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Grid Cells (grid + cell)
Terms modified by Grid Cells Selected AbstractsUsing the extended quarter degree grid cell system to unify mapping and sharing of biodiversity dataAFRICAN JOURNAL OF ECOLOGY, Issue 3 2009R. Larsen Abstract Information on the distribution of animal populations is essential for conservation planning and management. Unfortunately, shared coordinate-level data may have the potential to compromise sensitive species and generalized data are often shared instead to facilitate knowledge discovery and communication regarding species distributions. Sharing of generalized data is, unfortunately, often ad hoc and lacks scalable conventions that permit consistent sharing at larger scales and varying resolutions. One common convention in African applications is the Quarter Degree Grid Cells (QDGC) system. However, the current standard does not support unique references across the Equator and Prime Meridian. We present a method for extending QDGC nomenclature to support unique references at a continental scale for Africa. The extended QDGC provides an instrument for sharing generalized biodiversity data where laws, regulations or other formal considerations prevent or prohibit distribution of coordinate-level information. We recommend how the extended QDGC may be used as a standard, scalable solution for exchange of biodiversity information through development of tools for the conversion and presentation of multi-scale data at a variety of resolutions. In doing so, the extended QDGC represents an important alternative to existing approaches for generalized mapping and can help planners and researchers address conservation issues more efficiently. Résumé L'information sur la distribution des populations animales est essentielle pour la planification de la conservation et la gestion. Malheureusement, les données partagées au niveau des coordonnées risquent de compromettre les espèces sensibles, et les données généralisées sont souvent partagées pour faciliter la découverte et la communication des connaissances concernant la distribution des espèces. Le partage de données généralisées est, malheureusement, souvent opportuniste et manque de conventions mesurables qui permettraient le partage cohérent sur une plus grande échelle et à des résolutions variées. Une convention commune pour des applications africaines est le système de Quarter Degree Grid Cells (QDGC). Cependant, la norme actuelle ne supporte pas l'emploi des références uniques à travers l'Equateur et le premier méridien. Nous présentons une méthode pour étendre la nomenclature QDGC pour soutenir l'adoption de références uniques à l'échelle du continent, en Afrique. Le QDGC étendu fournit un instrument pour partager les données généralisées sur la biodiversité là où les lois, les réglementations et les autres considérations formelles empêchent ou interdisent la distribution de l'information au niveau coordonné. Nous disons dans quelle mesure le QDGC étendu peut être utilisé comme norme, une solution mesurable pour l'échange d'informations sur la biodiversité grâce au développement d'instruments pour la conversion et la présentation de données àéchelle multiple à des résolutions diverses. Ce faisant, le QDGC étendu représente une alternative importante aux approches existantes pour la cartographie généralisée et il peut aider les planificateurs et les chercheurs à traiter les problèmes de conservation plus efficacement. [source] Grid cells: The position code, neural network models of activity, and the problem of learningHIPPOCAMPUS, Issue 12 2008Peter E. Welinder Abstract We review progress on the modeling and theoretical fronts in the quest to unravel the computational properties of the grid cell code and to explain the mechanisms underlying grid cell dynamics. The goals of the review are to outline a coherent framework for understanding the dynamics of grid cells and their representation of space; to critically present and draw contrasts between recurrent network models of grid cells based on continuous attractor dynamics and independent-neuron models based on temporal interference; and to suggest open questions for experiment and theory. © 2008 Wiley-Liss, Inc. [source] First experience of compressible gas dynamics simulation on the Los Alamos roadrunner machineCONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 17 2009Paul R. Woodward Abstract We report initial experience with gas dynamics simulation on the Los Alamos Roadrunner machine. In this initial work, we have restricted our attention to flows in which the flow Mach number is less than 2. This permits us to use a simplified version of the PPM gas dynamics algorithm that has been described in detail by Woodward (2006). We follow a multifluid volume fraction using the PPB moment-conserving advection scheme, enforcing both pressure and temperature equilibrium between two monatomic ideal gases within each grid cell. The resulting gas dynamics code has been extensively restructured for efficient multicore processing and implemented for scalable parallel execution on the Roadrunner system. The code restructuring and parallel implementation are described and performance results are discussed. For a modest grid size, sustained performance of 3.89 Gflops,1 CPU-core,1 is delivered by this code on 36 Cell processors in 9 triblade nodes of a single rack of Roadrunner hardware. Copyright © 2009 John Wiley & Sons, Ltd. [source] A PCA-based modelling technique for predicting environmental suitability for organisms from presence recordsDIVERSITY AND DISTRIBUTIONS, Issue 1-2 2001M. P. Robertson We present a correlative modelling technique that uses locality records (associated with species presence) and a set of predictor variables to produce a statistically justifiable probability response surface for a target species. The probability response surface indicates the suitability of each grid cell in a map for the target species in terms of the suite of predictor variables. The technique constructs a hyperspace for the target species using principal component axes derived from a principal components analysis performed on a training dataset. The training dataset comprises the values of the predictor variables associated with the localities where the species has been recorded as present. The origin of this hyperspace is taken to characterize the centre of the niche of the organism. All the localities (grid-cells) in the map region are then fitted into this hyperspace using the values of the predictor variables at these localities (the prediction dataset). The Euclidean distance from any locality to the origin of the hyperspace gives a measure of the ,centrality' of that locality in the hyperspace. These distances are used to derive probability values for each grid cell in the map region. The modelling technique was applied to bioclimatic data to predict bioclimatic suitability for three alien invasive plant species (Lantana camara L., Ricinus communis L. and Solanum mauritianum Scop.) in South Africa, Lesotho and Swaziland. The models were tested against independent test records by calculating area under the curve (AUC) values of receiver operator characteristic (ROC) curves and kappa statistics. There was good agreement between the models and the independent test records. The pre-processing of climatic variable data to reduce the deleterious effects of multicollinearity, and the use of stopping rules to prevent overfitting of the models are important aspects of the modelling process. [source] Patterns and causes of species richness: a general simulation model for macroecologyECOLOGY LETTERS, Issue 9 2009Nicholas J. Gotelli Abstract Understanding the causes of spatial variation in species richness is a major research focus of biogeography and macroecology. Gridded environmental data and species richness maps have been used in increasingly sophisticated curve-fitting analyses, but these methods have not brought us much closer to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non-linearity. However, curve-fitting approaches are problematic because most theoretical models in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species' geographical ranges in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell of the domain. In contrast to curve-fitting analysis, simulation modelling explicitly incorporates the processes believed to be affecting the geographical ranges of species and generates a number of quantitative predictions that can be compared to empirical patterns. We describe three of the ,control knobs' for a GSM that specify simple rules for dispersal, evolutionary origins and environmental gradients. Binary combinations of different knob settings correspond to eight distinct simulation models, five of which are already represented in the literature of macroecology. The output from such a GSM will include the predicted species richness per grid cell, the range size frequency distribution, the simulated phylogeny and simulated geographical ranges of the component species, all of which can be compared to empirical patterns. Challenges to the development of the GSM include the measurement of goodness of fit (GOF) between observed data and model predictions, as well as the estimation, optimization and interpretation of the model parameters. The simulation approach offers new insights into the origin and maintenance of species richness patterns, and may provide a common framework for investigating the effects of contemporary climate, evolutionary history and geometric constraints on global biodiversity gradients. With further development, the GSM has the potential to provide a conceptual bridge between macroecology and historical biogeography. [source] Surface Heat Balance and Spatially Distributed Ablation Modelling at Koryto Glacier, Kamchatka Peninsula, RussiaGEOGRAFISKA ANNALER SERIES A: PHYSICAL GEOGRAPHY, Issue 4 2004Keiko Konya Abstract To investigate the characteristics of ablation at Koryto Glacier, a mountain glacier under maritime climate in Kamchatka Peninsula, Russia, we made field observations from August to early September 2000. At a site near the equilibrium line, the 31-day average net radiation, sensible heat flux, and latent heat flux were 43, 59 and 31 W,2, respectively. We developed a new distributed ablation model, which only needs measurements of air temperature and global radiation at one site. Hourly ablation rates at this site obtained by the energy balance method are related to measured air temperature and global radiation by linear multiple regression. A different set of multiple regression coefficients is fitted for snow and ice surfaces. Better estimates of ablation rate can be obtained by this approach than by other temperature index models. These equations are then applied to each grid cell of a digital elevation model to estimate spatially distributed hourly melt. Air temperature is extrapolated using a constant temperature lapse rate and global radiation is distributed considering topographic effects. The model enables us to calculate the hourly spatial distribution of ablation rates within the glacier area and could well provide a realistic simulation of ablation over the whole glacier. [source] Quantifying uncertainty in estimates of C emissions from above-ground biomass due to historic land-use change to cropping in AustraliaGLOBAL CHANGE BIOLOGY, Issue 8 2001Damian J. Barrett Abstract Quantifying continental scale carbon emissions from the oxidation of above-ground plant biomass following land-use change (LUC) is made difficult by the lack of information on how much biomass was present prior to vegetation clearing and on the timing and location of historical LUC. The considerable spatial variability of vegetation and the uncertainty of this variability leads to difficulties in predicting biomass C density (tC ha,1) prior to LUC. The issue of quantifying uncertainties in the estimation of land based sources and sinks of CO2, and the feasibility of reducing these uncertainties by further sampling, is critical information required by governments world-wide for public policy development on climate change issues. A quantitative statistical approach is required to calculate confidence intervals (the level of certainty) of estimated cleared above-ground biomass. In this study, a set of high-quality observations of steady state above-ground biomass from relatively undisturbed ecological sites across the Australian continent was combined with vegetation, topographic, climatic and edaphic data sets within a Geographical Information System. A statistical model was developed from the data set of observations to predict potential biomass and the standard error of potential biomass for all 0.05° (approximately 5 × 5 km) land grid cells of the continent. In addition, the spatial autocorrelation of observations and residuals from the statistical model was examined. Finally, total C emissions due to historic LUC to cultivation and cropping were estimated by combining the statistical model with a data set of fractional cropland area per land grid cell, fAc (Ramankutty & Foley 1998). Total C emissions from loss of above-ground biomass due to cropping since European colonization of Australia was estimated to be 757 MtC. These estimates are an upper limit because the predicted steady state biomass may be less than the above-ground biomass immediately prior to LUC because of disturbance. The estimated standard error of total C emissions was calculated from the standard error of predicted biomass, the standard error of fAc and the spatial autocorrelation of biomass. However, quantitative estimates of the standard error of fAc were unavailable. Thus, two scenarios were developed to examine the effect of error in fAc on the error in total C emissions. In the first scenario, in which fAc was regarded as accurate (i.e. a coefficient of variation, CV, of fAc = 0.0), the 95% confidence interval of the continental C emissions was 379,1135 MtC. In the second scenario, a 50% error in estimated cropland area was assumed (a CV of fAc = 0.50) and the estimated confidence interval increased to between 350 and 1294 MtC. The CV of C emissions for these two scenarios was 25% and 29%. Thus, while accurate maps of land-use change contribute to decreasing uncertainty in C emissions from LUC, the major source of this uncertainty arises from the prediction accuracy of biomass C density. It is argued that, even with large sample numbers, the high cost of sampling biomass carbon may limit the uncertainty of above-ground biomass to about a CV of 25%. [source] A new metric for evaluating the correspondence of spatial patterns in vegetation modelsGLOBAL ECOLOGY, Issue 4 2008Guoping Tang ABSTRACT Aim, To present a new metric, the ,opposite and identity' (OI) index, for evaluating the correspondence between two sets of simulated time-series dynamics of an ecological variable. Innovation, The OI index is introduced and its mathematical expression is defined using vectors to denote simulated variations of an ecological variable on the basis of the vector addition rule. The value of the OI index varies from 0 to 1 with a value 0 (or 1) indicating that compared simulations are opposite (or identical). An OI index with a value near 0.5 suggests that the difference in the amplitudes of variations between compared simulations is large. The OI index can be calculated in a grid cell, for a given biome and for time-series simulations. The OI indices calculated in each grid cell can be used to map the spatial agreement between compared simulations, allowing researchers to pinpoint the extent of agreement or disagreement between two simulations. The OI indices calculated for time-series simulations allow researchers to identify the time at which one simulation differs from another. A case study demonstrates the application and reliability of the OI index for comparing two simulated time-series dynamics of terrestrial net primary productivity in Asia from 1982 to 2000. In the case study, the OI index performs better than the correlation coefficient at accurately quantifying the agreement between two simulated time-series dynamics of terrestrial net primary productivity in Asia. Main conclusions, The OI index provides researchers with a useful tool and multiple flexible ways to compare two simulation results or to evaluate simulation results against observed spatiotemporal data. The OI index can, in some cases, quantify the agreement between compared spatiotemporal data more accurately than the correlation coefficient because of its insensitivity to influential data and outliers and the autocorrelation of simulated spatiotemporal data. [source] Environmental novelty is signaled by reduction of the hippocampal theta frequencyHIPPOCAMPUS, Issue 4 2008A. Jeewajee Abstract The hippocampal formation (HF) plays a key role in novelty detection, but the mechanisms remain unknown. Novelty detection aids the encoding of new information into memory,a process thought to depend on the HF and to be modulated by the theta rhythm of EEG. We examined EEG recorded in the HF of rats foraging for food within a novel environment, as it became familiar over the next five days, and in two more novel environments unexpectedly experienced in trials interspersed with familiar trials over three further days. We found that environmental novelty produces a sharp reduction in the theta frequency of foraging rats, that this reduction is greater for an unexpected environment than for a completely novel one, and that it slowly disappears with increasing familiarity. These results do not reflect changes in running speed and suggest that the septo-hippocampal system signals unexpected environmental change via a reduction in theta frequency. In addition, they provide evidence in support of a cholinergically mediated mechanism for novelty detection, have important implications for our understanding of oscillatory coding within memory and for the interpretation of event-related potentials, and provide indirect support for the oscillatory interference model of grid cell firing in medial entorhinal cortex. © 2007 Wiley-Liss, Inc. [source] An oscillatory interference model of grid cell firingHIPPOCAMPUS, Issue 9 2007Neil Burgess Abstract We expand upon our proposal that the oscillatory interference mechanism proposed for the phase precession effect in place cells underlies the grid-like firing pattern of dorsomedial entorhinal grid cells (O'Keefe and Burgess (2005) Hippocampus 15:853,866). The original one-dimensional interference model is generalized to an appropriate two-dimensional mechanism. Specifically, dendritic subunits of layer II medial entorhinal stellate cells provide multiple linear interference patterns along different directions, with their product determining the firing of the cell. Connection of appropriate speed- and direction- dependent inputs onto dendritic subunits could result from an unsupervised learning rule which maximizes postsynaptic firing (e.g. competitive learning). These inputs cause the intrinsic oscillation of subunit membrane potential to increase above theta frequency by an amount proportional to the animal's speed of running in the "preferred" direction. The phase difference between this oscillation and a somatic input at theta-frequency essentially integrates velocity so that the interference of the two oscillations reflects distance traveled in the preferred direction. The overall grid pattern is maintained in environmental location by phase reset of the grid cell by place cells receiving sensory input from the environment, and environmental boundaries in particular. We also outline possible variations on the basic model, including the generation of grid-like firing via the interaction of multiple cells rather than via multiple dendritic subunits. Predictions of the interference model are given for the frequency composition of EEG power spectra and temporal autocorrelograms of grid cell firing as functions of the speed and direction of running and the novelty of the environment. © 2007 Wiley-Liss, Inc. [source] A drought climatology for EuropeINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 13 2002Benjamin Lloyd-Hughes Abstract We present a high spatial resolution, multi-temporal climatology for the incidence of 20th century European drought. The climatology provides, for a given location or region, the time series of drought strength, the number, the mean duration, and the maximum duration of droughts of a given intensity, and the trend in drought incidence. The drought climatology is based on monthly standardized precipitation indices (SPIs) calculated on a 0.5° grid over the European region 35,70 °N and 35 °E,10 °W at time scales of 3, 6, 9, 12, 18, and 24 months for the period 1901,99. The standardized property facilitates the quantitative comparison of drought incidence at different locations and over different time scales. The standardization procedure (probability transformation) has been tested rigorously assuming normal, log,normal, and gamma statistics for precipitation. Near equivalence is demonstrated between the Palmer drought severity index (PDSI) and SPIs on time scales of 9 to 12 months. The mean number and duration by grid cell of extreme European drought events (SPI , ,2) on a time scale of 12 months is 6 ± 2 months and 27 ± 8 months respectively. The mean maximum drought duration is 48 ± 17 months. Trends in SPI and PDSI values indicate that the proportion of Europe experiencing extreme and/or moderate drought conditions has changed insignificantly during the 20th century. We hope the climatology will provide a useful resource for assessing both the regional vulnerability to drought and the seasonal predictability of the phenomenon. Copyright © 2002 Royal Meteorological Society. [source] Using habitat distribution models to evaluate large-scale landscape priorities for spatially dynamic speciesJOURNAL OF APPLIED ECOLOGY, Issue 1 2008Regan Early Summary 1Large-scale conservation planning requires the identification of priority areas in which species have a high likelihood of long-term persistence. This typically requires high spatial resolution data on species and their habitat. Such data are rarely available at a large geographical scale, so distribution modelling is often required to identify the locations of priority areas. However, distribution modelling may be difficult when a species is either not recorded, or not present, at many of the locations that are actually suitable for it. This is an inherent problem for species that exhibit metapopulation dynamics. 2Rather than basing species distribution models on species locations, we investigated the consequences of predicting the distribution of suitable habitat, and thus inferring species presence/absence. We used habitat surveys to define a vegetation category which is suitable for a threatened species that has spatially dynamic populations (the butterfly Euphydryas aurinia), and used this as the response variable in distribution models. Thus, we developed a practical strategy to obtain high resolution (1 ha) large scale conservation solutions for E. aurinia in Wales, UK. 3Habitat-based distribution models had high discriminatory power. They could generalize over a large spatial extent and on average predicted 86% of the current distribution of E. aurinia in Wales. Models based on species locations had lower discriminatory power and were poorer at generalizing throughout Wales. 4Surfaces depicting the connectivity of each grid cell were calculated for the predicted distribution of E. aurinia habitat. Connectivity surfaces provided a distance-weighted measure of the concentration of habitat in the surrounding landscape, and helped identify areas where the persistence of E. aurinia populations is expected to be highest. These identified successfully known areas of high conservation priority for E. aurinia. These connectivity surfaces allow conservation planning to take into account long-term spatial population dynamics, which would be impossible without being able to predict the species' distribution over a large spatial extent. 5Synthesis and applications. Where species location data are unsuitable for building high resolution predictive habitat distribution models, habitat data of sufficient quality can be easier to collect. We show that they can perform as well as or better than species data as a response variable. When coupled with a technique to translate distribution model predictions into landscape priority (such as connectivity calculations), we believe this approach will be a powerful tool for large-scale conservation planning. [source] Predicting habitat distribution and frequency from plant species co-occurrence dataJOURNAL OF BIOGEOGRAPHY, Issue 6 2007Christine Römermann Abstract Aim, Species frequency data have been widely used in nature conservation to aid management decisions. To determine species frequencies, information on habitat occurrence is important: a species with a low frequency is not necessarily rare if it occupies all suitable habitats. Often, information on habitat distribution is available for small geographic areas only. We aim to predict grid-based habitat occurrence from grid-based plant species distribution data in a meso-scale analysis. Location, The study was carried out over two spatial extents: Germany and Bavaria. Methods, Two simple models were set up to examine the number of characteristic plant species needed per grid cell to predict the occurrence of four selected habitats (species data from FlorKart, http://www.floraweb.de). Both models were calibrated in Bavaria using available information on habitat distribution, validated for other federal states, and applied to Germany. First, a spatially explicit regression model (generalized linear model (GLM) with assumed binomial error distribution of response variable) was obtained. Second, a spatially independent optimization model was derived that estimated species numbers without using spatial information on habitat distribution. Finally, an additional uncalibrated model was derived that calculated the frequencies of 24 habitats. It was validated using NATURA2000 habitat maps. Results, Using the Bavarian models it was possible to predict habitat distribution and frequency from the co-occurrence of habitat-specific species per grid cell. As the model validations for other German federal states were successful, the models were applied to all of Germany, and habitat distribution and frequencies could be retrieved for the national scale on the basis of habitat-specific species co-occurrences per grid cell. Using the third, uncalibrated model, which includes species distribution data only, it was possible to predict the frequencies of 24 habitats based on the co-occurrence of 24% of formation-specific species per grid cell. Predicted habitat frequencies deduced from this third model were strongly related to frequencies of NATURA2000 habitat maps. Main conclusions, It was concluded that it is possible to deduce habitat distributions and frequencies from the co-occurrence of habitat-specific species. For areas partly covered by habitat mappings, calibrated models can be developed and extrapolated to larger areas. If information on habitat distribution is completely lacking, uncalibrated models can still be applied, providing coarse information on habitat frequencies. Predicted habitat distributions and frequencies can be used as a tool in nature conservation, for example as correction factors for species frequencies, as long as the species of interest is not included in the model set-up. [source] The tripartite biogeographical index: a new tool for quantifying spatio-temporal differences in distribution patternsJOURNAL OF BIOGEOGRAPHY, Issue 4 2006Tom Schils Abstract Aims, First, to develop an index that quantifies biogeographical patterns based on the basic descriptors of presence/absence distribution patterns (F, frequency; C, connectivity; G, grouping). Second, to test the proposed biogeographical index on a data set of macrophyte communities in the Arabian Sea using distribution data of macro-algae and seagrasses throughout the Indian Ocean. Location, Arabian Sea (regional macrophyte community data) and the larger Indian Ocean (oceanic distribution data). Methods, The proposed index is derived from the Tulloss tripartite similarity index. The tripartite biogeographical index (TBI = ,F × C × G) is calculated for a specific taxon and incorporates several fundamental parameters of presence/absence data in grid cell (block) patterns. TBI accounts for the relative abundance of a taxon, the average grouping of its occurrences, the average of minimal absence intervals between taxon presences and the largest coherent cluster of taxon occurrences, and also incorporates dispersal aspects. The macrophytes from the case study are among the best documented marine organisms in the Indian Ocean. The regional distribution data from the Arabian Sea result from exhaustive species lists from Masirah Island (Oman) and the Socotra Archipelago (Yemen). Results, TBI values fit a linear scale corresponding to the proportional presence and the distributional spread of taxa within a given geographical area. The three functions that constitute TBI can be evaluated separately or in association with TBI, to give detailed information on the important factors that characterize the biogeographical distribution of a taxon (or larger entities consisting of multiple taxa such as communities). The case study on Arabian macrophytes clarifies the use and explanatory power of the index. Main conclusions, The biogeographical descriptors can be combined into an index which accurately quantifies taxon occurrences and distribution types on a single linear scale from rare/scattered to abundant/grouped. Together with its three functions, the index allows for a non-arbitrary selection of taxa and taxon groupings based on their distribution pattern. The analysis of TBI values for the Arabian macrophyte communities confirms previous biogeographical findings and enables more detailed statistical analyses of the distribution data. [source] Global Daily Reference Evapotranspiration Modeling and Evaluation,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 4 2008G.B. Senay Abstract:, Accurate and reliable evapotranspiration (ET) datasets are crucial in regional water and energy balance studies. Due to the complex instrumentation requirements, actual ET values are generally estimated from reference ET values by adjustment factors using coefficients for water stress and vegetation conditions, commonly referred to as crop coefficients. Until recently, the modeling of reference ET has been solely based on important weather variables collected from weather stations that are generally located in selected agro-climatic locations. Since 2001, the National Oceanic and Atmospheric Administration's Global Data Assimilation System (GDAS) has been producing six-hourly climate parameter datasets that are used to calculate daily reference ET for the whole globe at 1-degree spatial resolution. The U.S. Geological Survey Center for Earth Resources Observation and Science has been producing daily reference ET (ETo) since 2001, and it has been used on a variety of operational hydrological models for drought and streamflow monitoring all over the world. With the increasing availability of local station-based reference ET estimates, we evaluated the GDAS-based reference ET estimates using data from the California Irrigation Management Information System (CIMIS). Daily CIMIS reference ET estimates from 85 stations were compared with GDAS-based reference ET at different spatial and temporal scales using five-year daily data from 2002 through 2006. Despite the large difference in spatial scale (point vs. ,100 km grid cell) between the two datasets, the correlations between station-based ET and GDAS-ET were very high, exceeding 0.97 on a daily basis to more than 0.99 on time scales of more than 10 days. Both the temporal and spatial correspondences in trend/pattern and magnitudes between the two datasets were satisfactory, suggesting the reliability of using GDAS parameter-based reference ET for regional water and energy balance studies in many parts of the world. While the study revealed the potential of GDAS ETo for large-scale hydrological applications, site-specific use of GDAS ETo in complex hydro-climatic regions such as coastal areas and rugged terrain may require the application of bias correction and/or disaggregation of the GDAS ETo using downscaling techniques. [source] Modelling species diversity through species level hierarchical modellingJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 1 2005Alan E. Gelfand Summary., Understanding spatial patterns of species diversity and the distributions of individ-ual species is a consuming problem in biogeography and conservation. The Cape floristic region of South Africa is a global hot spot of diversity and endemism, and the Protea atlas project, with about 60 000 site records across the region, provides an extraordinarily rich data set to model patterns of biodiversity. Model development is focused spatially at the scale of 1, grid cells (about 37 000 cells total for the region). We report on results for 23 species of a flowering plant family known as Proteaceae (of about 330 in the Cape floristic region) for a defined subregion. Using a Bayesian framework, we developed a two-stage, spatially explicit, hierarchical logistic regression. Stage 1 models the potential probability of presence or absence for each species at each cell, given species attributes, grid cell (site level) environmental data with species level coefficients, and a spatial random effect. The second level of the hierarchy models the probability of observing each species in each cell given that it is present. Because the atlas data are not evenly distributed across the landscape, grid cells contain variable numbers of sampling localities. Thus this model takes the sampling intensity at each site into account by assuming that the total number of times that a particular species was observed within a site follows a binomial distribution. After assigning prior distributions to all quantities in the model, samples from the posterior distribution were obtained via Markov chain Monte Carlo methods. Results are mapped as the model-estimated probability of presence for each species across the domain. This provides an alternative to customary empirical ,range-of-occupancy' displays. Summing yields the predicted richness of species over the region. Summaries of the posterior for each environmental coefficient show which variables are most important in explaining the presence of species. Our initial results describe biogeographical patterns over the modelled region remarkably well. In particular, species local population size and mode of dispersal contribute significantly to predicting patterns, along with annual precipitation, the coefficient of variation in rainfall and elevation. [source] A buoyancy-based mixing-length proposal for cloudy boundary layersTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 604 2004E. Sáanchez Abstract The parametrization of boundary-layer clouds is approached here using a turbulence,kinetic energy closure, in conservative variables for non-precipitating processes and through a new proposal for the turbulence mixing length. A subgrid condensation scheme able to treat partially saturated conditions in a model grid cell is also necessary. An extension of the buoyancy-based Bougeault,Lacarrère mixing length is proposed, to take into account moist processes, and specifically the effects of phase changes. The asymmetry between upward and downward mixing processes is also considered for partial cloudiness conditions. The new proposal is tested for stratocumulus-capped marine boundary layers and for shallow cumulus convection, both over land and sea. The validation ismade against large-eddy simulation results obtained from model intercomparison cases, for stationary regimes as a first step, and then for the diurnal evolution of marine stratocumulus and shallow convection over land. Copyright © 2004 Royal Meteorological Society [source] The parametrization of drag induced by stratified flow over anisotropic orographyTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 568 2000J. F. Scinocca Abstract A new parametrization of drag arising from the flow over unresolved topography (UT) in a general-circulation model (GCM) is presented. It is comprised of three principle components: a parametrization of the source spectrum and drag associated with freely propagating hydrostatic gravity waves in the absence of rotation, a parametrization of the drag associated with low-level wave breaking, and a parametrization of low-level drag associated with upstream blocking and lee-vortex dynamics. Novel features of the scheme include: a new procedure for defining the UT in each GCM grid cell which takes account of the GCM resolution and includes only the scales represented by the parametrization scheme, a new method of representing the azimuthal distribution of vertical momentum flux by two waves whose direction and magnitude systematically vary with the flow direction and with the anisotropy of the UT in each GCM grid cell, and a new application of form drag in the lowest levels which can change the direction of the low-level flow so that it is more parallel to unresolved two-dimensional topographic ridges. The new scheme is tested in the Canadian Centre for Climate Modelling and Analysis third generation atmospheric GCM at horizontal resolutions of T47 and T63. Five-year seasonal means of present-day climate show that the new scheme improves mean sea level pressures (or mass distribution) and improves the tropospheric circulation when compared with the gravity-wave drag scheme used currently in the GCM. The benefits are most pronounced during northern hemisphere winter. It is also found that representing the azimuthal distribution of the momentum flux of the freely propagating gravity-wave field with two waves rather than just one allows 30-50% more gravity-wave momentum flux up into the middle atmosphere, depending on the season. The additional momentum flux into the middle atmosphere is expected to have a beneficial impact on GCMs that employ a more realistic representation of the stratosphere. [source] Performance of Sub-Saharan Vertebrates as Indicator Groups for Identifying Priority Areas for ConservationCONSERVATION BIOLOGY, Issue 1 2003Joslin L. Moore Often, these sets of important areas, referred to as priority sets, have been identified through use of data on a single taxon (e.g., birds), which is assumed to act as an indicator for all biodiversity. Using a database of the distributions of 3882 vertebrate species in sub-Saharan Africa, we conducted one of very few large-scale tests of this assumption. We used six potential indicator groups,birds, mammals, amphibians, snakes, threatened birds, and threatened mammals,to find priority sets of 200 areas that best represent the species in that group. Priority sets of grid cells designed to maximize representation of a single indicator group captured 83,93% of species in the other groups. This high degree of representation is consistent with observed high levels of overlap in the patterns of distribution of species in different groups. Those species of highest conservation interest were more poorly represented, however, with only 75,88% of other groups' threatened species and 63,76% of other groups' narrow-range species represented in the priority sets. We conclude that existing priority sets based on indicator groups provide a pragmatic basis for the immediate assessment of priorities for conservation at a continental scale. However, complete and efficient representation,especially of narrow-range species,will not be achieved through indicator groups alone. Therefore, priority-setting procedures must remain flexible so that new areas important for other taxa can be incorporated as data become available. Resumen: La meta de la identificación de prioridades globales y continentales de conservación es la identificación de áreas particularmente valiosas para la conservación en las cuales enfocar esfuerzos más detallados. A menudo, estos conjuntos de áreas importantes (referidas como conjuntos prioritarios) han sido identificados utilizando datos de un solo taxón (e. g. aves), el cual se supone que actúa como indicador de toda la biodiversidad. Utilizando una base de datos de la distribución de 3882 especies de vertebrados en África sub-Sahara, realizamos una de las pocas pruebas a gran escala de este supuesto. Utilizamos seis grupos de indicadores potenciales (aves, mamíferos, anfibios, serpientes, aves amenazadas y mamíferos amenazados ) para encontrar conjuntos prioritarios de 200 áreas que mejor representan las especies de ese grupo. Conjuntos prioritarios de celdas matriciales diseñadas para maximizar la representatividad de un grupo indicador capturaron 83,93% de las especies de los otros grupos. Este alto grado de representatividad es consistente con los altos niveles de superposición observados en los patrones de distribución de especies en los diferentes grupos. Sin embargo, las especies de mayor interés para la conservación estaban poco representadas, con solo 75,88% de las especies amenazadas de otros grupos y 63,76% de las especies de distribución restringida de otros grupos representados en los conjuntos prioritarios. Concluimos que los conjuntos prioritarios existentes, basados en grupos indicadores, proporcionan una base pragmática para la evaluación inmediata de las prioridades de conservación a escala continental. Sin embargo, no se logrará la representación completa y eficiente,especialmente de especies de distribución restringida,solo con grupos indicadores. Por lo tanto, los procedimientos de definición de prioridades deben permanecer flexibles para que se puedan incorporar nuevas áreas importantes para otros taxones a medida que se obtienen los datos. [source] Integrating species life-history traits and patterns of deforestation in amphibian conservation planningDIVERSITY AND DISTRIBUTIONS, Issue 1 2010C. G. Becker Abstract Aim, To identify priority areas for amphibian conservation in southeastern Brazil, by integrating species life-history traits and patterns of deforestation. Location, State of São Paulo, Brazil. Methods, We used the software Marxan to evaluate different scenarios of amphibian conservation planning. Our approach differs from previous methods by explicitly including two different landscape metrics; habitat split for species with aquatic larvae, and habitat loss for species with terrestrial development. We evaluated the effect of habitat requirements by classifying species breeding habitats in five categories (flowing water, still water permanent, still water temporary, bromeliad or bamboo, and terrestrial). We performed analyses using two scales, grid cells and watersheds and also considered nature preserves as protected areas. Results, We found contrasting patterns of deforestation between coastal and inland regions. Seventy-six grid cells and 14 watersheds are capable of representing each species at least once. When accounting for grid cells already protected in state and national parks and considering species habitat requirements we found 16 high-priority grid cells for species with one or two reproductive habitats, and only one cell representing species with four habitat requirements. Key areas for the conservation of species breeding in flowing and permanent still waters are concentrated in southern state, while those for amphibians breeding in temporary ponds are concentrated in central to eastern zones. Eastern highland zones are key areas for preserving species breeding terrestrially by direct or indirect development. Species breeding in bromeliads and bamboos are already well represented in protected areas. Main conclusions, Our results emphasize the need to integrate information on landscape configuration and species life-history traits to produce more ecologically relevant conservation strategies. [source] Predicting global abundance of a threatened species from its occurrence: implications for conservation planningDIVERSITY AND DISTRIBUTIONS, Issue 1 2009Marcos S. L. Figueiredo Abstract Aim, Global abundance is an important characteristic of a species that is correlated with geographical distribution and body size. Despite its importance these estimates are not available since reliable field estimates are either expensive or difficult to obtain. Based on the relationship between a species' local abundance and distribution, some authors propose that abundance can be obtained through spatial distribution data from maps plotted at different scales. This has never been tested over the entire geographical range of a species. Thus, the aim of this study was to estimate global abundance of the Neotropical primate Brachyteles hypoxanthus (northern muriqui) and compare the results with available field estimates. Location, From southern Bahia to Minas Gerais and Espírito Santo states, in the Brazilian Atlantic rain forest. Methods, We compiled 25 recent occurrence localities of B. hypoxanthus and plotted them in grid cells of five different sizes (1, 25, 50, 75 and 100 km per side) to evaluate the performance and accuracy of abundance estimates over a wide range of scales. The abundance estimates were obtained by the negative binomial distribution (NBD) method and corrected by average group size to take into account primate social habits. To assess the accuracy of the method, the predicted abundances were then compared to recent independent field estimates. Results, The NBD estimates were quite accurate in predicting B. hypoxanthus global abundance, once the gregarious habits of this species are taken into account. The predicted abundance estimates were not statistically different from those obtained from field estimates. Main conclusions, The NBD method seems to be a quick and reliable approach to estimate species abundance once several limiting factors are taken into account, and can greatly impact conservation planning, but further applications in macroecological and ecological theory testing needs improvement of the method. [source] Potential impacts of climate change on Sub-Saharan African plant priority area selectionDIVERSITY AND DISTRIBUTIONS, Issue 6 2006Colin J. McClean ABSTRACT The Global Strategy for Plant Conservation (GSPC) aims to protect 50% of the most important areas for plant diversity by 2010. This study selects sets of 1-degree grid cells for 37 sub-Saharan African countries on the basis of a large database of plant species distributions. We use two reserve selection algorithms that attempt to satisfy two of the criteria set by the GSPC. The grid cells selected as important plant cells (IPCs) are compared between algorithms and in terms of country and continental rankings between cells. The conservation value of the selected grid cells are then considered in relation to their future species complement given the predicted climate change in three future periods (2025, 2055, and 2085). This analysis uses predicted climate suitability for individual species from a previous modelling exercise. We find that a country-by-country conservation approach is suitable for capturing most, but not all, continentally IPCs. The complementarity-based reserve selection algorithms suggest conservation of a similar set of grid cells, suggesting that areas of high plant diversity and rarity may be well protected by a single pattern of conservation activity. Although climatic conditions are predicted to deteriorate for many species under predicted climate change, the cells selected by the algorithms are less affected by climate change predictions than non-selected cells. For the plant species that maintain areas of climatic suitability in the future, the selected set will include cells with climate that is highly suitable for the species in the future. The selected cells are also predicted to conserve a large proportion of the species richness remaining across the continent under climate change, despite the network of cells being less optimal in terms of future predicted distributions. Limitations to the modelling are discussed in relation to the policy implications for those implementing the GSPC. [source] Present and potential distribution of invasive garlic mustard (Alliaria petiolata) in North AmericaDIVERSITY AND DISTRIBUTIONS, Issue 4 2002Erik Welk Abstract. This paper demonstrates the use of a bioclimatic model mapped over geographical regions as a tool for spatially refined risk assessment for the establishment of non-indigenous plants with invasive behaviour. Drawing on the relationship between plant distribution and climate, the approach uses gridded spatial interpolated monthly means of temperature and precipitation linked with accurate maps of general native distribution ranges to predict the long-term potential of a plant species to invade a certain region. The ascertained potential for establishment is illustrated by the example of garlic mustard (Alliaria petiolata[M. Bieb.] Cavara & Grande) in North America. The first step is to calculate and visualize the number of populated grid cells along climatic gradients in frequency diagrams for the general native distribution range. Interpretations of the response curves recorded are used for assessing apparent climatic range boundaries. Modelling was gradually optimized based on the results of experience-based interpretations and by examining omission and over-representation errors. The obtained climatic model of the range of A. petiolata shows considerable congruencies with its mapped, native Eurasian range. Degrees of climatic similarity between North America and the native range of A. petiolata were calculated with the help of GIS methodology and were used to assess the regionally different likelihood of establishment in North America of the invasive species under consideration. [source] Dynamic distribution modelling: predicting the present from the pastECOGRAPHY, Issue 1 2009Stephen G. Willis Confidence in projections of the future distributions of species requires demonstration that recently-observed changes could have been predicted adequately. Here we use a dynamic model framework to demonstrate that recently-observed changes at the expanding northern boundaries of three British butterfly species can be predicted with good accuracy. Previous work established that the distributions of the study species currently lag behind climate change, and so we presumed that climate is not currently a major constraint at the northern range margins of our study species. We predicted 1970,2000 distribution changes using a colonisation model, MIGRATE, superimposed on a high-resolution map of habitat availability. Thirty-year rates and patterns of distribution change could be accurately predicted for each species (, goodness-of-fit of models >0.64 for all three species, corresponding to >83% of grid cells correctly assigned), using a combination of individual species traits, species-specific habitat associations and distance-dependent dispersal. Sensitivity analyses showed that population productivity was the most important determinant of the rate of distribution expansion (variation in dispersal rate was not studied because the species are thought to be similar in dispersal capacity), and that each species' distribution prior to expansion was critical in determining the spatial pattern of the current distribution. In future, modelling approaches that combine climate suitability and spatially-explicit population models, incorporating demographic variables and habitat availability, are likely to be valuable tools in projecting species' responses to climatic change and hence in anticipating management to facilitate species' dispersal and persistence. [source] Topographic spatial characterisation of grey seal Halichoerus grypus breeding habitat at a sub-seal size spatial grainECOGRAPHY, Issue 3 2001S. D. Twiss Expansion within breeding colonies may critically depend upon the availability of suitable breeding habitat. Here we use topographic modelling in a GIS to characterise suitable pupping habitat and accurately predict the pattern of colonisation in an expanding grey seal breeding colony-the Isle of May (Scotland), We use high resolution images from large format aerial photographs of the colony to generate sub-metre accurate Digital Terrain Models (DTMs), GIS modelling with these DTMs provides topographic measures of elevation, slope and ease of access to sea and freshwater pools at a 2 m grid cell size. Seal locations during the 1994 breeding season, with sex-age class, were also digitised from the same images. We examine how the physical attributes of cells (locations) with and without pups differ and identify areas suitable for pupping but remaining unoccupied during 1994. We predict patterns of future colonisation by characterising areas differentiated by the densities of pups within 5 m grid cells and identifying areas, both occupied or unoccupied, with a potential for increased future pupping densities. Our predictions were tested by examining pup distributions observed in the 1998 breeding season. Occupied sites were significantly closer to freshwater pools and access to the sea (p < 0.001) than unoccupied sites suggesting that proximity to water may restrict colony expansion before all areas of suitably flat terrain are occupied. All pup density classes occurred in sites with similar slope values and distance to pools. However, higher pupping densities occurred closer to access points (p = 0.014). Pup densities observed in 1998 revealed that our 1994 predictions were accurate (p < 0.0001). Only 12% of 466 grid cells had higher densities in 1998 than predicted, of which 88% differed by only 1 pup. These incorrectly classified cells occurred at the expanding edge of the colony (in a more topographically homogenous area) and at the main access points from the sea (major traffic zones). These results demonstrate the value of the accurate quantification of topographic parameters at the appropriate spatial grain (in this case below the size of the individual) for use in habitat classification and predictions of habitat utilization. [source] Inventory of shipping emissions in Izmit Gulf, TurkeyENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY, Issue 2 2010Alper Kiliç Abstract Ships are significant emissions sources in transportation sector. The environmental effects of shipping emissions become more serious because of insufficient international rules and inspections. Especially in inland waters, canals, straits, gulfs, and port areas emissions effects on environment and health are more important. Izmit Gulf is the major industrial, transport, and inland water region which is affected from shipping emissions with 37 ports and industrial plants. In this study, NOx, SO2, CO2, HC, and PM emission amounts from 11,645 ships called to Izmit Gulf in 2005. These emissions are classified according to ships operation modes and ship types. Annual shipping emissions are estimated as 5,356 t yr,1 for NOx, 4,305 t yr,1 for SO2, 254,261 t yr,1 for CO2, 232 t yr,1 for HC and 487 t yr,1 for PM. To determine the most probably effected regions in the gulf, the spatial distribution of NOx emissions within the Gulf region has been prepared in 1 × 1 Nm2 (Nautical miles) grid cells based on ship movement data along the various routes. Ships in Izmit Gulf contribute to urban pollution with sulfur dioxide significantly. © 2009 American Institute of Chemical Engineers Environ Prog, 2010 [source] Die Häufigkeit von Oenothera -Arten im westlichen MitteleuropaFEDDES REPERTORIUM, Issue 5-6 2003R. Wittig Professor Dr. Auf ausgewählten Industrie- und Verkehrstandorten in drei Ballungsgebieten des westlichen Mitteleuropas (Rhein-Ruhr-Gebiet: Nordrhein-Westfalen/ Deutschland; Frankfurt: Hessen/Deutschland; Oberrheingebiet: Baden-Württemberg/Deutschland und Elsass/ Frankreich) wurde in den Jahren 1999 bis 2002 an ausgewählten, Oenothera -reichen Standorten (Industriegelände, Bahngelände, Hafenanlagen) eine quantitative Bestandsaufnahme der Oenothera -Arten vorgenommen. Hierbei belegten O. biennis und O. fallax nahezu gleichrangig den ersten Platz in der Häufigkeitsliste. Mit teilweise recht deut-lichem Abstand folgen O. pycnocarpa und O. glazioviana auf den Plätzen 3 und 4. Bemerkenswer-terweise ergab eine gleichzeitig in Frankfurt durchgeführte Rasterkartierung der Oenothera -Arten die gleiche Reihenfolge dieser vier Spezies im Hinblick auf die Zahl der von ihnen besiedelten Rasterfelder. Wie der Vergleich mit älteren Arbeiten zeigt, in denen O. biennis stets als die eindeutig häufigste Art genannt wird, hat sich O. fallax offensichtlich erst in jüngster Zeit stark ausgebreitet. Frequency of species of Oenothera in Western Central Europe Between 1999 and 2002 a quantitative inventory of Oenothera species was carried out in three urban agglomeration areas in Western Central Europe [Rhine-Ruhr-Area: North Rhine-Westfalia/Germany; Frankfurt (Main) Hessen/Germany; Upper Rhine Area-Baden-Wurttemberg/Germany and Elsace/ France] in areas with a rich abundance of Oenothera (manufacturing plants, stations, docks) at selected industrial sites and locations with high volumes of traffic. Results revealed that Oenotherabiennis and O. fallax occur most frequently followed after a wide margin by Oenothera pycnocarpa and O. glazioviana in third and fourth position. It is noteworthy that a grid mapping of Oenothera species undertaken simultanously in Frankfurt revealed the same order of frequency for the four species with respect to the number of grid cells they occupy. A comparison with previous studies, which all name Oenothera biennis as the most frequently occurring species, demonstrates clearly that the high frequency of Oenothera fallax is the result of a recent development. [source] Human modification of the landscape and surface climate in the next fifty yearsGLOBAL CHANGE BIOLOGY, Issue 5 2002R. S. Defries Abstract Human modification of the landscape potentially affects exchanges of energy and water between the terrestrial biosphere and the atmosphere. This study develops a possible scenario for land cover in the year 2050 based on results from the IMAGE 2 (Integrated Model to Assess the Greenhouse Effect) model, which projects land-cover changes in response to demographic and economic activity. We use the land-cover scenario as a surface boundary condition in a biophysically-based land-surface model coupled to a general circulation model for a 15-years simulation with prescribed sea surface temperature and compare with a control run using current land cover. To assess the sensitivity of climate to anthropogenic land-cover change relative to the sensitivity to decadal-scale interannual variations in vegetation density, we also carry out two additional simulations using observed normalized difference vegetation index (NDVI) from relatively low (1982,83) and high (1989,90) years to describe the seasonal phenology of the vegetation. In the past several centuries, large-scale land-cover change occurred primarily in temperate latitudes through conversion of forests and grassland to highly productive cropland and pasture. Several studies in the literature indicate that past changes in surface climate resulting from this conversion had a cooling effect owing to changes in vegetation morphology (increased albedo). In contrast, this study indicates that future land-cover change, likely to occur predominantly in the tropics and subtropics, has a warming effect governed by physiological rather than morphological mechanisms. The physiological mechanism is to reduce carbon assimilation and consequently latent relative to sensible heat flux resulting in surface temperature increases up to 2 °C and drier hydrologic conditions in locations where land cover was altered in the experiment. In addition, in contrast to an observed decrease in diurnal temperature range (DTR) over land expected with greenhouse warming, results here suggest that future land-cover conversion in tropics could increase the DTR resulting from decreased evaporative cooling during the daytime. For grid cells with altered land cover, the sensitivity of surface temperature to future anthropogenic land-cover change is generally within the range induced by decadal-scale interannual variability in vegetation density in temperate latitudes but up to 1.5 °C warmer in the tropics. [source] Quantifying uncertainty in estimates of C emissions from above-ground biomass due to historic land-use change to cropping in AustraliaGLOBAL CHANGE BIOLOGY, Issue 8 2001Damian J. Barrett Abstract Quantifying continental scale carbon emissions from the oxidation of above-ground plant biomass following land-use change (LUC) is made difficult by the lack of information on how much biomass was present prior to vegetation clearing and on the timing and location of historical LUC. The considerable spatial variability of vegetation and the uncertainty of this variability leads to difficulties in predicting biomass C density (tC ha,1) prior to LUC. The issue of quantifying uncertainties in the estimation of land based sources and sinks of CO2, and the feasibility of reducing these uncertainties by further sampling, is critical information required by governments world-wide for public policy development on climate change issues. A quantitative statistical approach is required to calculate confidence intervals (the level of certainty) of estimated cleared above-ground biomass. In this study, a set of high-quality observations of steady state above-ground biomass from relatively undisturbed ecological sites across the Australian continent was combined with vegetation, topographic, climatic and edaphic data sets within a Geographical Information System. A statistical model was developed from the data set of observations to predict potential biomass and the standard error of potential biomass for all 0.05° (approximately 5 × 5 km) land grid cells of the continent. In addition, the spatial autocorrelation of observations and residuals from the statistical model was examined. Finally, total C emissions due to historic LUC to cultivation and cropping were estimated by combining the statistical model with a data set of fractional cropland area per land grid cell, fAc (Ramankutty & Foley 1998). Total C emissions from loss of above-ground biomass due to cropping since European colonization of Australia was estimated to be 757 MtC. These estimates are an upper limit because the predicted steady state biomass may be less than the above-ground biomass immediately prior to LUC because of disturbance. The estimated standard error of total C emissions was calculated from the standard error of predicted biomass, the standard error of fAc and the spatial autocorrelation of biomass. However, quantitative estimates of the standard error of fAc were unavailable. Thus, two scenarios were developed to examine the effect of error in fAc on the error in total C emissions. In the first scenario, in which fAc was regarded as accurate (i.e. a coefficient of variation, CV, of fAc = 0.0), the 95% confidence interval of the continental C emissions was 379,1135 MtC. In the second scenario, a 50% error in estimated cropland area was assumed (a CV of fAc = 0.50) and the estimated confidence interval increased to between 350 and 1294 MtC. The CV of C emissions for these two scenarios was 25% and 29%. Thus, while accurate maps of land-use change contribute to decreasing uncertainty in C emissions from LUC, the major source of this uncertainty arises from the prediction accuracy of biomass C density. It is argued that, even with large sample numbers, the high cost of sampling biomass carbon may limit the uncertainty of above-ground biomass to about a CV of 25%. [source] The geography of body size , challenges of the interspecific approachGLOBAL ECOLOGY, Issue 6 2007Shai Meiri ABSTRACT Recent compilations of large-scale data bases on the geographical distributions and body sizes of animals, coupled with developments in spatial statistics, have led to renewed interest in the geographical distribution of animal body sizes and the interspecific version of Bergmann's rule. Standard practice seems to be an examination of mean body sizes within higher taxa on gridded maps, with little regard to species richness or phylogeny. However, because the frequency distribution of body sizes is typically highly skewed, average size within grid cells may differ significantly between species-rich and species-poor cells even when the median and modal sizes remain constant. Species richness influences body size patterns because species are not added to communities at random in relation to their size: areas of low diversity are characterized by a higher range of body sizes than is expected by chance. Finally, a consideration of phylogenetic structure within taxa is necessary to elucidate whether patterns in the geography of size result from turnover between or within intermediate taxonomic levels. We suggest that the highest and lowest quantiles of body size distribution be mapped in order to expose possible physiological or ecological limitations on body size. [source] | |||||||||||||||||||||||||||||||||||||