栖息地适宜性指数在渔业科学中的应用进展

栖息地适宜性指数（habitat suitability index,HSI）于20世纪80年代提出之后,在渔业资源开发、管理、评估及保护等领域中得到广泛应用,已成为渔业科学研究的重要手段之一。简要概述了国内外HSI研究现状、理论和方法,以及应用现状和存在问题。并概括提出HSI研究和应用过程中,要充分考虑的问题有：（1）充分了解研究对象生活史过程及其生物学特性和所处的环境;（2）针对不同生长阶段和外部环境,选择合适的环境因子;（3）开展数据源合适时空标准的研究,建立环境因子等数据的规范;（4）根据历史资料和专家知识赋予各因子的合适权重;（5）针对不同目标（保护区、中心渔场、生物量估算等）,来选择备选的HSI模型;（6）通过各种模型的比较分析,选择合适的HSI模型;（7）利用实测数据和最新资料,对模型进行不断改进与修正,以提高模型的精度。     

Can incidental sighting data be used to elucidate habitat preferences and areas of suitable habitat for a cryptic species?

The involvement of communities in ecological studies has been shown to augment conservation efforts, especially for cryptic species. However, there is a lack of studies addressing the utility of incidental sighting records from community members in gaining knowledge on habitat preferences and distribution of suitable habitat for these organisms. This study compares preferences of the Lumholtz's tree kangaroo (Dendrolagus lumholtzi ; LTK), a cryptic rainforest folivore in northeastern Australia, for various habitat and climatic variables derived from data collected during scientific projects to those derived from incidental sighting records using ArcGIS and Maxent. Incidental sighting records suggest that the species uses a wider range of altitudes, annual rainfalls, annual mean temperatures and vegetation types than predicted by scientific studies. Incidental records also show that the species can persist in areas of lower rainfall during the wettest month and lower minimum temperature during the coldest month. Both data place the species within a comparable range of rainfalls during the driest month, maximum temperatures of the warmest month and soil types. When using identified preferences to assess the extent and distribution of suitable habitat, incidental records predicted more areas of suitable habitat than scientific records with an overlap of up to 91% between them. The present study proves that incidental sighting records can be a valuable part of the study of cryptic species and should be considered complementarily alongside scientific studies to obtain comprehensive ecological information of a species that can assist in its conservation.     

Extirpation, colonization, and habitat dynamics of a keystone species along an urban gradient

Using 5 years of patch occupancy data for 384 habitat fragments, we evaluated population and habitat dynamics of the black-tailed prairie dog in urban habitat remnants in the rapidly developing landscape of Denver, CO, USA. Specifically, we evaluated the landscape factors, including fragment area, age, and connectivity, that characterize the habitat fragments most likely to be colonized by prairie dogs, as well as those experiencing local extinctions. In addition, we determined which patch types were most often removed by land development. Sites in proximity to colonies were more likely to be colonized by prairie dogs. Local extinctions were most common on isolated colonies, and older and more isolated colonies were more likely to be extirpated by human activity. In general, smaller and older habitat patches were at the highest risk of being lost to land development. Our results provide observations of dynamic changes to the distribution of a potential keystone species in an urban area, which can be used to inform island biogeographic and metapopulation models for wildlife persistence in developing landscapes. Although populations are currently in decline, most local extinctions are the direct result of human activity, and we suggest that prairie dogs in this area can persist with appropriate management.     

河池市兜兰属植物资源及其保护利用初探

在查阅有关资料的基础上,采用样线调查和群落生态学相结合的调查方法,对河池市范围内兜兰属植物的分布数量和生境特征老蚌生珠调查分析。结果表明:河池市兜兰属植物资源丰富,共有6种兜兰属植物分布于全市10个县市区,但分布极不均匀;兜兰属植物生长于河池市石灰岩山地的常绿落叶阔叶林下的岩壁缝隙腐殖土上,所处环境条件脆弱,兜兰植株对环境的依存程度高;特殊的生物学特性、生境的丧失和过度采挖的其致濒的主要原因;在调查分析的基础上,提出了河池市兜兰属植物的保护利用对策。     

Machine learning highlights the importance of primary and secondary production in determining habitat for marine fish and macroinvertebrates

1. Species distribution models for marine organisms are increasingly used for a range of applications, including spatial planning, conservation, and fisheries management. These models have been constructed using a variety of mathematical forms and drawing on both physical and biological independent variables; however, what might be called first-generation models have mainly followed the form of linear models, or smoothing splines, informed by data collected in the context of fish surveys.
2. The performance of different classes of variables were tested in a series of species occurrence models built with machine learning methods, specifically evaluating the potential contribution of lower trophic level data. Random forest models were fitted based on the classification of the absence/presence for fish and macroinvertebrates surveyed on the US Northeast Continental Shelf.
3. The potential variables included physical, primary production, secondary production, and terrain variables. For accepted model fits, six variable importance measures were computed, which collectively showed that physical and secondary production variables make the greatest contribution across all models. In contrast, terrain variables made the least contribution to these models.
4. Multivariable analyses that account for all performance measures reinforce the role of water depth and temperature in defining species presence and absence; however, chlorophyll concentration and some specific zooplankton taxa, such as Metridia lucens and Paracalanus parvus, also make important contributions with strong seasonal variations.
5. Our results suggest that lower trophic level variables, if available, are valuable in the creation of species distribution models for marine organisms.

     

Distribution,habitat associations and conservation implications of Sri Lankan freshwater terrapins outside the protected area network

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Forecast skill for predicting distribution shifts: A retrospective experiment for marine fishes in the Eastern Bering Sea

Forecasting distribution shifts under novel environmental conditions is a major task for ecologists and conservationists. Researchers forecast distribution shifts using several tools including: predicting from an empirical relationship between a summary of distribution (population centroid) and annual time series (“annual regression,” AR); or fitting a habitat‐envelope model to historical distribution and forecasting given predictions of future environmental conditions (“habitat envelope,” HE). However, surprisingly little research has estimated forecast skill by fitting to historical data, forecasting distribution shifts and comparing forecasts with subsequent observations of distribution shifts. I demonstrate the important role of retrospective skill testing by forecasting poleward movement over 1‐, 2‐ or 3‐year periods for 20 fish and crab species in the Eastern Bering Sea and comparing forecasts with observed shifts. I specifically introduce an alternative vector‐autoregressive spatio‐temporal (VAST) forecasting model, which can include species temperature responses, and compare skill for AR, HE and VAST forecasts. Results show that the HE forecast has 30%–43% greater variance than predicting that future distribution is identical to the estimated distribution in the final year (a “persistence” forecast). Meanwhile, the AR explains 2%–6% and VAST explains 8%–25% of variance in poleward movement, and both have better performance than a persistence forecast. HE and AR both generate forecast intervals that are too narrow, while VAST models with or without temperature have appropriate width for forecast intervals. Retrospective skill testing for more regions and taxa should be used as a test bed to guide future improvements in methods for forecasting distribution shifts.     

Modelling the impacts of environmental variation on habitat suitability for Pacific saury in the Northwestern Pacific Ocean

We developed habitat suitability index (HSI) models for two size classes of Pacific saury Cololabis saira in the Northwestern Pacific Ocean. Environmental data, including sea surface temperature, sea surface height, salinity, and net primary production, and catch and effort data from Taiwanese distant‐water stick‐held dip net fisheries during the main fishing season (August–October) during 2002–2015 were used. Habitat preferences and suitable habitat area differed between size classes. The suitable habitat was located between 40–47.5°N and 145–165°E for large‐sized Pacific saury but encompassed a greater area (35–47°N and 140–165°E) for medium‐sized Pacific saury. Both size classes were affected by substantial interannual variation in the environmental variables, which in turn can be important in determining the potential fishing grounds. We found a significant negative relationship between the suitable habitat area and the Niño3.4 indices with a time‐lag of 6 months for the large‐sized (r = ?0.68) and medium‐sized (r = ?0.42) Pacific saury, respectively, as well as the total landings of Pacific saury by all fishing fleets (r = ?0.46). As remotely‐sensed environmental data become increasingly available, HSI models may prove useful for evaluation of possible changes in habitat suitability resulting from climate change or other environmental phenomena and in formulating scientific advice for management.     

Factors influencing the abundance of three common nearshore fishes in south‐west Lake Michigan

Variation in the distribution and abundance of nearshore fishes is critical to understand food web processes and fishery management issues in Lake Michigan. This study characterised patterns in abundance of three common nearshore species, yellow perch Perca flavescens (Mitchell), round goby Neogobius melanostomus (Pallas) and alewife Alosa pseudoharengus (Wilson), in relation to spatio‐temporal, abiotic and biotic factors using gillnet sampling conducted across 5 years at multiple locations representing different substrates. Significant variations were observed in alewife and round goby catches between locations. A negative relationship between round goby and age‐0 yellow perch catch was observed, indicating potential competition between the two species. This study demonstrates that variability in nearshore fish communities can be driven by factors including substrate and interspecific interactions. Given the prominent role these species play in Lake Michigan's food web and thus their importance to fishery production, a thorough understanding of these factors is warranted.     

Towards the development of a standardized method to monitor lakeshore hydromorphological restoration measures

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