Vegetation mapping of the Great Fish River basin,South Africa: Integrating spatial and multi‐spectral remote sensing techniques

Abstract. We present a remote sensing based vegetation mapping technique well suited to a heterogeneous, semi‐arid environment. 10 structural vegetation classes were identified and described on the ground. Using Landsat‐TM from two different seasons and a combination of three conventional classification techniques (including a multi‐temporal classification) we were unsuccessful in delineating all of the desired vegetation classes. We then employed a simple tex‐tural classification index, known as the Moving Standard Deviation Index (MSDI), that has been used to map degradation status. MSDI measures spatial variations in the landscape and is calculated by passing a 3 × 3 standard deviation filter across the Landsat‐TM red band. High MSDI values are associated with degraded or disturbed rangelands whilst low MSDI values are associated with undisturbed rangeland. A combination of two conventional multi‐spectral techniques and MSDI were used to produce a final vegetation classification at an accuracy of 84 %. MSDI successfully discriminated between two contrasting vegetation types of identical spectral properties and significantly strengthened the accuracy of the classification. We recommend the use of a tex‐tural index such as MSDI to supplement conventional vegetation classification techniques in heterogeneous, semi‐arid or arid environments.     

西藏阿里植物群落的间接梯度分析、数量分类与环境解释

根据对西藏阿里地区163个植物群落样地资料进行的多元分析——排序、数量分类与环境解释,给出了该地区植被的基本类型、生态梯度及其与环境因子的定量关系。基本分析方法包括3个步骤：1)通过无倾向对应分析(DCA)的两个排序向量揭示了阿里植被的两个主要生态梯度;2)由该梯度的二维散点图及二元指示种分析(TWINSPAN)分别产生非等级制与等级制的植物群落分类系统;3)以多元回归分析将排序值与环境及地理参数相联系而给出各类型的环境指标——定量环境解释。分析表明,阿里植被类型及其分布主要取决于热量与湿度梯度,前者可通过地理参数,后者则通过土壤特征的数学表达式来定量地确定。两梯度包含的类型、种类与生境差异颇大,由低山暖性荒漠直到高山冰缘植被,从隐带性沼泽与盐生草甸到高原地带性荒漠与草原均各得其位,各有其值。表明该数量分析法对于处理高度生态多样性的植物群落生态信息是十分有效的。     

A theory of evaluation applied to human-environment systems

1. 1. The writers present the general theory of evaluation that is being developed by their group.

2. 2. The evaluation of a human environment is a complex mental process.

3. 3. In an effort to express numerically the quality of an environment, one tends to oversimplify the complex aspects of it and the entailing problems in relation to its inhabitants.

4. 4. In this paper, some examples are taken in the evaluation of thermal environments, wherein much has been said and done in setting up numerical scales to express human comfort, and yet neither clear-cut explanations nor convincing logic seem to exist to terminate the argument over the widely scattered and sometimes seemingly contradicting experimental data.

5. 5. The writers suggest that many of the reasons for this confusion may be traced back to the oversimplified notion of evaluation.

6. 6. It is shown that there are various possibilities when looking at the scales of evaluation.

7. 7.|The nominal scale, least studied of all the four traditional scales, may be given a prominent place in evaluating a thermal environment. The pseudo-interval order scale is another example.

The new chronostratigraphic classification of the Ordovician System and its relations to major regional series and stages and to δ13C chemostratigraphy

The extensive work carried out during more than a decade by the International Subcommission on Ordovician Stratigraphy has resulted in a new global classification of the Ordovician System into three series and seven stages. Formal Global Boundary Stratotype Section and Points (GSSPs) for all stages have been selected and these and the new stage names have been ratified by the International Commission on Stratigraphy. Based on a variety of biostratigraphic data, these new units are correlated with chronostratigraphic series and stages in the standard regional classifications used in the UK, North America, Baltoscandia, Australia, China, Siberia and the Mediterranean‐North Gondwana region. Furthermore, based mainly on graptolite and conodont zones, the Ordovician is subdivided into 20 stage slices (SS) that have potential for precise correlations in both carbonate and shale facies. The new chronostratigraphic scheme is also tied to a new composite δ¹³C curve through the entire Ordovician.     

我国石炭系滑石板阶标准剖面的牙形刺

滑石板阶标准剖面的牙形刺主要有Neognathodussymmetricus,Declinognathodusnoduliferusnoduliferus,D .noduliferusinaequalis,D .lateralis,Idiognathoidescorrugatus,I .sinuatus和I .sulcatus等 ,应属Neognathodussymmetricus带 ;滑石板阶之底界则在Neognathodussymmetricus带中通过。由此可知 ,在标准剖面上 。     

Relevance of Global Forest Change Data Set to Local Conservation: Case Study of Forest Degradation in Masoala National Park,Madagascar

A global data set on forest cover change was recently published and made freely available for use (Hansen et al. 2013. Science 342: 850–853). Although this data set has been criticized for inaccuracies in distinguishing vegetation types at the local scale, it remains a valuable source of forest cover information for areas where local data is severely lacking. Masoala National Park, in northeastern Madagascar, is an example of a region for which very little spatially explicit forest cover information is available. Yet, this extremely diverse tropical humid forest is undergoing a dramatic rate of forest degradation and deforestation through illegal selective logging of rosewood and ebony, slash‐and‐burn agriculture, and damage due to cyclones. All of these processes result in relatively diffuse and small‐scale changes in forest cover. In this paper, we examine to what extent Hansen et al.'s global forest change data set captures forest loss within Masoala National Park by comparing its performance to a locally calibrated, object‐oriented classification approach. We verify both types of classification with substantial ground truthing. We find that both the global and local classifications perform reasonably well in detecting small‐scale slash‐and‐burn agriculture, but neither performs adequately in detecting selective logging. We conclude that since the use of the global forest change data set requires very little technical and financial investment, and performs almost as well as the more resource‐demanding, locally calibrated classification, it may be advantageous to use the global forest change data set even for local conservation purposes.     

Analysis of mitochondrial COI sequences of the Diachasmimorpha longicaudata (Hymenoptera: Braconidae) species complex in Thailand

Diachasmimorpha longicaudata is an Opiinae parasitoid used to control tephritid fruit flies, which cause tremendous economic losses of fruits worldwide. In Thailand, D. longicaudata is classified as three sibling species, DLA, DLB and DLBB, based on the morphological and biological species concepts but their genetic variation has not been studied. Therefore, we investigated the genetic differentiation of the mitochondrial COI gene to clarify the ambiguous taxonomy of this species complex. The 603‐bp COI region was sequenced from laboratory‐bred colonies and field‐collected specimens from seven locations representing five geographical regions in Thailand. DLA was associated with the host Bactrocera correcta while DLB and DLBB were associated with Bactrocera dorsalis. The interspecific nucleotide differences of COI sequences among the three groups ranged from 6.70% to 7.62% (Kimura 2‐parameter distance), which adequately separates species complexes within the order Hymenoptera and supports the current sibling species classification. The neighbor joining, maximum likelihood and consensus Bayesian phylogenetic trees constructed from COI sequences revealed that the three sibling species of laboratory and field‐collected D. longicaudata are monophyletic with 100% support. The high genetic variation and molecular phylogeny of the COI sequences were shown to discriminate between the D. longicaudata species examined in this study.     

The cephalopod macrosystem: A historical review, the present state of knowledge, and unsolved problems: 3. Classification of Bactritoidea and Ammonoidea

A new classification is proposed in which Bactritoidea and Ammonoidea are considered as subclasses. The subclass Bactritoidea includes a single order, Bactritida. The subclass Ammonoidea includes ten orders: Anarcestida (suborders Agoniatitina, Auguritina, Anarcestina, Gephurocerina, Timanocerina, and Prolecanitina), Tornocerida, Goniatitida (with suborders Goniatitina and Cyclolobina), Praeglyphiocerida, Clymeniida (with suborders Gonioclymeniina and Clymeniina), Medlicottiida, Ceratitida (with suborders Paraceltitina, Otocerina, Meekocerina, Sagecerina, Ptychitina, Ceratitina, Pinacocerina, Megaphyllitina, Arcestina, and Lobitina), Phyllocerida, Lytocerida (with suborders Lytocerina and Turrilitina), and Ammonitida (with suborders Psilocerina, Haplocerina, Stephanocerina, Cardiocerina, and Ancylocerina).     

Fine-scale habitat associations of Oklahoma's longspurs

Overwintering is a key demographic stage for migratory birds but remains poorly understood, especially among multiple declining grassland bird species. The non-breeding ranges all 4 species of longspur (i.e., chestnut-collared [Calcarius ornatus], Smith's [C. pictus], Lapland [C. lapponicus], thick-billed [Rhynchophanes mccownii]) overlap in Oklahoma and the Texas Panhandle, USA, making this region ideal to study their wintering ecology. We evaluated the relationship between wintering longspur occurrence and fine-scale habitat characteristics using a combination of standardized bird surveys and vegetation plot sampling. Our study encompassed large, representative tracts of 3 prairie ecosystems (i.e., shortgrass, mixed-grass, and tallgrass prairies) that intersect within the Southern Great Plains, during winters of 2018–2019 and 2019–2020. Using randomization tests and classification trees, we characterized longspur habitats and compared these associations across the 3 prairie ecosystems. Fine-scale winter habitats (horizontal structure, vertical structure, and species compositions) varied among all 4 longspur species, varied at very fine scales, and differed between grassland types. Our findings can be applied to the management of grasslands such as decreasing vegetation height in mixed-grass prairies for chestnut-collared longspurs or removing woody vegetation in shortgrass prairies for thick-billed longspurs to help develop full-life cycle conservation for longspurs, which have experienced population declines.