Above-ground biomass estimation using airborne discrete-return and full-waveform LiDAR data in a coniferous forest

The estimation of forest aboveground biomass (AGB) is critical for quantifying carbon stocks and essential for evaluating global carbon cycle. Many previous studies have estimated forest AGB using airborne discrete-return Light Detection and Ranging (LiDAR) data, while fewer studies predicted forest AGB using airborne full-waveform LiDAR data. The objective of this work was to evaluate the utility of airborne discrete-return and full-waveform LiDAR data in estimating forest AGB. To fulfill the objective, airborne discrete-return LiDAR-derived metrics (DR-metrics), full-waveform LiDAR-derived metrics (FW-metrics) and structure parameters (combining height metrics and canopy cover) were used to estimate forest AGB. Additionally, the combined use of DR- and FW-metrics through a nonlinear way was also evaluated for AGB estimation in a coniferous forest in Dayekou, Gansu province of China. Results indicated that both height metrics derived from discrete-return and full-waveform LiDAR data were stronger predictors of forest AGB compared with other LiDAR-derived metrics. Canopy cover derived from discrete-return LiDAR data was not sensitive to forest AGB, while canopy cover estimated by full-waveform LiDAR data (CC_WF) showed moderate correlation with forest AGB. Structure parameters derived from full-waveform LiDAR data, such as H75_FW * CC_FW, were closely related to forest AGB. In contrast, structure parameters derived from discrete-return LiDAR data were not suitable for estimating forest AGB due to the less sensitivity of canopy cover CC_DR2 to forest AGB. This research also concluded that the synergistic use of DR- and FW-metrics can provide better AGB estimates in coniferous forest.     

Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2 mission) with the goal of improving wildlife modeling for more locations across the globe.     

基于无人机激光雷达遥感的亚热带常绿阔叶林群落垂直结构分析

森林植被高度与树木分布格局是植物群落重要结构特征,也是计算森林生物量分布的重要参数。传统的森林群落调查方法耗费大量人力物力难以进行较大尺度的群落结构测量,而一般的遥感影像也难以获得精确的地形信息及垂直结构。近年来激光雷达(Light Detection and Ranging,LiDAR)技术快速发展,能够较好的进行植被三维特征的提取并被广泛应用于森林生态系统检测模拟。且随着无人机低空摄影技术的发展催生的无人机激光雷达(UAV-Lidar)更增加了激光雷达的灵活性以及获取较大范围植被冠层信息的能力。而受限于激光的穿透性以及不同植被类型郁闭度的影响,该技术的应用多局限于在针叶林群落的垂直结构研究,而在常绿阔叶林的研究中应用较少。为探究现有无人机激光雷达设备及垂直结构提取分析技术应用于常绿阔叶林的可行性,利用无人机载激光雷达遥感技术对哀牢山中山湿性常绿阔叶林3块面积1hm~2的样地进行基于数字表面模型以及数字地表高程模型做差得到树冠高度模型测量的植被冠层高度、基于局部最大值法进行单木位置提取并使用Clark-Evans最近邻体分析方法进行样地内高大乔木分布格局的计算。分析结果显示,植被高度提取精度平均大于95%,与地表实测的植被高度值拟合度较高,相关系数R~2介于0.833—0.927之间;3个样地冠层高度平均值分别为18.79、19.08、17.03 m,标准差分别为8.10、7.34、7.17 m。单木探测百分比平均86.3%,用户精度以及生产者精度平均分别为75.69%和65.15%。实测得出三个样地全部高大乔木空间分布格局均为聚集分布,而激光雷达测量结果显示为随机分布或均匀分布。实验显示基于无人机激光雷达技术能够很好地提取植被冠层高度信息并能够较好地获取树木位置,但对于树木空间分布格局判定的准确性有待于进一步探索。未来研究应从多角度对激光雷达测量造成的误差原因予以分析(如环境因素),并进一步研究更为精确的单木提取以及植被高度提取方法,为通过无人机激光雷达测算森林生物量及各种生态过程提供更加精准的指标数据。     

Modelling relationships between birds and vegetation structure using airborne LiDAR data: a review with case studies from agricultural and woodland environments

Airborne LiDAR (Light Detection and Ranging) is a remote sensing technology that offers the ability to collect high horizontal sampling densities of high vertical resolution vegetation height data, over larger spatial extents than could be obtained by field survey. The influence of vegetation structure on the bird is a key mechanism underlying bird–habitat models. However, manual survey of vegetation structure becomes prohibitive in terms of time and cost if sampling needs to be of sufficient density to incorporate fine-grained heterogeneity at a landscape extent. We show that LiDAR data can help bridge the gap between grain and extent in organism–habitat models. Two examples are provided of bird–habitat models that use structural habitat information derived from airborne LiDAR data. First, it is shown that data on crop and field boundary height can be derived from LiDAR data, and so have the potential to predict the distribution of breeding Sky Larks in a farmed landscape. Secondly, LiDAR-retrieved canopy height and structural data are used to predict the breeding success of Great Tits and Blue Tits in broad-leaved woodland. LiDAR thus offers great potential for parameterizing predictive bird–habitat association models. This could be enhanced by the combination of LiDAR data with multispectral remote sensing data, which enables a wider range of habitat information to be derived, including both structural and compositional characteristics.     

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.     

Structural complexity and land‐surface energy exchange along a gradient from arctic tundra to boreal forest

Question: Current climate changes in the Alaskan Arctic, which are characterized by increases in temperature and length of growing season, could alter vegetation structure, especially through increases in shrub cover or the movement of treeline. These changes in vegetation structure have consequences for the climate system. What is the relationship between structural complexity and partitioning of surface energy along a gradient from tundra through shrub tundra to closed canopy forest? Location: Arctic tundra‐boreal forest transition in the Alaskan Arctic. Methods: Along this gradient of increasing canopy complexity, we measured key vegetation characteristics, including community composition, biomass, cover, height, leaf area index and stem area index. We relate these vegetation characteristics to albedo and the partitioning of net radiation into ground, latent, and sensible heating fluxes. Results: Canopy complexity increased along the sequence from tundra to forest due to the addition of new plant functional types. This led to non‐linear changes in biomass, cover, and height in the understory. The increased canopy complexity resulted in reduced ground heat fluxes, relatively conserved latent heat fluxes and increased sensible heat fluxes. The localized warming associated with increased sensible heating over more complex canopies may amplify regional warming, causing further vegetation change in the Alaskan Arctic.     

Animal-habitat relationships in the Knysna Forest,South Africa: discrimination between forest types by birds and invertebrates

Summary Effects of forest plant species composition and physiognomy on bird and invertebrate communities were investigated in three discrete, relatively undisturbed forest types along a dry-wet soil moisture gradient. Using discriminant function analysis, a 100% floristic and a 78% vegetation structural discrimination were obtained between the three forest types. However, the bird communities of these different forest types were very similar in species composition, and had much lower densities than those normally encountered in other, superficially similar forests. Although an 81% discrimination between forest types was attained through analysis of ground surface invertebrates, measures of litter and aerial invertebrate abundance were also of limited use as discriminators. Historical and biogeographic factors, as well as the low nutritional levels in the soil and vegetation may be the causes of low bird and invertebrate density and diversity. It is concluded that floristics and vegetation structure have, at best, a minor influence on bird community structure, and possibly also on invertebrate community structure in the Knysna Forest.     

Habitat preferences of the bank voleMyodes glareolus in a Mediterranean mountain range

The bank voleMyodes glareolus Schreber, 1780 is a widely distributed rodent in Europe, being numerically dominant in small mammal communities living in temperate woodlands. However, it becomes scarce in southern Europe (Mediterranean area) where it reaches the southernmost limit of its distribution range. We studied the habitat preferences of bank voles in 9 plots in a transitional area between Mediterranean and Eurosiberian regions within a Mediterranean mountain. During the study period we captured 1919 small mammals of 9 species, including 287 bank voles (14.95%). Mean density ranged from zero individuals per plot (1.1 ha) at the boreo-subalpine scrubland to 10.27 ± 2.84 (SE) at a Mediterranean river woodland. Statistical path analysis was used to investigate relationships between mean bank vole density and climate and vegetation structure measured within plots. The variables selected by the structural equation model were those related to forest structure, like tree cover and height, dead vegetation, moss, and rock cover. Habitat moisture was also important (microclimatic conditions). Mean climate conditions (and elevation) did not have any significant effect on mean bank vole density, and no significant association with understorey vegetation (eg shrub and herbaceous cover) was observed. Our results pointed out that bank voles were habitat specialists in our study area, being more abundant and frequent in moist woodlands, and rare or absent in shrublands and grasslands.     

The vegetation of the forest-steppe region of Hustain Nuruu, Mongolia

The vegetation of a forest-steppe region in Hustain Nuruu, Mongolia, was studied by a phytocoenological approach. Eleven plant communities were recognized, comprising four steppe communities, two meadow communities, a tussock grassland, two shrub communities, a scrub community and a woodland community. The botanical and ecological characteristics of the different communities are discussed, with reference to the existing classification of Mongolian plant communities. Analysis of the present data indicates that a refinement or extension of the classification system is desirable, especially concerning the steppe(-related) communities. Discussion of the relative distribution of steppe and forest reveals that in the relatively dry location of Hustain Nuruu grassland and shrubland dominate the natural vegetation (88% of the area). Forest covers ca. 5% of the area, it is limited to sites where ground water is within rooting depth: north slopes above 1400 m (Betula platyphylla woodland) and along erosion gullies (fragmentary Ulmus pumila gallery woodland). Under natural conditions forest cover might reach 12%, but it is speculated that wild ungulates could maintain its extension at a lower level. The importance of forest is greater in forest-steppe regions with higher rainfall, but the factors determining the distribution of grassland and forest are expected to be similar.     

The use of medium point density LiDAR elevation data to determine plant community types in Baltic coastal wetlands

This study investigates the use of medium point density LiDAR (light detection and ranging) elevation data for identifying and locating plant community types in Baltic coastal wetlands. Ground-surveyed micro-topography data obtained using real-time kinematic differential GPS were used to analyse and correct the accuracy of LiDAR sourced elevation values in Matlab R2010a. Following the application of elevation corrections, 3 interpolation techniques were applied: Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and the Delaunay Triangulated Irregular Network (TIN) interpolation. Analysis showed that the TIN method produced a more robust model that adequately represented the micro-topographical variation across the wetland. The TIN elevation interpolation was then used to characterise the extent and distribution of the plant communities using known elevation preferences in one coastal wetland site, Tahu. The plant community model developed from the TIN elevation interpolation was then further ground-truthed in two separate Baltic coastal wetland sites, Matsalu and Kudani, in order to test model validity.The results showed that the accuracy of the LiDAR data varied dependent upon plant community type. In 5 of the 6 studied community types, the LiDAR data gave a mean elevation difference of 0.177 m (0.016 SD) above the dGPS elevations. With dGPS elevation corrections, the LiDAR data produced an accurate model of the location of the different plant community types, Kappa coefficient (κ) 0.63, at the initial site, Tahu. The model was found to be very accurate in one of the subsequent ground-truthed sites, κ 0.81, with a similar management history, but less accurate, κ 0.53, in a wetland more exposed to wave action and with a longer history of vegetation management.The inclusion of dGPS ground survey data was shown to considerably improve the accuracy of the LiDAR elevation data to facilitate the identification of plant community types on the basis of elevation. The approach developed in this study of Baltic coastal wetlands may provide a transferable method for rapidly and accurately mapping plant communities in other open environments.     

Characteristics of Golden‐winged Warbler territories in plant communities associated with regenerating forest and abandoned agricultural fields

In the Appalachian portion of their breeding range, Golden‐winged Warblers (Vermivora chrysoptera) nest in shrubland and regenerating forest communities created and maintained by disturbance. Because populations of Golden‐winged Warblers have exhibited precipitous declines in population throughout their Appalachian breeding range, management activities that create or maintain early successional habitat are a priority for many natural resource agencies and their conservation partners. Within these early successional habitats, however, additional information is still needed concerning the relative importance of different vegetation features in selection of breeding territories by Golden‐winged Warblers. Our objective, therefore, was to use logistic regression to estimate the probability of territory‐level occupancy by Golden‐winged Warblers in north‐central Pennsylvania at two sites, each with its own early successional community, based on vegetation characteristics. Our communities were composed of shrublands and regenerating forest sites resulting from two disturbances: agriculture and forest fire. Despite differences in vegetation structure, portions of both study areas (regenerating forest and old field) supported territorial Golden‐winged Warblers. Probability of territory occupancy by Golden‐winged Warblers increased with percent blackberry (Rubus) cover in the regenerating forest community, and decreased as basal area and distance to microedge increased (i.e., as vegetation patchiness decreased) in both communities. These habitat features have also been found to influence other aspects of Golden‐winged Warbler breeding ecology such as nest‐site selection, pairing success, and territory abundance. Vegetation features influencing Golden‐winged Warbler territory establishment can differ among shrubland and regenerating forest communities, and management decisions and outcomes may be affected by these differences. Our study provides a starting point for a more comprehensive hypothesis‐driven occupancy survey to investigate features of the territories of Golden‐winged Warblers across a broader geographic range and in different vegetation communities.     

Ungulate browsing on introduced pines differs between plant communities: Implications for invasion process and management

The effects of herbivory on plant invasions are broadly discussed, and many studies have led to widely debated theories. In particular, the effects of herbivores on pine invasion found in different studies vary; in some cases, they controlled their expansion, and in others, they promoted it. On the other hand, vulnerability to invasion by pines differs between community types. Sites with dunes and bare ground are the most heavily invaded, followed by grasslands, while shrublands and forests are least invaded. Because current evidence is mostly observational, some of the varying responses of pine invasions to herbivory should be examined further through replicated experiments. Here, we address experimentally the extent to which preference for the non‐native invasive Pinus contorta by domestic sheep (Ovis aries) depends on the vegetation type. We installed experimental enclosures within two adjacent communities, grassland and shrubland, and in each one, we planted seedlings of P. contorta Douglas and established a sheep density typically recommended for the study area. The number of browsed seedlings, the number and type of branches browsed per seedling, the reduction in height and probability of survival immediately after browsing period were recorded. The number of browsed seedlings and damage to the terminal bud were higher in grassland than in shrubland, while the number of browsed branches per seedling was higher in shrubland than grassland. The reductions in height and probability of survival immediately after browsing were similar in both communities. These results show that moderate levels of sheep herbivory could reduce 20% seedling survival in both communities; nevertheless, the damage patterns differ between them. The sheep browsed more substantial number of seedlings in grasslands than in shrublands. However, if sheep find the seedlings, they damage it more in shrublands. These results suggest that experimental studies comparing communities are important for pine invasion management.     

阿尔泰山两河源牧区草地群落生物量及物种多样性

群落生物量和物种多样性是表征草地生态系统数量特征的重要指标。该研究以新疆阿尔泰山南麓两河源放牧区草地为研究对象,利用样方法对两河源不同放牧区的草地植被进行调查,分析研究区生物量和物种多样性变化,探讨二者与环境因子之间的关联性,为草地群落物种保护以及草地可持续利用提供理论依据。结果表明：(1) 两河源不同牧区间群落盖度、高度、植株密度、地上生物量和单位盖度生物量存在差异。(2) 两河源牧区草地群落地上生物量与群落盖度、植株密度呈显著正相关关系(P<0.05),且地上生物量主要受草地群落盖度的影响;不同牧区的物种多样性指数有一定差异,但物种分布相对均匀。(3)两河源牧区草地群落生物量及物种多样性主要受气温和降水的影响。     

Synergistic influences of introduced herbivores and fire on vegetation change in northern Patagonia,Argentina

Question: We investigated how cattle and European hares, the two most widespread exotic herbivores in Patagonia, affect species composition, life‐form composition and community structure during the first 6 years of vegetation recovery following severe burning of fire‐resistant subalpine forests and fire‐prone tall shrublands. We asked how the effects of introduced herbivores on post‐fire plant community attributes affect flammability of the vegetation. Location: Nahuel Huapi National Park, northwest Patagonia, Argentina Methods: We installed fenced plots to exclude livestock and European hares from severely burned subalpine forests of Nothofagus pumilio and adjacent tall shrublands of N. antarctica. The former is an obligate seed reproducer, whereas the latter and all other woody dominants of the shrubland vigorously resprout after burning. Results: Repeated measures ANOVA of annual measurements over the 2001‐2006 period indicate that cattle and hare exclusion had significant but complex effects on the cover of graminoids, forbs, climber species and woody species in the two burned community types. Significant interactions between the effects of cattle and hares varied by plant life forms between the two communities, which implies that their synergistic effects are community dependent. Conclusions: Following severe fires, the combined effects of cattle and hares inhibit forest recovery and favour transition to shrublands dominated by resprouting woody species. This herbivore‐induced trend in vegetation structure is consistent with the hypothesis that the effects of exotic herbivores at recently burned sites contribute to an increase in the overall flammability of the Patagonian landscape.     

天然和人工固沙灌木林蜘蛛和甲虫分布与环境因子的关系

干旱区人工植被恢复驱动的土地利用变化强烈影响了地表和土栖的节肢动物群落结构及多样性。然而,我们对地表节肢动物群落关键类群-蜘蛛和甲虫对固沙植被恢复的响应及与环境变化关系的认识还很有限。以天然固沙灌木林和2种人工固沙灌木林为研究对象,运用方差分析和多变量分析等方法定量研究了干旱区天然和人工固沙植被区地表蜘蛛和甲虫分布特征及影响要素。结果表明,天然灌木林与人工梭梭、柽柳林地表蜘蛛和甲虫群落组成明显不同,人工梭梭、柽柳林地表蜘蛛活动密度和甲虫多样性均显著高于天然灌木林,而地表甲虫密度和蜘蛛多样性变化与之相反。两种人工固沙灌木林之间蜘蛛和甲虫群落组成也存在一定差异,人工柽柳林地表蜘蛛活动密度、多样性和甲虫物种丰富度均显著高于人工梭梭林。进一步分析发现,蜘蛛群落中狼蛛科、平腹蛛科、皿蛛亚科和球蛛科与甲虫群落中拟步甲科、步甲科和象甲科等一些甲虫种属对3种生境的选择模式不同决定了蜘蛛和甲虫群落聚集结构。植被、土壤环境因子与蜘蛛和甲虫pRDA和pCCA结果表明,草本生物量、凋落物量、土壤含砂量、电导率和灌木盖度是影响蜘蛛分布的主要环境因子,它们解释了82.1%的蜘蛛群落变异;灌木盖度、草本生物量、土壤pH和砂含量是影响甲虫群落分布的主要环境因子,它们解释了60.6%的甲虫群落变异。总之,人工固沙灌木恢复影响了植被和土壤环境,它们相互作用改变了荒漠-绿洲过渡区蜘蛛和甲虫等地表节肢动物的分布格局。     

Heterogeneity of xerophytic vegetation of limestone outcrops in a tropical deciduous forest region in southern México

The heterogeneity of xerophytic vegetation developing on limestone outcrops immersed in a tropical deciduous forest matrix was studied in Nizanda (S México). The study units comprised three clearly distinct communities based on their physiognomy and substrate, representing a gradient of edaphic aridity: (1) xerophytic scrub (XS); (2) tropical deciduous forest on rock (TDFr); and (3) tropical deciduous forest on deeper soil (TDFs). Structural and floristic variables were gathered in nine 100 m² plots by community. In the 0.27 ha sampled 211 plant species were recorded. Total floristic richness by community decreased with increasing edaphic aridity: 159 species in TDFs, 107 in TDFr, and 36 in XS. Although significant differences were observed between the three communities for only four structural variables (total and upper stratum species densities, and relative monocotyledon density and cover), other variables confirmed the differences between the two forest communities and the XS (total and upper stratum cover, density, and basal area). TDFr and XS also differed from TDFs with respect to lower stratum species density, and absolute monocotyledon density and cover. The results showed the importance of monocotyledons and the prevalence of clonality in TDFr and XS. A comparison between limestone outcrop and inselberg vegetation indicated a virtual absence of therophytes, graminoid herbs, cryptogamic crusts, and desiccation-tolerant and carnivorous plants in the former, whereas the prevalence of monocotyledon mats, and xerophytic and succulent plants is the most striking similarity between these rocky environments. Xerophytic vegetation of limestone outcrops in Nizanda may be seen as analogous of relictual communities that existed during a northbound migration of Neotropical flora, towards the arid zones of North America.     

中亚热带森林单木地上生物量的机载激光雷达估测

以雪峰山武冈林场为研究对象,利用遥感数据和地面实测样地数据,研究机载激光雷达（LiDAR）估测中亚热带森林乔木层单木地上生物量的能力.利用条件随机场和最优化方法实现LiDAR点云的单木分割,以单木尺度为对象提取的植被点云空间结构、回波特征以及地形特征等作为遥感变量,采用回归模型估测乔木层地上生物量.结果表明: 针叶林、阔叶林和针阔混交林的单木识别率分别为93%、86%和60%;多元逐步回归模型的调整决定系数分别为0.83、0.81和0.74,均方根误差分别为28.22、29.79和32.31 t·hm^-2;以冠层体积、树高百分位值、坡度和回波强度值构成的模型精度明显高于以树高为因子的传统回归模型精度.以单木为对象从LiDAR点云中提取的遥感变量有助于提高森林生物量估测精度.
     

Laserfarm – A high-throughput workflow for generating geospatial data products of ecosystem structure from airborne laser scanning point clouds

Quantifying ecosystem structure is of key importance for ecology, conservation, restoration, and biodiversity monitoring because the diversity, geographic distribution and abundance of animals, plants and other organisms is tightly linked to the physical structure of vegetation and associated microclimates. Light Detection And Ranging (LiDAR) — an active remote sensing technique — can provide detailed and high resolution information on ecosystem structure because the laser pulse emitted from the sensor and its subsequent return signal from the vegetation (leaves, branches, stems) delivers three-dimensional point clouds from which metrics of vegetation structure (e.g. ecosystem height, cover, and structural complexity) can be derived. However, processing 3D LiDAR point clouds into geospatial data products of ecosystem structure remains challenging across broad spatial extents due to the large volume of national or regional point cloud datasets (typically multiple terabytes consisting of hundreds of billions of points). Here, we present a high-throughput workflow called ‘Laserfarm’ enabling the efficient, scalable and distributed processing of multi-terabyte LiDAR point clouds from national and regional airborne laser scanning (ALS) surveys into geospatial data products of ecosystem structure. Laserfarm is a free and open-source, end-to-end workflow which contains modular pipelines for the re-tiling, normalization, feature extraction and rasterization of point cloud information from ALS and other LiDAR surveys. The workflow is designed with horizontal scalability and can be deployed with distributed computing on different infrastructures, e.g. a cluster of virtual machines. We demonstrate the Laserfarm workflow by processing a country-wide multi-terabyte ALS dataset of the Netherlands (covering ∼34,000 km² with ∼700 billion points and ∼ 16 TB uncompressed LiDAR point clouds) into 25 raster layers at 10 m resolution capturing ecosystem height, cover and structural complexity at a national extent. The Laserfarm workflow, implemented in Python and available as Jupyter Notebooks, is applicable to other LiDAR datasets and enables users to execute automated pipelines for generating consistent and reproducible geospatial data products of ecosystems structure from massive amounts of LiDAR point clouds on distributed computing infrastructures, including cloud computing environments. We provide information on workflow performance (including total CPU times, total wall-time estimates and average CPU times for single files and LiDAR metrics) and discuss how the Laserfarm workflow can be scaled to other LiDAR datasets and computing environments, including remote cloud infrastructures. The Laserfarm workflow allows a broad user community to process massive amounts of LiDAR point clouds for mapping vegetation structure, e.g. for applications in ecology, biodiversity monitoring and ecosystem restoration.     

Species Turnover and Vertical Partitioning of Ant Assemblages in the Brazilian Amazon: A Comparison of Forests and Savannas1

We measured beta diversity, or turnover in species composition, of ant assemblages inhabiting patches of forest and savanna (cerrado) near Alter do Chão, in the Brazilian Amazon. In addition, we assessed vertical partitioning of these assemblages by comparing the ground and lower vegetation strata within each habitat. Ants attracted to sardine baits were collected along transects in 39 savanna and 34 forest sites scattered over a 16 km × 16 km landscape. There were about twice as many species in the forest as in the savanna, and within both habitats, we collected more species on the ground than in the vegetation. Similar results were obtained when analyzing data at the level of individual transects, indicating that ant species richness is affected by both habitat and strata. About two‐thirds of the species recorded in the savanna were also found in the forest. Within both habitats, a large proportion of the species found in the least species‐rich stratum (vegetation) were also found in the richer one (ground). However, ordination analysis, using data from individual transects, revealed that different habitats and strata can be clearly discriminated from each other in terms of their ant species composition. Each habitat and stratum had a number of characteristic (indicator) species which, although generally not exclusive to that particular habitat and stratum, predominated there. Our findings indicate that habitat and strata specialization is an important factor governing the organization of ant communities in Amazonia.