Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates

Africa is predicted to be highly vulnerable to 21st century climatic changes. Assessing the impacts of these changes on Africa's biodiversity is, however, plagued by uncertainties, and markedly different results can be obtained from alternative bioclimatic envelope models or future climate projections. Using an ensemble forecasting framework, we examine projections of future shifts in climatic suitability, and their methodological uncertainties, for over 2500 species of mammals, birds, amphibians and snakes in sub‐Saharan Africa. To summarize a priori the variability in the ensemble of 17 general circulation models, we introduce a consensus methodology that combines co‐varying models. Thus, we quantify and map the relative contribution to uncertainty of seven bioclimatic envelope models, three multi‐model climate projections and three emissions scenarios, and explore the resulting variability in species turnover estimates. We show that bioclimatic envelope models contribute most to variability, particularly in projected novel climatic conditions over Sahelian and southern Saharan Africa. To summarize agreements among projections from the bioclimatic envelope models we compare five consensus methodologies, which generally increase or retain projection accuracy and provide consistent estimates of species turnover. Variability from emissions scenarios increases towards late‐century and affects southern regions of high species turnover centred in arid Namibia. Twofold differences in median species turnover across the study area emerge among alternative climate projections and emissions scenarios. Our ensemble of projections underscores the potential bias when using a single algorithm or climate projection for Africa, and provides a cautious first approximation of the potential exposure of sub‐Saharan African vertebrates to climatic changes. The future use and further development of bioclimatic envelope modelling will hinge on the interpretation of results in the light of methodological as well as biological uncertainties. Here, we provide a framework to address methodological uncertainties and contextualize results.     

共享社会经济路径下中国2020—2100年碳排放预测研究

碳排放和减碳经济代价研究日益受到学术界和决策者的关注,中国政府做出的关于争取在2060年前实现碳中和的表态引起了国际社会的热议。在此背景下,开展中国未来长时间序列碳排放的情景预测具有切实意义。基于可拓展的随机性环境影响评估模型（STIRPAT）评估了人口、经济和受教育程度对碳排放的影响,对比历史数据并验证了碳排放预测模型的准确性,结合共享社会经济路径（SSPs）情景的设定和模型参数,预测了5种情景下中国2020年至2100年的碳排放轨迹及经济代价。结果表明：（1）考虑碳排放达峰目标的实现,SSP3情景是中国未来发展的最佳情景,在此情景下,中国有望提前三年实现碳排放达峰目标;（2） SSP3情景可使中国年度总碳排放量和人均碳排放量处于相对其他四种情景的最低值,但需要付出累积GDP下降5.49%至8.80%的代价;（3）为完成在2060年前实现碳中和的承诺,中国政府在未来的40年需面对409.36-467.42 Gt的碳中和量;（4）2020年中国的碳排放强度将会较2005年水平下降40.52%至41.39%,2030年碳排放强度将会较2005年水平下降59.64%至60.75%。5种情境中,SSP5情景是降低碳排放强度的最佳情景,可最大程度地超额实现碳排放强度目标。未来,受经济发展、人口增长等重要因素影响,中国政府减碳压力将进一步加大。后疫情时代,考虑到能源供应的减少和高科技产业的发展,碳排放社会成本的上升将为中国创造一个使能源系统脱碳的机遇。中国应在"十四五"期间继续提升能源利用效率、升级产业结构、提倡低碳消费、实施隐含碳战略,以尽快实现碳减排目标。     

用诱蛾量和有效积温模型预测东北越冬代水稻二化螟发生期

在吉林省柳河县绿色稻米生产区,采用1999～2001年间3月1日后有效积温和水稻二化螟诱捕器诱蛾量数据,用线性模型探讨了当地有效积温和诱捕器诱蛾量之间的关系。由建立的线性模型确定越冬代水稻二化螟发蛾始盛期、高峰期和盛末期所需有效积温分别为238.323、339.418和483.398日·度。 采用吉林长春稻区2002～2004年3年间数据比较模型预测值和观察值之间的差异,有效积温的误差值在3.882～26.943日·度之间,相应时间误差为 0～3 天。模型预测准确性较好,可用以及时指导大田防治。     

东亚飞蝗发生的生态因素辨识及监测预测

基于前人研究成果,对中国东亚飞蝗发生的孕灾环境及其主要影响生态因素进行辨识.结果表明:蝗灾的动态变化与气候变化关系密切;飞蝗分布界限受气候带的影响;发生基地具有类似的孕灾环境特征;飞蝗发生发展与水文、气候、土壤和植被等主要生态因素的一定指标阈值有密切关系;传统的飞蝗预测研究多着重分析各生态因子与飞蝗消长的数理统计相关关系,近年多在大尺度气候背景下探讨适宜中长期的预测方法,国内外利用遥感等多种现代化手段对蝗灾进行大范围监测.     

OPTICAL MONITORING AND FORECASTING SYSTEMS FOR HARMFUL ALGAL BLOOMS: POSSIBILITY OR PIPE DREAM?

Monitoring programs for harmful algal blooms (HABs) are currently reactive and provide little or no means for advance warning. Given this, the development of algal forecasting systems would be of great use because they could guide traditional monitoring programs and provide a proactive means for responding to HABs. Forecasting systems will require near real-time observational capabilities and hydrodynamic/biological models designed to run in the forecast mode. These observational networks must detect and forecast over ecologically relevant spatial/ temporal scales. One solution is to incorporate a multiplatform optical approach utilizing remote sensing and in situ moored technologies. Recent advances in instrumentation and data-assimilative modeling may provide the components necessary for building an algal forecasting system. This review will outline the utility and hurdles of optical approaches in HAB detection and monitoring. In all the approaches, the desired HAB information must be isolated and extracted from the measured bulk optical signals. Examples of strengths and weaknesses of the current approaches to deconvolve the bulk optical properties are illustrated. After the phytoplankton signal has been isolated, species-recognition algorithms will be required, and we demonstrate one approach developed for Gymnodinium breve Davis. Pattern-recognition algorithms will be species-specific, reflecting the acclimation state of the HAB species of interest.Field data will provide inputs to optically based ecosystem models, which are fused to the observational networks through data-assimilation methods. Potential model structure and data-assimilation methods are reviewed.     

大型水母迁移规律和灾害监测预警技术研究进展

20世纪80年代以来,全球大型水母灾害发生频率与成灾种类不断增加,已严重影响了近海海洋渔业、沿海工业、滨海旅游业和海洋生态系统,已引起了各国政府高度重视,并且越来越多海洋工作者投身水母迁移等科学研究和监测预警工作中。回顾近年来国内外学者对水母漂移聚集和溯源等迁移规律的研究进展以及水母灾害监测预警工作现状。水母研究为预测预警工作服务,应侧重于开展系统的水母海上和室内试验,建立业务化立体监测体系;加强水母漂移聚集机理研究,建立更完善的水母预警模式。     

The role of vegetation–microclimate feedback in promoting shrub encroachment in the northern Chihuahuan desert

Many arid and semi‐arid landscapes around the world are affected by a shift from grassland to shrubland vegetation, presumably induced by climate warming, increasing atmospheric CO₂ concentrations, and/or changing land use. This major change in vegetation cover is likely sustained by positive feedbacks with the physical environment. Recent research has focused on a feedback with microclimate, whereby cold intolerant shrubs increase the minimum nocturnal temperatures in their surroundings. Despite the rich literature on the impact of land cover change on local climate conditions, changes in microclimate resulting from shrub expansion into desert grasslands have remained poorly investigated. It is unclear to what extent such a feedback can affect the maximum extent of shrub expansion and the configuration of a stable encroachment front. Here, we focus on the case of the northern Chihuahuan desert, where creosotebush (Larrea tridentata) has been replacing grasslands over the past 100–150 years. We use a process‐based coupled atmosphere‐vegetation model to investigate the role of this feedback in sustaining shrub encroachment in the region. Simulations indicate that the feedback allows juvenile shrubs to establish in the grassland during average years and, once established, reduce their vulnerability to freeze‐induced mortality by creating a warmer microclimate. Such a feedback is crucial in extreme cold winters as it may reduce shrub mortality. We identify the existence of a critical zone in the surroundings of the encroachment front, in which vegetation dynamics are bistable: in this zone, vegetation can be stable both as grassland and as shrubland. The existence of these alternative stable states explains why in most cases the shift from grass to shrub cover is found to be abrupt and often difficult to revert.     

A Bayesian forecasting model: predicting U.S. male mortality

This article presents a Bayesian approach to forecast mortality rates. This approach formalizes the Lee-Carter method as a statistical model accounting for all sources of variability. Markov chain Monte Carlo methods are used to fit the model and to sample from the posterior predictive distribution. This paper also shows how multiple imputations can be readily incorporated into the model to handle missing data and presents some possible extensions to the model. The methodology is applied to U.S. male mortality data. Mortality rate forecasts are formed for the period 1990-1999 based on data from 1959-1989. These forecasts are compared to the actual observed values. Results from the forecasts show the Bayesian prediction intervals to be appropriately wider than those obtained from the Lee-Carter method, correctly incorporating all known sources of variability. An extension to the model is also presented and the resulting forecast variability appears better suited to the observed data.     

水稻二化螟［Chilo suppressalis（Walker）］发生期预测模型的探讨

本文利用福建省永安市１９７８－１９８８年诱虫灯下二化螟蛾发生期资料和气象资料,通过影响因子与预测对象的相关分析来选择初选因子．再应用逐步判别分析方法建立第一代二化螟蛾发生期的预测模型。经对历史资料的回报检验,该模型的判别率达９０．１－１００％;经１９８９和１９９０年实报,预报等级符合实际发生等级。     

Poised to prosper? A cross‐system comparison of climate change effects on native and non‐native species performance

Climate change and biological invasions are primary threats to global biodiversity that may interact in the future. To date, the hypothesis that climate change will favour non‐native species has been examined exclusively through local comparisons of single or few species. Here, we take a meta‐analytical approach to broadly evaluate whether non‐native species are poised to respond more positively than native species to future climatic conditions. We compiled a database of studies in aquatic and terrestrial ecosystems that reported performance measures of non‐native (157 species) and co‐occurring native species (204 species) under different temperature, CO₂ and precipitation conditions. Our analyses revealed that in terrestrial (primarily plant) systems, native and non‐native species responded similarly to environmental changes. By contrast, in aquatic (primarily animal) systems, increases in temperature and CO₂ largely inhibited native species. There was a general trend towards stronger responses among non‐native species, including enhanced positive responses to more favourable conditions and stronger negative responses to less favourable conditions. As climate change proceeds, aquatic systems may be particularly vulnerable to invasion. Across systems, there could be a higher risk of invasion at sites becoming more climatically hospitable, whereas sites shifting towards harsher conditions may become more resistant to invasions.