Analyzing spatial count data,with an application to weed counts

Count data on a lattice may arise in observational studies of ecological phenomena. In this paper a hierarchical spatial model is used to analyze weed counts. Anisotropy is introduced, and a bivariate extension of the model is presented.     

Nile water pollution and technical efficiency of crop production in Egypt: an assessment using spatial and non-parametric modelling

Agriculture is considered one of the vital activities in Egypt; it consumes about 83 % of the Egyptian Nile water quota. This activity is becoming negatively affected by water pollution causing negative repercussion on land productivity and subsequently food security. This paper assesses the water quality for agriculture along the mainstream of the Nile in Egypt through spatial distributions modelling of total dissolved solids (TDS), using spatial statistical analysis. The study’s sample frame consists of 78 sampling points collected in February 2008 and located on the Nile mainstream and its two branches, Rosetta and Damietta. Exploratory spatial data analysis is carried out on the TDS, followed by plotting and modelling the experimental semi-variogram. Then, cross validation is executed in order to determine the best fitting model. Finally, surface mapping is generated by performing spatial interpolation, using kriging technique. The generated surface map shows that the TDS levels increase from Upper to Lower Egypt, exceeds the standard limit in Beni-Suef and Rosetta branch. In fact, high levels of TDS are known to have a negative effect on Egyptian agriculture through harmfully affecting the soil and consequently the crop yields. Therefore, an analysis of the effect of water pollution on technical efficiency of crop production is conducted using a non-parametric mathematical programming approach to frontier estimation. The results of this estimation indicated that the TDS is overutilized in all governorates except Aswan.     

Palatability mapping: a koala's eye view of spatial variation in habitat quality

Ecologists trying to understand the value of habitat to animals must first describe the value of resources contained in the habitat to animals and, second, they must describe spatial variation in resource quality at a resolution relevant to individual animal foraging. We addressed these issues in a study of koalas (Phascolarctos cinereus) in a Eucalyptus woodland. We measured beneficial and deterrent chemical characteristics as well as the palatability of trees using a near-infrared spectroscopic model based on direct feeding experiments. Tree use by koalas was influenced by tree size and foliar quality but was also context-dependent: trees were more likely to be visited if they were surrounded by small, unpalatable trees or by large, palatable trees. Spatial autocorrelation analysis and several mapping approaches demonstrated that foliar quality is spatially structured in the woodland at a scale relevant to foraging decisions by koalas and that the spatial structure is an important component of habitat quality.     

Analyzing and modelling spatial distribution of summering lesser kestrel: The role of spatial autocorrelation

In modelling spatial distribution of species, ignoring spatial autocorrelation (SA) and multicollinearity may lead to false ecological conclusions. Here we take into account both issues for examining and modelling the spatial pattern of abundance of the globally threatened lesser kestrel (Falco naumanni) during summer in a 38,400 ha area of northwestern Spain where large premigratory aggregations of the species occur. Spatial pattern was examined using Moran's correlogram, and models were built including geographical coordinates and autocovariate terms (which account for SA) in generalized linear models (GLM) and hierarchical partitioning (HP) models. HP models allow to alleviate multicollinearity. A grid-based approach was used by dividing the study area in 24 contiguous 4 km × 4 km squares where birds were counted in 2–3 visits per square (response variable). Environmental coarse-grained variables were extracted from a geographic information system (GIS) at three spatial extents. Moran's correlogram showed that lesser kestrel mean abundance per square was spatially autocorrelated up to 4–8 km. The results from both GLM and HP analyses were roughly compatible. The GLM models explained 80.0% of the variation in kestrel abundance and were the same at the three spatial extents. Lesser Kestrel abundance was not significantly explained by landscape variables, but was negatively related to both the distance to the nearest communal roost and distance to the nearest breeding colony with more of 10 breeding pairs of lesser kestrel. An autocovariate term added later in the GLM models improved both their explanatory power (from 74.5 to 80.0%) and model residuals, which were not longer spatially autocorrelated, fulfilling thus the statistical assumption of independent errors. Findings suggest that the spatial distribution of abundance of summering lesser kestrel is, at least, partially driven by endogenous causes, such as conspecific attraction. Exogenous causes such as finer-scale variables (e.g. type of crops and food available) are yet likely needed for lesser kestrel-environment relationships.     

Mixed but not admixed: a spatial analysis of genetic variation of an invasive ascidian on natural and artificial substrates

Following the introduction to a new area (pre-border dispersal), post-border processes determine the success in the establishment of non-indigenous species (NIS). However, little is known on how these post-border processes shape the genetic composition of NIS at regional scales. Here, we analyse genetic variation in introduced populations along impacted coastlines to infer demographic and kinship dynamics at the post-border stage. We used as a model system the ascidian species Microcosmus squamiger that has been introduced worldwide. This species can colonize and grow fast on man-made artificial structures, impacting activities such as mariculture. However, it can also establish itself on natural substrates, thus altering natural communities and becoming an ecological problem. We genotyped 302 individuals from eight populations established on natural and artificial substrates in the north-western Mediterranean Sea, using six microsatellite loci. We then compared the resulting genotypes with those found within the native range of the species. We found high levels of genetic diversity and allelic richness in all populations, with an overall deficit of heterozygotes. Autocorrelation analyses showed that there was no within-population genetic structure (at a scale of tens of metres); likewise, no significant differentiation in pairwise comparisons between populations (tens of kilometres apart) and no isolation-by-distance pattern was found. The results suggest that M. squamiger has a natural capacity for high dispersal from one patch of hard substrate to another and no differences whatsoever could be substantiated between natural and artificial substrates. Interestingly, two groups of genetically differentiated individuals were detected that were associated with the two ancestral source areas of the worldwide expansion of the species. Individual assignment tests showed the coexistence of individuals of these two clusters in all populations but with little interbreeding among them as the frequency of admixed individuals was only 15 %. The mechanism responsible for maintaining these genetic pools unmixed is unknown, but it does not appear to compromise post-border colonization of introduced populations.     

Characterization and variation of dissolved organic matter in composting: a critical review

● Effect of composting approaches on dissolved organic matter (DOM). ● Effect of composting conditions on the properties of DOM. ● Character indexes of DOM varied in composting. ● The size, hydrophobicity, humification, and electron transfer capacity increased. ● The hydrophilicity, protein-like materials, and aliphatic components reduced. As the most motive organic fraction in composting, dissolved organic matter (DOM) can contribute to the transfer and dispersal of pollutants and facilitate the global carbon cycle in aquatic ecosystems. However, it is still unclear how composting approaches and conditions influence the properties of compost-derived DOM. Further details on the shift of DOM character indexes are required. In this study, the change in properties of compost-derived DOM at different composting approaches and the effect of composting conditions on the DOM characteristics are summarized. Thereafter, the change in DOM character indexes’ in composting was comprehensively reviewed. Along with composting, the elements and spectral properties (chromophoric DOM (CDOM) and fluorescent DOM (FDOM)) were altered, size and hydrophobicity increased, and aromatic-C and electron transfer capacity were promoted. Finally, some prospects to improve this study were put forward. This paper should facilitate the people who have an interest in tracing the fate of DOM in composting.     

Synthesis and application of graphene-based sensors in biology: a review

Environmental Chemistry Letters - Biosensors are gaining interest in biomedical and environmental sciences. In particular, graphene-based biosensors are promising due to the unique properties of...     

水信息学及其在水环境中的应用研究综述

水信息学是一门新兴的学科,是在水范围内运用知识的新途径、元知识.它着重运用计算机技术、通信网络技术、3S技术、可视化技术等一系列高新技术,并结合传统水科学和工程学的方法,研究与水环境相关数据的收集、存储、处理、模拟、预测和结果显示等问题.文章首先探讨了几种不同的水环境概念及水环境研究模型,阐述了近年生态水力学模型的制约因素.生态水力学模型建市在时空一致性和质量能量守恒等假设上,而水生态系统的高度复杂性、非线性和时空特异性制约模型的发展.从"知识发现"和"知识管理"两个视角出发,重点阐述数学模型、数据挖掘、数据同化、数据驱动、地理信息系统、决策支持系统、商业软件等水信息学方法在水环境研究中的应用.目前水信息学还处于起步阶段,各方法交叉结合的研究还比较少,在今后的研究中有待加强,包括基于数据的各方法手段的结合、基于数据和基于过程的两者结合、水环境的知识发现和知识管理的结合等.     

Modelling of concentrations along a moving observer in an inhomogeneous plume. Biological application: model of odour-mediated insect flights

We develop a stochastic model for the time-evolution of scalar concentrations and temporal gradients in concentration experienced by observers moving within inhomogeneous plumes that are dispersing within turbulent flows. In this model, scalar concentrations and their gradients evolve jointly as a Markovian process. Underlying the model formulation is a natural generalisation of Thomson’s well mixed condition [Thomson DJ (1987) J Fluid Mech 180:529–556]. As a consequence model outputs are necessarily compatible with statistical properties of scalars observed in experiment that are used here as model input. We then use the model to examine how insects aloft within the atmospheric boundary-layer can locate odour sources by modulating their flight patterns in response to odour cues. Mechanisms underlying odour-mediated flights have been studied extensively at laboratory-scale but an understanding of these flights over landscape scales is still lacking. Insect flights are simulated by combining the stochastic model with a simple model of insect olfactory response. These simulations show the strong influence of wind speed on the distributions of the times taken by insects to locate the source. In accordance with experimental observations [Baker TC, Vickers NJ (1997) In: Insect pheromone research: new directions, pp 248–264; Mafra-Neto A, Cardé RT (1994) Nature 369:142–144], flight patterns are predicted to become straighter and shorter, and source location is predicted to become more likely as the mean wind speed increases. The most probable arrival time to the source decreases with the mean wind speed. It is shown that scale-free movement patterns arising from olfactory-driven foraging stem directly from the power-law distribution of concentration excursion times above/below a threshold level and are robust with respect to variations in Reynolds number. Flight lengths are well represented by a power law distribution in agreement with the observed patterns of foraging bumblebees [Heinrich B (1979) Oecologia 40(3):235–245].     

Importance of individual and environmental variation for invasive species spread: a spatial integral projection model

Plant survival, growth, and flowering are size dependent in many plant populations but also vary among individuals of the same size. This individual variation, along with variation in dispersal caused by differences in, e.g., seed release height, seed characteristics, and wind speed, is a key determinant of the spread rate of species through homogeneous landscapes. Here we develop spatial integral projection models (SIPMs) that include both demography and dispersal with continuous state variables. The advantage of this novel approach over discrete-stage spread models is that the effect of variation in plant size and size-dependent vital rates can be studied at much higher resolution. Comparing Neubert-Caswell matrix models to SIPMs allowed us to assess the importance of including individual variation in the models. As a test case we parameterized a SIPM with previously published data on the invasive monocarpic thistle Carduus nutans in New Zealand. Spread rate (c*) estimates were 34% lower than for standard spatial matrix models and stabilized with as few as seven evenly distributed size classes. The SIPM allowed us to calculate spread rate elasticities over the range of plant sizes, showing the size range of seedlings that contributed most to c* through their survival, growth and reproduction. The annual transitions of these seedlings were also the most important ones for local population growth (lambda). However, seedlings that reproduced within a year contributed relatively more to c* than to lambda. In contrast, plants that grow over several years to reach a large size and produce many more seeds, contributed relatively more to lambda than to c*. We show that matrix models pick up some of these details, while other details disappear within wide size classes. Our results show that SIPMs integrate various sources of variation much better than discrete-stage matrix models. Simpler, heuristic models, however, remain very valuable in studies where the main goal is to investigate the general impact of a life history stage on population dynamics. We conclude with a discussion of future extensions of SIPMs, including incorporation of continuous time and environmental drivers.     

Temporal and spatial variation in bacterial production in the water column over a coral reef

Production and doubling times of the bacterial populations in the water around and over the reefs at Lizard Island, Great Barrier Reef were measured during summer and winter, 1982 and 1983. Bacterial productivity, determined from the rate of tritiated thymidine incorporation into DNA, was high over the reef flats and a Thalassia hemprichii sand flat (28 to 58 g Cl^-1 d^-1). Bacterial growth rates increased during the day and fell at night over the reef flats and seagrass bed. Growth rates were slower over the reef front and in open water. Doubling times ranged from about 2 d in the open water to about 3 h over the reef flat in summer. As numbers did not increase, grazing was probably intense on the reef flats. Growth rates were much slower in winter. The main source of organic nutrient used by the bacteria was probably mucus released following photosynthesis in the corals. The cyanobacterium Synechococcus sp. was sometimes very numerous, especially in summer when 2×10⁸ cells l^-1 were recorded in one water mass. The number of bacteria was also very high in summer, with values ranging from 1×10⁹ to 2.5×10⁹l^-1.     

A multi-scale approach to modelling spatial and dynamic ecological patterns for reservoir's water quality management

With growing levels of urbanization and agriculture throughout the world, it is increasingly important that both research and management efforts take into account the effects of this widespread landscape alteration and its consequences for natural systems. Freshwater ecosystems, namely reservoirs, are particularly sensitive to land use changes. In this context, modelling can be very useful, for decision support, as an investigative tool to forecast the outcome of various scenarios, to guide current management in order to meet future targets and to develop integrated frameworks for management accordingly to the Water Framework Directive (WFD). The present paper examined the applicability of a holistic Stochastic-Dynamic Methodology (StDM), coupled with a Cellular Automata (CA) model, in capturing how expected changes at land use level will alter the ecological status of lentic ecosystems, namely at physicochemical and biological levels. The methodology was applied to Portuguese reservoirs located in the Douro's basin and illustrated with a series of stochastic-dynamic and spatial outputs taking into account expected scenarios regarding land use changes. Overall, the simulation results are encouraging since they seem to demonstrate the tool reliability in capturing the stochastic environmental dynamics of the selected metrics facing spatial explicit scenarios. The ultimate goal was to couple monitoring assessment and the described modelling techniques to ease management and decision making regarding the practical implementation of the WFD, both at the scale of the reservoir body and at the scale of the respective river watershed dynamics.     

Phosphorus in Phoenix: a budget and spatial representation of phosphorus in an urban ecosystem

As urban environments dominate the landscape, we need to examine how limiting nutrients such as phosphorus (P) cycle in these novel ecosystems. Sustainable management of P resources is necessary to ensure global food security and to minimize freshwater pollution. We used a spatially explicit budget to quantify the pools and fluxes of P in the Greater Phoenix Area in Arizona, USA, using the boundaries of the Central Arizona-Phoenix Long-Term Ecological Research site. Inputs were dominated by direct imports of food and fertilizer for local agriculture, while most outputs were small, including water, crops, and material destined for recycling. Internally, fluxes were dominated by transfers of food and feed from local agriculture and the recycling of human and animal excretion. Spatial correction of P dynamics across the city showed that human density and associated infrastructure, especially asphalt, dominated the distribution of P pools across the landscape. Phosphorus fluxes were dominated by agricultural production, with agricultural soils accumulating P. Human features (infrastructure, technology, and waste management decisions) and biophysical characteristics (soil properties, water fluxes, and storage) mediated P dynamics in Phoenix. P cycling was most notably affected by water management practices that conserve and recycle water, preventing the loss of waterborne P from the ecosystem. P is not intentionally managed, and as a result, changes in land use and demographics, particularly increased urbanization and declining agriculture, may lead to increased losses of P from this system. We suggest that city managers should minimize cross-boundary fluxes of P to the city. Reduced P fluxes may be accomplished through more efficient recycling of waste, therefore decreasing dependence on external nonrenewable P resources and minimizing aquatic pollution. Our spatial approach and consideration of both pools and fluxes across a heterogeneous urban ecosystem increases the utility of nutrient budgets for city managers. Our budget explicitly links processes that affect P cycling across space with the management of other resources (e.g., water). A holistic management strategy that deliberately couples the management of P and other resources should be a priority for cities in achieving urban sustainability.     

Residential radon concentration in the Abruzzo region (Italy): a different perspective for identifying radon prone areas

Indoor radon is an important risk factor for human health. Indeed radon inhalation is considered the second cause of lung cancer after smoking. During the last decades, in many countries huge efforts have been made in order to measuring, mapping and predicting radon levels in dwellings. Various researches have been devoted to identify those areas within the country where high radon concentrations are more likely to be found. Data collected through indoor radon surveys have been analysed adopting various statistical approaches, among which hierarchical Bayesian models and geostatistical tools are worth noting. The essential goal of this paper regards the identification of high radon concentration areas (the so-called radon prone areas) in the Abruzzo Region (Italy). In order to accurately pinpoint zones deserving attention for mitigation purpose, we adopt spatial cluster detection techniques, traditionally employed in epidemiology. As a first step, we assume that indoor radon measurements do not arise from a continuous spatial process; thus the geographic locations of dwellings where the radon measurements have been taken can be viewed as a realization of a spatial point process. Following this perspective, we adopt and compare recent cluster detection techniques: the simulated annealing scan statistic, the case event approach based on distance regression on the selection order and the elliptic spatial scan statistic. The analysis includes data collected during surveys carried out by the Regional Agency for the Environment Protection of Abruzzo (ARTA) in 1,861 random sampled dwellings across 277 municipalities of the Abruzzo region. The radon prone areas detected by the selected approaches are provided along with the summary statistics of the methods. Finally, the methodologies considered in this paper are tested on simulated data in order to evaluate their power and the precision of cluster location detection.