栽培药材川续断地上部分体积估算的最优样方选择

以贵州省黔南州龙里县内人工栽培的川续断(Dipsacus asperoides)为研究对象, 就如何选择最优样方的面积和数目来估算川续断地上部分体积进行了研究。首先运用球缺模型计算栽培川续断的地上体积, 然后利用基于套状样方的样带调查法研究估算川续断体积时的最优样方面积, 最后利用方差法计算最优采样数目。结果表明: (1)在只考虑相对平均值和相对消耗时, 25 m × 25 m是最优样方面积; 在此基础上进一步考虑到样方的边界效应和单位面积地上体积相对平均值的变化, 得出25 m × 50 m是最优样方面积。(2)如果预计置信度1-α是0.9, 绝对误差限度d是0.12, 总体方差S²按照常规取0.25, 则25 m × 50 m对应的最佳样方数目是25。(3)该研究实际采集了25个25 m × 50 m的样方, 计算后得到整个栽培园地(面积为72696.24 m ²)川续断的总体积90%的近似置信区间为[1909.798 m³, 2214.762 m³]。     

Effects of sampling time,species richness and observer on the exhaustiveness of plant censuses

Question: How may sampling time affect exhaustiveness of vegetation censuses in interaction with observer effect and quadrat species richness? Location: French lowland forests. Methods: Two data sets comprised of 75 timed, one‐hour censuses of vascular plants carried out by five observers on 24 400‐m² forest quadrats were analysed using mixed‐effect models. Results: The level of exhaustiveness increased in a semi‐logarithmic way with sampling time and decreased with quadrat species richness. After one hour, 20 to 30% of the species remained undetected by single observers. This proportion varied among observers and the discrepancy increased with increasing sampling time. Fixing the sampling time may make richness estimates vary less between observers but the time limit should be at least 30 min to reduce the bias in exhaustiveness between rich and poor quadrats. Conclusions We advocate the use of sampling methods based on spatially or temporally‐replicated censuses and statistical analyses that correct for the lack of census exhaustiveness in vegetation studies.     

Optimizing Posidonia oceanica (L.) Delile shoot density: Lessons learned from a shallow meadow

Although shoot patchiness has long been studied in Posidonia oceanica meadows, small scale spatial structure of P. oceanica meadows is poorly known, as very few studies focused on this feature. In order to analyze spatial patterns within P. oceanica meadows that appear uniformly dense and undisturbed, we collected shoot density data at the Capo Rizzuto Marine Protected Area (NE Mediterranean, Italy). Intensive sampling was carried out within a square lattice at small spatial scale (i.e. in the 10⁻¹–10² m² range) and shoot counts were obtained from sample quadrats of different size (60, 40, 20 cm). Spatial data analysis highlighted high irregularity in shoot density from centimetric to larger spatial scales. Therefore the deviation between shoot density estimates obtained using conventional methods and the overall average of quadrat counts (assumed as the best estimate for true density) was never negligible even when larger counting quadrats or higher numbers of replicates were adopted. While shoot density is regarded as the most important property of a P. oceanica meadow and as an indicator of ecosystem health, uncertainty in density estimates and unknown expected errors impair the effectivity of this approach. However, we showed that error could be predicted based on sampling intensity and design in an apparently uniform meadow. Although results from a single case study cannot be generalized, our work is the first attempt at analyzing the problems related to density estimates obtained from shoot counts and it shows how sampling can be optimized to achieve any desired level of accuracy.     

Stipa tenacissima aerial biomass estimated at regional scale in an Algerian steppe, using geostatistical tools

Data from systematic sampling may be independent or autocorrelated. In the latter case geostatistical tools are used to identify the spatial patterns within the universe sampled. Special formulas have been derived by Russo & Bresler (1982) to estimate the variance of a value averaged over several transect samples. We applied these formulas to the green biomass of the dominant perennial steppe grass, Stipa tenacissima or alfa, in a 400 km² region in North-West Algeria; thirty years ago, this region was considered one of the best sites for alfa. A two-level sampling design was implemented with stratification of the region and systematic sampling within each stratum; globally the study included fifteen transects, representing 713 1 m² quadrats. Autocorrelation up to 500 meters was detected in five semi-variograms or correlograms, which were fitted to linear models with a sill. Biomass averaged only 165 (±55) kg ha^-1. We discuss the processes that have lead to the rapid degradation of alfa steppes in northern Algeria and the variation in spatial patterns of alfa stands. Ignoring autocorrelation in systematic sampling leads to biased estimates of variances and standard errors.     

Are Plant Censuses Carried Out on Small Quadrats More Reliable than on Larger Ones?

Plant censuses are known to be significantly affected by observers’ biases. In this study, we checked whether the magnitude of observer effects (defined as the % of total variance) varied with quadrat size: we expected the census repeatability (% of the total variance that is not due to measurement errors) to be higher for small quadrats than for larger ones. Variations according to quadrat size of the repeatability of species richness, Simpson equitability and reciprocal diversity indices, Ellenberg indicator values, plant cover and plant frequency were assessed using 359 censuses of vascular plants. These were carried out independently by four professional botanists during spring 2002 on the same 18 forest plots, each comprising one 400-m² quadrat, four 4-m² and four 2-m² quadrats. Time expenditure was controlled for. General Linear Models using random effects only were applied to the ecological indices to estimate variance components and magnitude of the following effects (if possible): plot, quadrat, observer, plant species and two-way interactions. High repeatability was obtained for species richness and Ellenberg indicator values. Species richness and Ellenberg indicator values were generally more accurate but also more biased in large quadrats. Simpson reciprocal diversity and equitability indices were poorly repeatable (especially equitability) probably because plant cover estimates varied widely among observers, irrespective of quadrat size. Grouping small quadrats usually increased the repeatability of the variable considered (e.g. species richness, Simpson diversity, plant cover) but the number of plant species found on those pooled 16 m² was much lower than if large plots were sampled. We therefore recommend to use large, single quadrats for forest vegetation monitoring.     

Monitoring vegetation change caused by trampling: a study in the Cairngorms,Scotland

Summary

A study was made in the Cairngorms, Scotland to make recommendations for a monitoring scheme capable of detecting changes in the vegetation caused by recreational pressure following the development of a funicular railway. Four methods were used in field trials to assess percentage cover of plant species and gravel, rock and bare ground, where appropriate, in two vegetation types (open and closed). The methods used were visual estimates in 50 × 40 cm quadrats (Q), the mean of visual estimates in twenty 10 × 10 cm sub-quadrats of the 50 × 40 cm quadrats (Q₂₀), a modified point intercept method (RL) and photography. Variances between observers and between-quadrats were estimated for the different methods. The sampling design for detecting change was based on a model of variance, constructed from field trial data.

Between-observer and between-quadrat variances were related to mean percentage cover and approximated to a binomial distribution. The between-quadrat variance was larger than observer variance. The Q₂₀ method achieved appreciably better precision than the other methods. Analysis of half of the 10 × 10 cmsub-quadrats (1/2Q₂₀) selected in a checker board design achieved a relative efficiency of 78% compared with the Q₂₀. This result suggests that comparable precision to the Q₂₀ method could be achieved by choosing about 14 sub-quadrats in a larger quadrat, thus saving some time. Variation between quadrats also suggested that the Q₂₀ method was the one of choice for maximising precision. The precision of the photographic method was based on fewer data points, so is less accurate than other estimates.

Minimum sample sizes were estimated for detecting a 10% relative change of a species in open vegetation with 30% cover (i.e. a change from 30% to <27 or to >33% cover). With a 10 % Type II error rate and 5 % Type I error rate the minimum sample sizes were 47 quadrats for Q, 18 for Q ₂₀, 43 for RL, and 23 for the means of ten 10 × 10 cm sub-quadrats in open vegetation.

The most time-efficient field recording appeared to be the use of Q despite the required sample size being 2.6 times higher than that of Q₂₀. The far lower time requirement per quadrat, however, compensated for the higher numbers. The number of quadrats would depend on the specified change in percentage cover and on the statistical significance level used. For example, to detect a 10% absolute change in cover (i.e. from 30% to either <20 % or >40 % cover) at 95 % probability the net effective recording time is estimated at 5 h per vegetation type while to detect a 5 % change at 99 % probability would require c. 25 h. Larger samples may be required for other species or for species with a low initial cover.     

SPATIAL SCALE OF GENETIC STRUCTURE AND AN INDIRECT ESTIMATE OF GENE FLOW IN EELGRASS,ZOSTERA MARINA

In this study, the first investigation of population structure in an aquatic angiosperm, I show that populations of a marine angiosperm (eelgrass, Zostera marina) are genetically differentiated at a number of spatial scales. I find also that there is no correspondence between geographic and genetic distances separating subpopulations, an increasingly common result in spatially stratified studies of genetic structure in marine invertebrates. F-statistics, calculated for two years from electrophoretic variation at five polymorphic allozyme loci, indicate significant genetic differentiation among sampling quadrats within each of two bays (θ = 0.064-0.208), between tide zones within a bay (θ = 0.025-0.157) and between bays (θ = 0.079). Spatial autocorrelation analysis was used to explore genetic differentiation at smaller spatial scales; estimated patch sizes (within which genetic individuals are randomly associated) indicated no appeciable genetic structure at scales less than 20 m × 20 m. Calculated values of F-statistics were a function of the spatial scale from which samples were drawn: increasing the size of the “subpopulation” included in calculation of fixation indices for the same “total” sample resulted in an increase in the magnitude of f (e.g., from 0.092 to 0.181) and a decrease in θ (e.g., from 0.186 to 0.025). On the basis of the best estimate of the spatial scale of subpopulations, the effective number of migrants per generation (N_em) ranges from 1.1 to 2.8. Genetic consequences of the disturbance regime in the eelgrass habitat sampled were extreme variation between years in the allele richness and proportion of heterozygotes in a sample and a positive relationship between the extinction probability of patches and the genetic variance among them. The changes in F-statistics as a function of sampling scale and the observation that θ among sampled quadrats was positively associated with the probability of extinction among quadrats indicated that indirect estimates of gene flow (N_em) calculated from θ should be cautiously interpreted in populations that may not yet be in drift-migration equilibrium.     

Scale specific determinants of tree diversity in an old growth temperate forest in China

The major processes generating pattern in plant community composition depend upon the spatial scale and resolution of observation, therefore understanding the role played by spatial scale on species patterns is of major concern. In this study, we investigate how well environmental (topography and soil variables) and spatial variables explain variation in species composition in a 25-ha temperate forest in northeastern China. We used new variation partitioning approaches to discover the spatial scale (using multi-scale spatial PCNM variables) at which environmental heterogeneity and other spatially structured processes influence tree community composition. We also test the effect of changing grain of the study (i.e. quadrat size) on the variation partitioning results. Our results indicate that (1) species composition in the Changbai mixed broadleaf-conifer forest was controlled mainly by spatially structured soil variation at broad scales, while at finer scales most of the explained variation was of a spatial nature, pointing to the importance of biotic processes. (2) These results held at all sampling grains. However, reducing quadrat size progressively reduced both spatially and environmentally explained variance. This probably partly reflects increasing stochasticity in species abundances, and the smaller proportion of quadrats occupied by each species, when quadrat size is reduced. The results suggest that environmental heterogeneity (i.e. niche processes) and other biotic processes such as dispersal work together, but at different spatial scales, to build up diversity patterns.     

Habitat niche specialization in an understory species in a warm temperate forest

Relationships between microhabitat variables; understory light conditions in summer and winter, altitude, slope inclination and topographic categories (valley, ridge, and slope) and the distribution of Aucuba japonica Thunb. (Cornaceae), a common understory shrub species in Japan were examined using non-contagious 66, 20 × 20 m² quadrats. The Morishita’s I _δ suggested that A. japonica distributions were strongly heterogeneous among the quadrats. Therefore positive spatial autocorrelation of A. japonica at a within-quadrat level (≤20 m) was obvious. Moran’s I statistics showed a significant positive spatial autocorrelation in A. japonica abundance within the distance shorter than 60 m. But the partial Mantel tests suggested that the mass effect from neighboring quadrats would little explain A. japonica abundance in a quadrat. The partial Mantel tests also clearly showed that A. japonica distributions were strongly structured by topography and understory light conditions. Using Monte Carlo randomization tests, we found that A. japonica was aggregately distributed in quadrats in valley which were covered by deciduous canopies. Better understory light conditions in winter together with valley edaphic conditions may increase the abundance of A. japonica there. It is concluded that habitat niche specialization is important in structuring distribution of A. japonica in this forest community.     

The determination of an optimum sampling technique for biomass of herbaceous vegetation in a Central Australian woodland

The green standing material, dry standing material and litter in the herbaceous layer of a Central Australian woodland were sampled using sets of nested quadrats of various proportions. By minimizing the product of the time required to obtain the data and the relative variances of the mean weights of material, the optimum size of quadrat necessary for estimating biomass was found to be 1 m2 or less. The optimum shape of quadrat for litter was a very elongate rectangle, with the lengths of its sides in the ratio 1:16. There was no preferred shape for green or dry standing material in this case. No edge effect was detected. A method is given for determining the optimum number of quadrats for a known mean, variance and cost.     

Spatial Pattern Analysis of Plant-Parasitic Nematodes

Spatial patterns of Meloidogyne incognita, Tylenchorhynchus claytoni, Helicotylenchus dihystera, and Criconemella ornata were analyzed using Hill''s two-term local quadrat variance method (TTLQV), spectral analysis, and spatial correlation. Data were collected according to a systematic grid sampling plan from seven tobacco fields in North Carolina. Different estimates of nematode cluster size were obtained through TTLQV and spectral analysis. No relationship was observed between either estimate and nematode species, time of sampling (spring vs. fall), or mean density. Cluster size estimates obtained from spectral analysis depended on sampling block size. For each species examined, spatial correlations among nematode population densities were greater within plant rows than across rows, indicating that clusters were ellipsoidal with long axes oriented along plant rows. Analysis of mean square errors indicated that significant gains in sampling efficiency resulted from orienting the long axis of sampling blocks across plant rows. Spatial correlation was greater in the fall than in spring and was greater among 1 × 1-m quadrats than among 3 × 3-m quadrats.     

Six years of submerged plant community dynamics in a freshwater tidal wetland

1. The dynamics of a submerged plant community were studied for 6 years in a freshwater tidal wetland. The degree and nature of change at several spatial scales (quadrat, transect and overall community) was determined, and the implications for community stability were assessed. 2. A high degree of change was recorded in 1 m² quadrats, and this was reflected in 10 m² transects as well. In quadrats, mean species richness changed every year. Species richness changed in >60% of quadrats each year. Stem number changed by as many as several 100 stems per quadrat from one year to the next. 3. Richness varied more among quadrats than among transects and varied less at the community level than among either quadrats or transects. Greater stability at the spatial scale of the whole community was reflected in high scores on the Jaccard and Morasita–Horn indices and Kendall's coefficient of concordance. 4. Although most of the submerged species were perennials, persistence at the local scale was low, and 4‐year persistence exceeded 50% for only one species. Change in abundance was largely independent among the species. 5. In the face of great small‐scale changes, species remain in the community (and the community persists) because of high recruitment rates.     

A probability distribution model of small -scale species richness in plant communities

We devised a probability distribution model that best expressed species richness per quadrat in grassland communities, and clarified the mechanism by which the mean richness per quadrat was always larger than the variance among quadrats. Our model will aid in the understanding of community structures, and allow comparisons among different communities. The model was constructed based on relatively simple theoretical assumptions about the mechanisms in play in target communities. We assumed in the model that the number of species occurring in an actual quadrat, j, is the sum of “the fundamental number of species”, k (constant), and “a fluctuating number of species”, i (a Poisson variate with the mean of μ); that is, j = k + i, where i, j and k are non-negative integers. The probability that j species occur in a quadrat is given by a Poisson-like distribution (extended Poisson), with two parameters k and μ. The mean species richness in the probability distribution is expressed by λ (= k + μ), and the variance is λ − k. The proposed model afforded a good fit for the observed frequency distribution of species richness per quadrat. If even one species is common among many quadrats, the mean number of species per quadrat is greater than the variance. The greater the number of common species among quadrats is, the larger is the value of k, and then the more pronounced is the difference between the mean and the variance (although the variance does not change). We fitted the model to 55 datasets collected by ourselves from grasslands in various locations (Tibet, Inner Mongolia, Slovakia, or Japan), with varying quadrat size (0.25, 0.0625, or 0.01 m²), and under differing management status (various stocking densities).     

塔里木河中下游地区荒漠河岸林群落种间关系分析

采用 2× 2列联表, 应用Fisher精确检验法研究了新疆塔里木河中下游荒漠河岸林群落种间关系, 测定了16种植物、共 12 0个种对的种间联结性。研究结果表明 :1) 12 0个种对中有 17个种对分别在不同的样方尺度中表现出显著或极显著的种间联结, 约占总数的 14.2 % ;其中 13个种对为正关联, 4个种对为负关联 ;2 ) 不同取样面积对种间联结性分析的有效性有影响, 不同种对表现出种间联结的最小样方尺度不同 ;3) 随着样方面积的增大, 各种对自有不同的种间联结变化规律, 可归纳为 4种类型 ;4 ) 17个具种间联结的种对以灌木草本和草本草本的种对居多, 占总数的 76.5 % ;主要乔木树种胡杨 (Populuseuphratica) 与灌木之间、灌木和灌木之间趋向独立分布。     

Inventory and Bioindicator Sampling: Testing Pitfall and Winkler Methods with Ants in a South African Savanna

The sampling efficiency and consistency of pitfall traps and Winkler samples for inventory, bioindicator and ecological studies in savanna habitats was compared using ants. Pitfall traps are often used for ant collecting while Winkler litter sampling has until now had rather limited use. We test Winkler sampling for the first time in a South African savanna. Pitfall traps were more efficient and productive than Winkler sampling for epigaeic ants, with a greater total species richness and higher abundance of ants recorded. Winkler samples contributed few additional species. The relative abundance of different sized ants was different with the two collection methods. Winkler sampling was found to catch greater numbers of smaller ants than pitfall trapping, whereas pitfall trapping caught more larger ants. The standard collecting Winkler quadrat size of 1m² did not perform as well as 2× m² quadrats combined for one sample.     

Effects of canopy gaps on the genetic structure of Camellia japonica saplings in a Japanese old-growth evergreen forest

The genetic structure of Camellia japonica saplings was investigated in relation to canopy conditions in an old-growth evergreen forest in Tsushima, Japan. To elucidate effects of canopy gaps on genetic structure, a 1 ha study site was divided into 20 x 20 m quadrats, which were classified into a gap quadrats (GAP), closed canopy quadrats (CLS) and mixed quadrats. Five GAP quadrats and six CLS quadrats were analyzed separately. Isolation-by-distance was tested by examining the correlation between genetic distance and geographic distance. A significant positive correlation was detected for GAP quadrats, whilst that for CLS quadrats was significantly smaller and not significantly different from zero. On the other hand, an analysis using Moran's I spatial autocorrelation coefficients indicates that the genetic structure is weaker in GAP quadrats than in CLS quadrats in short distance classes. The values were significantly positive for both types of quadrat. These results, along with our field observations on flowering, suggest that canopy gaps affect the genetic structure of C. japonica saplings in two distinct ways. First, canopy gaps may promote flowering and mating in an isolation-by-distance manner within canopy gaps. Second, canopy gaps may promote seed production and resulting overlap in seed shadows may weaken fine-scale genetic structures.     

Sampling techniques and disturbance of algal vegetation in permanent quadrats

Summary In studying permanent quadrats established in an algal vegetation by means of sampling in the quadrat itself, the vegetation is exposed to the risk of disturbance by the sampling. By taking small samples (microsampling or reduced size sampling) this risk is reduced considerably. The quantitative minimal area of vegetation units ofVaucheria, filamentous green algae and Oscillatoriaceae is less than 20 mm². InVaucheria components, however, often the viability for cultivation purposes is the limiting factor for the size of a sample suitable for a complete analysis of the permanent quadrat. The minimum size of a viableVaucheria sample is 1 cm². The disturbance of the algal layer by other external factors is often more intense than that caused by sampling. Nomenclature follows Polderman (1975b). Contribution to the Symposium of the Working Group for Succession Research on Permanent Plots, held at Yerseke, The Netherlands, October 1975. The author thanks Dr. Ir. W. G. Beeftink for helpful criticism and Mrs. R.A. Polderman-Hall for correcting the English text. The investigation of the algal communities of saltmarshes in the Wadden area is a project of the Netherlands Organisation for the Advancement of Pure Research.     

Effect of inventory plot patterns in the floristic analysis of tropical woodland and dense forest

This study was set up to examine the effect of plot patterns on the accuracy of phytosociological characterization of tropical vegetation. Fifteen and twenty square plots of 1 ha were demarcated, respectively, in woodland and dense forest in Bénin. Each 1 ha plot was divided into 100 quadrats of one 100 m². Species of trees in each quadrat were identified and recorded. The cost in terms of time required to record tree species in each 1 ha plot and five random quadrats in a 1 ha plot were also recorded to compute the mean inventory effort for a team of three foresters. From the 100 quadrats in a 1 ha plot, fourteen independent subplots of square and rectangular plots with different sizes were considered by grouping together adjacent quadrats of 100 m². Eigenanalysis was carried out to compare the subplots. Moreover, the relationship between the relative loss of accuracy (RLA) and the size of subplots was modelled. Plot size highly influenced the RLA (P < 0.05). Findings indicated that the square plots of 1500 and 1000 m² with an inventory effort of 0.35 and 0.20 man‐days per subplot, respectively in tropical dense forests and woodlands appeared to be the most efficient in the phytosociological characterization of woody vegetation.     

Variogram analysis of the spatial genetic structure of continuous populations using multilocus microsatellite data

A geostatistical perspective on spatial genetic structure may explain methodological issues of quantifying spatial genetic structure and suggest new approaches to addressing them. We use a variogram approach to (i) derive a spatial partitioning of molecular variance, gene diversity, and genotypic diversity for microsatellite data under the infinite allele model (IAM) and the stepwise mutation model (SMM), (ii) develop a weighting of sampling units to reflect ploidy levels or multiple sampling of genets, and (iii) show how variograms summarize the spatial genetic structure within a population under isolation-by-distance. The methods are illustrated with data from a population of the epiphytic lichen Lobaria pulmonaria, using six microsatellite markers. Variogram-based analysis not only avoids bias due to the underestimation of population variance in the presence of spatial autocorrelation, but also provides estimates of population genetic diversity and the degree and extent of spatial genetic structure accounting for autocorrelation.     

Colony expansion model for describing the spatial distribution of populations

Two equations have been used frequently to describe the relation between the sample variance (s ²) and sample mean (m) of the number of individuals per quadrat: Taylor's power law, s ² = am ^b , and Iwao's m ^*−m regression, s ² = cm + dm ², where a, b, c, and d are constants. We can obtain biological information such as colony size and the degree of aggregation of colonies from parameters c and d of Iwao's m ^*−m regression. However, we cannot obtain such biological information from parameters a and b of Taylor's power law because these parameters have not been described by simple functions. To mitigate such in-convenience, I propose a mechanistic model that produces Taylor's power law; this model is called the colony expansion model. This model has the following two assumptions: (1) a population consists of a fixed number of colonies that lie across several quadrats, and (2) the number of individuals per unit occupied area of colony becomes v times larger in an allometric manner when the occupied area of colony becomes h times larger (v≥ 1, h≥ 1). The parameter h indicates the dispersal rate of organisms. We then obtain Taylor's power law with b = {ln[E(h)] + ln[E(v ²)]}/{ln[E(h)] + ln[E(v)]}, where E indicates the expectation. We can use the inverse of the exponent, 1/b, as an index of dispersal of individuals because it increases with increasing E(h). This model also yields a relation, known as the Kono–Sugino relation, between the proportion of occupied quadrats and the mean density per quadrat: −ln(1 −p) = fm ^g , where p is the proportion of occupied quadrats, f is a constant, and g = ln[E(h)]/{ln[E(h)] + ln[E(v)]}. We can use g as an index of dispersal as it increases with increasing E(h). The problem at low densities where Taylor's power law is not applicable is also discussed. Received: January 27, 2000 / Accepted: June 20, 2000