Terrestrial models and global change: challenges for the future

A wide variety of models have illustrated the potential importance of terrestrial biological feedbacks on climate and climate change; yet our ability to make precise predictions is severely limited, due to a high degree of uncertainty. In this paper, after briefly reviewing current models, we present challenges for new terrestrial models and introduce a simple mechanistic approach that may complement existing approaches.     

Amazonian biogenic volatile organic compounds under global change

Biogenic volatile organic compounds (BVOCs) play important roles at cellular, foliar, ecosystem and atmospheric levels. The Amazonian rainforest represents one of the major global sources of BVOCs, so its study is essential for understanding BVOC dynamics. It also provides insights into the role of such large and biodiverse forest ecosystem in regional and global atmospheric chemistry and climate. We review the current information on Amazonian BVOCs and identify future research priorities exploring biogenic emissions and drivers, ecological interactions, atmospheric impacts, depositional processes and modifications to BVOC dynamics due to changes in climate and land cover. A feedback loop between Amazonian BVOCs and the trends of climate and land‐use changes in Amazonia is then constructed. Satellite observations and model simulation time series demonstrate the validity of the proposed loop showing a combined effect of climate change and deforestation on BVOC emission in Amazonia. A decreasing trend of isoprene during the wet season, most likely due to forest biomass loss, and an increasing trend of the sesquiterpene to isoprene ratio during the dry season suggest increasing temperature stress‐induced emissions due to climate change.     

Towards an integrated global framework to assess the impacts of land use and management change on soil carbon: current capability and future vision

Intergovernmental Panel on Climate Change (IPCC) Tier 1 methodologies commonly underpin project‐scale carbon accounting for changes in land use and management and are used in frameworks for Life Cycle Assessment and carbon footprinting of food and energy crops. These methodologies were intended for use at large spatial scales. This can introduce error in predictions at finer spatial scales. There is an urgent need for development and implementation of higher tier methodologies that can be applied at fine spatial scales (e.g. farm/project/plantation) for food and bioenergy crop greenhouse gas (GHG) accounting to facilitate decision making in the land‐based sectors. Higher tier methods have been defined by IPCC and must be well evaluated and operate across a range of domains (e.g. climate region, soil type, crop type, topography), and must account for land use transitions and management changes being implemented. Furthermore, the data required to calibrate and drive the models used at higher tiers need to be available and applicable at fine spatial resolution, covering the meteorological, soil, cropping system and management domains, with quantified uncertainties. Testing the reliability of the models will require data either from sites with repeated measurements or from chronosequences. We review current global capability for estimating changes in soil carbon at fine spatial scales and present a vision for a framework capable of quantifying land use change and management impacts on soil carbon, which could be used for addressing issues such as bioenergy and biofuel sustainability, food security, forest protection, and direct/indirect impacts of land use change. The aim of this framework is to provide a globally accepted standard of carbon measurement and modelling appropriate for GHG accounting that could be applied at project to national scales (allowing outputs to be scaled up to a country level), to address the impacts of land use and land management change on soil carbon.     

Observed range dynamics of South African amphibians under conditions of global change

Changes in the size and location of species ranges are a recognized response to environmental changes. We assessed recent range dynamics of South African amphibians using data consolidated by the South African Frog Atlas Project, which provided both historical (1905–1995) and recent distribution data (1996–2003). Sampling differences were accounted for using a correction factor and subsampling protocols. Changes to the size of species ranges and shifts in the mean range centre for latitude, longitude and altitude were assessed. Most (70%) of the assessed species showed range contractions. Of the expected climate change predictions, only upslope shifts were supported (mean 47.6 m). There were no significant mean latitudinal shifts for the assessed group of species. Species of the Bushveld region shifted northwesterly and upslope, while species of the Winter Rainfall region also shifted northwesterly. The small, though significant, general taxon‐wide trends where minor in comparison to the wide variety of idiosyncratic, species‐specific range changes that were observed. The species‐specific observed range changes that were documented should be used to further investigate range change drivers on an individual species basis.     

The global distribution of cultivable lands: current patterns and sensitivity to possible climate change

Aim This study makes quantitative global estimates of land suitability for cultivation based on climate and soil constraints. It evaluates further the sensitivity of croplands to any possible changes in climate and atmospheric CO₂ concentrations. Location The location is global, geographically explicit. Methods The methods used are spatial data synthesis and analysis and numerical modelling. Results There is a cropland ‘reserve’ of 120%, mainly in tropical South America and Africa. Our climate sensitivity analysis indicates that the southern provinces of Canada, north‐western and north‐central states of the United States, northern Europe, southern Former Soviet Union and the Manchurian plains of China are most sensitive to changes in temperature. The Great Plains region of the United States and north‐eastern China are most sensitive to changes in precipitation. The regions that are sensitive to precipitation change are also sensitive to changes in CO₂, but the magnitude is small compared to the influence of direct climate change. We estimate that climate change, as simulated by global climate models, will expand cropland suitability by an additional 16%, mainly in the Northern Hemisphere high latitudes. However, the tropics (mainly Africa, northern South America, Mexico and Central America and Oceania) will experience a small decrease in suitability due to climate change. Main conclusions There is a large reserve of cultivable croplands, mainly in tropical South America and Africa. However, much of this land is under valuable forests or in protected areas. Furthermore, the tropical soils could potentially lose fertility very rapidly once the forest cover is removed. Regions that lie at the margins of temperature or precipitation limitation to cultivation are most sensitive to changes in climate and atmospheric CO₂ concentration. It is anticipated that climate change will result in an increase in cropland suitability in the Northern Hemisphere high latitudes (mainly in developed nations), while the tropics will lose suitability (mainly in developing nations).     

全球变化影响下的生态系统风险的相关理论及联系

全球变化深刻影响着全球生态系统,全球变化胁迫超过一定程度则会导致生态系统恢复力下降,极端事件频发,从而使生态系统服务功能退化甚至丧失.量化全球变化的风险,进而制定恰当的人为适应策略是目前应对全球变化的重要途径.全球变化可能降低生态系统的恢复力,从而导致生态系统脆弱性升高,引发生态系统退化风险.目前,相关研究多依托基于星...     

Decoupling of greenhouse gas emissions from global agricultural production: 1970–2050

Since 1970 global agricultural production has more than doubled; contributing ~1/4 of total anthropogenic greenhouse gas (GHG) burden in 2010. Food production must increase to feed our growing demands, but to address climate change, GHG emissions must decrease. Using an identity approach, we estimate and analyse past trends in GHG emission intensities from global agricultural production and land‐use change and project potential future emissions. The novel Kaya–Porter identity framework deconstructs the entity of emissions from a mix of multiple sources of GHGs into attributable elements allowing not only a combined analysis of the total level of all emissions jointly with emissions per unit area and emissions per unit product. It also allows us to examine how a change in emissions from a given source contributes to the change in total emissions over time. We show that agricultural production and GHGs have been steadily decoupled over recent decades. Emissions peaked in 1991 at ~12 Pg CO₂‐eq. yr^?1 and have not exceeded this since. Since 1970 GHG emissions per unit product have declined by 39% and 44% for crop‐ and livestock‐production, respectively. Except for the energy‐use component of farming, emissions from all sources have increased less than agricultural production. Our projected business‐as‐usual range suggests that emissions may be further decoupled by 20–55% giving absolute agricultural emissions of 8.2–14.5 Pg CO₂‐eq. yr^?1 by 2050, significantly lower than many previous estimates that do not allow for decoupling. Beyond this, several additional costcompetitive mitigation measures could reduce emissions further. However, agricultural GHG emissions can only be reduced to a certain level and a simultaneous focus on other parts of the food‐system is necessary to increase food security whilst reducing emissions. The identity approach presented here could be used as a methodological framework for more holistic food systems analysis.     

Increasing population and declining biological resources in the context of global change and globalization

In the context of over-consumption of natural resources in the name of development and rapid industrialization by a small section of the human population that is rapidly growing, the world is currently faced with a variety of environmental uncertainties. ‘Global change’ covering a whole variety of ecological issues, and ‘globalization’ in an economic sense, are two major phenomena that are responsible for these uncertainties. There is increasing evidence to suggest that the developing countries more than the developed, particularly the marginalized traditional (those living close to nature and natural resources) societies would be the worst sufferers. In order to cope with this problem in a situation where the traditional societies have to cope with rapidly depleting biodiversity on which they are dependant for their livelihood, there is an urgent need to explore additional pathways for sustainable management of natural resources and societal development. Such pathways should be based on a landscape management strategy, that takes into consideration the rich traditional ecological knowledge (TEK) that these societies have. This is critical because TEK is the connecting link between conservation and sustainable development. This paper explores the possibilities in this direction through a balanced approach to development, that links the ‘traditional’ with the ‘modern’, in a location-specific way.     

全球变化下植物物候研究的关键问题

总结了全球变化下植物物候研究的主要进展,针对该领域国内外的几个热点问题进行了讨论。植物物候研究的重心从以前的野外观测和初步统计分析逐步过渡到以揭示物候周期的调控机制和环境效应为主,研究手段从植物物候对环境变化做出反应的表象描述转移到多尺度、多要素耦合关系的综合分析。随着学科交叉研究的不断深入,植物物候研究从植物个体及居群适应性研究转向植物物候变化对生态系统、气候演变、农业生产乃至人类健康等方面影响的系统评估。并且在该转变过程中出现了几个关键性问题,如不同温度带大气温度与光周期对植物物候期贡献力问题、植物物候变化对气候变暖的非线性响应特征、群落水平上植物物候研究的复杂性、以及农业生态系统中作物物候研究的重要性等。对我国植物物候研究现状和管理体系中亟待解决的问题提出了建议。     

Land use for animal production in global change studies: Defining and characterizing a framework

Land use for animal production influences the earth system in a variety of ways, including local‐scale modification to biodiversity, soils, and nutrient cycling; regional changes in albedo and hydrology; and global‐scale changes in greenhouse gas and aerosol concentrations. Pasture is furthermore the single most extensive form of land cover, currently comprising about 22–26% of the earth's ice‐free land surface. Despite the importance and variable expressions of animal production, distinctions among different systems are effectively absent from studies of land use and land cover change. This deficiency is improving; however, livestock production system classifications are rarely applied in this context, and the most popular global land cover inventories still present only a single, usually poorly defined category of “pasture” or “rangeland” with no characterization of land use. There is a marked lack of bottom‐up, evidence‐based methodology, creating a pressing need to incorporate cross‐disciplinary evidence of past and present animal production systems into global change studies. Here, we present a framework, modified from existing livestock production systems, that is rooted in sociocultural, socioeconomic, and ecological contexts. The framework defines and characterizes the range of land usage pertaining to animal production, and is suitable for application in land use inventories and scenarios, land cover modeling, and studies on sustainable land use in the past, present, and future.     

Current and future distribution of a parasite with complex life cycle under global change scenarios: Echinococcus multilocularis in Europe

Global change is expected to have complex effects on the distribution and transmission patterns of zoonotic parasites. Modelling habitat suitability for parasites with complex life cycles is essential to further our understanding of how disease systems respond to environmental changes, and to make spatial predictions of their future distributions. However, the limited availability of high quality occurrence data with high spatial resolution often constrains these investigations. Using 449 reliable occurrence records for Echinococcus multilocularis from across Europe published over the last 35 years, we modelled habitat suitability for this parasite, the aetiological agent of alveolar echinococcosis, in order to describe its environmental niche, predict its current and future distribution under three global change scenarios, and quantify the probability of occurrence for each European country. Using a machine learning approach, we developed large-scale (25 × 25 km) species distribution models based on seven sets of predictors, each set representing a distinct biological hypothesis supported by current knowledge of the autecology of the parasite. The best-supported hypothesis included climatic, orographic and land-use/land-cover variables such as the temperature of the coldest quarter, forest cover, urban cover and the precipitation seasonality. Future projections suggested the appearance of highly suitable areas for E. multilocularis towards northern latitudes and in the whole Alpine region under all scenarios, while decreases in habitat suitability were predicted for central Europe. Our spatially explicit predictions of habitat suitability shed light on the complex responses of parasites to ongoing global changes.     

Climate change impacts on selected global rangeland ecosystem services

Rangelands are Earth's dominant land cover and are important providers of ecosystem services. Reliance on rangelands is projected to grow, thus understanding the sensitivity of rangelands to future climates is essential. We used a new ecosystem model of moderate complexity that allows, for the first time, to quantify global changes expected in rangelands under future climates. The mean global annual net primary production (NPP) may decline by 10 g C m^?2 year^?1 in 2050 under Representative Concentration Pathway (RCP) 8.5, but herbaceous NPP is projected to increase slightly (i.e., average of 3 g C m^?2 year^?1). Responses vary substantially from place‐to‐place, with large increases in annual productivity projected in northern regions (e.g., a 21% increase in productivity in the US and Canada) and large declines in western Africa (?46% in sub‐Saharan western Africa) and Australia (?17%). Soil organic carbon is projected to increase in Australia (9%), the Middle East (14%), and central Asia (16%) and decline in many African savannas (e.g., ?18% in sub‐Saharan western Africa). Livestock are projected to decline 7.5 to 9.6%, an economic loss of from $9.7 to $12.6 billion. Our results suggest that forage production in Africa is sensitive to changes in climate, which will have substantial impacts on the livelihoods of the more than 180 million people who raise livestock on those rangelands. Our approach and the simulation tool presented here offer considerable potential for forecasting future conditions, highlight regions of concern, and support analyses where costs and benefits of adaptations and policies may be quantified. Otherwise, the technical options and policy and enabling environment that are needed to facilitate widespread adaptation may be very difficult to elucidate.     

Predicted future distribution of the African skimmer in response to a changing climate,land cover and distance from water in the mid-Zambezi Valley

Climate models project a hot and dry future for Southern Africa. In this research, Maximum Entropy was used to model the extent to which climate change, land cover and distance from water edges may influence current and future distribution of the African skimmer in the mid-Zambezi Valley. Global Biodiversity Information Facility data collected between the years 2000–2019 were used to develop the models. Three models were built: one for current distribution and two for future distribution under Representative Concentration Pathways (RCPs) 2.6 and 6.0. Results revealed that annual precipitation and distance from water edges were the most important predictors of habitat suitability for the African skimmer under current and future climate. Temperature and land cover were least important in explaining current and future distribution of the species. The RCP 2.6 predicted future decrease in suitable habitat for the African skimmer in the mid-Zambezi Valley, while RCP 6.0 predicted future increase in suitable habitat for the species. This research conclusively revealed that precipitation and distance from water edges were consistently key predictors of suitable habitat for the African skimmer.     

Land management: data availability and process understanding for global change studies

In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human‐induced changes in terrestrial ecosystems that do not result in land‐cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one‐tenth of the ice‐free land surface is under intense human management, half under medium and one‐fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling.     

Challenges in using land use and land cover data for global change studies

Land use and land cover data play a central role in climate change assessments. These data originate from different sources and inventory techniques. Each source of land use/cover data has its own domain of applicability and quality standards. Often data are selected without explicitly considering the suitability of the data for the specific application, the bias originating from data inventory and aggregation, and the effects of the uncertainty in the data on the results of the assessment. Uncertainties due to data selection and handling can be in the same order of magnitude as uncertainties related to the representation of the processes under investigation. While acknowledging the differences in data sources and the causes of inconsistencies, several methods have been developed to optimally extract information from the data and document the uncertainties. These methods include data integration, improved validation techniques and harmonization of classification systems. Based on the data needs of global change studies and the data availability, recommendations are formulated aimed at optimal use of current data and focused efforts for additional data collection. These include: improved documentation using classification systems for land use/cover data; careful selection of data given the specific application and the use of appropriate scaling and aggregation methods. In addition, the data availability may be improved by the combination of different data sources to optimize information content while collection of additional data must focus on validation of available data sets and improved coverage of regions and land cover types with a high level of uncertainty. Specific attention in data collection should be given to the representation of land management (systems) and mosaic landscapes.     

The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – http://www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.     

Quantifying small‐scale deforestation and forest degradation in African woodlands using radar imagery

Carbon emissions from tropical land‐use change are a major uncertainty in the global carbon cycle. In African woodlands, small‐scale farming and the need for fuel are thought to be reducing vegetation carbon stocks, but quantification of these processes is hindered by the limitations of optical remote sensing and a lack of ground data. Here, we present a method for mapping vegetation carbon stocks and their changes over a 3‐year period in a > 1000 km² region in central Mozambique at 0.06 ha resolution. L‐band synthetic aperture radar imagery and an inventory of 96 plots are combined using regression and bootstrapping to generate biomass maps with known uncertainties. The resultant maps have sufficient accuracy to be capable of detecting changes in forest carbon stocks of as little as 12 MgC ha^?1 over 3 years with 95% confidence. This allows characterization of biomass loss from deforestation and forest degradation at a new level of detail. Total aboveground biomass in the study area was reduced by 6.9 ± 4.6% over 3 years: from 2.13 ± 0.12 TgC in 2007 to 1.98 ± 0.11 TgC in 2010, a loss of 0.15 ± 0.10 TgC. Degradation probably contributed 67% (96.9 ± 91.0 GgC) of the net loss of biomass, but is associated with high uncertainty. The detailed mapping of carbon stock changes quantifies the nature of small‐scale farming. New clearances were on average small (median 0.2 ha) and were often additions to already cleared land. Deforestation events reduced biomass from 33.5 to 11.9 MgC ha^?1 on average_. Contrary to expectations, we did not find evidence that clearances were targeted towards areas of high biomass. Our method is scalable and suitable for monitoring land cover change and vegetation carbon stocks in woodland ecosystems, and can support policy approaches towards reducing emissions from deforestation and degradation (REDD).     

附生植物对全球变化的响应及其生物指示作用

附生植物是一类生活在其他植物体上但不从宿主载体吸收营养和水分的特殊植物,其特有的形态结构和生态习性导致了它们对周围环境变化具有高度的敏感性和脆弱性.研究附生植物对全球变化的响应及其生物指示作用,具有重要的指导意义和应用价值.本文概述了附生植物对大气组成变化、气候变化和土地利用/覆盖方式转变等全球变化事件的响应及其生物指...