Quadrat Size Research Articles

SCALE OF DISTURBANCE AND THE STRUCTURE OF A TEMPERATE FISH GUILD

Although it is acknowledged that the spatial scale of sampling and experimentation is important in assessing the degree of stability of a community, multiple scales are rarely incorporated into the same study. We compared the persistence and resilience of a temperate blennioid fish guild at three scales spanning an order of magnitude. Replicate permanent square quadrats of three sizes (4 m2, 25 m2, 100 m2) were delimited within contiguous tracts of reef in two habitats: broken reef and macroalgal forest. Two forms of disturbance were applied to the treatment quadrats. Direct disturbance (fish removal) was applied to treatments in the broken reef habitat. Indirect disturbance (macroalgal removal) was applied to treatments in the macroalgal forest. Both experiments identified several scale-dependent effects. Large quadrats were less variable than smaller quadrats, probably due to reduced edge effects due to movement of fish in and out of the quadrats. The smallest quadrats did not adequately represent the available substratum types within the reef zone. This interacted with species-specific behavioral factors such as mobility and habitat association to consistently bias the blennioid composition within the smallest quadrats toward dominance of the most sedentary blennioid species. Fish responded to disturbance in different ways depending on the stage of their life cycle. Adult fish responded at scales within their motility range of only a few meters. In contrast, newly settling fish responded to the habitat at larger scales. Quadrat size also determined which assemblage dynamics could be measured. Within-year changes in guild composition due to species-specific settlement timing and survivorship could be measured only at larger scales. We conclude that different scales of monitoring and manipulation will determine what can be perceived by the researcher as well as how the organism will respond to disturbance.

Patterns of species richness in a limestone grassland under different treatments in relation to spatial scale

Abstract. In an experiment in a limestone grassland on the Baltic island of Öland, SE Sweden, nutrient and water supply, light intensity and grazing regime were altered in 10 combinations during four years in 10 plots of 0.25 m2 with subplots of 0.01 m2 and 0.0004 m2.Only the combined application of fertilizer and shade led to a strong decrease in average species richness (S1) at all scales. When comparing species numbers summed up over all 10 replicates of each treatment (Sn) at the three quadrat sizes, differences in effect of these treatments were much smaller, and were so already at the finest scale.α‐diversity, measured as (Sn ‐ S1 was quite constant over different scales for most treatments, i.e. diversity did not increase with an increase in scale. The ‘richness ratio’Sn/S1 decreased with increasing scale, indicating an increasing degree of homogeneity at larger scales.Treatments which only included fertilizer or shade, maintained high species richness; this high richness was also maintained in combination with grazing and could then be explained by the denser packing of vegetation. Patterns of species richness were correlated at the large scale, but not at the finer scales, indicating a high degree of spatial and temporal heterogeneity at the finer scales. With increasing quadrat size species persistence increased which explains the small effect of certain treatments.Clearly, a range of scales has to be sampled in this type of vegetation to be able to measure different patterns, which may occur under different experimental treatments. The finest scale in this study can become too small, when certain treatments result in a coarse‐grained vegetation pattern. The quadrat size of 10 cm x 10 cm should be included in the range of scales. It combines accuracy in sampling with efficiency in time effort, a reasonably large number of species sampled, and a strong differentiation in the effects of the various treatments.

Population structure and breeding biology in relation to conservation in the dioecious Gardenia actinocarpa (Rubiaceae) – a rare shrub of North Queensland rainforest

Knowledge of breeding systems of endangered plants is crucial in formulating effective management plans for their conservation. Consequently, spatial distribution, flowering and fruiting patterns of Gardenia actinocarpa Puttock (Rubiaceae), a rare and endemic dioecious shrub of lowland tropical rainforest of Cape Tribulation, North Queensland, Australia were documented in four sub-populations over a two year period. Sex ratio was unity in two of the sites, and significantly biased in favour of male plants in the other two sites. At most sites, analysis of spatial distribution of individuals indicated aggregated dispersion patterns irrespective of quadrat size and plant size/reproductive status. There was no evidence of niche differentiation nor switching of the sexes. The species exhibited an extended flowering pattern of almost six months. However, male trees flowered earlier, longer, and produced more flowers than female trees. Intensity of flowering was significantly correlated with plant size in both sexes. Fruit set was very low in each of the two years of observation, but was significantly predicted by female habitat light environment, flower production and plant size. The lack of neighbourhood effects such as male tree density, male tree flower production around a focal female tree and distance from a female tree to the nearest male tree on fruit set is an indication that G. actinocarpa pollinators are capable of carrying pollen over long distances. Conservation implications of these findings are discussed.

Effects of quadrat size and data measurement on the detection of boundaries

Abstract. With sampled field data, the accuracy of delineation of ecotones is directly related to the resolution of the data (i.e. spatial and measurement type) and to the edge detection algorithm used. In the present study the reliability is investigated of an edge detection algorithm (lattice‐wombling) to delimit vegetation boundaries when different spatial resolutions (quadrat sizes) are used. To quantify whether the edge detection algorithm is robust, it was applied to data from woody species in a second‐growth woodland measured at different spatial resolutions with different data types. Boundaries were found at similar locations using any reasonable quadrat size (ca. 200 m2) but there were some slight differences when using different vegetation measures (density versus presence/absence data).

Developing methods for quantifying the apparent abundance of fiddler crabs (Ocypodidae: Uca) in mangrove habitats

Counting the number of individuals emerging from burrows is the most practical method for estimating the apparent abundance of Australian Uca species living in mangrove habitats. Experiments were conducted to investigate the effect on counts of quadrat design, distance of observer, quadrat size, recovery time and observational technique. Significant differences in the apparent abundance of one species were found when the subjects were within 2 m of the observer, and when a conspicuous quadrat was used. The largest quadrat tested provided the least variability in counts but an intermediate size (0.56 m2) was more practical. Most Uca active within a 30‐min period emerged during the first 10 min regardless of site, species, sex or season. There was a linear correlation between scanning and continuous observation indicating that the former method could be useful when sampling time was limited. Temporal changes in the apparent abundance of Uca suggest that long‐term sampling and more detailed studies will be worthwhile.

Effects of sampling unit resolution on the estimation of spatial autocorrelation

Sensitivity of Moran’s I spatial autocorrelation coefficient in estimating the magnitude of autocorrelation of species abundance data is examined when different quadrat sizes and shapes are employed. Since the measure of plant abundance is a function of the quadrat size employed, it is expected that the estimation of spatial autocorrelation based on such quantitative data will also be affected by the quadrat size used. Woody plant abundance data are used to illustrate the effects of spatial resolution (quadrat size and shape) on the estimation of spatial autocorrelation. It is found that across quadrat sizes, while the magnitude of spatial autocorrelation varies, the overall shape of the correlograms remains consistent. Specifically, the intensity of spatial autocorrelation increases with quadrat size up to the quadrat sizes of 200-225 m2, where it reaches a plateau. Then, given that larger quadrat sizes are more likely to include more environmental variability, the intensity of spatial autocorrelation decreases at the largest quadrat size. With these data, the shape of the quadrat affects the estimation of spatial autocorrelation as well as the degree of anisotropy in the spatial patterns identified.

水田におけるスクミリンゴガイの密度推定 最適なコードラート面積の決定と，コードラート法，ライントランセクト法，マーキング法による推定密度の比較

水田におけるスクミリンゴガイの密度推定 最適なコードラート面積の決定と，コードラート法，ライントランセクト法，マーキング法による推定密度の比較

Evaluation of the dry weight rank method for botanical analysis of grassland by means of simulation

With the Dry Weight Rank (DWR) method of 't Mannetje and Haydock [see Journal of British Grassland Society (1963) 18, 268-275] for botanical analysis in pastures, the dry weight proportions of species are estimated from their first, second and third ranks in dry weight in single quadrats. The yield correction of Haydock and Shaw [see Australian Journal of Experimental Agriculture and Animal Husbandry (1975) 15, 663-670] is used additionally to solve the problem of the respective under- and overestimates of the dry weight proportions of high and low yielding species when these grow in patches. In this paper the DWR method is evaluated by means of computer simulation. Main element of the simulation model is a computer sampling program with which a fictitious vegetation can be sampled with a circular quadrat. The output shows that the DWR method works well using relatively small sampling quadrats with, on average, only a few plants per quadrat, irrespective of the horizontal vegetation structure. In vegetations where species grow patchwise, satisfactory results are also obtained using large quadrats with much more plants (i.e. tens) per quadrat. The reason is that in these cases also minor species can compete successfully for first, second and third ranks. However, it appeared that only a certain degree of patchiness is necessary, and with the usually applied quadrat sizes up to 25 dmsuperscript 2, probably in most vegetations this condition is fulfilled. Care should be taken in applying the DWR method for estimating species composition in recently sown grasslands where species usually occur more or less at random. In those cases, in principle a very small sampling quadrat (smaller than 1 dmsuperscript 2) could be used. However, this has practical limitations since the quadrat size should not be too small for realistic yield estimations, needed for the Haydock & Shaw yield correction. The simulations revealed that one condition (i.e., that the sampling quadrat should be at least as large that it usually contains three or more species) is not necessary because of the almost always perfect functioning of the correction for missing ranks. Generally speaking, a sampling quadrat should be chosen not larger than is strictly necessary from the viewpoint of horizontal vegetation structure and from the viewpoint of realistic yield estimations. Multipliers calculated from simulation data could satisfactorily mimic the original multipliers of DWR given by 't Mannetje & Haydock. It is postulated that the DWR method is well suited for studying vegetation changes in old, floristically diverse grasslands with dominant species often in moderate dry weight proportions and species usually growing in patches.

Increase and Patterns of Spread of Citrus Tristeza Virus Infections in Costa Rica and the Dominican Republic in the Presence of the Brown Citrus Aphid, Toxoptera citricida

ABSTRACT Citrus tristeza virus (CTV) was monitored for 4 years by monoclonal antibody probes via enzyme-linked immunosorbent assay in four citrus orchards in northern Costa Rica and four orchards in the Dominican Republic following the introduction of the brown citrus aphid, Toxoptera citricida. The Gompertz nonlinear model was selected as the most appropriate in most cases to describe temporal increase of CTV. Ordinary runs analysis for association of CTV-positive trees failed to show a spatial relationship of virus status among immediately adjacent trees within or across rows. The beta-binomial index of dispersion for various quadrat sizes suggested aggregations of CTV-positive trees for all plots within the quadrat sizes tested. Spatial autocorrelation analysis of proximity patterns suggested that aggregation often existed among quadrats of various sizes up to four lag distances; however, significant lag positions discontinuous from the main proximity pattern were rare. Some asymmetry was also detected for some spatial autocorrelation proximity patterns. These results were interpreted to mean that, although CTV-positive trees did not often influence immediately adjacent trees, virus transmission was common within a local area of influence that extended two to eight trees in all directions. Where asymmetry was indicated, this area of influence was somewhat elliptical. The spatial and temporal analyses gave some insight into possible underlying processes of CTV spread in the presence of T. citricida and suggested CTV spread was predominantly to trees within a local area. Patterns of longer-distance spread were not detected within the confines of the plot sizes tested. Longer-distance spread probably exists, but may well be of a complexity beyond the detection ability of the spatial analysis methods employed, or perhaps is on a scale larger than the dimensions of the plots studied.

The hierarchical tessellation model and its use in spatial analysis

The hierarchid tessellation model belongs to a class of spatial data models based on the recursive decomposition of space. The quadtree is one such tessellation and is characterized by square cells and a 1:4 decomposition ratio. To relax these constraints in the tessellation, a generalized hierarchical tessellation data model, called Adaptive Recursive Tessellations (ART), has been proposed. ART increases flexibility in the tessellation by the use of rectangular cells and variable decomposition ratios. In ART, users can specify cell sizes which are intuitively meaningful to their applications, or which can reflect the scales of data. ART is implemented in a data structure called Adaptive Recursive Run‐Encoding (ARRE), which is a variant of two‐dimensional run‐encoding whose running path can vary with the different tessellation structures incorporated in an ART model. Given the recognition of the benefits of implementing statistical spatial analysis in GIS, the use of hierarchical tessellation models such as ART in spatial analysis is discussed. Three examples are introduced to show how ART can: (1) be applied to solve the quadrat size problem in quadrat analysis of point patterns; (2) act as the data model in the variable resolution block kriging technique for geostatistical data to reduce variation in kriging error; and (3) facilitate the evaluation of spatial autocorrelation for area data at multiple map resolutions via the construction of a connectivity matrix for calculating spatial autocorrelation indices based on ARRE.

Aggregation of Sampling Units: An Analytical Solution to Predict Variance

Geographical variables generally show spatially structured patterns corresponding to intrinsic characteristics of the environment. The size of the sampling unit has a critical effect on our perception of phenomena and is closely related to the variance and correlation structure of the data. Geostatistical theory uses analytical relationships for change of support (change of sampling unit size), allowing prediction of the variance and autocorrelation structure that would be observed if a survey was conducted using different sampling unit sizes.To check the geostatistical predictions, we use a test case about tree density in the tropical rain forest of the Pasoh Reserve, Malaysia. This data set contains exhaustive information about individual tree locations, so it allows us to simulate and compare various sampling designs. The original data set was reorganized to compute tree densities for 5 times 5‐, 10 times 10‐, and 20 times 20‐meter quadrat sizes. Based upon the 5 times 5‐meter data set, the spatial structure is modeled using a nugget effect (white noise) plus an exponential model. The change of support relationships, using within‐quadrat variances inferred from the variogram model, predict the spatial autocorrelation structure and new variances corresponding to 10 times 10‐meter and 20 times 20‐meter quadrats. The theoretical and empirical results agreed closely, whereas neglecting the autocorrelation structure would have led to largely underestimating the variance. As the quadrat size increases, the range of autocorrelation increases, while the variance and the proportion of noise in the data decrease.

A community-level analysis of spatial mortality patterns

Spatial patterns of mortality often reflect ecological processes controlling sessile communities. An analysis combining indices of patchiness and species association that describes the effect of conspecifics and interspecifics on spatial patterns of mortality is introduced. This analysis may be especially suitable for community-level descriptions when low densities preclude ecologically meaningful examinations of population-level patterns. Because densities of individuals (expressed on a per quadrat basis) decrease with spatial scale (quadrat size), this analysis may be particularly appropriate for understanding the role of processes such as competition for substratum space whose intensities increase with increasing proximity among individuals. Alternatively, the usefulness of this analysis may be restricted to situations where all species are affected similarly by underlying causal processes. I used the analysis to examine small-scale ( 1 64 m 2 ) mortality patterns in two shallow-water gorgonian communities in Puerto Rico from 1983–1993. Analytical results, which were consistent with ‘random thinning’ Monte Carlo simulations, indicated that mortality is independent of abundances of conspecific and interspecific colonies. These results indicate that competition for substratum space among gorgonians does not play a major role in the dynamics of this community.

Flora of the Pro-Namib Desert Swakop River Catchment, Namibia: community classification and implications for desert vegetation sampling

Plant assemblages were studied in the Pro-Namib Desert Swakop River catchment in Namibia (southern Africa) in order to describe the communities present. Two surveys were conducted: a stratified survey of desert and dry riverbed vegetation and a grid-based survey of desert vegetation alone. In the first survey, ‘very high’ growth forms (plants >150 cm height) were recorded using eight 50 × 50 m quadrats in each of four habitats. In the second survey, all plants except grasses were split into high (plants > 50 cm) and low (plants < 50 cm) growth forms and each recorded using 25 quadrats on five 2·4 km transects (one per 600 m of transect) placed in parallel, 2 km apart (with minimum quadrat size determined by the nested quadrats method). Data from both surveys were analysed using standard classification (TWINSPAN) and ordination (DECORANA) techniques. These analyses were conducted for species and quadrats, both (1) with and without outliers (both cases), and (2) with and without downweighting of rare species (species only). However, the ecological interpretation of the results remained consistent throughout. Results from the stratified survey revealed distinct plant communities; (1) riparian woodland characterized byProsopis glandulosaandSalvadora persica, and (2) desert scrub characterized byAcacia reficiens, Commiphora glaucescensandC. virgata. Sub-communities in desert scrub were also recognized; these were plain and hill assemblages, distinguished by the presence or absence ofPhaeoptilum spinosum, respectively. These communities match geomorphological features of the desert landscape and may reflect differences in the availability of moisture. However, these communities were largely undetectable in the analyses of the grid-based survey dataset, which suggests that the scale of that survey was inadequate for the purpose of classification, despite the attainment of plateaus on the species–area curves for quadrats. These results therefore draw attention to the problems of rarity and scale in the study of desert plant communities.

The Humped Relationship Between Species Richness and Biomass -- Testing its Sensitivity to Sample Quadrat Size

Maximum species richness often occurs at intermediate levels of biomass (Grime 1973a,b, 1979; Al-Mufti et al. 1977), generating a humped relationship between species richness and biomass. This has been attributed to low biomass and low diversity co-occurring in harsh environments, and to intense competition at high biomass reducing species richness (Grime 1979; Abrams 1995). Oksanen (1996) asked whether the pattern might simply be a consequence of a humped relationship between biomass and plant number, combined with a monotonic relationship between plant number and species number. In Oksanen's 'no-interaction' model, both low and high biomass plant communities contain few plants (in a given area), and therefore inevitably contain few species. Oksanen's model requires three assumptions. Few would argue with the first two, which state that plants cannot be infinitely small (and therefore low biomass means few plants), and that large plants occupy more space than small ones (and therefore high biomass also means few plants). The third assumption states that 'the number of plants has an increasing monotonic relation to the number of species', and it is this assumption which we examine in this paper.

Local-density-derived semiempirical nonlocal pseudopotentials for InP with applications to large quantum dots

In the same way that atomic calculations have been used previously to extract bare ionic pseudopotentials, self-consistent bulk calculations can be used to construct screened atomic pseudopotentials. We use such a method to construct screened nonlocal atomic pseudopotentials for InP. A series of bulk, local-density-approximation (LDA) calculations are performed on a few InP crystal structures, covering a range of unit-cell volumes, to produce bulk potentials {${\mathrm{V}}_{\mathrm{LDA}}$ (G)}. By solving a set of linear equations, we extract from these crystalline potentials the corresponding screened atomic 'spherical LDA' (SLDA) potentials ${\mathrm{v}}_{\mathrm{SLDA}}^{\mathrm{\ensuremath{\alpha}}g}$(|q|) for sites \ensuremath{\alpha}=In or P. In combination with the nonlocal part of the usual LDA pseudopotentials, these SLDA potentials give band structures and wave functions that are virtually indistinguishable from the self-consistent LDA results for bulk InP. In the next step, we apply linear changes to the local SLDA potentials (while keeping the nonlocal potentials at their LDA values), to fit the band structures to experiment. Interestingly, this removal of LDA eigenvalue errors requires only small and subtle changes in the potential---mostly an upshift in the region near the cation core, with nearly no change at the bond center. Furthermore, the linear changes to the SLDA potentials result mostly in an upshift of the conduction bands with little effect on the valence bands. Because only small changes in the potential suffice to fit the bands to experimental results, the wave functions remain virtually unchanged relative to those in the original LDA calculation. Hence, we obtain semiempirical pseudopotentials which can produce ab initio LDA-quality wave functions with experimentally measured band structures, effective masses, and deformation potentials. The potentials obtained here were deposited on an FTP site and can be used by interested readers. Since the resulting pseudopotentials are 'soft' (with small high-momentum components), they can be applied within a plane-wave basis in combination with a Gaussian correction to large systems for which LDA calculations are prohibitively expensive. As an illustration, we apply our InP screened atomic pseudopotentials to calculate quantum size effects on the band gaps of InP dots with sizes up to 700 atoms. Good agreement is found between the theoretical and the experimental band gaps. Fitting the calculated band gaps ${\mathrm{E}}_{\mathrm{g}}$ (in unit of eV) versus the effective dot sizes D (in unit of \AA{}) gives ${\mathrm{E}}_{\mathrm{g}}$ =1.45+37.295/${\mathrm{D}}^{1.16}$ . This prediction differs significantly from the quadratic size dependence ${\mathrm{D}}^{\mathrm{\ensuremath{-}}2.0}$ expected from simple effective-mass theory.

Determinants of avian species richness at different spatial scales

ABSTRACT. Studies of factors influencing avian biodiversity yield very different results depending on the spatial scale at which species richness is calculated. Ecological studies at small spatial scales (plot size 0.0025–0.4 km2) emphasize the importance of habitat diversity, whereas biogeographical studies at large spatial scales (quadrat size 400–50,000 km2) emphasize variables related to available energy such as temperature. In order to bridge the gap between those two approaches the bird atlas data set of Lake Constance was used to study factors determining avian species diversity at the intermediate spatial scales of landscapes (quadrat size 4–36 km2). At these spatial scales bird species richness was influenced by habitat diversity and not by variables related to available energy probably because, at the landscape scale, variation in available energy is small. Changing quadrat size between 4 and 36 km2, but keeping the geographical extension of the study constant resulted in profound changes in the degree to which the amount of different habitat types was correlated with species richness. This suggests that high species diversity is achieved by different management regimes depending on the spatial scale at which species richness is calculated. However, generally, avian species diversity seems to be determined by spatial heterogeneity at the corresponding spatial scale. Thus, protecting the diversity of landscapes and ecosystems appears to ensure also high levels of species diversity.

Variance and spatial scales in a tropical rain forest: changing the size of sampling units

The size of a sampling unit has a critical effect on our perception of ecological phenomena; it influences the variance and correlation structure estimates of the data. Classical statistical theory works well to predict the changes in variance when there is no autocorrelation structure, but it is not applicable when the data are spatially autocorrelated. Geostatistical theory, on the other hand, uses analytical relationships to predict the variance and autocorrelation structure that would be observed if a survey was conducted using sampling units of a different size. To test the geostatistical predictions, we used information about individual tree locations in the tropical rain forest of the Pasoh Reserve, Malaysia. This allowed us to simulate and compare various sampling designs. The original data were reorganised into three artificial data sets, computing tree densities (number of trees per square meter in each quadrat) corresponding to three quadrat sizes (5×5, 10×10 and 20×20 m(2)). Based upon the 5×5 m(2) data set, the spatial structure was modelled using a random component (nugget effect) plus an exponential model for the spatially structured component. Using the within-quadrat variances inferred from the variogram model, the change of support relationships predicted the spatial autocorrelation structure and new variances corresponding to 10×10 m(2) and 20×20 m(2) quadrats. The theoretical and empirical results agreed closely, while the classical approach would have largely underestimated the variance. As quadrat size increases, the range of the autocorrelation model increases, while the variance and proportion of noise in the data decrease. Large quadrats filter out the spatial variation occurring at scales smaller than the size of their sampling units, thus increasing the proportion of spatially structured component with range larger than the size of the sampling units.

Species-Area and Species-Individual Relationships for Tropical Trees: A Comparison of Three 50-ha Plots

1 Species-accumulation curves for woody plants were calculated in three tropical forests, based on fully mapped 50-ha plots in wet, old-growth forest in Peninsular Malaysia, in moist, old-growth forest in central Panama, and in dry, previously logged forest in southern India. A total of 610 000 stems were identified to species and mapped to < Im accuracy. Mean species number and stem number were calculated in quadrats as small as 5 m x 5 m to as large as 1000 m x 500 m, for a variety of stem sizes above 10 mm in diameter. Species-area curves were generated by plotting species number as a function of quadrat size; species-individual curves were generated from the same data, but using stem number as the independent variable rather than area. 2 Species-area curves had different forms for stems of different diameters, but species-individual curves were nearly independent of diameter class. With < 10(4) stems, species-individual curves were concave downward on log-log plots, with curves from different forests diverging, but beyond about 104 stems, the log-log curves became nearly linear, with all three sites having a similar slope. This indicates an asymptotic difference in richness between forests: the Malaysian site had 2.7 times as many species as Panama, which in turn was 3.3 times as rich as India. 3 Other details of the species-accumulation relationship were remarkably similar between the three sites. Rectangular quadrats had 5-27% more species than square quadrats of the same area, with longer and narrower quadrats increasingly diverse. Random samples of stems drawn from the entire 50 ha had 10-30% more species than square quadrats with the same number of stems. At both Pasoh and BCI, but not Mudumalai. species richness was slightly higher among intermediate-sized stems (50-100mm in diameter) than in either smaller or larger sizes, These patterns reflect aggregated distributions of individual species, plus weak density-dependent forces that tend to smooth the species abundance distribution and 'loosen' aggregations as stems grow. 4 The results provide support for the view that within each tree community, many species have their abundance and distribution guided more by random drift than deterministic interactions. The drift model predicts that the species-accumulation curve will have a declining slope on a log-log plot, reaching a slope of O.1 in about 50 ha. No other model of community structure can make such a precise prediction. 5 The results demonstrate that diversity studies based on different stem diameters can be compared by sampling identical numbers of stems. Moreover, they indicate that stem counts < 1000 in tropical forests will underestimate the percentage difference in species richness between two diverse sites. Fortunately, standard diversity indices (Fisher's sc, Shannon-Wiener) captured diversity differences in small stem samples more effectively than raw species richness, but both were sample size dependent. Two nonparametric richness estimators (Chao. jackknife) performed poorly, greatly underestimating true species richness.

Multifractal Characterization of the Distribution Pattern of the Human Population

The generalized entropy, calculated from the quadrat counts of the population of the United States and Great Britain, is plotted against the logarithm of the quadrat size. These graphs are linear over a range of scales that corresponds to the size of a city up to the size of the country. This linearity indicates a strong scale‐invariant component to the spatial population distribution pattern. Measurements of the generalized q‐dimensions and alpha spectrum of the spatial population distribution patterns estimated from these graphs are presented.

Estimating the abundance of benthic invertebrates:a comparison of procedures and variability between observers

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 138:93-101 (1996) - doi:10.3354/meps138093 Estimating the abundance of benthic invertebrates: a comparison of procedures and variability between observers Benedetti-Cecchi L, Airoldi L, Abbiati M, Cinelli F Different procedures for underwater sampling of epifaunal organisms were compared for their robustness to bias due to observers and precision using multifactorial sampling designs. Variability among 3 observers was tested in relation to: (1) the method employed to estimate the percent cover of organisms (visual vs point-intercept technique); (2) the size of quadrats (50 x 50 vs 20 x 20 cm); (3) stress (sampling at the beginning vs the end of the dive), and (4) random factors that were likely to change from dive to dive. Precision was expressed in terms of standard errors (over 3 replicates) obtained with each method and size. Two cnidarians (Astroides calycularis and Leptosammia pruvoti) and 2 sponges (Petrosia ficiformis and Geodia cydonium) were considered in this study because of their abundance at the study site (a submarine cave). Much of the variability was related to significant differences between observers that changed from dive to dive for estimates of the cover of A. calycularis, and from dive to dive and with method for L. pruvoti. The small quadrats were more precise than the large ones when used to estimate the percent cover of A. calycularis and L. pruvoti, irrespective of method. In contrast, for P. ficiformis the small quadrats were more precise if sampled with the visual method, while the reverse occurred for the large quadrats. A trend toward a greater precision of the large quadrats sampled with the visual method was evident for G. cydonium, although no significant effects were found. Pilot studies and cost-benefit analyses were also used to determine the optimal allocation of resources (time) for sampling epifaunal organisms at different spatial scales in the cave, for each method and size of quadrats. The small units in conjunction with the visual method were most efficient. This procedure offered the best compromise between repeatability among observers, precision and maximization of replication for a fixed amount of resources. The large quadrats in conjunction with the visual method were probably more adequate for G. cydonium, given the apparent greater precision provided by this procedure for the large sponge. Caution is recommended in employing different researchers working on the same sampling project in extreme environments, at least before divergence among observers to changing environmental conditions is accounted for. Design of sampling . Robustness . Precision . Efficiency . Submarine caves . Invertebrates . Cost-benefit analyses Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 138. Publication date: July 25, 1996 Print ISSN:0171-8630; Online ISSN:1616-1599 Copyright © 1996 Inter-Research.