A new global dataset of bioclimatic indicators

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This study presents a new global gridded dataset of bioclimatic indicators at 0.5° by 0.5° resolution for historical and future conditions. The dataset, called CMCC-BioClimInd, provides a set of 35 bioclimatic indices, expressed as mean values over each time interval, derived from post-processing both climate reanalysis for historical period (1960–1999) and an ensemble of 11 bias corrected CMIP5 simulations under two greenhouse gas concentration scenarios for future climate projections along two periods (2040–2079 and 2060–2099). This new dataset complements the availability of spatialized bioclimatic information, crucial aspect in many ecological and environmental wide scale applications and for several disciplines, including forestry, biodiversity conservation, plant and landscape ecology. The data of individual indicators are publicly available for download in the commonly used Network Common Data Form 4 (NetCDF4) format.

Highlights

  • Background & SummaryClimate change impacts, affecting primarily ecosystems’ functions and human sectors, have become a crucial topic within the scientific community and most recently across the whole society and sustainable development efforts

  • Under faster and faster environmental modifications over lands[4], climate datasets and efficient processing chains applied on them allow answering many urgent questions of biogeographical sciences about climate change impacts on living organisms, even through the interactions they have with the surrounding natural resources, like water and soil

  • The primary data source to derive BioClimInd for future time horizons are the outputs of climate model simulations that, despite the substantial progress occurred in the last few decades, are still affected by both systematic and random errors preventing their direct use in climate impact studies without affecting their reliability[13,14,15]

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Summary

Background & SummaryExpand/Collapse icon

Climate change impacts, affecting primarily ecosystems’ functions and human sectors, have become a crucial topic within the scientific community (https://www.ipcc.ch/working-group/wg2/) and most recently across the whole society and sustainable development efforts (https://sustainabledevelopment.un.org/sdg[13]). The primary data source to derive BioClimInd for future time horizons are the outputs of climate model simulations that, despite the substantial progress occurred in the last few decades, are still affected by both systematic and random errors preventing their direct use in climate impact studies without affecting their reliability[13,14,15]. The CMCC-BioClimInd dataset contributes to widening the availability of spatial information useful to the community by (1) providing an ensemble of bioclimatic indicators for the historical and future time frames (e.g. Figs 1 and 2) (2) adopting models and/or other analysis methods for robust (i.e. taking into account uncertainty) climate change impacts’ assessments, at broad scale and in a wide range of research fields such as wildlife ecology, natural resources’ conservation and management, climate impacts’ mitigation. The exploitation of indicators instead of just raw climate variables enables easier inferring of relationships between the studied topic (species occurrence, resources availability etc.) and the climate regime to support decision for complex systems[36]; on the other hand, using the ensemble allows considering the variability across simulations due to the different models’ physics and the uncertain future development pathways[37]

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CitationsShowing 10 of 79 papers
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Evaluation of machine learning algorithms in predicting bluetongue virus infection occurrence based on different combinations of predictive risk factors
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Abstract Background:Bluetongue virus(BTV) is an arbovirus that causes lots of economic losses worldwide. The most common method of transmission is by vectorCulicoidesmidges. Due to this close relationship between the BTV infection and the vectors, many climate-related risk factors play a role in the occurrence of the disease. The predictive ability of Logistic Regression (LR), Support Vector Machines (SVM), Decision Tree (DT), Random Forest (RF), XGBoost and Artificial Neural Networks (ANN) algorithms in predicting the BTV infection occurrence was assessed. Evaluated predictive risk factors included 19 standard bioclimatic variables, meteorological variables, ruminant population density, elevation and land cover data.Results:Based on the results of the ExtraTreesClassifier algorithm, 19 variables were identified as important features in prediction which mostly included bioclimatic variables related to temperature. Different combinations of predictive risk factors were evaluated in separate models.ANN and RF algorithms, especially when all predictor variables were included together showed the best performance in predicting the BTV infection occurrence.Conclusions:RF and ANN algorithms outperformed other machine learning methods in predicting the occurrence of BTV infection, especially when all predictive risk factors were included. Moreover, compared to meteorological, ruminant population density, altitude and land cover features, bioclimatic variables especially those related to temperature played a more important role in predicting the occurrence of BTV infection using machine learning algorithms. The results of the present study could be helpful in planning BTV infection surveillance and adopting control and preventive strategies.

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Mapping bioclimatic units of Oaxaca in Mexico: A systematic assessment
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Bioclimatic classification (WBCS), which examines the relationship between vegetation distribution and climatic variables such as precipitation and temperature, is essential for understanding the ecological dynamics. This research focuses on producing a detailed bioclimatic map of Oaxaca, Mexico, at a spatial resolution of 30 arc-seconds, using the methodology developed by Rivas-Martínez et al. (2011). Oaxaca, characterised by its complex topography and diverse climatic conditions, provides a unique opportunity to study bioclimatic patterns in a tropical region. Using high-resolution climate data from Chelsa database, we identified and mapped different bioclimates, variants, thermotypes and ombrotypes horizons and levels of continentality within the tropical macrobioclimate. Our analysis revealed a rich diversity of bioclimatic zones, reflecting the complex interplay between Oaxaca’s physical geography and its bioclimates. The results, presented in high resolution maps, highlight the spatial variability and complexity of Oaxaca’s bioclimatic landscape. These findings are crucial for several applications, including biodiversity conservation, agricultural planning and climate change adaptation strategies. By providing an accurate bioclimatic classification, this study makes a significant contribution to bioclimatology and could give valuable insights into climate-vegetation relationships in tropical regions. This detailed bioclimatic map improves our understanding of the current ecological status of Oaxaca and serves as a critical tool for future environmental planning and conservation efforts. Furthermore, it could be the basis for planning in national programs that consider agriculture and forests in Mexico such as Programa Sembrando Vida (PSV).

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Checking bioclimatic variables that combine temperature and precipitation data before their use in species distribution models
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  • Austral Ecology
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Abstract The 19 BIOCLIM variables available from the WorldClim databases have become the most widely used set of climatic variables for creating species distribution models (SDMs) and ecological niche models (ENMs). Nevertheless, in recent years, there has been an increasing trend to exclude four of these variables from SDM/ENM analyses. The four values concerned are interactive as they combine both temperature and precipitation assessments. Their exclusion was justified initially due to discontinuities in their interpolated surfaces observed in a study using data from version 1 of WorldClim. The discontinuities were thought to be artefacts of the measures used, and such sudden changes were unlikely to be biologically meaningful. A freely available biodiversity database and an open access geographic information system were used here to check the four interactive variables for discontinuities in data from both versions 1 and 2 of WorldClim. Over most of the world, the four interactive BIOCLIM variables from WorldClim were found to change smoothly. Major and minor discontinuities, however, were noted for all four variables in specific parts of some of the six continents (excluding Antarctica) covered by WorldClim databases. Discontinuities were related to sudden changes in the quarterly periods used to calculate the variables. These discontinuities were often found in equatorial regions where there are only small changes in temperature across the year. Bimodal precipitation distributions may also cause problems. It is recommended that the quick and simple method described here should be used to facilitate visual inspection and numerical checking for possible discontinuities of these variables before SDM/ENM analyses. If discontinuities are found for an interactive variable in the study area, it is recommended that the variable should not be used. Ways in which the four variables could be recalculated when new databases are created are suggested to reduce discontinuity problems.

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The Intergovernmental Panel on Climate Change (IPCC) provides regular scientific assessments on climate change, its implications, and potential future risks based on estimated energy matrixes and policy pathways. The aim of this publication is to assess the risks climate change poses to biodiversity using projected IPCC climate scenarios for the period 2081–2100, combined with key species-sensitivity indicators and variables as a response to climate change projections. In doing so, we address how climate-change-driven pressures may affect biodiversity. Additionally, a novel causal relationship between extreme ambient temperature exposure levels and the corresponding effects on individual species, noted in this paper as the Upper Thermal-Tolerance Limit and Species Sensitivity Distribution (UTTL-SSD), provides a compelling explanation of how global warming affects biodiversity. Our study indicates that North American and Oceanian sites with humid continental and subtropical climates, respectively, are poised to realize temperature shifts that have been identified as potential key tipping-point triggers. Heat stress may significantly affect approximately 60–90% of mammals, 50% of birds, and 50% of amphibians in North American and Oceanian sites for durations ranging from 5 to 84 days per year from 2080. In the humid temperate oceanic climate of European sites, the climate conditions remain relatively stable; however, moderate cumulative effects on biodiversity have been identified, and additional biodiversity-assemblage threat profiles exist to represent these. Both the integration of IPCC-IUCN profiles and the UTTL-SSD response relationship for the species communities considered have resulted in the identification of the projected threats that climate pressures may impose under the considered IPCC scenarios, which would result in biodiversity degradation. The UTTL-SSD responses developed can be used to highlight potential breakdowns among trophic levels in food web structures, highlighting an additional critical element when addressing biodiversity and ecosystem concerns.

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In this study, the current distribution probability of Ephedra gerardiana (Somalata), a medicinally potent species of the Himalayas, was assessed, and its spatial distribution change was forecasted until the year 2100 under three Shared Socioeconomic Pathways. Here, we used the maximum entropy model (MaxEnt) on 274 spatially filtered occurrence data points accessed from GBIF and other publications, and 19 bioclimatic variables were used as predictors against the probability assessment. The area under the curve, Continuous Boyce Index, True Skill Statistics, and kappa values were used to evaluate and validate the model. It was observed that the SSP5-8.5, a fossil fuel-fed scenario, saw a maximum habitat decline for E. gerardiana driving its niche towards higher altitudes. Nepal Himalayas witnessed a maximum decline in suitable habitat for the species, whereas it gained area in Bhutan. In India, regions of Himachal Pradesh, Uttarakhand, Jammu and Kashmir, and Sikkim saw a maximum negative response to climate change by the year 2100. Mean annual temperature, isothermality, diurnal temperature range, and precipitation seasonality are the most influential variables isolated by the model that contribute in defining the species' habitat. The results provide evidence of the effects of climate change on the distribution of endemic species in the study area under different scenarios of emissions and anthropogenic coupling. Certainly, the area of consideration encompasses several protected areas, which will become more vulnerable to increased variability of climate, and regulating their boundaries might become a necessary step to conserve the regions' biodiversity in the future.

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Projection of Thermal Bioclimate of Egypt for the Paris Agreement Goals
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This paper presents the likely changes in the thermal bioclimate of Egypt under the Paris Agreement, which aimed to restrict global warming to increase by 1.5–2.0 °C. A mean multi-model ensemble (MME) of eight global climate models were employed to evaluate the two shared socioeconomic paths (SSP) scenarios SSP1-1.9 and SSP1-2.6, which indicated scenarios for 1.5 and 2.0 °C rates of warming, respectively. The spatial distribution of the observed bioclimate indicated higher values in the south and southeast regions. The findings showed that there was an increase in Egypt’s mean temperature by rates of 1.3 and 1.5 °C for SSP1-1.9 and SSP1-2.6, respectively, with a higher increase in the southeast. The SSP1-2.6 scenario showed a gradual temperature rise with time, while SSP1-1.9 projected a decrease in the far future. The daily temperature variation decreased in the same region, but this effect was amplified in the north by 0.2 °C. The seasonality decreased by −0.8 to −2.3% without any shift in isothermality. The maximum summer temperature increased more (1.3–2.2 °C) than the minimum winter temperature (0.9–1.5 °C), causing an increase in inter-seasonal variability. Most bioclimatic indicators more rapidly rose in the north and northeast regions of Egypt, according to the geographical distribution of their projections.

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Comparing the Performance of CMCC-BioClimInd and WorldClim Datasets in Predicting Global Invasive Plant Distributions.
  • Apr 26, 2023
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  • Feixue Zhang + 3 more

Species distribution modeling (SDM) has been widely used to predict the distribution of invasive plant species based on bioclimatic variables. However, the specific selection of these variables may affect the performance of SDM. This investigation elucidates a new bioclimate variable dataset (i.e., CMCC-BioClimInd) for its use in SDM. The predictive performance of SDM that includes WorldClim and CMCC-BioClimInd was evaluated by AUC and omission rate and the explanatory power of both datasets was assessed by the jackknife method. Furthermore, the ODMAP protocol was used to record CMCC-BioClimInd to ensure reproducibility. The results indicated that CMCC-BioClimInd effectively simulates invasive plant species' distribution. Based on the contribution rate of CMCC-BioClimInd to the distribution of invasive plant species, it was inferred that the modified and simplified continentality and Kira warmth index from CMCC-BioClimInd had a strong explanatory power. Under the 35 bioclimatic variables of CMCC-BioClimInd, alien invasive plant species are mainly distributed in equatorial, tropical, and subtropical regions. We tested a new bioclimate variable dataset to simulate the distribution of invasive plant species worldwide. This method has great potential to improve the efficiency of species distribution modeling, thereby providing a new perspective for risk assessment and management of global invasive plant species.

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A simple modelling approach was used to investigate the influence of habitat fragmentation on the distributions and regional population sizes of passerines breeding in 145 small woods in an arable landscape. Observed distributions in three consecutive years were compared with those predicted by random selection of woods by pairs (based on a Poisson distribution), and by a simulation model based on the area of habitat available and estimates of individual species minimum area requirements and territory sizes. None of the species studied were distributed randomly; some were distributed according to the area of woodland available, whereas others preferred either small or large woods. However, species distributions were influenced by their regional population sizes. When species population sizes were small, observed distributions could be predicted using algorithms based on area alone, but as numbers increased, algorithms using territory parameters were required. An absence of detectable territorial interaction suggested that space for more pairs of the species concerned had been available in our woods. Of the 14 species investigated, the models for only two consistently required the use of territory parameters, indicating that the available habitat could probably have accommodated more pairs of most of the species. Thus habitat fragmentation may reduce regional population sizes more than expected from the loss of habitat alone, to the extent that patches of suitable habitat may be unused, or occupied at low density.

  • Research Article
  • Cite Count Icon 24
  • 10.1098/rspb.1998.0383
Contemporary environmental correlates of endemic bird areas derived from meteorological satellite sensors
  • Jun 7, 1998
  • Proceedings of the Royal Society of London. Series B: Biological Sciences
  • D.D.P Johnson + 2 more

The present-day distribution of centres of endemism is the result of an interplay between historical biogeography and contemporary environmental conditions. The relative importance of these two factors has never been established, however, for want of information on both the distributions themselves and the continental-scale measurement of environmental variables. Recently published maps of avian endemism in Africa, and the increasing availability of continental-scale surrogates of climatic conditions derived from Earth-orbiting satellites, has allowed this problem to be addressed directly. In this paper, temporal-Fourier-processed surrogate meteorological data derived from the National Oceanic and Atmospheric Administration's series of polar-orbiting meteorological satellites and from the geostationary Meteosat satellites are used within a discriminant analytical framework to describe and predict areas of bird endemism in East Africa. The technique predicts endemic bird areas (EBAs) with an accuracy of 89% (mean 85%, range 70 to 89%). Contemporary environmental conditions, ultimately determined by climate, therefore appear to account for a substantial fraction of the observed variation in the distribution of EBAs. On the basis of these results, several hypotheses proposed to explain the distribution of centres of avian endemism are reviewed.

  • Research Article
  • Cite Count Icon 59
  • 10.1111/rec.12342
Using trait‐based ecology to restore resilient ecosystems: historical conditions and the future of montane forests in western North America
  • Feb 10, 2016
  • Restoration Ecology
  • Daniel C Laughlin + 3 more

Historical reference conditions have provided empirical benchmarks for guiding ecological restoration but the relevance of historical conditions has been questioned in this era of rapid global change. Trait‐based ecology offers an alternative approach for setting restoration objectives. If we understand which phenotypic traits confer high survival in a given environment, then we can restore assemblages of species with favorable trait combinations to reduce mortality risk, achieve functional outcomes, and enhance restoration success. Our objective was to compare restoration prescriptions based on historical reference conditions versus trait‐based objectives in southwestern United States mixed conifer forests. To optimize survival and enhance resilience under projected increasing frequencies of fire and drought, we constructed and evaluated models based on combinations of three traits: thick bark, dense wood, and moderate leaf nitrogen concentration. Models with multiple traits accurately derived historical species abundance distributions, which is a necessary condition for the application of trait‐based models under less certain future conditions. Model results indicated that trait‐based restoration objectives could be achieved in two ways: by manipulating abundances of species that already coexist at a site or by adding native species from warmer climates to the local species pool. The latter approach may create no‐analog communities of native species. Restoration goals based on either historical reference conditions or future projections are special cases of a more general class of desired future conditions that are derived from trait‐based objectives. Functional ecology provides a general, flexible, and theory‐based approach to restoring resilient ecosystems at a time of rapid environmental change.

  • Research Article
  • Cite Count Icon 1
  • 10.5846/stxb201604240775
1981-2015年我国大陆地区景观生态学研究文献分析
  • Jan 1, 2016
  • Acta Ecologica Sinica
  • 赵文武 Zhao Wenwu + 1 more

PDF HTML阅读 XML下载 导出引用 引用提醒 1981-2015年我国大陆地区景观生态学研究文献分析 DOI: 10.5846/stxb201604240775 作者: 作者单位: 北京师范大学,北京师范大学 资源学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目(41390462) A bibliometric analysis of landscape ecology in China mainland between 1981 and 2015 Author: Affiliation: Beijing Normal University,Beijing Normal University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在我国大陆地区,景观生态学已走过35周年,国际景观生态学会中国分会已经正式成立20周年。以“景观生态学”为主题词,检索得到1981-2015年我国大陆地区景观生态学学者发表的相关文献,对文献数量、文献期刊分布、文献所属研究机构、文献内容和文献国际影响力5个方面进行统计分析,得到关于我国大陆地区景观生态学研究发展历程和现状的几点认识。(1)我国大陆地区景观生态学研究按发表文献数量状况可划分为3个阶段:1981-1989年,景观生态相关研究较少,学科处于引进、吸收的初始阶段;1990-2006年,文献数量迅猛增长,我国大陆地区景观生态学学科发展成熟并壮大;2007年至今,景观生态学研究平稳发展,在思索中寻求创新。(2)我国大陆地区景观生态学研究文献发表刊物以生态、农业、资源与环境、地理测绘和园林领域刊物为主,刊物影响因子差别明显,景观生态学专业期刊在我国大陆地区有所欠缺。(3)景观生态学研究机构主要为以中国科学院生态环境研究中心和中国科学院沈阳应用生态研究所为代表的中国科学院研究所和以北京大学、北京林业大学和北京师范大学为代表的高校,各研究机构发挥所处地理环境优势和自身学科特色,对不同类型景观展开深入研究。(4)我国大陆地区景观生态学研究内容主要包括学科理论与技术方法、景观格局-生态过程-尺度的相互作用机制、景观生态学的部门应用等,其研究主题包括城市、农业、湿地、园林、气候变化、生物多样性、景观可持续等众多方面,其研究范式正经历着从“格局-过程-尺度”向“格局-过程-服务-可持续性”的变化过程。(5)就英文文献的发文量和被引频次而言,我国大陆地区景观生态学研究是国际景观生态学研究的重要组成部分,但其国际影响力有待于进一步提升。 Abstract:Landscape ecology is an interdisciplinary field that investigates landscape units, spatial patterns, and ecological processes. It can be used to improve landscape protection, management, planning, design, and sustainability at many different scales. The development of landscape ecology in China mainland began 35 years ago in1981 when the subject was introduced into China mainland for the first time. The International Association of Landscape Ecology in China (IALE China) was established in 1995. This study describes the development and status of landscape ecology research in China mainland by analyzing the articles published in the CNKI and Web of Science databases between1981 and 2015. The key term used for the literature search was landscape ecology, and both Chinese and English articles written by scientists in China mainland were included. The analysis of the detailed information was based on the number of related articles, journal names, research institutes, articles content, and international influence. The research results were as follows: (1) The development of landscape ecology in China mainland could be divided into three stages according to the number of related articles per year. Between 1981 and 1989, there was little research on landscape ecology in China mainland and the discipline was in its introduction and early development phase. Between 1990 and 2006, the number of related articles per year increased rapidly and landscape ecology in China mainland developed rapidly. Since 2007, landscape ecology in China mainland has been in a steady development phase where it has always been a challenging task to innovate and develop new ideas. (2) Articles on landscape ecology research in China mainland were published in ecology, agriculture, resources and environment, geographical mapping and architecture journals. There are no specialized journals on landscape ecology in China mainland, and the relative journals have different impact factors. (3) In terms of the number of published papers, the major research institutions for landscape ecology were the Chinese Academy of Sciences, such as the Research Center for Eco-Environmental Sciences and the Shenyang Institute of Applied Ecology; Peking University; Beijing Forestry University; and Beijing Normal University. They carried out comprehensive studies on landscape ecology by integrating geographical concerns with their own subject characteristics. (4) There were different research priorities at different periods of time; and three Chinese landscape ecology research areas were identified by key words analysis. These were landscape ecology discipline and technology research, the interaction mechanisms between landscape pattern, ecological processes, and scale, and the application of landscape ecology to different areas. Landscape ecology in China mainland included urban areas, agriculture, wetlands, gardens, climate change, biodiversity, and landscape sustainability, etc. The research paradigm for landscape ecology evolved from a “pattern-process-scale” to “pattern-process-service-sustainability”. (5) When the number and citation frequencies of articles included in Web of Science database were taken into account, China mainland’s international status in the field of landscape ecology has improved significantly since the 1990s. The total number of articles from China mainland was ranked 5th in the world. Although China mainland’s landscape ecology research contribution was an important part of international landscape ecology research, the article citation frequencies were low and its international influence may need to improve. The reference searching methods used in this study had serious limitations, and it was difficult to collect all the landscape ecology articles published by the scientists from China mainland. However, the 20th birthday of IALE-China is an appropriate time to review the progress made by the scientists over the last 35 years in the area of landscape ecology. 参考文献 相似文献 引证文献

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