Dynamics of a human‐modified tropical peat swamp forest revealed by repeat lidar surveys

Tropical peat swamp forests (PSFs) are globally important carbon stores under threat. In Southeast Asia, 35% of peatlands had been drained and converted to plantations by 2010, and much of the remaining forest had been logged, contributing significantly to global carbon emissions. Yet, tropical forests have the capacity to regain biomass quickly and forests on drained peatlands may grow faster in response to soil aeration, so the net effect of humans on forest biomass remains poorly understood. In this study, two lidar surveys (made in 2011 and 2014) are compared to map forest biomass dynamics across 96 km² of PSF in Kalimantan, Indonesia. The peatland is now legally protected for conservation, but large expanses were logged under concessions until 1998 and illegal logging continues in accessible portions. It was hypothesized that historically logged areas would be recovering biomass while recently logged areas would be losing biomass. We found that historically logged forests were recovering biomass near old canals and railways used by the concessions. Lidar detected substantial illegal logging activity—579 km of logging canals were located beneath the canopy. Some patches close to these canals have been logged in the 2011–2104 period (i.e. substantial biomass loss) but, on aggregate, these illegally logged regions were also recovering. Unexpectedly, rapid growth was also observed in intact forest that had not been logged and was over a kilometre from the nearest known canal, perhaps in response to greater aeration of surface peat. Comparing these results with flux measurements taken at other nearby sites, we find that carbon sequestration in above‐ground biomass may have offset roughly half the carbon efflux from peat oxidation. This study demonstrates the power of repeat lidar survey to map fine‐scale forest dynamics in remote areas, revealing previously unrecognized impacts of anthropogenic global change.     

基于机载激光雷达的中亚热带常绿阔叶林林窗特征

机载激光雷达(LiDAR)是一种新型主动式遥感技术,能直接获取多尺度高精度的冠层三维结构信息,将其推广到森林干扰生态学领域,可为林窗研究提供应用支撑.以湖南中亚热带常绿阔叶林为研究对象,利用小光斑LiDAR数据进行林窗识别和几何特征估测.选择合适的分辨率和内插方法生成冠层高程模型,采用计算机图形学方法估测林窗面积、边界木高度和形状指数,并进行野外观测验证.结果表明: 林窗识别率为94.8%,主要影响因素是林窗面积和林窗形成木类型;估测的林窗面积和边界木高与野外观测值呈较强线性相关,R²值分别为0.962和0.878,其中估测的林窗面积平均比野外观测值高19.9%,估测的林窗边界木高度平均比野外观测值低9.9%;区域内林窗密度为12.8个·hm^-2,占森林面积13.3%;林窗面积、边界木高和形状指数的平均值分别为85.06 m²、15.33 m和1.71,区域内多为较小面积、边缘效应不太显著的林窗.
     

基于激光雷达数据的森林表层土壤机质空间格局反演

森林土壤是陆地生态系统的主要碳库,其有机质含量是估算碳储量的基础数据,也是评价土壤碳汇功能的重要指标.利用2009年8月采集的凉水自然保护区激光雷达(LiDAR)数据和55块固定样地土壤有机质含量数据,结合偏最小二乘算法,反演森林表层土壤有机质的空间格局,提取并筛选出与土壤有机质分布相关的变量,分析并确定变量(强度、点数、高程、坡度和坡向)值与土壤有机质含量的相关关系,建立土壤有机质含量的预测模型并检验.结果表明:研究区域表层土壤有机质含量与强度、点数和高程3变量呈极显著相关(r分别为0.765、0.423和0.475);基于此3变量的预测模型对研究区域表层土壤有机质含量的预测结果可靠(精度83.3％,R2=0.725,RMSE=1.955).研究区林缘和郁闭度较小林分的表层土壤有机质含量＜100 g·kg-1;大部分区域表层土壤有机质含量为I00～ 150 g·kg-1,少部分区域为150 ～318.4 g· kg-1.     

Microbiologic air contamination and building-associated illness

Summary Microbiologic air contamination plays, among other factors, a role in building associated illnesses i.e., hypersensitivity diseases, bacterial and fungal infections, sick building syndrome. Airborne microorganisms are separated into obligate parasites, such as the viruses and a few bacteria, that must find a suitable host within a brief period, and facultative saprophytes that are usually found in living hosts an/or in the environment (primary and opportunistic pathogens). The etiology of hypersensitivity diseases is biological allergens such as those from fungi (moulds), bacteria,Amoebae and other protozoa. Humidifiers, cold air coils and porous material belonging to mechanical ventilation system can all be reservoirs/amplifiers/disseminators for living organisms, allergens or other microbial products. Legionella is an ubiquitous bacterium in the environment. Bioaerosols from potable water and air conditioning components appear to be the source of most human infections with this organism (Legionnaire's disease and Pontiac fever).Aspergillus fumigatus has a risk of penetration indoor but affects only people with seriously impaired immunity. Responsibility of airborne moulds, bacterial endotoxins or mycotoxins in sick building syndrome complaints is unclear. Design, operation and maintenance of ventilation systems are fundamental to assure well-being to building occupants.     

Habitat suitability modelling of an invasive plant with advanced remote sensing data

Aim  Lepidium latifolium (Brassicaceae; perennial pepperweed) is a noxious Eurasian weed invading riparian and wetland areas of the western USA. Understanding which sites are most susceptible to invasion by L. latifolium will allow more efficient management of this weed. We assessed the ability of advanced remote sensing techniques to develop habitat suitability models for L. latifolium .
Location  San Francisco Bay/Sacramento-San Joaquin River Delta, California, USA.
Methods  Lepidium latifolium distribution was mapped with hyperspectral image data of Rush Ranch Open Space Preserve, providing presence/absence data to train and validate habitat models. A high-resolution light detection and ranging digital elevation model was used to derive predictor environmental variables (distance to channel, distance to upland, elevation, slope, aspect and convexity). Aggregate decision tree models were used to predict the potential distribution of this species.
Results  Lepidium latifolium infested two zones: near the marshland–upland margin and along channels within the marsh. Topographical data, which are typically strongly correlated with wetland species distributions, were relatively unimportant to L. latifolium occurrence, although relevant microtopography information, particularly relative elevation, was subsumed in the distance to channel variable. The map of potential L. latifolium distribution reveals that Rush Ranch contains considerable habitat that it is susceptible to continued invasion.
Main conclusions  Lepidium latifolium invades relatively less stressful sites along the inundation and salinity gradients. Advanced remote sensing datasets were shown to be sufficient for species distribution modelling. Remote sensing offers powerful tools that deserve wider use in ecological research and management.     

Remotely sensed between‐individual functional trait variation in a temperate forest

1. Trait‐based ecology holds the promise to explain how plant communities work, for example, how functional diversity may support community productivity. However, so far it has been difficult to combine field‐based approaches assessing traits at the level of plant individuals with limited spatial coverage and approaches using remote sensing (RS) with complete spatial coverage but assessing traits at the level of vegetation pixels rather than individuals. By delineating all individual‐tree crowns within a temperate forest site and then assigning RS‐derived trait measures to these trees, we combine the two approaches, allowing us to use general linear models to estimate the influence of taxonomic or environmental variation on between‐ and within‐species variation across contiguous space.
2. We used airborne imaging spectroscopy and laser scanning to collect individual‐tree RS data from a mixed conifer‐angiosperm forest on a mountain slope extending over 5.5 ha and covering large environmental gradients in elevation as well as light and soil conditions. We derived three biochemical (leaf chlorophyll, carotenoids, and water content) and three architectural traits (plant area index, foliage‐height diversity, and canopy height), which had previously been used to characterize plant function, from the RS data. We then quantified the contributions of taxonomic and environmental variation and their interaction to trait variation and partitioned the remaining within‐species trait variation into smaller‐scale spatial and residual variation. We also investigated the correlation between functional trait and phylogenetic distances at the between‐species level. The forest consisted of 13 tree species of which eight occurred in sufficient abundance for quantitative analysis.
3. On average, taxonomic variation between species accounted for more than 15% of trait variation in biochemical traits but only around 5% (still highly significant) in architectural traits. Biochemical trait distances among species also showed a stronger correlation with phylogenetic distances than did architectural trait distances. Light and soil conditions together with elevation explained slightly more variation than taxonomy across all traits, but in particular increased plant area index (light) and reduced canopy height (elevation). Except for foliage‐height diversity, all traits were affected by significant interactions between taxonomic and environmental variation, the different responses of the eight species to the within‐site environmental gradients potentially contributing to the coexistence of the eight abundant species.
4. We conclude that with high‐resolution RS data it is possible to delineate individual‐tree crowns within a forest and thus assess functional traits derived from RS data at individual level. With this precondition fulfilled, it is then possible to apply tools commonly used in field‐based trait ecology to partition trait variation among individuals into taxonomic and potentially even genetic variation, environmental variation, and interactions between the two. The method proposed here presents a promising way of assessing individual‐based trait information with complete spatial coverage and thus allowing analysis of functional diversity at different scales. This information can help to better understand processes shaping community structure, productivity, and stability of forests.

     

Estimation of carbon storage based on individual tree detection in <Emphasis Type="Italic">Pinus densiflora</Emphasis> stands using a fusion of aerial photography and LiDAR data

The objective of this study was to estimate the carbon storage capacity of Pinus densiflora stands using remotely sensed data by combining digital aerial photography with light detection and ranging (LiDAR) data. A digital canopy model (DCM), generated from the LiDAR data, was combined with aerial photography for segmenting crowns of individual trees. To eliminate errors in over and under-segmentation, the combined image was smoothed using a Gaussian filtering method. The processed image was then segmented into individual trees using a marker-controlled watershed segmentation method. After measuring the crown area from the segmented individual trees, the individual tree diameter at breast height (DBH) was estimated using a regression function developed from the relationship observed between the field-measured DBH and crown area. The above ground biomass of individual trees could be calculated by an image-derived DBH using a regression function developed by the Korea Forest Research Institute. The carbon storage, based on individual trees, was estimated by simple multiplication using the carbon conversion index (0.5), as suggested in guidelines from the Intergovernmental Panel on Climate Change. The mean carbon storage per individual tree was estimated and then compared with the field-measured value. This study suggested that the biomass and carbon storage in a large forest area can be effectively estimated using aerial photographs and LiDAR data.     

Antibiotic resistance genes in multidrug-resistant Enterococcus spp. and Streptococcus spp. recovered from the indoor air of a large-scale swine-feeding operation

AIMS: In this study, multidrug-resistant bacteria previously recovered from the indoor air of a large-scale swine-feeding operation were tested for the presence of five macrolide, lincosamide and streptogramin (MLS) resistance genes and five tetracycline (tet) resistance genes. METHODS AND RESULTS: Enterococcus spp. (n = 16) and Streptococcus spp. (n =16) were analysed using DNA-DNA hybridization, polymerase chain reaction (PCR) and oligoprobing of PCR products. All isolates carried multiple MLS resistance genes, while 50% of the Enterococcus spp. and 44% of the Streptococcus spp. also carried multiple tet resistance genes. All Enterococcus spp. carried erm(A) and erm(B), 69% carried erm(F), 44% carried mef(A), 75% carried tet(M), 69% carried tet(L) and 19% carried tet(K). All Streptococcus spp. carried erm(B), 94% carried erm(F), 75% carried erm(A), 38% carried mef(A), 50% carried tet(M), 81% carried tet(L) and 13% carried tet(K). CONCLUSIONS: Multidrug resistance among airborne bacteria recovered from a swine operation is encoded by multiple MLS and tet resistance genes. These are the first data regarding resistance gene carriage among airborne bacteria from swine-feeding operations. SIGNIFICANCE AND IMPACT OF THE STUDY: The high prevalence of multiple resistance genes reported here suggests that airborne Gram-positive bacteria from swine operations may be important contributors to environmental reservoirs of resistance genes.     

Rate and diel periodicity of pheromone emission from female gypsy moths, (Lymantria dispar) determined with a glass-adsorption collection system

The rate of pheromone emission from wild and laboratory-reared gypsy moth (Lymantria dispar) (Lepidoptera: Lymantriidae) virgin females was determined with an all-glass aeration apparatus. This device incorporated a bed of 1-mm glass beads to extract entrained pheromone from the air flowing over the protruded gland. The temporal pattern of emission was established by monitoring individual females after eclosion for 24 consecutive 2-hr intervals.At a constant 24°C, both wild and laboratory females exhibited a similar diel periodicity of pheromone emission. The mean release rate increased after onset of photophase, generally attained maximal levels between 1600 and 2200 hr and declined during scotophase. Pheromone was released continuously and the mean daily emission increased with age for both wild and laboratory moths. The mean emission rate over the 48-hr monitoring interval was $\text{15.4 ng}\text{2 hr}$ for wild females vs $\text{14.7 ng}\text{2 hr}$ for laboratory moths. The peak emission from 2-day-old laboratory moths was ca.$\text{28 ng}\text{2 hr}$ compared with the ca.$\text{25 ng}\text{2 hr}$ released by their wild counterparts.The calling periodicity of laboratory females was determined at a constant 24°C and under a natural temperature rhythm. At 24°C, the proportion of females calling exceeded 45% throughout the diel period, whereas under the temperature rhythm, calling was virtually eliminated by temperatures below 15°C, indicating that temperature acts as an exogenous cue to modify the expression of the calling rhythm and thus potentially the periodicity of pheromone emission.