Inconstancy of Taylor'sb: Simulated sampling with different quadrat sizes and spatial distributions

Spatial and temporal variation of ecosystem properties at macroscales

Although spatial and temporal variation in ecological properties has been well-studied, crucial knowledge gaps remain for studies conducted at macroscales and for ecosystem properties related to material and energy. We test four propositions of spatial and temporal variation in ecosystem properties within a macroscale (1000 km's) extent. We fit Bayesian hierarchical models to thousands of observations from over two decades to quantify four components of variation - spatial (local and regional) and temporal (local and coherent); and to model their drivers. We found strong support for three propositions: (1) spatial variation at local and regional scales are large and roughly equal, (2) annual temporal variation is mostly local rather than coherent, and, (3) spatial variation exceeds temporal variation. Our findings imply that predicting ecosystem responses to environmental changes at macroscales requires consideration of the dominant spatial signals at both local and regional scales that may overwhelm temporal signals.

Spatial Distribution and Sampling Plans for Grapevine Plant Canopy-Inhabiting Scaphoideus titanus (Hemiptera: Cicadellidae) Nymphs

The paper deals with the study of the spatial distribution and the design of sampling plans for estimating nymph densities of the grape leafhopper Scaphoideus titanus Ball in vine plant canopies. In a reference vineyard sampled for model parameterization, leaf samples were repeatedly taken according to a multistage, stratified, random sampling procedure, and data were subjected to an ANOVA. There were no significant differences in density neither among the strata within the vineyard nor between the two strata with basal and apical leaves. The significant differences between densities on trunk and productive shoots led to the adoption of two-stage (leaves and plants) and three-stage (leaves, shoots, and plants) sampling plans for trunk shoots- and productive shoots-inhabiting individuals, respectively. The mean crowding to mean relationship used to analyze the nymphs spatial distribution revealed aggregated distributions. In both the enumerative and the sequential enumerative sampling plans, the number of leaves of trunk shoots, and of leaves and shoots of productive shoots, was kept constant while the number of plants varied. In additional vineyards data were collected and used to test the applicability of the distribution model and the sampling plans. The tests confirmed the applicability 1) of the mean crowding to mean regression model on the plant and leaf stages for representing trunk shoot-inhabiting distributions, and on the plant, shoot, and leaf stages for productive shoot-inhabiting nymphs, 2) of the enumerative sampling plan, and 3) of the sequential enumerative sampling plan. In general, sequential enumerative sampling was more cost efficient than enumerative sampling.

Fluctuation scaling, Taylor's law, and crime

Fluctuation scaling relationships have been observed in a wide range of processes ranging from internet router traffic to measles cases. Taylor’s law is one such scaling relationship and has been widely applied in ecology to understand communities including trees, birds, human populations, and insects. We show that monthly crime reports in the UK show complex fluctuation scaling which can be approximated by Taylor’s law relationships corresponding to local policing neighborhoods and larger regional and countrywide scales. Regression models applied to local scale data from Derbyshire and Nottinghamshire found that different categories of crime exhibited different scaling exponents with no significant difference between the two regions. On this scale, violence reports were close to a Poisson distribution (α = 1.057±0.026) while burglary exhibited a greater exponent (α = 1.292±0.029) indicative of temporal clustering. These two regions exhibited significantly different pre-exponential factors for the categories of anti-social behavior and burglary indicating that local variations in crime reports can be assessed using fluctuation scaling methods. At regional and countrywide scales, all categories exhibited scaling behavior indicative of temporal clustering evidenced by Taylor’s law exponents from 1.43±0.12 (Drugs) to 2.094±0081 (Other Crimes). Investigating crime behavior via fluctuation scaling gives insight beyond that of raw numbers and is unique in reporting on all processes contributing to the observed variance and is either robust to or exhibits signs of many types of data manipulation.

Determining the spatial autocorrelation of dengue vector populations: influences of mosquito sampling method, covariables, and vector control

We investigated spatial autocorrelation of female Aedes aegypti L. mosquito abundance from BG-Sentinel trap and sticky ovitrap collections in Cairns, north Queensland, Australia. BG-Sentinel trap collections in 2010 show a significant spatial autocorrelation across the study site and over a smaller spatial extent, while sticky ovitrap collections only indicate a non-significant, weak spatial autocorrelation. The BG-Sentinel trap collections were suitable for spatial interpolation using ordinary kriging and cokriging techniques. The uses of Premise Condition Index and potential breeding container data have helped improve our prediction of vector abundance. Semiovariograms and prediction maps indicate that the spatial autocorrelation of mosquito abundance determined by BG-Sentinel traps extends farther compared to sticky ovitrap collections. Based on our data, fewer BG-Sentinel traps are required to represent vector abundance at a series of houses compared to sticky ovitraps. A lack of spatial structure was observed following vector control treatment in the area. This finding has implications for the design and costs of dengue vector surveillance programs.

Spatial behavior comparison of Bactericera Cockerelli Sulc. (hemiptera: triozidae) in Mexico

During the last five years, Bactericera cockerelli Sulc. has caused significant economic losses in potato production in Mexico, due to the purple top and zebra chip diseases, since it acts as the vector of Candidatus Liberibacter psyllaurous. Despite its importance as a vector of serious potato diseases, the knowledge of its spatial distribution behavior, which could improve the efficiency of control measures, is entirely lacking. The main objective of this work was to compare the spatial distribution of the immature and adult stages of B. cockerelli obtained in a potato field by means of transect and quadrant sampling techniques and of geostatistics tools that allow the visualization of its spatial distribution in the field. Transect and quadrant samplings showed that the immature stages (eggs and nymphs) of B. cockerelli present a clustered distribution. The validation of the achieved semivariograms in the three dates of sampling corroborated the aggregated distribution of immatures and adults of the insect. The maps obtained in the sampling by using the quadrant or the transect approaches reflect the aggregated structure of the insect populations which did not infest 100% of the plot area. This allowed us to identify infested and free areas, what will aid in decisions for selecting alternatives of control.

Spatio-temporal dynamics of resident and immigrating populations of Carcinops pumilio (Coleoptera: Histeridae) in high-rise poultry facilities

The histerid beetle Carcinops pumilio (Erichson) is an important natural predator of the house fly, Musca domestica L., in accumulated poultry house manure. We examined the spatio-temporal dynamics of establishing adult C. pumilio in high-rise poultry facilities using conventional and geostatistical approaches. The growth curves of resident and immigrating populations followed logistic and exponential equations, respectively, and their rates of establishment were statistically the same. Frequency distributions for both populations were strongly positively skewed, and approximately 53% of sampling intervals were significantly modeled by the negative binomial. Taylor's power law indicated both populations to be aggregated, and gave excellent least squares regression fits to both populations. Correlograms, a geostatistical tool, suggested little local spatial structure (e.g., 2nd order effects) for either population. The resident population was 'randomly' aggregated: beetles were clustered around randomly distributed aggregations of house fly immatures. The immigrating population exhibited significant spatial trends (e.g., 1st order effects) consistently seen at all sampling intervals. C. pumilio spatial structure was represented primarily by this spatial trend; thus, immigration of C. pumilio may have been either a singular event in time, or initiating at 1 or multiple times from a singular location.

The temporal variability of animal abundances: measures, methods and patterns

From first principles, the temporal variability of a time series of abundances can be defined as the average deviation of values from a mean value on a proportional scale. In this paper we review: (i) the different kinds of temporal variability; (ii) the different ways in which it can be measured; (iii) the design of appropriate sampling schemes; (iv) methods of analysing variability; and (v) patterns in temporal variability. We emphasize that some commonly applied measures are not appropriate, that several do not measure the desired feature of time series, and the importance of considerations of trend and sampling error. A number of suggestions are made for the improvement of the basis for comparative analyses of levels of variability, and some of the potential pitfalls are identified. Given the serious faults in many previous analyses of ecological patterns in the temporal variability of animal abundances, emphasis is laid on the theoretical basis for different patterns, and hence a set of hypotheses for testing is generated.