The role of local and landscape level measures of greenness in modelling boreal plant species richness

Measurements of primary productivity and its heterogeneity based on satellite images can provide useful estimates of species richness and distribution patterns. However, species richness at a given site may depend not only on local habitat quality and productivity but also on the characteristics of the surrounding landscape. In this study we investigated whether the predictions of species richness of plant families in northern boreal landscape in Finland can be improved by incorporating greenness information from the surrounding landscape, as derived from remotely sensed data (mean, maximum, standard deviation and range values of NDVI derived from Landsat ETM), into local greenness models. Using plant species richness data of 28 plant families from 440 grid cells of 25 ha in size, generalized additive models (GAMs) were fitted into three different sets of explanatory variables: (1) local greenness only, (2) landscape greenness only, and (3) combined local and landscape greenness. The derived richness–greenness relationships were mainly unimodal or positively increasing but varied between different plant families, and depended also on whether greenness was measured as mean or maximum greenness. Incorporation of landscape level greenness variables improved significantly both the explanatory power and cross-validation statistics of the models including only local greenness variables. Landscape greenness information derived from remote sensing data integrated with local information has thus the potentiality to improve predictive assessments of species richness over extensive and inaccessible areas, especially in high-latitude landscapes. Overall, the significant relationship between plants and surrounding landscape quality detected here suggests that landscape factors should be considered in preserving species richness of boreal environments, as well as in conservation planning for biodiversity in other environments.     

Rarefaction and nonrandom spatial dispersion patterns

Rarefaction estimates how many species are expected in a random sample of individuals from a larger collection and allows meaningful comparisons among collections of different sizes. It assumes random spatial dispersion. However, two common dispersion patterns, within-species clumping and segregation among species, can cause rarefaction to overestimate the species richness of a smaller continuous area. We use field studies and computer simulations to determine (1) how robust rarefaction is to nonrandom spatial dispersion and (2) whether simple measures of spatial autocorrelation can predict the bias in rarefaction estimates. Rarefaction does not estimate species richness accurately for many communities, especially at small sample sizes. Measures of spatial autocorrelation of the more abundant species do not reliably predict amount of bias. Survey sites should be standardized to equal-sized areas before sampling. When sites are of equal area but differ in number of individuals sampled, rarefaction can standardize collections. When communities are sampled from different-sized areas, the mean and confidence intervals of species accumulation curves allow more meaningful comparisons among sites. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

The pattern of species turnover resulting from stochastic population dynamics: The model and field data

The model of random population dynamics in a sampling site returns geometric distribution of longevities of continuous presence (=persistence) and Poisson distribution of the presence–absence transitions. This discrete-time stochastic process describes the presence–absence pattern observed in the beetles surveyed 6 years on Mount Carmel, Israel. Homogeneous pools of species mostly on the Families rank, exhibit the predicted by the model patterns. Conformity to an ergodic hypothesis is the criterion of ecological homogeneity. This criterion assumes the equivalence of short-term behavior of entire pool and long-term behavior of any species from this pool. The pool of all 801 species of Order Coleoptera does not match the model. Thus a taxon of an arbitrary rank may not be considered a priory as a unit of ecological study. Determined from field data parameters of the model are biased and magnitude of the bias depends on longevity of the survey. Parameter of distribution depends also on species tolerance, which is the level adaptation of given species to given environment in given time interval. Random process of species turnover may be considered as a game of species to gain their presence against deteriorative fluctuations of environmental conditions.     

Modelling the abundance of three key plant species in New Zealand hill-pasture using a decision tree approach

Decision tree models were developed to investigate and predict the relative abundance of three key pasture plants [ryegrass (Lolium perenne), browntop (Agrostis capillaris), and white clover (Trifolium repens)] with integration of a geographical information system (GIS) in a naturalised hill-pasture in the North Island, New Zealand, and were compared with regression models with respect to model fit and predictive accuracy. The results indicated that the decision tree models had a better model fit in terms of average squared error (ASE) and a higher percentage of adequately predicted cases in model validation than the corresponding regression models. These decision tree models clearly revealed the relative importance of environmental and management variables in influencing the abundance of these three species. Hill slope was the most significant environmental factor influencing the abundance of ryegrass while soil Olsen P and annual P fertilizer input were the most significant factors influencing the abundance of browntop, and white clover, respectively. Soil Olsen P of approximately 10 μg/g, or a slope of about 10.5° was critical points where the competition between ryegrass and browntop tended to come to an equilibrium. Integrating the decision tree models with a GIS in this study not only facilitated the model development and analyses, but also provided a useful decision support tool in pasture management such as in assisting precision fertilizer placement. The insights obtained from the decision tree models also have important implications for pasture management, for example, it is important to maintain a soil Olsen P higher than 10 μg/g in order to keep the dominance of ryegrass in the hill-pasture.     

RESOLUTION OF ENDANGERED SPECIES ACT ISSUES IN PERMITTING TILE PLATEAU CREEK PIPELINE1

ABSTRACT: This paper describes how a hydrologic model proved to be a valuable tool to help interested parties understand impacts to four threatened and endangered fish species in the Upper Colorado River. In 1994, the Ute Water Conservancy District initiated permitting and design of the Plateau Creek pipeline replacement. The project was considered a major Federal action and therefore subject to the National Environmental Policy Act. Under Section 7 of the Endangered Species Act, the U.S. Fish and Wildlife Service (USFWS) entered the process to develop a Biological Opinion (BO) and determined that the project could potentially impact the endangered fish in the 15‐mile reach of the Colorado River. The Section 7 consultation was directed by a Core Committee comprised of stakeholders in the Upper Colorado River watershed. Hydrologic modeling became the evaluation tool for comparing flow reductions to USFWS target recovery flows and defining make‐up flow requirements to meet those targets. The Colorado River Recovery Implementation Program was designated to provide the make‐up flows. The USFWS released a final BO in December 1997, approving diversions through 2015. An Environmental Impact Statement for the project was completed and the Record of Decision was issued by the Bureau of Land Management in early 1998.     

Female mate choice determines reproductive isolation between sympatric butterflies

Animal courtship rituals are important for species recognition, and a variety of cues might be utilized to recognize conspecific mates. In this paper, we investigate different species-recognition mechanisms between two sympatric butterfly sister species: the wood white (Leptidea sinapis) and Real’s wood white (Leptidea reali). We show that males of both species frequently court heterospecific females both under laboratory and field conditions. The long-lasting elaborate courtships impose energetic costs, since the second courtship of males that were introduced to two subsequent conspecific females lasted on average only one fourth as long as the first courtship. In this paper, we demonstrate that premating reproductive isolation is dependent on female unwillingness to accept heterospecific mates. We studied female and male courtship behavior, chemical signaling, and the morphology of the sexually dimorphic antennae, one of the few male traits visible for females during courtship. We found no differences in ultraviolet (UV) reflectance and only small differences in longer wavelengths and brightness, significant between-species differences, but strongly overlapping distributions of male L. sinapis and L. reali antennal morphology and chemical signals and minor differences in courtship behavior. The lack of clear-cut between-species differences further explains the lack of male species recognition, and the overall similarity might have caused the long-lasting elaborate courtships, if females need prolonged male courtships to distinguish between con- and heterospecific suitors.     

珠江口沉积物中生物有效性硅的赋存形态及释放研究

运用A Tessier逐步化学连续提取法,研究了珠江口沉积物中各种生物有效性硅:Ⅰ-可交换离子态、Ⅱ-碳酸盐结合态、Ⅲ-铁锰氧化物结合态、Ⅳ-有机质和硫化物结合态.研究表明:表层沉积物中,Ⅲ为优势赋存态.在沉积柱C2中,Ⅲ＞Ⅳ＞Ⅱ＞Ⅰ,Ⅰ、Ⅱ随深度变化无规律性,Ⅲ随深度先升高后下降,Ⅳ表层含量较高,到达一定深度(18 cm左右)后骤降.释放试验表明:振荡在一定时间内有利于硅释放;而盐度对硅释放的影响比较复杂,低盐度(5%以内),随盐度升高,释放量下降.当盐度继续升高时释放量又增加,但高盐度对硅释放影响不大;硅的释放在pH值=3～8范围内随着pH值升高而减少.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

Protecting the piping plover under section 7 of the endangered species act

Section 7(a)(2) of the Endangered Species Act directs federal agencies to ensure that their actions do not jeopardize the continued existence of endangered and threatened species. The US Fish and Wildlife Service (USFWS) issues jeopardy or nonjeopardy biological opinions on proposed federal actions that affect endangered and threatened species. We summarize several biological opinions issued by the USFWS to protect the threatened piping plover (Charadrius melodus). These opinions address federal actions involving hundreds of piping plovers on the Missouri River system and a few piping plover pairs on short stretches of Atlantic coast beach. Some of these opinions are decisive, but most allow the proposed action to proceed conditional upon a lengthy set of reasonable and prudent alternatives to protect the piping plover. These conditions may prove difficult to track and will add to the workload of the USFWS.     

Spatial heterogeneity of vegetation under different grazing intensities in the Northwest Heilongjiang Steppe of China

In northern China, recent degradation of semi-arid grasslands caused by overgrazing is serious. At Green Grassland Village, west of Daqing City in Heilongjiang Province, three grasslands with different degrees of degradation were surveyed. In the survey, a new method of vegetation analysis based on the beta-binomial distribution, was adopted to describe the frequency of occurrence and spatial heterogeneity for each plant species.Chenopodium centrorubrum, Cleistogenes squarrosa and a Carex species were commonly found in the three grasslands. Non-degraded grassland with light grazing was dominated by Arundinella hirta, Filifolium sibiricium, Lespedeza hedysaroides, Potentilla verticillaris, Stipa baicalensis and Thymus serpyllum. These species belong to the erect-type or do not develop large clones under light grazing. These species can be used as indicators of a well-managed grassland in this area. On the other hand, the degraded grassland with heavy grazing was dominated by Artemisia spp. and Euphorbia humifusa var. pilosa. Artemisia spp., E. humifusa var. pilosa, Eragrostis pilosa and Setaria viridis belong to the creeping-type or develop rather large stocks or stolons under heavy utilization. These species increased the spatial heterogeneity in the degraded grassland with heavy grazing.Under degraded conditions, species diversity decreased and spatial heterogeneity of the communities tended to increase.