Tree dispersion in oak-dominated forests along an environmental gradient

Summary Spatial pattern was analyzed in seventeen stands of oak-dominated forest to address the hypothesis that species tended to be aggregated under favorable conditions and widely spaced in xeric, nutrient poor conditions. Trees were sampled at 80–100 points in each stand with the distance-to-nearest neighbor method. Soil samples were collected in each stand for analysis of total nitrogen, total phosphorus, total potassium, soil pH, soil texture, and soil organic matter. Growing season precipitation was also recorded from climate stations near each stand. Quercus stellata (Wang.) dominated 10 stands, Q. marilandica (Muenchh.) dominated three stands and these species were codominant in four stands. Principal components analysis identified a soil texture/fertility gradient across the study area. Quercus stellata and all species combined were aggregated in most stands, whereas Q. marilandica was mostly randomly distributed within a stand. Small trees of all species combined tended to be aggregated and large trees were randomly dispersed in all but two stands, suggesting competition. Mean distance between large-large pairs was always greater than mean distance between small-small pairs in all stands, but this difference was only significant in one stand. Correlations between nearest neighbor distance and combined size of nearest neighbors were significant and positive in 12 of 17 stands. In all cases, however, slopes were shallow suggesting that competition is weak in these communities and has a limited effect on spacing of neighboring trees. Contrary to our hypothesis, trees were more aggregated on coarse-textured soils with low organic matter content. For all species combined, degree of aggregation was unrelated to growing season precipitation. Aggregation appears to be common in these forests because environmental stress in many stands reduces growth rates. Trees have not yet reached a size at which competition or other interactions can greatly increase interplant distances and reduce the degree of aggregation. A simple graphical model is developed to describe the relationship between patterns, stress and competition in plant communities.     

荒漠草原不同土壤条件下猪毛蒿幼苗种群的点格局分析

采用摄影定位法测定了宁夏荒漠草原3种不同土壤条件下猪毛蒿（Artemisia scoparia）幼苗种群的空间格局,并应用完全空间随机模型、泊松聚块模型和嵌套双聚块模型对其分布格局进行了分析。结果表明：（1）在灰钙土生境下,猪毛蒿幼苗种群在小尺度上（0-2.85m）表现为聚集分布,随着尺度的增大先呈现为随机分布（2.85-3.75 m）,然后又呈现为均匀分布（3.75-5m）;在风沙土生境下,猪毛蒿幼苗种群在0-1.85 m之间表现为聚集分布,在1.85-2.35 m之间表现为随机分布,当尺度大于2.35 m时表现为均匀分布;而基岩风化残积土上的猪毛蒿幼苗种群在整个尺度上均呈现随机分布。（2）猪毛蒿种群幼苗在基岩风化残积土上符合泊松聚块模型,即猪毛蒿种群空间格局的聚块中不存在较高密度的小聚块;而在风沙土和灰钙土上则符合嵌套双聚块模型,即在大聚块中分布较高密度的小聚块。猪毛蒿幼苗种群空间格局的形成与土壤异质性存在着密切的联系,种群在空间中分布格局的形成机制可以通过种群空间格局的分析加以解释。     

从空间分布特征认识珍稀植物领春木的种群动态

领春木(Euptelea pleiosperrnum)系第三纪孑遗植物和东亚特有种,目前已被列为国家Ⅲ级重点保护植物.基于空间定位数据以最近邻体距离统计研究了神农架地区领春木的空间分布特征,比较幼苗(DBH≤2.5cm)、幼树(2.5～7.5cm)和成树(＞7.5cm)各径级(代表各生活史阶段)形成的时间序列上的空间格局差异,进而探讨空间格局与立苗、补员、种内竞争等种群动态过程的相互关系.结果显示,在邻域尺度上,领春木的空间格局呈聚集态;幼苗(或幼树)的大小与其距离最近幼树(或成树)的远近没有相关性,幼树(或成树)周围一定距离以内出现同等大小个体的概率约等于幼苗(或幼树)出现的概率,且幼树与最近幼苗(或成树与最近幼树)的平均距离与幼树之间(或成树之间)的平均最近邻体距离没有显著差异;任意个体的大小、任意个体与相应最近邻体的大小之和与相应的最近邻体距离均为显著的正相关关系,但幼树间的最近邻体距离并不大于幼苗随机死亡产生的最近邻体距离,成树间最近邻体距离也不大于幼苗+幼树随机死亡产生的最近邻体距离.这些结果表明,领春木的聚集分布可能与种子散布、生境异质性对立苗格局的作用有关;已定植的大个体可能不限制其邻域内小个体的布局与生长,但是长期的补员过程与邻体间的相互作用不无关系;邻体间存在一定程度的竞争作用,但是竞争强度并未充分激化至发生距离依赖的死亡.     

?2\sqrt 2 Rule for Controlling the Tree Pattern in Forest Cut

A forest’s productivity can be optimized by the application of rules derived from monopolized circles. A monopolized circle is defined as a circle whose center is a tree and whose radius is half of the distance between the tree itself and its nearest neighbor. Three characteristics of monopolized circle are proved. (1) Monopolized circles do not overlay each other, the nearest relationship being tangent. (2) “Full uniform pattern” means that the grid of trees (a×b=N) covers the whole plot, so that the distance between each tree in a row is the same as the row spacing. The total monopolized circle area with a full uniform pattern is independent on the number of trees and times the plot area. (3) If a tree is removed, the area of some trees’ monopolized circle will increase without decreasing the monopolized circles of the other trees. According to the above three characteristics, “uniform index” is defined as the total area of monopolized circles in a plot divided by the total area of the monopolized circles, arranged in a uniform pattern in the same shaped plot. According to the definition of monopolized circle, the distribution of uniform index for a random pattern and the variance of L is . It is evident that E(L) is independent on N and the plot area; hence, L is a relative index. L can be used to compare the uniformity among plots with different areas and the numbers of trees. In a random pattern, where L is equivalent to the tree density of the plot in which the number of trees is 1 and the area is π, the influence of tree number and plot area to L is eliminated. When n→∞, D(L)→0 and it indicates that the greater the number of tree is in the plots, the smaller the difference between the uniform indices will be. There are three types of patterns for describing tree distribution (aggregated, random, and uniform patterns). Since the distribution of L in the random pattern is accurately derived, L can be used to test the pattern types. The research on Moarshan showed that the whole plot has an aggregated pattern; the first, third, and sixth parts have an aggregated pattern; and the second, fourth, and fifth parts have a random pattern. None of the uniform indices is more than 0.318 (1/∏), which indicates that uniform patterns are rare in natural forests. The rules of uniform index can be applied to forest thinning. If you want to increase the value of uniform index, you must increase the total area of monopolized circles, which can be done by removing select trees. “Increasing area trees” are the removed trees and can increase the value of the uniform index. A tree is an increasing area tree if the distance between the tree and its second nearest neighbor is times longer than that between the tree itself and its first nearest neighbor, which is called the rule. It was very interesting to find that when six plots were randomly separated from the original plot, the proportion of increasing area trees in each plot was always about 0.5 without exception. In random pattern, the expected proportion of increasing area trees is about 0.35–0.44, which is different from the sampling value of 0.5. The reason is very difficult to explain, and further study is needed. Two criteria can be used to identify which trees should be removed to increase the uniform index during forest thinning. Those trees should be (1) trees whose monopolized circle areas are on the small side and (2) increasing area trees, which are found via the rule. Translated from Acta Ecologica Sinica, 2005, 25(1) (in Chinese)     

植物空间分布格局中邻体距离的概率分布模型及参数估计

最近邻体法是一类有效的植物空间分布格局分析方法,邻体距离的概率分布模型用于描述邻体距离的统计特征,属于常用的最近邻体法之一。然而,聚集分布格局中邻体距离(个体到个体)的概率分布模型表达式复杂,参数估计的计算量大。根据该模型期望和方差的特性,提出了一种简化的参数估计方法,并利用遗传算法来实现参数优化,结果表明遗传算法可以有效地估计的该模型的两个参数。同时,利用该模型拟合了加拿大南温哥华岛3个寒温带树种的空间分布数据,结果显示:该概率分布模型可以很好地拟合美国花旗松(P.menziesii)和西部铁杉(T.heterophylla)的邻体距离分布,但由于西北红柏(T.plicata)存在高度聚集的团簇分布,拟合结果不理想;美国花旗松在样地中近似随机分布,空间聚集参数对空间尺度的依赖性不强,但西北红柏和西部铁杉空间聚集参数具有尺度依赖性,随邻体距离阶数增加而变大。最后,讨论了该模型以及参数估计方法的优势和限制。     

Social Aggregation in Pea Aphids: Experiment and Random Walk Modeling

From bird flocks to fish schools and ungulate herds to insect swarms, social biological aggregations are found across the natural world. An ongoing challenge in the mathematical modeling of aggregations is to strengthen the connection between models and biological data by quantifying the rules that individuals follow. We model aggregation of the pea aphid, Acyrthosiphon pisum. Specifically, we conduct experiments to track the motion of aphids walking in a featureless circular arena in order to deduce individual-level rules. We observe that each aphid transitions stochastically between a moving and a stationary state. Moving aphids follow a correlated random walk. The probabilities of motion state transitions, as well as the random walk parameters, depend strongly on distance to an aphid''s nearest neighbor. For large nearest neighbor distances, when an aphid is essentially isolated, its motion is ballistic with aphids moving faster, turning less, and being less likely to stop. In contrast, for short nearest neighbor distances, aphids move more slowly, turn more, and are more likely to become stationary; this behavior constitutes an aggregation mechanism. From the experimental data, we estimate the state transition probabilities and correlated random walk parameters as a function of nearest neighbor distance. With the individual-level model established, we assess whether it reproduces the macroscopic patterns of movement at the group level. To do so, we consider three distributions, namely distance to nearest neighbor, angle to nearest neighbor, and percentage of population moving at any given time. For each of these three distributions, we compare our experimental data to the output of numerical simulations of our nearest neighbor model, and of a control model in which aphids do not interact socially. Our stochastic, social nearest neighbor model reproduces salient features of the experimental data that are not captured by the control.     

\sqrt 2 Rule for Controlling the Tree Pattern in Forest Cut

A forest’s productivity can be optimized by the application of rules derived from monopolized circles. A monopolized circle is defined as a circle whose center is a tree and whose radius is half of the distance between the tree itself and its nearest neighbor. Three characteristics of monopolized circle are proved. (1) Monopolized circles do not overlay each other, the nearest relationship being tangent. (2) “Full uniform pattern” means that the grid of trees (a×b=N) covers the whole plot, so that the distance between each tree in a row is the same as the row spacing. The total monopolized circle area with a full uniform pattern is independent on the number of trees and $\frac{\pi }{4}$ times the plot area. (3) If a tree is removed, the area of some trees’ monopolized circle will increase without decreasing the monopolized circles of the other trees. According to the above three characteristics, “uniform index” is defined as the total area of monopolized circles in a plot divided by the total area of the monopolized circles, arranged in a uniform pattern in the same shaped plot. According to the definition of monopolized circle, the distribution of uniform index $(L) = \frac{{\chi ^2 (2n)}}{{2\pi n}}$ for a random pattern and $E(L) = \frac{1}{\pi }$ the variance of L is $D(L) = \frac{1}{{n\pi ^2 }}$ . It is evident that E(L) is independent on N and the plot area; hence, L is a relative index. L can be used to compare the uniformity among plots with different areas and the numbers of trees. In a random pattern, where L is equivalent to the tree density of the plot in which the number of trees is 1 and the area is π, the influence of tree number and plot area to L is eliminated. When n→∞, D(L)→0 and $L \to \frac{1}{\pi } = 0.318$ it indicates that the greater the number of tree is in the plots, the smaller the difference between the uniform indices will be. There are three types of patterns for describing tree distribution (aggregated, random, and uniform patterns). Since the distribution of L in the random pattern is accurately derived, L can be used to test the pattern types. The research on Moarshan showed that the whole plot has an aggregated pattern; the first, third, and sixth parts have an aggregated pattern; and the second, fourth, and fifth parts have a random pattern. None of the uniform indices is more than 0.318 (1/∏), which indicates that uniform patterns are rare in natural forests. The rules of uniform index can be applied to forest thinning. If you want to increase the value of uniform index, you must increase the total area of monopolized circles, which can be done by removing select trees. “Increasing area trees” are the removed trees and can increase the value of the uniform index. A tree is an increasing area tree if the distance between the tree and its second nearest neighbor is $\sqrt 2 $ times longer than that between the tree itself and its first nearest neighbor, which is called the $\sqrt 2 $ rule. It was very interesting to find that when six plots were randomly separated from the original plot, the proportion of increasing area trees in each plot was always about 0.5 without exception. In random pattern, the expected proportion of increasing area trees is about 0.35–0.44, which is different from the sampling value of 0.5. The reason is very difficult to explain, and further study is needed. Two criteria can be used to identify which trees should be removed to increase the uniform index during forest thinning. Those trees should be (1) trees whose monopolized circle areas are on the small side and (2) increasing area trees, which are found via the $\sqrt 2 $ rule.     

Denaturation and renaturation of DNA. I. Equilibrium statistics of copolymeric DNA

The one-dimensional Ising model, with nearest neighbor correlation only, suitably modified, is used to explain the observed linear dependence of melting temperature of copolymeric DNA with GC content. Transition curves are plotted for regular, random, and Markoff distribution of base pairs for various values of a correlation parameter U between nearest neighbor bonds. Exact analytic formulas are given for fraction of bonds intact at a particular temperature for various regular distributions for all U and approximate ones for random and Markoff distributions for small U. A scheme is indicated for further improvement. The model, in principle, makes it possible to estimate the statistical distribution of base pairs from the detailed shape of the transition curve.     

Changes in growth and maturation parameters of Pacific sardine Sardinops sagax collected off California during a period of stock recovery from 1994 to 2010

Whether fluctuation in density influenced the growth and maturation variables of three aggregated cohorts (fish born during the 1986–1993, 1996–2003 and 2004–2008 periods) of Pacific sardine Sardinops sagax caeruleus collected off the Californian coast from 2004 to 2010 was investigated. Using a von Bertalanffy mixed‐effects model with aggregated cohorts as covariates, estimated growth rate significantly covaried with aggregated cohorts. Growth rate (K) was modelled as a fixed effect and estimated to be 0·264 ± 0·015 (±s.e ). Statistical contrasts among aggregated cohorts showed that the 1996–2003 cohorts had a significantly lower growth rate than the other two aggregated cohorts. The theoretical age at length zero (t₀) and the standard length at infinity (L_S∞) were modelled as random effects, and were estimated to be ?2·885 ± 0·259 (±s.e ) and 273·13 ± 6·533 mm (±s.e ). The relation of ovary‐free mass at length was significantly different among the three aggregated cohorts, with the allometric coefficient estimated to be 2·850 ± 0·013 (±s.e ) for the S. sagax population. The age‐at‐length trajectory of S. sagax born between 1986 and 2008 showed strong density dependence effects on somatic growth rates. In contrast to the density‐dependent nature of growth, the probability to be mature at‐size or at‐age was not significantly affected by aggregated cohort density. The size and the age‐at‐50% maturity were estimated to be 150·92 mm and 0·56 years, respectively. Stock migration, natural fluctuations in biomass and removal of older and larger S. sagax by fishing might have been interplaying factors controlling growth parameters during 1986–2010.     

√2 Rule for Controlling the Tree Pattern in Forest Cut

A forest's productivity can be optimized by the application of rules derived from monopolized circles.A monopolized circle is defined as a circle whose center is a tree and whose radius is half of the distance between the tree itself and its nearest neighbor.Three characteristics of monopolized circle are proved.(1) Monopolized circles do not overlay each other,the nearest relationship being tangent.(2)"Full uniform pattern"means that the grid of trees (a×=N) covers the whole plot,so that the distance between each tree in a row is the same as the row spacing.The total monopolized circle area with a full uniform pattern is independent on the number of trees and π/4 times the plot area.(3) If a tree is removed,the area of some trees'monopolized circle will increase without decreasing the monopolized circles of the other trees.According to the above three characteristics,"uniform index"is defined as the total area of monopolized circles in a plot divided by the total area of the monopolized circles,arranged in a uniform pattern in the same shaped plot.According to the definition of monopolized circle,the distribution of uniform index (L) = x2(2n)/2πn for a random pattern and E(L)=1/π;the variance of L is D(L)=1/nπ2.It is evident that E(L) is independent on N and the plot area;hence,L is a relative index.L can be used to compare the uniformity among plots with different areas and the numbers of trees.In a random pattern,where L is equivalent to the tree density of the plot in which the number of trees is 1 and the area is π,the influence of tree number and plot area to L is eliminated.When n→∞,D(L)→0 and L→1/π= 0.318;it indicates that the greater the number of tree is in the plots,the smaller the difference between the uniform indices will be.There are three types of patterns for describing tree distribution (aggregated,random,and uniform patterns).Since the distribution of L in the random pattern is accurately derived,L can be used to test the pattern types.The research on Moarshan showed that the whole plot has an aggregated pattern;the first,third,and sixth parts have an aggregated pattern;and the second,fourth,and fifth parts have a random pattern.None of the uniform indices is more than 0.318 (1/Ⅱ),which indicates that uniform patterns are rare in natural forests.The rules of uniform index can be applied to forest thinning.If you want to increase the value of uniform index,you must increase the total area of monopolized circles,which can be done by removing select trees."Increasing area trees"are the removed trees and can increase the value of the uniform index.A tree is an increasing area tree if the distance between the tree and its second nearest neighbor is √2 times longer than that between the tree itself and its first nearest neighbor,which is called the √2 rule.It was very interesting to find that when six plots were randomly separated from the original plot,the proportion of increasing area trees in each plot was always about 0.5 without exception.In random pattern,the expected proportion of increasing area trees is about 0.35-0.44,which is different from the sampling value of 0.5.The reason is very difficult to explain,and further study is needed.Two criteria can be used to identify which trees should be removed to increase the uniform index during forest thinning.Those trees should be (1) trees whose monopolized circle areas are on the small side and (2) increasing area trees,which are found via the √2 rule.     

Evaluating sampling designs by computer simulation: a case study with the Missouri bladderpod

To effectively manage rare populations, accurate monitoring data are critical. Yet many monitoring programs are initiated without careful consideration of whether chosen sampling designs will provide accurate estimates of population parameters. Obtaining accurate estimates is especially difficult when natural variability is high, or limited budgets determine that only a small fraction of the population can be sampled. The Missouri bladderpod, Lesquerella filiformis Rollins, is a federally threatened winter annual that has an aggregated distribution pattern and exhibits dramatic interannual population fluctuations. Using the simulation program SAMPLE, we evaluated five candidate sampling designs appropriate for rare populations, based on 4 years of field data: (1) simple random sampling, (2) adaptive simple random sampling, (3) grid-based systematic sampling, (4) adaptive grid-based systematic sampling, and (5) GIS-based adaptive sampling. We compared the designs based on the precision of density estimates for fixed sample size, cost, and distance traveled. Sampling fraction and cost were the most important factors determining precision of density estimates, and relative design performance changed across the range of sampling fractions. Adaptive designs did not provide uniformly more precise estimates than conventional designs, in part because the spatial distribution of L. filiformis was relatively widespread within the study site. Adaptive designs tended to perform better as sampling fraction increased and when sampling costs, particularly distance traveled, were taken into account. The rate that units occupied by L. filiformis were encountered was higher for adaptive than for conventional designs. Overall, grid-based systematic designs were more efficient and practically implemented than the others. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

INFLUENCE OF THE MULTILAYERED STRUCTURE ON THE MORPHOGENESIS OF MARCHANTIA SPERMATIDS

The multilayered structure (MLS) in a spermatid of Marchantia is the morphogenetic blueprint of the headpiece in a mature sperm. As the nucleus begins elongation, a curved, tapered nuclear projection follows the path of microtubules extending from the MLS and becomes inserted into an indented zone at the rear of the asymmetric organelle. The indented zone defines the most forward penetration of the nucleus into the sperm headpiece. Partial disorganization of MLS lower strata nearest the nuclear projection facilitates overlapping of the nucleus with the rearward part of the anterior mitochondrion. At the front of the nascent headpiece, the mitochondrion is stabilized against microtubules following total disorganization of intervening MLS strata. Penetration of the nuclear projection along the MLS and directed disorganization of MLS lower strata control ultimate disposition of headpiece components. The headpiece is isolated and molded into final shape by undercutting and constriction of the cell membrane.     

种群分布格局的多尺度分析

种群分布格局的分析对于了解种群空间分布规律以及种内与种间关系具有重要的意义。最近邻体分析方法 (Nearestneighboranalysis, NNA) 作为种群空间分布格局的重要分析方法, 仅局限于种群格局的单尺度分析。改进NNA方法以应用于种群格局的多尺度分析, 将有助于解决种群格局的尺度依赖性。该文在前人研究的基础上提出扩展最近邻体分析方法 (Extendednearestneighboranalysis, ENNA), 也即在传统Clark_Evans指数公式的基础上增加一个距离尺度参数d (m), 并定义其所对应的Clark_Evans 指数CE (d) 的计算公式及其相应的显著性检验计算公式 (u (d) ) 分别为 :CE (d) =rdA/rdE= (1Nd∑Ndi=1 rdi) / (0.5Ad/Nd+0.0 5 14Pd/Nd+0.0 4 1Pd/Nd3 /2 ) 和u (d) = (rdA-rdE) /σd, 在距离尺度d (m) 范围内, 参数rdA指样地内各个体与其最近邻体间距离的平均值 (m) 、rdE指相同环境中个体呈随机状态时最近邻体距离的平均值 (m) 、Nd 为样地内个体总数、rdi为第i个个体与其最近邻体间的距离 (m) 、Ad 为样地面积 (m2 ) 、Pd 为样地周长 (m) 和σd 代表标准差。ENNA尺度变换采用与分形理论中计算沙盒维数相类似的过程, 而格局类型判断的标准与传统最近邻体分析方法相同。传统最近邻体分析结果是EN NA中距离尺度d取最大值dmax时的一个特例。以广东省黑石顶自然保护区针阔叶混交林中的马尾松 (Pinusmas soniana) 、黄牛奶树 (Symplocoslaurina) 、水栗 (Castanopsisnigrescens) 、鼠刺 (Iteachinensis) 和桃金娘 (Rhodomyrtustomentosa) 等 5个代表性种群为例, 在地理信息系统软件ArcViewGIS技术平台上进行的实例研究显示, 5个种群均表现出不同程度的尺度相关性。由此表明, 该文提出的新方法ENNA能够检测出种群空间分布格局的尺度依赖性, 获得关于种群空间分布格局的多尺度信息, 是进行种群空间格局多尺度分析的有效方法。     

Spatial arrangement and diet overlap between colonies of desert ants

Summary The spatial patterns and diets of three desert ant species were examined. The results indicate that food competition may account for the spatial arrangement of these species, and that only intraspecific interactions may be required. Each ant species was significantly overdispersed, and the average intraspecific nearest neighbor distances were greater than the interspecific nearest neighbor distances. A test of pairwise spatial arrangment showed that all three species pairs were aggregated interspecifically. The level of the interspecific aggregation was related to the diet similarity of the species. The two species pairs with the lowest diet overlaps were significantly aggregated, and the species pair with the most similar diets was not significantly aggregated. Pairwise dietary overlaps between colonies showed that average intraspecific overlaps were significantly greater than interspecific diet overlaps. Furthermore, the diet overlap was significantly positively correlated to the mean nearest neighbor distance for the three intraspecific and three interspecific comparisons. These data indicate competition for food, especially within species, may be regulating the intercolony distances of these ant species. A computer simulation tested whether only intraspecific territoriality is necessary to produce the observed nearest neighbor distances. A simulation that placed colonies randomly on a patch confirmed that these colonies are intraspecifically overdispersed. By adding intraspecific territoriality, the simulation nearest neighbor distances fit the empirical data reasonably well. Thus interspecific competitive interactions seem unnecessary to account for the spatial arrangement of these species.     

MORPHOLOGICAL FLEXIBILITY OF COCCONEIS PLACENTULA (BACILLARIOPHYCEAE) NANOSTRUCTURE TO CHANGING SALINITY LEVELS1

Diatoms possess a silica frustule decorated with unique patterns of nanosize features. Here, we show for the first time from in situ samples that the size of the nanopores present at the surface of the diatom Cocconeis placentula Ehrenb. varies with fluctuating salinity levels. The observed reduction in nanopore size with decreasing salinity agrees with previous laboratory experiments. We also uniquely combined our observations with theoretical considerations to demonstrate that the decrease in the diffusive layer thickness is compensated for by the changes in pore size, which maintain a steady diffusive flux toward the diatom’s cell at different salinities. This process allows diatoms to absorb similar amount of nutrients whatever the salinity and as such to increase their ecological competitiveness in fluctuating environments. These results further suggest that the overall ecological success of diatoms, and their ability to react to environmental changes, may be controlled by the flexibility of the morphological characteristics of their frustules.     

Contrasting scales of oviposition and parasitism in praying mantids

We report on spatial patterns of parasitism of oothecae (egg cases) of praying mantises (Stagmomantis limbata) by torymid wasps, Podagrion spp. Using collections of mapped mantid oothecae from Riparian sites in the Sonoran desert and Grassland sites in the Chiricahua Mountains (both in Arizona, USA), we characterized the spatial distributions of oothecae and parasitism. The likelihood of an egg case suffering some parasitism was higher at Grassland sites, which had high oothecal densities, than at low-density Riparian sites. However, experimental isolation of Grassland oothecae to densities comparable to Riparian sites reduced parasitism rates. At Riparian sites, parasitized oothecae exhibited on average the same extent of parasitism as parasitized oothecae at high densities but with much greater variation. Indeed, large fractions of Riparian oothecae suffered both severe (>50%) and light (<20%) parasitism, whereas most parasitized Grassland oothecae suffered intermediate levels of parasitism. Analysis of first nearest neighbor distances indicated that the parasite load of an ootheca did not depend on its immediate isolation. However, extending the analysis to include subsequent nearest neighbors (using a technique from spatial statistics called the R(K) function), we found that even though oothecae of S. limbata were spatially clustered, some oothecae in a (statistically defined) cluster escaped parasitism when overall oothecal densities were low. This pattern suggests that when oothecae are sparsely distributed, Podagrion wasps exploit only a fraction of the oothecae available locally, even though the oothecae are strongly aggregated relative to their overall density. We suggest this lack of congruency in the scales of oothecal deposition and parasitism at low densities (which is absent when oothecae are at high densities) may be explained in part by behavioral aspects of the parasite's reproduction, including increased host fidelity by relatively sedentary female parasites. Received: June 13, 2000 / Accepted: October 16, 2000     

Properties of the nearest neighbor interchange metric for trees of small size

The crossover or nearest neighbor interchange metric has been proposed for use in numerical taxonomy to obtain a quantitative measure of distance between classifications that are modeled as unrooted binary trees with labeled leaves. This metric seems difficult to compute and its properties are poorly understood. A variant called the closest partition distance measure has also been proposed, but no efficient algorithm for its computation has yet appeared and its relationship to the nearest neighbor interchange metric is incompletely understood. I investigate four conjectures concerning the nearest neighbor interchange and closest partition distance measures and establish their validity for trees with as many as seven labeled vertices. For trees in this size range the two distance measures are identical. If a certain decomposition property holds for the nearest neighbor interchange metric, then the two distance measures are also identical at small distances for trees of any size.     

Spatial Characteristics of the Invasion of Acer platanoides on a Temperate Forested Island

We examined the spatial pattern of an introduced population of Norway maple (Acer platanoides L.) on a temperate forested island in order to quantify the influence of landscape context on invasion pattern. The spatial location of every Norway maple tree and sapling (≥0.5 m tall) that had invaded the island forest (n = 4496) was mapped using a global positioning system. The influence of landscape context was examined with the aid of a geographic information system and indices of spatial association. We found that the coniferous forest type was the most heavily invaded (71.9% of all Norway maple stems) when compared to either the hardwood or mixed conifer–hardwood forest types (5.4% and 19.3%, respectively). Across all forest types (excluding urban trees), the population was highly aggregated around roads and other Norway maple trees. For example, 90% of the population was within 40.8 m of a road with an average distance from road of 21.02 ± 0.40 m. This association around roads was significantly greater than would be predicted by chance alone (P < 0.001). Similarly, nearest neighbor distances averaged 4.5 ± 0.2 m with 90% of individuals within 8.3 m of another Norway maple. Measures of spatial association indicated that the invasion was significantly aggregated at both the stand and island scale. Nevertheless, a comparatively small but potentially influential set of individuals were observed at relatively long distances from the main invasion front. Ramifications of these disjunct establishments and other observed patterns are discussed in the context of current spread pattern theory, invasive species monitoring, and control efforts.     

ROLE OF LIGHT AND THE CELL CYCLE ON THE INDUCTION OF SPERMATOGENESIS IN A CENTRIC DIATOM1

The centric diatom, Thalassiosira weissflogii Grun., can be induced to undergo spermatogenesis by exposing cells maintained at saturating levels of continuous light to either dim light or darkness. Using flow cytometry to determine the relative DNA and chlorophyll content per cell, the number of cells within a population that responded to and induction signal was measured. From 0 to over 90% of a population differentiated into male gametes depending upon both the induction trigger and the population examined, regardless of the average cell size of the population. Through the use of synchromized cultures, we demonstrated that responsiveness to an induction trigger was a function of cell cycle stage; cells in early G₁ were not yet committed to complete mitosis and were induced to form male gametes, whereas cells further along in their cell cycle were unresponsive to these same cues. A simple model combining the influence of light on the mitotic cell cycle and on the induction of spermatogenesis is proposed to explain the observed diversity in population responses to changes in light conditions.     

Errors in instar determination of mayflies (Ephemeroptera) and stoneflies (Plecoptera) using the simple frequency, Janetschek, Cassie and Dyar's law methods

SUMMARY. 1. The reliability of the simple frequency, Janetschek, Cassie and Dyar's law methods for determining or corroborating instars of mayflies and stoneflies was evaluated using data from published studies, a population of Baetisca rogersi and populations simulated through use of random numbers and generated normal distributions. 2. The Janetschek and Cassie methods are variations of the simple frequency method that offer no significant advantage. Modes of the Cassie method, thought to represent instars, are much more difficult or impossible to detect than are the corresponding peaks of the other two methods. 3. Overlap in size between adjacent instars can lead to false instar peaks or modes in frequency plots. The potential for overlap in mayflies and stoneflies is greatly increased, compared to other insects, because of their large number of instars and known developmental variability. The normal distribution simulations demonstrated that instar size variability as low as 5–7.5% COV (coefficient of variability) may lead to false instar peaks when the number of instars is in the typical range. These simulations also indicated that even simple frequency plots with distinct peaks may result in inaccurate instar determinations. 4. The number of size classes used in an analysis was correlated with the number of peaks or modes revealed. The number of peaks greater than zero in the Janetschek plots for the Baetisca rogersi population varied from 5 to 53 as the number of size classes was varied from 20 to 188. Similarly for the random number simulations. the number of peaks varied from 6 to 41 as the number of size classes varied from 22 to 127. 5. Dyar's law semi-logarithmic plots do not corroborate instars determined through frequency methods, because the uniform spacing of‘instar’data points is the direct result of the uniform spacing of peaks in frequency plots of most data sources (including random numbers), whether or not peaks actually indicate instars. Also Dyar's law plots will‘corroborate’different numbers of instars depending on the peak selection criteria used. The potential for corroborating instars through supplemental rearing and best-fit analysis is discussed. 6. The future of mayfly—stonefly instar determination lies in the increased and more rigorous application of the rearing and Palmen body (mayflies only) methods.