A fully traits-based approach to modeling global vegetation distribution

Dynamic Global Vegetation Models (DGVMs) are indispensable for our understanding of climate change impacts. The application of traits in DGVMs is increasingly refined. However, a comprehensive analysis of the direct impacts of trait variation on global vegetation distribution does not yet exist. Here, we present such analysis as proof of principle. We run regressions of trait observations for leaf mass per area, stem-specific density, and seed mass from a global database against multiple environmental drivers, making use of findings of global trait convergence. This analysis explained up to 52% of the global variation of traits. Global trait maps, generated by coupling the regression equations to gridded soil and climate maps, showed up to orders of magnitude variation in trait values. Subsequently, nine vegetation types were characterized by the trait combinations that they possess using Gaussian mixture density functions. The trait maps were input to these functions to determine global occurrence probabilities for each vegetation type. We prepared vegetation maps, assuming that the most probable (and thus, most suited) vegetation type at each location will be realized. This fully traits-based vegetation map predicted 42% of the observed vegetation distribution correctly. Our results indicate that a major proportion of the predictive ability of DGVMs with respect to vegetation distribution can be attained by three traits alone if traits like stem-specific density and seed mass are included. We envision that our traits-based approach, our observation-driven trait maps, and our vegetation maps may inspire a new generation of powerful traits-based DGVMs.To understand and predict the impacts of climate change on system Earth, it is essential to predict global vegetation distribution and its attributes. Vegetation determines the fluxes of energy, water, and CO₂ to and from terrestrial ecosystems. So-called Dynamic Global Vegetation Models (DGVMs) (reviewed in ref. 1) are indispensable tools to make predictions on such biosphere–climate interactions. Despite their importance, DGVMs are among the most uncertain components of earth system models when predicting climate change (2).DGVMs have been built around the concept of Plant Functional Types (PFTs) (3). Traditionally, various functional attributes (or traits) were assumed to be constant for a given PFT. This assumption has various drawbacks (reviewed in ref. 4). For instance, it implies assuming that trait values used to parameterize PFTs are valid under past environmental conditions and will be valid under future conditions. As such, this assumption neglects acclimation and adaptation (5), nonrandom species extinction (6), and major differences in dispersal rates among species and within PFTs (7). Moreover, this assumption strongly hampers quantifying feedback mechanisms between vegetation and its environment.For these reasons, the application of traits in DGVMs is increasingly refined. Trait responses to, for example, different soil fertility conditions are described as an emergent property in relation to nutrient feedbacks (8). Also, acclimation processes are increasingly included by replacing constant photosynthesis and respiration parameters by functions of temperature or CO₂ (9, 10), with profound impacts on predicted carbon fluxes (11). Within current DGVMs, traits are varied within a PFT (12), not allowing for assessing the direct impacts of traits relative to its indirect effects (for example, through productivity, biomass, or feedbacks changing environmental conditions). A comprehensive analysis of the direct impacts of trait variation as such (within and between PFTs) on global vegetation functioning and distribution does not yet exist. However, the paradigm shifts from species-centered approaches to traits-based approaches (13), the rapid increase in the compilation and application of traits-based analyses (14, 15), and the associated conceptual advances (e.g., in assembly theory) (16) allow for such analyses independent of a DGVM.Our aim was to describe global trait variation and evaluate whether trait variation alone already allows for predicting the global distribution of vegetation types, which is one of the principle aims of DGVMs. We first empirically describe global trait distribution and global trait maps—independent of vegetation type—as a function of multiple environmental drivers. Subsequently, in a posterior calculation, we predict the occurrence probability of vegetation types. This way, we derive a DGVM-independent trait-driven estimate of global vegetation distribution. We envision that our approach may inspire a new generation of powerful traits-based DGVMs applying (fully) traits-based concepts to predict carbon, water, and energy fluxes.     

Using wavelength and slope to infer the historical origin of semiarid vegetation bands

Landscape-scale patterns of vegetation occur worldwide at interfaces between semiarid and arid climates. They are important as potential indicators of climate change and imminent regime shifts and are widely thought to arise from positive feedback between vegetation and infiltration of rainwater. On gentle slopes the typical pattern form is bands (stripes), oriented parallel to the contours, and their wavelength is probably the most accessible statistic for vegetation patterns. Recent field studies have found an inverse correlation between pattern wavelength and slope, in apparent contradiction with the predictions of mathematical models. Here I show that this “contradiction” is based on a flawed approach to calculating the wavelength in models. When pattern generation is considered in detail, the theory is fully consistent with empirical results. For realistic parameters, degradation of uniform vegetation generates patterns whose wavelength increases with slope, whereas colonization of bare ground gives the opposite trend. Therefore, the empirical finding of an inverse relationship can be used, in conjunction with climate records, to infer the historical origin of the patterns. Specifically, for the African Sahel my results suggest that banded vegetation originated by the colonization of bare ground during circa 1760–1790 or since circa 1850.Landscape-scale patterns of vegetation occur worldwide at interfaces between semiarid and arid climates (1). They are important as potential indicators of climate change and imminent regime shifts (2, 3). Although other mechanisms have been suggested (4, 5), the patterns are widely thought to arise from positive feedback between vegetation and infiltration of rainwater (3, 6). Local increases in vegetation density cause greater infiltration, which promotes further growth, whereas rain falling on sparsely vegetated areas tends to run off to adjacent vegetated patches. On gentle slopes, the typical pattern form is bands (stripes), oriented parallel to the contours (6, 7), and their wavelength is probably the most accessible statistic for vegetation patterns, because it can be estimated from remotely captured images. The database of wavelengths is extensive, and some studies also record slope gradient. In 1999 Eddy et al. (8) compiled various older data of this type. Both this and a parallel study by d’Herbès et al. (9) showed an inverse relationship: longer wavelengths tend to occur on shallower slopes. The inferred relationship was not very strong because the data came from a variety of locations and involved a range of vegetation types, with relatively few data points from any one study. However, an inverse relationship between slope and wavelength has also been found in three recent detailed studies, of the African Sahel (10) and southwest United States (5, 11).The dependence of wavelength on slope can also be investigated using mathematical models based on water redistribution. Those studies that have done this report the opposite trend: Wavelength increases with slope (11, 12). This apparent contradiction has led to questioning of the mechanistic basis for vegetation patterns (5, 11). However, previous studies have made the conventional assumption that patterns arise from preexisting unstable uniformly vegetated states. I will argue that this assumption, and hence the contradiction, are invalid. Further I will show that detailed consideration of pattern generation mechanisms in mathematical models can reproduce the observed inverse relationship, showing that this relationship is entirely consistent with the water redistribution mechanism. Moreover my approach gives valuable insights into the historical origin of these patterns.     

Gradual regime shifts in fairy circles

Large responses of ecosystems to small changes in the conditions—regime shifts—are of great interest and importance. In spatially extended ecosystems, these shifts may be local or global. Using empirical data and mathematical modeling, we investigated the dynamics of the Namibian fairy circle ecosystem as a case study of regime shifts in a pattern-forming ecosystem. Our results provide new support, based on the dynamics of the ecosystem, for the view of fairy circles as a self-organization phenomenon driven by water–vegetation interactions. The study further suggests that fairy circle birth and death processes correspond to spatially confined transitions between alternative stable states. Cascades of such transitions, possible in various pattern-forming systems, result in gradual rather than abrupt regime shifts.The response of ecosystems to climate variability and anthropogenic disturbances is a fundamental aspect of ecology. Much attention has been devoted recently to large responses of ecosystems to small environmental changes or disturbances. Such responses, often termed “catastrophic regime shifts,” are conceived of as abrupt transitions between two alternative stable states that occur uniformly across the ecosystem (1). Spatially extended systems can respond in different ways to varying conditions, including pattern formation (2–4) and spatially confined transitions to alternative stable states (5). When one of the alternative stable states is spatially patterned, a multitude of additional stable states can appear, each a mosaic of fixed domains that alternate between the uniform and the patterned states (4, 6, 7). The existence of such hybrid states can strongly affect the dynamics of state transitions in fluctuating environments (8) and may lead to gradual rather than abrupt shifts (5, 9). This prediction of pattern formation theory has never been tested either in a real ecosystem or in a model describing the dynamics of a specific ecosystem.Pattern formation is widespread in natural ecosystems (3, 10), but good case models for studying gradual regime shifts are not abundant. An outstanding candidate is the Namibian fairy circle (NFC) ecosystem, which is fairly homogeneous and undisturbed, and recently has been the subject of intense research (11–17). The NFC ecosystem consists of a uniform matrix of perennial grass, punctured by circular gaps of sandy bare soil—the fairy circles—that on landscape scales form nearly periodic patterns (12, 17).Various explanations for the formation of fairy circles have been suggested, including the release of poisonous gas and the feeding habits of ants and termites (14, 17, 18). These explanations, however, have not uncovered, as of yet, the small-scale feedbacks needed to account for the emergence of the large-scale order (2, 4, 10). On the other hand, it is well established by model studies and confirmed by empirical observations that patch-scale biomass-water feedbacks can lead to regular landscape-scale vegetation patterns and that periodic gap patterns, which highly resemble fairy circle patterns, can appear from uniform vegetation in response to water stress (3, 19–22). Indeed, recent detailed comparisons of fairy circle remote sensing data and model gap patterns show high similarity in static properties, such as hexagonal symmetry and spatial correlations of fairy circle size and distance (17).In this paper, we combine a theoretical analysis of a vegetation model, fitted to the biotic and abiotic conditions of the NFC ecosystem, with an empirical data analysis, to account for fairy circle dynamics in the NamibRand Nature Reserve from the years 2004 to 2013, thereby accomplishing two goals. The first goal is to substantiate the view of fairy circles as a pattern-formation phenomenon by complementing the current statistical evidence (11, 15, 17) with evidence based on the dynamics of the NFC ecosystem. The second goal is to demonstrate the feasibility of gradual regime shifts in the NFC ecosystem as cascades of unidirectional transitions across hybrid states.     

MODIS遥感图像在江宁县江滩钉螺分布研究中的应用

目的　分析MODIS遥感卫星图像中植被指数 (NDVI)与江宁县江滩各钉螺孳生地钉螺分布之间的关系 ,探索Terra MODIS遥感卫星图像在小范围江滩钉螺孳生地监测中的应用可能。方法　利用现场测量的江宁县 2 0 0 1年度各钉螺孳生地经纬度在ArcView 8.1软件上制作钉螺分布Vector图层 ;利用ERDAS 8.5软件空间模板板块中图层间信息添加功能 ,通过 2 0 0 1年度钉螺分布Vector图层从MODIS卫星图像中提取各钉螺孳生地NDVI。以相关性分析及多元逐步回归分析研究NDVI与钉螺分布间的关系。结果　江滩钉螺孳生地的螺密度与 4月下旬各钉螺孳生地平均NDVI(N2mean)、5月中旬各钉螺孳生地最大NDVI(N2 0max)呈正相关 (r分别为 0 .51、0 .50 ,P <0 .0 5) ;同时活螺框出现率与 4月下旬各钉螺孳生地平均NDVI(N2mean)呈正相关 (r=0 .51 ,P <0 .0 5)。进一步作回归分析结果显示 :江滩钉螺孳生地钉螺密度与 5月中旬各钉螺孳生地最大NDVI(N2 0max)存在 :Y1 =0 .0 0 947×N2 0max(P <0 .0 1 ,R2 =0 .73) ;活螺框出现率与 4月下旬各钉螺孳生地平均NDVI值(N2mean) ,存在 :Y2 =0 .0 1 86×N2mean(P <0 .0 1 ,R2 =0 .90 6)。结论　通过研究显示MODIS卫星图像较好地反映了江宁县江滩钉螺孳生地的植被分布状况 ,且可应用于小范围钉螺孳生地的     

基于生态健康的绿色植被指数数据采集及边缘计算

目的  在健康医疗大数据时代,更快、更精准地获取环境绿地暴露水平数据,助力对绿色植被暴露与健康的研究。 方法  利用Python设计一套能够进行自动化采集绿色植被指数的技术流程和程序。同时以国家健康医疗大数据平台为依托,对边缘计算在绿色植被指数采集应用进行探究和展望。 结果  该程序的运行极大缩短了对植被指数的处理时间,并且与传统专业软件获取的结果比较,具有较高的一致性,r>0.99。 结论  基于边缘计算的绿色植被指数的自动化采集可为国内绿色植被暴露与健康的研究提供技术支持。     

鼻咽侧位片鼻咽气道宽度测定在儿童腺样体肥大中的临床应用

目的探讨鼻咽侧位片鼻咽气道宽度测定在儿童腺样体肥大临床诊断及治疗中的意义。方法收集130例2—16岁因腺样体肥大在我院就诊的患儿,于鼻咽侧位片上测量鼻咽气道宽度最短径,并与临床鼻咽镜下测量进行比较及统计学分析。结果鼻咽侧位片测量与鼻咽镜下测量鼻咽气道宽度在统计学上存在着相当满意的一致性,统计学分析显示鼻咽气道宽度在0—5mm之间为重度肥大,宜采用手术治疗方式;在6～11mm之间中度肥大,可采取非手术方式治疗;≥12mm为轻度肥大,则可视为正常而不予治疗。结论鼻咽侧位片鼻咽气道宽度测定方法简单,测量准确,其测量结果可以为腺样体肥大的临床诊断及指导临床选择合适的治疗方法提供准确依据。     

广东省伊蚊密度与AVHRR卫星图像中植被指数的关系

目的 :分析美国国家海洋与航空管理局 甚高分辨率辐射计 (NOAA AVHRR)遥感卫星图像中植被指数与伊蚊密度之间的关系 ,探索AVHRR遥感卫星图像在大范围伊蚊种群监测的应用可能性 ,为建立伊蚊分布遥感预测模型提供理论依据 .方法 :利用广东省 1995年度实地监测到的各地伊蚊密度 ,计算出各市县每月的平均伊蚊密度 ,并以各市县的中心点经纬度在ArcGIS8.1软件上制作伊蚊分布“vector”图层 ;利用ERDAS8.5软件空间模块中图层间信息添加功能 ,通过1995年度伊蚊密度分布“vector”图层 ,从AVHRR卫星图像中提取各伊蚊点植被指数 .以相关性分析及多元逐步回归分析研究植被指数与伊蚊分布间的关系 .结果 :广东省流行季节与非流行季节的标准化植被指数 (normalizeddifferencevegeta tionindex ,NDVI)存在明显差异 ,且流行季节的最大标化植被指数 (NDVIMax e)、平均标化植被指数 (NDVIMean e)、最小标化植被指数 (NDVIMin e)要大于非流行季节的最大标化植被指数 (NDVIMax ne)、平均标化植被指数 (NDVIMean ne)、最小标化植被指数 (NDVIMean ne) (P <0 .0 1) ;相关分析表明 ,与伊蚊密度相关的植被指数有 7,8,9,10和 12mo的最大NDVI,3,7,11和 12mo的平均NDVI和 11mo的最小NDVI ,(P <0 .0 1) ;且有 :^YBI=- 14 86 5 +0 .6     

Epigaeic beetle communities of the Green Triangle plantation landscape,southern Australia: effect of remnant size,vegetation quality and structural complexity

Across the Green Triangle plantation landscape of south-eastern South Australia and south-western Victoria there remain remnant patches of native vegetation which vary considerably in both size and vegetation quality. This study focused on how the vegetation quality and or size of remnants embedded within the bluegum (Eucalyptus globulus) plantation landscape influence the local ground-dwelling Coleoptera (beetle) assemblages found within them. The aim was to particularise those remnant characteristics (in terms of size and vegetation quality) that are likely to result in the most effective protective management of local remnant beetle biodiversity. Pitfall sampling was carried out over a 13-month period. All beetles sampled via pitfall traps were identified to family level, and the three most abundant beetle families (Carabidae, Staphylinidae and Tenebrionidae) identified to genus. Remnant vegetation was assigned to one of the four quality categories (as defined by the Land for Wildlife (LFW) method), and structural attributes of the vegetation surrounding each trap were also measured.

Different beetle taxa responded independently to remnant vegetation quality and size, and to the measured vegetation structural variables. Mean beetle family abundance and estimated richness increased with decreasing remnant vegetation quality. However, when Carabidae, Staphylinidae and Tenebrionidae beetle families were analysed separately at genus level, taxa responded independently to vegetation quality and size. Furthermore, different vegetation structural variables such as the percentage cover of litter and shrubs as well as the number of overstorey stems were correlated with estimated richness of different beetle taxa. Beetle abundance was significantly influenced by mean litter depth and shrub and litter cover. This study also showed that remnants of different vegetation quality supported beetle assemblages composed of significantly different communities. However, these differences were not consistent between all sites of different vegetation quality, suggesting that there may be additional ecological characteristics within the landscape responsible for shaping remnant beetle communities. No single, specific quality of remnant vegetation was optimal for supporting the most diverse assemblage of beetles, as different taxa responded independently. A range of remnants of differing qualities maintained across the landscape may provide the resources needed for the widest range of beetle taxa, by accommodating their varying habitat requirements.     

MAPPING FOREST FIRES THROUGH SMOKE

Forest fires have been photographed from the air with infra-red film, and observations with an infra-red image converter have been used to map wild fires through heavy smoke.     

Successful laser-assisted removal of an infected ICD lead with a large vegetation

Infective endocarditis involving transvenous pacing leads is an uncommon but potentially lethal complication of implantable cardioverter-defibrillator (ICD) implantation. Complete removal of the device and the leads is presently considered to be the optimal treatment in such patients and laser-assisted lead removal is an effective and safe nonthoracotomy approach. However, large vegetations (>10 mm) attached to the lead limit nonthoracotomy explantation because of the potential for hemodynamically embarrassing pulmonary embolization. Laser extraction of leads with vegetation area >300 mm2 has rarely been reported. In this case report, we describe a patient with an infected ICD lead with vegetation greater than 41 x 12.5 mm (512 mm2) in size that was explanted with laser-assistance. The resulting pulmonary embolus produced a 33 x 20 mm pulmonary infarction without hemodynamic or respiratory compromise.