Euclidean geometry explains why lengths allow precise body mass estimates in terrestrial invertebrates: the case of oribatid mites

Indirect measures of soil invertebrate body mass M based on equations relating the latter to body length (l) are becoming increasingly used due to the required painstaking laboratory work and the technical difficulties involved in obtaining some thousands of reliable weight estimates for animals that can be very small. The implicit assumption of such equations is that dM/dV=δ, where V is body volume and δ is a constant density value. Classical Euclidean scaling implies that V∝l³∝M. One may thus derive M from l when the latter can provide a good estimate of V and the assumption of a constant δ is respected. In invertebrates, equations relating weight to length indicate that the power model always provides the best fit. However, authors only focused on the empirical estimation of slopes linking the body mass to the length measure variables, sometimes fitting exponential and linear models that are not theoretically grounded. This paper explicates how power laws derive from fundamental Euclidean scaling and describes the expected allometric exponents under the above assumptions. Based on the classical Euclidean scaling theory, an equivalent sphere is defined as a theoretical sphere with a volume equal to that of the organism whose body mass must be estimated. The illustrated application to a data set on soil oribatid mites helps clarify all these issues. Lastly, a general procedure for more precise estimation of M from V and δ is suggested.     

Density dependence in an island population of silvereyes

The population of silvereyes Zosterops lateralis chlorocephalus , on Heron Island, Great Barrier Reef has been monitored accurately since 1965. Between 1979 and 1993, the breeding success of all birds was determined by monitoring nests. The population fluctuated between 225 and 483 individuals. Four cyclones led to substantial mortality. As this data set is long-term, has little observation error, and is from an effectively closed population, it provides an unusual opportunity to examine density dependence in reproduction or mortality. Using a stochastic logistic model, we found clear evidence of density dependence in adult population size. Logistic regression suggested that fledgling survival decreased with the numbers of birds attempting to breed. There was also some suggestion that adult survival might be density dependent. The fitted stochastic logistic model predicts negligible risks of extinction for this population, in contrast to the predictions of a published population viability analysis. Whilst our statistical model including density dependence may provide better predictions of the "usual" behaviour of a population than a population viability analysis, we suggest that caution should be exercised when statistically fitted models are used to predict the behaviour of the population at extremes, such as near extinction.     

On the stabilization of animal numbers. Problems of testing

Summary When testing for regulation of population numbers, rather than using Bulmer's second test in cases where population numbers are estimated instead of measured, we prefer to correct Bulmer's first test for estimation error. A correction method is expounded, discussed, and applied to two series of census data: the pine looper of Klomp and the garden chafer of Milne. In neither case the tentative conclusion from using the uncorrected test was changed after correction. Therefore, in practice Bulmer's first test without correction can be used well as a first orientation. Twelve long series (more than 10 years) of census data of both univoltine and semelparous (a necessary condition) insects were tested for significant density dependence in the fluctuations of numbers with the randomization test of Pollard et al. None of the series, all we could find to meet the necessary condition as well as being longer than 10 years, showed significant density dependence at the 0.05 level, though the pine looper of Klomp did so at the 0.1 level. Next, the same series were tested for regulation in the sense of keeping density within limits with both the first test of Bulmer and the permutation test of Reddingius and Den Boer. Onky Klomp's pine looper population at Hoge Veluwe scored significantly. In a following paper this population will be considered more closely, in order to enable understanding of this test result.Communication No. 362 of the Biological Station, Wijster     

Models for testing

Summary This is a comment on a note by Solow (1990). It is shown that Solow's simulation results indicate that Bulmer's test for density dependence is non-robust to a particular kind of second-order Markovity that might well be overlooked by an ecologist. It is suggested that Solow's claim that Bulmer's test is insensitive is not wholly justified. Some scepticism concerning the applicability of statistical testing theory to animal population data is expressed.Communication no. 410 of the Biological Station, Wijster     

Estimating the Occupancy Rate of Spatially Rare or Hard to Detect Species: A Conditional Approach

Summary We consider the problem of estimating the occupancy rate of a target species in a region divided in spatial units (called quadrats); this quantity being defined as the proportion of quadrats occupied by this species. We mainly focus on spatially rare or hard to detect species that are typically detected in very few quadrats, and for which estimating the occupancy rate (with an acceptable precision) is problematic. We develop a conditional approach for estimating the quantity of interest; we condition on the presence of the target species in the region of study. We show that conditioning makes identifiable the occurrence and detectability parameters, regardless of the number of visits made in the sampled quadrats. Compared with an unconditional approach, it proves to be complementary, in that this allows us to deal with biological questions that cannot be addressed by the former. Two Bayesian analyses of the data are performed: one is noninformative, and the other takes advantage of the fact that some prior information on detectability is available. It emerges that taking such a prior into account significantly improves the precision of the estimate when the target species has been detected in few quadrats and is known to be easily detectable.     

用距离取样技术估算森林生境中的梅花鹿密度

作者于 1999年 9、 10月在日本国日光国立公园的一个梅花鹿 (Cervusnippon)高密度区域实施了 16次夜间探照样带距离法取样调查。采用车载探照记数和激光测距仪测距 ,记录了梅花鹿的结群大小和距样带中心样线的垂直距离。应用距离取样技术 (Distancesamplingtechnique ,DST)计算的结果表明 ,梅花鹿的密度为12 5 8头 /km2 (95%CI 10 0 7-157 3 ) ,在两侧 80m宽度的调查样带内梅花鹿的总发现率为 52 5% ;对线样带法的传统动物密度计算方法 (King s ,Hayne s ,Leopold s ,Gates sⅠ ,Gates sⅡ ,Gates sⅢ和Frye s方法 )的结果验证表明 ,这些传统密度计算方法过高估算梅花鹿的密度 ,其结果为距离取样技术 (DST)计算结果的 1 76(Frye′s法 ) -6 10 (Hayne′s法 )倍。因此 ,作者建议在使用线样带法测定动物密度时应尽量避免使用这些传统计算方法 ;不同地区间及同一地区不同季节间应用线样带法调查得到的动物个体记数值之间的比较存在偏差 ,应该使用距离取样技术计算动物的密度     

Estimates of subtropical forest biomass based on airborne LiDAR and Landsat 8 OLI data

 快速、定量、精确地估算区域森林生物量一直是森林生态功能评价以及碳储量研究的重要问题。该研究基于机载激光雷达(LiDAR)点云与Landsat 8 OLI多光谱数据, 借助江苏省常熟市虞山地区55块调查样地数据, 首先提取并分析了87个特征变量(53个OLI特征变量, 34个LiDAR特征变量)与森林地上、地下生物量的Pearson’s相关系数以进行变量优选, 然后利用多元逐步回归法建立森林生物量估算模型(OLI生物量估算模型和LiDAR生物量估算模型), 并与基于两种数据建立的综合生物量估算模型的结果进行比较, 讨论预测结果及其精确性。结果表明: 3种模型(OLI模型、LiDAR模型和综合模型)在所有样地无区分分析时, 地上和地下生物量的估算精度均达到0.4以上, 基于不同森林类型(针叶林、阔叶林、混交林)分析时地上和地下生物量的估算精度均有明显提高, 达到0.67及以上。利用分森林类型模型估算生物量, 综合生物量估算模型精度(地上生物量: R²为0.88; 地下生物量: R²为0.92)优于OLI生物量估算模型(地上生物量: R²为0.73; 地下生物量: R²为0.81)和LiDAR生物量估算模型(地上生物量: R²为0.86; 地下生物量: R²为0.83)。     

Dimanganese catalase—spectroscopic parameters from broken-symmetry density functional theory of the superoxidized MnIII/MnIV state

Broken-symmetry density functional theory was used to study the catalytic center of manganese catalase in the superoxidized Mn^III/Mn^IV state. Heisenberg exchange coupling constants, ⁵⁵Mn and ¹⁴N hyperfine coupling constants (hfcs) and nuclear quadrupole splittings, as well as the electronic g tensors were evaluated for different model systems of the active site after complete geometry optimizations in the high-spin and broken-symmetry states. A comparison of the experimental data with the spectroscopic parameters computed for the models with unprotonated and protonated -oxo bridges shows best agreement between theory and experiment for a Mn₂(-O)₂(-OAc) core. The calculated Mn–Mn distances and ⁵⁵Mn hfcs clearly support a dimanganese cluster with unprotonated -oxo bridges in the superoxidized state. Furthermore, it is shown that an interchange of the Mn^III and Mn^IV oxidation states in this trapped valence system leads to specific changes in the molecular and electronic structure of the manganese clusters.     

Grid — A space density analysis for recognition of noda in vegetation samples

Summary Recognition of noda is performed in a point cloud of n-space using grid analysis. The input data represent coordinates, preferably component scores, to reduce dimensionality. The exact position of the noda is approximated in an iterative search procedure which allows the user-defined space segments to drift into regions of high point density. The results are independent of group size and shape and they tend to compensate for uneven sampling in the different types of the survey site. The method gives flexibility in group recognition at different resolutions and provides a practical means to handling large data sets, while at the same time producing an optimal solution. The method, suitable to be used in the place of divisive clustering algorithms, has been applied to vegetation data with success. Results from two such applications are presented.The author expresses his thanks to Dr. L. Orlóci for discussions and critical review, and to the University of Western Ontario for computer time.     

A test of statistical techniques for detecting density dependence in sequential censuses of animal populations

Summary Principal and reduced major axes, and Bulmer's (1975) tests have been suggested as methods for detecting the presence of density dependence in a series of population censuses that are unsuitable for analysis by alternative means e.g. by k-factor analysis. These alternative methods are tested using census data, some of which are previously unpublished, from natural populations known from independent evidence to be subject to density dependent processes. All the methods fail to detect density dependence reliably, irrespective of sample size and the dynamics of the population. We conclude that none of the methods tested is sufficiently reliable to be useful as a test of density dependence in sequential censues of animal populations.     

Regulatory processes and population cyclicity in laboratory populations ofAnagasta kühniella (Zeller) (Lepidoptera: Phycitidae)

AsMatsumoto andHuffaker (1973) concluded that their initial universe size was too small for the proper separation of the effects of host density and dispersion on parasite performance, a larger universe of 38 1/2″ (length) ×38 1/2″ (width) ×3″ (height) was used. When individual parasites were exposed to fixed densities and dispersion patterns of host, they displayed an overall decrease in the parasitization rate when compared to the small universe. In all cases aHolling -type response resulted. When a group of 10 parasites per test was employed a Nicholsonian type of response resulted. In an experimentally confined space, the parasites displayed a mutual behavioral interference resulting in emigration which accelerated as the parasite density increased.