All Papers

Edward H. Allison, Allison L. Perry, Marie‐Caroline Badjeck, W. Neil Adger et al.

Abstract Anthropogenic global warming has significantly influenced physical and biological processes at global and regional scales. The observed and anticipated changes in global climate present significant opportunities and challenges for societies and economies. We compare the vulnerability of 132 national economies to potential climate change impacts on their capture fisheries using an indicator‐based approach. Countries in Central and Western Africa (e.g. Malawi, Guinea, Senegal, and Uganda), Peru and Colombia in north‐western South America, and four tropical Asian countries (Bangladesh, Cambodia, Pakistan, and Yemen) were identified as most vulnerable. This vulnerability was due to the combined effect of predicted warming, the relative importance of fisheries to national economies and diets, and limited societal capacity to adapt to potential impacts and opportunities. Many vulnerable countries were also among the world’s least developed countries whose inhabitants are among the world’s poorest and twice as reliant on fish, which provides 27% of dietary protein compared to 13% in less vulnerable countries. These countries also produce 20% of the world’s fish exports and are in greatest need of adaptation planning to maintain or enhance the contribution that fisheries can make to poverty reduction. Although the precise impacts and direction of climate‐driven change for particular fish stocks and fisheries are uncertain, our analysis suggests they are likely to lead to either increased economic hardship or missed opportunities for development in countries that depend upon fisheries but lack the capacity to adapt.

Eckehard G. Brockerhoff, Hervé Jactel, John A. Parrotta, Christopher P. Quine et al.

Losses of natural and semi-natural forests, mostly to agriculture, are a significant concern for biodiversity. Against this trend, the area of intensively managed plantation forests increases, and there is much debate about the implications for biodiversity. We provide a comprehensive review of the function of plantation forests as habitat compared with other land cover, examine the effects on biodiversity at the landscape scale, and synthesise context-specific effects of plantation forestry on biodiversity. Natural forests are usually more suitable as habitat for a wider range of native forest species than plantation forests but there is abundant evidence that plantation forests can provide valuable habitat, even for some threatened and endangered species, and may contribute to the conservation of biodiversity by various mechanisms. In landscapes where forest is the natural land cover, plantation forests may represent a low-contrast matrix, and afforestation of agricultural land can assist conservation by providing complementary forest habitat, buffering edge effects, and increasing connectivity. In contrast, conversion of natural forests and afforestation of natural non-forest land is detrimental. However, regional deforestation pressure for agricultural development may render plantation forestry a 'lesser evil' if forest managers protect indigenous vegetation remnants. We provide numerous context-specific examples and case studies to assist impact assessments of plantation forestry, and we offer a range of management recommendations. This paper also serves as an introduction and background paper to this special issue on the effects of plantation forests on biodiversity.

Ashraf Dewan, Yasushi Yamaguchi

Monika Böhm, Ben Collen, Jonathan Baillie, Philip Bowles et al.

Effective and targeted conservation action requires detailed information about species, their distribution, systematics and ecology as well as the distribution of threat processes which affect them. Knowledge of reptilian diversity remains surprisingly disparate, and innovative means of gaining rapid insight into the status of reptiles are needed in order to highlight urgent conservation cases and inform environmental policy with appropriate biodiversity information in a timely manner. We present the first ever global analysis of extinction risk in reptiles, based on a random representative sample of 1500 species (16% of all currently known species). To our knowledge, our results provide the first analysis of the global conservation status and distribution patterns of reptiles and the threats affecting them, highlighting conservation priorities and knowledge gaps which need to be addressed urgently to ensure the continued survival of the world’s reptiles. Nearly one in five reptilian species are threatened with extinction, with another one in five species classed as Data Deficient. The proportion of threatened reptile species is highest in freshwater environments, tropical regions and on oceanic islands, while data deficiency was highest in tropical areas, such as Central Africa and Southeast Asia, and among fossorial reptiles. Our results emphasise the need for research attention to be focussed on tropical areas which are experiencing the most dramatic rates of habitat loss, on fossorial reptiles for which there is a chronic lack of data, and on certain taxa such as snakes for which extinction risk may currently be underestimated due to lack of population information. Conservation actions specifically need to mitigate the effects of human-induced habitat loss and harvesting, which are the predominant threats to reptiles.

Wenju Cai, Lixin Wu, Matthieu Lengaigne, Tim Li et al.

The El Niño-Southern Oscillation (ENSO), which originates in the Pacific, is the strongest and most well-known mode of tropical climate variability. Its reach is global, and it can force climate variations of the tropical Atlantic and Indian Oceans by perturbing the global atmospheric circulation. Less appreciated is how the tropical Atlantic and Indian Oceans affect the Pacific. Especially noteworthy is the multidecadal Atlantic warming that began in the late 1990s, because recent research suggests that it has influenced Indo-Pacific climate, the character of the ENSO cycle, and the hiatus in global surface warming. Discovery of these pantropical interactions provides a pathway forward for improving predictions of climate variability in the current climate and for refining projections of future climate under different anthropogenic forcing scenarios.

Shaikh Shamim Hasan, Lin Zhen, Md. Giashuddin Miah, Tofayel Ahamed et al.

Changes in land use and ecosystem services influence each other and such changes have consequences for human wellbeing. In this paper, we review the research literature on how different types of ecosystem services are affected by LUC, and the consequences for human well-being. We begin with a review of the different types of ecosystem services. We examine the influence of LUC on provisioning ecosystem services due to mismatches between agricultural production and hydrological systems. We continue with a review of the impacts of LUC on supporting ecosystem services through the conversion of an ecosystem to cultivated land, and the resulting changes in soil properties and the hydrological balance. Next, We also discuss the regulating ecosystem services which are affected by LUC and alters water purification processes, as well as the effects on cultural ecosystem services. We conclude with a review of the valuation and quantification of the effects of LUC on the management of ecosystem services, and propose future research directions. Most of the research reveals a negative impact of LUC on ecosystem services, despite research gaps related to methods for valuing ecosystem services more accurately and for collecting social responses to the impacts of LUC on different ecosystem services.

Md. Manjurul Hussain, Ishtiak Mahmud

Trend analysis is one of the most important measurements in studying time series data. Both parametric and non-parametric tests are commonly used in trend analysis. Parametric tests require data to be independent and normally distributed. On the other hand, non-parametric trend tests require only that the data be independent and can tolerate outliers in the data However, parametric tests are more powerful than nonparametric ones.

Jennifer Luedtke, Janice Chanson, Kelsey Neam, Louise Hobin et al.

Abstract Systematic assessments of species extinction risk at regular intervals are necessary for informing conservation action 1,2 . Ongoing developments in taxonomy, threatening processes and research further underscore the need for reassessment 3,4 . Here we report the findings of the second Global Amphibian Assessment, evaluating 8,011 species for the International Union for Conservation of Nature Red List of Threatened Species. We find that amphibians are the most threatened vertebrate class (40.7% of species are globally threatened). The updated Red List Index shows that the status of amphibians is deteriorating globally, particularly for salamanders and in the Neotropics. Disease and habitat loss drove 91% of status deteriorations between 1980 and 2004. Ongoing and projected climate change effects are now of increasing concern, driving 39% of status deteriorations since 2004, followed by habitat loss (37%). Although signs of species recoveries incentivize immediate conservation action, scaled-up investment is urgently needed to reverse the current trends.

As a global society, we need to take action not only to prevent the potentially catastrophic effects of climate change but also to adapt to the unavoidable effects of climate change already imposed on the world. Fairness in Adaptation to Climate Change looks at the challenges of ensuring that policy responses to climate change do not place undue and unfair burdens on already vulnerable populations. All countries will be endangered by climate change risks from flood, drought, and other extreme weather events, but developing countries are more dependent on climate-sensitive livelihoods such as farming and fishing and hence are more vulnerable. Despite this, the concerns of developing countries are marginalized in climate policy decisions that exacerbate current vulnerabilities. Fairness in Adaptation to Climate Change brings together scholars from political science, economics, law, human geography, and climate science to offer the first assessment of the social justice issues in adaptation to climate change. The book outlines the philosophical underpinnings of different types of justice in relation to climate change, present inequities, and future burdens, and it applies these to real world examples of climate change adaptation in Bangladesh, Tanzania, Botswana, Namibia, and Hungary. It argues that the key to adapting to climate change lies in recognizing the equity and justice issues inherent in its causes and in human responses to it. Contributors W. Neil Adger, Paul Baer, Jon Barnett, Maria Bohn, Kirstin Dow, Saleemul Huq, Roger E. Kasperson, Mizan R. Khan, Janica Lane, Neil A. Leary, Robin Leichenko, Joanne Linnerooth-Bayer, M. J. Mace, Karen O'Brien, Jouni Paavola, Stephen H. Schneider, David S. G. Thomas, Chasca Twyman, Anna Vári

M. Mofijur, I.M. Rizwanul Fattah, Md. Asraful Alam, A. B. M. Saiful Islam et al.

COVID-19 has heightened human suffering, undermined the economy, turned the lives of billions of people around the globe upside down, and significantly affected the health, economic, environmental and social domains. This study aims to provide a comprehensive analysis of the impact of the COVID-19 outbreak on the ecological domain, the energy sector, society and the economy and investigate the global preventive measures taken to reduce the transmission of COVID-19. This analysis unpacks the key responses to COVID-19, the efficacy of current initiatives, and summarises the lessons learnt as an update on the information available to authorities, business and industry. This review found that a 72-hour delay in the collection and disposal of waste from infected households and quarantine facilities is crucial to controlling the spread of the virus. Broad sector by sector plans for socio-economic growth as well as a robust entrepreneurship-friendly economy is needed for the business to be sustainable at the peak of the pandemic. The socio-economic crisis has reshaped investment in energy and affected the energy sector significantly with most investment activity facing disruption due to mobility restrictions. Delays in energy projects are expected to create uncertainty in the years ahead. This report will benefit governments, leaders, energy firms and customers in addressing a pandemic-like situation in the future.

Roy Brouwer, Sonia Akter, Luke Brander, Enamul Haque

In this article we investigate the complex relationship between environmental risk, poverty, and vulnerability in a case study carried out in one of the poorest and most flood-prone countries in the world, focusing on household and community vulnerability and adaptive coping mechanisms. Based upon the steadily growing amount of literature in this field we develop and test our own analytical model. In a large-scale household survey carried out in southeast Bangladesh, we ask almost 700 floodplain residents living without any flood protection along the River Meghna about their flood risk exposure, flood problems, flood damage, and coping mechanisms. Novel in our study is the explicit testing of the effectiveness of adaptive coping strategies to reduce flood damage costs. We show that, households with lower income and less access to productive natural assets face higher exposure to risk of flooding. Disparity in income and asset distribution at community level furthermore tends to be higher at higher risk exposure levels, implying that individually vulnerable households are also collectively more vulnerable. Regarding the identification of coping mechanisms to deal with flood events, we look at both the ex ante household level preparedness for flood events and the ex post availability of community-level support and disaster relief. We find somewhat paradoxically that the people that face the highest risk of flooding are the least well prepared, both in terms of household-level ex ante preparedness and community-level ex post flood relief.

Abu Reza Md. Towfiqul Islam, Swapan Talukdar, Susanta Mahato, Sonali Kundu et al.

Floods are one of nature's most destructive disasters because of the immense damage to land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods. Therefore, earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters. In this study, we applied and assessed two new hybrid ensemble models, namely Dagging and Random Subspace (RS) coupled with Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM) which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin, the northern region of Bangladesh. The application of these models includes twelve flood influencing factors with 413 current and former flooding points, which were transferred in a GIS environment. The information gain ratio, the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors. For the validation and the comparison of these models, for the ability to predict the statistical appraisal measures such as Freidman, Wilcoxon signed-rank, and t-paired tests and Receiver Operating Characteristic Curve (ROC) were employed. The value of the Area Under the Curve (AUC) of ROC was above 0.80 for all models. For flood susceptibility modelling, the Dagging model performs superior, followed by RF, the ANN, the SVM, and the RS, then the several benchmark models. The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.

Frauke Feser, Burkhardt Rockel, Hans von Storch, Jörg Winterfeldt et al.

An important challenge in current climate modeling is to realistically describe small-scale weather statistics, such as topographic precipitation and coastal wind patterns, or regional phenomena like polar lows. Global climate models simulate atmospheric processes with increasingly higher resolutions, but still regional climate models have a lot of advantages. They consume less computation time because of their limited simulation area and thereby allow for higher resolution both in time and space as well as for longer integration times. Regional climate models can be used for dynamical down-scaling purposes because their output data can be processed to produce higher resolved atmospheric fields, allowing the representation of small-scale processes and a more detailed description of physiographic details (such as mountain ranges, coastal zones, and details of soil properties). However, does higher resolution add value when compared to global model results? Most studies implicitly assume that dynamical downscaling leads to output fields that are superior to the driving global data, but little work has been carried out to substantiate these expectations. Here a series of articles is reviewed that evaluate the benefit of dynamical downscaling by explicitly comparing results of global and regional climate model data to the observations. These studies show that the regional climate model generally performs better for the medium spatial scales, but not always for the larger spatial scales. Regional models can add value, but only for certain variables and locations—particularly those influenced by regional specifics, such as coasts, or mesoscale dynamics, such as polar lows. Therefore, the decision of whether a regional climate model simulation is required depends crucially on the scientific question being addressed.

Albert Klein Tank, T. C. Peterson, Dewan Abdul Quadir, Singay Dorji et al.

Changes in indices of climate extremes are studied on the basis of daily series of temperature and precipitation observations from 116 meteorological stations in central and south Asia. Averaged over all stations, the indices of temperature extremes indicate warming of both the cold tail and the warm tail of the distributions of daily minimum and maximum temperature between 1961 and 2000. For precipitation, most regional indices of wet extremes show little change in this period as a result of low spatial trend coherence with mixed positive and negative station trends. Relative to the changes in the total amounts, there is a slight indication of disproportionate changes in the precipitation extremes. Stations with near‐complete data for the longer period of 1901–2000 suggest that the recent trends in extremes of minimum temperature are consistent with long‐term trends, whereas the recent trends in extremes of maximum temperature are part of multidecadal climate variability.

Tanjena Rume, S. M. Didar-Ul Islam

The global outbreak of coronavirus disease 2019 (COVID-19) is affecting every part of human lives, including the physical world. The measures taken to control the spread of the virus and the slowdown of economic activities have significant effects on the environment. Therefore, this study intends to explore the positive and negative environmental impacts of the COVID-19 pandemic, by reviewing the available scientific literatures. This study indicates that, the pandemic situation significantly improves air quality in different cities across the world, reduces GHGs emission, lessens water pollution and noise, and reduces the pressure on the tourist destinations, which may assist with the restoration of the ecological system. In addition, there are also some negative consequences of COVID-19, such as increase of medical waste, haphazard use and disposal of disinfectants, mask, and gloves; and burden of untreated wastes continuously endangering the environment. It seems that, economic activities will return soon after the pandemic, and the situation might change. Hence, this study also outlines possible ways to achieve long-term environmental benefits. It is expected that the proper implementation of the proposed strategies might be helpful for the global environmental sustainability.

Shamsuddin Shahid, Houshang Behrawan

Heidi Kreibich, Anne F. Van Loon, Kai Schröter, Philip J. Ward et al.

Abstract Risk management has reduced vulnerability to floods and droughts globally 1,2 , yet their impacts are still increasing 3 . An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data 4,5 . On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change 3 .

Mansour Almazroui, Sajjad Saeed, Fahad Saeed, M. Nazrul Islam et al.

Abstract The latest Coupled Model Intercomparison Project phase 6 (CMIP6) dataset was analyzed to examine the projected changes in temperature and precipitation over six South Asian countries during the twenty-first century. The CMIP6 model simulations reveal biases in annual mean temperature and precipitation over South Asia in the present climate. In the historical period, the median of the CMIP6 model ensemble systematically underestimates the annual mean temperature for all the South Asian countries, while a mixed behavior is shown in the case of precipitation. In the future climate, the CMIP6 models display higher sensitivity to greenhouse gas emissions over South Asia compared with the CMIP5 models. The multimodel ensemble from 27 CMIP6 models projects a continuous increase in the annual mean temperature over South Asia during the twenty-first century under three future scenarios. The projected temperature shows a large increase (over 6 °C under SSP5-8.5 scenario) over the northwestern parts of South Asia, comprising the complex Karakorum and Himalayan mountain ranges. Any large increase in the mean temperature over this region will most likely result in a faster rate of glacier melting. By the end of the twenty-first century, the annual mean temperature (uncertainty range) over South Asia is projected to increase by 1.2 (0.7–2.1) °C, 2.1 (1.5–3.3) °C, and 4.3 (3.2–6.6) °C under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively, relative to the present (1995–2014) climate. The warming over South Asia is also continuous on the seasonal time scale. The CMIP6 models projected higher warming in the winter season than in the summer over South Asia, which if verified will have repercussions for snow/ice accumulations as well as winter cropping patterns. The annual mean precipitation is also projected to increase over South Asia during the twenty-first century under all scenarios. The rate of change in the projected annual mean precipitation varies considerably between the South Asian countries. By the end of the twenty-first century, the country-averaged annual mean precipitation (uncertainty range) is projected to increase by 17.1 (2.2–49.1)% in Bangladesh, 18.9 (−4.9 to 72)% in Bhutan, 27.3 (5.3–160.5)% in India, 19.5 (−5.9 to 95.6)% in Nepal, 26.4 (6.4–159.7)% in Pakistan, and 25.1 (−8.5 to 61.0)% in Sri Lanka under the SSP5-8.5 scenario. The seasonal precipitation projections also shows large variability. The projected winter precipitation reveals a robust increase over the western Himalayas, with a corresponding decrease over the eastern Himalayas. On the other hand, the summer precipitation shows a robust increase over most of the South Asia region, with the largest increase over the arid region of southern Pakistan and adjacent areas of India, under the high-emission scenario. The results presented in this study give detailed insights into CMIP6 model performance over the South Asia region, which could be extended further to develop adaptation strategies, and may act as a guideline document for climate change related policymaking in the region.

Gerald A. Meehl, Julie M. Arblaster, William D. Collins

Abstract A six-member ensemble of twentieth-century simulations with changes to only time-evolving global distributions of black carbon aerosols in a global coupled climate model is analyzed to study the effects of black carbon (BC) aerosols on the Indian monsoon. The BC aerosols act to increase lower-tropospheric heating over South Asia and reduce the amount of solar radiation reaching the surface during the dry season, as noted in previous studies. The increased meridional tropospheric temperature gradient in the premonsoon months of March–April–May (MAM), particularly between the elevated heat source of the Tibetan Plateau and areas to the south, contributes to enhanced precipitation over India in those months. With the onset of the monsoon, the reduced surface temperatures in the Bay of Bengal, Arabian Sea, and over India that extend to the Himalayas act to reduce monsoon rainfall over India itself, with some small increases over the Tibetan Plateau. Precipitation over China generally decreases due to the BC aerosol effects. There is a weakened latitudinal SST gradient resulting from BC aerosols in the model simulations as seen in the observations, and this is present in the multiple-forcings experiments with the Community Climate System Model, version 3 (CCSM3), which includes natural and anthropogenic forcings (including BC aerosols). The BC aerosols and consequent weakened latitudinal SST gradient in those experiments are associated with increased precipitation during MAM in northern India and over the Tibetan Plateau, with some decreased precipitation over southwest India, the Bay of Bengal, Burma, Thailand, and Malaysia, as seen in observations. During the summer monsoon season, the model experiments show that BC aerosols have likely contributed to observed decreasing precipitation trends over parts of India, Bangladesh, Burma, and Thailand. Analysis of single ensemble members from the multiple-forcings experiment suggests that the observed increasing precipitation trends over southern China appear to be associated with natural variability connected to surface temperature changes in the northwest Pacific.