Fungal spore concentrations in the air at Tiruchirapalli (India) 1987–1988

Summary Using an aeroscope, airborne fungal spores were sampled for two years, 1987–1988 at Tiruchirapalli, Tamil Nadu, India. The aerospora components, their seasonal and annual variations in incidence in the air are discussed and a spore calendar for Tiruchirapalli is presented.     

Structural diversity indices based on airborne LiDAR as ecological indicators for managing highly dynamic landscapes

An objective, quantifiable index of structural biodiversity that could be rapidly obtained with reduced or no field effort is essential for the use of structure as universal ecological indicator for ecosystem management. Active remote sensing provides a rapid assessment tool to potentially guide land managers in highly dynamic and spatially complex landscapes. These landscapes are often dependent on frequent disturbance regimes and characterized by high endemism.We propose a modified Shannon–Wiener Index and modified Evenness Index as stand structural complexity indices for surrogates of ecosystem health. These structural indices are validated at Tall Timbers Research Station the site of one of the longest running fire ecology studies in southeastern U.S. This site is dominated by highly dynamic pine-grassland woodlands maintained with frequent fire. Once the dominant ecosystem in the Southeast, this woodland complex has been cleared for agriculture or converted to other cover types, and depends on a frequent (1- to 3-year fire return interval) low- to moderate-intensity fire regime to prevent succession to mixed hardwood forests and maintain understory species diversity. Structural evaluation of the impact of multiple disturbance regimes included height profiles and derived metrics for five different fire interval treatments; 1-year, 2-year, 3-year, mixed fire frequency (a combination of 2- and 4-year fire returns), and fire exclusion. The 3-dimensional spatial arrangement of structural elements was used to assess hardwood encroachment and changes in structural complexity. In agreement with other research, 3-year fire return interval was considered to be the best fire interval treatment for maintaining the pine-grassland woodlands, because canopy cover and vertical diversity indices were shown to be statistically higher in fire excluded and less frequently burned plots than in 1- and 2-year fire interval treatments. We developed a LiDAR-derived structural diversity index, LHDI, and propose that an ecosystem-specific threshold target for management intervention can be developed, based on significant shifts in structure and composition using this new index.Structural diversity indices can be valuable surrogates of ecosystem biodiversity, and ecosystem-specific target values can be developed as objective quantifiable goals for conservation and ecosystem integrity, particularly in remote areas.     

Canopy closure estimation in a temperate forest using airborne LiDAR and LANDSAT ETM+ data

Aims　Forest canopy closure is one of the essential factors in forest survey, and plays an important role in forest ecosystem management. It is of great significance to study how to apply LiDAR (light detection and ranging) data efficiently in remote sensing estimation of forest canopy closure. LiDAR can be used to obtain data fast and accurately and therefore be used as training and validation data to estimate forest canopy closure in large spatial scale. It can compensate for the insufficiency (e.g. labor-intensive, time-consuming) of conventional ground survey, and provide foundations to forest inventory.Methods　In this study, we estimated canopy closure of a temperate forest in Genhe forest of Da Hinggan Ling area, Nei Mongol, China, using LiDAR and LANDSAT ETM+ data. Firstly, we calculated the canopy closure from ALS (Airborne Laser Scanning) high density point cloud data. Then, the estimated canopy closure from ALS data was used as training and validation data to modeling and inversion from eight vegetation indices computed from LANDSAT ETM+ data. Three approaches, multi-variable stepwise regression (MSR), random forest (RF) and Cubist, were developed and tested to estimate canopy closure from these vegetation indices, respectively.Important findings The validation results showed that the Cubist model yielded the highest accuracy compared to the other two models (determination coefficient (R²) = 0.722, root mean square error (RMSE) = 0.126, relative root mean square error (rRMSE) = 0.209, estimation accuracy (EA) = 79.883%). The combination of LiDAR data and LANDSAT ETM+ showed great potential to accurately estimate the canopy closure of the temperate forest. However, the model prediction capability needs to be further improved in order to be applied in larger spatial scale. More independent variables from other remotely sensed datasets, e.g. topographic data, texture information from high-resolution imagery, should be added into the model. These variables can help to reduce the influence of optical image, vegetation indices, terrain and shadow and so on. Moreover, the accuracy of the LiDAR-derived canopy closure needs to be further validated in future studies.     

北京市三个功能区空气微生物中值直径及粒径分布特征

空气中微生物对人类健康的危害除了与微生物的种类和浓度有关外,还与微生物粒子的大小密切相关,并且不同粒径的空气微生物对人们健康影响的作用机理不同。通过定点试验调查,运用国产安德森生物粒子取样器着重研究北京市3个功能区(文教区-中国科学院生态环境研究中心所在区域、交通干线-西直门和公园绿地-北京植物园)空气微生物的中值直径和粒径分布。结果表明,不同功能区空气微生物的粒径分布相同,空气细菌,真菌与放线菌的粒径分布各不相同。空气细菌粒径呈偏态分布,空气真菌呈对数正态分布,空气放线菌的分布特征与空气真菌相反,主要分布在>8.2μm和<2.0μm级中。不同属真菌的粒径分布也不相同,枝孢属、青霉属和曲霉属呈对数正态分布,链格孢属和无孢菌为偏态分布。空气细菌的中值直径明显大于空气真菌和放线菌。交通干线和公园绿地空气细菌和真菌粒子中值直径明显大于文教区,放线菌粒子中值直径交通干线明显高于文教区和公园绿地。空气微生物中值直径在一年各月中没有明显的变化规律。     

Airborne Laser Scanning as a Tool for Lowland Floodplain Vegetation Monitoring

Monitoring of three-dimensional floodplain vegetation structure is essential for ecological studies, as well as for hydrodynamic modelling of rivers. Height and density of submerged vegetation and density of emergent vegetation are the key characteristics from which roughness parameters in hydraulic models are derived. Airborne laser scanning is a technique with broad applications in vegetation structure mapping, which therefore may be a promising tool in monitoring floodplain vegetation for river management applications. This paper first provides an introduction to the laser scanning technique, and reviews previous studies on the extraction of vegetation height and density of forests, low vegetation and meadows or unvegetated areas. Reliable predictions using laser scan data have been reported for forest height (R²=0.64–0.98), parameters related to forest density, such as stem number, stem diameter, biomass, timber volume or basal area (R²=0.42–0.93), and herbaceous vegetation height (summer condition; R²=0.75–0.89). No empirical relations have been reported on density of herbaceous vegetation. Laser data of meadows and unvegetated areas show too much noise to predict vegetation structure correctly. In a case study for the lower Rhine river, the potential of laser scan mapping of vegetation structure was further explored for winter conditions. Three laser-derived metrics that are often reported in the literature have been applied to characterize local vertical distributions of laser reflections. The laser data clearly show the large structural differences both between and within vegetation units that currently are the basis of floodplain vegetation and roughness mapping. The results indicate that airborne laser scanning is a promising technique for extraction of 3D-structure of floodplain vegetation in winter, except for meadows and unvegetated areas.     

Ability of plant pathogenic fungi Gibberella fujikuroi and Fusarium commune to react with airborne methyl jasmonate

ABSTRACT

The pathogenic fungi Gibberella fujikuroi and Fusarium commune produce jasmonic acid. The application of volatile deuterium-labeled methyl jasmonate increased the amount of nonlabeled JA present in G. fujikuroi and F. commune. These results indicate that the fungi have the ability to react with airborne methyl jasmonate in a manner similar to a plant.     

Characterization of an alpine tree line using airborne LiDAR data and physiological modeling

Understanding what environmental drivers control the position of the alpine tree line is important for refining our understanding of plant stress and tree development, as well as for climate change studies. However, monitoring the location of the tree line position and potential movement is difficult due to cost and technical challenges, as well as a lack of a clear boundary. Advanced remote sensing technologies such as Light Detection and Ranging (LiDAR) offer significant potential to map short individual tree crowns within the transition zone despite the lack of predictive capacity. Process‐based forest growth models offer a complementary approach by quantifying the environmental stresses trees experience at the tree line, allowing transition zones to be defined and ultimately mapped. In this study, we investigate the role remote sensing and physiological, ecosystem‐based modeling can play in the delineation of the alpine tree line. To do so, we utilize airborne LiDAR data to map tree height and stand density across a series of altitudinal gradients from below to above the tree line within the Swiss National Park (SNP), Switzerland. We then utilize a simple process‐based model to assess the importance of seasonal variations on four climatically related variables that impose non‐linear constraints on photosynthesis. Our results indicate that all methods predict the tree line to within a 50 m altitudinal zone and indicate that aspect is not a driver of significant variations in tree line position in the region. Tree cover, rather than tree height is the main discriminator of the tree line at higher elevations. Temperatures in fall and spring are responsible for the major differences along altitudinal zones, however, changes in evaporative demand also control plant growth at lower altitudes. Our results indicate that the two methods provide complementary information on tree line location and, when combined, provide additional insights into potentially endangered forest/grassland transition zones.     

Bioaerosol biomonitoring: Sampling optimization for molecular microbial ecology

Bioaerosols (or biogenic aerosols) have largely been overlooked by molecular ecologists. However, this is rapidly changing as bioaerosols play key roles in public health, environmental chemistry and the dispersal ecology of microbes. Due to the low environmental concentrations of bioaerosols, collecting sufficient biomass for molecular methods is challenging. Currently, no standardized methods for bioaerosol collection for molecular ecology research exist. Each study requires a process of optimization, which greatly slows the advance of bioaerosol science. Here, we evaluated air filtration and liquid impingement for bioaerosol sampling across a range of environmental conditions. We also investigated the effect of sampling matrices, sample concentration strategies and sampling duration on DNA yield. Air filtration using polycarbonate filters gave the highest recovery, but due to the faster sampling rates possible with impingement, we recommend this method for fine ‐scale temporal/spatial ecological studies. To prevent bias for the recovery of Gram‐positive bacteria, we found that the matrix for impingement should be phosphate‐buffered saline. The optimal method for bioaerosol concentration from the liquid matrix was centrifugation. However, we also present a method using syringe filters for rapid in‐field recovery of bioaerosols from impingement samples, without compromising microbial diversity for high ‐throughput sequencing approaches. Finally, we provide a resource that enables molecular ecologists to select the most appropriate sampling strategy for their specific research question.