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Sample records for abundance biomass estimates

  1. 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.

  2. 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

  3. 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

  4. Abundance estimation and conservation biology

    USGS Publications Warehouse

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

    2004-01-01

    Abundance is the state variable of interest in most population–level ecological research and in most programs involving management and conservation of animal populations. Abundance is the single parameter of interest in capture–recapture models for closed populations (e.g., Darroch, 1958; Otis et al., 1978; Chao, 2001). The initial capture–recapture models developed for partially (Darroch, 1959) and completely (Jolly, 1965; Seber, 1965) open populations represented efforts to relax the restrictive assumption of population closure for the purpose of estimating abundance. Subsequent emphases in capture–recapture work were on survival rate estimation in the 1970’s and 1980’s (e.g., Burnham et al., 1987; Lebreton et al.,1992), and on movement estimation in the 1990’s (Brownie et al., 1993; Schwarz et al., 1993). However, from the mid–1990’s until the present time, capture–recapture investigators have expressed a renewed interest in abundance and related parameters (Pradel, 1996; Schwarz & Arnason, 1996; Schwarz, 2001). The focus of this session was abundance, and presentations covered topics ranging from estimation of abundance and rate of change in abundance, to inferences about the demographic processes underlying changes in abundance, to occupancy as a surrogate of abundance. The plenary paper by Link & Barker (2004) is provocative and very interesting, and it contains a number of important messages and suggestions. Link & Barker (2004) emphasize that the increasing complexity of capture–recapture models has resulted in large numbers of parameters and that a challenge to ecologists is to extract ecological signals from this complexity. They offer hierarchical models as a natural approach to inference in which traditional parameters are viewed as realizations of stochastic processes. These processes are governed by hyperparameters, and the inferential approach focuses on these hyperparameters. Link & Barker (2004) also suggest that our attention

  5. The estimation of microbial biomass.

    PubMed

    Harris, C M; Kell, D B

    1985-01-01

    Methods that have been used to estimate the content, and in some cases the nature, of the microbial biomass in a sample are reviewed. The methods may be categorised in terms of their principle (physical, chemical, biological or mathematical/computational), their speed (real-time or otherwise) and the amount of automation/expense involved. For sparse populations, where the output signal is to be enhanced by growth of the organisms, physical, chemical and biological approaches may be of equal merit, whilst in systems, such as laboratory and industrial fermentations, in which the microbial biomass content is high, physical methods (alone) can permit the real-time estimation of microbial biomass.

  6. 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.

  7. Abundance, biomass and production of juvenile flatfish in southeastern kattegat

    NASA Astrophysics Data System (ADS)

    Pihl, L.

    Abundance, biomass and production of juvenile 0- and 1-group flatfish were estimated at 1.5 to 11.0 m depth from May 1984 to May 1987 in southeastern Kattegat. Species studied were: Plaice, Pleuronectes platessa (L.), sole, Solea solea (L.), dab, Limanda limanda (L.), turbot, Scophthalmus maximus (L.), brill, Scophthalmus rhombus (L.), and flounder, Platichthys flesus (L.). Highest abundance and biomass of 0- and 1-group flatfish occurred in July and August each year. Plaice, sole, turbot, brill and flounder were mainly found as 0-group at 1.5 to 5.0 m, but as 1-group they also occupied deeper water. 0- and 1-group dab occurred in the highest density at 5.0 to 11.0 m. Total summer (May to September) production at 1.5 to 5.0 m of the dominant species, plaice, sole and dab, were 98, 23 and 88 g AFDW per 100 m 2 during the three years investigated. Corresponding figures for the depth range 5.0 to 11.0 m were 12, 13 and 53 g AFDW per 100 m 2. Effects of eutrophication on the area as a nursery ground for flatfish are discussed.

  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. [Effects of sewage discharge on abundance and biomass of meiofauna].

    PubMed

    Huang, De-Ming; Liu, Xiao-Shou; Lin, Ming-Xian; Chen, Huai-Pu; Wei, Lian-Ming; Huang, Xin; Zhang, Zhi-Nan

    2014-10-01

    In order to elucidate the effects of sewage discharge on abundance and biomass of meio- fauna, a seasonal survey was carried out on meiofauna at stations with different distances to a sewage outlet in the middle intertidal zone of No. 1 bathing beach in Huiquan Bay, Qingdao in spring (April), summer (August), autumn (October) and winter (December), 2011. The results showed that the annual average meiofaunal abundance was (1859.9 ± 705.1) ind · 10 cm(-2), with higher values of (2444.9 ± 1220.5) ind · 10 cm(-2) at Station S2 (20 m to the sewage outlet) and (2492.2 ± 1839.9) ind · 10 cm(-2) at Station S3 (40 m to the sewage outlet), while the lowest value of (327.9 ± 183.2) ind · 10 cm(-2) was observed at Station S1 (0 m to the sewage outlet) in terms of horizontal distribution. The annual average biomass was (1513.4 ± 372.7) μg · 10 cm(-2). Meiofaunal abundance and biomass varied seasonally with the highest values in spring and the lowest values in summer. A total of 11 meiofaunal groups were identified, including nematodes, copepods, polychaetes, oligochaetes, tardigrades, halacaroideans, planarians, ostracods, isopods, crustacean nauplii and others. Free-living marine nematodes were the dominant group constituting 83. 1% of the total abundance, followed by benthic copepods, accounting for 12. 8% of the total abundance. In terms of vertical distribution, most of the meiofauna concentrated in the top 0-2 cm, and the meiofauna abundance decreased with increasing the sediment depth. Meiofauna was also noted to migrate deeper into the sediment in the winter. Pearson correlation analysis showed that meiofaunal abundance and biomass had highly significant negative correlations with sediment median particle diameter and organic matter content. In addition, tourism-induced activities affected meiofaunal abundance and distribution. A comparison with historical data from similar studies was carried out, and the applicability of the ratio of abundance of nematodes

  12. Estimating phytoplankton biomass and productivity. Final report

    SciTech Connect

    Janik, J.J.; Taylor, W.D.; Lambou, V.W.

    1981-06-01

    Estimates of phytoplankton biomass and rates of production can provide a manager with some insight into questions concerning trophic state, water quality, and aesthetics. Methods for estimation of phytoplankton biomass include a gravimetric approach, microscopic enumeration, and chlorophyll analysis, Strengths and weaknesses of these and other methods are presented. Productivity estimation techniques are discussed including oxygen measurement, carbon dioxide measurements, carbon 14 measurements, and the chlorophyll method. Again, strengths and weaknesses are presented.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  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. 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.

  20. 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.

  1. 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.

  2. 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...

  3. 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...

  4. 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.

  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. 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.

  7. 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.

  8. 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

  9. [Estimation of Shenyang urban forest green biomass].

    PubMed

    Liu, Chang-fu; He, Xing-yuan; Chen, Wei; Zhao, Gui-ling; Xu, Wen-duo

    2007-06-01

    Based on ARC/GIS and by using the method of "planar biomass estimation", the green biomass (GB) of Shenyang urban forests was measured. The results demonstrated that the GB per unit area was the highest (3.86 m2.m(-2)) in landscape and relaxation forest, and the lowest (2.27 m2.m(-2)) in ecological and public welfare forest. The GB per unit area in urban forest distribution area was 2.99 m2.m(-2), and that of the whole Shenyang urban area was 0.25 m2.m(-2). The total GB of Shenyang urban forests was about 1.13 x 10(8) m2, among which, subordinated forest, ecological and public welfare forest, landscape and relaxation forest, road forest, and production and management forest accounted for 36.64% , 23.99% , 19.38% , 16.20% and 3.79%, with their GB being 4. 15 x 10(7), 2.72 x 10(7), 2.20 x 10(7), 1.84 x 10(7) and 0.43 x 10(7) m2, respectively. The precision of the method "planar biomass estimation" was 91.81% (alpha = 0.05) by credit test. PMID:17763717

  10. Relative importance of phosphorus, fish biomass, and watershed land use as drivers of phytoplankton abundance in shallow lakes.

    PubMed

    Gorman, Matt W; Zimmer, Kyle D; Herwig, Brian R; Hanson, Mark A; Wright, Robert G; Vaughn, Sean R; Younk, Jerry A

    2014-01-01

    Phytoplankton abundance in shallow lakes is potentially influenced by ambient phosphorus concentrations, nutrient loading accentuated by human activities in lake watersheds, and abundance of planktivorous and benthivorous fish. However, few studies have simultaneously assessed the relative importance of these factors influencing phytoplankton abundance over large spatial scales. We assessed relative influences of watershed characteristics, total phosphorus concentrations, and fish biomass on phytoplankton abundance in 70 shallow lakes in western Minnesota (USA) during summer 2005 and 2006. Our independent variables included total phosphorus (TP), benthivore biomass, planktivore biomass, summed planktivore and benthivore biomass (summed fish), areal extent of agriculture in the watershed, region (prairie versus parkland lakes), and year. Predictive models containing from one to three independent variables were compared using an information theoretic approach. The most parsimonious model consisted of TP and summed fish, and had over 10,000-fold greater support compared to models using just TP or summed fish, or models comprised of other variables. We also found no evidence that relative importance of predictor variables differed between regions or years, and parameter estimates of TP and summed fish were temporally and spatially consistent. TP and summed fish were only weakly correlated, and the model using both variables was a large improvement over using either variable alone. This indicates these two variables can independently increase phytoplankton abundance, which emphasizes the importance of managing both nutrients and fish when trying to control phytoplankton abundance in shallow lakes.

  11. Remarkable amphibian biomass and abundance in an isolated wetland: implications for wetland conservation.

    PubMed

    Gibbons, J Whitfield; Winne, Christopher T; Scott, David E; Willson, John D; Glaudas, Xavier; Andrews, Kimberly M; Todd, Brian D; Fedewa, Luke A; Wilkinson, Lucas; Tsaliagos, Ria N; Harper, Steven J; Greene, Judith L; Tuberville, Tracey D; Metts, Brian S; Dorcas, Michael E; Nestor, John P; Young, Cameron A; Akre, Tom; Reed, Robert N; Buhlmann, Kurt A; Norman, Jason; Croshaw, Dean A; Hagen, Cris; Rothermel, Betsie B

    2006-10-01

    Despite the continuing loss of wetland habitats and associated declines in amphibian populations, attempts to translate wetland losses into measurable losses to ecosystems have been lacking. We estimated the potential productivity from the amphibian community that would be compromised by the loss of a single isolated wetland that has been protected from most industrial, agricultural, and urban impacts for the past 54 years. We used a continuous drift fence at Ellenton Bay, a 10-ha freshwater wetland on the Savannah River Site, near Aiken, South Carolina (U.S.A.), to sample all amphibians for 1 year following a prolonged drought. Despite intensive agricultural use of the land surrounding Ellenton Bay prior to 1951, we documented 24 species and remarkably high numbers and biomass of juvenile amphibians (>360,000 individuals; >1,400 kg) produced during one breeding season. Anurans (17 species) were more abundant than salamanders (7 species), comprising 96.4% of individual captures. Most (95.9%) of the amphibian biomass came from 232095 individuals of a single species of anuran (southern leopard frog[Rana sphenocephala]). Our results revealed the resilience of an amphibian community to natural stressors and historical habitat alteration and the potential magnitude of biomass and energy transfer from isolated wetlands to surrounding terrestrial habitat. We attributed the postdrought success of amphibians to a combination of adult longevity (often >5 years), a reduction in predator abundance, and an abundance of larval food resources. Likewise, the increase of forest cover around Ellenton Bay from <20% in 1951 to >60% in 2001 probably contributed to the long-term persistence of amphibians at this site. Our findings provide an optimistic counterpoint to the issue of the global decline of biological diversity by demonstrating that conservation efforts can mitigate historical habitat degradation.

  12. 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

  13. 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.

  14. 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

  15. 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

  16. Toward reliable estimates of abundance: comparing index methods to assess the abundance of a Mammalian predator.

    PubMed

    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

  17. 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.

  18. 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.

  19. Zooplankton biomass estimated from digitalized images in Antarctic waters: A calibration exercise

    NASA Astrophysics Data System (ADS)

    HernáNdez-León, Santiago; Montero, Irene

    2006-05-01

    The direct measurement of zooplankton biomass following the different analytical procedures normally requires the destruction of the samples. The use of conversion factors to estimate biomass from nondestructive methods is still a challenge. The widespread use of image analyzers and optical counters in biological oceanography provides a useful tool to measure the abundance and size spectrum of zooplanktonic organisms in real or quasi-real time. Both methodologies measure the equivalent spherical diameter and/or the body area of organisms. In order to estimate biomass from the highly valuable information generated by the size spectrum of the sample, we measured the relationship between individual body area and individual biomass of the most common species and groups of zooplankton in Antarctic waters. The slope of the regression for each different species and groups of taxa was not significantly different from that obtained by pooling all taxa, thus providing a general relationship for the entire size spectrum of zooplankton. The biomass estimated from the body area spectrum of samples obtained around the Antarctic Peninsula agreed with other measurements of biomass in the region. The proposed conversion factor could provide for rapid estimates of biomass of net-collected zooplankton from imaging devices or optical plankton counters.

  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. Estimating site occupancy and abundance using indirect detection indices

    USGS Publications Warehouse

    Stanley, T.R.; Royle, J. Andrew

    2005-01-01

    Knowledge of factors influencing animal distribution and abundance is essential in many areas of ecological research, management, and policy-making. Because common methods for modeling and estimating abundance (e.g., capture-recapture, distance sampling) are sometimes not practical for large areas or elusive species, indices are sometimes used as surrogate measures of abundance. We present an extension of the Royle and Nichols (2003) generalization of the MacKenzie et al. (2002) site-occupancy model that incorporates length of the sampling interval into the, model for detection probability. As a result, we obtain a modeling framework that shows how useful information can be extracted from a class of index methods we call indirect detection indices (IDIs). Examples of IDIs include scent station, tracking tube, snow track, tracking plate, and hair snare surveys. Our model is maximum likelihood, and it can be used to estimate site occupancy and model factors influencing patterns of occupancy and abundance in space. Under certain circumstances, it can also be used to estimate abundance. We evaluated model properties using Monte Carlo simulations and illustrate the method with tracking tube and scent station data. We believe this model will be a useful tool for determining factors that influence animal distribution and abundance.

  2. Incorporating availability for detection in estimates of bird abundance

    USGS Publications Warehouse

    Diefenbach, D.R.; Marshall, M.R.; Mattice, J.A.; Brauning, D.W.

    2007-01-01

    Several bird-survey methods have been proposed that provide an estimated detection probability so that bird-count statistics can be used to estimate bird abundance. However, some of these estimators adjust counts of birds observed by the probability that a bird is detected and assume that all birds are available to be detected at the time of the survey. We marked male Henslow's Sparrows (Ammodramus henslowii) and Grasshopper Sparrows (A. savannarum) and monitored their behavior during May-July 2002 and 2003 to estimate the proportion of time they were available for detection. We found that the availability of Henslow's Sparrows declined in late June to <10% for 5- or 10-min point counts when a male had to sing and be visible to the observer; but during 20 May-19 June, males were available for detection 39.1% (SD = 27.3) of the time for 5-min point counts and 43.9% (SD = 28.9) of the time for 10-min point counts (n = 54). We detected no temporal changes in availability for Grasshopper Sparrows, but estimated availability to be much lower for 5-min point counts (10.3%, SD = 12.2) than for 10-min point counts (19.2%, SD = 22.3) when males had to be visible and sing during the sampling period (n = 80). For distance sampling, we estimated the availability of Henslow's Sparrows to be 44.2% (SD = 29.0) and the availability of Grasshopper Sparrows to be 20.6% (SD = 23.5). We show how our estimates of availability can be incorporated in the abundance and variance estimators for distance sampling and modify the abundance and variance estimators for the double-observer method. Methods that directly estimate availability from bird counts but also incorporate detection probabilities need further development and will be important for obtaining unbiased estimates of abundance for these species. ?? The American Ornithologists' Union, 2007.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. Estimating the number of species in a stochastic abundance model.

    PubMed

    Chao, Anne; Bunge, John

    2002-09-01

    Consider a stochastic abundance model in which the species arrive in the sample according to independent Poisson processes, where the abundance parameters of the processes follow a gamma distribution. We propose a new estimator of the number of species for this model. The estimator takes the form of the number of duplicated species (i.e., species represented by two or more individuals) divided by an estimated duplication fraction. The duplication fraction is estimated from all frequencies including singleton information. The new estimator is closely related to the sample coverage estimator presented by Chao and Lee (1992, Journal of the American Statistical Association 87, 210-217). We illustrate the procedure using the Malayan butterfly data discussed by Fisher, Corbet, and Williams (1943, Journal of Animal Ecology 12, 42-58) and a 1989 Christmas Bird Count dataset collected in Florida, U.S.A. Simulation studies show that this estimator compares well with maximum likelihood estimators (i.e., empirical Bayes estimators from the Bayesian viewpoint) for which an iterative numerical procedure is needed and may be infeasible.

  13. The effects of acoustic misclassification on cetacean species abundance estimation.

    PubMed

    Caillat, Marjolaine; Thomas, Len; Gillespie, Douglas

    2013-09-01

    To estimate the density or abundance of a cetacean species using acoustic detection data, it is necessary to correctly identify the species that are detected. Developing an automated species classifier with 100% correct classification rate for any species is likely to stay out of reach. It is therefore necessary to consider the effect of misidentified detections on the number of observed data and consequently on abundance or density estimation, and develop methods to cope with these misidentifications. If misclassification rates are known, it is possible to estimate the true numbers of detected calls without bias. However, misclassification and uncertainties in the level of misclassification increase the variance of the estimates. If the true numbers of calls from different species are similar, then a small amount of misclassification between species and a small amount of uncertainty around the classification probabilities does not have an overly detrimental effect on the overall variance. However, if there is a difference in the encounter rate between species calls and/or a large amount of uncertainty in misclassification rates, then the variance of the estimates becomes very large and this dramatically increases the variance of the final abundance estimate.

  14. 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

  15. 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

  16. New aerial survey and hierarchical model to estimate manatee abundance

    USGS Publications Warehouse

    Langimm, Cahterine A.; Dorazio, Robert M.; Stith, Bradley M.; Doyle, Terry J.

    2011-01-01

    Monitoring the response of endangered and protected species to hydrological restoration is a major component of the adaptive management framework of the Comprehensive Everglades Restoration Plan. The endangered Florida manatee (Trichechus manatus latirostris) lives at the marine-freshwater interface in southwest Florida and is likely to be affected by hydrologic restoration. To provide managers with prerestoration information on distribution and abundance for postrestoration comparison, we developed and implemented a new aerial survey design and hierarchical statistical model to estimate and map abundance of manatees as a function of patch-specific habitat characteristics, indicative of manatee requirements for offshore forage (seagrass), inland fresh drinking water, and warm-water winter refuge. We estimated the number of groups of manatees from dual-observer counts and estimated the number of individuals within groups by removal sampling. Our model is unique in that we jointly analyzed group and individual counts using assumptions that allow probabilities of group detection to depend on group size. Ours is the first analysis of manatee aerial surveys to model spatial and temporal abundance of manatees in association with habitat type while accounting for imperfect detection. We conducted the study in the Ten Thousand Islands area of southwestern Florida, USA, which was expected to be affected by the Picayune Strand Restoration Project to restore hydrology altered for a failed real-estate development. We conducted 11 surveys in 2006, spanning the cold, dry season and warm, wet season. To examine short-term and seasonal changes in distribution we flew paired surveys 1–2 days apart within a given month during the year. Manatees were sparsely distributed across the landscape in small groups. Probability of detection of a group increased with group size; the magnitude of the relationship between group size and detection probability varied among surveys. Probability

  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. [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

  19. 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.

  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. [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.

  2. [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

  3. 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.

  4. 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.

  5. Estimates of brown bear abundance on Kodiak Island, Alaska

    USGS Publications Warehouse

    Barnes, V.G.; Smith, R.B.

    1998-01-01

    During 1987-94 we used capture-mark-resight (CMR) methodology and rates of observation (bears/hour and bears/100 km2) of unmarked brown bears (Ursus arctos middendorffi) during intensive aerial surveys (IAS) to estimate abundance of brown bears on Kodiak Island and to establish a baseline for monitoring population trends. CMR estimates were obtained on 3 study areas; density ranged from 216-234 bears/1,000 km2 for independent animals and 292-342 bears/1,000 km2 including dependent offspring. Rates of observation during IAS ranged from 1.4-5.4 independent bears/hour and 2.9-18.0 independent bears/100 km2. Density estimates for independent bears on each IAS area were obtained by dividing mean number of bears observed during replicate surveys by estimated sightability (based on CMR-derived sightability in areas with similar habitat. Brown bear abundance on 21 geographic units of Kodiak Island and 3 nearby islands was estimated by extrapolation from CMR and IAS data using comparisons of habitat characteristics and sport harvest information. Population estimates for independent and total bears were 1,800 and 2,600. The CMR and IAS procedures offer alternative means, depending on management objective and available resources, of measuring population trend of brown bears on Kodiak Island.

  6. 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.

  7. 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.

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

    SciTech Connect

    none,

    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.

  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. 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.

  11. 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.

  12. 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.

  13. [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

  14. 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.

  15. 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.

  16. Estimating Culicoides sonorensis biting midge abundance using digital image analysis.

    PubMed

    Osborne, C J; Mayo, C E; Mullens, B A; Maclachlan, N J

    2014-12-01

    ImageJ is an open-source software tool used for a variety of scientific objectives including cell counting, shape analysis and image correction. This technology has previously been used to estimate mosquito abundance in surveillance efforts. However, the utility of this application for estimating abundance or parity in the surveillance of Culicoides spp. (Diptera: Ceratopogonidae) has not yet been tested. Culicoides sonorensis (Wirth and Jones), a biting midge often measuring 2.0-2.5 mm in length, is an economically important vector of ruminant arboviruses in California. Current surveillance methods use visual sorting for the characteristics of midges and are very time-intensive for large studies. This project tested the utility of ImageJ as a tool to assist in gross trap enumeration as well as in parity analysis of C. sonorensis in comparison with traditional visual methods of enumeration using a dissecting microscope. Results confirmed that automated counting of midges is a reliable means of approximating midge numbers under certain conditions. Further evaluation confirmed accurate and time-efficient parity analysis in comparison with hand sorting. The ImageJ software shows promise as a tool that can assist and expedite C. sonorensis surveillance. Further, these methods may be useful in other insect surveillance activities.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  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. 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

  5. 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

  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. 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.

  7. New estimates of nitrous oxide emissions from biomass burning

    NASA Technical Reports Server (NTRS)

    Cofer, W. R., III; Levine, J. S.; Winstead, E. L.; Stocks, B. J.

    1991-01-01

    The recent discovery of an artifact producing increased levels of N2O in combustion gas samples collected and stored in grab bottles before chemical analysis has resulted in the downgrading of fossil-fuel combustion and the questioning of biomass burning as important sources of N2O. As almost all reported analyses of N2O produced from biomass burning have involved essentially the same collection and analysis protocols as used in the fossil-fuel studies, this source of N2O must also be reexamined. Here, measurements of N2O made over a large prescribed fire using a near real-time in situ measurement technique are reported and compared with measurements of N2O from simultaneously collected grab-bottle samples. The results from 27 small laboratory biomass test fires are also used to help clarify the validity of earlier assessments. It is concluded that biomass burning contributes about seven percent of atmospheric N2O, as opposed to earlier estimates of several times this value.

  8. 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.

  9. 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.

  10. 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.

  11. Helium abundances on the moon: Assumptions and estimates

    NASA Astrophysics Data System (ADS)

    Taylor, Lawrence A.

    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 Is/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 HeT), versus 3 to 9 ppm in the Highlands. However, the relationships between Is/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.

  12. Soil Nutrient Content Influences the Abundance of Soil Microbes but Not Plant Biomass at the Small-Scale

    PubMed Central

    Koorem, Kadri; Gazol, Antonio; Öpik, Maarja; Moora, Mari; Saks, Ülle; Uibopuu, Annika; Sõber, Virve; Zobel, Martin

    2014-01-01

    Small-scale heterogeneity of abiotic and biotic factors is expected to play a crucial role in species coexistence. It is known that plants are able to concentrate their root biomass into areas with high nutrient content and also acquire nutrients via symbiotic microorganisms such as arbuscular mycorrhizal (AM) fungi. At the same time, little is known about the small-scale distribution of soil nutrients, microbes and plant biomass occurring in the same area. We examined small-scale temporal and spatial variation as well as covariation of soil nutrients, microbial biomass (using soil fatty acid biomarker content) and above- and belowground biomass of herbaceous plants in a natural herb-rich boreonemoral spruce forest. The abundance of AM fungi and bacteria decreased during the plant growing season while soil nutrient content rather increased. The abundance of all microbes studied also varied in space and was affected by soil nutrient content. In particular, the abundance of AM fungi was negatively related to soil phosphorus and positively influenced by soil nitrogen content. Neither shoot nor root biomass of herbaceous plants showed any significant relationship with variation in soil nutrient content or the abundance of soil microbes. Our study suggests that plants can compensate for low soil phosphorus concentration via interactions with soil microbes, most probably due to a more efficient symbiosis with AM fungi. This compensation results in relatively constant plant biomass despite variation in soil phosphorous content and in the abundance of AM fungi. Hence, it is crucial to consider both soil nutrient content and the abundance of soil microbes when exploring the mechanisms driving vegetation patterns. PMID:24637633

  13. [Effects of Slope Position and Soil Horizon on Soil Microbial Biomass and Abundance in Karst Primary Forest of Southwest China].

    PubMed

    Feng, Shu-zhen; Su, Yi-rong; Zhang, Wei; Chen, Xiang-bi; He, Xun-yang

    2015-10-01

    To explore the effects of slope position and soil horizon on soil microbial biomass and abundance, chloroform fumigation extraction methods and real-time fluorescence-based quantitative PCR (Real-time PCR) were adopted to quantify the changes of soil microbial biomass C, N and abundance of bacteria and fungi, respectively. Soil samples were harvested from three horizons along profile, i. e., leaching horizon (A, 0-10 cm), transitional horizon (AB, 30-50 cm) and alluvial horizon (B, 70-100 cm), which were collected from the upper, middle and lower slope positions of a karst primary forest ecosystem. The results showed that slope position, soil horizon and their interaction significantly influenced the soil microbial biomass and abundance (P < 0.05). Different from A horizon, where SMBC was greater in lower than in upper slope position (P < 0.05), SMBC in AB and B horizons were highest in middle slope position. Similarly, SMBN was greater in lower than in upper slope position for A, AB and B horizons. Besides soil bacterial abundance in B horizon and fungal abundance in AB layer, the middle slope position had the highest value for all the three soil horizons (P < 0.05). Stepwise regression analysis showed that soil organic carbon, available nitrogen and pH were the key factors responsible for SMBC and SMBN variation, respectively, while the important factors responsible for the variation of bacteria abundance were available nitrogen and available phosphorus, and that for fungi abundance variation were available potassium.

  14. Estimation of methanogen biomass by quantitation of coenzyme M

    SciTech Connect

    Elias, D.A.; Krumholz, L.R.; Tanner, R.S.; Suflita, J.M.

    1999-12-01

    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. The authors standardized a simple method for estimating methanogen biomass in a variety of environmental matrices. In this procedure they used the thiol biomarker coenzyme M (CoM) (2-mercaptoethanesulfonic acid), which is known to be present in tall methanogenic bacteria. A high-performance liquid chromatography-based method for detecting thiols in pore water 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. The authors 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.

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

    USGS Publications Warehouse

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

    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.

  16. Predicting tree heights for biomass estimates in tropical forests

    NASA Astrophysics Data System (ADS)

    Molto, Q.; Hérault, B.; Boreux, J.-J.; Daullet, M.; Rousteau, A.; Rossi, V.

    2013-05-01

    The recent development of REDD+ mechanisms require reliable estimation of carbon stocks, especially in tropical forests that are particularly threatened by global changes. Even if tree height is a crucial variable to compute the above-ground forest biomass, tree heights are rarely measured in large-scale forest census because it requires consequent extra-effort. Tree height have thus to be predicted thanks to height models. Height and diameter of all trees above 10 cm of diameter were measured in thirty-three half-ha plots and nine one-ha plots throughout the northern French Guiana, an area with substantial climate and environmental gradients. We compared four different model shapes and found that the Michaelis-Menten shape was the most appropriate for the tree biomass prediction. Model parameters values were significantly different from one forest plot to another and neglecting these differences would lead to large errors in biomass estimates. Variables from the forest stand structure explained a sufficient part of the plot-to-plot variations of the height model parameters to affect the AGB predictions. In the forest stands dominated by small trees, the trees were found to have rapid height growth for small diameters. In forest stands dominated by larger trees, the trees were found to have the greatest heights for large diameters. The above-ground biomass estimation uncertainty of the forest plots was reduced by the use of the forest structure-based height model. It demonstrates the feasibility and the importance of height modeling in tropical forest for carbon mapping. Tree height is definitely an important variable for AGB estimations. When the tree heights are not measured in an inventory, they can be predicted with a height-diameter model. This model can account for plot-to plot variations in height-diameter relationship thank to variables describing the plots. The variables describing the stand structure of the plots are efficient for this. We found that

  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. 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.

  19. Estimates of bacterial growth from changes in uptake rates and biomass.

    PubMed Central

    Kirchman, D; Ducklow, H; Mitchell, R

    1982-01-01

    Rates of nucleic acid synthesis have been used to examine microbiol growth in natural waters. These rates are calculated from the incorporation of [3H]adenine and [3H]thymidine for RNA and DNA syntheses, respectively. Several additional biochemical parameters must be measured or taken from the literature to estimate growth rates from the incorporation of the tritiated compounds. We propose a simple method of estimating a conversion factor which obviates measuring these biochemical parameters. The change in bacterial abundance and incorporation rates of [3H]thymidine was measured in samples from three environments. The incorporation of exogenous [3H]thymidine was closely coupled with growth and cell division as estimated from the increase in bacterial biomass. Analysis of the changes in incorporation rates and initial bacterial abundance yielded a conversion factor for calculating bacterial production rates from incorporation rates. Furthermore, the growth rate of only those bacteria incorporating the compound can be estimated. The data analysis and experimental design can be used to estimate the proportion of nondividing cells and to examine changes in cell volumes. PMID:6760812

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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

    2016-06-21

    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.

  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. "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…

  7. 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...

  8. 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.

  9. 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.

  10. 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

  11. An easy field method for estimating the abundance of culicid larval instars.

    PubMed

    Carron, Alexandre; Duchet, Claire; Gaven, Bruno; Lagneau, Christophe

    2003-12-01

    A new method is proposed that avoids manual counting of mosquito larvae in order to estimate larval abundance in the field. This method is based on the visual comparison between abundance, in a standardized sampling tray (called an abacus), with 5 (abacus 5) or 10 (abacus 10) diagrammatically prepared abundance classes. Accuracy under laboratory and field conditions and individual bias have been evaluated and both abaci provide a reliable estimation of abundance in both conditions. There is no individual bias, whether people are familiar or not with its use. They could also be used for a quick estimation of larval treatment effectiveness, for the study of population dynamics and spatial distribution.

  12. 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...

  13. 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...

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

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

    USGS Publications Warehouse

    Dodd, C.K.; 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.

  2. [Effects of adding straw carbon source to root knot nematode diseased soil on soil microbial biomass and protozoa abundance].

    PubMed

    Zhang, Si-Hui; Lian, Jian-Hong; Cao, Zhi-Ping; Zhao, Li

    2013-06-01

    A field experiment with successive planting of tomato was conducted to study the effects of adding different amounts of winter wheat straw (2.08 g x kg(-1), 1N; 4.16 g x kg(-1), 2N; and 8.32 g x kg(-1), 4N) to the soil seriously suffered from root knot nematode disease on the soil microbial biomass and protozoa abundance. Adding straw carbon source had significant effects on the contents of soil microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) and the abundance of soil protozoa, which all decreased in the order of 4N > 2N > 1N > CK. The community structure of soil protozoa also changed significantly under straw addition. In the treatments with straw addition, the average proportion of fagellate, amoeba, and ciliates accounted for 36.0%, 59.5%, and 4.5% of the total protozoa, respectively. Under the same adding amounts of wheat straw, there was an increase in the soil MBC and MBN contents, MBC/MBN ratio, and protozoa abundance with increasing cultivation period. PMID:24066551

  3. [Effects of adding straw carbon source to root knot nematode diseased soil on soil microbial biomass and protozoa abundance].

    PubMed

    Zhang, Si-Hui; Lian, Jian-Hong; Cao, Zhi-Ping; Zhao, Li

    2013-06-01

    A field experiment with successive planting of tomato was conducted to study the effects of adding different amounts of winter wheat straw (2.08 g x kg(-1), 1N; 4.16 g x kg(-1), 2N; and 8.32 g x kg(-1), 4N) to the soil seriously suffered from root knot nematode disease on the soil microbial biomass and protozoa abundance. Adding straw carbon source had significant effects on the contents of soil microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) and the abundance of soil protozoa, which all decreased in the order of 4N > 2N > 1N > CK. The community structure of soil protozoa also changed significantly under straw addition. In the treatments with straw addition, the average proportion of fagellate, amoeba, and ciliates accounted for 36.0%, 59.5%, and 4.5% of the total protozoa, respectively. Under the same adding amounts of wheat straw, there was an increase in the soil MBC and MBN contents, MBC/MBN ratio, and protozoa abundance with increasing cultivation period.

  4. 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.

  5. Microalgae on the arctic ocean section, 1994: species abundance and biomass

    NASA Astrophysics Data System (ADS)

    Booth, Beatrice C.; Horner, Rita A.

    Algal species from the ice, the water directly below the ice (the sub-ice area), and the water column from 21 stations in the Arctic Ocean were examined using epifluorescence and inverted light microscopy. Biomass of autotrophic dinoflagellates and other miscellaneous autotrophic flagellates was determined for the first time in the central Arctic basins. Together these two groups dominated phytoplankton biomass in 74% of samples from the central Arctic, with diatom biomass predominant in the remainder. Picophytoplankton at selected stations in the Canada and Makarov Basins contributed 93% to autotroph cell numbers and 36% to autotroph biomass. Diatom species achieved high biomass in ice and sub-ice samples. The centric diatom Melosira arctica dominated the sub-ice area, while pennate diatoms were major contributors to the ice samples. Despite ample silicate concentrations in the water, diatom frustules were often lightly silicified.

  6. 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...

  7. 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.

  8. 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.

  9. Estimating Lion Abundance using N-mixture Models for Social Species

    PubMed Central

    Belant, Jerrold L.; Bled, Florent; Wilton, Clay M.; Fyumagwa, Robert; Mwampeta, Stanslaus B.; Beyer, Dean E.

    2016-01-01

    Declining populations of large carnivores worldwide, and the complexities of managing human-carnivore conflicts, require accurate population estimates of large carnivores to promote their long-term persistence through well-informed management We used N-mixture models to estimate lion (Panthera leo) abundance from call-in and track surveys in southeastern Serengeti National Park, Tanzania. Because of potential habituation to broadcasted calls and social behavior, we developed a hierarchical observation process within the N-mixture model conditioning lion detectability on their group response to call-ins and individual detection probabilities. We estimated 270 lions (95% credible interval = 170–551) using call-ins but were unable to estimate lion abundance from track data. We found a weak negative relationship between predicted track density and predicted lion abundance from the call-in surveys. Luminosity was negatively correlated with individual detection probability during call-in surveys. Lion abundance and track density were influenced by landcover, but direction of the corresponding effects were undetermined. N-mixture models allowed us to incorporate multiple parameters (e.g., landcover, luminosity, observer effect) influencing lion abundance and probability of detection directly into abundance estimates. We suggest that N-mixture models employing a hierarchical observation process can be used to estimate abundance of other social, herding, and grouping species. PMID:27786283

  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.

  12. 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

  13. From grass to forest biomass: uncertainty estimates with lidar remote sensing (Invited)

    NASA Astrophysics Data System (ADS)

    Popescu, S. C.; Zhao, K.; Feagin, R. A.; Gatziolis, D.; Sheridan, R.; Srinivasan, S.; Ku, N.; Kulawardhana, R. W.

    2013-12-01

    Lidar remote sensing from three platforms - ground, airborne, and spaceborne - has the capability to acquire direct three-dimensional measurements of the vegetation canopy that are useful for estimating biophysical characteristics, including biomass. Each platform provides data over different spatial scales and enables biomass and carbon estimates with different levels of uncertainty. The overall goal of this presentation is to discuss error sources involved in biomass estimation with lidar remote sensing, with terrestrial, airborne, and satellite sensors, with examples of studies of coastal vegetation grasses, brush, and forests. Specific objectives will focus on the accuracy of estimating vegetation dimensions, such as height and crown widths, allometrics used to derive biomass, regression models for biomass estimation, and comparison between methods and sensors. In our studies, ICESat height variables were able to explain 80% of the variance associated with the reference forest biomass derived from airborne lidar, with an RMSE of 37.7 Mg/ha. For salt marshes, the combination of airborne lidar and multispectral variables explained 47% of the biomass variance, whereas the best models using lidar and multi-spectral data separately explained 37% and 28% of variances in live biomass measurements respectively. Terrestrial lidar was able to explain up to 81% of the variance associated with the aboveground biomass of rangeland woody plants in a semi-arid environment in Texas. With airborne lidar and a scale-invariant approach, previous work suggests that regression models can accurately predict biomass and yield consistent predictive performances across a variety of scales ranging from 80% to 95% biomass variance explained, with RMSE values from 14. 3 Mg/ha to 33.7 Mg/ha among regression models. The results of these studies demonstrate the ability of using lidar remote sensing on multiple platforms for assessing aboveground biomass and the uncertainty of estimates and

  14. 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.

  15. 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.

  16. Remote sensing of submerged vegetation canopies for biomass estimation

    NASA Technical Reports Server (NTRS)

    Armstrong, Roy A.

    1993-01-01

    The visible bands of the Landsat Thematic Mapper (TM) sensor were used in an empirical assessment of seagrass biomass on shallow banks near Lee Stocking Island in the Bahamas. The TM bands were transformed to minimize the depth-dependent variance in the bottom reflectance signal. Regression analyses were performed between the transformed bands and field measurements of seagrass standing crop (above-ground biomass). Regression equations using spectral data accounted for up to 80 per cent of the variability in seagrass biomass. The unexplained variance was ascribed to variations in bottom sediment color.

  17. 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

  18. 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

  19. 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.

  20. Tropical Forest Biomass Estimation from Vertical Fourier Transforms of Lidar and InSAR Profiles

    NASA Astrophysics Data System (ADS)

    Treuhaft, R. N.; Goncalves, F.; Drake, J.; Hensley, S.; Chapman, B. D.; Michel, T.; Dos Santos, J. R.; Dutra, L.; Graca, P. A.

    2010-12-01

    Structural forest biomass estimation from lidar or interferometric SAR (InSAR) has demonstrated better performance than radar-power-based approaches for the higher biomasses (>150 Mg/ha) found in tropical forests. Structural biomass estimation frequently regresses field biomass to some function of forest height. With airborne, 25-m footprint lidar data and fixed-baseline C-band InSAR data over tropical wet forests of La Selva Biological Station, Costa Rica, we compare the use of Fourier transforms of vertical profiles at a few frequencies to the intrinsically low-frequency “average height”. RMS scatters of Fourier-estimated biomass about field-measured biomass improved by 40% and 20% over estimates base on average height from lidar and fixed-baseline InSAR, respectively. Vertical wavelengths between 14 and 100 m were found to best estimate biomass. The same airborne data acquisition over La Selva was used to generate many 10’s of repeat-track L-band InSAR baselines with time delays of 1-72 hours, and vertical wavelengths of 5-100 m. We will estimate biomass from the Fourier transforms of L-band radar power profiles (InSAR complex coherence). The effects of temporal decorrelation will be modeled in the Fourier domain to try to model and reduce their impact. Using L-band polarimetric interferometry, average heights will be estimated as well and biomass regression performance compared to the Fourier transform approach. The more traditional approach of using L-band radar polarimetry will also be compared to structural biomass estimation.

  1. 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

  2. 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.; 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.

  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. 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.

  5. Estimating sturgeon abundance in the Carolinas using side-scan sonar

    USGS Publications Warehouse

    Flowers, H. Jared; Hightower, Joseph E.

    2015-01-01

    Sturgeons (Acipenseridae) are one of the most threatened taxa worldwide, including species in North Carolina and South Carolina. Populations of Atlantic Sturgeon Acipenser oxyrinchus in the Carolinas have been significantly reduced from historical levels by a combination of intense fishing and habitat loss. There is a need for estimates of current abundance, to describe status, and for estimates of historical abundance in order to provide realistic recovery goals. In this study we used N-mixture and distance models with data acquired from side-scan sonar surveys to estimate abundance of sturgeon in six major sturgeon rivers in North Carolina and South Carolina. Estimated abundances of sturgeon greater than 1 m TL in the Carolina distinct population segment (DPS) were 2,031 using the count model and 1,912 via the distance model. The Pee Dee River had the highest overall abundance of any river at 1,944 (count model) or 1,823 (distance model). These estimates do not account for sturgeon less than 1 m TL or occurring in riverine reaches not surveyed or in marine waters. Comparing the two models, the N-mixture model produced similar estimates using less data than the distance model with only a slight reduction of estimated precision.

  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.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

    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. On-line biomass estimation in biosurfactant production process by Candida lipolytica UCP 988.

    PubMed

    da Costa Albuquerque, Clarissa Daisy; de Campos-Takaki, Galba Maria; Fileti, Ana Maria Frattini

    2008-11-01

    Biomass is an important variable in biosurfactant production process. However, such bioprocess variable, usually, is collected by sampling and determined by off-line analysis, with significant time delay. Therefore, simple and reliable on-line biomass estimation procedures are highly desirable. An artificial neural network model (ANN) is presented for the on-line estimation of biomass concentration, in biosurfactant production by Candida lipolytica UCP 988, as a nonlinear function of pH and dissolved oxygen. Several configurations were evaluated while developing the optimal ANN model. The optimal ANN model consists of one hidden layer with four neurons. The performance of the ANN was checked using experimental data. The results obtained indicate a very good predictive capacity for the ANN-based software sensor with values of R2 of 0.969 and RMSE of 0.021 for biomass concentration. Estimated biomass using the ANN was proved to be a simple, robust and accurate method.

  8. Using mark-recapture methods to estimate fish abundance in small mountain lakes

    USGS Publications Warehouse

    Gresswell, Robert E.; Liss, W.J.; Lomnicky, G.A.; Deimling, E.; Hoffman, Robert L.; Tyler, T.

    1997-01-01

    The majority of lacustrine fish populations in the western USA are located far from the nearest road. Although mark-recapture techniques are widely accepted for estimating population abundance, these techniques have been broadly ignored for fisheries surveys in remote mountain lakes because of restricted access and associated logistical constraints. In this study, mark recapture experiments were used to estimate fish population abundance in nine small (< 7 ha) lakes of the North Cascades National Park Service Complex. Fish in the mark sample were collected by angling, fin-clipped, and immediately released; fish were recaptured with variable mesh monofilament gill nets. A single-census Petersen estimator was used to calculate abundance in each lake, and assumptions for unbiased estimates appeared to be satisfied in most cases. Post-release mortality of angler-captured fish was low. The small size of these lakes in conjunction with the brief period of rime allotted for each individual experiment apparently reduced the probability of unequal vulnerability and mortality for marked and unmarked fish. Single-census mark-recapture experiments appeared to provide reasonable estimates of population abundance in these mountain lakes. Resulting estimates furnish a substantial increase in information when compared to more ubiquitous assessments of relative abundance, but the logistical requirements are modest. We believe that this technique may useful for survey purposes in other small, remote lakes.

  9. 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...

  10. 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...

  11. A comparison of abundance estimates from extended batch-marking and Jolly–Seber-type experiments

    PubMed Central

    Cowen, Laura L E; Besbeas, Panagiotis; Morgan, Byron J T; Schwarz, Carl J

    2014-01-01

    Little attention has been paid to the use of multi-sample batch-marking studies, as it is generally assumed that an individual's capture history is necessary for fully efficient estimates. However, recently, Huggins et al. (2010) present a pseudo-likelihood for a multi-sample batch-marking study where they used estimating equations to solve for survival and capture probabilities and then derived abundance estimates using a Horvitz–Thompson-type estimator. We have developed and maximized the likelihood for batch-marking studies. We use data simulated from a Jolly–Seber-type study and convert this to what would have been obtained from an extended batch-marking study. We compare our abundance estimates obtained from the Crosbie–Manly–Arnason–Schwarz (CMAS) model with those of the extended batch-marking model to determine the efficiency of collecting and analyzing batch-marking data. We found that estimates of abundance were similar for all three estimators: CMAS, Huggins, and our likelihood. Gains are made when using unique identifiers and employing the CMAS model in terms of precision; however, the likelihood typically had lower mean square error than the pseudo-likelihood method of Huggins et al. (2010). When faced with designing a batch-marking study, researchers can be confident in obtaining unbiased abundance estimators. Furthermore, they can design studies in order to reduce mean square error by manipulating capture probabilities and sample size. PMID:24558576

  12. A comparison of abundance estimates from extended batch-marking and Jolly-Seber-type experiments.

    PubMed

    Cowen, Laura L E; Besbeas, Panagiotis; Morgan, Byron J T; Schwarz, Carl J

    2014-01-01

    Little attention has been paid to the use of multi-sample batch-marking studies, as it is generally assumed that an individual's capture history is necessary for fully efficient estimates. However, recently, Huggins et al. (2010) present a pseudo-likelihood for a multi-sample batch-marking study where they used estimating equations to solve for survival and capture probabilities and then derived abundance estimates using a Horvitz-Thompson-type estimator. We have developed and maximized the likelihood for batch-marking studies. We use data simulated from a Jolly-Seber-type study and convert this to what would have been obtained from an extended batch-marking study. We compare our abundance estimates obtained from the Crosbie-Manly-Arnason-Schwarz (CMAS) model with those of the extended batch-marking model to determine the efficiency of collecting and analyzing batch-marking data. We found that estimates of abundance were similar for all three estimators: CMAS, Huggins, and our likelihood. Gains are made when using unique identifiers and employing the CMAS model in terms of precision; however, the likelihood typically had lower mean square error than the pseudo-likelihood method of Huggins et al. (2010). When faced with designing a batch-marking study, researchers can be confident in obtaining unbiased abundance estimators. Furthermore, they can design studies in order to reduce mean square error by manipulating capture probabilities and sample size.

  13. Structural Biomass Estimation from L-band Interferometric SAR and Lidar

    NASA Astrophysics Data System (ADS)

    Treuhaft, R. N.; Chapman, B. D.; Goncalves, F.; Hensley, S.; dos Santos, J. R.; Graca, P. A.; Dutra, L.

    2011-12-01

    After a review of biomass estimation from interferometric SAR (InSAR) at all bands over the last 15 years, and a brief review of lidar biomass estimation, this paper discusses structure and biomass estimation from simultaneously acquired (not repeat-track) InSAR at L-band. We will briefly discuss the history of regression of biomass to InSAR raw observations (coherence and phase) and structural parameters (height, standard deviation, Fourier component). Lidar biomass estimation from functions of the waveform will be discussed. We review our structural and biomass estimation results for C-band InSAR at vertical polarization for 12-14 baselines in La Selva Biological Station, Costa Rica. C-band vertical scales were between 12 and 100 m for structure estimation, but only between 50 and 100 m for biomass estimation, due to phase calibration problems at the shorter vertical wavelengths (larger baselines). Most of the talk will be spent on L-band, simultaneously acquired multibaseline InSAR, also at La Selva, acquired at vertical polarization. Because the vertical interferometric scale is proportional to the radar altitude times the wavelength over the baseline length, the AirSAR aircraft had to be flown very low (1.2 km) to realize vertical scales at L-band of 60 m and higher. Our lidar biomass estimation suggests that vertical scales of 14 m-100 m are optimal for biomass estimation. We will try three different approaches to biomass estimation with the limited high vertical scales we have available: 1) We will regress biomass to Fourier transforms as in the C-band and lidar study, but with 60 m - 100+ m vertical scales we do not expect accuracies to be as high as for the lidar demonstration (58 Mg/ha RMS scatter of estimated about field biomass for biomasses up to 450 Mg/ha), which used Fourier vertical wavelengths of 15 m-20 m. In addition to using Fourier components, 2) we will report the use of the derivative of the InSAR complex coherence with respect to Fourier

  14. 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

  15. 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.

  16. 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.

  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.

  18. Incorrect representation of uncertainty in the modeling of growth leads to biased estimates of future biomass.

    PubMed

    Valle, Denis

    2011-06-01

    Biomass is a fundamental measure in the natural sciences, and numerous models have been developed to forecast timber and fishery yields, forest carbon content, and other environmental services that depend on biomass estimates. We derive general results that reveal how dynamic models that simulate growth as an increase in a linear measure of size (e.g., diameter, length, height) result in biased estimates of future mean biomass when uncertainty in growth is misrepresented. Our case study shows how models of tree growth that predict the same mean diameter increment, but with alternative representations of growth uncertainty, result in almost a threefold difference in the projections of future mean tree biomass after a 20-yr simulation. These results have important implications concerning our ability to accurately predict future biomass and all the related environmental services (e.g., forest carbon content, timber and fishery yields). If the objective is to predict future biomass, we strongly recommend that: (1) ecological modelers should choose a growth model based on a variable more linearly related to biomass (e.g., tree basal area instead of tree diameter for forest models); (2) if field measurements preclude the use of variables other than the linear measure of size, both the mean and other statistical moments (e.g., covariances) should be carefully modeled; (3) careful assessment be done on models that aggregate similar individuals (i.e., cohort models) to see if neglecting autocorrelated growth from individuals leads to biased estimates of future mean biomass.

  19. 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

  20. 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

  1. 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...

  2. 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.

  3. 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.

  4. [Estimation models of understory shrub biomass and their applications in red soil hilly region].

    PubMed

    Zeng, Hui-Qing; Liu, Qi-Jing; Feng, Zong-Wei; Ma, Ze-Qing; Hu, Li-Le

    2007-10-01

    With 16 familiar species of understory shrub at Qianyezhou ecological experimental station in red soil hilly region under Chinese Academy of Sciences as test objects, crown area (A(c)) and projected volume (V(c)) were used as the variables for building quadratic and power allometric equations, respectively, to estimate the biomass of individual populations, and mixed-model was used to estimate the biomass of the 16 species. The best-fit models were applied to estimate the biomass of understory shrub in different forest types. The results showed that the biomass of shrub layer varied significantly among different stand types. With species-specific models, the biomass in deciduous, secondary, and coniferous forests was estimated as 4 773, 3 175 and 733 kg x hm(-2), respectively; while with mixed model, the estimation result was a little lower, being 3 946, 2 772 and 840 kg x hm(-2), respectively. Under the conditions of species-specific models being not established, mixed model was more convenient and practical in estimating the biomass of understory shrub.

  5. Reliability of biomass burning estimates from savanna fires: Biomass burning in northern Australia during the 1999 Biomass Burning and Lightning Experiment B field campaign

    NASA Astrophysics Data System (ADS)

    Russell-Smith, Jeremy; Edwards, Andrew C.; Cook, Garry D.

    2003-02-01

    This paper estimates the two-daily extent of savanna burning and consumption of fine (grass and litter) fuels from an extensive 230,000 km2 region of northern Australia during August-September 1999 encompassing the Australian continental component of the Biomass Burning and Lightning Experiment B (BIBLE B) campaign [, 2002]. The extent of burning for the study region was derived from fire scar mapping of imagery from the advanced very high resolution radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) satellite. The mapping was calibrated and verified with reference to one Landsat scene and associated aerial transect validation data. Fine fuel loads were estimated using published fuel accumulation relationships for major regional fuel types. It is estimated that more than 43,000 km2 was burnt during the 25 day study period, with about 19 Mt of fine (grass and litter) fuels. This paper examines assumptions and errors associated with these estimates. It is estimated from uncalibrated fire mapping derived from AVHRR imagery that 417,500 km2 of the northern Australian savanna was burnt in 1999, of which 136,405 km2, or 30%, occurred in the Northern Territory study region. Using generalized fuel accumulation equations, such biomass burning consumed an estimated 212.3 Mt of fine fuels, but no data are available for consumption of coarse fuels. This figure exceeds a recent estimate, based on fine fuels only, for the combined Australian savanna and temperate grassland biomass burning over the period 1990-1999 but is lower than past estimates derived from classification approaches. We conclude that (1) fire maps derived from coarse-resolution optical imagery can be applied relatively reliably to estimate the extent of savanna fires, generally with 70-80% confidence using the approach adopted here, over the major burning period in northern Australia and (2) substantial further field assessment and associated modeling of fuel accumulation

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. [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.

  13. Abundance and biomass responses of microbial food web components to hydrology and environmental gradients within a floodplain of the River Danube.

    PubMed

    Palijan, Goran

    2012-07-01

    This study investigated the relationships of time-dependent hydrological variability and selected microbial food web components. Samples were collected monthly from the Kopački Rit floodplain in Croatia, over a period of 19 months, for analysis of bacterioplankton abundance, cell size and biomass; abundance of heterotrophic nanoflagellates and nanophytoplankton; and concentration of chlorophyll a. Similar hydrological variability at different times of the year enabled partition of seasonal effects from hydrological changes on microbial community properties. The results suggested that, unlike some other studies investigating sites with different connectivity, bacterioplankton abundance, and phytoplankton abundance and biomass increased during lentic conditions. At increasing water level, nanophytoplankton showed lower sensitivity to disturbance in comparison with total phytoplankton biomass: this could prolong autotrophic conditions within the floodplain. Bacterioplankton biomass, unlike phytoplankton, was not impacted by hydrology. The bacterial biomass less affected by hydrological changes can be an important additional food component for the floodplain food web. The results also suggested a mechanism controlling bacterial cell size independent of hydrology, as bacterial cell size was significantly decreased as nanoflagellate abundance increased. Hydrology, regardless of seasonal sucession, has the potential to structure microbial food webs, supporting microbial development during lentic conditions. Conversely, other components appear unaffected by hydrology or may be more strongly controlled by biotic interactions. This research, therefore, adds to understanding on microbial food web interactions in the context of flood and flow pulses in river-floodplain ecosystems.

  14. 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.

  15. 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.

  16. 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.

  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. The importance of crown dimensions to improve tropical tree biomass estimates.

    PubMed

    Goodman, Rosa C; Phillips, Oliver L; Baker, Timothy R

    2014-06-01

    Tropical forests play a vital role in the global carbon cycle, but the amount of carbon they contain and its spatial distribution remain uncertain. Recent studies suggest that once tree height is accounted for in biomass calculations, in addition to diameter and wood density, carbon stock estimates are reduced in many areas. However, it is possible that larger crown sizes might offset the reduction in biomass estimates in some forests where tree heights are lower because even comparatively short trees develop large, well-lit crowns in or above the forest canopy. While current allometric models and theory focus on diameter, wood density, and height, the influence of crown size and structure has not been well studied. To test the extent to which accounting for crown parameters can improve biomass estimates, we harvested and weighed 51 trees (11-169 cm diameter) in southwestern Amazonia where no direct biomass measurements have been made. The trees in our study had nearly half of total aboveground biomass in the branches (44% +/- 2% [mean +/- SE]), demonstrating the importance of accounting for tree crowns. Consistent with our predictions, key pantropical equations that include height, but do not account for crown dimensions, underestimated the sum total biomass of all 51 trees by 11% to 14%, primarily due to substantial underestimates of many of the largest trees. In our models, including crown radius greatly improves performance and reduces error, especially for the largest trees. In addition, over the full data set, crown radius explained more variation in aboveground biomass (10.5%) than height (6.0%). Crown form is also important: Trees with a monopodial architectural type are estimated to have 21-44% less mass than trees with other growth patterns. Our analysis suggests that accounting for crown allometry would substantially improve the accuracy of tropical estimates of tree biomass and its distribution in primary and degraded forests.

  19. 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.

  20. 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

  1. 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

  2. Optimal sampling design for estimating spatial distribution and abundance of a freshwater mussel population

    USGS Publications Warehouse

    Pooler, P.S.; Smith, D.R.

    2005-01-01

    We compared the ability of simple random sampling (SRS) and a variety of systematic sampling (SYS) designs to estimate abundance, quantify spatial clustering, and predict spatial distribution of freshwater mussels. Sampling simulations were conducted using data obtained from a census of freshwater mussels in a 40 X 33 m section of the Cacapon River near Capon Bridge, West Virginia, and from a simulated spatially random population generated to have the same abundance as the real population. Sampling units that were 0.25 m 2 gave more accurate and precise abundance estimates and generally better spatial predictions than 1-m2 sampling units. Systematic sampling with ???2 random starts was more efficient than SRS. Estimates of abundance based on SYS were more accurate when the distance between sampling units across the stream was less than or equal to the distance between sampling units along the stream. Three measures for quantifying spatial clustering were examined: Hopkins Statistic, the Clumping Index, and Morisita's Index. Morisita's Index was the most reliable, and the Hopkins Statistic was prone to false rejection of complete spatial randomness. SYS designs with units spaced equally across and up stream provided the most accurate predictions when estimating the spatial distribution by kriging. Our research indicates that SYS designs with sampling units equally spaced both across and along the stream would be appropriate for sampling freshwater mussels even if no information about the true underlying spatial distribution of the population were available to guide the design choice. ?? 2005 by The North American Benthological Society.

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. [Band depth analysis and partial least square regression based winter wheat biomass estimation using hyperspectral measurements].

    PubMed

    Fu, Yuan-Yuan; Wang, Ji-Hua; Yang, Gui-Jun; Song, Xiao-Yu; Xu, Xin-Gang; Feng, Hai-Kuan

    2013-05-01

    The major limitation of using existing vegetation indices for crop biomass estimation is that it approaches a saturation level asymptotically for a certain range of biomass. In order to resolve this problem, band depth analysis and partial least square regression (PLSR) were combined to establish winter wheat biomass estimation model in the present study. The models based on the combination of band depth analysis and PLSR were compared with the models based on common vegetation indexes from the point of view of estimation accuracy, subsequently. Band depth analysis was conducted in the visible spectral domain (550-750 nm). Band depth, band depth ratio (BDR), normalized band depth index, and band depth normalized to area were utilized to represent band depth information. Among the calibrated estimation models, the models based on the combination of band depth analysis and PLSR reached higher accuracy than those based on the vegetation indices. Among them, the combination of BDR and PLSR got the highest accuracy (R2 = 0.792, RMSE = 0.164 kg x m(-2)). The results indicated that the combination of band depth analysis and PLSR could well overcome the saturation problem and improve the biomass estimation accuracy when winter wheat biomass is large.

  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. 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

  11. 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

  12. Evaluation of an aerial survey to estimate abundance of wintering ducks in Mississippi

    USGS Publications Warehouse

    Pearse, A.T.; Dinsmore, S.J.; Kaminski, R.M.; Reinecke, K.J.

    2008-01-01

    Researchers have successfully designed aerial surveys that provided precise estimates of wintering populations of ducks over large physiographic regions, yet few conservation agencies have adopted these probability-based sampling designs for their surveys. We designed and evaluated an aerial survey to estimate abundance of wintering mallards {Anas platyrhynchos), dabbling ducks (tribe Anatini) other than mallards, diving ducks (tribes Aythini, Mergini, and Oxyurini), and total ducks in western Mississippi, USA. We used design-based sampling of fixed width transects to estimate population indices (I?), and we used model-based methods to correct population indices for visibility bias and estimate population abundance (N?) for 14 surveys during winters 2002-2004. Correcting for bias increased estimates of mallards, other dabbling ducks, and diving ducks by an average of 40-48% among all surveys and contributed 48-61% of the estimated variance of N?. However, mean-squared errors were consistently less for N? than I?. Estimates of N? met our goals for precision (CV < 15%) in 7 of 14 surveys for mallards, 5 surveys for other dabbling ducks, no surveys for diving ducks, and 10 surveys for total ducks. Generally, we estimated more mallards and other dabbling ducks in mid- and late winter (Jan-Feb) than early winter (Nov-Dec) and determined that population indices from the late 1980s were nearly 3 times greater than those from our study. We developed a method to display relative densities of ducks spatially as an additional application of survey data. Our study advanced methods of estimating abundance of wintering waterfowl, and we recommend this design for continued monitoring of wintering ducks in western Mississippi and similar physiographic regions.

  13. Evaluation of an aerial survey to estimate abundance of wintering ducks in Mississippi

    USGS Publications Warehouse

    Pearse, A.T.; Dinsmore, S.J.; Kaminski, R.M.; Reinecke, K.J.

    2008-01-01

    Researchers have successfully designed aerial surveys that provided precise estimates of wintering populations of ducks over large physiographic regions, yet few conservation agencies have adopted these probability-based sampling designs for their surveys. We designed and evaluated an aerial survey to estimate abundance of wintering mallards {Anas platyrhynchos), dabbling ducks (tribe Anatini) other than mallards, diving ducks (tribes Aythini, Mergini, and Oxyurini), and total ducks in western Mississippi, USA. We used design-based sampling of fixed width transects to estimate population indices (I??), and we used model-based methods to correct population indices for visibility bias and estimate population abundance (N??) for 14 surveys during winters 2002-2004. Correcting for bias increased estimates of mallards, other dabbling ducks, and diving ducks by an average of 40-48% among all surveys and contributed 48-61% of the estimated variance of N??. However, mean-squared errors were consistently less for N?? than I??. Estimates of N?? met our goals for precision (CV ??? 15%) in 7 of 14 surveys for mallards, 5 surveys for other dabbling ducks, no surveys for diving ducks, and 10 surveys for total ducks. Generally, we estimated more mallards and other dabbling ducks in mid- and late winter (Jan-Feb) than early winter (Nov-Dec) and determined that population indices from the late 1980s were nearly 3 times greater than those from our study. We developed a method to display relative densities of ducks spatially as an additional application of survey data. Our study advanced methods of estimating abundance of wintering waterfowl, and we recommend this design for continued monitoring of wintering ducks in western Mississippi and similar physiographic regions.

  14. 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.

  15. 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

  16. 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

  17. 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...

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. Natural forest biomass estimation based on plantation information using PALSAR data.

    PubMed

    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.

  4. 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.

  5. 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.

  6. 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...

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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

  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. 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.

  17. 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

    2015-01-28

    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.

  18. 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

  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. 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

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

    PubMed

    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

  3. 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.

  4. 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.

  5. 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.

  6. A multimodal detection model of dolphins to estimate abundance validated by field experiments.

    PubMed

    Akamatsu, Tomonari; Ura, Tamaki; Sugimatsu, Harumi; Bahl, Rajendar; Behera, Sandeep; Panda, Sudarsan; Khan, Muntaz; Kar, S K; Kar, C S; Kimura, Satoko; Sasaki-Yamamoto, Yukiko

    2013-09-01

    Abundance estimation of marine mammals requires matching of detection of an animal or a group of animal by two independent means. A multimodal detection model using visual and acoustic cues (surfacing and phonation) that enables abundance estimation of dolphins is proposed. The method does not require a specific time window to match the cues of both means for applying mark-recapture method. The proposed model was evaluated using data obtained in field observations of Ganges River dolphins and Irrawaddy dolphins, as examples of dispersed and condensed distributions of animals, respectively. The acoustic detection probability was approximately 80%, 20% higher than that of visual detection for both species, regardless of the distribution of the animals in present study sites. The abundance estimates of Ganges River dolphins and Irrawaddy dolphins fairly agreed with the numbers reported in previous monitoring studies. The single animal detection probability was smaller than that of larger cluster size, as predicted by the model and confirmed by field data. However, dense groups of Irrawaddy dolphins showed difference in cluster sizes observed by visual and acoustic methods. Lower detection probability of single clusters of this species seemed to be caused by the clumped distribution of this species.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. Estimating Sonoran pronghorn abundance and survival with fecal DNA and capture-recapture methods.

    PubMed

    Woodruff, Susannah P; Lukacs, Paul M; Christianson, David; Waits, Lisette P

    2016-10-01

    Population abundance estimates are important for management but can be challenging to determine in low-density, wide-ranging, and endangered species, such as Sonoran pronghorn (Antilocapra americana sonoriensis). The Sonoran pronghorn population has been increasing; however, population estimates are currently derived from a biennial aerial count that does not provide survival or recruitment estimates. We identified individuals through noninvasively collected fecal DNA and used robust-design capture-recapture to estimate abundance and survival for Sonoran pronghorn in the United States from 2013 to 2014. In 2014 we generated separate population estimates for pronghorn gathered near 13 different artificial water holes and for pronghorn not near water holes. The population using artificial water holes had 116 (95% CI 102-131) and 121 individuals (95% CI 112-132) in 2013 and 2014, respectively. For all locations, we estimated there were 144 individuals (95% CI 132-157). Adults had higher annual survival probabilities (0.83, 95% CI 0.69-0.92) than fawns (0.41, 95% CI 0.21-0.65). Our use of targeted noninvasive genetic sampling and capture-recapture with Sonoran pronghorn fecal DNA was an effective method for monitoring a large proportion of the population. Our results provided the first survival estimates for this population in over 2 decades and precise estimates of the population using artificial water holes. Our method could be used for targeted sampling of broadly distributed species in other systems, such as in African savanna ecosystems, where many species congregate at watering sites. PMID:26918820

  12. 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.

  13. Estimating Sonoran pronghorn abundance and survival with fecal DNA and capture-recapture methods.

    PubMed

    Woodruff, Susannah P; Lukacs, Paul M; Christianson, David; Waits, Lisette P

    2016-10-01

    Population abundance estimates are important for management but can be challenging to determine in low-density, wide-ranging, and endangered species, such as Sonoran pronghorn (Antilocapra americana sonoriensis). The Sonoran pronghorn population has been increasing; however, population estimates are currently derived from a biennial aerial count that does not provide survival or recruitment estimates. We identified individuals through noninvasively collected fecal DNA and used robust-design capture-recapture to estimate abundance and survival for Sonoran pronghorn in the United States from 2013 to 2014. In 2014 we generated separate population estimates for pronghorn gathered near 13 different artificial water holes and for pronghorn not near water holes. The population using artificial water holes had 116 (95% CI 102-131) and 121 individuals (95% CI 112-132) in 2013 and 2014, respectively. For all locations, we estimated there were 144 individuals (95% CI 132-157). Adults had higher annual survival probabilities (0.83, 95% CI 0.69-0.92) than fawns (0.41, 95% CI 0.21-0.65). Our use of targeted noninvasive genetic sampling and capture-recapture with Sonoran pronghorn fecal DNA was an effective method for monitoring a large proportion of the population. Our results provided the first survival estimates for this population in over 2 decades and precise estimates of the population using artificial water holes. Our method could be used for targeted sampling of broadly distributed species in other systems, such as in African savanna ecosystems, where many species congregate at watering sites.

  14. 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

  15. Mapping functional traits: comparing abundance and presence-absence estimates at large spatial scales.

    PubMed

    Newbold, Tim; Butchart, Stuart H M; Sekercioğlu, Cağan H; Purves, Drew W; Scharlemann, Jörn P W

    2012-01-01

    Efforts to quantify the composition of biological communities increasingly focus on functional traits. The composition of communities in terms of traits can be summarized in several ways. Ecologists are beginning to map the geographic distribution of trait-based metrics from various sources of data, but the maps have not been tested against independent data. Using data for birds of the Western Hemisphere, we test for the first time the most commonly used method for mapping community trait composition - overlaying range maps, which assumes that the local abundance of a given species is unrelated to the traits in question - and three new methods that as well as the range maps include varying degrees of information about interspecific and geographic variation in abundance. For each method, and for four traits (body mass, generation length, migratory behaviour, diet) we calculated community-weighted mean of trait values, functional richness and functional divergence. The maps based on species ranges and limited abundance data were compared with independent data on community species composition from the American Christmas Bird Count (CBC) scheme coupled with data on traits. The correspondence with observed community composition at the CBC sites was mostly positive (62/73 correlations) but varied widely depending on the metric of community composition and method used (R(2): 5.6 × 10(-7) to 0.82, with a median of 0.12). Importantly, the commonly-used range-overlap method resulted in the best fit (21/22 correlations positive; R(2): 0.004 to 0.8, with a median of 0.33). Given the paucity of data on the local abundance of species, overlaying range maps appears to be the best available method for estimating patterns of community composition, but the poor fit for some metrics suggests that local abundance data are urgently needed to allow more accurate estimates of the composition of communities.

  16. 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.

  17. Crowd-Sourced Calibration: The GEDI Strategy for Empirical Biomass Estimation Using Spaceborne Lidar

    NASA Astrophysics Data System (ADS)

    Dubayah, R.

    2015-12-01

    The central task in estimating forest biomass from spaceborne sensors is the development of calibration equations that relate observed forest structure to biomass at a variety of spatial scales. Empirical methods generally rely on statistical estimation or machine learning techniques where field-based estimates of biomass at the plot level are associated with post-launch observations of variables such as canopy height and cover. For global-scale mapping the process is complex and leads to a number of questions: How many calibrations are required to capture non-stationarity in the relationships? Where does one calibration begin and another end? Should calibrations be conditioned by biome? Vegetation type? Land-use? Post-launch calibrations lead to further complications, such as the requirement to have sufficient field plot data underneath potentially sparse satellite observations, spatial and temporal mismatches in scale between field plots and pixels, and geolocation uncertainty, both in the plots and the satellite data. The Global Ecosystem Dynamics Investigation (GEDI) is under development by NASA to estimate forest biomass. GEDI will deploy a multi-beam lidar on the International Space Station and provide billions of observations of forest structure per year. Because GEDI uses relatively small footprints, about 25 m diameter, post-launch calibration is exceptionally problematic for the reasons listed earlier. Instead, GEDI will use a kind of "crowd-sourced" calibration strategy where existing lidar observations and the corresponding plot biomass will be assembled from data contributed by the science community. Through a process of continuous updating, calibrations will be refined as more data is ingested. This talk will focus on the GEDI pre-launch calibration strategy and present initial progress on its development, and how it forms the basis for meeting mission biomass requirements.

  18. 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.

  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. 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.

  1. 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...

  2. 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.

  3. Influences of temperature and nutrients on Synechococcus abundance and biomass in the southern Mid-Atlantic Bight

    NASA Astrophysics Data System (ADS)

    Moisan, Tiffany A.; Blattner, Kristen L.; Makinen, Carla P.

    2010-07-01

    Synechococci are small (<1 μm) coccoid prokaryotes that play a significant ecological role in microbial food webs and are important contributors to carbon and nitrogen biogeochemical cycles. Under funding from NOAA and NASA, we developed a time series observatory to understand the seasonal variability of Synechococcus and other phytoplankton. Our goal is to understand the distribution and relative contribution of Synechococcus to the carbon cycle and how they relate to nutrients and temperature. Synechococcus in the southern Mid-Atlantic Bight exhibited a clear seasonal abundance pattern in both inshore and offshore waters—peaking in abundance (11×10 4 cells ml -1) during warm periods of summer. Synechococci were numerically important during periods of stratification when waters were warm and macronutrients were low. Using a simple algorithm to convert cellular volume to cellular carbon using image analysis, we estimated that Synechococcus cellular carbon ranged from 0.1 to 1.5 pg C per cell and was most significant compared to total particulate carbon in the summer peaking at ˜25% of the total carbon available. No direct correlations were found between Synechococcus abundance and nitrate, nitrite, ammonium, phosphate, and silicate. However, inshore Synechococcus abundance peaked at 10 4 cells ml -1 when nitrogen concentrations were lowest. Our results suggest that Synechococcus is adapted to warm temperatures and are capable of demonstrating rapid growth during summer when macronutrients are limiting. The ability of Synechococcus to take advantage of high summer temperatures, low nutrient concentrations and low light levels allows them to maintain a picoplankton community during periods of low detritus and nanophytoplankton is nutrient limited. Temperature-dependence is important in altering the size spectrum of the phytoplankton community and affects the carbon cycle on the Mid Atlantic Bight.

  4. 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.

  5. 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.

  6. Conservation in a cup of water: estimating biodiversity and population abundance from environmental DNA.

    PubMed

    Lodge, David M; Turner, Cameron R; Jerde, Christopher L; Barnes, Matthew A; Chadderton, Lindsay; Egan, Scott P; Feder, Jeffrey L; Mahon, Andrew R; Pfrender, Michael E

    2012-06-01

    Three mantras often guide species and ecosystem management: (i) for preventing invasions by harmful species, 'early detection and rapid response'; (ii) for conserving imperilled native species, 'protection of biodiversity hotspots'; and (iii) for assessing biosecurity risk, 'an ounce of prevention equals a pound of cure.' However, these and other management goals are elusive when traditional sampling tools (e.g. netting, traps, electrofishing, visual surveys) have poor detection limits, are too slow or are not feasible. One visionary solution is to use an organism's DNA in the environment (eDNA), rather than the organism itself, as the target of detection. In this issue of Molecular Ecology, Thomsen et al. (2012) provide new evidence demonstrating the feasibility of this approach, showing that eDNA is an accurate indicator of the presence of an impressively diverse set of six aquatic or amphibious taxa including invertebrates, amphibians, a fish and a mammal in a wide range of freshwater habitats. They are also the first to demonstrate that the abundance of eDNA, as measured by qPCR, correlates positively with population abundance estimated with traditional tools. Finally, Thomsen et al. (2012) demonstrate that next-generation sequencing of eDNA can quantify species richness. Overall, Thomsen et al. (2012) provide a revolutionary roadmap for using eDNA for detection of species, estimates of relative abundance and quantification of biodiversity.

  7. Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests

    NASA Astrophysics Data System (ADS)

    Vaglio Laurin, Gaia; Puletti, Nicola; Chen, Qi; Corona, Piermaria; Papale, Dario; Valentini, Riccardo

    2016-10-01

    Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests. This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables. We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R2 = 0.72) and species richness (R2 = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment.

  8. 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.

  9. Chemical abundances of damped Ly alpha systems:. A new method for estimating dust depletion effects

    NASA Astrophysics Data System (ADS)

    Vladilo, G.

    2002-08-01

    A new method is presented for recovering the abundances of Damped Ly alpha systems (DLAs) taking into account the effects of dust depletion. For the first time, possible variations of the chemical composition of the dust are taken into account in estimating the depletions. No prior assumptions on the extinction properties of the dust are required. The method requires a set of abundances measured in the gas and a set of parameters describing the chemical properties of the dust. A large subset of these parameters is determined from interstellar observations; the others are free parameters for which an educated guess can be made. The method is able to recover the abundances of the SMC starting from SMC interstellar measurements apparently discrepant from the stellar ones. Application of the method to 22 DLAs with available [Fe/H] and [Si/Fe] measurements gives the following results: (1) the mean metallicity of the corrected data is < [Fe/H]> =~ -1.0 dex, about 0.5 dex higher than that of the original data; (2) the slope of the [Fe/H] versus redshift relation is steeper for the corrected data (m =~ -0.3 dex) than for the original ones (m =~ -0.2 dex); (3) the corrected [Si/Fe] ratios are less enhanced, on average, than those found in Galactic stars of similar, low metallicity; (4) a decrease of the [Si/Fe] versus [Fe/H] ratios, expected by ``time delay'' models of chemical evolution, is found for the corrected data; (5) the [Si/Fe] ratios tend to increase with redshift once corrected; (6) consistency between [Si/Fe] and [S/Zn] measurements, two independent estimators of the alpha /Fe ratio, is found only for the corrected abundances.

  10. 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. 

  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. 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.

  13. 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.

  14. READSCAN: a fast and scalable pathogen discovery program with accurate genome relative abundance estimation

    PubMed Central

    Rashid, Mamoon; Pain, Arnab

    2013-01-01

    Summary: READSCAN is a highly scalable parallel program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets. READSCAN accurately classified human and viral sequences on a 20.1 million reads simulated dataset in <27 min using a small Beowulf compute cluster with 16 nodes (Supplementary Material). Availability: http://cbrc.kaust.edu.sa/readscan Contact: arnab.pain@kaust.edu.sa or raeece.naeem@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23193222

  15. 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.

  16. 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

  17. 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

  18. 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.

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

    DOE PAGES

    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

  20. 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.

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

    PubMed

    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.

  2. Improved leaf area index based biomass estimations for Zostera marina L.

    PubMed

    Solana-Arellano, Elena; Echavarria-Heras, Hector; Gallegos Martinez, Margarita

    2003-12-01

    The application of special scanning technologies in plant population studies makes it now possible to offer reliable indirect estimations of Leaf Area Index (LAI). This has stimulated the adaptation of related biomass assessment methods and has provided a way to simplify tedious laboratory procedures whilst avoiding destructive sampling. Particularly, above-ground biomass for Zostera marina L. has been expressed depending linearly on Leaf Area Index. Nevertheless, we demonstrate that this approach produces biased estimations. It is also shown that expressing leaf dry weight by means of an allometric function of length and width can eliminate bias. Furthermore, the dominant term of the associated power series expansion becomes the aforementioned linear representation in terms of Leaf Area Index. The consistency of the estimation methods derived from the allometric model was tested using data from a Z. marina meadow. Consequently, the improved method is expected to become a valuable tool for the reduction of the uncertainty associated with the estimation of above-ground biomass through the use of Leaf Area Index.

  3. 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

  4. Fluorometric detection and estimation of fungal biomass on cultural heritage materials.

    PubMed

    Konkol, Nick; McNamara, Christopher J; Mitchell, Ralph

    2010-02-01

    A wide variety of cultural heritage materials are susceptible to fungal deterioration. The paper, canvas, and stone constituents of our cultural heritage are subjected to harmful physical and chemical processes as they are slowly consumed by fungi. Remediation of fungal contamination can be costly and risk further damage to cultural artifacts. Early detection of fungal growth would permit the use of relatively noninvasive treatments to remediate fungal contamination before visible or lasting damage to the object has occurred. Current methods used for the detection and measurement of microbial biomass, such as colony counts, microscopic biovolume estimation, and ergosterol analysis are expensive and time consuming, or are inappropriate for use with fungi. Beta-N-acetylhexosaminidase (3.2.1.52) activity provides a reliable estimation of fungal biomass in soil and on building materials. Adapted for use on cultural heritage materials' fluorogenic 4-methylumbelliferyl (MUF) labeled substrate N-acetyl-beta-d-glucosaminide (NAG) was used to detect beta-N-acetylhexosaminidase activity in the fungus Aspergillus niger. Fluorescence increased linearly with fungal biomass and the sensitivity of the assay was comparable to other biochemical techniques. The fluorometric assay was used to monitor fungal biomass on a variety of cultural heritage materials non-destructively, and without the introduction of chemicals or solvents to the surfaces.

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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

  18. Estimation of aboveground biomass in forests using multi-sensor (LIDAR, IFSAR, ETM+) fusion

    NASA Astrophysics Data System (ADS)

    Hyde, P.; Dubuyah, R.; Blair, B.; Hofton, M.; Hunsaker, C.; Pierce, L.; Walker, W.

    2002-05-01

    Aboveground biomass in forests, or the dry weight of standing trees, is a key ecosystem parameter for carbon dynamics, fire modeling, and biodiversity studies. Field-based assessments are expensive and methods to scale from field plots to landscapes are not generally accepted. Remote sensing potentially provides a cost-effective alternative, but no single sensor has yet to provide accurate, consistent estimates in all biomes. Passive optical sensors and synthetic aperture radar (SAR) have been proven effective only in young, structurally simple forests. Light detecting and ranging (LIDAR) has been effective in old-growth, structurally complex forests, but data are not widely available. Combining information from these sensors will leverage the high information content, high cost LIDAR data with lower cost, more widely available SAR and passive optical data. In this study, Landsat ETM+, x-band interferometric SAR, and airborne LIDAR from the Laser Vegetation Imaging Sensor (LVIS) were statistically fused using a decision tree classifier and compared to field-based estimates of biomass in Sierra National Forest, CA, USA. Biomass estimates derived from all sensors combined were more accurate than those derived from any single sensor.

  19. 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

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

    PubMed

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

    2015-06-04

    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

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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

  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. 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

  8. Forest Volume and Biomass estimation from SAR/LIDAR/Optical Fusion in Chile

    NASA Astrophysics Data System (ADS)

    Kellndorfer, J. M.; Walker, W. S.; Goetz, S. J.; Cormier, T.; Kirsch, K.; Gonzalez, S.; Rombach, M.

    2009-12-01

    The paper reports on research to investigate ALOS/PALSAR L-band radar and optical time series data in conjunction with airborne lidar datasets to develop advanced data fusion algorithms for biomass and ecosystem structure measurements in support of the NASA DESDynI mission. The research is based on the acquisition of ALOS/PALSAR time series data beginning in 2007 and the timely confluence of these acquisitions with other highly relevant remote sensing and ground reference data sets in forested areas in Chile. Through collaboration with Digimapas Chile, the project has access to 75,000 km2 of 1-meter resolution full-waveform small footprint lidar (SFPL) data and 0.5 m resolution digital orthophoto imagery covering the commercial forests of Arauco, one of the largest cellulose producers in Latin America. Field inventory data from Arauco are used to test terrain and environmental influences on biomass estimation from empirical regression tree based data fusion approaches. The SAR data acquisitions available from PALSAR during the project time frame will span a five year period from 2007 to 2011, allowing investigations into how L-band time series data, similar to that expected from the DESDynI SAR (backscatter and interferometric coherence), can be used to build (1) the DESDynI biomass map product to be produced at the end of the “designed mission life” (i.e., 3 and/or 5/5+ years) and (2) annual maps of aboveground biomass change.

  9. 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.

  10. Estimation of cell volume and biomass of penicillium chrysogenum using image analysis.

    PubMed

    Packer, H L; Keshavarz-Moore, E; Lilly, M D; Thomas, C R

    1992-02-20

    A methodology for the estimation of biomass for the penicillin fermentation using image analysis is presented. Two regions of hyphae are defined to describe the growth of mycelia during fermentation: (1) the cytoplasmic region, and (2) the degenerated region including large vacuoles. The volume occupied by each of these regions in a fixed volume of sample is estimated from area measurements using image analysis. Areas are converted to volumes by treating the hyphae as solid cylinders with the hyphal diameter as the cylinder diameter. The volumes of the cytoplasmic and degenerated regions are converted into dry weight estimations using hyphal density values available from the literature. The image analysis technique is able to estimate biomass even in the presence of nondissolved solids of a concentration of up to 30 gL(-1). It is shown to estimate successfully concentrations of mycelia from 0.03 to 38 gL(-1). Although the technique has been developed for the penicillin fermentation, it should be applicable to other (nonpellected) fungal fermentations.

  11. Predicting tree heights for biomass estimates in tropical forests - a test from French Guiana

    NASA Astrophysics Data System (ADS)

    Molto, Q.; Hérault, B.; Boreux, J.-J.; Daullet, M.; Rousteau, A.; Rossi, V.

    2014-06-01

    The recent development of REDD+ mechanisms requires reliable estimation of carbon stocks, especially in tropical forests that are particularly threatened by global changes. Even though tree height is a crucial variable for computing aboveground forest biomass (AGB), it is rarely measured in large-scale forest censuses because it requires extra effort. Therefore, tree height has to be predicted with height models. The height and diameter of all trees over 10 cm in diameter were measured in 33 half-hectare plots and 9 one-hectare plots throughout northern French Guiana, an area with substantial climate and environmental gradients. We compared four different model shapes and found that the Michaelis-Menten shape was most appropriate for the tree biomass prediction. Model parameter values were significantly different from one forest plot to another, and this leads to large errors in biomass estimates. Variables from the forest stand structure explained a sufficient part of plot-to-plot variations of the height model parameters to improve the quality of the AGB predictions. In the forest stands dominated by small trees, the trees were found to have rapid height growth for small diameters. In forest stands dominated by larger trees, the trees were found to have the greatest heights for large diameters. The aboveground biomass estimation uncertainty of the forest plots was reduced by the use of the forest structure-based height model. It demonstrated the feasibility and the importance of height modeling in tropical forests for carbon mapping. When the tree heights are not measured in an inventory, they can be predicted with a height-diameter model and incorporating forest structure descriptors may improve the predictions.

  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. Effects of sampling design on the estimation of adult mosquito abundance.

    PubMed

    Reisen, W K; Lothrop, H D

    1999-06-01

    During 1994-5, Culex tarsalis comprised 75% of the 902,643 adult female mosquitoes collected by 63 dry-ice-baited Centers for Disease Control (CDC)-style traps operated biweekly in a uniform sampling grid that covered the southern Coachella Valley, Riverside County, California. The ln(y + 1) transformation successfully controlled the variance and normalized the distribution of catch size among trap nights. When tested by analysis of variance, abundance varied significantly among months, years, and trap sites. Although the trap by months interaction was not significant, female distribution changed seasonally as larval habitats shifted from wetlands along the Salton Sea to agriculture to managed duck marshes. Conditional simulations utilized subsets of trap sites to compare sampling designs that required no (uniform, random, and transect designs) or prior (best-estimate and stratified random designs) knowledge of mosquito spatial distribution. All designs provided similar information on population seasonal trends, but a stratified random design provided the most accurate and precise simulation. A uniform trap grid that employed every 2nd trap site subsequently was adopted by the Coachella Valley Mosquito and Vector Control District to provide information on focal changes in abundance indicative of missed or newly created larval habitats or control failures. PMID:10412106

  14. 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.

  15. Estimating the global abundance of ground level presence of particulate matter (PM2.5).

    PubMed

    Lary, David J; Faruque, Fazlay S; Malakar, Nabin; Moore, Alex; Roscoe, Bryan; Adams, Zachary L; Eggelston, York

    2014-12-01

    With the increasing awareness of the health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground level airborne particulate matter with a diameter of 2.5 microns or less (PM2.5). Here we use a suite of remote sensing and meteorological data products together with ground-based observations of particulate matter from 8,329 measurement sites in 55 countries taken 1997-2014 to train a machine-learning algorithm to estimate the daily distributions of PM2.5 from 1997 to the present. In this first paper of a series, we present the methodology and global average results from this period and demonstrate that the new PM2.5 data product can reliably represent global observations of PM2.5 for epidemiological studies.

  16. 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

  17. 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 E.; 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.

  18. 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

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

    PubMed

    Siddig, Ahmed A; 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/m(2) 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

  20. 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.

  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. 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.

  4. 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.

  5. Estimation of Forest Biomass Increment Using Tree-ring data and Hydro-Ecological Modeling in a Rugged Forested Landscape

    NASA Astrophysics Data System (ADS)

    Lee, B.; Kang, S.; Kim, E.; Kim, Y.

    2006-12-01

    Terrestrial carbon sequestration by forest biomass is an important component of global carbon cycle, which is closely related to the greenhouse effect and climate system. Many researchers have studied on how to estimate forest biomass accurately and they utilized various methods including ecological modeling, remote sensing, and field measurements. However, it is still highly uncertain to estimate the forest biomass accurately and predict the future change. In particular, where water limitation is likely expected, carbon and water relations should be considered importantly in predicting vegetation primary production. The main objective of this study is to estimate biomass increments in the Gwangneung Experimental Forest (GEF) and to compare them with the simulation results of RHESSys, a GIS-based hydro-ecological model designed to simulate water and nutrient fluxes. We measured biomass and to estimate biomass increments using tree-ring data from 1991 to 2004, and they were calculated by using the single tree biomass equation. Average biomass increment during the study period was 271.38 g C m-2yr-1. RHESSys simulations need to a certain number of years to allow carbon and nitrogen stores to stabilize (spin up), which provides initial condition of the model simulation from 1991 to 2004. The data of Leaf Area Index (LAI) and daily stream discharge were used for model calibration. In addition, the results of biomass increment measurement from 1991 to 1997 in GEF were used for model parameterization, and those from 1998 to 2004 were used for validation. Our preliminary simulation results indicated that the simulation results of RHESSys model on the biomass increment was reasonably accurate, but in order to improve the prediction accuracy of this model, we concluded that various efforts on model verification and field data collection are required. *Keyword: Biomass increment, Hydro-Ecological Model. *Acknowledgement : This work was supported by the 2nd phase Brain Korea

  6. 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

  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. 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.

  9. 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.

  10. 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

  11. Use of miniroutes and Breeding Bird Survey data to estimate abundance

    USGS Publications Warehouse

    Robbins, C.S.; Dowell, B.A.

    1986-01-01

    1. Information on relative abundance is easily obtained and adds greatly to the value of an atlas project. 2. The Breeding Bird Survey (BBS) provides annual counts (birds per 50 roadside stops) that can be used to: (1) map relative abundance by physiographic region within a state or province, (2) map relative abundance on a more local scale by using results from individual routes, or (3) compute estimates of total state populations of a species. Where BBS coverage is too scanty to permit mapping, extra temporary routes may be established to provide additional information for the atlas. Or, if continuing coverage is anticipated, additional permanent random routes can be assigned by the U. S. Fish and Wildlife Service. 3. Miniroutes of 15 or more stops can be established in individual atlas blocks to serve the dual purposes of providing efficient uniform coverage and providing information on relative abundance. Miniroutes can also be extracted from BBS routes to supplement special atlas coverage, or vice versa; but the data from the BBS will not be confined to individual atlas blocks. 4. Advantages of 15- or 20-stop Miniroutes over 25-stop Miniroutes are several: the ability to do two per morning and the lower variability among M1niroute results. Also, many 5-km atlas blocks do not have enough secondary roads to accommodate 25 stops at one-half mile intervals. Disadvantages of 15-stop Miniroutes starting at sunrise are the smaller numbers of birds recorded, missing of the very productive dawn chorus period (Robbins 1981), and missing crepuscular species (rails, woodcock, owls, and goatsuckers). 5. Advantages of recording counts of individuals rather than checking only species presence at Miniroute stops are that: (1) relative abundance can be mapped rather than frequency only (a measure of frequency is already available in the number of blocks recording each species); (2) population change can be measured over a period of years when the next atlas is made; and (3

  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. 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

  14. 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

  15. 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.

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

    DOE PAGES

    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

  17. 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.

  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.

  19. 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

  20. 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.

  1. [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

  2. [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

  3. Use of forest inventories and geographic information systems to estimate biomass density of tropical forests: Application to tropical Africa.

    PubMed

    Brown, S; Gaston, G

    1995-01-01

    One of the most important databases needed for estimating emissions of carbon dioxide resulting from changes in the cover, use, and management of tropical forests is the total quantity of biomass per unit area, referred to as biomass density. Forest inventories have been shown to be valuable sources of data for estimating biomass density, but inventories for the tropics are few in number and their quality is poor. This lack of reliable data has been overcome by use of a promising approach that produces geographically referenced estimates by modeling in a geographic information system (GIS). This approach has been used to produce geographically referenced, spatial distributions of potential and actual (circa 1980) aboveground biomass density of all forests types in tropical Africa. Potential and actual biomass density estimates ranged from 33 to 412 Mg ha(-1) (10(6)g ha(-1)) and 20 to 299 Mg ha(-1), respectively, for very dry lowland to moist lowland forests and from 78 to 197 Mg ha(-1) and 37 to 105 Mg ha(-1), respectively, for montane-seasonal to montane-moist forests. Of the 37 countries included in this study, more than half (51%) contained forests that had less than 60% of their potential biomass. Actual biomass density for forest vegetation was lowest in Botswana, Niger, Somalia, and Zimbabwe (about 10 to 15 Mg ha(-1)). Highest estimates for actual biomass density were found in Congo, Equatorial Guinea, Gabon, and Liberia (305 to 344 Mg ha(-1)). Results from this research effort can contribute to reducing uncertainty in the inventory of country-level emission by providing consistent estimates of biomass density at subnational scales that can be used with other similarly scaled databases on change in land cover and use.

  4. 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.

  5. 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.

  6. Applying ICESat/GLAS data to estimate forest aboveground biomass on Hokkaido, Japan

    NASA Astrophysics Data System (ADS)

    Hayashi, M.; Saigusa, N.; Oguma, H.; Yamao, Y.; Yamagata, Y.; Takao, G.

    2013-12-01

    Spaceborne Light Detection And Ranging (LiDAR) has an ability to measure forest resources with high accuracy, therefore, it will contribute to evaluating global carbon cycle or addressing climate change. We then evaluated the potential of spaceborne LiDAR to measure forest resources, and used Geoscience Laser Altimeter System (GLAS) data obtained with the Ice, Cloud, and land Elevation Satellite (ICESat) to develop an estimation methodology for forest biomass. The study area was the island of Hokkaido, Japan. We compared two estimation methods: (i) a direct method that uses some of the GLAS waveform parameters to estimate aboveground biomass (AGB) directly, and (ii) an allometric method that uses an allometric equation to estimate AGB from the canopy height estimated from the GLAS waveform. We used two kinds of ground truth data: (i) field survey data in situ measurements of AGB by the Bitterlich method at 106 points within GLAS footprints, and (ii) airborne LiDAR data from maximum canopy height measurements at 481 points within GLAS footprints. We then used the field survey data to develop the AGB estimation equation of the direct method by carrying out a multiple regression analysis that related GLAS waveform parameters to AGB. For the allometric method, we also carried out a multiple regression analysis using the airborne LiDAR data to estimate canopy height from GLAS data. Two parameters were used as the explanatory variables: a 'terrain index' calculated from the ground elevation difference within a GLAS footprint, and a 'GLAS waveform extent'. The root mean square error (RMSE) of the canopy height estimates was 4.1 m. We used the allometric equation determined from the field survey data to relate canopy height to AGB and then estimated the AGB from the GLAS estimates of canopy height. The accuracy of the AGB estimates obtained by these two estimation methods was determined by comparison with the field survey data. The RMSEs of the direct and allometric

  7. 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

  8. Estimating Above Ground Biomass using LiDAR in the Northcoast Redwood Forests

    NASA Astrophysics Data System (ADS)

    Rao, M.; Stewart, E.

    2010-12-01

    In recent years, LiDAR (Light Intensity Detection Amplification and Ranging) is increasingly being used in estimating biophysical parameters related to forested environments. The main goal of the project is to estimate long-term biomass accumulation and carbon sequestration potential of the redwoods ecosystem. The project objectives are aimed at providing an assessment of carbon pools within the redwood ecosystem. Specifically, we intend to develop a relational model based on LiDAR-based canopy estimates and extensive ground-based measurements available for the old-growth redwood forest located within the Prairie Creek Redwoods State Park, CA. Our preliminary analysis involved developing a geospatial database, including LiDAR data collected in 2007 for the study site, and analyzing the data using USFS Fusion software. The study area comprised of a 12-acres section of coastal redwood (Sequoia sempervirens) in the Prairie Creek Redwoods State Park, located in Orick, CA. A series of analytical steps were executed using the USFS FUSION software to produce some intermediate data such as bare earth model, canopy height model, canopy coverage model, and canopy maxima treelist. Canopy maxima tree tops were compared to ground layer to determine height of tree tops. A total of over 1000 trees were estimated, and then with thinning (to eliminate errors due to low vegetation > 3 meters tall), a total of 950 trees were delineated. Ground measurements were imported as a point based shapefile and then compared to the treetop heights created from LiDAR data to the actual ground referenced data. The results were promising as most estimated treetops were within 1-3 meters of the ground measurements and generally within 3-5m of the actual tree height. Finally, we are in the process of applying some allometric equations to estimate above ground biomass using some of the LiDAR-derived canopy metrics.

  9. A Bayesian geostatistical estimation of biomass in semi-arid rangelands by combining airborne and terrestrial laser scanning data

    NASA Astrophysics Data System (ADS)

    Li, A.; Glenn, N. F.

    2012-12-01

    Biomass of vegetation is critical for carbon cycle research. Estimating biomass from field survey data is laborious and/or destructive and thus retrieving biomass from remote sensing data may be advantageous. Most remote sensing biomass studies have focused on forest ecosystems, while few have focused on low stature vegetation, such as grasses in semi-arid environments. Biomass estimates for grass are significant for studying wildlife habitat, assessing fuel loads, and studying climate change response in semi-arid regions. Recent research has demonstrated the ability of small footprint airborne laser scanning (ALS) data to extract sagebrush height characteristics and the ability of terrestrial laser scanning (TLS) data to estimate vegetation volume over semi-arid rangelands. ALS has somewhat lower resolution than TLS, but has improved spatial coverage over TLS. Combining ALS and TLS is a powerful tool to estimate biomass on regional scales. Bayesian geostatistics, also known as Bayesian Maximum Entropy (BME), can fuse multiple data sources across scales and provide estimation uncertainties for the integration of ALS and TLS data for grass biomass. Regression models are used to approximately delineate the relationship between field biomass measurements and TLS derived height and shape metrics. We then consider TLS plot-level data at the point scale with ALS data at the area scale. The regularization method is utilized to establish the scaling relations between TLS-derived and ALS-derived metrics. The metric maps from the ALS level are reconstructed using a BME method based on regularized variograms. We gain biomass and estimation uncertainty on the regional scale by introducing updated metrics into the model. In order to evaluate the effectiveness of the BME method, we develop simple independent regression models by assuming the TLS-derived metrics as ground reference data. Therefore, the regression model is used to correct the ALS-estimated values and we retrieve

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  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. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Variability in abundance of temperate reef fishes estimated by visual census.

    PubMed

    Irigoyen, Alejo J; Galván, David E; Venerus, Leonardo A; Parma, Ana M

    2013-01-01

    Identifying sources of sampling variation and quantifying their magnitude is critical to the interpretation of ecological field data. Yet, most monitoring programs of reef fish populations based on underwater visual censuses (UVC) consider only a few of the factors that may influence fish counts, such as the diver or census methodology. Recent studies, however, have drawn attention to a broader range of processes that introduce variability at different temporal scales. This study analyzes the magnitude of different sources of variation in UVCs of temperate reef fishes off Patagonia (Argentina). The variability associated with time-of-day, tidal state, and time elapsed between censuses (minutes, days, weeks and months) was quantified for censuses conducted on the five most conspicuous and common species: Pinguipes brasilianus, Pseudopercis semifasciata, Sebastes oculatus, Acanthistius patachonicus and Nemadactylus bergi. Variance components corresponding to spatial heterogeneity and to the different temporal scales were estimated using nested random models. The levels of variability estimated for the different species were related to their life history attributes and behavior. Neither time-of-day nor tidal state had a significant effect on counts, except for the influence of tide on P. brasilianus. Spatial heterogeneity was the dominant source of variance in all but one species. Among the temporal scales, the intra-annual variation was the highest component for most species due to marked seasonal fluctuations in abundance, followed by the weekly and the instantaneous variation; the daily component was not significant. The variability between censuses conducted at different tidal levels and time-of-day was similar in magnitude to the instantaneous variation, reinforcing the conclusion that stochastic variation at very short time scales is non-negligible and should be taken into account in the design of monitoring programs and experiments. The present study provides

  1. Variability in Abundance of Temperate Reef Fishes Estimated by Visual Census

    PubMed Central

    Irigoyen, Alejo J.; Galván, David E.; Venerus, Leonardo A.; Parma, Ana M.

    2013-01-01

    Identifying sources of sampling variation and quantifying their magnitude is critical to the interpretation of ecological field data. Yet, most monitoring programs of reef fish populations based on underwater visual censuses (UVC) consider only a few of the factors that may influence fish counts, such as the diver or census methodology. Recent studies, however, have drawn attention to a broader range of processes that introduce variability at different temporal scales. This study analyzes the magnitude of different sources of variation in UVCs of temperate reef fishes off Patagonia (Argentina). The variability associated with time-of-day, tidal state, and time elapsed between censuses (minutes, days, weeks and months) was quantified for censuses conducted on the five most conspicuous and common species: Pinguipes brasilianus, Pseudopercis semifasciata, Sebastes oculatus, Acanthistius patachonicus and Nemadactylus bergi. Variance components corresponding to spatial heterogeneity and to the different temporal scales were estimated using nested random models. The levels of variability estimated for the different species were related to their life history attributes and behavior. Neither time-of-day nor tidal state had a significant effect on counts, except for the influence of tide on P. brasilianus. Spatial heterogeneity was the dominant source of variance in all but one species. Among the temporal scales, the intra-annual variation was the highest component for most species due to marked seasonal fluctuations in abundance, followed by the weekly and the instantaneous variation; the daily component was not significant. The variability between censuses conducted at different tidal levels and time-of-day was similar in magnitude to the instantaneous variation, reinforcing the conclusion that stochastic variation at very short time scales is non-negligible and should be taken into account in the design of monitoring programs and experiments. The present study provides

  2. 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.

  3. 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.

  4. 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.

  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. 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.

  7. 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

  8. 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

  9. 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

  10. 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

  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. 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

  13. 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

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. Satellite Estimates of Single Scattering Albedo and Optical Depth of Biomass Burning Carbonaceous Aerosols

    NASA Technical Reports Server (NTRS)

    Torres, O.; Herman, J. R.; Bhartia, P. K.; Hsu, N. C.

    1998-01-01

    Satellite based estimates of aerosol single scattering albedo (ssa), over both land and water surfaces, have been obtained for the first time using measurements of backscattered radiation in the near ultraviolet by the Total Ozone Mapping Spectrometer (TOMS). The retrieval of ssa and aerosol optical depth is based on the strong spectral contrast in the near-UV resulting from the interaction between the particle absorption and scattering (both Rayleigh and Mie) processes. We use the multi-year data set on backscattered radiances by the TOMS family of instruments to analyze the time and space variability of biomass burning generated carbonaceous aerosols. Results of a comparative analysis of satellite derived optical depth and available sunphotometer measurements will also be presented.

  1. 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.

  2. Estimation of potential biomass resource and biogas production from aquatic plants in Argentina

    SciTech Connect

    Fitzsimons, R.E.; Laurino, C.N.; Vallejos, R.H.

    1982-08-01

    It is expected that the future construction of the Parana Medio Hydroelectric Project on the middle Parana River in Argentina will lead to the accumulation of floating hydrophytes, mainly water hyacinth. Several problems are related to aquatic plants, and steps for efficient control of the vegetation should be taken. If mechanical control is used, the biomass must be processed, preferably in a useful way. Water hyacinth growth in the middle Parana River has been measured and its bioconversion to methane by anaerobic fermentation determined. It is estimated that gross methane production may be between 1. and 4.1 x 10/sup 9/ m/sup 3//yr. The fermentation residue production, with a potential value as soil condition, may represent between 54.9 and 221.4 x 10/sup 3/t nitrogen/year, i.e., between 2 and 8 times the present nitrogen fertilizer demand in Argentina.

  3. 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.

  4. Use of Spectral Radiance to Estimate In-Season Biomass and Grain Yield in Nitrogen- and Water-Stressed Corn.

    PubMed

    Osborne, S. L.; Schepers, J. S.; Francis, D. D.; Schlemmer, M. R.

    2002-01-01

    Current technologies for measuring plant water status are limited, while recently remote sensing techniques for estimating N status have increased with limited research on the interaction between the two stresses. Because plant water status methods are time-consuming and require numerous observations to characterize a field, managers could benefit from remote sensing techniques to assist in irrigation and N management decisions. A 2-yr experiment was initiated to determine specific wavelengths and/or combinations of wavelengths indicative of water stress and N deficiencies, and to evaluate these wavelengths for estimating in-season biomass and corn (Zea mays L.) grain yield. The experiment was a split-plot design with three replications. The treatment structure had five N rates (0, 45, 90, 134, and 269 kg N ha(-1)) and three water treatments [dryland, 0.5 evapotranspiration (ET), and full ET]. Canopy spectral radiance measurements (350-2500 nm) were taken at various growth stages (V6-V7, V13-V16, and V14-R1). Specific wavelengths for estimating crop biomass, N concentration, grain yield, and chlorophyll meter readings changed with growth stage and sampling date. Changes in total N and biomass in the presence of a water stress were estimated using near-infrared (NIR) reflectance and the water absorption bands. Reflectance in the green and NIR regions were used to estimate total N and biomass without water stress. Reflectance at 510, 705, and 1135 nm were found for estimating chlorophyll meter readings regardless of year or sampling date.

  5. Interannual and Spatial Variability in Maturity of Walleye Pollock Gadus chalcogrammus and Implications for Spawning Stock Biomass Estimates in the Gulf of Alaska

    PubMed Central

    Kruse, Gordon H.; Dorn, Martin W.

    2016-01-01

    Catch quotas for walleye pollock Gadus chalcogrammus, the dominant species in the groundfish fishery off Alaska, are set by applying harvest control rules to annual estimates of spawning stock biomass (SSB) from age-structured stock assessments. Adult walleye pollock abundance and maturity status have been monitored in early spring in Shelikof Strait in the Gulf of Alaska for almost three decades. The sampling strategy for maturity status is largely characterized as targeted, albeit opportunistic, sampling of trawl tows made during hydroacoustic surveys. Trawl sampling during pre-spawning biomass surveys, which do not adequately account for spatial patterns in the distribution of immature and mature fish, can bias estimated maturity ogives from which SSB is calculated. Utilizing these maturity data, we developed mixed-effects generalized additive models to examine spatial and temporal patterns in walleye pollock maturity and the influence of these patterns on estimates of SSB. Current stock assessment practice is to estimate SSB as the product of annual estimates of numbers at age, weight at age, and mean maturity at age for 1983-present. In practice, we found this strategy to be conservative for a time period from 2003–2013 as, on average, it underestimates SSB by a 4.7 to 11.9% difference when compared to our estimates of SSB that account for spatial structure or both temporal and spatial structure. Inclusion of spatially explicit information for walleye pollock maturity has implications for understanding stock reproductive biology and thus the setting of sustainable harvest rates used to manage this valuable fishery. PMID:27736982

  6. Comparison of anchovy biomass estimates measured by trawls, egg production methods and hydro-acoustics in the Chesapeake Bay and the Korea Strait

    NASA Astrophysics Data System (ADS)

    Jung, Sukgeun; Houde, Edward D.

    2014-06-01

    We compared estimates of anchovy biomass derived from trawl surveys, egg production method (EPM) and acoustic surveys, conducted in two remote regions. Biomass density of bay anchovy Anchoa mitchilli was estimated in Chesapeake Bay, USA, by trawls, EPM and acoustics from 1989 to 2000. Biomass density of Pacific anchovy Engraulis japonicus was estimated in the Korea Strait using EPM, simulation-based daily cohort analysis and acoustics from 1984 to 2006. Most of the existing estimates already had considered body-size-dependent gear selectivity, highlyvariable instantaneous natural mortality of anchovy eggs, and avoidance of trawl nets by adult anchovy. Despite great variability in the ratio of trawl to acoustic biomass estimates (0.034-8.35), annually-averaged biomass density of young-ofthe-year individuals derived by the two methods were similar for bay anchovy in Chesapeake Bay and Pacific anchovy in the Korea Strait (0.83 and 0.70 g m-3, respectively). Results suggested that, despite substantial uncertainty, anchovy biomass estimates are generally compatible between EPM and acoustics. However, reported estimates of biomass density derived from the two acoustic surveys in the Korea Strait differed by a factor of 28, suggesting that further improvements in calibrations are required to reliably estimate anchovy biomass. The comparisons suggested that all biomass estimates could be biased and will require comparison and validation by other, independent sampling methods.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. Toward Aboveground Biomass Estimation with RADAR, Lidar and Optical Remote Sensing Data in Southern Mexico

    NASA Astrophysics Data System (ADS)

    Urbazaev, M.; Thiel, C. J.; Schmullius, C.

    2014-12-01

    Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed (1) for understanding and managing the processes involved in the carbon cycle, and (2) supporting international policies for climate change mitigation and adaption. Using remote sensing techniques it is possible to provide spatially explicit information of AGB from local to global scales. In this work we present the first results on the use of multi-sensor remote sensing data to estimate AGB over three test sites in southern Mexico. In order to develop a set of AGB retrieval algorithms, we firstly compared different SAR parameters (e.g. multi-polarized backscatter intensities and interferometric coherence) obtained from ALOS PALSAR sensor and Landsat imagery with field-based AGB estimates using empirical regressions and analyzed the relationships between them. The next steps of the work will be development of a two-stage up-scaling approach: firstly, to enlarge the cal/val data, we propose to estimate AGB along airborne LiDAR (from G-LiHT sensor) transects using field-based AGB and LiDAR height metrics. With LiDAR-based AGB we will then calibrate SAR parameters in a non-parametric model (e.g., randomForest) to create AGB maps over the study areas. An overall aim of the study is the analysis of capabilities and limitations of SAR data for AGB mapping and the investigation of the potential synergistic use of SAR, LiDAR and optical systems.The proposed monitoring tool will facilitate quantitative estimations in loss of carbon storage and support the selection of terrestrial (e.g. tropical dry forests, shrublands) sites for conservation priorities with high value for the national carbon budget.

  13. 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

  14. Estimation of Tree Height, Biomass, and Standing Carbon in Miombo Woodlands Using Radar Interferometry

    NASA Astrophysics Data System (ADS)

    Ribiero, N. S.; Washington-Allen, R. A.; Simard, M.; Shugart, H. H.

    2007-12-01

    Savannas and woodlands are a major component of the world's vegetation covering one-sixth of the global land surface and one-half of the African continent. They account for about 30% of the primary production of all terrestrial vegetation. The southern African savannas cover 54% of the sub-continent with a plant diversity of approximately 8500 species and approximately 50% endemism. Miombo covers about two thirds of Mozambique and estimations of its biomass are critical because ecosystem services provided include food, fiber, and fuel for 39 million rural peoples and another 15 million urban dwellers in southern Africa. The Shuttle Radar Topography Mission (SRTM) C-band derived digital terrain model (DTM) can be used to estimate tree height by subtracting a base-level digital elevation model (DEM) from the calibrated SRTM. SRTM C-band's wavelength is such that there is partial penetration of the tree canopy before scattering which results in an underestimate of tree height. Consequently, mean tree height data from 50 30-m x 30-m random-stratified field plots in Niassa Reserve were used to bias the SRTM data up to average tree height and thus calibrate. However, DEMs in developing countries, particularly Africa, are not usually present and have to be developed either from field survey, orthophotography, or topographic maps. We derived a bare-ground binary mask from a land cover map of Niassa Reserve in northern Mozambique. The land cover map was generated from a Landsat Enhanced Thematic Mapper (ETM+) scene and the binary mask was overlaid against the SRTM to derive ground elevations from the SRTM. The resulting point map of elevations was spatially interpolated using thin plate spines with tension to derive a base-level DEM. The DEM was then subtracted from the calibrated SRTM to get tree heights. Secondly we explored the derivation of an independent base elevation DEM using the last return of the NASA Geoscience Laser Altimeter System (GLAS) and compared this to

  15. 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

  16. 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.

  17. Estimating aboveground biomass in Avicennia marina plantation in Indian Sundarbans using high-resolution satellite data

    NASA Astrophysics Data System (ADS)

    Manna, Sudip; Nandy, Subrata; Chanda, Abhra; Akhand, Anirban; Hazra, Sugata; Dadhwal, Vinay Kumar

    2014-01-01

    Mangroves are active carbon sequesters playing a crucial role in coastal ecosystems. In the present study, aboveground biomass (AGB) was estimated in a 5-year-old Avicennia marina plantation (approximate area ≈190 ha) of Indian Sundarbans using high-resolution satellite data in order to assess its carbon sequestration potential. The reflectance values of each band of LISS IV satellite data and the vegetation indices, viz., normalized difference vegetation index (NDVI), optimized soil adjusted vegetation index (OSAVI), and transformed difference vegetation index (TDVI), derived from the satellite data, were correlated with the AGB. OSAVI showed the strongest positive linear relationship with the AGB and hence carbon content of the stand. OSAVI was found to predict the AGB to a great extent (r=0.72) as it is known to nullify the background soil reflectance effect added to vegetation reflectance. The total AGB of the entire plantation was estimated to be 236 metric tons having a carbon stock of 54.9 metric tons, sequestered within a time span of 5 years. Integration of this technique for monitoring and management of young mangrove plantations will give time and cost effective results.

  18. 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.

  19. Estimates of emissions from open biomass burning in Tropical Asia during 2000-2007

    NASA Astrophysics Data System (ADS)

    Chang, D.

    2009-04-01

    Biomass burning in tropical Asia emits large amounts of trace gases and particulate matters to atmosphere, which have significant influence in climate change and atmospheric chemistry. Emissions from open biomass burning in tropical Asia are estimated during seven fire years 2000-2006 (i.e., April 1st 2000-March 31st 2007), using newly released L3JRC burned area product and MODIS burned area product (MCD45A1). Over seven fire years, both burned areas and fire emissions showed clearly spatial and inter-annual variations. The L3JRC burned areas ranged from 31.3×103 km2 for fire year 2005 to 57.5×103 km2 for 2000, while the MODIS burned areas ranged from 64.9×103 km2 for fire year 2002 to 127.0×103 km2 for 2004. We compared the total burned areas and forest burned areas derived from the two separate products with publication data for several typical countries and found that the L3JRC results were comparable to previous studies and the MODIS results showed significant overestimation. The annual average L3JRC-based emissions were 29915, 1948, 90, 30, 12, 105, and 871 Gg yr-1 for CO2, CO, CH4, NOx, BC, OC, and PM2.5 respectively, while MODIS-based emissions were 86740, 5222, 230, 83, 33, 296, and 2188 Gg yr-1, 60.2%-65.5% higher than L3JRC. Forest fires were the largest contributor to fire emissions, though burned area within forest biomes only constituted a minority of total burned area. Fire emissions were mainly concentrated in Myanmar, Cambodia and India. Furthermore, the seasonal distribution of fire emissions was in good agreement with that of total burned areas.

  20. 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

  1. 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

  2. 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

  3. Spatial variation in abundance, size and orientation of juvenile corals related to the biomass of parrotfishes on the Great Barrier Reef, Australia.

    PubMed

    Trapon, Melanie L; Pratchett, Morgan S; Hoey, Andrew S

    2013-01-01

    For species with complex life histories such as scleractinian corals, processes occurring early in life can greatly influence the number of individuals entering the adult population. A plethora of studies have examined settlement patterns of coral larvae, mostly on artificial substrata, and the composition of adult corals across multiple spatial and temporal scales. However, relatively few studies have examined the spatial distribution of small (≤50 mm diameter) sexually immature corals on natural reef substrata. We, therefore, quantified the variation in the abundance, composition and size of juvenile corals (≤50 mm diameter) among 27 sites, nine reefs, and three latitudes spanning over 1000 km on Australia's Great Barrier Reef. Overall, 2801 juveniles were recorded with a mean density of 6.9 (±0.3 SE) ind.m(-2), with Acropora, Pocillopora, and Porites accounting for 84.1% of all juvenile corals surveyed. Size-class structure, orientation on the substrate and taxonomic composition of juvenile corals varied significantly among latitudinal sectors. The abundance of juvenile corals varied both within (6-13 ind.m(-2)) and among reefs (2.8-11.1 ind.m(-2)) but was fairly similar among latitudes (6.1-8.2 ind.m(-2)), despite marked latitudinal variation in larval supply and settlement rates previously found at this scale. Furthermore, the density of juvenile corals was negatively correlated with the biomass of scraping and excavating parrotfishes across all sites, revealing a potentially important role of parrotfishes in determining distribution patterns of juvenile corals on the Great Barrier Reef. While numerous studies have advocated the importance of parrotfishes for clearing space on the substrate to facilitate coral settlement, our results suggest that at high biomass they may have a detrimental effect on juvenile coral assemblages. There is, however, a clear need to directly quantify rates of mortality and growth of juvenile corals to understand the relative

  4. Gas-liquid slug-flow oxygen transport and non-invasive biomass estimation in hollow-fiber reactors

    SciTech Connect

    Smith, W.J.

    1989-01-01

    Maintenance of non-limiting concentrations of dissolved gases at the surface of a particulate biocatalyst is a formidable barrier to the development of ultra-compact bioreactors. The method proposed here for supplying dissolved gases resembles the microcirculation of vertebrates. In the microcirculation, two phases, oxygen-rich hemoglobin-packed erythrocytes and nutrient-rich plasma, pass alternately through the capillaries. In slug-flow membrane bioreactors, two phases, oxygen-rich gas bubbles and slugs of aqueous nutrient medium, flow alternately on one side of a semipermeable membrane while cells grow on the opposite side. Protein synthesis rates were measured for Bacillus licheniformis 749C cultures immobilized in slug-flow hollow-fiber membrane reactors. The cultures required oxygen for growth and protein synthesis. A mathematical model of slug-flow identified the operating conditions corresponding to either continuous or periodic oxygen supply within the reactors. Synthesis rates within the slug-flow reactors were higher than those predicted by the model; the model apparently underestimated concentrations of soluble nutrients in the biomass. Non-invasive estimates of the total immobilized biomass are needed to monitor and control the biomass density, and hence the transport properties of the biomass phase. Investigators have used two non-invasive methods: in situ monitoring of an aggregate property, such as electrical conductivity; and inferential estimates based on substrate consumption and metabolic models. Techniques were developed to estimate immobilized biomass concentrations and growth rates from sulfur mass balances. Additionally, global mass balances showed that time-averaged biomass specific growth rates can be estimated from effluent concentrations of any substrate with a finite yield coefficient.

  5. Zooplankton abundance and biomass size spectra in the East Antarctic sea-ice zone during the winter-spring transition

    NASA Astrophysics Data System (ADS)

    Wallis, Jake R.; Swadling, Kerrie M.; Everett, Jason D.; Suthers, Iain M.; Jones, Hugh J.; Buchanan, Pearse J.; Crawford, Christine M.; James, Lainey C.; Johnson, Robert; Meiners, Klaus M.; Virtue, Patti; Westwood, Karen; Kawaguchi, So

    2016-09-01

    Sea ice is an influential feature in Southern Ocean-Antarctic marine environments creating a 2-phase vertical ecosystem. The lack of information on how this system influences community structure during the winter-spring transition, however, is largely lacking. Zooplankton form the link that bridges these environments, with the meiofaunal and algal communities within sea ice directly influencing the epipelagic zooplankton community at the ice-water interface. A combination of methods including sea-ice coring, umbrella net sampling and Laser Optical Plankton Counter were used to describe the vertical structure of zooplankton and meiofaunal communities. The distribution of meiofauna and chlorophyll a both played important roles in structuring the zooplankton community within this dynamic region. Many dominant taxa, including Calanus propinquus and Oithona similis, directly responded to the high availability of algae present within the bottom strata of sea ice. The sea-ice associated species Stephos longipes represented a strong link between this 2-phase ecosystem. Observations of the vertical distribution of biomass obtained from the LOPC suggests that the responses of these species to the sea ice directly influences the vertical structure of zooplankton during the winter-spring transition.

  6. 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.

  7. Regional forest biomass estimation using ICESat/GLAS spaceborne LiDAR

    NASA Astrophysics Data System (ADS)

    Hayashi, M.; Saigusa, N.; Habura, B.; Sawada, Y.; Yamagata, Y.; Hirano, T.; Ichii, K.

    2015-12-01

    Spaceborne LiDAR can observe vertical structure of forests and provide a means for accurate forest monitoring, therefore, it may meet the growing demand of forest resources monitoring on a large scale. This study aims to clarify the potential of ICESat/GLAS, which had been the only spaceborne LiDAR up to now, for forest resources monitoring on a regional scale. The study areas were three regions: Hokkaido Island in Japan (cool-temperate forest), Borneo Island (tropical forest) and Siberia (boreal forest). Firstly, we conducted field measurements at 106 points in Hokkaido and 37 points in Borneo to measure the average canopy height (Lorey's height) and the above-ground biomass (AGB) for each GLAS-footprint, then, we developed some models to estimate canopy height and AGB from the GLAS waveform parameters. Next, we applied the developed models to the GLAS data which were 14,000 points in Hokkaido, and 130,000 points in Borneo, to estimate canopy height and AGB on a regional scale. As a result, we clarified the forest condition concerning canopy height and AGB for each region, namely, the average value, the comparison between the average of each forest type, and the spatial distribution. Furthermore, we detected the AGB change over the years (forest degradation) and estimated the forest loss rate of 1.6% yr-1 in Borneo. Next, we applied the developed models in Hokkaido to the 1,600,000 points GLAS data observed in Siberia. As a result, we clarified that the average AGB in Siberia was a remarkable low value as compared with those in Hokkaido and Borneo, and that the AGB change over the years (forest degradation) was significant in the southern region of western Siberia. This study showed that spaceborne LiDAR had an ability of forest resources monitoring on a regional scale for various forests over the world.

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. Examination of high resolution rainfall products and satellite greenness indices for estimating patch and landscape forage biomass

    NASA Astrophysics Data System (ADS)

    Angerer, Jay Peter

    Assessment of vegetation productivity on rangelands is needed to assist in timely decision making with regard to management of the livestock enterprise as well as to protect the natural resource. Characterization of the vegetation resource over large landscapes can be time consuming, expensive and almost impossible to do on a near real-time basis. The overarching goal of this study was to examine available technologies for implementing near real-time systems to monitor forage biomass available to livestock on a given landscape. The primary objectives were to examine the ability of the Climate Prediction Center Morphing Product (CMORPH) and Next Generation Weather Radar (NEXRAD) rainfall products to detect and estimate rainfall at semi-arid sites in West Texas, to verify the ability of a simulation model (PHYGROW) to predict herbaceous biomass at selected sites (patches) in a semi-arid landscape using NEXRAD rainfall, and to examine the feasibility of using cokriging for integrating simulation model output and satellite greenness imagery (NDVI) for producing landscape maps of forage biomass in Mongolia's Gobi region. The comparison of the NEXRAD and CMORPH rainfall products to gage collected rainfall revealed that NEXRAD outperformed the CMORPH rainfall with lower estimation bias, lower variability, and higher estimation efficiency. When NEXRAD was used as a driving variable in PHYGROW simulations that were calibrated using gage measured rainfall, model performance for estimating forage biomass was generally poor when compared to biomass measurements at the sites. However, when model simulations were calibrated using NEXRAD rainfall, performance in estimating biomass was substantially better. A suggested reason for the improved performance was that calibration with NEXRAD adjusted the model for the general over or underestimation of rainfall by the NEXRAD product. In the Gobi region of Mongolia, the PHYGROW model performed well in predicting forage biomass except

  13. 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

  14. 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.

  15. Biomass burning losses of carbon estimated from ecosystem modeling and satellite data analysis for the Brazilian Amazon region

    NASA Astrophysics Data System (ADS)

    Potter, Christopher; Brooks Genovese, Vanessa; Klooster, Steven; Bobo, Matthew; Torregrosa, Alicia

    To produce a new daily record of gross carbon emissions from biomass burning events and post-burning decomposition fluxes in the states of the Brazilian Legal Amazon (Instituto Brasileiro de Geografia e Estatistica (IBGE), 1991. Anuario Estatistico do Brasil, Vol. 51. Rio de Janeiro, Brazil pp. 1-1024). We have used vegetation greenness estimates from satellite images as inputs to a terrestrial ecosystem production model. This carbon allocation model generates new estimates of regional aboveground vegetation biomass at 8-km resolution. The modeled biomass product is then combined for the first time with fire pixel counts from the advanced very high-resolution radiometer (AVHRR) to overlay regional burning activities in the Amazon. Results from our analysis indicate that carbon emission estimates from annual region-wide sources of deforestation and biomass burning in the early 1990s are apparently three to five times higher than reported in previous studies for the Brazilian Legal Amazon (Houghton et al., 2000. Nature 403, 301-304; Fearnside, 1997. Climatic Change 35, 321-360), i.e., studies which implied that the Legal Amazon region tends toward a net-zero annual source of terrestrial carbon. In contrast, our analysis implies that the total source fluxes over the entire Legal Amazon region range from 0.2 to 1.2 Pg C yr -1, depending strongly on annual rainfall patterns. The reasons for our higher burning emission estimates are (1) use of combustion fractions typically measured during Amazon forest burning events for computing carbon losses, (2) more detailed geographic distribution of vegetation biomass and daily fire activity for the region, and (3) inclusion of fire effects in extensive areas of the Legal Amazon covered by open woodland, secondary forests, savanna, and pasture vegetation. The total area of rainforest estimated annually to be deforested did not differ substantially among the previous analyses cited and our own.

  16. Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica

    NASA Astrophysics Data System (ADS)

    Dubayah, R. O.; Sheldon, S. L.; Clark, D. B.; Hofton, M. A.; Blair, J. B.; Hurtt, G. C.; Chazdon, R. L.

    2010-06-01

    In this paper we present the results of an experiment to measure forest structure and biomass dynamics over the tropical forests of La Selva Biological Station in Costa Rica using a medium resolution lidar. Our main objective was to observe changes in forest canopy height, related height metrics, and biomass, and from these map sources and sinks of carbon across the landscape. The Laser Vegetation Imaging Sensor (LVIS) measured canopy structure over La Selva in 1998 and again in 2005. Changes in waveform metrics were related to field-derived changes in estimated aboveground biomass from a series of old growth and secondary forest plots. Pairwise comparisons of nearly coincident lidar footprints between years showed canopy top height changes that coincided with expected changes based on land cover types. Old growth forests had a net loss in height of -0.33 m, while secondary forests had net gain of 2.08 m. Multiple linear regression was used to relate lidar metrics with biomass changes for combined old growth and secondary forest plots, giving an r2 of 0.65 and an RSE of 10.5 Mg/ha, but both parametric and bootstrapped confidence intervals were wide, suggesting weaker model performance. The plot level relationships were then used to map biomass changes across La Selva using LVIS at a 1 ha scale. The spatial patterns of biomass changes matched expected patterns given the distribution of land cover types at La Selva, with secondary forests showing a gain of 25 Mg/ha and old growth forests showing little change (2 Mg/ha). Prediction intervals were calculated to assess uncertainty for each 1 ha cell to ascertain whether the data and methods used could confidently estimate the sign (source or sink) of the biomass changes. The resulting map showed most of the old growth areas as neutral (no net biomass change), with widely scattered and isolated sources and sinks. Secondary forests in contrast were mostly sinks or neutral, but were never sources. By quantifying both the

  17. 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}.

  18. 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.

  19. 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

  20. 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.

  1. Estimating forest biomass with GLAS samples and MODIS imagery in Northeastern China

    NASA Astrophysics Data System (ADS)

    Fu, Anmin; Sun, Guoqing; Guo, Zhifeng

    2009-10-01

    The forest ecosystem in Northeastern China (NEC) is approximately 25% proportion of total forested area of China, which has been undergoing dramatic changes due to massive loggings and forest fires in the last several decades and successively intensive manual afforestation and closing protective recovery since 1990s. It is a hot region for scientific research in carbon balance. In this paper, national land cover GIS data, moderate resolution imaging spectroradiometer (MODIS) imagery, and vertical waveform of Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and Land Elevation Satellite (ICESAT) were combined together to map forest aboveground biomass (AGB) in the NEC. Firstly, GLAS waveform has the advantage of three dimensional observations and can play the role as sampling footprints for forest biomes. The estimation algorithm was developed between field survey samples and height profile indices of GLAS waveform to predict forest AGB by neural net regression model. The correlation coefficient R2 between GLAS forest AGB and field-investigated ones was 0.73. Secondly, MODIS data affords spatially continuous images and can be used to stratify forested regions as statistical districts. one hundred of spectral clusters were derived from MODIS phenological curve of enhanced vegetation index (EVI) and near infrared (NIR) channel by K-Means method and stratified for the statistics of GLAS forest AGB samples. The result illustrates spatial pattern forest AGB and explores its total amount in the NEC.

  2. Biomass estimation in a tropical wet forest using Fourier transforms of profiles from lidar or interferometric SAR

    NASA Astrophysics Data System (ADS)

    Treuhaft, R. N.; Gonçalves, F. G.; Drake, J. B.; Chapman, B. D.; dos Santos, J. R.; Dutra, L. V.; Graça, P. M. L. A.; Purcell, G. H.

    2010-12-01

    Tropical forest biomass estimation based on the structure of the canopy is a burgeoning and crucial remote sensing capability for balancing terrestrial carbon budgets. This paper introduces a new approach to structural biomass estimation based on the Fourier transform of vertical profiles from lidar or interferometric SAR (InSAR). Airborne and field data were used from 28 tropical wet forest stands at La Selva Biological Station, Costa Rica, with average biomass of 229 Mg-ha-1. RMS scatters of remote sensing biomass estimates about field measurements were 58.3 Mg-ha-1, 21%, and 76.1 Mg-ha-1, 26%, for lidar and InSAR, respectively. Using mean forest height, the RMS scatter was 97 Mg-ha-1, ≈34% for both lidar and InSAR. The confidence that Fourier transforms are a significant improvement over height was >99% for lidar and ≈90% for InSAR. Lidar Fourier transforms determined the useful range of vertical wavelengths to be 14 m to 100 m.

  3. 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).

  4. 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

  5. Integrating acoustic telemetry into mark-recapture models to improve the precision of apparent survival and abundance estimates.

    PubMed

    Dudgeon, Christine L; Pollock, Kenneth H; Braccini, J Matias; Semmens, Jayson M; Barnett, Adam

    2015-07-01

    Capture-mark-recapture models are useful tools for estimating demographic parameters but often result in low precision when recapture rates are low. Low recapture rates are typical in many study systems including fishing-based studies. Incorporating auxiliary data into the models can improve precision and in some cases enable parameter estimation. Here, we present a novel application of acoustic telemetry for the estimation of apparent survival and abundance within capture-mark-recapture analysis using open population models. Our case study is based on simultaneously collecting longline fishing and acoustic telemetry data for a large mobile apex predator, the broadnose sevengill shark (Notorhynchus cepedianus), at a coastal site in Tasmania, Australia. Cormack-Jolly-Seber models showed that longline data alone had very low recapture rates while acoustic telemetry data for the same time period resulted in at least tenfold higher recapture rates. The apparent survival estimates were similar for the two datasets but the acoustic telemetry data showed much greater precision and enabled apparent survival parameter estimation for one dataset, which was inestimable using fishing data alone. Combined acoustic telemetry and longline data were incorporated into Jolly-Seber models using a Monte Carlo simulation approach. Abundance estimates were comparable to those with longline data only; however, the inclusion of acoustic telemetry data increased precision in the estimates. We conclude that acoustic telemetry is a useful tool for incorporating in capture-mark-recapture studies in the marine environment. Future studies should consider the application of acoustic telemetry within this framework when setting up the study design and sampling program.

  6. 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.

  7. Estimates of biomass burning emissions in tropical Asia based on satellite-derived data

    NASA Astrophysics Data System (ADS)

    Chang, D.; Song, Y.

    2009-09-01

    Biomass burning in tropical Asia emits large amounts of trace gases and particulate matters into the atmosphere, which has significant implications for atmospheric chemistry and climatic change. In this study, emissions from open biomass burning over tropical Asia were evaluated during seven fire years from 2000-2006 (1 April 2000-31 March 2007). Burned areas were estimated from newly published 1-km L3JRC and 500-m MODIS burned area products (MCD45A1). Available fuel loads and emission factors were assigned for each vegetation type in a GlobCover characterisation map, and fuel moisture content was taken into account when calculating combustion factors. Over the whole period, both burned areas and fire emissions clearly showed spatial and seasonal variations. The L3JRC burned areas ranged from 31 165 km2 in fire year 2005 to 57 313 km2 in 2000, while the MCD45A1 burned areas ranged from 54 260 km2 in fire year 2001 to 127 068 km2 in 2004. Comparisons of L3JRC and MCD45A1 burned areas with ground-based measurements and other satellite information were constructed in several major burning regions, and results suggested that MCD45A1 performed better in most areas than L3JRC did although with a certain degree of underestimation of burned forest areas. The average annual L3JRC-based emissions were 125, 12, 0.98, 1.91, 0.11, 0.89, 0.044, 0.022, 0.42, 3.40, and 3.68 Tg yr

  8. 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

  9. [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

  10. Estimating pre-fire biomass for the 2013 California Rim Fire using airborne LiDAR and Landsat data

    NASA Astrophysics Data System (ADS)

    Garcia-Alonso, M.; Casas Planes, Á.; Koltunov, A.; Ustin, S.; Falk, M.; Ramirez, C.

    2014-12-01

    Accurate knowledge of the amount and distribution of fuels is critical for appropriate fire planning and management, but also to improve carbon emissions estimates resulting from both wildland and prescribed fires. Airborne LiDAR (ALS) data has shown great capability to determine the amount of biomass in different ecosystems. Nevertheless, for most incidents a pre-fire LiDAR dataset that would enable the characterization of fuels before the incident is not available. Addressing this problem, we investigated the potential of combining a post-fire ALS dataset and a pre-fire Landsat image to model the pre-fire biomass distribution for the third-largest wildfire in California history, the Rim fire. Very high density (≈ 20 points/m2) ALS data was acquired covering the burned area plus a 2 km buffer. 500+ ALS-plots were located throughout the buffer area using a stratified random sampling scheme, with the strata defined by species group (coniferous, hardwood, and mixed forests) and diametric classes (5-9.9"; 10-19.9"; 20-29.9" and >30"). In these plots, individual tree crowns were delineated by the Watershed algorithm. Crown delineation was visually refined to avoid over- and under-segmentation errors, and the tree biomass was determined based on species-specific allometric equations. The biomass estimates for correctly delineated trees were subsequently aggregated to the plot-level. The next step is to derive a model relating the plot-level biomass to plot-level ALS-derived height and intensity metrics as explanatory variables. This model will be used to map pre-fire biomass in the buffer area outside the burn. To determine pre-fire biomass inside the fire perimeter, where ALS data are not available, we will use a statistical approach based on spectral information provided by a pre-fire Landsat image and its relationships with the 2 km buffer LiDAR-derived biomass estimates. We will validate our results with field measurements collected independently, before the fire.

  11. Estimating stellar atmospheric parameters, absolute magnitudes and elemental abundances from the LAMOST spectra with Kernel-based Principal Component Analysis

    NASA Astrophysics Data System (ADS)

    Xiang, M.-S.; Liu, X.-W.; Shi, J.-R.; Yuan, H.-B.; Huang, Y.; Luo, A.-L.; Zhang, H.-W.; Zhao, Y.-H.; Zhang, J.-N.; Ren, J.-J.; Chen, B.-Q.; Wang, C.; Li, J.; Huo, Z.-Y.; Zhang, W.; Wang, J.-L.; Zhang, Y.; Hou, Y.-H.; Wang, Y.-F.

    2016-10-01

    Accurate determination of stellar atmospheric parameters and elemental abundances is crucial for Galactic archeology via large-scale spectroscopic surveys. In this paper, we estimate stellar atmospheric parameters - effective temperature Teff, surface gravity log g and metallicity [Fe/H], absolute magnitudes MV and MKs, α-element to metal (and iron) abundance ratio [α/M] (and [α/Fe]), as well as carbon and nitrogen abundances [C/H] and [N/H] from the LAMOST spectra with a multivariate regression method based on kernel-based principal component analysis, using stars in common with other surveys (Hipparcos, Kepler, APOGEE) as training data sets. Both internal and external examinations indicate that given a spectral signal-to-noise ratio (SNR) better than 50, our method is capable of delivering stellar parameters with a precision of ˜100 K for Teff, ˜0.1 dex for log g, 0.3 - 0.4 mag for MV and MKs, 0.1 dex for [Fe/H], [C/H] and [N/H], and better than 0.05 dex for [α/M] ([α/Fe]). The results are satisfactory even for a spectral SNR of 20. The work presents first determinations of [C/H] and [N/H] abundances from a vast data set of LAMOST, and, to our knowledge, the first reported implementation of absolute magnitude estimation directly based on the observed spectra. The derived stellar parameters for millions of stars from the LAMOST surveys will be publicly available in the form of value-added catalogues.

  12. \\Space: A new code to estimate \\temp, \\logg, and elemental abundances

    NASA Astrophysics Data System (ADS)

    Boeche, C.

    2016-09-01

    \\Space is a FORTRAN95 code that derives stellar parameters and elemental abundances from stellar spectra. To derive these parameters, \\Space does not measure equivalent widths of lines nor it uses templates of synthetic spectra, but it employs a new method based on a library of General Curve-Of-Growths. To date \\Space works on the wavelength range 5212-6860 Å and 8400-8921 Å, and at the spectral resolution R=2000-20000. Extensions of these limits are possible. \\Space is a highly automated code suitable for application to large spectroscopic surveys. A web front end to this service is publicly available at http://dc.g-vo.org/SP_ACE together with the library and the binary code.

  13. A visual survey technique for deep-water fishes: estimating anglerfish Lophius spp. abundance in closed areas.

    PubMed

    McIntyre, F D; Collie, N; Stewart, M; Scala, L; Fernandes, P G

    2013-10-01

    A visual survey technique was employed to estimate the abundance and distribution of anglerfish Lophius spp. in areas where destructive sampling methods, such as trawling, are unacceptable. To enable visual surveying at depths of over 300 m, a deep towed vehicle was developed equipped with video, lights and other sensors and was towed at speeds of up to 1·5 m s⁻¹ and altitudes of up to 10 m (from the seabed) to survey large areas of the seabed around the Rockall Bank in the north-west Atlantic Ocean. The system allowed for areas up to 125 000 m² to be surveyed, a substantial area comparable to that surveyed by demersal-trawl sampling. Lophius spp. densities ranged from 15 to 736 fish km⁻²; these are comparable to estimated Lophius spp. densities determined by trawl surveys in adjacent areas. Estimates of Lophius spp. abundance in the closed areas ranged between 99,855 and 176,887 for the time series considered (2007-2011). PMID:24090546

  14. 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

  15. 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

  16. Improved Radiometric Capabilities of Landsat 8, Coupled With Lidar, Estimate Semi-arid Rangeland Biomass and Cover

    NASA Astrophysics Data System (ADS)

    Dhakal, S.; Glenn, N. F.; Li, A.; Spaete, L.; Shinneman, D. J.; Arkle, R.; Pilliod, D.; Mcllroy, S.; Baun, C.

    2015-12-01

    Remote sensing based quantification of semi-arid rangeland vegetation provides the large scale observations necessary for monitoring native plants distribution, estimating fuel loads and measuring carbon storage. Improved signal to noise ratio and radiometric resolution of recent satellite imagery and fine scale 3-dimensional information from lidar provides opportunities for refined measurements of vegetation structure. We leverage a large number of Landsat 8 and lidar-based metrics for prediction of biomass and cover of shrubs in the semi-arid rangeland of the western United States. Time-series Landsat 8 images were used to develop 20 ratio based vegetation indices. Similarly, 35 vegetation metrics, including metrics based on numerical values (e.g. elevation, canopy height) and on density of points (e.g. canopy density) were developed from airborne lidar point clouds. These vegetation indices and metrics were trained and linked to insitu measurements (n=141) with the Random Forest regression to impute biomass and cover map across a large scale. We also validate our model with an independent data-set (n=44), explaining up to 63% of variation in cover and 53% in biomass. The preliminary results suggest that Landsat performs better in estimating vegetation cover whereas lidar performs better in estimating biomass with no significant relationship to topographic variables (e.g. slope, aspect and elevation). We further compare our results with historical fire data to show that both biomass and cover decreases with the increase of fire frequency in the study site. This study demonstrates the new opportunities of using Landsat 8 with established lidar approaches to better quantify vegetation in semiarid ecosystems.

  17. Estimates of global biomass burning emissions for reactive greenhouse gases (CO, NMHCs, and NOx) and CO2

    NASA Astrophysics Data System (ADS)

    Jain, Atul K.; Tao, Zhining; Yang, Xiaojuan; Gillespie, Conor

    2006-03-01

    Open fire biomass burning and domestic biofuel burning (e.g., cooking, heating, and charcoal making) algorithms have been incorporated into a terrestrial ecosystem model to estimate CO2 and key reactive GHGs (CO, NOx, and NMHCs) emissions for the year 2000. The emissions are calculated over the globe at a 0.5° × 0.5° spatial resolution using tree density imagery, and two separate sets of data each for global area burned and land clearing for croplands, along with biofuel consumption rate data. The estimated global and annual total dry matter (DM) burned due to open fire biomass burning ranges between 5221 and 7346 Tg DM/yr, whereas the resultant emissions ranges are 6564-9093 Tg CO2/yr, 438-568 Tg CO/yr, 11-16 Tg NOx/yr (as NO), and 29-40 Tg NMHCs/yr. The results indicate that land use changes for cropland is one of the major sources of biomass burning, which amounts to 25-27% (CO2), 25 -28% (CO), 20-23% (NO), and 28-30% (NMHCs) of the total open fire biomass burning emissions of these gases. Estimated DM burned associated with domestic biofuel burning is 3,114 Tg DM/yr, and resultant emissions are 4825 Tg CO2/yr, 243 Tg CO/yr, 3 Tg NOx/yr, and 23 Tg NMHCs/yr. Total emissions from biomass burning are highest in tropical regions (Asia, America, and Africa), where we identify important contributions from primary forest cutting for croplands and domestic biofuel burning.

  18. Seasonal and diel effects on acoustic fish biomass estimates: application to a shallow reservoir with untargeted common carp (Cyprinus carpio)

    USGS Publications Warehouse

    Djemali, Imed; Yule, Daniel; Guillard, Jean

    2016-01-01

    The aim of the present study was to understand how seasonal fish distributions affect acoustically derived fish biomass estimates in a shallow reservoir in a semi-arid country (Tunisia). To that end, sampling events were performed during four seasons (spring (June), summer (September), autumn (December) and winter (March)) that included day and night surveys. A Simrad EK60 echosounder, equipped with two 120-kHz split-beam transducers for simultaneous horizontal and vertical beaming, was used to sample the entire water column. Surveys during spring and summer and daytime hours of winter were deemed unusable owing to high methane flux from the sediment, and during the day survey of autumn, fish were close to the reservoir bottom leading to low detectability. It follows that acoustic surveys should be conducted only at night during the cold season (December–March) for shallow reservoirs having carp Cyprinus carpio (L.) as the dominant species. Further, night-time biomass estimates during the cold season declined significantly (P < 0.001) from autumn to winter. Based on our autumn night-time survey, overall fish biomass in the Bir-Mcherga Reservoir was high (mean (± s.d.) 185 ± 98 tonnes (Mg)), but annual fishery exploitation is low (19.3–24.1 Mg) because the fish biomass is likely dominated by invasive carp not targeted by fishers. The results suggest that controlling carp would help improve the fishery.

  19. Estimating vocal repertoire size is like collecting coupons: a theoretical framework with heterogeneity in signal abundance.

    PubMed

    Kershenbaum, Arik; Freeberg, Todd M; Gammon, David E

    2015-05-21

    Vocal repertoire size is an important behavioural measure in songbirds and mammals with complex vocal communication systems, and has traditionally been used as an indicator of individual fitness, cognitive ability, and social structure. Estimates of asymptotic repertoire size have typically been made using curve fitting techniques. However, the exponential model usually applied in these techniques has never been provided with a theoretical justification based on probability theory, and the model has led to inaccurate estimates. We derived the precise expression for the expected number of distinct signal types observed for a fixed sampling effort: a variation of what is known in the statistical literature as the "Coupon Collector׳s problem". We used empirical data from three species (northern mockingbird, Carolina chickadee, and rock hyrax) to assess the performance of the Coupon Collector model compared to commonly used techniques, such as exponential fitting and repertoire enumeration, and also tested the different models against simulated artificial data sets with the statistical properties of the empirical data. We found that when signal probabilities are dissimilar, the Coupon Collector model provides far more accurate estimates of repertoire size than traditional techniques. Enumeration and exponential curve fitting greatly underestimated repertoire size, despite appearing to have reached saturation. Application of the Coupon Collector model can generate more accurate estimates of repertoire size than the commonly used exponential model of repertoire discovery, and could go a long way towards re-establishing repertoire size as a useful indicator in animal communication research.

  20. 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

  1. 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 gr