrifier abundances, with stimulation or inhibition of specific bacterial groups that however do not result in a re-structured community. PMID:25961719

  9. Aboveground Biomass Estimation in a Tidal Brackish Marsh Using Simulated Thematic Mapper Spectral Data

    NASA Technical Reports Server (NTRS)

    Hardisky, M.; Klemas, V.

    1984-01-01

    Spectral radiance data were collected from the ground and from a low altitude aircraft in an attempt to gain some insight into the potential utility of actual Thematic Mapper data for biomass estimation in wetland plant communities. No attempt was made to distinguish individual plant species within brackish marsh plant associations. Rather, it was decided to lump plant species with similar canopy morphologies and then estimate from spectral radiance data the biomass of the group. The rationale for such an approach is that plants with a similar morphology will produce a similar reflecting or absorping surface (i.e., canopy) for incoming electromagnetic radiation. Variations in observed reflectance from different plant communities with a similar canopy morphology are more likely to be a result of biomass differences than a result of differences in canopy architecture. If the hypothesis that plants with a similar morphology exhibit similar reflectance characteristics is true, then biomass can be estimated based on a model for the dominant plant morphology within a plant association and the need for species discrimination has effectively been eliminated.

  10. Abundance estimation of Ixodes ticks (Acari: Ixodidae) on roe deer (Capreolus capreolus)

    PubMed Central

    Lödige, Christina; Alings, Matthias; Vor, Torsten; Rühe, Ferdinand

    2010-01-01

    Despite the importance of roe deer as a host for Ixodes ticks in central Europe, estimates of total tick burden on roe deer are not available to date. We aimed at providing (1) estimates of life stage and sex specific (larvae, nymphs, males and females, hereafter referred to as tick life stages) total Ixodes burden and (2) equations which can be used to predict the total life stage burden by counting the life stage on a selected body area. Within a period of 1½ years, we conducted whole body counts of ticks from 80 hunter-killed roe deer originating from a beech dominated forest area in central Germany. Averaged over the entire study period (winter 2007–summer 2009), the mean tick burden per roe deer was 64.5 (SE ± 10.6). Nymphs were the most numerous tick life stage per roe deer (23.9 ± 3.2), followed by females (21.4 ± 3.5), larvae (10.8 ± 4.2) and males (8.4 ± 1.5). The individual tick burden was highly aggregated (k = 0.46); levels of aggregation were highest in larvae (k = 0.08), followed by males (k = 0.40), females (k = 0.49) and nymphs (k = 0.71). To predict total life stage specific burdens based on counts on selected body parts, we provide linear equations. For estimating larvae abundance on the entire roe deer, counts can be restricted to the front legs. Tick counts restricted to the head are sufficient to estimate total nymph burden and counts on the neck are appropriate for estimating adult ticks (females and males). In order to estimate the combined tick burden, tick counts on the head can be used for extrapolation. The presented linear models are highly significant and explain 84.1, 77.3, 90.5, 91.3, and 65.3% (adjusted R2) of the observed variance, respectively. Thus, these models offer a robust basis for rapid tick abundance assessment. This can be useful for studies aiming at estimating effects of abiotic and biotic factors on tick abundance, modelling tick population dynamics, modelling tick-borne pathogen

  11. ESTIMATION OF TROPICAL FOREST STRUCTURE AND BIOMASS FROM FUSION OF RADAR AND LIDAR MEASUREMENTS (Invited)

    NASA Astrophysics Data System (ADS)

    Saatchi, S. S.; Dubayah, R.; Clark, D. B.; Chazdon, R.

    2009-12-01

    Radar and Lidar instruments are active remote sensing sensors with the potential of measuring forest vertical and horizontal structure and the aboveground biomass (AGB). In this paper, we present the analysis of radar and lidar data acquired over the La Selva Biological Station in Costa Rica. Radar polarimetry at L-band (25 cm wavelength), P-band (70 cm wavelength) and interferometry at C-band (6 cm wavelength) and VV polarization were acquired by the NASA/JPL airborne synthetic aperture radar (AIRSAR) system. Lidar images were provided by a large footprint airborne scanning Lidar known as the Laser Vegetation Imaging Sensor (LVIS). By including field measurements of structure and biomass over a variety of forest types, we examined: 1) sensitivity of radar and lidar measurements to forest structure and biomass, 2) accuracy of individual sensors for AGB estimation, and 3) synergism of radar imaging measurements with lidar imaging and sampling measurements for improving the estimation of 3-dimensional forest structure and AGB. The results showed that P-band radar combined with any interformteric measurement of forest height can capture approximately 85% of the variation of biomass in La Selva at spatial scales larger than 1 hectare. Similar analysis at L-band frequency captured only 70% of the variation. However, combination of lidar and radar measurements improved estimates of forest three-dimensional structure and biomass to above 90% for all forest types. We present a novel data fusion approach based on a Baysian estimation model with the capability of incorporating lidar samples and radar imagery. The model was used to simulate the potential of data fusion in future satellite mission scenarios as in BIOMASS (planned by ESA) at P-band and DESDynl (planned by NASA) at L-band. The estimation model was also able to quantify errors and uncertainties associated with the scale of measurements, spatial variability of forest structure, and differences in radar and lidar

  12. RNA-Seq alignment to individualized genomes improves transcript abundance estimates in multiparent populations.

    PubMed

    Munger, Steven C; Raghupathy, Narayanan; Choi, Kwangbom; Simons, Allen K; Gatti, Daniel M; Hinerfeld, Douglas A; Svenson, Karen L; Keller, Mark P; Attie, Alan D; Hibbs, Matthew A; Graber, Joel H; Chesler, Elissa J; Churchill, Gary A

    2014-09-01

    Massively parallel RNA sequencing (RNA-seq) has yielded a wealth of new insights into transcriptional regulation. A first step in the analysis of RNA-seq data is the alignment of short sequence reads to a common reference genome or transcriptome. Genetic variants that distinguish individual genomes from the reference sequence can cause reads to be misaligned, resulting in biased estimates of transcript abundance. Fine-tuning of read alignment algorithms does not correct this problem. We have developed Seqnature software to construct individualized diploid genomes and transcriptomes for multiparent populations and have implemented a complete analysis pipeline that incorporates other existing software tools. We demonstrate in simulated and real data sets that alignment to individualized transcriptomes increases read mapping accuracy, improves estimation of transcript abundance, and enables the direct estimation of allele-specific expression. Moreover, when applied to expression QTL mapping we find that our individualized alignment strategy corrects false-positive linkage signals and unmasks hidden associations. We recommend the use of individualized diploid genomes over reference sequence alignment for all applications of high-throughput sequencing technology in genetically diverse populations. PMID:25236449

  13. Effects of prior detections on estimates of detection probability, abundance, and occupancy

    USGS Publications Warehouse

    Riddle, Jason D.; Mordecai, Rua S.; Pollock, Kenneth H.; Simons, Theodore R.

    2010-01-01

    Survey methods that account for detection probability often require repeated detections of individual birds or repeated visits to a site to conduct Counts or collect presence-absence data. Initial encounters with individual species or individuals of a species could influence detection probabilities for subsequent encounters. For example, observers may be more likely to redetect a species or individual once they are aware of the presence of that species or individual at a particular site. Not accounting for these effects could result in biased estimators of detection probability, abundance, and occupancy. We tested for effects of prior detections in three data sets that differed dramatically by species, geographic location, and method of counting birds. We found strong support (AIC weights from 83% to 100%) for models that allowed for the effects of prior detections. These models produced estimates of detection probability, abundance, and occupancy that differed substantially from those produced by models that ignored the effects of prior detections. We discuss the consequences of the effects of prior detections on estimation for several sampling methods and provide recommendations for avoiding these effects through survey design or by modeling them when they cannot be avoided. 

  14. Evaluating abundance estimate precision and the assumptions of a count-based index for small mammals

    USGS Publications Warehouse

    Wiewel, A.S.; Adams, A.A.Y.; Rodda, G.H.

    2009-01-01

    Conservation and management of small mammals requires reliable knowledge of population size. We investigated precision of markrecapture and removal abundance estimates generated from live-trapping and snap-trapping data collected at sites on Guam (n 7), Rota (n 4), Saipan (n 5), and Tinian (n 3), in the Mariana Islands. We also evaluated a common index, captures per unit effort (CPUE), as a predictor of abundance. In addition, we evaluated cost and time associated with implementing live-trapping and snap-trapping and compared species-specific capture rates of selected live- and snap-traps. For all species, markrecapture estimates were consistently more precise than removal estimates based on coefficients of variation and 95 confidence intervals. The predictive utility of CPUE was poor but improved with increasing sampling duration. Nonetheless, modeling of sampling data revealed that underlying assumptions critical to application of an index of abundance, such as constant capture probability across space, time, and individuals, were not met. Although snap-trapping was cheaper and faster than live-trapping, the time difference was negligible when site preparation time was considered. Rattus diardii spp. captures were greatest in Haguruma live-traps (Standard Trading Co., Honolulu, HI) and Victor snap-traps (Woodstream Corporation, Lititz, PA), whereas Suncus murinus and Mus musculus captures were greatest in Sherman live-traps (H. B. Sherman Traps, Inc., Tallahassee, FL) and Museum Special snap-traps (Woodstream Corporation). Although snap-trapping and CPUE may have utility after validation against more rigorous methods, validation should occur across the full range of study conditions. Resources required for this level of validation would likely be better allocated towards implementing rigorous and robust methods.

  15. Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.

    PubMed

    Riegel, Joseph B; Bernhardt, Emily; Swenson, Jennifer

    2013-01-01

    Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R(2) values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R(2) of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas. PMID:23840837

  16. Estimating Above-Ground Carbon Biomass in a Newly Restored Coastal Plain Wetland Using Remote Sensing

    PubMed Central

    Riegel, Joseph B.; Bernhardt, Emily; Swenson, Jennifer

    2013-01-01

    Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R2 values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R2 of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas. PMID:23840837

  17. Estimating spatial variation in Alberta forest biomass from a combination of forest inventory and remote sensing data

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Huang, S.; Hogg, E. H.; Lieffers, V.; Qin, Y.; He, F.

    2013-12-01

    Uncertainties in the estimation of tree biomass carbon storage across large areas pose challenges for the study of forest carbon cycling at regional and global scales. In this study, we attempted to estimate the present biomass carbon storage in Alberta, Canada, by taking advantage of a spatially explicit dataset derived from a combination of forest inventory data from 1968 plots and spaceborne light detection and ranging (LiDAR) canopy height data. Ten climatic variables together with elevation, were used for model development and assessment. Four approaches, including spatial interpolation, non-spatial and spatial regression models, and decision-tree based modelling with random forests algorithm (a machine-learning technique), were compared to find the "best" estimates. We found that the random forests approach provided the best accuracy for biomass estimates. Non-spatial and spatial regression models gave estimates similar to random forests, while spatial interpolation greatly overestimated the biomass storage. Using random forests, the total biomass stock in Alberta forests was estimated to be 3.11 × 109 Mg, with the average biomass density of 77.59 Mg ha-1. At the species level, three major tree species, lodgepole pine, trembling aspen and white spruce, stocked about 1.91 × 109 Mg biomass, accounting for 61% of total estimated biomass. Spatial distribution of biomass varied with natural regions, land cover types, and species. And the relative importance of predictor variables on determining biomass distribution varied with species. This study showed that the combination of ground-based inventory data, spaceborne LiDAR data, land cover classification, climatic and environmental variables was an efficient way to estimate the quantity, distribution and variation of forest biomass carbon stocks across large regions.

  18. Evaluation of methods to estimate lake herring spawner abundance in Lake Superior

    USGS Publications Warehouse

    Yule, D.L.; Stockwell, J.D.; Cholwek, G.A.; Evrard, L.M.; Schram, S.; Seider, M.; Symbal, M.

    2006-01-01

    Historically, commercial fishers harvested Lake Superior lake herring Coregonus artedi for their flesh, but recently operators have targeted lake herring for roe. Because no surveys have estimated spawning female abundance, direct estimates of fishing mortality are lacking. The primary objective of this study was to determine the feasibility of using acoustic techniques in combination with midwater trawling to estimate spawning female lake herring densities in a Lake Superior statistical grid (i.e., a 10′ latitude × 10′ longitude area over which annual commercial harvest statistics are compiled). Midwater trawling showed that mature female lake herring were largely pelagic during the night in late November, accounting for 94.5% of all fish caught exceeding 250 mm total length. When calculating acoustic estimates of mature female lake herring, we excluded backscattering from smaller pelagic fishes like immature lake herring and rainbow smelt Osmerus mordax by applying an empirically derived threshold of −35.6 dB. We estimated the average density of mature females in statistical grid 1409 at 13.3 fish/ha and the total number of spawning females at 227,600 (95% confidence interval = 172,500–282,700). Using information on mature female densities, size structure, and fecundity, we estimate that females deposited 3.027 billion (109) eggs in grid 1409 (95% confidence interval = 2.356–3.778 billion). The relative estimation error of the mature female density estimate derived using a geostatistical model—based approach was low (12.3%), suggesting that the employed method was robust. Fishing mortality rates of all mature females and their eggs were estimated at 2.3% and 3.8%, respectively. The techniques described for enumerating spawning female lake herring could be used to develop a more accurate stock–recruitment model for Lake Superior lake herring.

  19. Breeding chorus indices are weakly related to estimated abundance of boreal chorus frogs

    USGS Publications Warehouse

    Corn, P.S.; Muths, E.; Kissel, A.M.; Scherer, R. D.

    2011-01-01

    Call surveys used to monitor breeding choruses of anuran amphibians generate index values that are frequently used to represent the number of male frogs present, but few studies have quantified this relationship. We compared abundance of male Boreal Chorus Frogs (Pseudacris maculata), estimated using capture–recapture methods in two populations in Colorado, to call index values derived from automated recordings. Single index values, such as might result from large monitoring efforts, were unrelated to population size. A synthetic call saturation index (CSI), the daily proportion of the maximum possible sum of index values derived from multiple recordings, was greater in larger populations, but the relationship was not highly predictive.

  20. Horvitz-Thompson survey sample methods for estimating large-scale animal abundance

    USGS Publications Warehouse

    Samuel, M.D.; Garton, E.O.

    1994-01-01

    Large-scale surveys to estimate animal abundance can be useful for monitoring population status and trends, for measuring responses to management or environmental alterations, and for testing ecological hypotheses about abundance. However, large-scale surveys may be expensive and logistically complex. To ensure resources are not wasted on unattainable targets, the goals and uses of each survey should be specified carefully and alternative methods for addressing these objectives always should be considered. During survey design, the impoflance of each survey error component (spatial design, propofiion of detected animals, precision in detection) should be considered carefully to produce a complete statistically based survey. Failure to address these three survey components may produce population estimates that are inaccurate (biased low), have unrealistic precision (too precise) and do not satisfactorily meet the survey objectives. Optimum survey design requires trade-offs in these sources of error relative to the costs of sampling plots and detecting animals on plots, considerations that are specific to the spatial logistics and survey methods. The Horvitz-Thompson estimators provide a comprehensive framework for considering all three survey components during the design and analysis of large-scale wildlife surveys. Problems of spatial and temporal (especially survey to survey) heterogeneity in detection probabilities have received little consideration, but failure to account for heterogeneity produces biased population estimates. The goal of producing unbiased population estimates is in conflict with the increased variation from heterogeneous detection in the population estimate. One solution to this conflict is to use an MSE-based approach to achieve a balance between bias reduction and increased variation. Further research is needed to develop methods that address spatial heterogeneity in detection, evaluate the effects of temporal heterogeneity on survey

  1. Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia

    NASA Astrophysics Data System (ADS)

    Sousa, Adélia M. O.; Gonçalves, Ana Cristina; Mesquita, Paulo; Marques da Silva, José R.

    2015-03-01

    Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands.

  2. Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

    SciTech Connect

    Aziz, Ramy K.; Dwivedi, Bhakti; Akhter, Sajia; Breitbart, Mya; Edwards, Robert A.

    2015-05-08

    Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set of publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. By adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution.

  3. ELM: an Algorithm to Estimate the Alpha Abundance from Low-resolution Spectra

    NASA Astrophysics Data System (ADS)

    Bu, Yude; Zhao, Gang; Pan, Jingchang; Bharat Kumar, Yerra

    2016-01-01

    We have investigated a novel methodology using the extreme learning machine (ELM) algorithm to determine the α abundance of stars. Applying two methods based on the ELM algorithm—ELM+spectra and ELM+Lick indices—to the stellar spectra from the ELODIE database, we measured the α abundance with a precision better than 0.065 dex. By applying these two methods to the spectra with different signal-to-noise ratios (S/Ns) and different resolutions, we found that ELM+spectra is more robust against degraded resolution and ELM+Lick indices is more robust against variation in S/N. To further validate the performance of ELM, we applied ELM+spectra and ELM+Lick indices to SDSS spectra and estimated α abundances with a precision around 0.10 dex, which is comparable to the results given by the SEGUE Stellar Parameter Pipeline. We further applied ELM to the spectra of stars in Galactic globular clusters (M15, M13, M71) and open clusters (NGC 2420, M67, NGC 6791), and results show good agreement with previous studies (within 1σ). A comparison of the ELM with other widely used methods including support vector machine, Gaussian process regression, artificial neural networks, and linear least-squares regression shows that ELM is efficient with computational resources and more accurate than other methods.

  4. Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

    PubMed Central

    Aziz, Ramy K.; Dwivedi, Bhakti; Akhter, Sajia; Breitbart, Mya; Edwards, Robert A.

    2015-01-01

    Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set of publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. We propose adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution. PMID:26005436

  5. Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

    DOE PAGESBeta

    Aziz, Ramy K.; Dwivedi, Bhakti; Akhter, Sajia; Breitbart, Mya; Edwards, Robert A.

    2015-05-08

    Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set ofmore » publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. By adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution.« less

  6. Estimating stem volume and biomass of Pinus koraiensis using LiDAR data.

    PubMed

    Kwak, Doo-Ahn; Lee, Woo-Kyun; Cho, Hyun-Kook; Lee, Seung-Ho; Son, Yowhan; Kafatos, Menas; Kim, So-Ra

    2010-07-01

    The objective of this study was to estimate the stem volume and biomass of individual trees using the crown geometric volume (CGV), which was extracted from small-footprint light detection and ranging (LiDAR) data. Attempts were made to analyze the stem volume and biomass of Korean Pine stands (Pinus koraiensis Sieb. et Zucc.) for three classes of tree density: low (240 N/ha), medium (370 N/ha), and high (1,340 N/ha). To delineate individual trees, extended maxima transformation and watershed segmentation of image processing methods were applied, as in one of our previous studies. As the next step, the crown base height (CBH) of individual trees has to be determined; information for this was found in the LiDAR point cloud data using k-means clustering. The LiDAR-derived CGV and stem volume can be estimated on the basis of the proportional relationship between the CGV and stem volume. As a result, low tree-density plots had the best performance for LiDAR-derived CBH, CGV, and stem volume (R (2) = 0.67, 0.57, and 0.68, respectively) and accuracy was lowest for high tree-density plots (R (2) = 0.48, 0.36, and 0.44, respectively). In the case of medium tree-density plots accuracy was R (2) = 0.51, 0.52, and 0.62, respectively. The LiDAR-derived stem biomass can be predicted from the stem volume using the wood basic density of coniferous trees (0.48 g/cm(3)), and the LiDAR-derived above-ground biomass can then be estimated from the stem volume using the biomass conversion and expansion factors (BCEF, 1.29) proposed by the Korea Forest Research Institute (KFRI). PMID:20182905

  7. Estimation of Biomass and Carbon Stocks in Rubber Plantation Using Thaichote Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Charoenjit, Kitsanai; Zuddas, Pierpaolo; Allemand, Pascal

    2014-05-01

    This goal of study is to improve model for estimate biomass and carbon stocks of rubber plantation (clone RRIM 600) in sub-basin of mae num prasae, East Thailand with total area is 232 Km2. We mapped 2011 of the biomass and carbon stocks with the used of integrated Thaichote satellite imagery and field data. In order to tree girth prediction and tree density population, we applied the objected based image analysis (OBIA) which include image mining and modeling by linear multiple regression, then estimate biomass and carbon stocks in rubber plantation. The image mining includes spectral, vegetation, textural and mask information for modeling construction. We found an parameters of the Global Environmental Monitoring Index (GEMI) and texture of homogeneity, dissimilarity, contrast and variance were accepted relationship of tree girt prediction with R2 0.865. The total amount of biomass and carbon stocks in study area is 2,227 Kt and 991.5 KtC respectively. For summary of study area, the annual sequestered in 2011 is 121.3 tCO2 from the atmosphere and the rubber plantation at mature age stage (25 years) had highest capacity of sequestered at 33.53 tCO2 ha-1 yr-1.

  8. Estimating Biomass Burning Emissions for Carbon Cycle Science and Resource Monitoring & Management

    NASA Astrophysics Data System (ADS)

    French, N. H.; McKenzie, D.; Erickson, T. A.; McCarty, J. L.; Ottmar, R. D.; Kasischke, E. S.; Prichard, S. J.; Hoy, E.; Endsley, K.; Hamermesh, N. K.

    2012-12-01

    Biomass burning emissions, including emissions from wildland fire, agricultural and rangeland burning, and peatland fires, impact the atmosphere dramatically. Current tools to quantify emission sources are developing quickly in a response to the need by the modeling community to assess fire's role in the carbon cycle and the land management community to understand fire effects and impacts on air quality. In a project funded by NASA, our team has developed methods to spatially quantify wildland fire emissions for the contiguous United States (CONUS) and Alaska (AK) at regional scales. We have also developed a prototype web-based information system, the Wildland Fire Emissions Information System (WFEIS) to make emissions modeling tools and estimates for the CONUS and AK available to the user community. With new funding through two NASA programs, our team from MTRI, USFS, and UMd will be further developing WFEIS to provide biomass burning emissions estimates for the carbon cycle science community and for land and air quality managers, to improve the way emissions estimates are calculated for a variety of disciplines. In this poster, we review WFEIS as it currently operates and the plans to extend the current system for use by the carbon cycle science community (through the NASA Carbon Monitoring System Program) and resource management community (through the NASA Applications Program). Features to be enhanced include an improved accounting of biomass present in canopy fuels that are available for burning in a forest fire, addition of annually changing vegetation biomass/fuels used in computing fire emissions, and quantification of the errors present in the estimation methods in order to provide uncertainty of emissions estimates across CONUS and AK. Additionally, WFEIS emissions estimates will be compared with results obtained with the Global Fire Emissions Database (GFED), which operates at a global scale at a coarse spatial resolution, to help improve GFED estimates

  9. Isoform-level ribosome occupancy estimation guided by transcript abundance with Ribomap

    PubMed Central

    Wang, Hao; McManus, Joel; Kingsford, Carl

    2016-01-01

    Summary: Ribosome profiling is a recently developed high-throughput sequencing technique that captures approximately 30 bp long ribosome-protected mRNA fragments during translation. Because of alternative splicing and repetitive sequences, a ribosome-protected read may map to many places in the transcriptome, leading to discarded or arbitrary mappings when standard approaches are used. We present a technique and software that addresses this problem by assigning reads to potential origins proportional to estimated transcript abundance. This yields a more accurate estimate of ribosome profiles compared with a naïve mapping. Availability and implementation: Ribomap is available as open source at http://www.cs.cmu.edu/∼ckingsf/software/ribomap. Contact: carlk@cs.cmu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153676

  10. Estimating species - area relationships by modeling abundance and frequency subject to incomplete sampling.

    PubMed

    Yamaura, Yuichi; Connor, Edward F; Royle, J Andrew; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

    2016-07-01

    Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a

  11. Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

    USGS Publications Warehouse

    Yamaura, Yuichi; Connor, Edward F.; Royle, Andy; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

    2016-01-01

    Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied

  12. How should detection probability be incorporated into estimates of relative abundance?

    USGS Publications Warehouse

    MacKenzie, D.I.; Kendall, W.L.

    2002-01-01

    Determination of the relative abundance of two populations, separated by time or space, is of interest in many ecological situations. We focus on two estimators of relative abundance, which assume that the probability that an individual is detected at least once in the survey is either equal or unequal for the two populations. We present three methods for incorporating the collected information into our inference. The first method, proposed previously, is a traditional hypothesis test for evidence that detection probabilities are unequal. However, we feel that, a priori, it is more likely that detection probabilities are actually different; hence, the burden of proof should be shifted, requiring evidence that detection probabilities are practically equivalent. The second method we present, equivalence testing, is one approach to doing so. Third, we suggest that model averaging could be used by combining the two estimators according to derived model weights. These differing approaches are applied to a mark-recapture experiment on Nuttail's cottontail rabbit (Sylvilagus nuttallii) conducted in central Oregon during 1974 and 1975, which has been previously analyzed by other authors.

  13. Relationships between recapture rates from different gears for estimating walleye abundance in northern Wisconsin lakes

    USGS Publications Warehouse

    Rogers, M.W.; Hansen, M.J.; Beard, T.D., Jr.

    2005-01-01

    Maximizing sampling efficiency and reducing sampling costs are desirable goals for fisheries management agencies. Expensive and labor-intensive methods (such as mark-recapture) are commonly used to estimate the population abundance of walleye Sander vitreus, but more efficient methods may be available. We compared recapture rates from surveys and harvests to evaluate the efficiency of currently used recapture gears and the potential for using gears that require less effort. To evaluate the usefulness of walleye harvest as mark-recapture samples, we used errors-in-variables models to determine whether recapture rates differed between fyke-netting and spearing, electrofishing and spearing, and electrofishing and angling. We found no significant differences between fyke-netting and adult walleye electrofishing recapture rates or between spearing and adult walleye electrofishing recapture rates. In contrast, we found that recapture rates from angling and electrofishing differed significantly in lakes with and without minimum length limits. We concluded that the lack of significant differences between the slopes of some harvest and survey recapture rates may allow the use of harvest recapture rates to estimate walleye abundance, but the biases associated with each gear should be considered. We also concluded that more attention should be given to understanding the biases of recapture gears. ?? Copyright by the American Fisheries Society 2005.

  14. A regional estimate of convective transport of CO from biomass burning

    NASA Technical Reports Server (NTRS)

    Pickering, Kenneth E.; Scala, John R.; Thompson, Anne M.; Tao, Wei-Kuo; Simpson, Joanne

    1992-01-01

    A regional-scale estimate of the fraction of biomass burning emissions that are transported to the free troposphere by deep convection is presented. The focus is on CO and the study region is a part of Brazil that underwent intensive deforestation in the 1980s. The method of calculation is stepwise, scaling up from a prototype convective event, the dynamics of which are well-characterized, to the vertical mass flux of carbon monoxide over the region. Given uncertainties in CO emissions from biomass burning and the representativeness of the prototype event, it is estimated that 10-40 percent of CO emissions from the burning region may be rapidly transported to the free troposphere over the burning region. These relatively fresh emissions will produce O3 efficiently in the free troposphere where O3 has a longer lifetime than in the boundary layer.

  15. Lidar Estimation of Aboveground Biomass in a Tropical Coastal Forest of Gabon

    NASA Astrophysics Data System (ADS)

    Meyer, V.; Saatchi, S. S.; Poulsen, J.; Clark, C.; Lewis, S.; White, L.

    2012-12-01

    Estimation of tropical forest carbon stocks is a critical yet challenging problem from both ground surveys and remote sensing measurements. However, with its increasing importance in global climate mitigation and carbon cycle assessment, there is a need to develop new techniques to measure forest carbon stocks at landscape scales. Progresses have been made in terms of above ground biomass (AGB) monitoring techniques using ground measurements, with the development of tree allometry techniques. Besides, studies have shown that new remote sensing technologies such as Lidar can give accurate information on tree height and forest structure at a landscape level and can be very useful to estimate AGB. This study examines the ability of small footprint Lidar to estimate above ground biomass in Mondah forest, Gabon. Mondah forest is a coastal tropical forest that is partially flooded and includes areas of mangrove. Its mean annual temperature is 18.8C and mean annual precipitation is 2631mm/yr. Its proximity to the capital of Gabon, Libreville, makes it particularly subject to environmental pressure. The analysis is based on small footprint Lidar waveform information and relative height (RH) metrics that correspond to the percentiles of energy of the signal (25%, 50%, 75% and 100%). AGB estimation is calibrated with ground measurements. Ground-estimated AGB is calculated using allometric equations based on tree diameter, wood density and tree height. Lidar-derived AGB is calculated using a linear regression model between the four Lidar RH metrics and ground-estimated AGB and using available models developed in other tropical regions that use one height metric, average wood density, and tree stocking number. We present uncertainty of different approaches and discuss the universality of lidar biomass estimation models in tropical forests.

  16. North Sea Scyphomedusae; summer distribution, estimated biomass and significance particularly for 0-group Gadoid fish

    NASA Astrophysics Data System (ADS)

    Hay, S. J.; Hislop, J. R. G.; Shanks, A. M.

    Data on the by-catch of Scyphomedusae from pelagic trawls was collected during the routine ICES International 0-group Gadoid Surveys of the North Sea, in June and July of the years 1971-1986 (except 1984). These data are used to describe the distributions, abundances and biomasses of three common North Sea Scyphomedusae: Aurelia aurita (L.), Cyanea capillata (L.) and C. lamarckii (Péron & Lesuer). Information is also presented on inter-annual variability, size (umbrella diameter) frequencies and, for the Cyanea species, umbrella diameter: wet weight relationships. The general role and ecological significance of Scyphomedusae is discussed and, given the well known 'shelter' relationships between Scyphomedusae and certain 0-group fish, whiting ( Merlangius merlangus) and haddock ( Melanogrammus aeglefinus), in particular. The data were examined for evidence of such relationships. Aurelia aurita, although fairly widespread in the northern North Sea was virtually absent from the central North Sea but very abundant in coastal waters. This species was particularly abundant off the Scottish east coast and especially in the Moray Firth. Cyanea lamerckii was most abundant in the southern and eastern North Sea. More widespread than Aurelia, this species was also most abundant in coastal regions, particularly off the Danish west coast. Cyanea capillata, with a more northern distribution was also more widely distributed and abundant offshore. This species was most abundant in the area between the Orkney/Shetland Isles and the Norwegian Deep and in shelf waters of the north west approaches to the North Sea. As with C. lamarckii it was also, in some years, abundant off the Scottish east coast and west of Denmark. The abundance and the size frequency of the jellyfish show considerable inter-annual variability, and variability between regions of the North Sea. It is considered that hydrographic variability and differences in food supply to both medusae and to their sessile

  17. Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

    NASA Technical Reports Server (NTRS)

    Nelson, Ross; Naesset, Erik; Gobakken, T.; Gregoire, T.; Stahl, G.

    2009-01-01

    A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

  18. Improved allometric models to estimate the aboveground biomass of tropical trees.

    PubMed

    Chave, Jérôme; Réjou-Méchain, Maxime; Búrquez, Alberto; Chidumayo, Emmanuel; Colgan, Matthew S; Delitti, Welington B C; Duque, Alvaro; Eid, Tron; Fearnside, Philip M; Goodman, Rosa C; Henry, Matieu; Martínez-Yrízar, Angelina; Mugasha, Wilson A; Muller-Landau, Helene C; Mencuccini, Maurizio; Nelson, Bruce W; Ngomanda, Alfred; Nogueira, Euler M; Ortiz-Malavassi, Edgar; Pélissier, Raphaël; Ploton, Pierre; Ryan, Casey M; Saldarriaga, Juan G; Vieilledent, Ghislain

    2014-10-01

    Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development. PMID:24817483

  19. Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation

    USGS Publications Warehouse

    Zipkin, Elise F.; Leirness, Jeffery B.; Kinlan, Brian P.; O'Connell, Allan F.; Silverman, Emily D.

    2014-01-01

    Determining appropriate statistical distributions for modeling animal count data is important for accurate estimation of abundance, distribution, and trends. In the case of sea ducks along the U.S. Atlantic coast, managers want to estimate local and regional abundance to detect and track population declines, to define areas of high and low use, and to predict the impact of future habitat change on populations. In this paper, we used a modified marked point process to model survey data that recorded flock sizes of Common eiders, Long-tailed ducks, and Black, Surf, and White-winged scoters. The data come from an experimental aerial survey, conducted by the United States Fish & Wildlife Service (USFWS) Division of Migratory Bird Management, during which east-west transects were flown along the Atlantic Coast from Maine to Florida during the winters of 2009–2011. To model the number of flocks per transect (the points), we compared the fit of four statistical distributions (zero-inflated Poisson, zero-inflated geometric, zero-inflated negative binomial and negative binomial) to data on the number of species-specific sea duck flocks that were recorded for each transect flown. To model the flock sizes (the marks), we compared the fit of flock size data for each species to seven statistical distributions: positive Poisson, positive negative binomial, positive geometric, logarithmic, discretized lognormal, zeta and Yule–Simon. Akaike’s Information Criterion and Vuong’s closeness tests indicated that the negative binomial and discretized lognormal were the best distributions for all species for the points and marks, respectively. These findings have important implications for estimating sea duck abundances as the discretized lognormal is a more skewed distribution than the Poisson and negative binomial, which are frequently used to model avian counts; the lognormal is also less heavy-tailed than the power law distributions (e.g., zeta and Yule–Simon), which are

  20. Reconciling LCROSS and Orbital Neutron Water Abundance Estimates in Cabeus Crater

    NASA Technical Reports Server (NTRS)

    Elphic, Richard; Teodoro, Luis F.; Eke, Vincent R.; Paige, David A.; Siegler, Matthew A.; Colaprete, Anthony

    2011-01-01

    The Lunar Prospector Neutron Spectrometer (LPNS) first revealed Cabeus crater (84.9 deg S, 35.5degW) as having the highest inferred hydrogen on the Moon. Because of the broad LPNS footprint (approximately 40 km FWHM), the apparent peak water-equivalent hydrogen (WEH) concentration is only approximately 0.25 wt%, but could be much higher in smaller areas than the spectrometer footprint. Earlier image reconstruction work suggested that areas within permanent shadow have abundances approximately 1 wt% WEH. However, the LCROSS impact yielded total water estimates, ice plus vapor, of between 3 and 10 wt%. The large disagreement between LCROSS and apparent orbital values imply that either the ice is buried, by perhaps as much as 50 to 100 cm; or the ice distribution within Cabeus is spatially inhomogeneous, or both. Modeling reveals that the areal extent of a "shallow permafrost zone" is far greater than the area of permanent shadow. Ice can be virtually stable for billions of years within a few tens of centimeters of the surface in these areas. However, the LCROSS impact took place in an area of permanent shadow. If stably-trapped volatiles can be found in locales that receive occasional, oblique sunlight, landed missions may target these sites and eventual resource exploitation may be done more easily. Are orbital neutron data consistent with areally-extensive, volatile-rich cold traps? Orbital epithermal neutron data over the northern half of Cabeus (near the LCROSS impact site) are consistent with 0.2 wt% WEH or less in the "permafrost zone" near the crater. On the other hand, pixon reconstructions that confine the hydrogen enhancements to permanent shadow result in higher abundance estimates -- around 1 wt% if homogeneously mixed. But if the PSR abundance is increased to 10 wt%, consistent with the sum of all H-bearing compounds seen by LCROSS, a much larger-than-observed reduction in neutron count rate would be seen from orbit. It is likely that volatiles are

  1. Evaluation of non-destructive methods for estimating biomass in marshes of the upper Texas, USA coast

    USGS Publications Warehouse

    Whitbeck, M.; Grace, J.B.

    2006-01-01

    The estimation of aboveground biomass is important in the management of natural resources. Direct measurements by clipping, drying, and weighing of herbaceous vegetation are time-consuming and costly. Therefore, non-destructive methods for efficiently and accurately estimating biomass are of interest. We compared two non-destructive methods, visual obstruction and light penetration, for estimating aboveground biomass in marshes of the upper Texas, USA coast. Visual obstruction was estimated using the Robel pole method, which primarily measures the density and height of the canopy. Light penetration through the canopy was measured using a Decagon light wand, with readings taken above the vegetation and at the ground surface. Clip plots were also taken to provide direct estimates of total aboveground biomass. Regression relationships between estimated and clipped biomass were significant using both methods. However, the light penetration method was much more strongly correlated with clipped biomass under these conditions (R2 value 0.65 compared to 0.35 for the visual obstruction approach). The primary difference between the two methods in this situation was the ability of the light-penetration method to account for variations in plant litter. These results indicate that light-penetration measurements may be better for estimating biomass in marshes when plant litter is an important component. We advise that, in all cases, investigators should calibrate their methods against clip plots to evaluate applicability to their situation. ?? 2006, The Society of Wetland Scientists.

  2. Estimation of biological nitrogen fixation by black locust in short-rotation forests using natural 15N abundance method

    NASA Astrophysics Data System (ADS)

    Veste, M.; Böhm, C.; Quinckenstein, A.; Freese, D.

    2012-04-01

    The importance of short rotation forests and agroforestry systems for woody biomass production for bioenergy will increase in Central Europe within the next decades. In this context, black locust (Robinia pseudoacacia) has a high growth potential especially at marginal, drought-susceptible sites such as occur in Brandenburg State (Eastern Germany). As a pioneer tree species black locust grows under a wide range of site conditions. The native range of black locust in Northern America is classified by a humid to sub-humid climate with a mean annual precipitation of 1020 to 1830 mm. In Central and Eastern Europe, this species is cultivated in a more continental climate with an annual precipitation often below 600 mm. Therefore, black locust is known to be relatively drought tolerant compared to other temperate, deciduous tree species. Because of its N2-fixation ability black locust plays generally an important role for the improvement of soil fertility. This effect is of particular interest at marginal sites in the post-mining landscapes. In order to estimate the N2-fixation potential of black locust at marginal sites leaf samples were taken from black locust trees in short rotation plantations planted between 1995 and 2007 in post-mining sites south of Cottbus (Brandenburg, NE Germany). The variation of the natural 15N abundance was measured to evaluate the biological nitrogen fixation. The nitrogen derived from the atmosphere can be calculated using a two-pool model from the quotient of the natural 15N abundances of the N2-fixing plant and the plant available soil N. Because representatively determining the plant available soil N is difficult, a non-N2-fixing reference plant growing at the same site with a similar root system and temporal N uptake pattern to the N2-fixing plant is often used. In our case we used red oak (Quercus rubra) as a reference. The average nitrogen content in the leaves of black locust ranged from 3.1% (C/N 14.8) in 15 years old trees to 3

  3. Enumeration and Biomass Estimation of Bacteria in Aquifer Microcosm Studies by Flow Cytometry

    PubMed Central

    DeLeo, P. C.; Baveye, P.

    1996-01-01

    Flow cytometry was used to enumerate and characterize bacteria from a sand column microcosm simulating aquifer conditions. Pure cultures of a species of Bacillus isolated from subsurface sediments or Bacillus megaterium were first evaluated to identify these organisms' characteristic histograms. Counting was then carried out with samples from the aquifer microcosms. Enumeration by flow cytometry was compared with more-traditional acridine orange direct counting. These two techniques gave statistically similar results. However, counting by flow cytometry, in this case, surveyed a sample size 700 times greater than did acridine orange direct counting (25 (mu)l versus 0.034 (mu)l) and required 1/10 the time (2 h versus 20 h). Flow cytometry was able to distinguish the same species of bacteria grown under different nutrient conditions, and it could distinguish changes in cell growth patterns, specifically single cell growth versus chained cell growth in different regions of an aquifer microcosm. A biomass estimate was calculated by calibrating the total fluorescence of a sample from a pure culture with the dry weight of a freeze-dried volume from the original pure culture. Growth conditions significantly affected histograms and biomass estimates, so the calibration was carried out with cells grown under conditions similar to those in the aquifer microcosm. Costs associated with using flow cytometry were minimal compared with the amount of time saved in counting cells and estimating biomass. PMID:16535470

  4. Matching the Best Viewing Angle in Depth Cameras for Biomass Estimation Based on Poplar Seedling Geometry

    PubMed Central

    Andújar, Dionisio; Fernández-Quintanilla, César; Dorado, José

    2015-01-01

    In energy crops for biomass production a proper plant structure is important to optimize wood yields. A precise crop characterization in early stages may contribute to the choice of proper cropping techniques. This study assesses the potential of the Microsoft Kinect for Windows v.1 sensor to determine the best viewing angle of the sensor to estimate the plant biomass based on poplar seedling geometry. Kinect Fusion algorithms were used to generate a 3D point cloud from the depth video stream. The sensor was mounted in different positions facing the tree in order to obtain depth (RGB-D) images from different angles. Individuals of two different ages, e.g., one month and one year old, were scanned. Four different viewing angles were compared: top view (0°), 45° downwards view, front view (90°) and ground upwards view (−45°). The ground-truth used to validate the sensor readings consisted of a destructive sampling in which the height, leaf area and biomass (dry weight basis) were measured in each individual plant. The depth image models agreed well with 45°, 90° and −45° measurements in one-year poplar trees. Good correlations (0.88 to 0.92) between dry biomass and the area measured with the Kinect were found. In addition, plant height was accurately estimated with a few centimeters error. The comparison between different viewing angles revealed that top views showed poorer results due to the fact the top leaves occluded the rest of the tree. However, the other views led to good results. Conversely, small poplars showed better correlations with actual parameters from the top view (0°). Therefore, although the Microsoft Kinect for Windows v.1 sensor provides good opportunities for biomass estimation, the viewing angle must be chosen taking into account the developmental stage of the crop and the desired parameters. The results of this study indicate that Kinect is a promising tool for a rapid canopy characterization, i.e., for estimating crop biomass

  5. Matching the best viewing angle in depth cameras for biomass estimation based on poplar seedling geometry.

    PubMed

    Andújar, Dionisio; Fernández-Quintanilla, César; Dorado, José

    2015-01-01

    In energy crops for biomass production a proper plant structure is important to optimize wood yields. A precise crop characterization in early stages may contribute to the choice of proper cropping techniques. This study assesses the potential of the Microsoft Kinect for Windows v.1 sensor to determine the best viewing angle of the sensor to estimate the plant biomass based on poplar seedling geometry. Kinect Fusion algorithms were used to generate a 3D point cloud from the depth video stream. The sensor was mounted in different positions facing the tree in order to obtain depth (RGB-D) images from different angles. Individuals of two different ages, e.g., one month and one year old, were scanned. Four different viewing angles were compared: top view (0°), 45° downwards view, front view (90°) and ground upwards view (-45°). The ground-truth used to validate the sensor readings consisted of a destructive sampling in which the height, leaf area and biomass (dry weight basis) were measured in each individual plant. The depth image models agreed well with 45°, 90° and -45° measurements in one-year poplar trees. Good correlations (0.88 to 0.92) between dry biomass and the area measured with the Kinect were found. In addition, plant height was accurately estimated with a few centimeters error. The comparison between different viewing angles revealed that top views showed poorer results due to the fact the top leaves occluded the rest of the tree. However, the other views led to good results. Conversely, small poplars showed better correlations with actual parameters from the top view (0°). Therefore, although the Microsoft Kinect for Windows v.1 sensor provides good opportunities for biomass estimation, the viewing angle must be chosen taking into account the developmental stage of the crop and the desired parameters. The results of this study indicate that Kinect is a promising tool for a rapid canopy characterization, i.e., for estimating crop biomass

  6. Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing

    NASA Astrophysics Data System (ADS)

    Ni-Meister, Wenge; Lee, Shihyan; Strahler, Alan H.; Woodcock, Curtis E.; Schaaf, Crystal; Yao, Tian; Ranson, K. Jon; Sun, Guoqing; Blair, J. Bryan

    2010-06-01

    Lidar-based aboveground biomass is derived based on the empirical relationship between lidar-measured vegetation height and aboveground biomass, often leading to large uncertainties of aboveground biomass estimates at large scales. This study investigates whether the use of any additional lidar-derived vegetation structure parameters besides height improves aboveground biomass estimation. The analysis uses data collected in the field and with the Laser Vegetation Imaging Sensor (LVIS), and the Echidna® validation instrument (EVI), a ground-based hemispherical-scanning lidar data in New England in 2003 and 2007. Our field data analysis shows that using wood volume (approximated by the product of basal area and top 10% tree height) and vegetation type (conifer/softwood or deciduous/hardwood forests, providing wood density) has the potential to improve aboveground biomass estimates at large scales. This result is comparable to previous individual-tree based analyses. Our LVIS data analysis indicates that structure parameters that combine height and gap fraction, such as RH100*cover and RH50*cover, are closely related to wood volume and thus biomass particularly for conifer forests. RH100*cover and RH50*cover perform similarly or even better than RH50, a good biomass predictor found in previous study. This study shows that the use of structure parameters that combine height and gap fraction (rather than height alone) improves the aboveground biomass estimate, and that the fusion of lidar and optical remote sensing (to provide vegetation type) will provide better aboveground biomass estimates than using lidar alone. Our ground lidar analysis shows that EVI provides good estimates of wood volume, and thus accurate estimates of aboveground biomass particularly at the stand level.

  7. Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach

    USGS Publications Warehouse

    Martin, Julien; Royle, J. Andrew; MacKenzie, Darryl I.; Edwards, Holly H.; Kery, Marc; Gardner, Beth

    2011-01-01

    Summary 1. Binomial mixture models use repeated count data to estimate abundance. They are becoming increasingly popular because they provide a simple and cost-effective way to account for imperfect detection. However, these models assume that individuals are detected independently of each other. This assumption may often be violated in the field. For instance, manatees (Trichechus manatus latirostris) may surface in turbid water (i.e. become available for detection during aerial surveys) in a correlated manner (i.e. in groups). However, correlated behaviour, affecting the non-independence of individual detections, may also be relevant in other systems (e.g. correlated patterns of singing in birds and amphibians). 2. We extend binomial mixture models to account for correlated behaviour and therefore to account for non-independent detection of individuals. We simulated correlated behaviour using beta-binomial random variables. Our approach can be used to simultaneously estimate abundance, detection probability and a correlation parameter. 3. Fitting binomial mixture models to data that followed a beta-binomial distribution resulted in an overestimation of abundance even for moderate levels of correlation. In contrast, the beta-binomial mixture model performed considerably better in our simulation scenarios. We also present a goodness-of-fit procedure to evaluate the fit of beta-binomial mixture models. 4. We illustrate our approach by fitting both binomial and beta-binomial mixture models to aerial survey data of manatees in Florida. We found that the binomial mixture model did not fit the data, whereas there was no evidence of lack of fit for the beta-binomial mixture model. This example helps illustrate the importance of using simulations and assessing goodness-of-fit when analysing ecological data with N-mixture models. Indeed, both the simulations and the goodness-of-fit procedure highlighted the limitations of the standard binomial mixture model for aerial

  8. A spatially explicit estimate of the prewhaling abundance of the endangered North Atlantic right whale.

    PubMed

    Monsarrat, Sophie; Pennino, M Grazia; Smith, Tim D; Reeves, Randall R; Meynard, Christine N; Kaplan, David M; Rodrigues, Ana S L

    2016-08-01

    The North Atlantic right whale (NARW) (Eubalaena glacialis) is one of the world's most threatened whales. It came close to extinction after nearly a millennium of exploitation and currently persists as a population of only approximately 500 individuals. Setting appropriate conservation targets for this species requires an understanding of its historical population size, as a baseline for measuring levels of depletion and progress toward recovery. This is made difficult by the scarcity of records over this species' long whaling history. We sought to estimate the preexploitation population size of the North Atlantic right whale and understand how this species was distributed across its range. We used a spatially explicit data set on historical catches of North Pacific right whales (NPRWs) (Eubalaena japonica) to model the relationship between right whale relative density and the environment during the summer feeding season. Assuming the 2 right whale species select similar environments, we projected this model to the North Atlantic to predict how the relative abundance of NARWs varied across their range. We calibrated these relative abundances with estimates of the NPRW total prewhaling population size to obtain high and low estimates for the overall NARW population size prior to exploitation. The model predicted 9,075-21,328 right whales in the North Atlantic. The current NARW population is thus <6% of the historical North Atlantic carrying capacity and has enormous potential for recovery. According to the model, in June-September NARWs concentrated in 2 main feeding areas: east of the Grand Banks of Newfoundland and in the Norwegian Sea. These 2 areas may become important in the future as feeding grounds and may already be used more regularly by this endangered species than is thought. PMID:26632250

  9. Biomass and estimated production properties of size-fractionated zooplankton in the Yellow Sea, China

    NASA Astrophysics Data System (ADS)

    Huo, Yuanzi; Sun, Song; Zhang, Fang; Wang, Minxiao; Li, Chaolun; Yang, Bo

    2012-06-01

    The size-fractionated zooplankton biomass, taxonomic composition, and production calculated by formulas basing on Ikeda-Motoda's physiological methods were studied on the basis of samples taken from six cruises in the Yellow Sea. Zooplankton was size-fractionated using sieves into ~ 2 mm, 1-2 mm, 0.5-1 mm, 0.25-0.5 mm and 0.16-0.25 mm groups. The results showed that the average zooplankton biomass was 84.03 mg DM m- 3 in May, followed in order by September, June, March, August and December with 42.34, 38.36, 32.37, 27.17 and 21.83 mg DM m- 3, respectively. The contribution of ~ 2 mm, 1-2 mm, 0.5-1 mm, 0.25-0.5 mm and 0.16-0.25 mm groups to the total biomass was in the range of 15.2-27.4%, 13.2-29.4%, 14.7-18.2%, 15.8-22.6% and 16.3-34.2%, respectively, during the investigating period. The biomass of all size groups was all highest in May, and except that the biomass of 0.16-0.25 mm group was lowest in August, the biomass of other size groups was lowest in December. The dominant zooplankton species (or taxa) in each group were similar between six cruises. The estimated zooplankton production was highest in May with 1.97 mg C m- 3 d- 1, and was lowest in December with 0.51 mg C m- 3 d- 1, and was in the range of 0.67-1.44 mg C m- 3 d- 1 in other investigating months. The estimated annual zooplankton production was 0.37 g C m- 3 y- 1. The two smallest groups aggregately comprised 59-84% of the net-zooplankton production in the Yellow Sea. The geographical distribution of size-fractionated zooplankton biomass and production was significantly affected by the complex physical features of the Yellow Sea. When the Yellow Sea Cold Bottom Water appeared from June to September, the biomass and production of zooplankton larger than 1 mm were higher inside the cold water mass area than outside it, while the zooplankton smaller than 1 mm showed contrary results. The higher biomass and production of all zooplankton groups occurred in the southern part of the study area in

  10. Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV

    NASA Astrophysics Data System (ADS)

    Pölönen, I.; Saari, H.; Kaivosoja, J.; Honkavaara, E.; Pesonen, L.

    2013-10-01

    Hyperspectral imaging based precise fertilization is challenge in the northern Europe, because of the cloud conditions. In this paper we will introduce schemes for the biomass and nitrogen content estimations from hyperspectral images. In this research we used the Fabry-Perot interferometer based hypespectral imager that enables hyperspectral imaging from lightweight UAVs. During the summers 2011 and 2012 imaging and flight campaigns were carried out on the Finnish test field. Estimation mehtod uses features from linear and non-linear unmixing and vegetation indices. The results showed that the concept of small hyperspectral imager, UAV and data analysis is ready to operational use.

  11. Total aboveground biomass (TAGB) estimation using IFSAR: speckle noise effect on TAGB in tropical forest

    NASA Astrophysics Data System (ADS)

    Misbari, S.; Hashim, M.

    2014-02-01

    Total Aboveground Biomass (TAGB) estimation is critically important to enhance understanding of dynamics of carbon fluxes between atmosphere and terrestrial ecosystem. For humid tropical forest, it is a challenging task for researchers due to complex canopy structure and predominant cloud cover. Optical sensors are only able to sense canopy crown. In contrast, radar technology is able to sense sub-canopy structure of the forest with penetration ability through the cloud for precise biomass estimation with validation from field data including diameter at breast height (DBH) of trees. This study is concerned about estimation of TAGB through the utilization of Interferometry Synthetic Aperture Radar (IFSAR). Based on this study, it is found that the stand parameters such as DBH and backscattered on IFSAR image has high correlation, R2=0.6411. The most suitable model for TAGB estimation on IFSAR is Chave Model with R2=0.9139. This study analyzes the impact brought by speckle noises on IFSAR image. It is found that filtering process has improves TAGB estimation about +30% using several filtering schemes especially Gamma filter for 11×11 window size. Using field data obtained from a primary tropical forest at Gerik, Perak, TAGBestimation can be validated and the assessment has been carried out.

  12. Estimating forest species abundance through linear unmixing of CHRIS/PROBA imagery

    NASA Astrophysics Data System (ADS)

    Stagakis, Stavros; Vanikiotis, Theofilos; Sykioti, Olga

    2016-09-01

    The advancing technology of hyperspectral remote sensing offers the opportunity of accurate land cover characterization of complex natural environments. In this study, a linear spectral unmixing algorithm that incorporates a novel hierarchical Bayesian approach (BI-ICE) was applied on two spatially and temporally adjacent CHRIS/PROBA images over a forest in North Pindos National Park (Epirus, Greece). The scope is to investigate the potential of this algorithm to discriminate two different forest species (i.e. beech - Fagus sylvatica, pine - Pinus nigra) and produce accurate species-specific abundance maps. The unmixing results were evaluated in uniformly distributed plots across the test site using measured fractions of each species derived by very high resolution aerial orthophotos. Landsat-8 images were also used to produce a conventional discrete-type classification map of the test site. This map was used to define the exact borders of the test site and compare the thematic information of the two mapping approaches (discrete vs abundance mapping). The required ground truth information, regarding training and validation of the applied mapping methodologies, was collected during a field campaign across the study site. Abundance estimates reached very good overall accuracy (R2 = 0.98, RMSE = 0.06). The most significant source of error in our results was due to the shadowing effects that were very intense in some areas of the test site due to the low solar elevation during CHRIS acquisitions. It is also demonstrated that the two mapping approaches are in accordance across pure and dense forest areas, but the conventional classification map fails to describe the natural spatial gradients of each species and the actual species mixture across the test site. Overall, the BI-ICE algorithm presented increased potential to unmix challenging objects with high spectral similarity, such as different vegetation species, under real and not optimum acquisition conditions. Its

  13. Estimation and Bias Correction of Aerosol Abundance using Data-driven Machine Learning and Remote Sensing

    NASA Technical Reports Server (NTRS)

    Malakar, Nabin K.; Lary, D. L.; Moore, A.; Gencaga, D.; Roscoe, B.; Albayrak, Arif; Petrenko, Maksym; Wei, Jennifer

    2012-01-01

    Air quality information is increasingly becoming a public health concern, since some of the aerosol particles pose harmful effects to peoples health. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. The comparison between the AOD measured from the ground-based Aerosol Robotic Network (AERONET) system and the satellite MODIS instruments at 550 nm shows that there is a bias between the two data products. We performed a comprehensive analysis exploring possible factors which may be contributing to the inter-instrumental bias between MODIS and AERONET. The analysis used several measured variables, including the MODIS AOD, as input in order to train a neural network in regression mode to predict the AERONET AOD values. This not only allowed us to obtain an estimate, but also allowed us to infer the optimal sets of variables that played an important role in the prediction. In addition, we applied machine learning to infer the global abundance of ground level PM2.5 from the AOD data and other ancillary satellite and meteorology products. This research is part of our goal to provide air quality information, which can also be useful for global epidemiology studies.

  14. Have ozone effects on carbon sequestration been over-estimated? A new biomass response function for wheat

    NASA Astrophysics Data System (ADS)

    Pleijel, H.; Danielsson, H.; Simpson, D.; Mills, G.

    2014-04-01

    Elevated levels of tropospheric ozone can significantly impair the growth of crops. The reduced removal of CO2 by plants leads to higher atmospheric concentrations of CO2, enhancing radiative forcing. Ozone effects on economic yield, e.g. the grain yield of wheat (Triticum aestivum L.) are currently used to model effects on radiative forcing. However, changes in grain yield do not necessarily reflect changes in total biomass. Based on analysis of 21 ozone exposure experiments with field-grown wheat, we investigated whether use of effects on grain yield as a~proxy for effects on biomass under- or over-estimates effects on biomass. First, we confirmed that effects on partitioning and biomass loss are both of significant importance for wheat yield loss. Then we derived ozone dose response functions for biomass loss and for harvest index (the proportion of above-ground biomass converted to grain) based on twelve experiments and recently developed ozone uptake modelling for wheat. Finally, we used a European scale chemical transport model (EMEP MSC-West) to assess the effect of ozone on biomass (-9%) and grain yield (-14%) loss over Europe. Based on yield data per grid square, we estimated above ground biomass losses due to ozone in 2000 in Europe totalling 22.2 million tonnes. Incorrectly applying the grain yield response function to model effects on biomass instead of the biomass response function of this paper would have indicated total above ground biomass losses totalling 38.1 million (i.e. overestimating effects by 15.9 million tonnes). A key conclusion from our study is that future assessments of ozone induced loss of agroecosystem carbon storage should use response functions for biomass, such as that provided in this paper, not grain yield, to avoid overestimation of the indirect radiative forcing from ozone effects on crop biomass accumulation.

  15. Calibrating abundance indices with population size estimators of red back salamanders (Plethodon cinereus) in a New England forest

    PubMed Central

    Ellison, Aaron M.; Jackson, Scott

    2015-01-01

    Herpetologists and conservation biologists frequently use convenient and cost-effective, but less accurate, abundance indices (e.g., number of individuals collected under artificial cover boards or during natural objects surveys) in lieu of more accurate, but costly and destructive, population size estimators to detect and monitor size, state, and trends of amphibian populations. Although there are advantages and disadvantages to each approach, reliable use of abundance indices requires that they be calibrated with accurate population estimators. Such calibrations, however, are rare. The red back salamander, Plethodon cinereus, is an ecologically useful indicator species of forest dynamics, and accurate calibration of indices of salamander abundance could increase the reliability of abundance indices used in monitoring programs. We calibrated abundance indices derived from surveys of P. cinereus under artificial cover boards or natural objects with a more accurate estimator of their population size in a New England forest. Average densities/m2 and capture probabilities of P. cinereus under natural objects or cover boards in independent, replicate sites at the Harvard Forest (Petersham, Massachusetts, USA) were similar in stands dominated by Tsuga canadensis (eastern hemlock) and deciduous hardwood species (predominantly Quercus rubra [red oak] and Acer rubrum [red maple]). The abundance index based on salamanders surveyed under natural objects was significantly associated with density estimates of P. cinereus derived from depletion (removal) surveys, but underestimated true density by 50%. In contrast, the abundance index based on cover-board surveys overestimated true density by a factor of 8 and the association between the cover-board index and the density estimates was not statistically significant. We conclude that when calibrated and used appropriately, some abundance indices may provide cost-effective and reliable measures of P. cinereus abundance that could

  16. Genetic Determinants for Enzymatic Digestion of Lignocellulosic Biomass Are Independent of Those for Lignin Abundance in a Maize Recombinant Inbred Population1[W][OPEN

    PubMed Central

    Penning, Bryan W.; Sykes, Robert W.; Babcock, Nicholas C.; Dugard, Christopher K.; Held, Michael A.; Klimek, John F.; Shreve, Jacob T.; Fowler, Matthew; Ziebell, Angela; Davis, Mark F.; Decker, Stephen R.; Turner, Geoffrey B.; Mosier, Nathan S.; Springer, Nathan M.; Thimmapuram, Jyothi; Weil, Clifford F.; McCann, Maureen C.; Carpita, Nicholas C.

    2014-01-01

    Biotechnological approaches to reduce or modify lignin in biomass crops are predicated on the assumption that it is the principal determinant of the recalcitrance of biomass to enzymatic digestion for biofuels production. We defined quantitative trait loci (QTL) in the Intermated B73 × Mo17 recombinant inbred maize (Zea mays) population using pyrolysis molecular-beam mass spectrometry to establish stem lignin content and an enzymatic hydrolysis assay to measure glucose and xylose yield. Among five multiyear QTL for lignin abundance, two for 4-vinylphenol abundance, and four for glucose and/or xylose yield, not a single QTL for aromatic abundance and sugar yield was shared. A genome-wide association study for lignin abundance and sugar yield of the 282-member maize association panel provided candidate genes in the 11 QTL of the B73 and Mo17 parents but showed that many other alleles impacting these traits exist among this broader pool of maize genetic diversity. B73 and Mo17 genotypes exhibited large differences in gene expression in developing stem tissues independent of allelic variation. Combining these complementary genetic approaches provides a narrowed list of candidate genes. A cluster of SCARECROW-LIKE9 and SCARECROW-LIKE14 transcription factor genes provides exceptionally strong candidate genes emerging from the genome-wide association study. In addition to these and genes associated with cell wall metabolism, candidates include several other transcription factors associated with vascularization and fiber formation and components of cellular signaling pathways. These results provide new insights and strategies beyond the modification of lignin to enhance yields of biofuels from genetically modified biomass. PMID:24972714

  17. Genetic Determinants for Enzymatic Digestion of Lignocellulosic Biomass Are Independent of Those for Lignin Abundance in a Maize Recombinant Inbred Population

    DOE PAGESBeta

    Penning, Bryan W.; Sykes, Robert W.; Babcock, Nicholas C.; Dugard, Christopher K.; Held, Michael A.; Klimek, John F.; Shreve, Jacob T.; Fowler, Matthew; Ziebell, Angela; Davis, Mark F.; et al

    2014-06-27

    Biotechnological approaches to reduce or modify lignin in biomass crops are predicated on the assumption that it is the principal determinant of the recalcitrance of biomass to enzymatic digestion for biofuels production. We defined quantitative trait loci (QTL) in the Intermated B73 x 3 Mo17 recombinant inbred maize (Zea mays) population using pyrolysis molecular-beam mass spectrometry to establish stem lignin content and an enzymatic hydrolysis assay to measure glucose and xylose yield. Among five multiyear QTL for lignin abundance, two for 4-vinylphenol abundance, and four for glucose and/or xylose yield, not a single QTL for aromatic abundance and sugar yieldmore » was shared. A genome-wide association study for lignin abundance and sugar yield of the 282- member maize association panel provided candidate genes in the 11 QTL of the B73 and Mo17 parents but showed that many other alleles impacting these traits exist among this broader pool of maize genetic diversity. B73 and Mo17 genotypes exhibited large differences in gene expression in developing stem tissues independent of allelic variation. Combining these complementary genetic approaches provides a narrowed list of candidate genes. A cluster of SCARECROW-LIKE9 and SCARECROW-LIKE14 transcription factor genes provides exceptionally strong candidate genes emerging from the genome-wide association study. In addition to these and genes associated with cell wall metabolism, candidates include several other transcription factors associated with vascularization and fiber formation and components of cellular signaling pathways. Finally, these results provide new insights and strategies beyond the modification of lignin to enhance yields of biofuels from genetically modified biomass.« less

  18. Genetic Determinants for Enzymatic Digestion of Lignocellulosic Biomass Are Independent of Those for Lignin Abundance in a Maize Recombinant Inbred Population.

    PubMed

    Penning, Bryan W; Sykes, Robert W; Babcock, Nicholas C; Dugard, Christopher K; Held, Michael A; Klimek, John F; Shreve, Jacob T; Fowler, Matthew; Ziebell, Angela; Davis, Mark F; Decker, Stephen R; Turner, Geoffrey B; Mosier, Nathan S; Springer, Nathan M; Thimmapuram, Jyothi; Weil, Clifford F; McCann, Maureen C; Carpita, Nicholas C

    2014-06-27

    Biotechnological approaches to reduce or modify lignin in biomass crops are predicated on the assumption that it is the principal determinant of the recalcitrance of biomass to enzymatic digestion for biofuels production. We defined quantitative trait loci (QTL) in the Intermated B73 × Mo17 recombinant inbred maize (Zea mays) population using pyrolysis molecular-beam mass spectrometry to establish stem lignin content and an enzymatic hydrolysis assay to measure glucose and xylose yield. Among five multiyear QTL for lignin abundance, two for 4-vinylphenol abundance, and four for glucose and/or xylose yield, not a single QTL for aromatic abundance and sugar yield was shared. A genome-wide association study for lignin abundance and sugar yield of the 282-member maize association panel provided candidate genes in the 11 QTL of the B73 and Mo17 parents but showed that many other alleles impacting these traits exist among this broader pool of maize genetic diversity. B73 and Mo17 genotypes exhibited large differences in gene expression in developing stem tissues independent of allelic variation. Combining these complementary genetic approaches provides a narrowed list of candidate genes. A cluster of SCARECROW-LIKE9 and SCARECROW-LIKE14 transcription factor genes provides exceptionally strong candidate genes emerging from the genome-wide association study. In addition to these and genes associated with cell wall metabolism, candidates include several other transcription factors associated with vascularization and fiber formation and components of cellular signaling pathways. These results provide new insights and strategies beyond the modification of lignin to enhance yields of biofuels from genetically modified biomass. PMID:24972714

  19. Genetic Determinants for Enzymatic Digestion of Lignocellulosic Biomass Are Independent of Those for Lignin Abundance in a Maize Recombinant Inbred Population

    SciTech Connect

    Penning, Bryan W.; Sykes, Robert W.; Babcock, Nicholas C.; Dugard, Christopher K.; Held, Michael A.; Klimek, John F.; Shreve, Jacob T.; Fowler, Matthew; Ziebell, Angela; Davis, Mark F.; Decker, Stephen R.; Turner, Geoffrey B.; Mosier, Nathan S.; Springer, Nathan M.; Thimmapuram, Jyothi; Weil, Clifford F.; McCann, Maureen C.; Carpita, Nicholas C.

    2014-06-27

    Biotechnological approaches to reduce or modify lignin in biomass crops are predicated on the assumption that it is the principal determinant of the recalcitrance of biomass to enzymatic digestion for biofuels production. We defined quantitative trait loci (QTL) in the Intermated B73 x 3 Mo17 recombinant inbred maize (Zea mays) population using pyrolysis molecular-beam mass spectrometry to establish stem lignin content and an enzymatic hydrolysis assay to measure glucose and xylose yield. Among five multiyear QTL for lignin abundance, two for 4-vinylphenol abundance, and four for glucose and/or xylose yield, not a single QTL for aromatic abundance and sugar yield was shared. A genome-wide association study for lignin abundance and sugar yield of the 282- member maize association panel provided candidate genes in the 11 QTL of the B73 and Mo17 parents but showed that many other alleles impacting these traits exist among this broader pool of maize genetic diversity. B73 and Mo17 genotypes exhibited large differences in gene expression in developing stem tissues independent of allelic variation. Combining these complementary genetic approaches provides a narrowed list of candidate genes. A cluster of SCARECROW-LIKE9 and SCARECROW-LIKE14 transcription factor genes provides exceptionally strong candidate genes emerging from the genome-wide association study. In addition to these and genes associated with cell wall metabolism, candidates include several other transcription factors associated with vascularization and fiber formation and components of cellular signaling pathways. Finally, these results provide new insights and strategies beyond the modification of lignin to enhance yields of biofuels from genetically modified biomass.

  20. Geographical and seasonal variations in mesozooplankton abundance and biomass in relation to environmental parameters in Lake Shinji Ohashi River Lake Nakaumi brackish-water system, Japan

    NASA Astrophysics Data System (ADS)

    Uye, S.; Shimazu, T.; Yamamuro, M.; Ishitobi, Y.; Kamiya, H.

    2000-10-01

    We measured the abundance and biomass of the major taxonomic groups of mesozooplankton at six stations in Lake Shinji-Ohashi River-Lake Nakaumi brackish-water system, Japan, monthly for three full years (1995-1997), except for one station (for 1 year and 9 months). Over the entire area, copepods overwhelmingly dominated the zooplankton community both in terms of abundance (mean: 87.9%) and biomass (83.4%). The remaining taxa were cladocerans (i.e. Diphanosoma brachyurum, Evadone tergestina, Penilia avirostris, Podon leuckarti and Podon polyphemoides), appendicularians ( Oikopleura dioica and Oikopleura longicauda), chaetognaths ( Sagitta crassa) and the larvae of benthos (e.g. polychaetes, bivalves, gastropods and malacostracans). The geographical and seasonal variations of the mesozooplankton community were therefore principally explained by the variations of the copepod community. The geographical difference in copepod species composition was associated with salinity preference or tolerance of respective species. In Lake Shinji, where the salinity was lowest (mean: 4.0), Sinocalanus tenellus was monospecifically abundant with sporadic occurrence of Pseudodiaptomus inopinus. In Ohashi River (mean salinity: 9.9), Acartia hudsonica, Acartia sinjiensis, Eurytemora pacifica and Oithona davisae added to the community. At central and southeast Lake Nakaumi and in Honjo District, where mean salinity ranged from 16.4 to 21.7, these four species became more important than S. tenellus and P. inopinus. At the entrance of Sakai Strait, where the salinity was highest (mean: 24.0), Paracalanus spp. constituted a significant component. Due to large temperature fluctuation with season, the copepods showed remarkable seasonal variations in abundance and biomass, with enormous annual peaks in winter-spring. These annual peaks might be attributed to scarce occurrence of predators.

  1. Re-Constructing Historical Adélie Penguin Abundance Estimates by Retrospectively Accounting for Detection Bias

    PubMed Central

    Southwell, Colin; Emmerson, Louise; Newbery, Kym; McKinlay, John; Kerry, Knowles; Woehler, Eric; Ensor, Paul

    2015-01-01

    Seabirds and other land-breeding marine predators are considered to be useful and practical indicators of the state of marine ecosystems because of their dependence on marine prey and the accessibility of their populations at breeding colonies. Historical counts of breeding populations of these higher-order marine predators are one of few data sources available for inferring past change in marine ecosystems. However, historical abundance estimates derived from these population counts may be subject to unrecognised bias and uncertainty because of variable attendance of birds at breeding colonies and variable timing of past population surveys. We retrospectively accounted for detection bias in historical abundance estimates of the colonial, land-breeding Adélie penguin through an analysis of 222 historical abundance estimates from 81 breeding sites in east Antarctica. The published abundance estimates were de-constructed to retrieve the raw count data and then re-constructed by applying contemporary adjustment factors obtained from remotely operating time-lapse cameras. The re-construction process incorporated spatial and temporal variation in phenology and attendance by using data from cameras deployed at multiple sites over multiple years and propagating this uncertainty through to the final revised abundance estimates. Our re-constructed abundance estimates were consistently higher and more uncertain than published estimates. The re-constructed estimates alter the conclusions reached for some sites in east Antarctica in recent assessments of long-term Adélie penguin population change. Our approach is applicable to abundance data for a wide range of colonial, land-breeding marine species including other penguin species, flying seabirds and marine mammals. PMID:25909636

  2. Re-constructing historical Adélie penguin abundance estimates by retrospectively accounting for detection bias.

    PubMed

    Southwell, Colin; Emmerson, Louise; Newbery, Kym; McKinlay, John; Kerry, Knowles; Woehler, Eric; Ensor, Paul

    2015-01-01

    Seabirds and other land-breeding marine predators are considered to be useful and practical indicators of the state of marine ecosystems because of their dependence on marine prey and the accessibility of their populations at breeding colonies. Historical counts of breeding populations of these higher-order marine predators are one of few data sources available for inferring past change in marine ecosystems. However, historical abundance estimates derived from these population counts may be subject to unrecognised bias and uncertainty because of variable attendance of birds at breeding colonies and variable timing of past population surveys. We retrospectively accounted for detection bias in historical abundance estimates of the colonial, land-breeding Adélie penguin through an analysis of 222 historical abundance estimates from 81 breeding sites in east Antarctica. The published abundance estimates were de-constructed to retrieve the raw count data and then re-constructed by applying contemporary adjustment factors obtained from remotely operating time-lapse cameras. The re-construction process incorporated spatial and temporal variation in phenology and attendance by using data from cameras deployed at multiple sites over multiple years and propagating this uncertainty through to the final revised abundance estimates. Our re-constructed abundance estimates were consistently higher and more uncertain than published estimates. The re-constructed estimates alter the conclusions reached for some sites in east Antarctica in recent assessments of long-term Adélie penguin population change. Our approach is applicable to abundance data for a wide range of colonial, land-breeding marine species including other penguin species, flying seabirds and marine mammals. PMID:25909636

  3. Estimating aboveground biomass in interior Alaska with Landsat data and field measurements

    USGS Publications Warehouse

    Ji, Lei; Wylie, Bruce K.; Nossov, Dana R.; Peterson, Birgit; Waldrop, Mark P.; McFarland, Jack W.; Rover, Jennifer R.; Hollingsworth, Teresa N.

    2012-01-01

    Terrestrial plant biomass is a key biophysical parameter required for understanding ecological systems in Alaska. An accurate estimation of biomass at a regional scale provides an important data input for ecological modeling in this region. In this study, we created an aboveground biomass (AGB) map at 30-m resolution for the Yukon Flats ecoregion of interior Alaska using Landsat data and field measurements. Tree, shrub, and herbaceous AGB data in both live and dead forms were collected in summers and autumns of 2009 and 2010. Using the Landsat-derived spectral variables and the field AGB data, we generated a regression model and applied this model to map AGB for the ecoregion. A 3-fold cross-validation indicated that the AGB estimates had a mean absolute error of 21.8 Mg/ha and a mean bias error of 5.2 Mg/ha. Additionally, we validated the mapping results using an airborne lidar dataset acquired for a portion of the ecoregion. We found a significant relationship between the lidar-derived canopy height and the Landsat-derived AGB (R2 = 0.40). The AGB map showed that 90% of the ecoregion had AGB values ranging from 10 Mg/ha to 134 Mg/ha. Vegetation types and fires were the primary factors controlling the spatial AGB patterns in this ecoregion.

  4. Validation of abundance estimates from mark–recapture and removal techniques for rainbow trout captured by electrofishing in small streams

    USGS Publications Warehouse

    Rosenberger, Amanda E.; Dunham, Jason B.

    2005-01-01

    Estimation of fish abundance in streams using the removal model or the Lincoln - Peterson mark - recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams. For one-, two-, three-, and four-pass sampling effort in closed sites, we evaluated the influences of fish size and habitat characteristics on sampling efficiency and the accuracy of removal abundance estimates. We also examined the use of models to generate unbiased estimates of fish abundance through adjustment of total catch or biased removal estimates. Our results suggested that the assumptions of the mark - recapture model were satisfied and that abundance estimates based on this approach were unbiased. In contrast, the removal model assumptions were not met. Decreasing sampling efficiencies over removal passes resulted in underestimated population sizes and overestimates of sampling efficiency. This bias decreased, but was not eliminated, with increased sampling effort. Biased removal estimates based on different levels of effort were highly correlated with each other but were less correlated with unbiased mark - recapture estimates. Stream size decreased sampling efficiency, and stream size and instream wood increased the negative bias of removal estimates. We found that reliable estimates of population abundance could be obtained from models of sampling efficiency for different levels of effort. Validation of abundance estimates requires extra attention to routine sampling considerations but can help fisheries biologists avoid pitfalls associated with biased data and facilitate standardized comparisons among studies that employ different sampling methods.

  5. A robust and efficient method for estimating enzyme complex abundance and metabolic flux from expression data.

    PubMed

    Barker, Brandon E; Sadagopan, Narayanan; Wang, Yiping; Smallbone, Kieran; Myers, Christopher R; Xi, Hongwei; Locasale, Jason W; Gu, Zhenglong

    2015-12-01

    A major theme in constraint-based modeling is unifying experimental data, such as biochemical information about the reactions that can occur in a system or the composition and localization of enzyme complexes, with high-throughput data including expression data, metabolomics, or DNA sequencing. The desired result is to increase predictive capability and improve our understanding of metabolism. The approach typically employed when only gene (or protein) intensities are available is the creation of tissue-specific models, which reduces the available reactions in an organism model, and does not provide an objective function for the estimation of fluxes. We develop a method, flux assignment with LAD (least absolute deviation) convex objectives and normalization (FALCON), that employs metabolic network reconstructions along with expression data to estimate fluxes. In order to use such a method, accurate measures of enzyme complex abundance are needed, so we first present an algorithm that addresses quantification of complex abundance. Our extensions to prior techniques include the capability to work with large models and significantly improved run-time performance even for smaller models, an improved analysis of enzyme complex formation, the ability to handle large enzyme complex rules that may incorporate multiple isoforms, and either maintained or significantly improved correlation with experimentally measured fluxes. FALCON has been implemented in MATLAB and ATS, and can be downloaded from: https://github.com/bbarker/FALCON. ATS is not required to compile the software, as intermediate C source code is available. FALCON requires use of the COBRA Toolbox, also implemented in MATLAB. PMID:26381164

  6. Uncommon or cryptic? Challenges in estimating leopard seal abundance by conventional but state-of-the-art methods

    NASA Astrophysics Data System (ADS)

    Southwell, Colin; Paxton, Charles G. M.; Borchers, David; Boveng, Peter; Rogers, Tracey; de la Mare, William K.

    2008-04-01

    The method traditionally used to estimate pack-ice seal abundance employs sighting surveys from ships or aircraft to estimate the number of seals hauled out on the ice, combined with studies of haul-out behaviour to estimate the proportion of time spent on the ice. Application of this approach has been improved in recent times by developments in survey methodology and satellite technology that theoretically allow biases in the estimation of hauled-out abundance and haul-out behaviour to be accounted for that previously could not be addressed. A survey using these conventional but state-of-the-art methods was undertaken in the summer of 1999/2000 off east Antarctica between longitudes 64°E and 150°E to estimate the abundance of leopard ( Hydrurga leptonyx) and other pack-ice seal species. Because they are either uncommon or very cryptic, very few leopard seals were encountered despite a large survey effort. This presented challenges in both application of the methods and analysis of the data. Abundance estimates were derived using a number of plausible predictive models. The model considered as the most reliable returned best estimates of 7300 and 12,100 for definite and definite plus probable leopard seal sightings, respectively, with 95% confidence intervals of 3700-14,500 and 7100-23,400. These estimates are likely to be negatively biased and should be treated as minimum estimates only.

  7. Assessing General Relationships Between Above-Ground Biomass and Vegetation Structure Parameters for Improved Carbon Estimate from Lidar Remote Sensing

    NASA Astrophysics Data System (ADS)

    Ni-Meister, W.; Lee, S.; Strahler, A. H.; Woodcock, C. E.; Schaaf, C.; Yao, T.; Ranson, J.; Sun, G.; Blair, J. B.

    2009-12-01

    Lidar remote sensing uses vegetation height to estimate large-scale above-ground biomass. However, lidar height and biomass relationships are empirical and thus often lead to large uncertainties in above-ground biomass estimates. This study uses vegetation structure measurements from field: an airborne lidar (Laser Vegetation Imaging Sensor, LVIS)) and a full wave form ground-based lidar (Echidna® validation instrument, EVI) collected in the New England region in 2003 and 2007, to investigate using additional vegetation structure parameters besides height for improved above-ground biomass estimation from lidar. Our field data analysis shows that using woody volume (approximated by the product of basal area and top 10% tree height) and vegetation type (conifer/softwood or deciduous/hardwood forests, providing wood density) has the potential to improve above-ground biomass estimates at large scale. This result is comparable to previous work by Chave et al. (2005), which focused on individual trees. However this study uses a slightly different approach, and our woody volume is estimated differently from Chave et al. (2005). Previous studies found that RH50 is a good predictor of above-ground biomass (Drake et al., 2002; 2003). Our LVIS data analysis shows that structure parameters that combine height and gap fraction, such as RH100*cover and RH50*cover, perform similarly or even better than RH50. We also found that the close relationship of RH100*cover and RH50*cover with woody volume explains why they are good predictors of above-ground biomass. RH50 is highly related to RH100*cover, and this explains why RH50 is a better predictor of biomass than RH100. This study shows that using structure parameters combining height and gap fraction improve above-ground biomass estimate compared to height alone, and fusion of lidar and optical remote sensing (to provide vegetation type) will provide better above-ground biomass estimates than lidar alone. Ground lidar analysis

  8. Comparing new and conventional methods to estimate benthic algal biomass and composition in freshwaters.

    PubMed

    Kahlert, Maria; McKie, Brendan G

    2014-11-01

    We compared conventional microscope-based methods for quantifying biomass and community composition of stream benthic algae with output obtained for these parameters from a new instrument (the BenthoTorch), which measures fluorescence of algal pigments in situ. Benthic algae were studied in 24 subarctic oligotrophic (1.7-26.9, median 7.2 μg total phosphorus L(-1)) streams in Northern Sweden. Readings for biomass of the total algal mat, quantified as chlorophyll a, did not differ significantly between the BenthoTorch (median 0.52 μg chlorophyll a cm(-2)) and the conventional method (median 0.53 μg chlorophyll a cm(-2)). However, quantification of community composition of the benthic algal mat obtained using the BenthoTorch did not match those obtained from conventional methods. The BenthoTorch indicated a dominance of diatoms, whereas microscope observations showed a fairly even distribution between diatoms, blue-green algae (mostly nitrogen-fixing) and green algae (mostly large filamentous), and also detected substantial biovolumes of red algae in some streams. These results most likely reflect differences in the exact parameters quantified by the two methods, as the BenthoTorch does not account for variability in cell size and the presence of non-chlorophyll bearing biomass in estimating the proportion of different algal groups, and does not distinguish red algal chlorophyll from that of other algal groups. Our findings suggest that the BenthoTorch has utility in quantifying biomass expressed as μg chlorophyll a cm(-2), but its output for the relative contribution of different algal groups to benthic algal biomass should be used with caution. PMID:25277172

  9. A hyperspectral approach to estimating biomass and plant production in a heterogeneous restored temperate peatland

    NASA Astrophysics Data System (ADS)

    Byrd, K. B.; Schile, L. M.; Windham-Myers, L.; Kelly, M.; Hatala, J.; Baldocchi, D. D.

    2012-12-01

    Restoration of drained peatlands that are managed to reverse subsidence through organic accretion holds significant potential for large-scale carbon storage and sequestration. This potential has been demonstrated in an experimental wetland restoration site established by the U.S. Geological Survey in 1997 on Twitchell Island in the Sacramento-San Joaquin River Delta, where soil carbon storage is up to 1 kg C m-2 and root and rhizome production can reach over 7 kg m-2 annually. Remote sensing-based estimation of biomass and productivity over a large spatial extent helps to monitor carbon storage potential of these restored peatlands. Extensive field measurements of plant biophysical characteristics such as biomass, leaf area index, and the fraction of absorbed photosynthetically active radiation (fAPAR) [an important variable in light-use efficiency (LUE) models] have been collected for agricultural systems and forests. However the small size and local spatial variability of U.S. Pacific Coast wetlands pose new challenges for measuring these variables in the field and generating estimates through remote sensing. In particular background effects of non-photosynthetic vegetation (NPV), floating aquatic vegetation, and inundation of wetland vegetation influence the relationship between field measurements and multispectral or hyperspectral indices. Working at the USGS experimental wetland site, characterized by variable water depth and substantial NPV, or thatch, we collected field data on hardstem bulrush (Schoenoplectus acutus) and cattail (Typha spp.) coupled with reflectance data from a field spectrometer (350-2500 nm) every two to three weeks during the summers of 2011 and 2012. We calculated aboveground biomass with existing allometric relationships, and fAPAR was measured with line and point quantum sensors. We analyzed reflectance data to develop hyperspectral and multispectral indices that predict biomass and fAPAR and account for background effects of water

  10. First Estimates of the Radiative Forcing of Aerosols Generated from Biomass Burning Using Satellite Data

    NASA Technical Reports Server (NTRS)

    Christopher, Sundar A.; Kliche, Donna A.; Chou, Joyce; Welch, Ronald M.

    1996-01-01

    Collocated measurements from the Advanced Very High Resolution Radiometer (AVHRR) and the Earth Radiation Budget Experiment (ERBE) scanner are used to examine the radiative forcing of atmospheric aerosols generated from biomass burning for 13 images in South America. Using the AVHRR, Local Area Coverage (LAC) data, a new technique based on a combination of spectral and textural measures is developed for detecting these aerosols. Then, the instantaneous shortwave, longwave, and net radiative forcing values are computed from the ERBE instantaneous scanner data. Results for the selected samples from 13 images show that the mean instantaneous net radiative forcing for areas with heavy aerosol loading is about -36 W/sq m and that for the optically thin aerosols are about -16 W/sq m. These results, although preliminary, provide the first estimates of radiative forcing of atmospheric aerosols from biomass burning using satellite data.

  11. First Estimates of the Radiative Forcing of Aerosols Generated from Biomass Burning using Satellite Data

    NASA Technical Reports Server (NTRS)

    Chistopher, Sundar A.; Kliche, Donna V.; Chou, Joyce; Welch, Ronald M.

    1996-01-01

    Collocated measurements from the Advanced Very High Resolution Radiometer (AVHRR) and the Earth Radiation Budget Experiment (ERBE) scanner are used to examine the radiative forcing of atmospheric aerosols generated from biomass burning for 13 images in South America. Using the AVHRR, Local Area Coverage (LAC) data, a new technique based on a combination of spectral and textural measures is developed for detecting these aerosols. Then, the instantaneous shortwave, longwave, and net radiative forcing values are computed from the ERBE instantaneous scanner data. Results for the selected samples from 13 images show that the mean instantaneous net radiative forcing for areas with heavy aerosol loading is about -36 W/sq m and that for the optically thin aerosols are about -16 W/sq m. These results, although preliminary, provide the first estimates of radiative forcing of atmospheric aerosols from biomass burning using satellite data.

  12. Chilean blue whales as a case study to illustrate methods to estimate abundance and evaluate conservation status of rare species.

    PubMed

    Williams, Rob; Hedley, Sharon L; Branch, Trevor A; Bravington, Mark V; Zerbini, Alexandre N; Findlay, Ken P

    2011-06-01

    Often abundance of rare species cannot be estimated with conventional design-based methods, so we illustrate with a population of blue whales (Balaenoptera musculus) a spatial model-based method to estimate abundance. We analyzed data from line-transect surveys of blue whales off the coast of Chile, where the population was hunted to low levels. Field protocols allowed deviation from planned track lines to collect identification photographs and tissue samples for genetic analyses, which resulted in an ad hoc sampling design with increased effort in areas of higher densities. Thus, we used spatial modeling methods to estimate abundance. Spatial models are increasingly being used to analyze data from surveys of marine, aquatic, and terrestrial species, but estimation of uncertainty from such models is often problematic. We developed a new, broadly applicable variance estimator that showed there were likely 303 whales (95% CI 176-625) in the study area. The survey did not span the whales' entire range, so this is a minimum estimate. We estimated current minimum abundance relative to pre-exploitation abundance (i.e., status) with a population dynamics model that incorporated our minimum abundance estimate, likely population growth rates from a meta-analysis of rates of increase in large baleen whales, and two alternative assumptions about historic catches. From this model, we estimated that the population was at a minimum of 9.5% (95% CI 4.9-18.0%) of pre-exploitation levels in 1998 under one catch assumption and 7.2% (CI 3.7-13.7%) of pre-exploitation levels under the other. Thus, although Chilean blue whales are probably still at a small fraction of pre-exploitation abundance, even these minimum abundance estimates demonstrate that their status is better than that of Antarctic blue whales, which are still <1% of pre-exploitation population size. We anticipate our methods will be broadly applicable in aquatic and terrestrial surveys for rarely encountered species

  13. Impact of biomass burning on urban air quality estimated by organic tracers: Guangzhou and Beijing as cases

    NASA Astrophysics Data System (ADS)

    Wang, Qiaoqiao; Shao, Min; Liu, Ying; William, Kuster; Paul, Goldan; Li, Xiaohua; Liu, Yuan; Lu, Sihua

    The impacts of biomass burning have not been adequately studied in China. In this work, chemical compositions of volatile organic compounds and particulate organic matters were measured in August 2005 in Beijing and in October 2004 in Guangzhou city. The performance of several possible tracers for biomass burning is compared by using acetonitrile as a reference compound. The correlations between the possible tracers and acetonitrile show that the use of K + as a tracer could result in bias because of the existence of other K + sources in urban areas, while chloromethane is not reliable due to its wide use as industrial chemical. The impact of biomass burning on air quality is estimated using acetonitrile and levoglucosan as tracers. The results show that the impact of biomass burning is ubiquitous in both suburban and urban Guangzhou, and the frequencies of air pollution episodes significantly influenced by biomass burning were 100% for Xinken and 58% for downtown Guangzhou city. Fortunately, the air quality in only 2 out of 22 days was partly impacted by biomass burning in August in Beijing, the month that 2008 Olympic games will take place. The quantitative contribution of biomass burning to ambient PM2.5 concentrations in Guangzhou city was also estimated by the ratio of levoglocusan to PM2.5 in both the ambient air and biomass burning plumes. The results show that biomass burning contributes 3.0-16.8% and 4.0-19.0% of PM2.5 concentrations in Xinken and Guangzhou downtown, respectively.

  14. Factors influencing benthic bacterial abundance, biomass, and activity on the northern continental margin and deep basin of the Gulf of Mexico

    NASA Astrophysics Data System (ADS)

    Deming, Jody W.; Carpenter, Shelly D.

    2008-12-01

    As part of a larger project on the deep benthos of the Gulf of Mexico, an extensive data set on benthic bacterial abundance ( n>750), supplemented with cell-size and rate measurements, was acquired from 51 sites across a depth range of 212-3732 m on the northern continental slope and deep basin during the years 2000, 2001, and 2002. Bacterial abundance, determined by epifluorescence microscopy, was examined region-wide as a function of spatial and temporal variables, while subsets of the data were examined for sediment-based chemical or mineralogical correlates according to the availability of collaborative data sets. In the latter case, depth of oxygen penetration helped to explain bacterial depth profiles into the sediment, but only porewater DOC correlated significantly (inversely) with bacterial abundance ( p<0.05, n=24). Other (positive) correlations were detected with TOC, C/N ratios, and % sand when the analysis was restricted to data from the easternmost stations ( p<0.05, n=9-12). Region-wide, neither surface bacterial abundance (3.30-16.8×10 8 bacteria cm -3 in 0-1 cm and 4-5 cm strata) nor depth-integrated abundance (4.84-17.5×10 13 bacteria m -2, 0-15 cm) could be explained by water depth, station location, sampling year, or vertical POC flux. In contrast, depth-integrated bacterial biomass, derived from measured cell sizes of 0.027-0.072 μm 3, declined significantly with station depth ( p<0.001, n=56). Steeper declines in biomass were observed for the cross-slope transects (when unusual topographic sites and abyssal stations were excluded). The importance of resource changes with depth was supported by the positive relationship observed between bacterial biomass and vertical POC flux, derived from measures of overlying productivity, a relationship that remained significant when depth was held constant (partial correlation analysis, p<0.05, df=50). Whole-sediment incubation experiments under simulated in situ conditions, using 3H-thymidine or 14C

  15. The Use of Aerosol Optical Depth in Estimating Trace Gas Emissions from Biomass Burning Plumes

    NASA Astrophysics Data System (ADS)

    Jones, N.; Paton-Walsh, C.; Wilson, S.; Meier, A.; Deutscher, N.; Griffith, D.; Murcray, F.

    2003-12-01

    We have observed significant correlations between aerosol optical depth (AOD) at 500 nm and column amounts of a number of biomass burning indicators (carbon monoxide, hydrogen cyanide, formaldehyde and ammonia) in bushfire smoke plumes over SE Australia during the 2001/2002 and 2002/2003 fire seasons from remote sensing measurements. The Department of Chemistry, University of Wollongong, operates a high resolution Fourier Transform Spectrometer (FTS), in the city of Wollongong, approximately 80 km south of Sydney. During the recent bushfires we collected over 1500 solar FTIR spectra directly through the smoke over Wollongong. The total column amounts of the biomass burning indicators were calculated using the profile retrieval software package SFIT2. Using the same solar beam, a small grating spectrometer equipped with a 2048 pixel CCD detector array, was used to calculate simultaneous aerosol optical depths. This dataset is therefore unique in its temporal sampling, location to active fires, and range of simultaneously measured constituents. There are several important applications of the AOD to gas column correlation. The estimation of global emissions from biomass burning currently has very large associated uncertainties. The use of visible radiances measured by satellites, and hence AOD, could significantly reduce these uncertainties by giving a direct estimate of global emissions of gases from biomass burning through application of the AOD to gas correlation. On a more local level, satellite-derived aerosol optical depth maps could be inverted to infer approximate concentration levels of smoke-related pollutants at the ground and in the lower troposphere, and thus can be used to determine the nature of any significant health impacts.

  16. An inventory-based approach for estimating the managed China's forest biomass carbon stock

    NASA Astrophysics Data System (ADS)

    Huang, M.; Yu, G.; Yue, X.; Wang, J.

    2014-12-01

    China's forests cover a large area and have the characteristics of young age thus have the potential for a major role in mitigate the rate of global climate change. On the basis of forest inventory data and spatial distribution of forest stand age and forest type, we developed an approach for estimating yearly China's forest biomass carbon stocks change. Using this approach, we estimated the changes of forest carbon stock due to management practice and forest age structure change, respectively, and predicted China's future carbon potential based on national forest expansion plan. We also discussed sustainable harvesting intensity for the expanded forest of 2020. The spatial pattern of forest biomass carbon density in 2001 showed high in southwestern and northeastern areas, and low in the other regions, meanwhile the high C sinks appeared in the southwestern and northeastern young-aged forests and low in the southwestern and northeastern old-aged forests. The total forest biomass C stock of China increased from 6.06 Pg C in 2001 to 7.88 Pg C in 2013, giving a total increase of 1.82 Pg C, in which 0.45 Pg C is caused by forest expansion. The average C sink during 2002-2013 was 151.83 Tg C, in which 75.5% is the results of forest growth and 24.5% is caused by forest expansion. With the assumption of China's forest area will expand by 40 million hectares from 2006 to 2020, the forest C stock in 2020 is predicted as 9.04 Pg C. Harvesting intensity experiments conducted on the expanded forest of 2020 shown higher harvesting level will lead to decline in forest biomass in long term. The harvesting level of 2% is an optimal harvesting intensity for sustainable development of China's forest resources.

  17. Trap Array Configuration Influences Estimates and Precision of Black Bear Density and Abundance

    PubMed Central

    Wilton, Clay M.; Puckett, Emily E.; Beringer, Jeff; Gardner, Beth; Eggert, Lori S.; Belant, Jerrold L.

    2014-01-01

    Spatial capture-recapture (SCR) models have advanced our ability to estimate population density for wide ranging animals by explicitly incorporating individual movement. Though these models are more robust to various spatial sampling designs, few studies have empirically tested different large-scale trap configurations using SCR models. We investigated how extent of trap coverage and trap spacing affects precision and accuracy of SCR parameters, implementing models using the R package secr. We tested two trapping scenarios, one spatially extensive and one intensive, using black bear (Ursus americanus) DNA data from hair snare arrays in south-central Missouri, USA. We also examined the influence that adding a second, lower barbed-wire strand to snares had on quantity and spatial distribution of detections. We simulated trapping data to test bias in density estimates of each configuration under a range of density and detection parameter values. Field data showed that using multiple arrays with intensive snare coverage produced more detections of more individuals than extensive coverage. Consequently, density and detection parameters were more precise for the intensive design. Density was estimated as 1.7 bears per 100 km2 and was 5.5 times greater than that under extensive sampling. Abundance was 279 (95% CI = 193–406) bears in the 16,812 km2 study area. Excluding detections from the lower strand resulted in the loss of 35 detections, 14 unique bears, and the largest recorded movement between snares. All simulations showed low bias for density under both configurations. Results demonstrated that in low density populations with non-uniform distribution of population density, optimizing the tradeoff among snare spacing, coverage, and sample size is of critical importance to estimating parameters with high precision and accuracy. With limited resources, allocating available traps to multiple arrays with intensive trap spacing increased the amount of information

  18. Using multi-frequency radar and discrete-return LiDAR measurements to estimate above-ground biomass and biomass components in a coastal temperate forest

    NASA Astrophysics Data System (ADS)

    Tsui, Olivier W.; Coops, Nicholas C.; Wulder, Michael A.; Marshall, Peter L.; McCardle, Adrian

    2012-04-01

    Height measurements from small-footprint discrete-return LiDAR and backscatter coefficients from C- and L-band radar were used independently and in combination to estimate above-ground component and total biomass for a coniferous temperate forest, located on Vancouver Island, British Columbia, Canada. Reference biomass data were obtained from plot-level data and used for comparison against the LiDAR and radar-based biomass models. For the LiDAR-only model, height metrics such as mean first return height and percentiles (e.g., 10th and 90th) of first returns correlated best to total above-ground and stem biomass. While percent of first returns above 2 m and percentiles (75th and 90th) of first returns height metrics correlated best to crown biomass. A comparison between above-ground components and total biomass indicate that stem biomass displayed the highest relationship with the LiDAR measurements while crown biomass showed the lowest relationship with relative root mean squared error ranging from 16% to 22%, respectively. Alternatively, the radar-only models indicated that for C-band radar, a combination of HH and VV backscatter demonstrated the most significant correlation with forest biomass compared to coherence based models with a relative root mean squared error of 53%. For L-band radar, a combination of HH and HV backscatter showed the most significant correlation compared to coherence based models with a relative root mean squared error of 44%. Exploring a mixture of C- and L-band backscatter and coherence based models revealed that a combination of C-HV and L-HV coherence magnitudes provided the best radar relationship with forest biomass with a relative root mean squared error of 35%. Also for all radar-based models, L- and C-band backscatter and coherence magnitudes were poorly correlated with individual biomass components when compared to total above-ground biomass. The addition of C- and L-band backscatter and coherence variables to the Li

  19. Estimating Consumption to Biomass Ratio in Non-Stationary Harvested Fish Populations.

    PubMed

    Wiff, Rodrigo; Roa-Ureta, Ruben H; Borchers, David L; Milessi, Andrés C; Barrientos, Mauricio A

    2015-01-01

    The food consumption to biomass ratio (C) is one of the most important population parameters in ecosystem modelling because its quantifies the interactions between predator and prey. Existing models for estimating C in fish populations are per-recruit cohort models or empirical models, valid only for stationary populations. Moreover, empirical models lack theoretical support. Here we develop a theory and derive a general modelling framework to estimate C in fish populations, based on length frequency data and the generalised von Bertalanffy growth function, in which models for stationary populations with a stable-age distributions are special cases. Estimates using our method are compared with estimates from per-recruit cohort models for C using simulated harvested fish populations of different lifespans. The models proposed here are also applied to three fish populations that are targets of commercial fisheries in southern Chile. Uncertainty in the estimation of C was evaluated using a resampling approach. Simulations showed that stationary and non-stationary population models produce different estimates for C and those differences depend on the lifespan, fishing mortality and recruitment variations. Estimates of C using the new model exhibited smoother inter-annual variation in comparison with a per-recruit model estimates and they were also smaller than C predicted by the empirical equations in all population assessed. PMID:26528721

  20. Estimating Consumption to Biomass Ratio in Non-Stationary Harvested Fish Populations

    PubMed Central

    Wiff, Rodrigo; Roa-Ureta, Ruben H.; Borchers, David L.; Milessi, Andrés C.; Barrientos, Mauricio A.

    2015-01-01

    The food consumption to biomass ratio (C) is one of the most important population parameters in ecosystem modelling because its quantifies the interactions between predator and prey. Existing models for estimating C in fish populations are per-recruit cohort models or empirical models, valid only for stationary populations. Moreover, empirical models lack theoretical support. Here we develop a theory and derive a general modelling framework to estimate C in fish populations, based on length frequency data and the generalised von Bertalanffy growth function, in which models for stationary populations with a stable-age distributions are special cases. Estimates using our method are compared with estimates from per-recruit cohort models for C using simulated harvested fish populations of different lifespans. The models proposed here are also applied to three fish populations that are targets of commercial fisheries in southern Chile. Uncertainty in the estimation of C was evaluated using a resampling approach. Simulations showed that stationary and non-stationary population models produce different estimates for C and those differences depend on the lifespan, fishing mortality and recruitment variations. Estimates of C using the new model exhibited smoother inter-annual variation in comparison with a per-recruit model estimates and they were also smaller than C predicted by the empirical equations in all population assessed. PMID:26528721

  1. Estimating spatial variation in Alberta forest biomass from a combination of forest inventory and remote sensing data

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Huang, S.; Hogg, E. H.; Lieffers, V.; Qin, Y.; He, F.

    2014-05-01

    Uncertainties in the estimation of tree biomass carbon storage across large areas pose challenges for the study of forest carbon cycling at regional and global scales. In this study, we attempted to estimate the present aboveground biomass (AGB) in Alberta, Canada, by taking advantage of a spatially explicit data set derived from a combination of forest inventory data from 1968 plots and spaceborne light detection and ranging (lidar) canopy height data. Ten climatic variables, together with elevation, were used for model development and assessment. Four approaches, including spatial interpolation, non-spatial and spatial regression models, and decision-tree-based modeling with random forests algorithm (a machine-learning technique), were compared to find the "best" estimates. We found that the random forests approach provided the best accuracy for biomass estimates. Non-spatial and spatial regression models gave estimates similar to random forests, while spatial interpolation greatly overestimated the biomass storage. Using random forests, the total AGB stock in Alberta forests was estimated to be 2.26 × 109 Mg (megagram), with an average AGB density of 56.30 ± 35.94 Mg ha-1. At the species level, three major tree species, lodgepole pine, trembling aspen and white spruce, stocked about 1.39 × 109 Mg biomass, accounting for nearly 62% of total estimated AGB. Spatial distribution of biomass varied with natural regions, land cover types, and species. Furthermore, the relative importance of predictor variables on determining biomass distribution varied with species. This study showed that the combination of ground-based inventory data, spaceborne lidar data, land cover classification, and climatic and environmental variables was an efficient way to estimate the quantity, distribution and variation of forest biomass carbon stocks across large regions.

  2. Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms, volume 2. [Oklahoma and Texas

    NASA Technical Reports Server (NTRS)

    Rosenthal, W. D.; Mcfarland, M. J.; Theis, S. W.; Jones, C. L. (Principal Investigator)

    1982-01-01

    Agricultural crop classification models using two or more spectral regions (visible through microwave) were developed and tested and biomass was estimated by including microwave with visible and infrared data. The study was conducted at Guymon, Oklahoma and Dalhart, Texas utilizing aircraft multispectral data and ground truth soil moisture and biomass information. Results indicate that inclusion of C, L, and P band active microwave data from look angles greater than 35 deg from nadir with visible and infrared data improved crop discrimination and biomass estimates compared to results using only visible and infrared data. The active microwave frequencies were sensitive to different biomass levels. In addition, two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass.

  3. [Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite].

    PubMed

    Yu, Chao; Chen, Liang-fu; Li, Shen-shen; Tao, Jin-hua; Su, Lin

    2015-03-01

    Biomass burning makes up an important part of both trace gases and particulate matter emissions, which can efficiently degrade air quality and reduce visibility, destabilize the global climate system at regional to global scales. Burned area is one of the primary parameters necessary to estimate emissions, and considered to be the largest source of error in the emission inventory. Satellite-based fire observations can offer a reliable source of fire occurrence data on regional and global scales, a variety of sensors have been used to detect and map fires in two general approaches: burn scar mapping and active fire detection. However, both of the two approaches have limitations. In this article, we explore the relationship between hotspot data and burned area for the Southeastern United States, where a significant amount of biomass burnings from both prescribed and wild fire took place. MODIS (Moderate resolution imaging spectrometer) data, which has high temporal-resolution, can be used to monitor ground biomass. burning in time and provided hot spot data in this study. However, pixel size of MODIS hot spot can't stand for the real ground burned area. Through analysis of the variation of vegetation band reflectance between pre- and post-burn, we extracted the burned area from Landsat-5 TM (Thematic Mapper) images by using the differential normalized burn ratio (dNBR) which is based on TM band4 (0.84 μm) and TM band 7(2.22 μm) data. We combined MODIS fire hot spot data and Landsat-5 TM burned scars data to build the burned area estimation model, results showed that the linear correlation coefficient is 0.63 and the relationships vary as a function of vegetation cover. Based on the National Land Cover Database (NLCD), we built burned area estimation model over different vegetation cover, and got effective burned area per fire pixel, values for forest, grassland, shrub, cropland and wetland are 0.69, 1.27, 0.86, 0.72 and 0.94 km2 respectively. We validated the

  4. Estimating DNA coverage and abundance in metagenomes using a gamma approximation

    PubMed Central

    Hooper, Sean D.; Dalevi, Daniel; Pati, Amrita; Mavromatis, Konstantinos; Ivanova, Natalia N.; Kyrpides, Nikos C.

    2010-01-01

    Motivation: Shotgun sequencing generates large numbers of short DNA reads from either an isolated organism or, in the case of metagenomics projects, from the aggregate genome of a microbial community. These reads are then assembled based on overlapping sequences into larger, contiguous sequences (contigs). The feasibility of assembly and the coverage achieved (reads per nucleotide or distinct sequence of nucleotides) depend on several factors: the number of reads sequenced, the read length and the relative abundances of their source genomes in the microbial community. A low coverage suggests that most of the genomic DNA in the sample has not been sequenced, but it is often difficult to estimate either the extent of the uncaptured diversity or the amount of additional sequencing that would be most efficacious. In this work, we regard a metagenome as a population of DNA fragments (bins), each of which may be covered by one or more reads. We employ a gamma distribution to model this bin population due to its flexibility and ease of use. When a gamma approximation can be found that adequately fits the data, we may estimate the number of bins that were not sequenced and that could potentially be revealed by additional sequencing. We evaluated the performance of this model using simulated metagenomes and demonstrate its applicability on three recent metagenomic datasets. Contact: sean.d.hooper@genpat.uu.se Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20008478

  5. Estimating DNA coverage and abundance in metagenomes using a gamma approximation

    SciTech Connect

    Hooper, Sean D; Dalevi, Daniel; Pati, Amrita; Mavromatis, Konstantinos; Ivanova, Natalia N; Kyrpides, Nikos C

    2010-01-01

    Shotgun sequencing generates large numbers of short DNA reads from either an isolated organism or, in the case of metagenomics projects, from the aggregate genome of a microbial community. These reads are then assembled based on overlapping sequences into larger, contiguous sequences (contigs). The feasibility of assembly and the coverage achieved (reads per nucleotide or distinct sequence of nucleotides) depend on several factors: the number of reads sequenced, the read length and the relative abundances of their source genomes in the microbial community. A low coverage suggests that most of the genomic DNA in the sample has not been sequenced, but it is often difficult to estimate either the extent of the uncaptured diversity or the amount of additional sequencing that would be most efficacious. In this work, we regard a metagenome as a population of DNA fragments (bins), each of which may be covered by one or more reads. We employ a gamma distribution to model this bin population due to its flexibility and ease of use. When a gamma approximation can be found that adequately fits the data, we may estimate the number of bins that were not sequenced and that could potentially be revealed by additional sequencing. We evaluated the performance of this model using simulated metagenomes and demonstrate its applicability on three recent metagenomic datasets.

  6. Statistical Estimates of the Long-Term Impact of Land-Use Disturbance on Woody Biomass in the Midwest (USA)

    NASA Astrophysics Data System (ADS)

    McLachlan, J. S.; Moore, D. J.; Zhu, J.; Feng, X.; Paciorek, C. J.; Williams, J. W.; Goring, S. J.; Hartfield, K. A.

    2014-12-01

    The impact on carbon balance of land-use transformations in eastern North America since the time of Euroamerican settlement is important at the global scale. And yet, our understanding of the baseline conditions of pre-settlement vegetation is generally weak. Many estimates of terrestrial carbon pools before Euroamerican settlement are based on hypothetical potential vegetation, and even data-derived estimates of biomass do not have statistical estimates of uncertainty. We fit a spatial statistical model to forest survey (PLS) data from the time of settlement across Midwesterm states from Minnesota to Indiana. Our spatial model scales diameter data from the PLS surveys by standard allometries to produce maps at 8km resolution of biomass with associated uncertainty for all major tree taxa and plant functional types and for total woody biomass. General trends in biomass are consistent with previous estimates, but fine scale heterogeneity is more revealed in our biomass product. A full accounting of uncertainty in settlement-era biomass allows us to assess the extent to which biomass has recovered across a vegetation gradient from subboreal forests to oak savannas and prairies and across land-use histories ranging from preserved old-growth forests through areas reforesting after intensive logging and agriculture to areas currently experiencing a range of intensive human activity.

  7. Estimation of potential biomass resource and biogas production from aquatic plants in Argentina

    NASA Astrophysics Data System (ADS)

    Fitzsimons, R. E.; Laurino, C. N.; Vallejos, R. H.

    1982-08-01

    The use of aquatic plants in artificial lakes as a biomass source for biogas and fertilizer production through anaerobic fermentation is evaluated, and the magnitude of this resource and the potential production of biogas and fertilizer are estimated. The specific case considered is the artificial lake that will be created by the construction of Parana Medio Hydroelectric Project on the middle Parana River in Argentina. The growth of the main aquatic plant, water hyacinth, on the middle Parana River has been measured, and its conversion to methane by anaerobic fermentation is determined. It is estimated that gross methane production may be between 1.0-4.1 x 10 to the 9th cu cm/year. The fermentation residue can be used as a soil conditioner, and it is estimated production of the residue may represent between 54,900-221,400 tons of nitrogen/year, a value which is 2-8 times the present nitrogen fertilizer demand in Argentina.

  8. Mid-Term Status of the Forest Dragon III: Data Collection and Regional Aboveground Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Pang, Yong; Li, Zengyuan; Liu, Luxia; Lu, Hao; Jia, Wen; Liu, Qingwang; Tian, Xin; Zhang, Ruiying; Shmullius, Christiana

    2014-11-01

    In the 1st two years of Forest Dragon 3 project, Chinese groups engaged in following activities: 1) field measurements and airborne campaigns for forest map validation, 2) regional forest aboveground biomass (AGB) estimation algorithm development and map generation. The AGB estimation by fusion multisensor fusion was investigated. Two campaigns consist of in-situ observation, airborne flight and spaceborne measurements were designed and implemented in the Heilongjiang Province and Yunnan Province of China. The Heilongjiang Province is located in Northeast China and has typical temperate forest. The Yunnan Province is located in Southwest China and contains multiple forest types including tropical forest. By using these observation data from different scales, multi-source satellite data were used to estimate spatial explicit AGB for Da Xinganling study area.

  9. Estimated Rock Abundance and Thermophysical Parameters in Oppenheimer Crater on the Moon

    NASA Astrophysics Data System (ADS)

    Bauch, Karin E.; Hiesinger, Harald; Ivanov, Mikhail; van der Bogert, Carolyn H.; Pasckert, Jan-Hendrik; Weinauer, Julia

    2016-04-01

    Oppenheimer crater is located in the north-east of the South Pole-Aitken basin (SPA), the largest impact structure on the Moon [e.g., 1]. The crater is ˜215km in diameter and has an estimated age of ˜4.1 Ga [2]. The floor of Oppenheimer shows evidence of dark mantling deposits and a concentric system of graben structures close to the rim of the crater [3]. Image and topography data show that the floor is flat apart from the graben structures and subsequent impacts on the floor. Oppenheimer-U (˜40km) and -H (˜35km) are floor-fractured craters within the north-west and south-east portions of Oppenheimer crater [3]. Dark mantling deposits on the floor are associated with the graben system. [3] estimated an age between ˜3.98Ga and ˜3.66Ga for the pyroclastic activity, based on crater size-frequency distribution (CSFD) measurements on Lunar Reconnaissance Orbiter (LRO) WAC and NAC images. In this study we compare the mapping results of [3] with temperature data of the LRO Diviner experiment [4] using a numerical model [5, 6]. Nighttime temperature variations are directly influenced by the surface and subsurface thermophysical properties, namely bulk density, heat capacity, and thermal conductivity [7, 8]. These properties can be summarized to a thermal inertia, which represents the ability to conduct and store heat [8]. Low thermal inertia units, such as dust and other fine grained material, quickly respond to temperature changes, which results in large temperature amplitudes between the lunar day and night. On the other hand, high thermal inertia material, e.g. rocks or bedrock, take more time to heat up during the day and reradiate the heat during the night [8]. Relative rock abundances are derived from temperature measurements of the same location at different wavelengths. Brightness temperatures are a function of wavelength and increase with decreasing wavelength [9, 10]. This nonlinearity of the Planck radiance can be used to determine the amount of

  10. Simultaneously Sparse and Low-Rank Abundance Matrix Estimation for Hyperspectral Image Unmixing

    NASA Astrophysics Data System (ADS)

    Giampouras, Paris V.; Themelis, Konstantinos E.; Rontogiannis, Athanasios A.; Koutroumbas, Konstantinos D.

    2016-08-01

    In a plethora of applications dealing with inverse problems, e.g. in image processing, social networks, compressive sensing, biological data processing etc., the signal of interest is known to be structured in several ways at the same time. This premise has recently guided the research to the innovative and meaningful idea of imposing multiple constraints on the parameters involved in the problem under study. For instance, when dealing with problems whose parameters form sparse and low-rank matrices, the adoption of suitably combined constraints imposing sparsity and low-rankness, is expected to yield substantially enhanced estimation results. In this paper, we address the spectral unmixing problem in hyperspectral images. Specifically, two novel unmixing algorithms are introduced, in an attempt to exploit both spatial correlation and sparse representation of pixels lying in homogeneous regions of hyperspectral images. To this end, a novel convex mixed penalty term is first defined consisting of the sum of the weighted $\\ell_1$ and the weighted nuclear norm of the abundance matrix corresponding to a small area of the image determined by a sliding square window. This penalty term is then used to regularize a conventional quadratic cost function and impose simultaneously sparsity and row-rankness on the abundance matrix. The resulting regularized cost function is minimized by a) an incremental proximal sparse and low-rank unmixing algorithm and b) an algorithm based on the alternating minimization method of multipliers (ADMM). The effectiveness of the proposed algorithms is illustrated in experiments conducted both on simulated and real data.

  11. Acoustic estimates of abundance and distribution of spawning lake trout on Sheboygan Reef in Lake Michigan

    USGS Publications Warehouse

    Warner, D.M.; Claramunt, R.M.; Janssen, J.; Jude, D.J.; Wattrus, N.

    2009-01-01

    Efforts to restore self-sustaining lake trout (Salvelinus namaycush) populations in the Laurentian Great Lakes have had widespread success in Lake Superior; but in other Great Lakes, populations of lake trout are maintained by stocking. Recruitment bottlenecks may be present at a number of stages of the reproduction process. To study eggs and fry, it is necessary to identify spawning locations, which is difficult in deep water. Acoustic sampling can be used to rapidly locate aggregations of fish (like spawning lake trout), describe their distribution, and estimate their abundance. To assess these capabilities for application to lake trout, we conducted an acoustic survey covering 22 km2 at Sheboygan Reef, a deep reef (<40 m summit) in southern Lake Michigan during fall 2005. Data collected with remotely operated vehicles (ROV) confirmed that fish were large lake trout, that lake trout were 1–2 m above bottom, and that spawning took place over specific habitat. Lake trout density exhibited a high degree of spatial structure (autocorrelation) up to a range of ~190 m, and highest lake trout and egg densities occurred over rough substrates (rubble and cobble) at the shallowest depths sampled (36–42 m). Mean lake trout density in the area surveyed (~2190 ha) was 5.8 fish/ha and the area surveyed contained an estimated 9500–16,000 large lake trout. Spatial aggregation in lake trout densities, similarity of depths and substrates at which high lake trout and egg densities occurred, and relatively low uncertainty in the lake trout density estimate indicate that acoustic sampling can be a useful complement to other sampling tools used in lake trout restoration research.

  12. Effects of soil tillage and management of crop residues on soil properties: abundance, biomass and diversity of earthworms, soil structure and nutrient evolutions

    NASA Astrophysics Data System (ADS)

    lemtiri, Aboulkacem

    2013-04-01

    The living soil is represented by soil biota that interacts with aboveground biota and with the abiotic environment, soil structure, soil reaction, organic matter, nutrient contents, aso. Maintenance of soil organic matter through integrated soil fertility management is an important issue to conciliate soil quality and agricultural productivity. Earthworms are key actors in soil structure formation through the production of casts and the incorporation of soil organic matter in the soil. Research is still needed about the interactive effects of various tillage and crop residue management practices on earthworm populations and physical and chemical properties of soil. To investigate the impacts of two tillage management systems and two cropping systems on earthworm populations, soil structure evolution and nutrient dynamics, we carried out a three years study in an experimental field. The aims of this experimentation, were to assess the effects of the tillage systems (ploughing versus reduced tillage) and the availability of crop residues (export versus no export) on (i) the abundance, biomass and diversity of earthworms, on the soil structure and on the temporal variation of water extractable nutrients and organic carbon. The first results show that tillage management did significantly affect earthworm abundance and biomass. However, crop residue management did not affect abundance, biomass and diversity of earthworms. Regarding soil physical properties, the tillage affected the compaction profiles within the top 30cm. The analysis of nutrient and organic carbon dynamics show divergent trends (decrease of calcium and magnesium, increase of hot water extractable carbon and phosphorus…) but no clear effect of the studied factors could be identified. The question of the initial soil variability raised as a crucial point in the discussion.

  13. Consideraciones para la estimacion de abundancia de poblaciones de mamiferos. [Considerations for the estimation of abundance of mammal populations.

    USGS Publications Warehouse

    Walker, R.S.; Novare, A.J.; Nichols, J.D.

    2000-01-01

    Estimation of abundance of mammal populations is essential for monitoring programs and for many ecological investigations. The first step for any study of variation in mammal abundance over space or time is to define the objectives of the study and how and why abundance data are to be used. The data used to estimate abundance are count statistics in the form of counts of animals or their signs. There are two major sources of uncertainty that must be considered in the design of the study: spatial variation and the relationship between abundance and the count statistic. Spatial variation in the distribution of animals or signs may be taken into account with appropriate spatial sampling. Count statistics may be viewed as random variables, with the expected value of the count statistic equal to the true abundance of the population multiplied by a coefficient p. With direct counts, p represents the probability of detection or capture of individuals, and with indirect counts it represents the rate of production of the signs as well as their probability of detection. Comparisons of abundance using count statistics from different times or places assume that the p are the same for all times or places being compared (p= pi). In spite of considerable evidence that this assumption rarely holds true, it is commonly made in studies of mammal abundance, as when the minimum number alive or indices based on sign counts are used to compare abundance in different habitats or times. Alternatives to relying on this assumption are to calibrate the index used by testing the assumption of p= pi, or to incorporate the estimation of p into the study design.

  14. Estimation and Mapping of Coastal Mangrove Biomass Using Both Passive and Active Remote Sensing Method

    NASA Astrophysics Data System (ADS)

    Yiqiong, L.; Lu, W.; Zhou, J.; Gan, W.; Cui, X.; Lin, G., Sr.

    2015-12-01

    Mangrove forests play an important role in global carbon cycle, but carbon stocks in different mangrove forests are not easily measured at large scale. In this research, both active and passive remote sensing methods were used to estimate the aboveground biomass of dominant mangrove communities in Zhanjiang National Mangrove Nature Reserve in Guangdong, China. We set up a decision tree including spectral, texture, position and geometry indexes to achieve mangrove inter-species classification among 5 main species named Aegiceras corniculatum, Aricennia marina, Bruguiera gymnorrhiza, Kandelia candel, Sonneratia apetala by using 5.8m multispectral ZY-3 images. In addition, Lidar data were collected and used to obtain the canopy height of different mangrove species. Then, regression equations between the field measured aboveground biomass and the canopy height deduced from Lidar data were established for these mangrove species. By combining these results, we were able to establish a relatively accurate method for differentiating mangrove species and mapping their aboveground biomass distribution at the estuary scale, which could be applied to mangrove forests in other regions.

  15. Satellite Estimates of the Direct Radiative Forcing of Biomass Burning Aerosols Over South America and Africa

    NASA Technical Reports Server (NTRS)

    Christopher, Sundar A.; Wang, Min; Kliche, Donna V.; Berendes, Todd; Welch, Ronald M.; Yang, S.K.

    1997-01-01

    Atmospheric aerosol particles, both natural and anthropogenic are important to the earth's radiative balance. Therefore it is important to provide adequate validation information on the spatial, temporal and radiative properties of aerosols. This will enable us to predict realistic global estimates of aerosol radiative effects more confidently. The current study utilizes 66 AVHRR LAC (Local Area Coverage) and coincident Earth Radiation Budget Experiment (ERBE) images to characterize the fires, smoke and radiative forcings of biomass burning aerosols over four major ecosystems of South America.

  16. Beyond Radar Backscatter: Estimating Forest Structure and Biomass with Radar Interferometry and Lidar Remote Sensing

    NASA Astrophysics Data System (ADS)

    Lavalle, M.; Ahmed, R.

    2014-12-01

    Mapping forest structure and aboveground biomass globally is a major challenge that the remote sensing community has been facing for decades. Radar backscatter is sensitive to biomass only up to a certain amount (about 150 tons/ha at L-band and 300 tons/ha at P-band), whereas lidar remote sensing is strongly limited by poor spatial coverage. In recent years radar interferometry, including its extension to polarimetric radar interferometry (PolInSAR), has emerged as a new technique to overcome the limitations of radar backscatter. The idea of PolInSAR is to use jointly interferometric and polarimetric radar techniques to separate different scattering mechanisms and retrieve the vertical structure of forests. The advantage is to map ecosystem structure continuously over large areas and independently of cloud coverage. Experiments have shown that forest height - an important proxy for biomass - can be estimated using PolInSAR with accuracy between 15% and 20% at plot level. At AGU we will review the state-of-art of repeat-pass PolInSAR for biomass mapping, including its potential and limitations, and discuss how merging lidar data with PolInSAR data can be beneficial not only for product cross-validation but also for achieving better estimation of ecosystem properties over large areas. In particular, lidar data are expected to aid the inversion of PolInSAR models by providing (1) better identification of ground under the canopy, (2) approximate information of canopy structure in limited areas, and (3) maximum tree height useful for mapping PolInSAR temporal decorrelation. We will show our tree height and biomass maps using PolInSAR L-band JPL/UAVSAR data collected in tropical and temperate forests, and P-band ONERA/TROPISAR data acquired in French Guiana. LVIS lidar data will be used, as well as SRTM data, field measurements and inventory data to support our study. The use of two different radar frequencies and repeat-pass JPL UAVSAR data will offer also the

  17. Crop biomass and evapotranspiration estimation using SPOT and Formosat-2 Data

    NASA Astrophysics Data System (ADS)

    Veloso, Amanda; Demarez, Valérie; Ceschia, Eric; Claverie, Martin

    2013-04-01

    The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the

  18. Optimal Wavelength Selection on Hyperspectral Data with Fused Lasso for Biomass Estimation of Tropical Rain Forest

    NASA Astrophysics Data System (ADS)

    Takayama, T.; Iwasaki, A.

    2016-06-01

    Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous large-area forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number of training samples is smaller than the dimensionality of the samples due to limitation of require time, cost, and human resources for field surveys. A common approach to addressing this problem is reducing the dimensionality of dataset. Also, acquired hyperspectral data usually have low signal-to-noise ratio due to a narrow bandwidth and local or global shifts of peaks due to instrumental instability or small differences in considering practical measurement conditions. In this work, we propose a methodology based on fused lasso regression that select optimal bands for the biomass prediction model with encouraging sparsity and grouping, which solves the small-sample-size problem by the dimensionality reduction from the sparsity and the noise and peak shift problem by the grouping. The prediction model provided higher accuracy with root-mean-square error (RMSE) of 66.16 t/ha in the cross-validation than other methods; multiple linear analysis, partial least squares regression, and lasso regression. Furthermore, fusion of spectral and spatial information derived from texture index increased the prediction accuracy with RMSE of 62.62 t/ha. This analysis proves efficiency of fused lasso and image texture in biomass estimation of tropical forests.

  19. Effects of sampling conditions on DNA-based estimates of American black bear abundance

    USGS Publications Warehouse

    Laufenberg, Jared S.; Van Manen, Frank T.; Clark, Joseph D.

    2013-01-01

    DNA-based capture-mark-recapture techniques are commonly used to estimate American black bear (Ursus americanus) population abundance (N). Although the technique is well established, many questions remain regarding study design. In particular, relationships among N, capture probability of heterogeneity mixtures A and B (pA and pB, respectively, or p, collectively), the proportion of each mixture (π), number of capture occasions (k), and probability of obtaining reliable estimates of N are not fully understood. We investigated these relationships using 1) an empirical dataset of DNA samples for which true N was unknown and 2) simulated datasets with known properties that represented a broader array of sampling conditions. For the empirical data analysis, we used the full closed population with heterogeneity data type in Program MARK to estimate N for a black bear population in Great Smoky Mountains National Park, Tennessee. We systematically reduced the number of those samples used in the analysis to evaluate the effect that changes in capture probabilities may have on parameter estimates. Model-averaged N for females and males were 161 (95% CI = 114–272) and 100 (95% CI = 74–167), respectively (pooled N = 261, 95% CI = 192–419), and the average weekly p was 0.09 for females and 0.12 for males. When we reduced the number of samples of the empirical data, support for heterogeneity models decreased. For the simulation analysis, we generated capture data with individual heterogeneity covering a range of sampling conditions commonly encountered in DNA-based capture-mark-recapture studies and examined the relationships between those conditions and accuracy (i.e., probability of obtaining an estimated N that is within 20% of true N), coverage (i.e., probability that 95% confidence interval includes true N), and precision (i.e., probability of obtaining a coefficient of variation ≤20%) of estimates using logistic regression. The capture probability

  20. RVC-CAL library for endmember and abundance estimation in hyperspectral image analysis

    NASA Astrophysics Data System (ADS)

    Lazcano López, R.; Madroñal Quintín, D.; Juárez Martínez, E.; Sanz Álvaro, C.

    2015-10-01

    Hyperspectral imaging (HI) collects information from across the electromagnetic spectrum, covering a wide range of wavelengths. Although this technology was initially developed for remote sensing and earth observation, its multiple advantages - such as high spectral resolution - led to its application in other fields, as cancer detection. However, this new field has shown specific requirements; for instance, it needs to accomplish strong time specifications, since all the potential applications - like surgical guidance or in vivo tumor detection - imply real-time requisites. Achieving this time requirements is a great challenge, as hyperspectral images generate extremely high volumes of data to process. Thus, some new research lines are studying new processing techniques, and the most relevant ones are related to system parallelization. In that line, this paper describes the construction of a new hyperspectral processing library for RVC-CAL language, which is specifically designed for multimedia applications and allows multithreading compilation and system parallelization. This paper presents the development of the required library functions to implement two of the four stages of the hyperspectral imaging processing chain--endmember and abundances estimation. The results obtained show that the library achieves speedups of 30%, approximately, comparing to an existing software of hyperspectral images analysis; concretely, the endmember estimation step reaches an average speedup of 27.6%, which saves almost 8 seconds in the execution time. It also shows the existence of some bottlenecks, as the communication interfaces among the different actors due to the volume of data to transfer. Finally, it is shown that the library considerably simplifies the implementation process. Thus, experimental results show the potential of a RVC-CAL library for analyzing hyperspectral images in real-time, as it provides enough resources to study the system performance.

  1. Estimating fresh grass/herb biomass from HYMAP data using the red edge position

    NASA Astrophysics Data System (ADS)

    Cho, Moses A.; Sobhan, Istiak M.; Skidmore, Andrew K.

    2006-08-01

    Remote sensing of grass/herb quantity is essential for rangeland management of livestock and wildlife. Spectral indices such as NDVI, determined from red and near infrared bands are affected by variable soil and atmospheric conditions and saturate in dense vegetation. Alternatively, the wavelength of maximum slope in the red-NIR transition, termed the red edge position (REP) has potential to mitigate these effects. But the utility of the REP using air- and space-borne imagery is determined by the availability of narrow bands in the region of the red edge and the simplicity of the extraction method. Very recently, we proposed a simple technique for extracting the REP called the linear extrapolation method [Cho and Skidmore, Remote Sens. Environ., 101(2006)118.]. The purpose of this study was to evaluate the potential of the linear extrapolation method for estimating fresh grass/herb biomass and compare its performance with the four-point linear interpolation and three-point Lagrangian interpolation methods. The REPs were derived from atmospherically corrected HYMAP images collected over Majella National Park, Italy in July 2004. The predictive capabilities of various REP linear regression models were evaluated using leave-one-out cross validation and test set validation methods. For both validation methods, the linear extrapolation REP models produced higher correlations with grass/herb biomass and lower prediction errors compared with the linear interpolation and Lagrangian REP models. This study demonstrates the potential of REPs extracted by the linear extrapolation method using HYMAP data for estimating fresh grass/herb biomass.

  2. Estimating Vegetative Fuel Loadings and Fuel Moisture Using Satellite Data for Modeling Biomass Burning Emissions

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Kondragunta, S.; Kogan, F.; Tarpley, J. D.; Guo, W.; Wiedinmyer, C.; Schmidt, C.

    2005-12-01

    Biomass burning is the second largest source of aerosols, which affects air quality and the Earth's radiation budget. Because the emissions of aerosols is strongly influenced by factors such as biomass density, combustion efficiency, and burned area, current burning emission estimates are rather imprecise and vary markedly with different methodologies. The aim of this study is to model biomass burning emissions using satellite-derived vegetative fuel loadings, fuel moisture, and burned areas in the USA. For this purpose, we first developed an approach for mapping vegetative fuel loadings using Moderate-Resolution Imaging Spectroradiometer (MODIS) data at a spatial resolution of 1 km. MODIS data used in this study are land cover types, vegetation continuous fields, and a time series of leaf-area index (LAI). The LAI data were used to produce live leaf fuel loadings varying with vegetation types and vegetation fractions. For forest regions, the maximum leaf fuel loading within a year was applied to calculate branch fuel loadings and total tree fuel loadings using tree allometric models. Since fuel combustion efficiency and emission factors are functions of fuel moisture, we then determined weekly fuel moisture categories from AVHRR-based vegetation condition index (VCI). The VCI was calculated by normalizing the NDVI (normalized difference vegetation index) to the difference of the extreme NDVI fluctuations (maximum and minimum) from 1982-2004. This dataset is reliable since it is calibrated using post-launch algorithms and temporally smoothed. Further, we derived sub-pixel fire size from GOES WF-ABBA fire product. This fire product is available at 30 minutes interval. We used all these inputs to estimate aerosols (PM2.5, particulate mass for particles with diameter < 2.5 μ-m) for each individual fire in 2002 across the USA. We will present the algorithm details and the analysis of the derived emissions.

  3. The effect of animal movement on line transect estimates of abundance.

    PubMed

    Glennie, Richard; Buckland, Stephen T; Thomas, Len

    2015-01-01

    Line transect sampling is a distance sampling method for estimating the abundance of wild animal populations. One key assumption of this method is that all animals are detected at their initial location. Animal movement independent of the transect and observer can thus cause substantial bias. We present an analytic expression for this bias when detection within the transect is certain (strip transect sampling) and use simulation to quantify bias when detection falls off with distance from the line (line transect sampling). We also explore the non-linear relationship between bias, detection, and animal movement by varying detectability and movement type. We consider animals that move in randomly orientated straight lines, which provides an upper bound on bias, and animals that are constrained to a home range of random radius. We find that bias is reduced when animal movement is constrained, and bias is considerably smaller in line transect sampling than strip transect sampling provided that mean animal speed is less than observer speed. By contrast, when mean animal speed exceeds observer speed the bias in line transect sampling becomes comparable with, and may exceed, that of strip transect sampling. Bias from independent animal movement is reduced by the observer searching further perpendicular to the transect, searching a shorter distance ahead and by ignoring animals that may overtake the observer from behind. However, when animals move in response to the observer, the standard practice of searching further ahead should continue as the bias from responsive movement is often greater than that from independent movement. PMID:25799206

  4. Bayesian network for estimating the interaction between ecological health and waterfowl abundance

    NASA Astrophysics Data System (ADS)

    Teng, Te Hui; Fang, Wei Ta; Yu, Hwa Lung

    2013-04-01

    The serious decrease of biodiversity which is mainly induced by Habitat disappear is important issue of species field and in the world. The study area chooses Tauyuan County at subtropical area because of the most artificial farm ponds in Taiwan where the total area includes 27 km2. The effectiveness of these ponds is storage and irrigation and also supplies all kinds of environment like refuges for migratory birds, especially for water birds. Due to human development, farm ponds in this city not only suffer from largely disappear recent year, but also lead to the habitat and bird species reduce. Biological research usually contains incomplete and uncertain information, therefore, this study adopts Bayesian Network model to analyze interaction between land use and water birds. The habitat parameters include elevation, urbanization, building area, farm area, reconsolidation, forest area, irrigation area, farm pond area and lawn area; the biological factors have reproductive capacity, habitat condition, hydrological condition and food source. Using this structure can estimate the interaction of spatiotemporal abundance distribution between habitat parameter and biological parameter. In addition, the former results can define all the reasonable relationship of all hidden states and provide decision-makers with reasonable evaluation.

  5. HYDROACOUSTIC ESTIMATES OF ABUNDANCE AND SPATIAL DISTRIBUTION OF PELAGIC PREY FISHES IN WESTERN LAKE SUPERIOR

    EPA Science Inventory

    Lake herring (Coregonus artedi) and rainbow smelt (Osmerus mordax) are a valuable prey resource for the recovering lake trout (Salvelinus namaycush). However, their respective biomasses may be insufficient to support the current predator demand. In August 1977, we assessed the ...

  6. Euphausiid distribution along the Western Antarctic Peninsula—Part A: Development of robust multi-frequency acoustic techniques to identify euphausiid aggregations and quantify euphausiid size, abundance, and biomass

    NASA Astrophysics Data System (ADS)

    Lawson, Gareth L.; Wiebe, Peter H.; Stanton, Timothy K.; Ashjian, Carin J.

    2008-02-01

    Methods were refined and tested for identifying the aggregations of Antarctic euphausiids ( Euphausia spp.) and then estimating euphausiid size, abundance, and biomass, based on multi-frequency acoustic survey data. A threshold level of volume backscattering strength for distinguishing euphausiid aggregations from other zooplankton was derived on the basis of published measurements of euphausiid visual acuity and estimates of the minimum density of animals over which an individual can maintain visual contact with its nearest neighbor. Differences in mean volume backscattering strength at 120 and 43 kHz further served to distinguish euphausiids from other sources of scattering. An inversion method was then developed to estimate simultaneously the mean length and density of euphausiids in these acoustically identified aggregations based on measurements of mean volume backscattering strength at four frequencies (43, 120, 200, and 420 kHz). The methods were tested at certain locations within an acoustically surveyed continental shelf region in and around Marguerite Bay, west of the Antarctic Peninsula, where independent evidence was also available from net and video systems. Inversion results at these test sites were similar to net samples for estimated length, but acoustic estimates of euphausiid density exceeded those from nets by one to two orders of magnitude, likely due primarily to avoidance and to a lesser extent to differences in the volumes sampled by the two systems. In a companion study, these methods were applied to the full acoustic survey data in order to examine the distribution of euphausiids in relation to aspects of the physical and biological environment [Lawson, G.L., Wiebe, P.H., Ashjian, C.J., Stanton, T.K., 2008. Euphausiid distribution along the Western Antarctic Peninsula—Part B: Distribution of euphausiid aggregations and biomass, and associations with environmental features. Deep-Sea Research II, this issue [doi:10.1016/j.dsr2.2007.11.014

  7. Estimation of aboveground woody biomass using HJ-1 and Radarsat-2 data for deciduous forests in Daxing'anling, China

    NASA Astrophysics Data System (ADS)

    Liu, Qian; Yang, Le; Liu, Qinhuo; Li, Jing

    2014-11-01

    Accurate estimation of forest aboveground biomass is important for global carbon budgets and ecosystem change studies. Most algorithms for regional or global aboveground biomass estimation using optical and microwave remote sensing data are based on empirical regression and non-parametric training methods, which require large amount of ground measurements for training and are lacking of explicit interaction mechanisms between electromagnetic wave and vegetation. In this study, we proposed an optical/microwave synergy method based on a coherent polarimetric SAR model to estimate woody biomass. The study area is sparse deciduous forest dominated by birch with understory of shrubs and herbs in Daxing'anling, China. HJ-1, Radarsat-2 images, and field LAI were collected during May to August in 2013, tree biophysical parameters were measured at the field campaign during August to September in 2012. The effects of understory and wet ground were evaluated by introducing the NDVI derived from HJ-1 image and rain rate. Field measured LAI was used as an input to the SAR model to define the scattering and attenuation of the green canopy to the total backscatter. Finally, an logarithmic equation between the backscatter coefficient of direct forest scattering mechanism and woody biomass was generated (R2=0.582). The retrieval results were validated with the ground biomass measurements (RMSE=29.01ton/ha). The results indicated the synergy of optical and microwave remote sensing data based on SAR model has the potential to improve the accuracy of woody biomass estimation.

  8. Canopy Vertical Spatial Scales which Constrain Biomass in a Tropical Forest at the Plot Level: Unifying Lidar and InSAR for Biomass Estimation

    NASA Astrophysics Data System (ADS)

    Treuhaft, R. N.; Goncalves, F. G.; Drake, J. B.; Chapman, B. D.; Dos Santos, J. R.; Dutra, L. V.; Graca, P. M.; Purcell, G. H.

    2009-12-01

    Structural remote sensing of forest biomass, using lidar and/or interferometric synthetic aperture radar (InSAR), often involves regressing field measured biomass against remotely sensed characteristics of the vertical density profile. Because spaceborne lidar or InSAR sensors will estimate structural characteristics averaged at the plot level (0.04-1 hectare), and because tropical forests contain 40% of the Earth’s forested biomass, this study focuses on the scales of vertical characteristics which best correlate with tropical forest biomass. This work suggests that the structural characteristics used in both lidar and InSAR biomass estimation, such as mean height or total height or height of median energy, are based on the behavior of Fourier vertical frequency components of vegetation density near zero frequency; that is, they are very low-spatial frequency characteristics of the vertical vegetation distribution. In this work, we ask which other vertical Fourier frequencies in lidar- or InSAR-produced structure metrics can best correlate with field biomass. Using lidar (LVIS) data from La Selva Biological Station, Costa Rica, taken in 2005, lidar canopy observations are Fourier transformed in the vertical direction to decompose into vertical frequency components. Each baseline of an InSAR observation, the complex coherence, is this Fourier transform of the canopy, if the ground contribution can be neglected. Using the qualitative similarity in vertical profiles seen by lidar, InSAR (at C-band, from AirSAR in 2004), and field measurements in the La Selva data, we produce the equivalent many (1000’s of) InSAR baselines from the lidar data and, using the lidar-simulated InSAR, determine the optimal spatial frequencies—baselines at DESDynI orbital altitudes for InSAR—which would estimate biomass in this wet tropical forest most accurately for either technique. For biomass ranging from 39-490 Mg/ha, regressing field biomass against some function of height

  9. Mark-recapture and mark-resight methods for estimating abundance with remote cameras: a carnivore case study

    USGS Publications Warehouse

    Alanso, Robert S.; McClintock, Brett T.; Lyren, Lisa M.; Boydston, Erin E.; Crooks, Kevin R.

    2015-01-01

    Abundance estimation of carnivore populations is difficult and has prompted the use of non-invasive detection methods, such as remotely-triggered cameras, to collect data. To analyze photo data, studies focusing on carnivores with unique pelage patterns have utilized a mark-recapture framework and studies of carnivores without unique pelage patterns have used a mark-resight framework. We compared mark-resight and mark-recapture estimation methods to estimate bobcat (Lynx rufus) population sizes, which motivated the development of a new "hybrid" mark-resight model as an alternative to traditional methods. We deployed a sampling grid of 30 cameras throughout the urban southern California study area. Additionally, we physically captured and marked a subset of the bobcat population with GPS telemetry collars. Since we could identify individual bobcats with photos of unique pelage patterns and a subset of the population was physically marked, we were able to use traditional mark-recapture and mark-resight methods, as well as the new “hybrid” mark-resight model we developed to estimate bobcat abundance. We recorded 109 bobcat photos during 4,669 camera nights and physically marked 27 bobcats with GPS telemetry collars. Abundance estimates produced by the traditional mark-recapture, traditional mark-resight, and “hybrid” mark-resight methods were similar, however precision differed depending on the models used. Traditional mark-recapture and mark-resight estimates were relatively imprecise with percent confidence interval lengths exceeding 100% of point estimates. Hybrid mark-resight models produced better precision with percent confidence intervals not exceeding 57%. The increased precision of the hybrid mark-resight method stems from utilizing the complete encounter histories of physically marked individuals (including those never detected by a camera trap) and the encounter histories of naturally marked individuals detected at camera traps. This new estimator

  10. Mark-recapture and mark-resight methods for estimating abundance with remote cameras: a carnivore case study.

    PubMed

    Alonso, Robert S; McClintock, Brett T; Lyren, Lisa M; Boydston, Erin E; Crooks, Kevin R

    2015-01-01

    Abundance estimation of carnivore populations is difficult and has prompted the use of non-invasive detection methods, such as remotely-triggered cameras, to collect data. To analyze photo data, studies focusing on carnivores with unique pelage patterns have utilized a mark-recapture framework and studies of carnivores without unique pelage patterns have used a mark-resight framework. We compared mark-resight and mark-recapture estimation methods to estimate bobcat (Lynx rufus) population sizes, which motivated the development of a new "hybrid" mark-resight model as an alternative to traditional methods. We deployed a sampling grid of 30 cameras throughout the urban southern California study area. Additionally, we physically captured and marked a subset of the bobcat population with GPS telemetry collars. Since we could identify individual bobcats with photos of unique pelage patterns and a subset of the population was physically marked, we were able to use traditional mark-recapture and mark-resight methods, as well as the new "hybrid" mark-resight model we developed to estimate bobcat abundance. We recorded 109 bobcat photos during 4,669 camera nights and physically marked 27 bobcats with GPS telemetry collars. Abundance estimates produced by the traditional mark-recapture, traditional mark-resight, and "hybrid" mark-resight methods were similar, however precision differed depending on the models used. Traditional mark-recapture and mark-resight estimates were relatively imprecise with percent confidence interval lengths exceeding 100% of point estimates. Hybrid mark-resight models produced better precision with percent confidence intervals not exceeding 57%. The increased precision of the hybrid mark-resight method stems from utilizing the complete encounter histories of physically marked individuals (including those never detected by a camera trap) and the encounter histories of naturally marked individuals detected at camera traps. This new estimator may be

  11. Closing a gap in tropical forest biomass estimation: accounting for crown mass variation in pantropical allometries

    NASA Astrophysics Data System (ADS)

    Ploton, P.; Barbier, N.; Momo, S. T.; Réjou-Méchain, M.; Boyemba Bosela, F.; Chuyong, G.; Dauby, G.; Droissart, V.; Fayolle, A.; Goodman, R. C.; Henry, M.; Kamdem, N. G.; Katembo Mukirania, J.; Kenfack, D.; Libalah, M.; Ngomanda, A.; Rossi, V.; Sonké, B.; Texier, N.; Thomas, D.; Zebaze, D.; Couteron, P.; Berger, U.; Pélissier, R.

    2015-12-01

    Accurately monitoring tropical forest carbon stocks is an outstanding challenge. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference in the coming years. However, this reference model shows a systematic bias for the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass dataset on 673 trees measured in five tropical countries (101 trees > 100 cm in diameter) and an original dataset of 130 forest plots (1 ha) from central Africa to quantify the error of biomass allometric models at the individual and plot levels when explicitly accounting or not accounting for crown mass variations. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees ≥ 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Accounting for a crown mass proxy in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error from -23-16 to 0-10 %. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by accounting for a crown mass proxy for the largest trees in a stand, thus suggesting that

  12. Investigating the association of fish abundance and biomass with cold-water corals in the deep Northeast Atlantic Ocean using a generalised linear modelling approach

    NASA Astrophysics Data System (ADS)

    Biber, Matthias F.; Duineveld, Gerard C. A.; Lavaleye, Marc S. S.; Davies, Andrew J.; Bergman, Magda J. N.; van den Beld, Inge M. J.

    2014-01-01

    Cold-water corals (CWC) can form complex three-dimensional structures that can support a diverse macro- and megafaunal community. These reef structures provide important biogenic habitats that can act as refuge, feeding, spawning and nursery areas for fish. However, quantitative data assessing the linkage between CWC and fish are scarce. The North Atlantic Ocean is a key region in the worldwide distribution of Lophelia pertusa, which is thought to be the most widespread frame-work forming cold-water coral species in the world. This study examined the relationship between fish and CWC reefs in the northeast Atlantic Ocean by means of video and remotely sensed data from three different CWC communities (Rockall Bank, Hatton Bank and the Belgica Mound Province). Using a tethered camera system, 37 transects were recorded during a period of 8 years. Fish-coral association was investigated using a generalised linear modelling (GLM) approach. Overall, Lepidion eques was the most abundant fish species present (143 ind. ha-1). Other common species were Sigmops bathyphilus (17 ind. ha-1), Synaphobranchus kaupii (15 ind. ha-1), Helicolenus dactylopterus (16 ind. ha-1) and Mora moro (7 ind. ha-1). The highest fish biomass was measured for Lophius piscatorius (26.3 kg ha-1). Other species with a high biomass were Helicolenus dactylopterus (4.3 kg ha-1), Lepidion eques (13.2 kg ha-1) and Mora moro (7.8 kg ha-1). Overall, no significant difference in fish abundance and biomass was found at coral framework habitats compared to non-coral areas. The relationship between fish and coral framework varied among fish species and study site. Fish count and length modelling results showed that terrain variables explain a small proportion of the variation of our data. Depth, coral-framework and terrain rugosity were generally the most important explanatory variables, but this varied with species and study site.

  13. Estimating grassland aboveground biomass using multitemporal MODIS data in the West Songnen Plain, China

    NASA Astrophysics Data System (ADS)

    Li, Fei; Jiang, Lei; Wang, Xufeng; Zhang, Xiaoqiang; Zheng, Jiajia; Zhao, Qianjun

    2013-01-01

    The West Songnen Plain is an ecologically fragile area. The grasslands on the plain have been seriously degraded over the past five decades and this process is continuing. The reliable estimation of grassland aboveground biomass (AGB) provides scientific data for determining the livestock stocking rate on rangeland. AGB is also of considerable significance for biodiversity and environmental protection in this region. Remote sensing is the most effective way to estimate grassland AGB on a regional scale. Multitemporal, remotely sensed data were used for grassland AGB estimation with statistical models and an artificial neural network (ANN), and the accuracy of estimation for these methods was compared. The results demonstrate that the use of multi-temporal remotely sensed data has advantages for grassland AGB estimation, whether with statistical models or ANN methods, compared with single-temporal remotely sensed data, although the ANN had a higher accuracy of estimation for grassland AGB. Finally, the grassland AGB on the Songnen Plain was estimated with the ANN using multitemporal MODIS data. The spatial distribution pattern of grassland AGB showed large variations, and grassland productivity was generally low. The maximum green weight of the grassland AGB was 927.22 g/m2 and was mainly distributed on the northeast of the West Songnen Plain. The minimum green weight of the grassland AGB was 194.82 g/m2 and was mainly distributed on the central and southwestern West Songnen Plain. Most of the areas had medium- and low-yielding grasses. The significant increases of population and livestock number were the primary and direct reasons for the decrease in grassland quality. This study will contribute to policy making for the control of grazing and for biodiversity and environmental protection.

  14. Optimal Atmospheric Correction for Above-Ground Forest Biomass Estimation with the ETM+ Remote Sensor.

    PubMed

    Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon

    2015-01-01

    The reflectance of the Earth's surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE's, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development. PMID:26263996

  15. Optimal Atmospheric Correction for Above-Ground Forest Biomass Estimation with the ETM+ Remote Sensor

    PubMed Central

    Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon

    2015-01-01

    The reflectance of the Earth’s surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE’s, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development. PMID:26263996

  16. Improved estimates of forest vegetation structure and biomass with a LiDAR-optimized sampling design

    NASA Astrophysics Data System (ADS)

    Hawbaker, Todd J.; Keuler, Nicholas S.; Lesak, Adrian A.; Gobakken, Terje; Contrucci, Kirk; Radeloff, Volker C.

    2009-06-01

    LiDAR data are increasingly available from both airborne and spaceborne missions to map elevation and vegetation structure. Additionally, global coverage may soon become available with NASA's planned DESDynI sensor. However, substantial challenges remain to using the growing body of LiDAR data. First, the large volumes of data generated by LiDAR sensors require efficient processing methods. Second, efficient sampling methods are needed to collect the field data used to relate LiDAR data with vegetation structure. In this paper, we used low-density LiDAR data, summarized within pixels of a regular grid, to estimate forest structure and biomass across a 53,600 ha study area in northeastern Wisconsin. Additionally, we compared the predictive ability of models constructed from a random sample to a sample stratified using mean and standard deviation of LiDAR heights. Our models explained between 65 to 88% of the variability in DBH, basal area, tree height, and biomass. Prediction errors from models constructed using a random sample were up to 68% larger than those from the models built with a stratified sample. The stratified sample included a greater range of variability than the random sample. Thus, applying the random sample model to the entire population violated a tenet of regression analysis; namely, that models should not be used to extrapolate beyond the range of data from which they were constructed. Our results highlight that LiDAR data integrated with field data sampling designs can provide broad-scale assessments of vegetation structure and biomass, i.e., information crucial for carbon and biodiversity science.

  17. Estimation of black carbon content for biomass burning aerosols from multi-channel Raman lidar data

    NASA Astrophysics Data System (ADS)

    Talianu, Camelia; Marmureanu, Luminita; Nicolae, Doina

    2015-04-01

    Biomass burning due to natural processes (forest fires) or anthropical activities (agriculture, thermal power stations, domestic heating) is an important source of aerosols with a high content of carbon components (black carbon and organic carbon). Multi-channel Raman lidars provide information on the spectral dependence of the backscatter and extinction coefficients, embedding information on the black carbon content. Aerosols with a high content of black carbon have large extinction coefficients and small backscatter coefficients (strong absorption), while aerosols with high content of organic carbon have large backscatter coefficients (weak absorption). This paper presents a method based on radiative calculations to estimate the black carbon content of biomass burning aerosols from 3b+2a+1d lidar signals. Data is collected at Magurele, Romania, at the cross-road of air masses coming from Ukraine, Russia and Greece, where burning events are frequent during both cold and hot seasons. Aerosols are transported in the free troposphere, generally in the 2-4 km altitude range, and reaches the lidar location after 2-3 days. Optical data are collected between 2011-2012 by a multi-channel Raman lidar and follows the quality assurance program of EARLINET. Radiative calculations are made with libRadTran, an open source radiative model developed by ESA. Validation of the retrievals is made by comparison to a co-located C-ToF Aerosol Mass Spectrometer. Keywords: Lidar, aerosols, biomass burning, radiative model, black carbon Acknowledgment: This work has been supported by grants of the Romanian National Authority for Scientific Research, Programme for Research- Space Technology and Advanced Research - STAR, project no. 39/2012 - SIAFIM, and by Romanian Partnerships in priority areas PNII implemented with MEN-UEFISCDI support, project no. 309/2014 - MOBBE

  18. A likelihood framework for joint estimation of salmon abundance and migratory timing using telemetric mark-recapture

    USGS Publications Warehouse

    Bromaghin, Jeffrey; Gates, Kenneth S.; Palmer, Douglas E.

    2010-01-01

    Many fisheries for Pacific salmon Oncorhynchus spp. are actively managed to meet escapement goal objectives. In fisheries where the demand for surplus production is high, an extensive assessment program is needed to achieve the opposing objectives of allowing adequate escapement and fully exploiting the available surplus. Knowledge of abundance is a critical element of such assessment programs. Abundance estimation using mark—recapture experiments in combination with telemetry has become common in recent years, particularly within Alaskan river systems. Fish are typically captured and marked in the lower river while migrating in aggregations of individuals from multiple populations. Recapture data are obtained using telemetry receivers that are co-located with abundance assessment projects near spawning areas, which provide large sample sizes and information on population-specific mark rates. When recapture data are obtained from multiple populations, unequal mark rates may reflect a violation of the assumption of homogeneous capture probabilities. A common analytical strategy is to test the hypothesis that mark rates are homogeneous and combine all recapture data if the test is not significant. However, mark rates are often low, and a test of homogeneity may lack sufficient power to detect meaningful differences among populations. In addition, differences among mark rates may provide information that could be exploited during parameter estimation. We present a temporally stratified mark—recapture model that permits capture probabilities and migratory timing through the capture area to vary among strata. Abundance information obtained from a subset of populations after the populations have segregated for spawning is jointly modeled with telemetry distribution data by use of a likelihood function. Maximization of the likelihood produces estimates of the abundance and timing of individual populations migrating through the capture area, thus yielding

  19. Prediction intervals: Placing real bounds on regression-based allometric estimates of biomass.

    PubMed

    Ward, Peter J

    2015-07-01

    Biomass allometry studies routinely assume that regression models can be applied across species and sites, and that goodness of fit of a regression model to its derivation dataset indicates both the relevance of the model to a new dataset and the likely error. Assuming that a model is relevant for a new sample, a prediction interval is a useful error measure for stand mass. Prediction coverage tests whether the model and hence the interval are appropriate in the new sample. Data for three similar shrubby species from four similar sites were combined in various ways to test the impact of varying levels of biodiverse heterogeneity on the performance of the four models most commonly used in published biomass studies. No one model performed consistently well predicting new data, and validation checks were not good indicators of prediction coverage. The highly variable results suggest that the common models might contain insufficient variables. Euclidean distance was used to quantify the relative similarity of samples as a possible means of estimating prediction coverage; it proved unsuccessful with these data. PMID:25974741

  20. Initial estimates of mercury emissions to the atmosphere from global biomass burning.

    PubMed

    Friedli, H R; Arellano, A F; Cinnirella, S; Pirrone, N

    2009-05-15

    The average global annual mercury emission estimate from biomass burning (BMB) for 1997-2006 is 675 +/- 240 Mg/year. This is equivalentto 8% of all currently known anthropogenic and natural mercury emissions. By season, the largest global emissions occur in August and September, the lowest during northern winters. The interannual variability is large and region-specific, and responds to drought conditions. During this particular time period, the largest mercury emissions are from tropical and boreal Asia, followed by Africa and South America. They do not coincide with the largest carbon biomass burning emissions, which originate from Africa. Frequently burning grasslands in Africa and Australia, and agricultural waste burning globally, contribute relatively little to the mercury budget The released mercury from BMB is eventually deposited locally and globally and contributes to the formation of toxic bioaccumulating methyl mercury. Furthermore, increasing temperature in boreal regions, where the largest soil mercury pools reside, is expected to exacerbate mercury emission because of more frequent larger, and more intense fires. PMID:19544847

  1. Estimation of aboveground biomass in Mediterranean forests by statistical modelling of ASTER fraction images

    NASA Astrophysics Data System (ADS)

    Fernández-Manso, O.; Fernández-Manso, A.; Quintano, C.

    2014-09-01

    Aboveground biomass (AGB) estimation from optical satellite data is usually based on regression models of original or synthetic bands. To overcome the poor relation between AGB and spectral bands due to mixed-pixels when a medium spatial resolution sensor is considered, we propose to base the AGB estimation on fraction images from Linear Spectral Mixture Analysis (LSMA). Our study area is a managed Mediterranean pine woodland (Pinus pinaster Ait.) in central Spain. A total of 1033 circular field plots were used to estimate AGB from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) optical data. We applied Pearson correlation statistics and stepwise multiple regression to identify suitable predictors from the set of variables of original bands, fraction imagery, Normalized Difference Vegetation Index and Tasselled Cap components. Four linear models and one nonlinear model were tested. A linear combination of ASTER band 2 (red, 0.630-0.690 μm), band 8 (short wave infrared 5, 2.295-2.365 μm) and green vegetation fraction (from LSMA) was the best AGB predictor (Radj2=0.632, the root-mean-squared error of estimated AGB was 13.3 Mg ha-1 (or 37.7%), resulting from cross-validation), rather than other combinations of the above cited independent variables. Results indicated that using ASTER fraction images in regression models improves the AGB estimation in Mediterranean pine forests. The spatial distribution of the estimated AGB, based on a multiple linear regression model, may be used as baseline information for forest managers in future studies, such as quantifying the regional carbon budget, fuel accumulation or monitoring of management practices.

  2. Is the simple auger coring method reliable for below-ground standing biomass estimation in Eucalyptus forest plantations?

    PubMed Central

    Levillain, Joseph; Thongo M'Bou, Armel; Deleporte, Philippe; Saint-André, Laurent; Jourdan, Christophe

    2011-01-01

    Background and Aims Despite their importance for plant production, estimations of below-ground biomass and its distribution in the soil are still difficult and time consuming, and no single reliable methodology is available for different root types. To identify the best method for root biomass estimations, four different methods, with labour requirements, were tested at the same location. Methods The four methods, applied in a 6-year-old Eucalyptus plantation in Congo, were based on different soil sampling volumes: auger (8 cm in diameter), monolith (25 × 25 cm quadrate), half Voronoi trench (1·5 m3) and a full Voronoi trench (3 m3), chosen as the reference method. Key Results With the reference method (0–1m deep), fine-root biomass (FRB, diameter <2 mm) was estimated at 1·8 t ha−1, medium-root biomass (MRB diameter 2–10 mm) at 2·0 t ha−1, coarse-root biomass (CRB, diameter >10 mm) at 5·6 t ha−1 and stump biomass at 6·8 t ha−1. Total below-ground biomass was estimated at 16·2 t ha−1 (root : shoot ratio equal to 0·23) for this 800 tree ha−1 eucalypt plantation density. The density of FRB was very high (0·56 t ha−1) in the top soil horizon (0–3 cm layer) and decreased greatly (0·3 t ha−1) with depth (50–100 cm). Without labour requirement considerations, no significant differences were found between the four methods for FRB and MRB; however, CRB was better estimated by the half and full Voronoi trenches. When labour requirements were considered, the most effective method was auger coring for FRB, whereas the half and full Voronoi trenches were the most appropriate methods for MRB and CRB, respectively. Conclusions As CRB combined with stumps amounted to 78 % of total below-ground biomass, a full Voronoi trench is strongly recommended when estimating total standing root biomass. Conversely, for FRB estimation, auger coring is recommended with a design pattern accounting for the spatial variability of fine-root distribution. PMID

  3. Subtropical Forest Biomass Estimation Using Airborne LiDAR and Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Pang, Yong; Li, Zengyuan

    2016-06-01

    Forests have complex vertical structure and spatial mosaic pattern. Subtropical forest ecosystem consists of vast vegetation species and these species are always in a dynamic succession stages. It is very challenging to characterize the complexity of subtropical forest ecosystem. In this paper, CAF's (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System was used to collect waveform Lidar and hyperspectral data in Puer forest region, Yunnan province in the Southwest of China. The study site contains typical subtropical species of coniferous forest, evergreen broadleaf forest, and some other mixed forests. The hypersectral images were orthorectified and corrected into surface reflectance with support of Lidar DTM product. The fusion of Lidar and hyperspectral can classify dominate forest types. The lidar metrics improved the classification accuracy. Then forest biomass estimation was carried out for each dominate forest types using waveform Lidar data, which get improved than single Lidar data source.

  4. Asteroseismic estimate of helium abundance of a solar analog binary system

    SciTech Connect

    Verma, Kuldeep; Antia, H. M.; Faria, João P.; Monteiro, Mário J. P. F. G.; Basu, Sarbani; Mazumdar, Anwesh; Appourchaux, Thierry; Chaplin, William J.; García, Rafael A.

    2014-08-01

    16 Cyg A and B are among the brightest stars observed by Kepler. What makes these stars more interesting is that they are solar analogs. 16 Cyg A and B exhibit solar-like oscillations. In this work we use oscillation frequencies obtained using 2.5 yr of Kepler data to determine the current helium abundance of these stars. For this we use the fact that the helium ionization zone leaves a signature on the oscillation frequencies and that this signature can be calibrated to determine the helium abundance of that layer. By calibrating the signature of the helium ionization zone against models of known helium abundance, the helium abundance in the envelope of 16 Cyg A is found to lie in the range of 0.231 to 0.251 and that of 16 Cyg B lies in the range of 0.218 to 0.266.

  5. A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS)

    PubMed Central

    2012-01-01

    Background Lidar height data collected by the Geosciences Laser Altimeter System (GLAS) from 2002 to 2008 has the potential to form the basis of a globally consistent sample-based inventory of forest biomass. GLAS lidar return data were collected globally in spatially discrete full waveform “shots,” which have been shown to be strongly correlated with aboveground forest biomass. Relationships observed at spatially coincident field plots may be used to model biomass at all GLAS shots, and well-established methods of model-based inference may then be used to estimate biomass and variance for specific spatial domains. However, the spatial pattern of GLAS acquisition is neither random across the surface of the earth nor is it identifiable with any particular systematic design. Undefined sample properties therefore hinder the use of GLAS in global forest sampling. Results We propose a method of identifying a subset of the GLAS data which can justifiably be treated as a simple random sample in model-based biomass estimation. The relatively uniform spatial distribution and locally arbitrary positioning of the resulting sample is similar to the design used by the US national forest inventory (NFI). We demonstrated model-based estimation using a sample of GLAS data in the US state of California, where our estimate of biomass (211 Mg/hectare) was within the 1.4% standard error of the design-based estimate supplied by the US NFI. The standard error of the GLAS-based estimate was significantly higher than the NFI estimate, although the cost of the GLAS estimate (excluding costs for the satellite itself) was almost nothing, compared to at least US$ 10.5 million for the NFI estimate. Conclusions Global application of model-based estimation using GLAS, while demanding significant consolidation of training data, would improve inter-comparability of international biomass estimates by imposing consistent methods and a globally coherent sample frame. The methods presented here

  6. PALSAR 50 m mosaic data based national level biomass estimation in Cambodia for implementation of REDD+ mechanism.

    PubMed

    Avtar, Ram; Suzuki, Rikie; Takeuchi, Wataru; Sawada, Haruo

    2013-01-01

    Tropical countries like Cambodia require information about forest biomass for successful implementation of climate change mitigation mechanism related to Reducing Emissions from Deforestation and forest Degradation (REDD+). This study investigated the potential of Phased Array-type L-band Synthetic Aperture Radar Fine Beam Dual (PALSAR FBD) 50 m mosaic data to estimate Above Ground Biomass (AGB) in Cambodia. AGB was estimated using a bottom-up approach based on field measured biomass and backscattering (σ(o)) properties of PALSAR data. The relationship between the PALSAR σ(o) HV and HH/HV with field measured biomass was strong with R(2) = 0.67 and 0.56, respectively. PALSAR estimated AGB show good results in deciduous forests because of less saturation as compared to dense evergreen forests. The validation results showed a high coefficient of determination R(2) = 0.61 with RMSE  = 21 Mg/ha using values up to 200 Mg/ha biomass. There were some uncertainties because of the uncertainty in the field based measurement and saturation of PALSAR data. AGB map of Cambodian forests could be useful for the implementation of forest management practices for REDD+ assessment and policies implementation at the national level. PMID:24116012

  7. Above-ground biomass estimation of tuberous bulrush ( Bolboschoenus planiculmis) in mudflats using remotely sensed multispectral image

    NASA Astrophysics Data System (ADS)

    Kim, Ji Yoon; Im, Ran-Young; Do, Yuno; Kim, Gu-Yeon; Joo, Gea-Jae

    2016-03-01

    We present a multivariate regression approach for mapping the spatial distribution of above-ground biomass (AGB) of B. planiculmis using field data and coincident moderate spatial resolution satellite imagery. A total of 232 ground sample plots were used to estimate the biomass distribution in the Nakdong River estuary. Field data were overlain and correlated with digital values from an atmospherically corrected multispectral image (Landsat 8). The AGB distribution was derived using empirical models trained with field-measured AGB data. The final regression model for AGB estimation was composed using the OLI3, OLI4, and OLI7 spectral bands. The Pearson correlation between the observed and predicted biomass was significant (R = 0.84, p < 0.0001). OLI3 made the largest contribution to the final model (relative coefficient value: 53.4%) and revealed a negative relationship with the AGB biomass. The total distribution area of B. planiculmis was 1,922,979 m2. Based on the model estimation, the total AGB had a dry weight (DW) of approximately 298.2 tons. The distribution of high biomass stands (> 200 kg DW/900 m2) constituted approximately 23.91% of the total vegetated area. Our findings suggest the expandability of remotely sensed products to understand the distribution pattern of estuarine plant productivity at the landscape level.

  8. PALSAR 50 m Mosaic Data Based National Level Biomass Estimation in Cambodia for Implementation of REDD+ Mechanism

    PubMed Central

    Avtar, Ram; Suzuki, Rikie; Takeuchi, Wataru; Sawada, Haruo

    2013-01-01

    Tropical countries like Cambodia require information about forest biomass for successful implementation of climate change mitigation mechanism related to Reducing Emissions from Deforestation and forest Degradation (REDD+). This study investigated the potential of Phased Array-type L-band Synthetic Aperture Radar Fine Beam Dual (PALSAR FBD) 50 m mosaic data to estimate Above Ground Biomass (AGB) in Cambodia. AGB was estimated using a bottom-up approach based on field measured biomass and backscattering (σo) properties of PALSAR data. The relationship between the PALSAR σo HV and HH/HV with field measured biomass was strong with R2 = 0.67 and 0.56, respectively. PALSAR estimated AGB show good results in deciduous forests because of less saturation as compared to dense evergreen forests. The validation results showed a high coefficient of determination R2 = 0.61 with RMSE  = 21 Mg/ha using values up to 200 Mg/ha biomass. There were some uncertainties because of the uncertainty in the field based measurement and saturation of PALSAR data. AGB map of Cambodian forests could be useful for the implementation of forest management practices for REDD+ assessment and policies implementation at the national level. PMID:24116012

  9. Abundance of adult horseshoe crabs (Limulus polylphemus) in Delaware Bay estimated from a bay-wide mark-recapture study

    USGS Publications Warehouse

    Smith, D.R.; Millard, M.J.; Eyler, S.

    2006-01-01

    Estimates of the abundance of American horseshoe crabs (Limulus polyphemus) are important to determine egg production and to manage populations for the energetic needs of shorebirds that feed on horseshoe crab eggs. In 2003, over 17,500 horseshoe crabs were tagged and released throughout Delaware Bay, and recaptured crabs came from spawning surveys that were conducted during peak spawning. We used two release cohorts to test for a temporary effect of tagging on spawning behavior and we adjusted the number of releases according to relocation rates from a telemetry study. The abundance estimate was 20 million horseshoe crabs (90% confidence interval: 13-28 million), of which 6.25 million (90% CI: 4.0-8.8 million) were females. The combined harvest rate for Delaware, New Jersey, Virginia, and Maryland in 2003 was 4% (90% CI: 3-6%) of the abundance estimate. Over-wintering of adults in Delaware Bay could explain, in part, differences in estimates from ocean-trawl surveys. Based on fecundity of 88,000 eggs per female, egg production was 5.5??1011 (90% CI: 3.5??1011, 7.7??1011), but egg availability for shorebirds also depended on overlap between horseshoe crab and shorebird migrations, density-dependent bioturbation, and wave-mediated vertical transport.

  10. Techniques and methods for estimating abundance of larval and metamorphosed sea lampreys in Great Lakes tributaries, 1995 to 2001

    USGS Publications Warehouse

    Slade, Jeffrey W.; Adams, Jean V.; Christie, Gavin C.; Cuddy, Douglas W.; Fodale, Michael F.; Heinrich, John W.; Quinlan, Henry R.; Weise, Jerry G.; Weisser, John W.; Young, Robert J.

    2003-01-01

    Before 1995, Great Lakes streams were selected for lampricide treatment based primarily on qualitative measures of the relative abundance of larval sea lampreys, Petromyzon marinus. New integrated pest management approaches required standardized quantitative measures of sea lamprey. This paper evaluates historical larval assessment techniques and data and describes how new standardized methods for estimating abundance of larval and metamorphosed sea lampreys were developed and implemented. These new methods have been used to estimate larval and metamorphosed sea lamprey abundance in about 100 Great Lakes streams annually and to rank them for lampricide treatment since 1995. Implementation of these methods has provided a quantitative means of selecting streams for treatment based on treatment cost and estimated production of metamorphosed sea lampreys, provided managers with a tool to estimate potential recruitment of sea lampreys to the Great Lakes and the ability to measure the potential consequences of not treating streams, resulting in a more justifiable allocation of resources. The empirical data produced can also be used to simulate the impacts of various control scenarios.

  11. Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material.

    PubMed

    Thomas, Austen C; Deagle, Bruce E; Eveson, J Paige; Harsch, Corie H; Trites, Andrew W

    2016-05-01

    DNA metabarcoding is a powerful new tool allowing characterization of species assemblages using high-throughput amplicon sequencing. The utility of DNA metabarcoding for quantifying relative species abundances is currently limited by both biological and technical biases which influence sequence read counts. We tested the idea of sequencing 50/50 mixtures of target species and a control species in order to generate relative correction factors (RCFs) that account for multiple sources of bias and are applicable to field studies. RCFs will be most effective if they are not affected by input mass ratio or co-occurring species. In a model experiment involving three target fish species and a fixed control, we found RCFs did vary with input ratio but in a consistent fashion, and that 50/50 RCFs applied to DNA sequence counts from various mixtures of the target species still greatly improved relative abundance estimates (e.g. average per species error of 19 ± 8% for uncorrected vs. 3 ± 1% for corrected estimates). To demonstrate the use of correction factors in a field setting, we calculated 50/50 RCFs for 18 harbour seal (Phoca vitulina) prey species (RCFs ranging from 0.68 to 3.68). Applying these corrections to field-collected seal scats affected species percentages from individual samples (Δ 6.7 ± 6.6%) more than population-level species estimates (Δ 1.7 ± 1.2%). Our results indicate that the 50/50 RCF approach is an effective tool for evaluating and correcting biases in DNA metabarcoding studies. The decision to apply correction factors will be influenced by the feasibility of creating tissue mixtures for the target species, and the level of accuracy needed to meet research objectives. PMID:26602877

  12. Investigating Appropriate Sampling Design for Estimating Above-Ground Biomass in Bruneian Lowland Mixed Dipterocarp Forest

    NASA Astrophysics Data System (ADS)

    Lee, S.; Lee, D.; Abu Salim, K.; Yun, H. M.; Han, S.; Lee, W. K.; Davies, S. J.; Son, Y.

    2014-12-01

    Mixed tropical forest structure is highly heterogeneous unlike plantation or mixed temperate forest structure, and therefore, different sampling approaches are required. However, the appropriate sampling design for estimating the above-ground biomass (AGB) in Bruneian lowland mixed dipterocarp forest (MDF) has not yet been fully clarified. The aim of this study was to provide supportive information in sampling design for Bruneian forest carbon inventory. The study site was located at Kuala Belalong lowland MDF, which is part of the Ulu Tembulong National Park, Brunei Darussalam. Six 60 m × 60 m quadrats were established, separated by a distance of approximately 100 m and each was subdivided into quadrats of 10 m × 10 m, at an elevation between 200 and 300 m above sea level. At each plot all free-standing trees with diameter at breast height (dbh) ≥ 1 cm were measured. The AGB for all trees with dbh ≥ 10 cm was estimated by allometric models. In order to analyze changes in the diameter-dependent parameters used for estimating the AGB, different quadrat areas, ranging from 10 m × 10 m to 60 m × 60 m, were used across the study area, starting at the South-West end and moving towards the North-East end. The derived result was as follows: (a) Big trees (dbh ≥ 70 cm) with sparse distribution have remarkable contribution to the total AGB in Bruneian lowland MDF, and therefore, special consideration is required when estimating the AGB of big trees. Stem number of trees with dbh ≥ 70 cm comprised only 2.7% of all trees with dbh ≥ 10 cm, but 38.5% of the total AGB. (b) For estimating the AGB of big trees at the given acceptable limit of precision (p), it is more efficient to use large quadrats than to use small quadrats, because the total sampling area decreases with the former. Our result showed that 239 20 m × 20 m quadrats (9.6 ha in total) were required, while 15 60 m × 60 m quadrats (5.4 ha in total) were required when estimating the AGB of the trees

  13. Estimation of crops biomass and evapotranspiration from high spatial and temporal resolutions remote sensing data

    NASA Astrophysics Data System (ADS)

    Claverie, Martin; Demarez, Valérie; Duchemin, Benoît.; Ceschia, Eric; Hagolle, Olivier; Ducrot, Danielle; Keravec, Pascal; Beziat, Pierre; Dedieu, Pierre

    2010-05-01

    Carbon and water cycles are closely related to agricultural activities. Agriculture has been indeed identified by IPCC 2007 report as one of the options to sequester carbon in soil. Concerning the water resources, their consumptions by irrigated crops are called into question in view of demographic pressure. In the prospect of an assessment of carbon production and water consumption, the use of crop models at a regional scale is a challenging issue. The recent availability of high spatial resolution (10 m) optical sensors associated to high temporal resolution (1 day) such as FORMOSAT-2 and, in the future, Venµs and SENTINEL-2 will offer new perspectives for agricultural monitoring. In this context, the objective of this work is to show how multi-temporal satellite observations acquired at high spatial resolution are useful for a regional monitoring of following crops biophysical variables: leaf area index (LAI), aboveground biomass (AGB) and evapotranspiration (ET). This study focuses on three summer crops dominant in South-West of France: maize, sunflower and soybean. A unique images data set (82 FORMOSAT-2 images over four consecutive years, 2006-2009) was acquired for this project. The experimental data set includes LAI and AGB measurements over eight agricultural fields. Two fields were intensively monitored where ET flux were measured with a 30 minutes time step using eddy correlation methods. The modelisation approach is based on FAO-56 method coupled with a vegetation functioning model based on Monteith theory: the SAFY model [5]. The model operates at a daily time step model to provide estimates of plant characteristics (LAI, AGB), soil conditions (soil water content) and water use (ET). As a key linking variable, LAI is deduced from FORMOSAT-2 reflectances images, and then introduced into the SAFY model to provide spatial and temporal estimates of these biophysical variables. Most of the SAFY parameters are crop related and have been fixed according to

  14. Estimation of occupancy, breeding success, and predicted abundance of golden eagles (Aquila chrysaetos) in the Diablo Range, California, 2014

    USGS Publications Warehouse

    Wiens, J. David; Kolar, Patrick S.; Fuller, Mark R.; Hunt, W. Grainger; Hunt, Teresa

    2015-01-01

    We used a multistate occupancy sampling design to estimate occupancy, breeding success, and abundance of territorial pairs of golden eagles (Aquila chrysaetos) in the Diablo Range, California, in 2014. This method uses the spatial pattern of detections and non-detections over repeated visits to survey sites to estimate probabilities of occupancy and successful reproduction while accounting for imperfect detection of golden eagles and their young during surveys. The estimated probability of detecting territorial pairs of golden eagles and their young was less than 1 and varied with time of the breeding season, as did the probability of correctly classifying a pair’s breeding status. Imperfect detection and breeding classification led to a sizeable difference between the uncorrected, naïve estimate of the proportion of occupied sites where successful reproduction was observed (0.20) and the model-based estimate (0.30). The analysis further indicated a relatively high overall probability of landscape occupancy by pairs of golden eagles (0.67, standard error = 0.06), but that areas with the greatest occupancy and reproductive potential were patchily distributed. We documented a total of 138 territorial pairs of golden eagles during surveys completed in the 2014 breeding season, which represented about one-half of the 280 pairs we estimated to occur in the broader 5,169-square kilometer region sampled. The study results emphasize the importance of accounting for imperfect detection and spatial heterogeneity in studies of site occupancy, breeding success, and abundance of golden eagles.

  15. Hierarchical distance-sampling models to estimate population size and habitat-specific abundance of an island endemic

    USGS Publications Warehouse

    Sillett, Scott T.; Chandler, Richard B.; Royle, J. Andrew; Kéry, Marc; Morrison, Scott A.

    2012-01-01

    Population size and habitat-specific abundance estimates are essential for conservation management. A major impediment to obtaining such estimates is that few statistical models are able to simultaneously account for both spatial variation in abundance and heterogeneity in detection probability, and still be amenable to large-scale applications. The hierarchical distance-sampling model of J. A. Royle, D. K. Dawson, and S. Bates provides a practical solution. Here, we extend this model to estimate habitat-specific abundance and rangewide population size of a bird species of management concern, the Island Scrub-Jay (Aphelocoma insularis), which occurs solely on Santa Cruz Island, California, USA. We surveyed 307 randomly selected, 300 m diameter, point locations throughout the 250-km2 island during October 2008 and April 2009. Population size was estimated to be 2267 (95% CI 1613-3007) and 1705 (1212-2369) during the fall and spring respectively, considerably lower than a previously published but statistically problematic estimate of 12 500. This large discrepancy emphasizes the importance of proper survey design and analysis for obtaining reliable information for management decisions. Jays were most abundant in low-elevation chaparral habitat; the detection function depended primarily on the percent cover of chaparral and forest within count circles. Vegetation change on the island has been dramatic in recent decades, due to release from herbivory following the eradication of feral sheep (Ovis aries) from the majority of the island in the mid-1980s. We applied best-fit fall and spring models of habitat-specific jay abundance to a vegetation map from 1985, and estimated the population size of A. insularis was 1400-1500 at that time. The 20-30% increase in the jay population suggests that the species has benefited from the recovery of native vegetation since sheep removal. Nevertheless, this jay's tiny range and small population size make it vulnerable to natural

  16. Hierarchical distance-sampling models to estimate population size and habitat-specific abundance of an island endemic.

    PubMed

    Sillett, T Scott; Chandler, Richard B; Royle, J Andrew; Kery, Marc; Morrison, Scott A

    2012-10-01

    Population size and habitat-specific abundance estimates are essential for conservation management. A major impediment to obtaining such estimates is that few statistical models are able to simultaneously account for both spatial variation in abundance and heterogeneity in detection probability, and still be amenable to large-scale applications. The hierarchical distance-sampling model of J. A. Royle, D. K. Dawson, and S. Bates provides a practical solution. Here, we extend this model to estimate habitat-specific abundance and rangewide population size of a bird species of management concern, the Island Scrub-Jay (Aphelocoma insularis), which occurs solely on Santa Cruz Island, California, USA. We surveyed 307 randomly selected, 300 m diameter, point locations throughout the 250-km2 island during October 2008 and April 2009. Population size was estimated to be 2267 (95% CI 1613-3007) and 1705 (1212-2369) during the fall and spring respectively, considerably lower than a previously published but statistically problematic estimate of 12 500. This large discrepancy emphasizes the importance of proper survey design and analysis for obtaining reliable information for management decisions. Jays were most abundant in low-elevation chaparral habitat; the detection function depended primarily on the percent cover of chaparral and forest within count circles. Vegetation change on the island has been dramatic in recent decades, due to release from herbivory following the eradication of feral sheep (Ovis aries) from the majority of the island in the mid-1980s. We applied best-fit fall and spring models of habitat-specific jay abundance to a vegetation map from 1985, and estimated the population size of A. insularis was 1400-1500 at that time. The 20-30% increase in the jay population suggests that the species has benefited from the recovery of native vegetation since sheep removal. Nevertheless, this jay's tiny range and small population size make it vulnerable to natural

  17. Ocean Lidar Measurements of Beam Attenuation and a Roadmap to Accurate Phytoplankton Biomass Estimates

    NASA Astrophysics Data System (ADS)

    Hu, Yongxiang; Behrenfeld, Mike; Hostetler, Chris; Pelon, Jacques; Trepte, Charles; Hair, John; Slade, Wayne; Cetinic, Ivona; Vaughan, Mark; Lu, Xiaomei; Zhai, Pengwang; Weimer, Carl; Winker, David; Verhappen, Carolus C.; Butler, Carolyn; Liu, Zhaoyan; Hunt, Bill; Omar, Ali; Rodier, Sharon; Lifermann, Anne; Josset, Damien; Hou, Weilin; MacDonnell, David; Rhew, Ray

    2016-06-01

    Beam attenuation coefficient, c, provides an important optical index of plankton standing stocks, such as phytoplankton biomass and total particulate carbon concentration. Unfortunately, c has proven difficult to quantify through remote sensing. Here, we introduce an innovative approach for estimating c using lidar depolarization measurements and diffuse attenuation coefficients from ocean color products or lidar measurements of Brillouin scattering. The new approach is based on a theoretical formula established from Monte Carlo simulations that links the depolarization ratio of sea water to the ratio of diffuse attenuation Kd and beam attenuation C (i.e., a multiple scattering factor). On July 17, 2014, the CALIPSO satellite was tilted 30° off-nadir for one nighttime orbit in order to minimize ocean surface backscatter and demonstrate the lidar ocean subsurface measurement concept from space. Depolarization ratios of ocean subsurface backscatter are measured accurately. Beam attenuation coefficients computed from the depolarization ratio measurements compare well with empirical estimates from ocean color measurements. We further verify the beam attenuation coefficient retrievals using aircraft-based high spectral resolution lidar (HSRL) data that are collocated with in-water optical measurements.

  18. Spatially-explicit estimates of greenhouse-gas payback times for perennial cellulosic biomass production on open lands in the Lake States

    NASA Astrophysics Data System (ADS)

    Sahajpal, R.

    2015-12-01

    The development of renewable energy sources is an integral step towards mitigating the carbon dioxide induced component of climate change. One important renewable source is plant biomass, comprising both food crops such as corn (Zea mays) and cellulosic biomass from short-rotation woody crops (SRWC) such as hybrid-poplar (Populus spp.) and Willow (Salix spp.). Due to their market acceptability and excellent energy balance, cellulosic feedstocks represent an abundant and if managed properly, a carbon-neutral and environmentally beneficial resource. We evaluate how site variability impacts the greenhouse-gas (GHG) benefits of SRWC plantations on lands potentially suited for bioenergy feedstock production in the Lake States (Minnesota, Wisconsin, Michigan). We combine high-resolution, spatially-explicit estimates of biomass, soil organic carbon and nitrous oxide emissions for SRWC plantations from the Environmental Policy Integrated Climate (EPIC) model along with life cycle analysis results from the GREET model to determine the greenhouse-gas payback time (GPBT) or the time needed before the GHG savings due to displacement of fossil fuels exceeds the initial losses from plantation establishment. We calibrate our models using unique yield and N2O emission data from sites across the Lake states that have been converted from pasture and hayfields to SRWC plantations. Our results show a reduction of 800,000 ha in non-agricultural open land availability for biomass production, a loss of nearly 37% (see attached figure). Overall, GPBTs range between 1 and 38 years, with the longest GPBTs occurring in the northern Lake states. Initial soil nitrate levels and site drainage potential explain more than half of the variation in GPBTs. Our results indicate a rapidly closing window of opportunity to establish a sustainable cellulosic feedstock economy in the Lake States.

  19. Mark-Recapture and Mark-Resight Methods for Estimating Abundance with Remote Cameras: A Carnivore Case Study

    PubMed Central

    Alonso, Robert S.; McClintock, Brett T.; Lyren, Lisa M.; Boydston, Erin E.; Crooks, Kevin R.

    2015-01-01

    Abundance estimation of carnivore populations is difficult and has prompted the use of non-invasive detection methods, such as remotely-triggered cameras, to collect data. To analyze photo data, studies focusing on carnivores with unique pelage patterns have utilized a mark-recapture framework and studies of carnivores without unique pelage patterns have used a mark-resight framework. We compared mark-resight and mark-recapture estimation methods to estimate bobcat (Lynx rufus) population sizes, which motivated the development of a new "hybrid" mark-resight model as an alternative to traditional methods. We deployed a sampling grid of 30 cameras throughout the urban southern California study area. Additionally, we physically captured and marked a subset of the bobcat population with GPS telemetry collars. Since we could identify individual bobcats with photos of unique pelage patterns and a subset of the population was physically marked, we were able to use traditional mark-recapture and mark-resight methods, as well as the new “hybrid” mark-resight model we developed to estimate bobcat abundance. We recorded 109 bobcat photos during 4,669 camera nights and physically marked 27 bobcats with GPS telemetry collars. Abundance estimates produced by the traditional mark-recapture, traditional mark-resight, and “hybrid” mark-resight methods were similar, however precision differed depending on the models used. Traditional mark-recapture and mark-resight estimates were relatively imprecise with percent confidence interval lengths exceeding 100% of point estimates. Hybrid mark-resight models produced better precision with percent confidence intervals not exceeding 57%. The increased precision of the hybrid mark-resight method stems from utilizing the complete encounter histories of physically marked individuals (including those never detected by a camera trap) and the encounter histories of naturally marked individuals detected at camera traps. This new estimator

  20. Utilizing national agriculture imagery program data to estimate tree cover and biomass of pinyon and juniper woodlands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With the encroachment of pinyon (Pinus ssp.) and juniper (Juniperus ssp.) (P-J) woodlands into sagebrush steppe communities, there is an increasing interest in rapid, accurate, and inexpensive quantification methods to estimate tree canopy cover and aboveground biomass over large landscapes. The o...

  1. Estimating Yellow Starthistle (Centaurea solstitialis) Leaf Area Index and Aboveground Biomass with the Use of Hyperspectral Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral remote-sensed data were obtained via a Compact Airborne Spectrographic Imager-II (CASI-II) and used to estimate leaf-area index (LAI) and aboveground biomass of a highly invasive weed species, yellow starthistle (YST). In parallel, 34 ground-based field plots were used to measure abov...

  2. Estimating leaf area index and aboveground biomass of an invasive weed (yellow starthistle, Centaurea solstitalis L.) using airborne hyperspectral data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral remote sensed data was obtained via a Compact Airborne Spectrographic Imager (CASI) and used to estimate leaf area index (LAI) and aboveground biomass of a highly invasive weed species, yellow starthistle (Centaurea solstitialis L.). In parallel, 34 ground-based field plots were used t...

  3. Use of the Robust Design to Estimate Seasonal Abundance and Demographic Parameters of a Coastal Bottlenose Dolphin (Tursiops aduncus) Population

    PubMed Central

    Smith, Holly C.; Pollock, Ken; Waples, Kelly; Bradley, Stuart; Bejder, Lars

    2013-01-01

    As delphinid populations become increasingly exposed to human activities we rely on our capacity to produce accurate abundance estimates upon which to base management decisions. This study applied mark–recapture methods following the Robust Design to estimate abundance, demographic parameters, and temporary emigration rates of an Indo-Pacific bottlenose dolphin (Tursiops aduncus) population off Bunbury, Western Australia. Boat-based photo-identification surveys were conducted year-round over three consecutive years along pre-determined transect lines to create a consistent sampling effort throughout the study period and area. The best fitting capture–recapture model showed a population with a seasonal Markovian temporary emigration with time varying survival and capture probabilities. Abundance estimates were seasonally dependent with consistently lower numbers obtained during winter and higher during summer and autumn across the three-year study period. Specifically, abundance estimates for all adults and juveniles (combined) varied from a low of 63 (95% CI 59 to 73) in winter of 2007 to a high of 139 (95% CI 134 to148) in autumn of 2009. Temporary emigration rates (γ') for animals absent in the previous period ranged from 0.34 to 0.97 (mean  =  0.54; ±SE 0.11) with a peak during spring. Temporary emigration rates for animals present during the previous period (γ'') were lower, ranging from 0.00 to 0.29, with a mean of 0.16 (± SE 0.04). This model yielded a mean apparent survival estimate for juveniles and adults (combined) of 0.95 (± SE 0.02) and a capture probability from 0.07 to 0.51 with a mean of 0.30 (± SE 0.04). This study demonstrates the importance of incorporating temporary emigration to accurately estimate abundance of coastal delphinids. Temporary emigration rates were high in this study, despite the large area surveyed, indicating the challenges of sampling highly mobile animals which range over large spatial areas. PMID:24130781

  4. Use of the robust design to estimate seasonal abundance and demographic parameters of a coastal bottlenose dolphin (Tursiops aduncus) population.

    PubMed

    Smith, Holly C; Pollock, Ken; Waples, Kelly; Bradley, Stuart; Bejder, Lars

    2013-01-01

    As delphinid populations become increasingly exposed to human activities we rely on our capacity to produce accurate abundance estimates upon which to base management decisions. This study applied mark-recapture methods following the Robust Design to estimate abundance, demographic parameters, and temporary emigration rates of an Indo-Pacific bottlenose dolphin (Tursiops aduncus) population off Bunbury, Western Australia. Boat-based photo-identification surveys were conducted year-round over three consecutive years along pre-determined transect lines to create a consistent sampling effort throughout the study period and area. The best fitting capture-recapture model showed a population with a seasonal Markovian temporary emigration with time varying survival and capture probabilities. Abundance estimates were seasonally dependent with consistently lower numbers obtained during winter and higher during summer and autumn across the three-year study period. Specifically, abundance estimates for all adults and juveniles (combined) varied from a low of 63 (95% CI 59 to 73) in winter of 2007 to a high of 139 (95% CI 134 to148) in autumn of 2009. Temporary emigration rates (γ') for animals absent in the previous period ranged from 0.34 to 0.97 (mean  =  0.54; ±SE 0.11) with a peak during spring. Temporary emigration rates for animals present during the previous period (γ'') were lower, ranging from 0.00 to 0.29, with a mean of 0.16 (± SE 0.04). This model yielded a mean apparent survival estimate for juveniles and adults (combined) of 0.95 (± SE 0.02) and a capture probability from 0.07 to 0.51 with a mean of 0.30 (± SE 0.04). This study demonstrates the importance of incorporating temporary emigration to accurately estimate abundance of coastal delphinids. Temporary emigration rates were high in this study, despite the large area surveyed, indicating the challenges of sampling highly mobile animals which range over large spatial areas. PMID:24130781

  5. Bacterioplankton in antarctic ocean waters during late austral winter: abundance, frequency of dividing cells, and estimates of production.

    PubMed

    Hanson, R B; Shafer, D; Ryan, T; Pope, D H; Lowery, H K

    1983-05-01

    Bacterioplankton productivity in Antarctic waters of the eastern South Pacific Ocean and Drake Passage was estimated by direct counts and frequency of dividing cells (FDC). Total bacterioplankton assemblages were enumerated by epifluorescent microscopy. The experimentally determined relationship between in situ FDC and the potential instantaneous growth rate constant (mu) is best described by the regression equation ln mu = 0.081 FDC - 3.73. In the eastern South Pacific Ocean, bacterioplankton abundance (2 x 10 to 3.5 x 10 cells per ml) and FDC (11%) were highest at the Polar Front (Antarctic Convergence). North of the Subantarctic Front, abundance and FDC were between 1 x 10 to 2 x 10 cells per ml and 3 to 5%, respectively, and were vertically homogeneous to a depth of 600 m. In Drake Passage, abundance (10 x 10 cells per ml) and FDC (16%) were highest in waters south of the Polar Front and near the sea ice. Subantarctic waters in Drake Passage contained 4 x 10 cells per ml with 4 to 5% FDC. Instantaneous growth rate constants ranged between 0.029 and 0.088 h. Using estimates of potential mu and measured standing stocks, we estimated productivity to range from 0.62 mug of C per liter . day in the eastern South Pacific Ocean to 17.1 mug of C per liter . day in the Drake Passage near the sea ice. PMID:16346297

  6. Quantification of uncertainty in aboveground biomass estimates derived from small-footprint LiDAR data

    NASA Astrophysics Data System (ADS)

    Xu, Q.; Greenberg, J. A.; Li, B.; Ramirez, C.; Balamuta, J. J.; Evans, K.; Man, A.; Xu, Z.

    2015-12-01

    A promising approach to determining aboveground biomass (AGB) in forests comes through the use of individual tree crown delineation (ITCD) techniques applied to small-footprint LiDAR data. These techniques, when combined with allometric equations, can produce per-tree estimates of AGB. At this scale, AGB estimates can be quantified in a manner similar to how ground-based forest inventories are produced. However, these approaches have significant uncertainties that are rarely described in full. Allometric equations are often based on species-specific diameter-at-breast height (DBH) relationships, but neither DBH nor species can be reliably determined using remote sensing analysis. Furthermore, many approaches to ITCD only delineate trees appearing in the upper canopy so subcanopy trees are often missing from the inventories. In this research, we performed a propagation-of-error analysis to determine the spatially varying uncertainties in AGB estimates at the individual plant and stand level for a large collection of LiDAR acquisitions covering a large portion of California. Furthermore, we determined the relative contribution of various aspects of the analysis towards the uncertainty, including errors in the ITCD results, the allometric equations, the taxonomic designation, and the local biophysical environment. Watershed segmentation was used to obtain the preliminary crown segments. Lidar points within the preliminary segments were extracted to form profiling data of the segments, and then mode detection algorithms were applied to identify the tree number and tree heights within each segment. As part of this analysis, we derived novel "remote sensing aware" allometric equations and their uncertainties based on three-dimensional morphological metrics that can be accurately derived from LiDAR data.

  7. Improving artificial forest biomass estimates using afforestation age information from time series Landsat stacks.

    PubMed

    Liu, Liangyun; Peng, Dailiang; Wang, Zhihui; Hu, Yong

    2014-11-01

    China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R (2)) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R (2) values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades. PMID:25034235

  8. Estimates of forest biomass carbon storage inLiaoning Province of Northeast China: a review and assessment.

    PubMed

    Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

    2014-01-01

    Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha(-1) in 1980 to 31.0 Mg ha(-1) in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations. PMID:24586881

  9. Landscape ecology of eastern coyotes based on large-scale estimates of abundance.

    PubMed

    Kays, Roland W; Gompper, Matthew E; Ray, Justina C

    2008-06-01

    Since their range expansion into eastern North America in the mid-1900s, coyotes (Canis latrans) have become the region's top predator. Although widespread across the region, coyote adaptation to eastern forests and use of the broader landscape are not well understood. We studied the distribution and abundance of coyotes by collecting coyote feces from 54 sites across a diversity of landscapes in and around the Adirondacks of northern New York. We then genotyped feces with microsatellites and found a close correlation between the number of detected individuals and the total number of scats at a site. We created habitat models predicting coyote abundance using multi-scale vegetation and landscape data and ranked them with an information-theoretic model selection approach. These models allow us to reject the hypothesis that eastern forests are unsuitable habitat for coyotes as their abundance was positively correlated with forest cover and negatively correlated with measures of rural non-forest landscapes. However, measures of vegetation structure turned out to be better predictors of coyote abundance than generalized "forest vs. open" classification. The best supported models included those measures indicative of disturbed forest, especially more open canopies found in logged forests, and included natural edge habitats along water courses. These forest types are more productive than mature forests and presumably host more prey for coyotes. A second model with only variables that could be mapped across the region highlighted the lower density of coyotes in areas with high human settlement, as well as positive relationships with variables such as snowfall and lakes that may relate to increased numbers and vulnerability of deer. The resulting map predicts coyote density to be highest along the southwestern edge of the Adirondack State Park, including Tug Hill, and lowest in the mature forests and more rural areas of the central and eastern Adirondacks. Together, these

  10. Thermal efficiency and particulate pollution estimation of four biomass fuels grown on wasteland

    SciTech Connect

    Kandpal, J.B.; Madan, M.

    1996-10-01

    The thermal performance and concentration of suspended particulate matter were studied for 1-hour combustion of four biomass fuels, namely Acacia nilotica, Leucaena leucocepholea, Jatropha curcus, and Morus alba grown in wasteland. Among the four biomass fuels, the highest thermal efficiency was achieved with Acacia nilotica. The suspended particulate matter concentration for 1-hour combustion of four biomass fuels ranged between 850 and 2,360 {micro}g/m{sup 3}.

  11. Estimating grizzly and black bear population abundance and trend in Banff National Park using noninvasive genetic sampling.

    PubMed

    Sawaya, Michael A; Stetz, Jeffrey B; Clevenger, Anthony P; Gibeau, Michael L; Kalinowski, Steven T

    2012-01-01

    We evaluated the potential of two noninvasive genetic sampling methods, hair traps and bear rub surveys, to estimate population abundance and trend of grizzly (Ursus arctos) and black bear (U. americanus) populations in Banff National Park, Alberta, Canada. Using Huggins closed population mark-recapture models, we obtained the first precise abundance estimates for grizzly bears (N= 73.5, 95% CI = 64-94 in 2006; N= 50.4, 95% CI = 49-59 in 2008) and black bears (N= 62.6, 95% CI = 51-89 in 2006; N= 81.8, 95% CI = 72-102 in 2008) in the Bow Valley. Hair traps had high detection rates for female grizzlies, and male and female black bears, but extremely low detection rates for male grizzlies. Conversely, bear rubs had high detection rates for male and female grizzlies, but low rates for black bears. We estimated realized population growth rates, lambda, for grizzly bear males (λ= 0.93, 95% CI = 0.74-1.17) and females (λ= 0.90, 95% CI = 0.67-1.20) using Pradel open population models with three years of bear rub data. Lambda estimates are supported by abundance estimates from combined hair trap/bear rub closed population models and are consistent with a system that is likely driven by high levels of human-caused mortality. Our results suggest that bear rub surveys would provide an efficient and powerful means to inventory and monitor grizzly bear populations in the Central Canadian Rocky Mountains. PMID:22567089

  12. Improving estimation of tree carbon stocks by harvesting aboveground woody biomass within airborne LiDAR flight areas

    NASA Astrophysics Data System (ADS)

    Colgan, M.; Asner, G. P.; Swemmer, A. M.

    2011-12-01

    The accurate estimation of carbon stored in a tree is essential to accounting for the carbon emissions due to deforestation and degradation. Airborne LiDAR (Light Detection and Ranging) has been successful in estimating aboveground carbon density (ACD) by correlating airborne metrics, such as canopy height, to field-estimated biomass. This latter step is reliant on field allometry which is applied to forest inventory quantities, such as stem diameter and height, to predict the biomass of a given tree stem. Constructing such allometry is expensive, time consuming, and requires destructive sampling. Consequently, the sample sizes used to construct such allometry are often small, and the largest tree sampled is often much smaller than the largest in the forest population. The uncertainty resulting from these sampling errors can lead to severe biases when the allometry is applied to stems larger than those harvested to construct the allometry, which is then subsequently propagated to airborne ACD estimates. The Kruger National Park (KNP) mission of maintaining biodiversity coincides with preserving ecosystem carbon stocks. However, one hurdle to accurately quantifying carbon density in savannas is that small stems are typically harvested to construct woody biomass allometry, yet they are not representative of Kruger's distribution of biomass. Consequently, these equations inadequately capture large tree variation in sapwood/hardwood composition, root/shoot/leaf allocation, branch fall, and stem rot. This study eliminates the "middleman" of field allometry by directly measuring, or harvesting, tree biomass within the extent of airborne LiDAR. This enables comparisons of field and airborne ACD estimates, and also enables creation of new airborne algorithms to estimate biomass at the scale of individual trees. A field campaign was conducted at Pompey Silica Mine 5km outside Kruger National Park, South Africa, in Mar-Aug 2010 to harvest and weigh tree mass. Since

  13. A Bayesian approach to estimate the biomass of anchovies off the coast of Perú.

    PubMed

    Quiroz, Zaida C; Prates, Marcos O; Rue, Håvard

    2015-03-01

    The Northern Humboldt Current System (NHCS) is the world's most productive ecosystem in terms of fish. In particular, the Peruvian anchovy (Engraulis ringens) is the major prey of the main top predators, like seabirds, fish, humans, and other mammals. In this context, it is important to understand the dynamics of the anchovy distribution to preserve it as well as to exploit its economic capacities. Using the data collected by the "Instituto del Mar del Perú" (IMARPE) during a scientific survey in 2005, we present a statistical analysis that has as main goals: (i) to adapt to the characteristics of the sampled data, such as spatial dependence, high proportions of zeros and big size of samples; (ii) to provide important insights on the dynamics of the anchovy population; and (iii) to propose a model for estimation and prediction of anchovy biomass in the NHCS offshore from Perú. These data were analyzed in a Bayesian framework using the integrated nested Laplace approximation (INLA) method. Further, to select the best model and to study the predictive power of each model, we performed model comparisons and predictive checks, respectively. Finally, we carried out a Bayesian spatial influence diagnostic for the preferred model. PMID:25257036

  14. Above ground biomass estimation from lidar and hyperspectral airbone data in West African moist forests.

    NASA Astrophysics Data System (ADS)

    Vaglio Laurin, Gaia; Chen, Qi; Lindsell, Jeremy; Coomes, David; Cazzolla-Gatti, Roberto; Grieco, Elisa; Valentini, Riccardo

    2013-04-01

    The development of sound methods for the estimation of forest parameters such as Above Ground Biomass (AGB) and the need of data for different world regions and ecosystems, are widely recognized issues due to their relevance for both carbon cycle modeling and conservation and policy initiatives, such as the UN REDD+ program (Gibbs et al., 2007). The moist forests of the Upper Guinean Belt are poorly studied ecosystems (Vaglio Laurin et al. 2013) but their role is important due to the drier condition expected along the West African coasts according to future climate change scenarios (Gonzales, 2001). Remote sensing has proven to be an effective tool for AGB retrieval when coupled with field data. Lidar, with its ability to penetrate the canopy provides 3D information and best results. Nevertheless very limited research has been conducted in Africa tropical forests with lidar and none to our knowledge in West Africa. Hyperspectral sensors also offer promising data, being able to evidence very fine radiometric differences in vegetation reflectance. Their usefulness in estimating forest parameters is still under evaluation with contrasting findings (Andersen et al. 2008, Latifi et al. 2012), and additional studies are especially relevant in view of forthcoming satellite hyperspectral missions. In the framework of the EU ERC Africa GHG grant #247349, an airborne campaign collecting lidar and hyperspectral data has been conducted in March 2012 over forests reserves in Sierra Leone and Ghana, characterized by different logging histories and rainfall patterns, and including Gola Rainforest National Park, Ankasa National Park, Bia and Boin Forest Reserves. An Optech Gemini sensor collected the lidar dataset, while an AISA Eagle sensor collected hyperspectral data over 244 VIS-NIR bands. The lidar dataset, with a point density >10 ppm was processed using the TIFFS software (Toolbox for LiDAR Data Filtering and Forest Studies)(Chen 2007). The hyperspectral dataset, geo

  15. Use of portable antennas to estimate abundance of PIT-tagged fish in small streams: Factors affecting detection probability

    USGS Publications Warehouse

    O'Donnell, Matthew J.; Horton, Gregg E.; Letcher, Benjamin H.

    2010-01-01

    Portable passive integrated transponder (PIT) tag antenna systems can be valuable in providing reliable estimates of the abundance of tagged Atlantic salmon Salmo salar in small streams under a wide range of conditions. We developed and employed PIT tag antenna wand techniques in two controlled experiments and an additional case study to examine the factors that influenced our ability to estimate population size. We used Pollock's robust-design capture–mark–recapture model to obtain estimates of the probability of first detection (p), the probability of redetection (c), and abundance (N) in the two controlled experiments. First, we conducted an experiment in which tags were hidden in fixed locations. Although p and c varied among the three observers and among the three passes that each observer conducted, the estimates of N were identical to the true values and did not vary among observers. In the second experiment using free-swimming tagged fish, p and c varied among passes and time of day. Additionally, estimates of N varied between day and night and among age-classes but were within 10% of the true population size. In the case study, we used the Cormack–Jolly–Seber model to examine the variation in p, and we compared counts of tagged fish found with the antenna wand with counts collected via electrofishing. In that study, we found that although p varied for age-classes, sample dates, and time of day, antenna and electrofishing estimates of N were similar, indicating that population size can be reliably estimated via PIT tag antenna wands. However, factors such as the observer, time of day, age of fish, and stream discharge can influence the initial and subsequent detection probabilities.

  16. Biogas production from Pongamia biomass wastes and a model to estimate biodegradability from their composition.

    PubMed

    Gunaseelan, Victor Nallathambi

    2014-02-01

    In this study, I investigated the chemical characteristics, biochemical methane potential, conversion kinetics and biodegradability of untreated and NaOH-treated Pongamia plant parts, and pod husk and press cake from the biodiesel industry to evaluate their suitability as an alternative feedstock for biogas production. The untreated Pongamia seeds exhibited the maximum CH4 yield of 473 ml g (-1) volatile solid (VS) added. Yellow, withered leaves gave a yield as low as 122 ml CH4 g (-1) VS added. There were significant variations in the CH4 production rate constants, which ranged from 0.02 to 0.15 d (-1), and biodegradability, which ranged from 0.25 to 0.98. NaOH treatment of leaf and pod husk, which were highly rich in fibers, increased the yields by 15-22% and CH4 production rate constants by 20-75%. Utilization of Pongamia wastes in biogas digesters not only influences the economics of biodiesel production but also yields CH4 fuel and protects the environment. The experimental data from this study were used to develop a multiple regression model, which could estimate biodegradability based on biochemical characteristics. The model predicted the biodegradability of previously published biomass wastes (r(2) = 0.88) from their biochemical composition. The theoretical CH4 yields estimated as 350 ml g(-1) chemical oxygen demand destroyed are much higher than the experimental yields as 100% biodegradability is assumed for each substrate. Upon correcting the theoretical CH4 yields with biodegradability data obtained from chemical analyses of substrates, their ultimate CH4 yields could be predicted rapidly. PMID:24519227

  17. Spatially explicit estimates of stock size, structure and biomass of North Atlantic albacore Tuna (Thunnus alalunga)

    NASA Astrophysics Data System (ADS)

    Lehodey, P.; Senina, I.; Dragon, A.-C.; Arrizabalaga, H.

    2014-04-01

    The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. Unlike standard stock assessment models, new state-of-the-art ecosystem models require geo-referenced fishing data with highest possible spatial resolution. This study presents an application to the north Atlantic albacore tuna stock with a careful definition and validation of a spatially explicit fishing dataset prepared from publically available sources (ICCAT) for its use in a spatial ecosystem and population dynamics model (SEAPODYM) to provide the first spatially explicit estimate of albacore density in the North Atlantic by life stage. Density distributions are provided (http://doi.pangaea.de/10.1594/PANGAEA.831499) together with the fishing data used for these estimates http://doi.pangaea.de/10.1594/PANGAEA.830797, http://doi.pangaea.de/10.15 1594/PANGAEA.828168, http://doi.pangaea.de/10.1594/PANGAEA.828170, and http://doi.pangaea.de/10.1594/PANGAEA.828171 (see section Source Data References).

  18. Comparative biomass structure and estimated carbon flow in food webs in the deep Gulf of Mexico

    NASA Astrophysics Data System (ADS)

    Rowe, Gilbert T.; Wei, Chihlin; Nunnally, Clifton; Haedrich, Richard; Montagna, Paul; Baguley, Jeffrey G.; Bernhard, Joan M.; Wicksten, Mary; Ammons, Archie; Briones, Elva Escobar; Soliman, Yousra; Deming, Jody W.

    2008-12-01

    A budget of the standing stocks and cycling of organic carbon associated with the sea floor has been generated for seven sites across a 3-km depth gradient in the NE Gulf of Mexico, based on a series of reports by co-authors on specific biotic groups or processes. The standing stocks measured at each site were bacteria, Foraminifera, metazoan meiofauna, macrofauna, invertebrate megafauna, and demersal fishes. Sediment community oxygen consumption (SCOC) by the sediment-dwelling organisms was measured at each site using a remotely deployed benthic lander, profiles of oxygen concentration in the sediment pore water of recovered cores and ship-board core incubations. The long-term incorporation and burial of organic carbon into the sediments has been estimated using profiles of a combination of stable and radiocarbon isotopes. The total stock estimates, carbon burial, and the SCOC allowed estimates of living and detrital carbon residence time within the sediments, illustrating that the total biota turns over on time scales of months on the upper continental slope but this is extended to years on the abyssal plain at 3.6 km depth. The detrital carbon turnover is many times longer, however, over the same depths. A composite carbon budget illustrates that total carbon biomass and associated fluxes declined precipitously with increasing depth. Imbalances in the carbon budgets suggest that organic detritus is exported from the upper continental slope to greater depths offshore. The respiration of each individual "size" or functional group within the community has been estimated from allometric models, supplemented by direct measurements in the laboratory. The respiration and standing stocks were incorporated into budgets of carbon flow through and between the different size groups in hypothetical food webs. The decline in stocks and respiration with depth were more abrupt in the larger forms (fishes and megafauna), resulting in an increase in the relative predominance of

  19. [Models for biomass estimation of four shrub species planted in urban area of Xi'an city, Northwest China].

    PubMed

    Yao, Zheng-Yang; Liu, Jian-Jun

    2014-01-01

    Four common greening shrub species (i. e. Ligustrum quihoui, Buxus bodinieri, Berberis xinganensis and Buxus megistophylla) in Xi'an City were selected to develop the highest correlation and best-fit estimation models for the organ (branch, leaf and root) and total biomass against different independent variables. The results indicated that the organ and total biomass optimal models of the four shrubs were power functional model (CAR model) except for the leaf biomass model of B. megistophylla which was logarithmic functional model (VAR model). The independent variables included basal diameter, crown diameter, crown diameter multiplied by height, canopy area and canopy volume. B. megistophylla significantly differed from the other three shrub species in the independent variable selection, which were basal diameter and crown-related factors, respectively. PMID:24765849

  20. Water- and radiation-use efficiency models for estimating biomass production

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Simple biomass production models are used to assess crop productivity under a wide range of environmental conditions, typically as a component of comprehensive crop growth models. Two simple biomass production models are widely used, one based on radiation-use efficiency, e (B=e St fi), and the oth...

  1. Estimating population abundance and mapping distribution of wintering sea ducks in coastal waters of the mid-Atlantic

    USGS Publications Warehouse

    Koneff, M.D.; Royle, J. Andrew; Forsell, D.J.; Wortham, J.S.; Boomer, G.S.; Perry, M.C.

    2005-01-01

    Survey design for wintering scoters (Melanitta sp.) and other sea ducks that occur in offshore waters is challenging because these species have large ranges, are subject to distributional shifts among years and within a season, and can occur in aggregations. Interest in winter sea duck population abundance surveys has grown in recent years. This interest stems from concern over the population status of some sea ducks, limitations of extant breeding waterfowl survey programs in North America and logistical challenges and costs of conducting surveys in northern breeding regions, high winter area philopatry in some species and potential conservation implications, and increasing concern over offshore development and other threats to sea duck wintering habitats. The efficiency and practicality of statistically-rigorous monitoring strategies for mobile, aggregated wintering sea duck populations have not been sufficiently investigated. This study evaluated a 2-phase adaptive stratified strip transect sampling plan to estimate wintering population size of scoters, long-tailed ducks (Clangua hyemalis), and other sea ducks and provide information on distribution. The sampling plan results in an optimal allocation of a fixed sampling effort among offshore strata in the U.S. mid-Atlantic coast region. Phase I transect selection probabilities were based on historic distribution and abundance data, while Phase 2 selection probabilities were based on observations made during Phase 1 flights. Distance sampling methods were used to estimate detection rates. Environmental variables thought to affect detection rates were recorded during the survey and post-stratification and covariate modeling were investigated to reduce the effect of heterogeneity on detection estimation. We assessed cost-precision tradeoffs under a number of fixed-cost sampling scenarios using Monte Carlo simulation. We discuss advantages and limitations of this sampling design for estimating wintering sea duck

  2. Gradient anaysis of biomass in Costa Rica and a first estimate of total emissions of greenhouse gases from biomass burning

    SciTech Connect

    Helmer, E.H.; Brown, S.

    1997-12-31

    One important component of sustainable development for a nation is the degree to which it can balance greenhouse gas (GHG) exchange with the atmosphere. Scientists at NHEERL-WED recently estimated the release of such GHGs from the conversion of a range of forest types in Costa Rica between 1940-1983. They also evaluated the influence of environmental gradients that affect the rates and patterns of deforestation and the carbon pools of the forest cleared on GHG emissions.

  3. Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops

    NASA Astrophysics Data System (ADS)

    Kross, Angela; McNairn, Heather; Lapen, David; Sunohara, Mark; Champagne, Catherine

    2015-02-01

    Leaf area index (LAI) and biomass are important indicators of crop development and the availability of this information during the growing season can support farmer decision making processes. This study demonstrates the applicability of RapidEye multi-spectral data for estimation of LAI and biomass of two crop types (corn and soybean) with different canopy structure, leaf structure and photosynthetic pathways. The advantages of Rapid Eye in terms of increased temporal resolution (∼daily), high spatial resolution (∼5 m) and enhanced spectral information (includes red-edge band) are explored as an individual sensor and as part of a multi-sensor constellation. Seven vegetation indices based on combinations of reflectance in green, red, red-edge and near infrared bands were derived from RapidEye imagery between 2011 and 2013. LAI and biomass data were collected during the same period for calibration and validation of the relationships between vegetation indices and LAI and dry above-ground biomass. Most indices showed sensitivity to LAI from emergence to 8 m2/m2. The normalized difference vegetation index (NDVI), the red-edge NDVI and the green NDVI were insensitive to crop type and had coefficients of variations (CV) ranging between 19 and 27%; and coefficients of determination ranging between 86 and 88%. The NDVI performed best for the estimation of dry leaf biomass (CV = 27% and r2 = 090) and was also insensitive to crop type. The red-edge indices did not show any significant improvement in LAI and biomass estimation over traditional multispectral indices. Cumulative vegetation indices showed strong performance for estimation of total dry above-ground biomass, especially for corn (CV ≤ 20%). This study demonstrated that continuous crop LAI monitoring over time and space at the field level can be achieved using a combination of RapidEye, Landsat and SPOT data and sensor-dependant best-fit functions. This approach eliminates/reduces the need for reflectance

  4. Abundance, Distribution and Estimated Consumption (kg fish) of Piscivorous Birds Along the Yakima River, Washington State; Implications for Fisheries Management, 2002 Annual Report.

    SciTech Connect

    Major, III, Walter; Grassley, James M.; Ryding, Kristen E.

    2003-05-01

    This report is divided into two chapters. The abstract for chapter one is--Understanding of the abundance and spatial and temporal distributions of piscivorous birds and their potential consumption of fish is an increasingly important aspect of fisheries management. During 1999-2002, we determined the abundance and distribution and estimated the maximum consumption (kg biomass) of fish-eating birds along the length of the Yakima River in Washington State. Sixteen different species were observed during the 4-yr study, but only half of those were observed during all years. Abundance and estimated consumption of fish within the upper and middle sections of the river were dominated by common mergansers (Mergus merganser) which are known to breed in those reaches. Common mergansers accounted for 78 to 94% of the estimated total fish take for the upper river or approximately 28,383 {+-} 1,041 kg over the 4 yrs. A greater diversity of avian piscivores occurred in the lower river and potential impacts to fish populations was more evenly distributed among the species. In 1999-2000, great blue herons potentially accounted for 29 and 36% of the fish consumed, whereas in 2001-2002 American white pelicans accounted for 53 and 55%. We estimated that approximately 75,878 {+-} 6,616 kg of fish were consumed by piscivorous birds in the lower sections of the river during the study. Bird assemblages differed spatially along the river with a greater abundance of colonial nesting species within the lower sections of the river, especially during spring and the nesting season. The abundance of avian piscivores and consumption estimates are discussed within the context of salmonid supplementation efforts on the river and juvenile out-migration. The abstract for chapter two is--Consumption of fish by piscivorous birds may be a significant constraint on efforts to enhance salmonid populations within tributaries to the Columbia River in Washington State. During 1999-2002, we determined the

  5. Twig and foliar biomass estimation equations for major plant species in the Tanana River basin of interior Alaska. Forest Service research paper

    SciTech Connect

    Yarie, J.; Mead, B.R.

    1988-09-01

    Equations are presented for estimating the twig, foliage, and combined biomass for 58 plant species in interior Alaska. The equations can be used for estimating biomass from percentage of the foliar cover of 10-centimeter layers in a vertical profile from 0 to 6 meters. Few differences were found in regressions of the same species between layers except when the ratio of foliar-to-twig biomass changed drastically between layers, for example, Rosa acicularis Lindl. Eighteen species were tested for regression differences between years. Thirteen showed no significant differences, five were different. Of these five, three were feather mosses for which live and dead biomass are easily confused when measured.

  6. Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China

    PubMed Central

    Shao, Zhenfeng; Zhang, Linjing

    2016-01-01

    Estimation of forest aboveground biomass is critical for regional carbon policies and sustainable forest management. Passive optical remote sensing and active microwave remote sensing both play an important role in the monitoring of forest biomass. However, optical spectral reflectance is saturated in relatively dense vegetation areas, and microwave backscattering is significantly influenced by the underlying soil when the vegetation coverage is low. Both of these conditions decrease the estimation accuracy of forest biomass. A new optical and microwave integrated vegetation index (VI) was proposed based on observations from both field experiments and satellite (Landsat 8 Operational Land Imager (OLI) and RADARSAT-2) data. According to the difference in interaction between the multispectral reflectance and microwave backscattering signatures with biomass, the combined VI (COVI) was designed using the weighted optical optimized soil-adjusted vegetation index (OSAVI) and microwave horizontally transmitted and vertically received signal (HV) to overcome the disadvantages of both data types. The performance of the COVI was evaluated by comparison with those of the sole optical data, Synthetic Aperture Radar (SAR) data, and the simple combination of independent optical and SAR variables. The most accurate performance was obtained by the models based on the COVI and optical and microwave optimal variables excluding OSAVI and HV, in combination with a random forest algorithm and the largest number of reference samples. The results also revealed that the predictive accuracy depended highly on the statistical method and the number of sample units. The validation indicated that this integrated method of determining the new VI is a good synergistic way to combine both optical and microwave information for the accurate estimation of forest biomass. PMID:27338378

  7. Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China.

    PubMed

    Shao, Zhenfeng; Zhang, Linjing

    2016-01-01

    Estimation of forest aboveground biomass is critical for regional carbon policies and sustainable forest management. Passive optical remote sensing and active microwave remote sensing both play an important role in the monitoring of forest biomass. However, optical spectral reflectance is saturated in relatively dense vegetation areas, and microwave backscattering is significantly influenced by the underlying soil when the vegetation coverage is low. Both of these conditions decrease the estimation accuracy of forest biomass. A new optical and microwave integrated vegetation index (VI) was proposed based on observations from both field experiments and satellite (Landsat 8 Operational Land Imager (OLI) and RADARSAT-2) data. According to the difference in interaction between the multispectral reflectance and microwave backscattering signatures with biomass, the combined VI (COVI) was designed using the weighted optical optimized soil-adjusted vegetation index (OSAVI) and microwave horizontally transmitted and vertically received signal (HV) to overcome the disadvantages of both data types. The performance of the COVI was evaluated by comparison with those of the sole optical data, Synthetic Aperture Radar (SAR) data, and the simple combination of independent optical and SAR variables. The most accurate performance was obtained by the models based on the COVI and optical and microwave optimal variables excluding OSAVI and HV, in combination with a random forest algorithm and the largest number of reference samples. The results also revealed that the predictive accuracy depended highly on the statistical method and the number of sample units. The validation indicated that this integrated method of determining the new VI is a good synergistic way to combine both optical and microwave information for the accurate estimation of forest biomass. PMID:27338378

  8. Biomass estimation during macro-scale solid-state fermentation of basidiomycetes using established and novel approaches.

    PubMed

    Steudler, Susanne; Bley, Thomas

    2015-07-01

    Solid-state fermentation (SSF) has been utilised in food production for millennia and is well suited for the cultivation of basidiomycetes, due to the robustness of the process and the possibility of using lignocellulose as the substrate. Basidiomycetes produce diverse enzymes and various primary and secondary metabolites, many of which have biotechnological potential. The quantification of the fungal biomass present is essential for the characterisation of growth kinetics in processes such as SSF. In SSF, fungi grow into the substrate and use it as a nutrient source. Therefore, direct biomass determination is not possible and indirect methods have to be employed. In the presented study, we compared 11 methods for quantifying fungal biomass during SSF of the basidiomycete Trametes hirsuta in a newly developed laboratory reactor (working volume 10 L). The methods were based on measuring the levels of six cell-specific components (ergosterol, glucosamine, nucleic acids, number of fungal nuclei, protein and genomic DNA) and estimations of biological activity (respiration, activities of lignolytic and cellulolytic enzymes, and the glucose and protein contents of the liquid). The methods were evaluated with regards to reproducibility and plausibility of the results, time and resource requirements, possible influential factors, and matrix effects. The most reliable biomass estimates were obtained from measurements of ergosterol content, number of nuclei, and respiration. Thus, these three methods were deemed most suitable for process control and modelling. PMID:25656698

  9. Hydroacoustic estimation of zooplankton biomass at two shoal complexes in the Apostle Islands Region of Lake Superior

    USGS Publications Warehouse

    Holbrook, B.V.; Hrabik, T.R.; Branstrator, D.K.; Yule, D.L.; Stockwell, J.D.

    2006-01-01

    Hydroacoustics can be used to assess zooplankton populations, however, backscatter must be scaled to be biologically meaningful. In this study, we used a general model to correlate site-specific hydroacoustic backscatter with zooplankton dry weight biomass estimated from net tows. The relationship between zooplankton dry weight and backscatter was significant (p < 0.001) and explained 76% of the variability in the dry weight data. We applied this regression to hydroacoustic data collected monthly in 2003 and 2004 at two shoals in the Apostle Island Region of Lake Superior. After applying the regression model to convert hydroacoustic backscatter to zooplankton dry weight biomass, we used geostatistics to analyze the mean and variance, and ordinary kriging to create spatial zooplankton distribution maps. The mean zooplankton dry weight biomass estimates from plankton net tows and hydroacoustics were not significantly different (p = 0.19) but the hydroacoustic data had a significantly lower coefficient of variation (p < 0.001). The maps of zooplankton distribution illustrated spatial trends in zooplankton dry weight biomass that were not discernable from the overall means.

  10. Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

    NASA Technical Reports Server (NTRS)

    Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

    2012-01-01

    The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized

  11. Nitrogen content, 15N natural abundance and biomass of the two pleurocarpous mosses Pleurozium schreberi (Brid.) Mitt. and Scleropodium purum (Hedw.) Limpr. in relation to atmospheric nitrogen deposition.

    PubMed

    Solga, A; Burkhardt, J; Zechmeister, H G; Frahm, J-P

    2005-04-01

    The suitability of the two pleurocarpous mosses Pleurozium schreberi and Scleropodium purum for assessing spatial variation in nitrogen deposition was investigated. Sampling was carried out at eight sites in the western part of Germany with bulk deposition rates ranging between 6.5 and 18.5 kg N ha(-1) yr(-1). In addition to the effect of deposition on the nitrogen content of the two species, its influence on 15N natural abundance (delta15N values) and on productivity was examined. Annual increases of the mosses were used for all analyses. Significant relationships between bulk N deposition and nitrogen content were obtained for both species; delta15N-values reflected the ratio of NH4-N to NO3-N in deposition. A negative effect of nitrogen input on productivity, i.e. decreasing biomass per area with increasing N deposition due to a reduction of stem density, was particularly evident with P. schreberi. Monitoring of N deposition by means of mosses is considered an important supplement to existing monitoring programs. It makes possible an improved spatial resolution, and thus those areas that receive high loads of nitrogen are more easily discernible. PMID:15620592

  12. Estimating the loss of C, N and microbial biomass from Biological Soil Crusts under simulated rainfall

    NASA Astrophysics Data System (ADS)

    Gommeaux, M.; Malam Issa, O.; Bouchet, T.; Valentin, C.; Rajot, J.-L.; Bertrand, I.; Alavoine, G.; Desprats, J.-F.; Cerdan, O.; Fatondji, D.

    2012-04-01

    Most areas where biological soil crusts (BSC) develop undergo a climate with heavy but sparse rainfall events. The hydrological response of the BSC, namely the amount of runoff, is highly variable. Rainfall simulation experiments were conducted in Sadoré, south-western Niger. The aim was to estimate the influence of the BSC coverage on the quantity and quality of water, particles and solutes exported during simulated rainfall events. Ten 1 m2 plots were selected based on their various degree of BSC cover (4-89%) and type of underlying physical crust (structural or erosion crusts). The plots are located on similar sandy soil with moderate slope (3-6%). The experiments consisted of two rainfall events, spaced at 22-hours interval: 60 mm/h for 20 min, and 120 mm/h for 10 min. During each experiments particles dectached and runoff water were collected and filtered in the laboratory. C and N content were determined both in water and sediments samples.. These analyses were completed by measurements of phospholipid fatty acids and chlorophyll a contents in sediments and BSC samples collected before and after the rainfall. Mineral N and microbial biomass carbon of BSC samples were also analysed. The results confirmed that BSC reduce the loss of particles and exert a protective effect on soils with regard to particle detachment by raindrop. However there is no general relationship between the BSC coverage and the loss of C and N due to runoff. Contrarily, the C and N content in the sediments is negatively correlated to their mass. The type of physical crust on which the BSC develop also has to be taken into account. These results will contribute to the region-wide modeling of the role of BSC in biogeochemical cycles.

  13. Harvesting Duke FACE: improving estimates of productivity and biomass under elevated CO2

    NASA Astrophysics Data System (ADS)

    McCarthy, H. R.; Oren, R.; Kim, D.; Tor-ngern, P.; Johnsen, K. H.; Maier, C. A.

    2013-12-01

    Free air CO2 enrichment experiments (FACE) have greatly advanced our knowledge on the impacts of increasing atmospheric CO2 concentrations in developing and mature ecosystems. These experiments have provided years of data on changes in physiology and ecosystem functions, such as photosynthesis, water use, net primary productivity (NPP), ecosystem carbon storage, and nutrient cycling. As these experiments come to a close, there has also been the opportunity to add critically lacking biometric data, which can be obtained only through destructive measurements. After 15 years of CO2 elevation at the Duke Forest FACE, a 28 year old pine plantation with a hardwood understory, a vast array of biometric data was obtained through harvesting of >1150 trees in both elevated and ambient CO2 plots. Harvested trees included pines and hardwoods, understory and overstory trees. The harvest provided direct assessments of leaf, stem and branch biomass, as well as the vertical distribution of these masses. In combination with leaf and wood level properties (e.g. specific leaf area, wood density), it was possible to explore potential CO2 effects on allometric relationships between plant parts, and stem and canopy shape and distribution. Although stimulatory effects of elevated CO2 on NPP are well established in this forest (averaging 27%), harvest results thus far indicate few changes in basic allometric relationships, such as height-diameter relationships, proportion of mass contained in different plant parts (stems vs. leaves vs. branches), distribution of leaves within the canopy and stem shape. The coupling of site-specific biometric relationships with long-term data on tree growth and mortality will reduce current sources of uncertainty in estimates of NPP and carbon storage under future increased CO2 conditions. Recent efforts in data-model synthesis have demonstrated the critical need for such data as constraints and initial values in ecosystem and earth system models; these

  14. Estimated abundance of wild burros surveyed on Bureau of Land Management Lands in 2014

    USGS Publications Warehouse

    Griffin, Paul C.

    2015-01-01

    The Bureau of Land Management (BLM) requires accurate estimates of the numbers of wild horses (Equus ferus caballus) and burros (Equus asinus) living on the lands it manages. For over ten years, BLM in Arizona has used the simultaneous double-observer method of recording wild burros during aerial surveys and has reported population estimates for those surveys that come from two formulations of a Lincoln-Petersen type of analysis (Graham and Bell, 1989). In this report, I provide those same two types of burro population analysis for 2014 aerial survey data from six herd management areas (HMAs) in Arizona, California, Nevada, and Utah. I also provide burro population estimates based on a different form of simultaneous double-observer analysis, now in widespread use for wild horse surveys that takes into account the potential effects on detection probability of sighting covariates including group size, distance, vegetative cover, and other factors (Huggins, 1989, 1991). The true number of burros present in the six areas surveyed was not known, so population estimates made with these three types of analyses cannot be directly tested for accuracy in this report. I discuss theoretical reasons why the Huggins (1989, 1991) type of analysis should provide less biased estimates of population size than the Lincoln-Petersen analyses and why estimates from all forms of double-observer analyses are likely to be lower than the true number of animals present in the surveyed areas. I note reasons why I suggest using burro observations made at all available distances in analyses, not only those within 200 meters of the flight path. For all analytical methods, small sample sizes of observed groups can be problematic, but that sample size can be increased over time for Huggins (1989, 1991) analyses by pooling observations. I note ways by which burro population estimates could be tested for accuracy when there are radio-collared animals in the population or when there are simultaneous

  15. Spatially Explicit Large Area Biomass Estimation: Three Approaches Using Forest Inventory and Remotely Sensed Imagery in a GIS

    PubMed Central

    Wulder, Michael A.; White, Joanne C.; Fournier, Richard A.; Luther, Joan E.; Magnussen, Steen

    2008-01-01

    Forest inventory data often provide the required base data to enable the large area mapping of biomass over a range of scales. However, spatially explicit estimates of above-ground biomass (AGB) over large areas may be limited by the spatial extent of the forest inventory relative to the area of interest (i.e., inventories not spatially exhaustive), or by the omission of inventory attributes required for biomass estimation. These spatial and attributional gaps in the forest inventory may result in an underestimation of large area AGB. The continuous nature and synoptic coverage of remotely sensed data have led to their increased application for AGB estimation over large areas, although the use of these data remains challenging in complex forest environments. In this paper, we present an approach to generating spatially explicit estimates of large area AGB by integrating AGB estimates from multiple data sources; 1. using a lookup table of conversion factors applied to a non-spatially exhaustive forest inventory dataset (R2 = 0.64; RMSE = 16.95 t/ha), 2. applying a lookup table to unique combinations of land cover and vegetation density outputs derived from remotely sensed data (R2 = 0.52; RMSE = 19.97 t/ha), and 3. hybrid mapping by augmenting forest inventory AGB estimates with remotely sensed AGB estimates where there are spatial or attributional gaps in the forest inventory data. Over our 714,852 ha study area in central Saskatchewan, Canada, the AGB estimate generated from the forest inventory was approximately 40 Mega tonnes (Mt); however, the inventory estimate represents only 51% of the total study area. The AGB estimate generated from the remotely sensed outputs that overlap those made from the forest inventory based approach differ by only 2 %; however in total, the remotely sensed estimate is 30 % greater (58 Mt) than the estimate generated from the forest inventory when the entire study area is accounted for. Finally, using the hybrid approach, whereby

  16. Using LANDSAT digital data for estimating green biomass. [Throckmorton, Texas test site and Great Plans Corridor, US

    NASA Technical Reports Server (NTRS)

    Deering, D. W.; Haas, R. H. (Principal Investigator)

    1980-01-01

    The author has identified the following significant results. Relationships between the quantity of mixed prairie rangeland vegetation and LANDSAT MSS response were studied during four growing seasons at test sites throughout the United States Great Plans region. A LANDSAT derived parameter, the normalized difference was developed from theoretical considerations fro statistical estimation of the amount and seasonal condition of rangeland vegetation. This parameter was tested for application to local assessment of green forage biomass and regional monitoring of range feed conditions and drought. Results show that for grasslands in the Great Plains with near continuous vegetative cover and free of heavy brush and forbs, the LANDSAT digital data can provide a useful estimate of the quantity of green forage biomass (within 250 kg/ha), and at least five levels of pasture and range feed conditions can be adequately mapped for extended regions.

  17. A Rao-Blackwellized particle filter for joint parameter estimation and biomass tracking in a stochastic predator-prey system.

    PubMed

    Martín-Fernández, Laura; Gilioli, Gianni; Lanzarone, Ettore; Miguez, Joaquin; Pasquali, Sara; Ruggeri, Fabrizio; Ruiz, Diego P

    2014-06-01

    Functional response estimation and population tracking in predator-prey systems are critical problems in ecology. In this paper we consider a stochastic predator-prey system with a Lotka-Volterra functional response and propose a particle filtering method for: (a) estimating the behavioral parameter representing the rate of effective search per predator in the functional response and (b) forecasting the population biomass using field data. In particular, the proposed technique combines a sequential Monte Carlo sampling scheme for tracking the time-varying biomass with the analytical integration of the unknown behavioral parameter. In order to assess the performance of the method, we show results for both synthetic and observed data collected in an acarine predator-prey system, namely the pest mite Tetranychus urticae and the predatory mite Phytoseiulus persimilis. PMID:24506552

  18. Estimates of abundance of vapor condensate from the impacts of asteroids and comets on the Moon

    NASA Astrophysics Data System (ADS)

    Svetsov, Vladimir; Shuvalov, Valery

    The hypervelocity impacts of asteroids and comets on the Moon and planets can vaporize a substantial mass of target rock comparable with the mass of a projectile. The vapor expands, forming a vapor plume, and, when it cools and reaches the liquid-vapor coexistence curve, molten spherules can condense from the vapor. Ejecta layers bearing condensate spherules have been found on the Earth along with melt droplet spherules, however, the impact-vapor condensate is extremely rare among the lunar samples. The current average impact velocities on the Moon and Earth differ only slightly, and the main distinction is probably that the vapor plume expands to the atmosphere on the Earth and into vacuum on the Moon. Using available ANEOS equations of states for quartz and dunite we have determined parameters behind shock waves for impact velocities from 9 to 30 km/s and calculated release adiabats from various points on the Hugoniot curves to very low pressures. For impacts of quartz projectiles on quartz targets at velocities 9-16 km/s the release adiabats come to the liquid branch of the two-phase curve and, during the following expansion of two-phase mixture, the shock-compressed material vaporizes and does not condense. The condensate can appear during the plume expansion only at higher impact velocities. Using our hydrocode SOVA, we have made numerical simulations of the impacts of quartz and dunite spherical projectiles on the targets from the same materials. Along with the masses of condensates we calculated the masses of melted material. The calculated ratio of vaporized mass to the melted mass proved to be of the order of 0.1. However, we obtained that at velocities below 20 km/s the condensate mass is only a small fraction of vapor and melt masses and, consequently, the major part of vapor disperses in vacuum in the form of separate molecules. At impact velocity 15 km/s the relative abundance of silicate condensates is 0.001 - 0.0001 in accordance with the studies of

  19. Automated and Accurate Estimation of Gene Family Abundance from Shotgun Metagenomes.

    PubMed

    Nayfach, Stephen; Bradley, Patrick H; Wyman, Stacia K; Laurent, Timothy J; Williams, Alex; Eisen, Jonathan A; Pollard, Katherine S; Sharpton, Thomas J

    2015-11-01

    Shotgun metagenomic DNA sequencing is a widely applicable tool for characterizing the functions that are encoded by microbial communities. Several bioinformatic tools can be used to functionally annotate metagenomes, allowing researchers to draw inferences about the functional potential of the community and to identify putative functional biomarkers. However, little is known about how decisions made during annotation affect the reliability of the results. Here, we use statistical simulations to rigorously assess how to optimize annotation accuracy and speed, given parameters of the input data like read length and library size. We identify best practices in metagenome annotation and use them to guide the development of the Shotgun Metagenome Annotation Pipeline (ShotMAP). ShotMAP is an analytically flexible, end-to-end annotation pipeline that can be implemented either on a local computer or a cloud compute cluster. We use ShotMAP to assess how different annotation databases impact the interpretation of how marine metagenome and metatranscriptome functional capacity changes across seasons. We also apply ShotMAP to data obtained from a clinical microbiome investigation of inflammatory bowel disease. This analysis finds that gut microbiota collected from Crohn's disease patients are functionally distinct from gut microbiota collected from either ulcerative colitis patients or healthy controls, with differential abundance of metabolic pathways related to host-microbiome interactions that may serve as putative biomarkers of disease. PMID:26565399

  20. Automated and Accurate Estimation of Gene Family Abundance from Shotgun Metagenomes

    PubMed Central

    Nayfach, Stephen; Bradley, Patrick H.; Wyman, Stacia K.; Laurent, Timothy J.; Williams, Alex; Eisen, Jonathan A.; Pollard, Katherine S.; Sharpton, Thomas J.

    2015-01-01

    Shotgun metagenomic DNA sequencing is a widely applicable tool for characterizing the functions that are encoded by microbial communities. Several bioinformatic tools can be used to functionally annotate metagenomes, allowing researchers to draw inferences about the functional potential of the community and to identify putative functional biomarkers. However, little is known about how decisions made during annotation affect the reliability of the results. Here, we use statistical simulations to rigorously assess how to optimize annotation accuracy and speed, given parameters of the input data like read length and library size. We identify best practices in metagenome annotation and use them to guide the development of the Shotgun Metagenome Annotation Pipeline (ShotMAP). ShotMAP is an analytically flexible, end-to-end annotation pipeline that can be implemented either on a local computer or a cloud compute cluster. We use ShotMAP to assess how different annotation databases impact the interpretation of how marine metagenome and metatranscriptome functional capacity changes across seasons. We also apply ShotMAP to data obtained from a clinical microbiome investigation of inflammatory bowel disease. This analysis finds that gut microbiota collected from Crohn’s disease patients are functionally distinct from gut microbiota collected from either ulcerative colitis patients or healthy controls, with differential abundance of metabolic pathways related to host-microbiome interactions that may serve as putative biomarkers of disease. PMID:26565399

  1. New method for estimating bacterial cell abundances in natural samples by use of sublimation

    NASA Technical Reports Server (NTRS)

    Glavin, Daniel P.; Cleaves, H. James; Schubert, Michael; Aubrey, Andrew; Bada, Jeffrey L.

    2004-01-01

    We have developed a new method based on the sublimation of adenine from Escherichia coli to estimate bacterial cell counts in natural samples. To demonstrate this technique, several types of natural samples, including beach sand, seawater, deep-sea sediment, and two soil samples from the Atacama Desert, were heated to a temperature of 500 degrees C for several seconds under reduced pressure. The sublimate was collected on a cold finger, and the amount of adenine released from the samples was then determined by high-performance liquid chromatography with UV absorbance detection. Based on the total amount of adenine recovered from DNA and RNA in these samples, we estimated bacterial cell counts ranging from approximately 10(5) to 10(9) E. coli cell equivalents per gram. For most of these samples, the sublimation-based cell counts were in agreement with total bacterial counts obtained by traditional DAPI (4,6-diamidino-2-phenylindole) staining.

  2. Comparing the above-ground component biomass estimates of western junipers using airborne and full-waveform terrestrial laser scanning data

    NASA Astrophysics Data System (ADS)

    Shrestha, R.; Glenn, N. F.; Spaete, L.; Hardegree, S. P.

    2012-12-01

    With the rapid expansion into shrub steppe and grassland ecosystems over the last century, western juniper (Juniperus occidentalis var. occidentalis Hook) is becoming a major component of the regional carbon pool in the Intermountain West. Understanding how biomass is allocated across individual tree components is necessary to understand the uncertainties in biomass estimates and more accurately quantify biomass and carbon dynamics in these ecosystems. Estimates of component biomass are also important for canopy fuel load assessment and predicting rangeland fire behavior. Airborne LiDAR can capture vegetation structure over larger scales, but the high crown penetration and sampling density of terrestrial laser scanner (TLS) instruments can better capture tree components. In this study, we assessed the ability of airborne LiDAR to estimate biomass of tree components of western juniper with validation data from field measured tees and a full-waveform TLS. Sixteen juniper trees (height range 1.5-10 m) were randomly selected using a double sampling strategy from different height classes in the Reynolds Creek Experimental Watershed in the Owyhee Mountains, southwestern Idaho, USA. Each tree was scanned with a full-waveform TLS, and the dry biomass of each component (foliage, branches and main stem) were measured by destructive harvesting of the trees. We compare the allometric relationships of biomass estimates of the tree components obtained from field-measured trees and TLS-based estimates with the estimates from discrete-return airborne-LiDAR based estimates.

  3. [Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

    PubMed

    Liu, Feng; Tan, Chang; Lei, Pi-Feng

    2014-11-01

    Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation. PMID:25898621

  4. Uncertainty estimation in integrated LiDAR- and radar-derived biomass maps at key national-level map scales

    NASA Astrophysics Data System (ADS)

    Joshi, N.; Fensholt, R.; Saatchi, S. S.; Mitchard, E. T.

    2013-12-01

    The international Reducing Emissions from Deforestation and Degradation (REDD) program requires accurate and cost-effective techniques of national-level mapping of above-ground biomass (AGB) and ground-sampling strategies. This paper explores a multi-sensor (radar and low-density airborne LiDAR) integration approach for country-wide AGB estimation and mapping in Denmark, selected as a test-country due to the unique availability of country-wide remote sensing and forest inventory data. We assess the potential use of ALOS PALSAR L-band radar and ENVISAT ASAR C-band radar in prediction and mapping of AGB with accuracies similar to LiDAR-derived AGB estimates at different map scales. We start by creating a LiDAR-based ';ground truth' map, using LiDAR-derived 95th Percentile of heights >1 m weighted by the Canopy Density ratio, together with 113 AGB plots to map AGB at a 0.25 ha resolution across the country. A leave-20%-out cross-validation indicates that the AGB estimates have a mean absolute error of 41 Mg ha-1 and a negative mean bias error of 1.7 Mg ha-1. Though the LiDAR model appears to have an overall species-specific bias for conifers and broadleaf (-5.2 Mg ha-1 and +12.3 Mg ha-1 respectively), these are found to be insignificant (p>0.05) when accounting for species sampling bias and the under-prediction of plots containing high-biomass (> 350 Mg ha-1). Using the LiDAR-derived biomass map as a ';truth-map', biomass-backscatter relations will be quantified at three map scales (0.25 ha, 1 ha and 100 ha) and using three spatial sampling frameworks (full-dataset, stratified random sampling equally representing low and high biomass pixels, clustered sampling). The approach aims to derive a minimal-sampling and mapping strategy for L- and C-band radar that achieves at least 20% accuracy in AGB estimation, along with quantified sources of error from ground-AGB estimates, scaling and sampling. It is expected that mapping techniques, uncertainty quantification and

  5. Estimating number of species and relative abundances in stream-fish communities: effects of sampling effort and discontinuous spatial distributions

    USGS Publications Warehouse

    Angermeier, Paul L.; Smogor, Roy A.

    1995-01-01

    We sampled fishes and measured microhabitat in series of contiguous habitat units (riffles, runs, pools) in three Virginia streams. We used Monte Carlo simulations to construct hypothetical series of habitat units, then examined how number of species, similarity in relative abundances, and number of microhabitats accumulated with increasing number of habitat units (i.e., sampling effort). Proportions of all species and microhabitats represented were relatively low and variable at low sampling effort, but increased asymptotically and became less variable with greater sampling effort. To facilitate comparisons among streams, we fitted simulation results to negative exponential curves. The curves indicated that 90% of the species present were usually found by sampling 5 to 14 habitat units (stream length of 22–67 stream widths). Estimates of species relative abundances required less sampling effort for a given accuracy than estimates of number of species. Rates of species accumulation (with effort) varied among streams and reflected discontinuity in species distributions among habitat units. Most discontinuity seemed to be due to low population density rather than to habitat selectivity. Results from an Illinois stream corroborated our findings from Virginia, and suggested that greater sampling effort is needed to characterize fish community structure in more homogeneous stream reaches.

  6. A sampling design and model for estimating abundance of Nile crocodiles while accounting for heterogeneity of detectability of multiple observers

    USGS Publications Warehouse

    Shirley, Matthew H.; Dorazio, Robert M.; Abassery, Ekramy; Elhady, Amr A.; Mekki, Mohammed S.; Asran, Hosni H.

    2012-01-01

    As part of the development of a management program for Nile crocodiles in Lake Nasser, Egypt, we used a dependent double-observer sampling protocol with multiple observers to compute estimates of population size. To analyze the data, we developed a hierarchical model that allowed us to assess variation in detection probabilities among observers and survey dates, as well as account for variation in crocodile abundance among sites and habitats. We conducted surveys from July 2008-June 2009 in 15 areas of Lake Nasser that were representative of 3 main habitat categories. During these surveys, we sampled 1,086 km of lake shore wherein we detected 386 crocodiles. Analysis of the data revealed significant variability in both inter- and intra-observer detection probabilities. Our raw encounter rate was 0.355 crocodiles/km. When we accounted for observer effects and habitat, we estimated a surface population abundance of 2,581 (2,239-2,987, 95% credible intervals) crocodiles in Lake Nasser. Our results underscore the importance of well-trained, experienced monitoring personnel in order to decrease heterogeneity in intra-observer detection probability and to better detect changes in the population based on survey indices. This study will assist the Egyptian government establish a monitoring program as an integral part of future crocodile harvest activities in Lake Nasser

  7. Field trials of line transect methods applied to estimation of desert tortoise abundance

    USGS Publications Warehouse

    Anderson, David R.; Burnham, Kenneth P.; Lubow, Bruce C.; Thomas, L. E. N.; Corn, Paul Stephen; Medica, Philip A.; Marlow, R.W.

    2001-01-01

    We examine the degree to which field observers can meet the assumptions underlying line transect sampling to monitor populations of desert tortoises (Gopherus agassizii). We present the results of 2 field trials using artificial tortoise models in 3 size classes. The trials were conducted on 2 occasions on an area south of Las Vegas, Nevada, where the density of the test population was known. In the first trials, conducted largely by experienced biologists who had been involved in tortoise surveys for many years, the density of adult tortoise models was well estimated (-3.9% bias), while the bias was higher (-20%) for subadult tortoise models. The bias for combined data was -12.0%. The bias was largely attributed to the failure to detect all tortoise models on or near the transect centerline. The second trials were conducted with a group of largely inexperienced student volunteers and used somewhat different searching methods, and the results were similar to the first trials. Estimated combined density of subadult and adult tortoise models had a negative bias (-7.3%), again attributable to failure to detect some models on or near the centerline. Experience in desert tortoise biology, either comparing the first and second trials or in the second trial with 2 experienced biologists versus 16 novices, did not have an apparent effect on the quality of the data or the accuracy of the estimates. Observer training, specific to line transect sampling, and field testing are important components of a reliable survey. Line transect sampling represents a viable method for large-scale monitoring of populations of desert tortoise; however, field protocol must be improved to assure the key assumptions are met.

  8. An evaluation of the efficiency of minnow traps for estimating the abundance of minnows in desert spring systems

    USGS Publications Warehouse

    Peterson, James T.; Scheerer, Paul D.; Clements, Shaun

    2015-01-01

    Desert springs are sensitive aquatic ecosystems that pose unique challenges to natural resource managers and researchers. Among the most important of these is the need to accurately quantify population parameters for resident fish, particularly when the species are of special conservation concern. We evaluated the efficiency of baited minnow traps for estimating the abundance of two at-risk species, Foskett Speckled Dace Rhinichthys osculus ssp. and Borax Lake Chub Gila boraxobius, in desert spring systems in southeastern Oregon. We evaluated alternative sample designs using simulation and found that capture–recapture designs with four capture occasions would maximize the accuracy of estimates and minimize fish handling. We implemented the design and estimated capture and recapture probabilities using the Huggins closed-capture estimator. Trap capture probabilities averaged 23% and 26% for Foskett Speckled Dace and Borax Lake Chub, respectively, but differed substantially among sample locations, through time, and nonlinearly with fish body size. Recapture probabilities for Foskett Speckled Dace were, on average, 1.6 times greater than (first) capture probabilities, suggesting “trap-happy” behavior. Comparison of population estimates from the Huggins model with the commonly used Lincoln–Petersen estimator indicated that the latter underestimated Foskett Speckled Dace and Borax Lake Chub population size by 48% and by 20%, respectively. These biases were due to variability in capture and recapture probabilities. Simulation of fish monitoring that included the range of capture and recapture probabilities observed indicated that variability in capture and recapture probabilities in time negatively affected the ability to detect annual decreases by up to 20% in fish population size. Failure to account for variability in capture and recapture probabilities can lead to poor quality data and study inferences. Therefore, we recommend that fishery researchers and

  9. Double-observer approach to estimating egg mass abundance of vernal pool breeding amphibians

    USGS Publications Warehouse

    Grant, E.H.C.; Jung, R.E.; Nichols, J.D.; Hines, J.E.

    2005-01-01

    Interest in seasonally flooded pools, and the status of associated amphibian populations, has initiated programs in the northeastern United States to document and monitor these habitats. Counting egg masses is an effective way to determine the population size of pool-breeding amphibians, such as wood frogs (Rana sylvatica) and spotted salamanders (Ambystoma maculatum). However, bias is associated with counts if egg masses are missed. Counts unadjusted for the proportion missed (i.e., without adjustment for detection probability) could lead to false assessments of population trends. We used a dependent double-observer method in 2002-2003 to estimate numbers of wood frog and spotted salamander egg masses at seasonal forest pools in 13 National Wildlife Refuges, 1 National Park, 1 National Seashore, and 1 State Park in the northeastern United States. We calculated detection probabilities for egg masses and examined whether detection probabilities varied by species, observers, pools, and in relation to pool characteristics (pool area, pool maximum depth, within-pool vegetation). For the 2 years, model selection indicated that no consistent set of variables explained the variation in data sets from individual Refuges and Parks. Because our results indicated that egg mass detection probabilities vary spatially and temporally, we conclude that it is essential to use estimation procedures, such as double-observer methods with egg mass surveys, to determine population sizes and trends of these species.

  10. Estimating Dungeness crab (Cancer magister) abundance: Crab pots and dive transects compared

    USGS Publications Warehouse

    Taggart, S.J.; O'Clair, C. E.; Shirley, T.C.; Mondragon, J.

    2004-01-01

    Dungeness crabs (Cancer magister) were sampled with commercial pots and counted by scuba divers on benthic transects at eight sites near Glacier Bay, Alaska. Catch per unit of effort (CPUE) from pots was compared to the density estimates from dives to evaluate the bias and power of the two techniques. Yearly sampling was conducted in two seasons: April and September, from 1992 to 2000. Male CPUE estimates from pots were significantly lower in April than in the following September; a step-wise regression demonstrated that season accounted for more of the variation in male CPUE than did temperature. In both April and September, pot sampling was significantly biased against females. When females were categorized as ovigerous and nonovigerous, it was clear that ovigerous females accounted for the majority of the bias because pots were not biased against nonovigerous females. We compared the power of pots and dive transects in detecting trends in populations and found that pots had much higher power than dive transects. Despite their low power, the dive transects were very useful for detecting bias in our pot sampling and in identifying the optimal times of year to sample so that pot bias could be avoided.

  11. A New Method for Estimating Bacterial Abundances in Natural Samples using Sublimation

    NASA Technical Reports Server (NTRS)

    Glavin, Daniel P.; Cleaves, H. James; Schubert, Michael; Aubrey, Andrew; Bada, Jeffrey L.

    2004-01-01

    We have developed a new method based on the sublimation of adenine from Escherichia coli to estimate bacterial cell counts in natural samples. To demonstrate this technique, several types of natural samples including beach sand, seawater, deep-sea sediment, and two soil samples from the Atacama Desert were heated to a temperature of 500 C for several seconds under reduced pressure. The sublimate was collected on a cold finger and the amount of adenine released from the samples then determined by high performance liquid chromatography (HPLC) with UV absorbance detection. Based on the total amount of adenine recovered from DNA and RNA in these samples, we estimated bacterial cell counts ranging from approx. l0(exp 5) to l0(exp 9) E. coli cell equivalents per gram. For most of these samples, the sublimation based cell counts were in agreement with total bacterial counts obtained by traditional DAPI staining. The simplicity and robustness of the sublimation technique compared to the DAPI staining method makes this approach particularly attractive for use by spacecraft instrumentation. NASA is currently planning to send a lander to Mars in 2009 in order to assess whether or not organic compounds, especially those that might be associated with life, are present in Martian surface samples. Based on our analyses of the Atacama Desert soil samples, several million bacterial cells per gam of Martian soil should be detectable using this sublimation technique.

  12. Biomass burning emissions of reactive gases estimated from satellite data analysis and ecosystem modeling for the Brazilian Amazon region

    NASA Astrophysics Data System (ADS)

    Potter, Christopher; Brooks-Genovese, Vanessa; Klooster, Steven; Torregrosa, Alicia

    2002-10-01

    To produce a new daily record of trace gas emissions from biomass burning events for the Brazilian Legal Amazon, we have combined satellite advanced very high resolution radiometer (AVHRR) data on fire counts together for the first time with vegetation greenness imagery as inputs to an ecosystem biomass model at 8 km spatial resolution. This analysis goes beyond previous estimates for reactive gas emissions from Amazon fires, owing to a more detailed geographic distribution estimate of vegetation biomass, coupled with daily fire activity for the region (original 1 km resolution), and inclusion of fire effects in extensive areas of the Legal Amazon (defined as the Brazilian states of Acre, Amapá, Amazonas, Maranhao, Mato Grosso, Pará, Rondônia, Roraima, and Tocantins) covered by open woodland, secondary