Geographical variability in, and temperature effects on, the phenology of Maniola jurtina and Pyronia tithonus (Lepidoptera, Satyrinae) in England and Wales

ABSTRACT. 1. Geographical variability in, and temperature effects on, the mean date of adult flight period and the SD about this date are analysed for two univoltine, grassland butterflies in England and Wales from 1976 to 1985. Data were collected on the Butterfly Monitoring Scheme for Maniola jurtina (L.) at twenty-nine sites and Pyronia tithonus (L.) at twenty sites.
2. Substantial variability for mean date and SD occurs between years and between sites. Changes in mean date between years tend to occur consistently at different sites. The species show some parallel in variation between sites, especially for mean date.
3. June maximum temperature accounts for 95% and 75% of the variation in mean date between years in M. jurtina and P. tithonus , respectively ( r =-0.97 and -0.87). Similar relationships occur for temperatures cumulated over the period of post-winter development from March to July or August.
4. Greater geographical variability in phenology, and a generally less synchronized flight period in M.jurtina may be associated with broader habitat preferences than in P. tithonus.
5. The mean date of adult flight period remains at roughly the same date at more northerly latitudes. In M.jurtina the flight period becomes more synchronized, begins later and ends earlier in the north. P. tithonus shows little or no indication of such a response to latitude. This is discussed with regard to changes in season length and factors limiting the species'range.     

Host plants and butterfly biology. Do host‐plant strategies drive butterfly status?

Abstract. 1. To determine whether rarity and decline is linked to organism ecology, associations have been examined between butterfly larval host‐plant competitive, stress‐tolerant, ruderal (C‐S‐R) strategies and butterfly biology. 2. Associations have been sought between mean C‐S‐R scores for larval host plants with butterfly life history, morphology and physiology variables, resource use, population attributes, geography, and conservation status. Comparisons are carried out across species and controlled for phylogenetic patterning. 3. Butterfly biology is linked to host‐plant strategies. An increasing tendency of a butterfly's host plants to a particular strategy biases that butterfly species to functionally linked life‐history attributes and resource breadth and type. In turn, population attributes and geography are significantly and substantially affected by host choice and the strategies of these host plants. 4. The greatest contrast is between butterfly species whose host plants are labelled C and R strategists and those whose host plants are labelled S strategists. Increasingly high host‐plant C and R strategy scores bias butterflies to rapid development, short early stages, multivoltinism, long flight periods, early seasonal emergence, higher mobility, polyphagy, wide resource availability and biotope occupancy, open, areally expansive, patchy population structures, denser distributions, wider geographical ranges, resistance to range retractions as well as to increasing rarity in the face of environmental changes. Increasing host‐plant S strategy scores have reversed tendencies, biasing those butterfly species to extended development times, fewer broods, short flight periods, smaller wing expanse and lower mobility, monophagy, restricted resource exploitation and biotope occupancy, closed, areally limited populations with typical metapopulation structures, sparse distributions, and limited geographical ranges, range retractions, and increased rarity. 5. Species with S strategy host plants are species vulnerable to current environmental changes and species of conservation concern.     

Vegetation condition assessment and monitoring from sequences of satellite imagery

Summary   Vegetation changes over time are important indicators of condition, and are particularly important as targets or triggers for management. Satellite image data have unique capacities to provide information on changes in vegetation. In particular, Landsat imagery has the spatial resolution and a historical archive that make it relevant to providing information for understanding and management of native vegetation at a range of scales from small remnant to region. Regional and national vegetation monitoring programs based on time series Landsat imagery are now operational in Australia. These programs and their data have huge potential to provide information for conservation and natural resource management questions. They have already found multiple applications, including applications to biodiversity assessment and planning. This paper presents some examples of the delivery and application of satellite image monitoring information in the context of vegetation management.     

高原湖泊湿地以植被指示为主的环评指标初探

分析探讨高原湖泊湿地的环境评价中,如何应用一套由植被为主指示要素构成的环评指标,并以云南石林长湖湖泊湿地为实例。按植被及其植物区系组成、动物区系和生境方面所表现特征的现况,共设置以植被特征为主的10个评定指示要素。使用此类指标评价的前提是:所评的各个高原湖泊湿地,均在上述10个所规定的指示要素方面,已取得调查研究的定量和定性数据资料。所以本方案的使用,反而促成各高原湖泊湿地在以植被特征为主各评价要素的进一步考察和研究,以作为参评的依据。     

The selection, testing and application of terrestrial insects as bioindicators

Although the uses and merits of terrestrial insects as indicators have been extensively discussed, there is a lack of clear definition, goal directedness and hypothesis testing in studies in the field. In an attempt to redress some of these issues and outline an approach for further studies, three categories of terrestrial insect indicators, corresponding to differences in their application, are proposed, i.e. environmental, ecological and biodiversity indicators. The procedures in terrestrial insect bioindicator studies should start with a clear definition of the study objectives and proposed use of the bioindicator, as well as with a consideration of the scale at which the study is to be carried out. Bioindication studies are conducted at a variety of spatial and temporal scales within the context of earth-system processes, but the objectives of the study will largely determine the scale at which it would be optimally conducted. There is a tendency for studies to be conducted below their space-time scaling functions, giving them apparent predictability. The selection of potential indicator taxa or groups is then based on a priori suitability criteria, the identification of predictive relationships between the indicator and environmental variables and, most importantly, the development and testing of hypotheses according to the correlative patterns found. Finally, recommendations for the use of the indicator in monitoring should be made. Although advocating rigorous, long-term protocols to identify indicators may presently be questionable in the face of the urgency with which conservation decisions have to be made, this approach is critical if bioindicators are to be used with any measurable degree of confidence.