陆地生物圈模型的发展与应用

陆地生物圈与大气圈和水圈之间能量、水和碳氮等元素的交换和循环对整个地球系统产生了深刻的影响。陆地生物圈模型(TBM)是研究陆地生态系统如何响应和反馈全球变化的重要方法和工具。通过对从生态系统到区域和全球陆地生物圈不同空间尺度的植被动态、生物地球物理和生物地球化学循环过程、水循环和水文过程、自然干扰和人类活动等过程时间动态的模拟, 陆地生物圈模型被广泛地应用于评估和归因过去陆地生物圈的时空变化和预测陆地生物圈对未来全球变化的响应和反馈。该文简要回顾了陆地生物圈模型的发展, 总结了模型对陆地生态系统主要过程的刻画和模型在生态系统生态学的应用, 并对未来陆地生物圈模型的发展和应用进行了展望。     

A closer look at novel climates: new methods and insights at continental to landscape scales

Novel climates – emerging conditions with no analog in the observational record – are an open problem in ecological modeling. Detecting extrapolation into novel conditions is a critical step in evaluating bioclimatic projections of how species and ecosystems will respond to climate change. However, biologically informed novelty detection methods remain elusive for many modeling algorithms. To assist with bioclimatic model design and evaluation, we present a first‐approximation assessment of general novelty based on a simple and consistent characterization of climate. We build on the seminal global analysis of Williams et al. (2007 PNAS, 104, 5738) by assessing of end‐of‐21st‐century novelty for North America at high spatial resolution and by refining their standardized Euclidean distance into an intuitive Mahalanobian metric called sigma dissimilarity. Like this previous study, we found extensive novelty in end‐of‐21st‐century projections for the warm southern margin of the continent as well as the western Arctic. In addition, we detected localized novelty in lower topographic positions at all latitudes: By the end of the 21st century, novel climates are projected to emerge at low elevations in 80% and 99% of ecoregions in the RCP4.5 and RCP8.5 emissions scenarios, respectively. Novel climates are limited to 7% of the continent's area in RCP4.5, but are much more extensive in RCP8.5 (40% of area). These three risk factors for novel climates – regional susceptibility, topographic position, and the magnitude of projected climate change – represent a priori evaluation criteria for the credibility of bioclimatic projections. Our findings indicate that novel climates can emerge in any landscape. Interpreting climatic novelty in the context of nonlinear biological responses to climate is an important challenge for future research.     

Spatial scale affects novel and disappeared climate change projections in Alaska

The formation of novel and disappeared climates between the last glacial maximum (LGM) and the present is important to consider to understand the expansion and contraction of species niches and distributions, as well as the formation and loss of communities and ecological interactions over time. Our choice in climate data resolution has the potential to complicate predictions of the ecological impacts of climate change, since climate varies from local to global scales and this spatial variation is reflected in climate data. To address this issue, we downscaled LGM and modern (1975–2005) 30‐year averaged climate data to 60‐m resolution for the entire state of Alaska for 10 different climate variables, and then upsampled each variable to coarser resolutions (60 m to 12 km). We modeled the distributions of novel and disappeared climates to evaluate the locations and fractional area of novel and disappeared climates for each of our climate variables and resolutions. Generally, novel and disappeared climates were located in southern Alaska, although there were cases where some disappeared climates existed within coastal and interior Alaska. Climate resolution affected the fractional area of novel and disappeared climates in three patterns: As the spatial resolution of climate became coarser, the fractional area of novel and disappeared climates (a) increased, (b) decreased, or (c) had no explainable relationship. Overall, we found the use of coarser climate data increased the fractional area of novel and disappeared climates due to decreased environmental variability and removal of climate extremes. Our results reinforce the importance of downscaling coarse climate data and suggest that studies analyzing the effects of climate change on ecosystems may overestimate or underestimate their conclusions when utilizing coarse climate data.     

Conservation implications of adaptation to tropical climates from a historical perspective

Tropical climates and the biodiversity associated with them have long interested natural historians. Alexander von Humboldt inspired a generation of scientists, such as Charles Darwin and Alfred Russel Wallace, to observe and study tropical ecosystems. More recently, the mid‐20th century saw Theodosius Dobzhansky and Daniel Janzen lay the foundations for studying adaptation to tropical climates. Now in the 21st century, we are beginning to realize the threats posed by current and future climate change to tropical populations which, despite relatively low levels of projected warming for low‐latitude regions, face potentially significant detrimental impacts. Building on the insights of researchers in decades and centuries past, improved understanding of tropical ecology, evolution and biogeography will help us to conceive how future global change will impact on biodiversity.     

Time of emergence of novel climates for North American migratory bird populations

To better understand the ecological implications of global climate change for species that display geographically and seasonally dynamic life‐history strategies, we need to determine where and when novel climates are projected to first emerge. Here, we use a multivariate approach to estimate time of emergence (ToE) of novel climates based on three climate variables (precipitation, minimum and maximum temperature) at a weekly temporal resolution within the Western Hemisphere over a 280‐yr period (2021–2300) under a high emissions scenario (RCP8.5). We intersect ToE estimates with weekly estimates of relative abundance for 77 passerine bird species that migrate between temperate breeding grounds in North America and southern tropical and subtropical wintering grounds using observations from the eBird citizen‐science database. During the non‐breeding season, migrants that winter within the tropics are projected to encounter novel climates during the second half of this century. Migrants that winter in the subtropics are projected to encounter novel climates during the first half of the next century. During the beginning of the breeding season, migrants on their temperate breeding grounds are projected to encounter novel climates during the first half of the next century. During the end of the breeding season, migrants are projected to encounter novel climates during the second half of this century. Thus, novel climates will first emerge ca 40–50 yr earlier during the second half of the breeding season. These results emphasize the large seasonal and spatial variation in the formation of novel climates, and the pronounced challenges migratory birds are likely to encounter during this century, especially on their tropical wintering grounds and during the transition from breeding to migration. When assessing the ecological implications of climate change, our findings emphasize the value of applying a full annual cycle perspective using standardized metrics that promote comparisons across space and time.     

陆地生态系统碳密度格局研究概述

 准确了解陆地生态系统中碳密度的时空格局及其影响因子和作用机制,对于估算和预测不同类型生态系统中的植被和土壤的碳存储能力、判定碳汇、制定缓解全球变化的合理政策措施,具有重要意义。该文综述了现有研究中发现的世界陆地生态系统碳密度空间分布的地带性规律及中国陆地生态系统碳密度格局的独特特点。在全球尺度上,植被碳密度分布与植物生物量格局基本一致,除北方森林外其余大部分随纬度升高而减小;土壤碳密度则随纬度升高而增大。陆地生态系统中北方森林和热带森林的总体碳密度最高,不同的是,前者的碳主要集中在土壤中,而后者则集中在植被中。但在区域尺度上,由于气候、地形及人类活动影响,这种规律性可能会发生变化甚至不起作用。水热条件、土壤养分、生物多样性、气候和大气CO2浓度的变化以及土地利用与覆盖变化等是碳密度空间格局形成和发生变化的驱动因子。在某一特定区域,它们通过直接或间接提高植被净初级生产力,抑制呼吸和分解作用来增加陆地生态系统碳密度。综合分析特定时空条件下各因子对碳存储量的影响是解释碳密度分布现状,预测碳密度格局变化的关键,但目前的研究对各项驱动因子的作用机制、影响强度及多个因子间的相互作用仍不是很清楚,需要加强该方面的研究力度。碳密度研究中的数据获取、机理分析和过程模拟等方面仍存在很大的不确定性,因此有必要建立规范统一的碳密度测量估算系统和更为精准有效的估算模型,进行多尺度、多精度水平的综合研究。     

Implementing plant hydraulic architecture within the LPJ Dynamic Global Vegetation Model

Aim To implement plant hydraulic architecture within the Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ–DGVM), and to test the model against a set of observational data. If the model can reproduce major patterns in vegetation and ecosystem processes, we consider this to be an important linkage between plant physiology and larger‐scale ecosystem dynamics. Location The location is global, geographically distributed. Methods A literature review was carried out to derive model formulations and parameter values for representing the hydraulic characteristics of major global plant functional types (PFTs) in a DGVM. After implementing the corresponding formulations within the LPJ–DGVM, present‐day model output was compared to observational data. Results The model reproduced observed broad‐scale patterns in potential natural vegetation, but it failed to distinguish accurately between different types of grassland and savanna vegetation, possibly related to inadequate model representations of water fluxes in the soil and wildfire effects. Compared to a version of the model using an empirical formulation for calculating plant water supply without considering plant hydraulic architecture, the new formulation improved simulated patterns of vegetation in particular for dry shrublands. Global‐scale simulation results for runoff and actual evapotranspiration (AET) corresponded well to available data. The model also successfully reproduced the magnitude and seasonal cycle of AET for most EUROFLUX forests, while modelled variation in NPP across a large number of sites spanning several biomes showed a strong correlation with estimates from field measurements. Main conclusions The model was generally confirmed by comparison to observational data. The novel model representation of water flow within plants makes it possible to resolve mechanistically the effects of hydraulic differences between plant functional groups on vegetation structure, water cycling, and competition. This may be an advantage when predicting ecosystem responses to nonextant climates, in particular in areas dominated by dry shrubland vegetation.     

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co‐occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage‐level information.     

Back to the future: using historical climate variation to project near‐term shifts in habitat suitable for coast redwood

Studies that model the effect of climate change on terrestrial ecosystems often use climate projections from downscaled global climate models (GCMs). These simulations are generally too coarse to capture patterns of fine‐scale climate variation, such as the sharp coastal energy and moisture gradients associated with wind‐driven upwelling of cold water. Coastal upwelling may limit future increases in coastal temperatures, compromising GCMs’ ability to provide realistic scenarios of future climate in these coastal ecosystems. Taking advantage of naturally occurring variability in the high‐resolution historic climatic record, we developed multiple fine‐scale scenarios of California climate that maintain coherent relationships between regional climate and coastal upwelling. We compared these scenarios against coarse resolution GCM projections at a regional scale to evaluate their temporal equivalency. We used these historically based scenarios to estimate potential suitable habitat for coast redwood (Sequoia sempervirens D. Don) under ‘normal’ combinations of temperature and precipitation, and under anomalous combinations representative of potential future climates. We found that a scenario of warmer temperature with historically normal precipitation is equivalent to climate projected by GCMs for California by 2020–2030 and that under these conditions, climatically suitable habitat for coast redwood significantly contracts at the southern end of its current range. Our results suggest that historical climate data provide a high‐resolution alternative to downscaled GCM outputs for near‐term ecological forecasts. This method may be particularly useful in other regions where local climate is strongly influenced by ocean–atmosphere dynamics that are not represented by coarse‐scale GCMs.     

Predicting potential climate change impacts with bioclimate envelope models: a palaeoecological perspective

Aim We assess the realism of bioclimate envelope model projections for anticipated future climates by validating ecosystem reconstructions for the late Quaternary with fossil and pollen data. Specifically, we ask: (1) do climate conditions with no modern analogue negatively affect the accuracy of ecosystem reconstructions? (2) are bioclimate envelope model projections biased towards under‐predicting forested ecosystems? (3) given a palaeoecological perspective, are potential habitat projections for the 21st century within model capabilities? Location Western North America. Methods We used an ensemble classifier modelling approach (RandomForest) to spatially project the climate space of modern ecosystem classes throughout the Holocene (at 6000, 9000, 11,000, 14,000, 16,000, and 21,000 YBP) using palaeoclimate surfaces generated by two general circulation models (GFDL and CCM1). The degree of novel arrangement of climate variables was quantified with the multivariate Mahalanobis distance to the nearest modern climatic equivalent. Model projections were validated against biome classifications inferred from 1460 palaeoecological records. Results Model accuracy assessed against independent palaeoecology data is generally low for the present day, increases for 6000 YBP, and then rapidly declines towards the last glacial maximum, primarily due to the under‐prediction of forested biomes. Misclassifications were closely correlated with the degree of climate dissimilarity from the present day. For future projections, no‐analogue climates unexpectedly emerged in the coastal Pacific Northwest but were absent throughout the rest of the study area. Main conclusions Bioclimate envelope models could approximately reconstruct ecosystem distributions for the mid‐ to late‐Holocene but proved unreliable in the Late Pleistocene. We attribute this failure to a combination of no‐analogue climates and a potential lack of niche conservatism in tree species. However, climate dissimilarities in future projections are comparatively minor (similar to those of the mid‐Holocene), and we conclude that no‐analogue climates should not compromise the accuracy of model predictions for the next century.     

Predicting co-distribution patterns of parrots and woody plants under global changes: The case of the Lilac-crowned Amazon and Neotropical dry forests

Global climate and land-use changes are the most significant causes of the current habitat loss and biodiversity crisis. Although there is information measuring these global changes, we lack a full understanding of how they impact community assemblies and species interactions across ecosystems. Herein, we assessed the potential distribution of eight key woody plant species associated with the habitat of the endangered Lilac-crowned Amazon (Amazon finschi) under global changes scenarios (2050′s and 2070′s), to answer the following questions: (1) how do predicted climate and land-use changes impact these species’ individual distributions and co-distribution patterns?; and (2) how effective is the existing Protected Area network for safeguarding the parrot species, the plant species, and their biological interactions? Our projections were consistent identifying the species that are most vulnerable to climate change. The distribution ranges of most of the species tended to decrease under future climates. These effects were strongly exacerbated when incorporating land-use changes into models. Even within existing protected areas, >50 % of the species’ remaining distribution and sites with the highest plant richness were predicted to be lost in the future under these combined scenarios. Currently, both individual species ranges and sites of highest richness of plants, shelter a high proportion (ca. 40 %) of the Lilac-crowned Amazon distribution. However, this spatial congruence could be reduced in the future, potentially disrupting the ecological associations among these taxa. We provide novel evidence for decision-makers to enhance conservation efforts to attain the long-term protection of this endangered Mexican endemic parrot and its habitat.     

Why decadal to century timescale palaeoclimate data are needed to explain present‐day patterns of biological diversity and change

The current distribution of species, environmental conditions and their interactions represent only one snapshot of a planet that is continuously changing, in part due to human influences. To distinguish human impacts from natural factors, the magnitude and pace of climate shifts, since the Last Glacial Maximum, are often used to determine whether patterns of diversity today are artefacts of past climate change. In the absence of high‐temporal resolution palaeoclimate reconstructions, this is generally done by assuming that past climate change occurred at a linear pace between widely spaced (usually, ≥1,000 years) climate snapshots. We show here that this is a flawed assumption because regional climates have changed significantly across decades and centuries during glacial–interglacial cycles, likely causing rapid regional replacement of biota. We demonstrate how recent atmosphere‐ocean general circulation model (AOGCM) simulations of the climate of the past 21,000 years can provide credible estimates of the details of climate change on decadal to centennial timescales, showing that these details differ radically from what might be inferred from longer timescale information. High‐temporal resolution information can provide more meaningful estimates of the magnitude and pace of climate shifts, the location and timing of drivers of physiological stress, and the extent of novel climates. They also produce new opportunities to directly investigate whether short‐term climate variability is more important in shaping biodiversity patterns rather than gradual changes in long‐term climatic means. Together, these more accurate measures of past climate instability are likely to bring about a better understanding of the role of palaeoclimatic change and variability in shaping current macroecological patterns in many regions of the world.     

Tree‐ring analysis and modeling approaches yield contrary response of circumboreal forest productivity to climate change

Circumboreal forest ecosystems are exposed to a larger magnitude of warming in comparison with the global average, as a result of warming‐induced environmental changes. However, it is not clear how tree growth in these ecosystems responds to these changes. In this study, we investigated the sensitivity of forest productivity to climate change using ring width indices (RWI) from a tree‐ring width dataset accessed from the International Tree‐Ring Data Bank and gridded climate datasets from the Climate Research Unit. A negative relationship of RWI with summer temperature and recent reductions in RWI were typically observed in continental dry regions, such as inner Alaska and Canada, southern Europe, and the southern part of eastern Siberia. We then developed a multiple regression model with regional meteorological parameters to predict RWI, and then applied to these models to predict how tree growth will respond to twenty‐first‐century climate change (RCP8.5 scenario). The projections showed a spatial variation and future continuous reduction in tree growth in those continental dry regions. The spatial variation, however, could not be reproduced by a dynamic global vegetation model (DGVM). The DGVM projected a generally positive trend in future tree growth all over the circumboreal region. These results indicate that DGVMs may overestimate future wood net primary productivity (NPP) in continental dry regions such as these; this seems to be common feature of current DGVMs. DGVMs should be able to express the negative effect of warming on tree growth, so that they simulate the observed recent reduction in tree growth in continental dry regions.     

Predicting Novel Riparian Ecosystems in a Changing Climate

Rapid changes in global climate are likely to alter species assemblages and environmental characteristics resulting in novel ecosystems. The ability to predict characteristics of future ecosystems is crucial for environmental planning and the development of effective climate change adaptation strategies. This paper presents an approach for envisioning novel ecosystems in future climates. Focusing on riparian ecosystems, we use qualitative process models to predict likely abiotic and biotic changes in four case study systems: tropical coastal floodplains, temperate streams, high mountain streams and urban riparian zones. We concentrate on functional groups rather than individual species and consider dispersal constraints and the capacity for genetic adaptation. Our scenarios suggest that climatic changes will reduce indigenous diversity, facilitate non-indigenous invasion (especially C4 graminoids), increase fragmentation and result in simplified and less distinctive riparian ecosystems. Compared to models based on biota-environment correlations, process models built on mechanistic understanding (like Bayesian belief networks) are more likely to remain valid under novel climatic conditions. We posit that predictions based on species’ functional traits will facilitate regional comparisons and can highlight effects of climate change on ecosystem structure and function. Ecosystems that have experienced similar modification to that expected under climate change (for example, altered flow regimes of regulated rivers) can be used to help inform and evaluate predictions. By manipulating attributes of these system models (for example, magnitude of climatic changes or adaptation strategies used), implications of various scenarios can be assessed and optimal management strategies identified.     

森林碳库特征及驱动因子分析研究进展

森林碳库作为全球碳库的重要组成部分,在区域以及全球碳循环中发挥重要作用。森林生态系统有机碳库主要由3部分组成:活植物碳库、土壤有机质碳库和死植物体碳库。各碳库时空差异很大,使研究森林碳储存机制存在很大的不确定性。在全球或者区域尺度上,森林生物量(与森林碳储量密切相关)呈现出清晰的分布格局,但对于这些格局的驱动因子与地上生物量的相关关系和尺度外推程度尚有很大的争议。分别讨论了气候、土壤、地形和生物因子对地上生物量的影响;而后,从各生态因子与地上生物量之间的直接或者间接关系入手,分析了各因子与生物量之间的交互作用,认为目前运用相同的处理方式来研究环境因子和生物因子对森林生物量的影响是不合适的。文章最后介绍两种新的研究方法:层次模型和生境分类,以期用来重新评估生态因子对森林生物量的影响,有助于更准确的了解森林碳储存机制。     

Indicators of biodiversity and ecosystem services: a synthesis across ecosystems and spatial scales

According to the Millennium Ecosystem Assessment, common indicators are needed to monitor the loss of biodiversity and the implications for the sustainable provision of ecosystem services. However, a variety of indicators are already being used resulting in many, mostly incompatible, monitoring systems. In order to synthesise the different indicator approaches and to detect gaps in the development of common indicator systems, we examined 531 indicators that have been reported in 617 peer‐reviewed journal articles between 1997 and 2007. Special emphasis was placed on comparing indicators of biodiversity and ecosystem services across ecosystems (forests, grass‐ and shrublands, wetlands, rivers, lakes, soils and agro‐ecosystems) and spatial scales (from patch to global scale). The application of biological indicators was found most often focused on regional and finer spatial scales with few indicators applied across ecosystem types. Abiotic indicators, such as physico‐chemical parameters and measures of area and fragmentation, are most frequently used at broader (regional to continental) scales. Despite its multiple dimensions, biodiversity is usually equated with species richness only. The functional, structural and genetic components of biodiversity are poorly addressed despite their potential value across habitats and scales. Ecosystem service indicators are mostly used to estimate regulating and supporting services but generally differ between ecosystem types as they reflect ecosystem‐specific services. Despite great effort to develop indicator systems over the past decade, there is still a considerable gap in the widespread use of indicators for many of the multiple components of biodiversity and ecosystem services, and a need to develop common monitoring schemes within and across habitats. Filling these gaps is a prerequisite for linking biodiversity dynamics with ecosystem service delivery and to achieving the goals of global and sub‐global initiatives to halt the loss of biodiversity.     

Genomics of natural history collections for understanding evolution in the wild

A long‐standing question in biology is how organisms change through time and space in response to their environment. This knowledge is of particular relevance to predicting how organisms might respond to future environmental changes caused by human‐induced global change. Usually researchers make inferences about past events based on an understanding of current static genetic patterns, but these are limited in their capacity to inform on underlying past processes. Natural history collections (NHCs) represent a unique and critical source of information to provide temporally deep and spatially broad time‐series of samples. By using NHC samples, researchers can directly observe genetic changes over time and space and link those changes with specific ecological/evolutionary events. Until recently, such genetic studies were hindered by the intrinsic challenges of NHC samples (i.e. low yield of highly fragmented DNA). However, recent methodological and technological developments have revolutionized the possibilities in the novel field of NHC genomics. In this Special Feature, we compile a range of studies spanning from methodological aspects to particular case studies which demonstrate the enormous potential of NHC samples for accessing large genomic data sets from the past to advance our knowledge on how populations and species respond to global change at multiple spatial–temporal scales. We also highlight possible limitations, recommendations and a few opportunities for future researchers aiming to study NHC genomics.     

Meta-ecosystems: a theoretical framework for a spatial ecosystem ecology

This contribution proposes the meta‐ecosystem concept as a natural extension of the metapopulation and metacommunity concepts. A meta‐ecosystem is defined as a set of ecosystems connected by spatial flows of energy, materials and organisms across ecosystem boundaries. This concept provides a powerful theoretical tool to understand the emergent properties that arise from spatial coupling of local ecosystems, such as global source–sink constraints, diversity–productivity patterns, stabilization of ecosystem processes and indirect interactions at landscape or regional scales. The meta‐ecosystem perspective thereby has the potential to integrate the perspectives of community and landscape ecology, to provide novel fundamental insights into the dynamics and functioning of ecosystems from local to global scales, and to increase our ability to predict the consequences of land‐use changes on biodiversity and the provision of ecosystem services to human societies.     

番茄TNAC基因的鉴定及表达分析

TNAC是一组茄科植物特有的NAC基因,目前尚未见有关番茄TNAC基因的报道。前期研究中,我们将来自于番茄、拟南芥和水稻三个物种的NAC蛋白构建进化树,发现有一分支仅包含番茄的26个SlNAC蛋白,本研究对其进一步鉴定和分析。结果显示,其中10个SlNAC蛋白具备TNAC典型序列特征。进而,采用实时定量PCR分析番茄TNAC基因在不同组织器官中的表达情况及对不同胁迫处理的响应模式。除一个番茄TNAC基因的转录产物未被检测到之外,2个在所有器官中均表达,7个均显示出明显的器官特异性。分别用250 mmol·L^-1 NaCl、15% PEG 6000和4℃处理番茄幼苗后,8个TNAC基因对至少一种胁迫有明显的响应。研究结果为预测这些SlNACs的生物学功能提供重要线索,也为深入理解这类茄科植物特有的NAC基因扮演的角色提供新的资料。