296 research outputs found
Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling
Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activity, and deforestation rates to estimate emissions for the Brazilian state of Mato Grosso during 2001â2005. Our model of DEforestation CArbon Fluxes (DECAF) runs at 250-m spatial resolution with a monthly time step to capture spatial and temporal heterogeneity in fire dynamics in our study area within the ''arc of deforestation'', the southern and eastern fringe of the Amazon tropical forest where agricultural expansion is most concentrated. Fire emissions estimates from our modelling framework were on average 90 Tg C year<sup>&minus;1</sup>, mostly stemming from fires associated with deforestation (74%) with smaller contributions from fires from conversions of Cerrado or pastures to cropland (19%) and pasture fires (7%). In terms of carbon dynamics, about 80% of the aboveground living biomass and litter was combusted when forests were converted to pasture, and 89% when converted to cropland because of the highly mechanized nature of the deforestation process in Mato Grosso. The trajectory of land use change from forest to other land uses often takes more than one year, and part of the biomass that was not burned in the dry season following deforestation burned in consecutive years. This led to a partial decoupling of annual deforestation rates and fire emissions, and lowered interannual variability in fire emissions. Interannual variability in the region was somewhat dampened as well because annual emissions from fires following deforestation and from maintenance fires did not covary, although the effect was small due to the minor contribution of maintenance fires. Our results demonstrate how the DECAF model can be used to model deforestation fire emissions at relatively high spatial and temporal resolutions. Detailed model output is suitable for policy applications concerned with annual emissions estimates distributed among post-clearing land uses and science applications in combination with atmospheric emissions modelling to provide constrained global deforestation fire emissions estimates. DECAF currently estimates emissions from fire; future efforts can incorporate other aspects of net carbon emissions from deforestation including soil respiration and regrowth
Doctorsâ recognition and management of melanoma patientsâ risk: an Australian population-based study
Background Guidelines recommend that health professionals identify and manage individuals at high risk of developing melanoma, but there is limited population-based evidence demonstrating real-world practices. Objective A population-based, observational study was conducted in the state of New South Wales, Australia to determine doctorsâ knowledge of melanoma patientsâ risk and to identify factors associated with better identification and clinical management. Methods Data were analysed for 1889 patients with invasive, localised melanoma in the Melanoma Patterns of Care study. This study collected data on all melanoma diagnoses notified to the stateâs cancer registry during a 12-month period from 2006 to 2007, as well as questionnaire data from the doctors involved in their care. Results Three-quarters (74%) of patients had doctors who were aware of their risk factor status with respect to personal and family history of melanoma and the presence of many moles. Doctors working in general practice, skin cancer clinics and dermatology settings had better knowledge of patientsâ risk factors than plastic surgeons. Doctors were 15% more likely to know the family history of younger melanoma patients (<40 years) than of those â„80 years (95% confidence interval 4â26%). Early detection-related follow-up advice was more likely to be given to younger patients, by doctors aware of their patientsâ risk status, by doctors practising in plastic surgery, dermatology and skin cancer clinic settings, and by female doctors. Conclusion Both patient-related and doctor-related factors were associated with doctorsâ recognition and management of melanoma patientsâ risk and could be the focus of strategies for improving care
Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009)
New burned area datasets and top-down constraints from atmospheric
concentration measurements of pyrogenic gases have decreased the large
uncertainty in fire emissions estimates. However, significant gaps remain in
our understanding of the contribution of deforestation, savanna, forest,
agricultural waste, and peat fires to total global fire emissions. Here we
used a revised version of the Carnegie-Ames-Stanford-Approach (CASA)
biogeochemical model and improved satellite-derived estimates of area
burned, fire activity, and plant productivity to calculate fire emissions
for the 1997â2009 period on a 0.5° spatial resolution with a monthly
time step. For November 2000 onwards, estimates were based on burned area,
active fire detections, and plant productivity from the MODerate resolution
Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on
the MODIS era. We used maps of burned area derived from the Tropical Rainfall
Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track
Scanning Radiometer (ATSR) active fire data prior to MODIS (1997â2000) and
estimates of plant productivity derived from Advanced Very High Resolution
Radiometer (AVHRR) observations during the same period. Average global fire
carbon emissions according to this version 3 of the Global Fire Emissions
Database (GFED3) were 2.0 Pg C year<sup>â1</sup> with significant interannual
variability during 1997â2001 (2.8 Pg C year<sup>â1</sup> in 1998 and
1.6 Pg C year<sup>â1</sup> in 2001). Globally, emissions during 2002â2007 were relatively
constant (around 2.1 Pg C year<sup>â1</sup>) before declining in 2008
(1.7 Pg C year<sup>â1</sup>) and 2009 (1.5 Pg C year<sup>â1</sup>) partly due to lower deforestation
fire emissions in South America and tropical Asia. On a regional basis,
emissions were highly variable during 2002â2007 (e.g., boreal Asia, South
America, and Indonesia), but these regional differences canceled out at a
global level. During the MODIS era (2001â2009), most carbon emissions were
from fires in grasslands and savannas (44%) with smaller contributions
from tropical deforestation and degradation fires (20%), woodland fires
(mostly confined to the tropics, 16%), forest fires (mostly in the
extratropics, 15%), agricultural waste burning (3%), and tropical peat
fires (3%). The contribution from agricultural waste fires was likely a
lower bound because our approach for measuring burned area could not detect
all of these relatively small fires. Total carbon emissions were on average
13% lower than in our previous (GFED2) work. For reduced trace gases such
as CO and CH<sub>4</sub>, deforestation, degradation, and peat fires were more
important contributors because of higher emissions of reduced trace gases
per unit carbon combusted compared to savanna fires. Carbon emissions from
tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year<sup>â1</sup>.
The carbon emissions from these fires may not be balanced
by regrowth following fire. Our results provide the first global assessment
of the contribution of different sources to total global fire emissions for
the past decade, and supply the community with an improved 13-year fire
emissions time series
Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept
The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONEâs aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver:
1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators;
2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species;
3. A proposal for a cost-effective biodiversity monitoring system.
There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme.
The issues that we faced were many:
1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset.
2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything.
3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration.
4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output.
EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data.
EBONE in its initial development, focused on three main indicators covering:
(i) the extent and change of habitats of European interest in the context of a general habitat assessment;
(ii) abundance and distribution of selected species (birds, butterflies and plants); and
(iii) fragmentation of natural and semi-natural areas.
For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles:
using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples.
For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved.
Restricted access to European wide species data prevented work on the indicator âabundance and distribution of speciesâ.
With respect to the indicator âfragmentationâ, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations
Geological controls on the geometry of incised-valley fills: Insights from a global dataset of late-Quaternary examples
Incised valleys that develop due to relative sea-level change are common features of continental shelves and coastal plains. Assessment of the factors that control the geometry of incised-valley fills has hitherto largely relied on conceptual, experimental or numerical models, else has been grounded on case studies of individual depositional systems. Here, a database-driven statistical analysis of 151 late-Quaternary incised-valley fills has been performed, the aim being to investigate the geological controls on their geometry.
Results of this analysis have been interpreted with consideration of the role of different processes in determining the geometry of incised-valley fills through their effect on the degree and rate of river incision, and on river size and mobility. The studied incised-valley fills developed along active margins are thicker and wider, on average, than those along passive margins, suggesting that tectonic setting exerts a control on the geometry of incised-valley fills, likely through effects on relative sea-level change and river behaviour, and in relation to distinct characteristics of basin physiography, water discharge and modes of sediment delivery. Valley-fill geometry is positively correlated with the associated drainage-basin size, confirming the dominant role of water discharge. Climate is also inferred to exert a potential control on valley-fill dimensions, possibly through modulations of temperature, peak precipitation, vegetation and permafrost, which would in turn affect water discharge, rates of sediment supply and valley-margin stability. Shelves with slope breaks that are currently deeper than 120 m contain incised-valley fills that are thicker and wider, on average, than those hosted on shelves with breaks shallower than 120 m. No correlation exists between valley-fill thickness and present-day coastal-prism convexity, which is measured as the difference in gradient between lower coastal plains and inner shelves.
These findings challenge some concepts embedded in sequence stratigraphic thinking, and have significant implications for analysis and improved understanding of source-to-sink sediment route-ways, and for attempting predictions of the occurrence and characteristics of hydrocarbon reservoirs
Search for composite and exotic fermions at LEP 2
A search for unstable heavy fermions with the DELPHI detector at LEP is
reported. Sequential and non-canonical leptons, as well as excited leptons and
quarks, are considered. The data analysed correspond to an integrated
luminosity of about 48 pb^{-1} at an e^+e^- centre-of-mass energy of 183 GeV
and about 20 pb^{-1} equally shared between the centre-of-mass energies of 172
GeV and 161 GeV. The search for pair-produced new leptons establishes 95%
confidence level mass limits in the region between 70 GeV/c^2 and 90 GeV/c^2,
depending on the channel. The search for singly produced excited leptons and
quarks establishes upper limits on the ratio of the coupling of the excited
fermio
Search for charginos in e+e- interactions at sqrt(s) = 189 GeV
An update of the searches for charginos and gravitinos is presented, based on
a data sample corresponding to the 158 pb^{-1} recorded by the DELPHI detector
in 1998, at a centre-of-mass energy of 189 GeV. No evidence for a signal was
found. The lower mass limits are 4-5 GeV/c^2 higher than those obtained at a
centre-of-mass energy of 183 GeV. The (\mu,M_2) MSSM domain excluded by
combining the chargino searches with neutralino searches at the Z resonance
implies a limit on the mass of the lightest neutralino which, for a heavy
sneutrino, is constrained to be above 31.0 GeV/c^2 for tan(beta) \geq 1.Comment: 22 pages, 8 figure
Search for lightest neutralino and stau pair production in light gravitino scenarios with stau NLSP
Promptly decaying lightest neutralinos and long-lived staus are searched for
in the context of light gravitino scenarios. It is assumed that the stau is the
next to lightest supersymmetric particle (NLSP) and that the lightest
neutralino is the next to NLSP (NNLSP). Data collected with the Delphi detector
at centre-of-mass energies from 161 to 183 \GeV are analysed. No evidence of
the production of these particles is found. Hence, lower mass limits for both
kinds of particles are set at 95% C.L.. The mass of gaugino-like neutralinos is
found to be greater than 71.5 GeV/c^2. In the search for long-lived stau,
masses less than 70.0 to 77.5 \GeVcc are excluded for gravitino masses from 10
to 150 \eVcc . Combining this search with the searches for stable heavy leptons
and Minimal Supersymmetric Standard Model staus a lower limit of 68.5 \GeVcc
may be set for the stau mas
Hadronization properties of b quarks compared to light quarks in e+e- -> q qbar from 183 to 200 GeV
The DELPHI detector at LEP has collected 54 pb^{-1} of data at a
centre-of-mass energy around 183 GeV during 1997, 158 pb^{-1} around 189 GeV
during 1998, and 187 pb^{-1} between 192 and 200 GeV during 1999. These data
were used to measure the average charged particle multiplicity in e+e- -> b
bbar events, _{bb}, and the difference delta_{bl} between _{bb} and the
multiplicity, _{ll}, in generic light quark (u,d,s) events: delta_{bl}(183
GeV) = 4.55 +/- 1.31 (stat) +/- 0.73 (syst) delta_{bl}(189 GeV) = 4.43 +/- 0.85
(stat) +/- 0.61 (syst) delta_{bl}(200 GeV) = 3.39 +/- 0.89 (stat) +/- 1.01
(syst). This result is consistent with QCD predictions, while it is
inconsistent with calculations assuming that the multiplicity accompanying the
decay of a heavy quark is independent of the mass of the quark itself.Comment: 13 pages, 2 figure
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