Litter decomposes slowly on shaded steep slope and sunny gentle slope in a typical steppe ecoregion

Plant litter decomposition is mainly affected by litter properties and environmental factors, but the influence of terrain on litter decomposition is not well understood. We studied the effects of terrain on litter decomposition over a period of 12 months at six locations in a typical steppe ecoregion and measured the concomitant release of carbon (C), nitrogen (N), and phosphorus (P). The study site has two aspects, shaded and sunny, each aspect having three slopes: 15°, 30°, and 45°. The same mixed litter was used at each location to exclude the influence of litter quality variation. Results showed that soil temperature and moisture, solar radiation, and plant species diversity varied by terrain, which in turn, affected the k‐value (standardized total effects, 0.78, 0.12, 0.92, 0.23, respectively) and the release of C (0.72, –0.25, 0.83, 0.24, respectively), N (0.89, –0.45, 0.76, 0.40, respectively) and P (0.88, 0.77, 0.58, 0.57, respectively). K‐value and C release decreased with increasing slope on shaded aspect, while increased with increasing slope on sunny aspect. The release of N and P decreased with increasing slope on the shaded aspect. K‐value and C, N, and P release were significantly higher on shaded than that on sunny aspect at 15° and 30°, while at 45°, it was higher on sunny than on shaded aspect. The litter mass loss was slower on shaded 45° and sunny 15°. So moderate grazing or mowing could be used to reduce litter accumulation and accelerate litter decomposition on these terrains. Structural equation modeling indicated that soil temperature and solar radiation had the greatest influence on k‐value and C, N, and P release, and these two factors were directly related to soil moisture and plant species diversity. Overall, our results emphasize the need to consider terrain for litter decomposition in typical steppe ecoregions.     

Contrasting spatial heterogeneity of sessile organisms within mussel (Perna perna L.) beds in relation to topographic variability

We examined the spatial heterogeneity in three sessile rocky shore organisms, the mussel Perna perna, the barnacle Octomeris angulosa (Sowerby) and the red alga Gelidium pristoides (Turn.) at a range of continuous local scales along horizontal transects within mid- and upper mussel beds of South African shores. We also examined the relationships between variability of organisms and topographic features (rock depressions, slope, aspect), and between mussel, barnacle and algal variability over the same scales. To estimate spatial heterogeneity, we analyzed scaling properties of semivariograms using a fractal approach. Relationships between different variables at the different scales were examined by cross-semivariograms. Spatial dependence of P. perna variability increased with spatial dependence of topographic variability, so that scaling regions of mussel and topographic distributions corresponded well. This relationship often improved with larger local scales (mussel cover increased with depressions, steeper slope and aspect towards waves), while at smaller spatial scales, variability in mussel cover was less well explained by variability in topography. The variability of the barnacle O. angulosa exhibited spatial dependence, even on topographically unstructured shores. In contrast, the distribution of the alga G. pristoides revealed high fractal dimensions, showing spatial independence on topographically unstructured shores. Algae also showed a very strong negative relationship with mussels at most local scales, and a negative relationship with barnacles in upper zones, especially at larger local scales. Barnacles may show clear spatial dependence because of hydrodynamics (at larger local scales) and the need to find a future mate in close proximity (at smaller local scales), while algae may show a strong negative relationship with mussels because of competition for space.     

Identification and characterization of cyclic diguanylate signaling systems controlling rugosity in Vibrio cholerae

Vibrio cholerae, the causative agent of the disease cholera, can generate rugose variants that have an increased capacity to form biofilms. Rugosity and biofilm formation are critical for the environmental survival and transmission of the pathogen, and these processes are controlled by cyclic diguanylate (c-di-GMP) signaling systems. c-di-GMP is produced by diguanylate cyclases (DGCs) and degraded by phosphodiesterases (PDEs). Proteins that contain GGDEF domains act as DGCs, whereas proteins that contain EAL or HD-GYP domains act as PDEs. In the V. cholerae genome there are 62 genes that are predicted to encode proteins capable of modulating the cellular c-di-GMP concentration. We previously identified two DGCs, VpvC and CdgA, that can control the switch between smooth and rugose. To identify other c-di-GMP signaling proteins involved in rugosity, we generated in-frame deletion mutants of all genes predicted to encode proteins with GGDEF and EAL domains and then searched for mutants with altered rugosity. In this study, we identified two new genes, cdgG and cdgH, involved in rugosity control. We determined that CdgH acts as a DGC and positively regulates rugosity, whereas CdgG does not have DGC activity and negatively regulates rugosity. In addition, epistasis analysis with CdgG, CdgH, and other DGCs and PDEs controlling rugosity revealed that CdgG and CdgH act in parallel with previously identified c-di-GMP signaling proteins to control rugosity in V. cholerae. We also determined that PilZ domain-containing c-di-GMP binding proteins contribute minimally to rugosity, indicating that there are additional c-di-GMP binding proteins controlling rugosity in V. cholerae.     

Occupancy in dynamic systems: accounting for multiple scales and false positives using environmental DNA to inform monitoring

Occupancy is an important metric to understand current and future trends in populations that have declined globally. In addition, occupancy can be an efficient tool for conducting landscape-scale and long-term monitoring. A challenge for occupancy monitoring programs is to determine the appropriate spatial scale of analysis and to obtain precise occupancy estimates for elusive species. We used a multi-scale occupancy model to assess occupancy of Columbia spotted frogs in the Great Basin, USA, based on environmental DNA (eDNA) detections. We collected three replicate eDNA samples at 220 sites across the Great Basin. We estimated and modeled ecological factors that described watershed and site occupancy at multiple spatial scales simultaneously while accounting for imperfect detection. Additionally, we conducted visual and dipnet surveys at all sites and used our paired detections to estimate the probability of a false positive detection for our eDNA sampling. We applied the estimated false positive rate to our multi-scale occupancy dataset and assessed changes in model selection. We had higher naïve occupancy estimates for eDNA (0.37) than for traditional survey methods (0.20). We estimated our false positive detection rate per qPCR replicate at 0.023 (95% CI: 0.016–0.033). When the false positive rate was applied to the multi-scale dataset, we did not observe substantial changes in model selection or parameter estimates. Conservation and resource managers have an increasing need to understand species occupancy in highly variable landscapes where the spatial distribution of habitat changes significantly over time due to climate change and human impact. A multi-scale occupancy approach can be used to obtain regional occupancy estimates that can account for spatially dynamic differences in availability over time, especially when assessing potential declines. Additionally, this study demonstrates how eDNA can be used as an effective tool for improved occupancy estimates across broad geographic scales for long-term monitoring.     

Using Web images to train a deep neural network to detect sparsely distributed wildlife in large volumes of remotely sensed imagery: A case study of polar bears on sea ice

Remote sensing can be a valuable alternative or complement to traditional techniques for monitoring wildlife populations, but often entails operational bottlenecks at the image analysis stage. For example, photographic aerial surveys have several advantages over surveys employing airborne observers or other more intrusive monitoring techniques, but produce onerous amounts of imagery for manual analysis when conducted across vast areas, such as the Arctic. Deep learning algorithms, chiefly convolutional neural networks (CNNs), have shown promise for automatically detecting wildlife in large and/or complex image sets. But for sparsely distributed species, such as polar bears (Ursus maritimus), there may not be sufficient known instances of the animals in an image set to train a CNN. We investigated the feasibility of instead providing ‘synthesized’ training data to a CNN to detect polar bears throughout large volumes of aerial imagery from a survey of the Baffin Bay subpopulation. We harvested 534 miscellaneous images of polar bears from the Web that we edited to more closely resemble 21 known images of bears from the aerial survey that were solely used for validation. We combined the Web images of polar bears with 6292 random background images from the aerial survey to train a CNN (ResNet-50), which subsequently correctly classified 20/21 (95%) bear images from the survey and 1172/1179 (99.4%) random background validation images. Given that even a small background misclassification rate could produce multitudinous false positives over many thousands of photos, we describe a potential workflow to efficiently screen out erroneous detections. We also discuss potential avenues to improve CNN accuracy, and the broader applicability of our approach to other image-based wildlife monitoring scenarios. Our results demonstrate the feasibility of using miscellaneously sourced images of animals to train deep neural networks for specific wildlife detection tasks.     

Potential pitfalls in rescaling digital terrain model-derived attributes for ecological studies

Terrain attributes (e.g., slope, rugosity) derived in Geographic Information Systems (GIS) from digital terrain models (DTMs) are widely used in both terrestrial and marine ecological studies due to their potential to act as surrogates of species distribution. However, the spatial resolution of DTMs is often altered to match the scale at which species observations were collected. Here, we highlight the significance of adequately reporting the methods used to derive terrain attributes from DTMs and the consequences of their incorrect reporting in ecological studies. To ensure full repeatability of studies, they should report (i) the source and the resolution of the original DTM; (ii) the algorithm used to calculate terrain attributes; (iii) the method used for rescaling (e.g., aggregating or resampling, using the mean or maximum values); and (iv) the order in which these operations were performed. We contrast the effects of two common scale alteration approaches for the derivation of terrain attributes from DTMs. These two scale alteration methods differ in the step at which the change is performed: (i) the resolution alteration is performed after computing terrain attributes from the original DTM at the native resolution, or (ii) the resolution alteration is performed on the native DTM before computing terrain attributes. While these approaches conceptually do the same thing (i.e., change the resolution of the terrain attributes), we demonstrate that they produce two distinct sets of variables that are not interchangeable and describe different properties of the terrain. In a species distribution modelling (SDM) context, the first approach calculates terrain attribute values within the cell where a species is found, while the second approach calculates terrain attribute values with respect to neighbouring cells. A mutual substitution of the two approaches results in a decrease of models' discrimination ability and in misleading spatial predictions of species probability of occurrence. Regardless of the DTM-derived attribute, we argue that the choice of the approach should be carefully guided by both the ecological scale relevant to the question being asked and the performance of pre-analyses. We emphasize that selected methods be clearly described to encourage reproducibility and proper interpretation of results, thus enabling a better understanding of the role of scale in ecology.     

Hierarchical multi-scale occupancy estimation for monitoring wildlife populations

Occupancy estimation is an effective analytic framework, but requires repeated surveys of a sample unit to estimate the probability of detection. Detection rates can be estimated from spatially replicated rather than temporally replicated surveys, but this may violate the closure assumption and result in biased estimates of occupancy. We present a new application of a multi-scale occupancy model that permits the simultaneous use of presence–absence data collected at 2 spatial scales and uses a removal design to estimate the probability of detection. Occupancy at the small scale corresponds to local territory occupancy, whereas occupancy at the large scale corresponds to regional occupancy of the sample units. Small-scale occupancy also corresponds to a spatial availability or coverage parameter where a species may be unavailable for sampling at a fraction of the survey stations. We applied the multi-scale occupancy model to a hierarchical sample design for 2 bird species in the Black Hills National Forest: brown creeper (Certhia americana) and lark sparrow (Chondestes grammacus). Our application of the multi-scale occupancy model is particularly well suited for hierarchical sample designs, such as spatially replicated survey stations within sample units that are typical of avian monitoring programs. The model appropriately accounts for the non-independence of the spatially replicated survey stations, addresses the closure assumption for the spatially replicated survey stations, and is useful for decomposing the observation process into detection and availability parameters. This analytic approach is likely to be useful for monitoring at local and regional scales, modeling multi-scale habitat relationships, and estimating population state variables for rare species of conservation concern. © 2011 The Wildlife Society.     

Temporal Changes in Forest Contexts at Multiple Extents: Three Decades of Fragmentation in the Gran Chaco (1979-2010), Central Argentina

The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979–2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (P _f) and structural connectivity (P _ff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting P _f vs. P _ff mean values and were compared across spatial extents. The distributions of P _f across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of P _f’s variability along with the increment of the mean slope of the P _f ‘s scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation and sustainable management of the dry Chaco should take into account both the context of each habitat location and the scales over which a forest pattern might be preserved, altered or restored.     

Relationships Between Reef Fish Communities and Remotely Sensed Rugosity Measurements in Biscayne National Park,Florida, USA

The realization that coral reef ecosystem management must occur across multiple spatial scales and habitat types has led scientists and resource managers to seek variables that are easily measured over large areas and correlate well with reef resources. Here we investigate the utility of new technology in airborne laser surveying (NASA Experimental Advanced Airborne Research Lidar (EAARL)) in assessing topographical complexity (rugosity) to predict reef fish community structure on shallow (<10 m deep) patch reefs. Marine portions of Biscayne National Park, Florida, USA, were surveyed remotely using the EAARL, and reef fish populations were visually surveyed on 10 patch reefs at independent, randomly selected stations (n = 10–13 per reef). Rugosity at each station was assessed in situ by divers using the traditional chain-transect method (10-m scale), and remotely using the EAARL submarine topography data at multiple spatial scales (2, 5, and 10 m). The rugosity and biological datasets were analyzed together to elucidate the predictive power of EAARL rugosity in describing the variance in reef fish community variables and to assess the correlation between chain-transect and EAARL rugosity. EAARL rugosity was not well correlated with chain-transect rugosity, or with species richness of fishes (although statistically significant, the amount of variance explained by the model was very low). Variance in reef fish community attributes was better explained in reef-by-reef variability than by physical variables. However, once the reef-by-reef variability was taken into account in a two-way analysis of variance, the importance of rugosity could be seen on individual reefs. Fish species richness and abundance were statistically higher at high rugosity stations compared to medium and low rugosity stations, as predicted by prior ecological research. The EAARL shows promise as an important mapping tool for reef resource managers as they strive to inventory and protect coral reef resources.     

Applying structure-from-motion habitat reconstruction and GIS terrain analysis to test hypotheses about nest-site selection by shorebirds

Habitat variables related to vegetation type and structure are routinely identified as important components of nest-site selection for birds. For ground-nesting birds, small-scale (< 0.5 m) microtopography may also play a role in nest-site selection through its effects on nest concealment and microclimate. Manual measurements of microtopography are challenging, time-consuming, and subject to user error. Ultrahigh-density point clouds generated using structure-from-motion (SfM) algorithms and photomosaics captured during Unmanned Aerial Vehicle (UAV) surveys can potentially provide detailed topographical measurements with less error. We used multiple indices of surface roughness to examine the effect of microtopography on nest site selection by White-rumped Sandpipers (Calidris fuscicollis) at East Bay Migratory Bird Sanctuary, Nunavut, Canada. We measured microtopography manually using the relative height index within a 1-m radius of used and unused sites. We generated three digital indices of surface roughness for 1-m and 5-m scales around nests and unused sites, including standard deviation of slope, slope variability, and 2D:3D area ratio. We compared the digital indices of used and unused sites at both spatial scales. Relative height of nearby hummocks was significantly lower at nests than at unused sites, indicating selection for flatter sites. Similarly, two of three digitally calculated terrain roughness indices were significantly lower at nests than unused sites at both the 1-m and 5-m scales. The 2D:3D ratio did not differ between nests and unused sites. Manual and UAV-derived measures were significantly correlated, but with substantial unexplained variation (Pearson’s r = 0.35–0.46). Our results suggest that White-rumped Sandpipers select nest sites in areas with low terrain roughness, potentially to increase their field of view to monitor approaching predators. We also demonstrate the applicability of SfM habitat reconstruction for testing hypotheses of small-scale habitat variables that may be impossible to study using traditional methods.     

New potential for enhancing concomitant chemoradiotherapy with FDA approved concentrations of cisplatin via the photoelectric effect

We predict, for the first time, that by using United States Food and Drug Administration approved concentrations of cisplatin, major radiosensitization may be achieved via photoelectric mechanism during concomitant chemoradiotherapy (CCRT). Our analytical calculations estimate that radiotherapy (RT) dose to cancer cells may be enhanced via this mechanism by over 100% during CCRT. The results proffer new potential for significantly enhancing CCRT via an emerging clinical scenario, where the cisplatin is released in-situ from RT biomaterials loaded with cisplatin nanoparticles.     

A Local Agreement Filtering Algorithm for Transmission EM Reconstructions

We present LAFTER, an algorithm for de-noising single particle reconstructions from cryo-EM.Single particle analysis entails the reconstruction of high-resolution volumes from tens of thousands of particle images with low individual signal-to-noise. Imperfections in this process result in substantial variations in the local signal-to-noise ratio within the resulting reconstruction, complicating the interpretation of molecular structure. An effective local de-noising filter could therefore improve interpretability and maximise the amount of useful information obtained from cryo-EM maps.LAFTER is a local de-noising algorithm based on a pair of serial real-space filters. It compares independent half-set reconstructions to identify and retain shared features that have power greater than the noise. It is capable of recovering features across a wide range of signal-to-noise ratios, and we demonstrate recovery of the strongest features at Fourier shell correlation (FSC) values as low as 0.144 over a 256³-voxel cube. A fast and computationally efficient implementation of LAFTER is freely available.We also propose a new way to evaluate the effectiveness of real-space filters for noise suppression, based on the correspondence between two FSC curves: 1) the FSC between the filtered and unfiltered volumes, and 2) C_ref, the FSC between the unfiltered volume and a hypothetical noiseless volume, which can readily be estimated from the FSC between two half-set reconstructions.     

Measures of giant panda habitat selection across multiple spatial scales for species conservation

Examining ecological processes across spatial scales is crucial as animals select and use resources at different scales. We carried out field surveys in September 2005, March–September 2006, and April 2007, and used ecological niche factor analysis to determine habitat preferences for the giant panda (Ailuropoda melanoleuca) across 4 spatial scales: daily movement, core range, home range, and seasonal elevational migration. We found that giant pandas prefer conifer forest and mixed forest at higher than average elevation (2,157 m) of study area in the 4 scale models. However, we also observed significant scale differences in habitat selection. The strength of habitat preference increased with scale for the 2 disturbed forests (sparse forest and fragmented forest), and decreased with scale for 0–30° gentle slope and south- and north-facing aspect. Furthermore, habitat suitability patterns were scale-dependent. These findings highlight the need to determine species–environment associations across multiple scales for habitat management and species conservation. © 2012 The Wildlife Society.     

Palaeoecological evidence of a historical collapse of corals at Pelorus Island,inshore Great Barrier Reef,following European settlement

The inshore reefs of the Great Barrier Reef (GBR) have undergone significant declines in water quality following European settlement (approx. 1870 AD). However, direct evidence of impacts on coral assemblages is limited by a lack of historical baselines prior to the onset of modern monitoring programmes in the early 1980s. Through palaeoecological reconstructions, we report a previously undocumented historical collapse of Acropora assemblages at Pelorus Island (central GBR). High-precision U-series dating of dead Acropora fragments indicates that this collapse occurred between 1920 and 1955, with few dates obtained after 1980. Prior to this event, our results indicate remarkable long-term stability in coral community structure over centennial scales. We suggest that chronic increases in sediment flux and nutrient loading following European settlement acted as the ultimate cause for the lack of recovery of Acropora assemblages following a series of acute disturbance events (SST anomalies, cyclones and flood events). Evidence for major degradation in reef condition owing to human impacts prior to modern ecological surveys indicates that current monitoring of inshore reefs on the GBR may be predicated on a significantly shifted baseline.     

Habitat complexity and fish size affect the detection of Indo-Pacific lionfish on invaded coral reefs

A standard approach to improving the accuracy of reef fish population estimates derived from underwater visual censuses (UVCs) is the application of species-specific correction factors, which assumes that a species’ detectability is constant under all conditions. To test this assumption, we quantified detection rates for invasive Indo-Pacific lionfish (Pterois volitans and P. miles), which are now a primary threat to coral reef conservation throughout the Caribbean. Estimates of lionfish population density and distribution, which are essential for managing the invasion, are currently obtained through standard UVCs. Using two conventional UVC methods, the belt transect and stationary visual census (SVC), we assessed how lionfish detection rates vary with lionfish body size and habitat complexity (measured as rugosity) on invaded continuous and patch reefs off Cape Eleuthera, the Bahamas. Belt transect and SVC surveys performed equally poorly, with both methods failing to detect the presence of lionfish in >50 % of surveys where thorough, lionfish-focussed searches yielded one or more individuals. Conventional methods underestimated lionfish biomass by ~200 %. Crucially, detection rate varied significantly with both lionfish size and reef rugosity, indicating that the application of a single correction factor across habitats and stages of invasion is unlikely to accurately characterize local populations. Applying variable correction factors that account for site-specific lionfish size and rugosity to conventional survey data increased estimates of lionfish biomass, but these remained significantly lower than actual biomass. To increase the accuracy and reliability of estimates of lionfish density and distribution, monitoring programs should use detailed area searches rather than standard visual survey methods. Our study highlights the importance of accounting for sources of spatial and temporal variation in detection to increase the accuracy of survey data from coral reef systems.     

Biogeographical homogeneity of Caribbean coral reef benthos

Caribbean reef benthic assemblages have been considered biogeographically homogeneous at regional scales, but this concept was recently challenged by Williams et al. (2015, Journal of Biogeography, 42 , 1327–1335). These authors concluded that benthic assemblages exhibit considerable biogeographical variability at regional and smaller scales, that rugosity and wave exposure play key roles in structuring assemblages, and that homogenization has yet to occur at a regional scale. We reassess their conclusions using recently published benthic and fish surveys that targeted sites either protected from fishing or intensively overfished. For sponges, regional variation in assemblages is mostly attributable to the removal of chemically undefended species by sponge‐eating fishes at sites protected from overfishing. We maintain that Caribbean benthic assemblages are remarkably homogeneous when compared to reefs in other tropical regions, and were likely more homogeneous before the localized effects of intensive fishing resulted in top‐down ecosystem alterations in benthic assemblages.     

Knowledge-based framework for delineation and classification of ephemeral plant communities in riverine landscapes to support EC Habitat Directive assessment

Riverine landscapes are shaped by the spatio-temporal dynamics of the water regime. Water level transitions induce a shift in plant species composition from aquatic to ephemeral vegetation communities in riparian habitats. Hence, the occurrence of these ephemerals is strongly related to the hydrological connectivity and therefore used as indicator for the assessment of riparian habitat types. The delineation and assessment of such habitat types is time-consuming due to the indifferent occurrence of the plants. Therefore, in this study a knowledge-based framework is presented to provide readily usable polygons to support subsequent field surveys on species level. Different hierarchical scales range from hydrological connectivity classes to watercourses and to the micro-morphological classification of riparian habitats. The object-based image analysis approach was used to extract information from terrain and groundwater models, aerial images, and thematic data. The study site is located in the Danube floodplains east of Vienna Natura 2000 site. The micro-morphological classification of the watercourses resulted in the delineation of the classes Waterbodies, Riparian Habitats and the remaining Transition Zones. Watercourses with high flow velocity or with low hydrological connectivity show a small portion of potentially suitable riparian habitats for ephemeral vegetation communities. The framework with focus on terrain models delineating the shape of the riparian habitats performed well with an overall accuracy of 90% (kappa = 0.74). The thresholds in the framework were set fixed or calculated automatically to facilitate an application by spatial ecologist due to the combination of remote sensing techniques and GIS functionalities. The knowledge-based framework can be adapted to provide a harmonised and standardised dataset for any riverine study area.     

基于CFD模拟的不同地形格局风场规律及其风感规划对策

近地表地形的风场受坡度坡向、地表形态和空间格局等地形要素的控制,从而影响人的"风感"体验,是人居环境的选址与布局需要考虑的重要因素。通过建立地形3D模型、划分网格、设定模拟工况,运用Fluent 14.0软件对不同山体地形坡度、形态和格局的风场进行CFD （Computational Fluid Dynamics）模拟。结果发现：（1）坡度在0.3以下对地形风场影响较小;当坡度大于0.5时,随坡度增大背风坡风影区逐渐增大,挡风效果更加明显;坡度大于0.7以后,随着风影区加大,回流涡旋更加明显。（2）风场受到周边地形形体的影响,尤其是迎风面和背风面截面变化率。迎风面截面变化率越大,风速变化越快;背风面截面变化越大,背风面的出现风影区和回流涡旋的几率越大。迎风面出现凹形迎风口会形成气体滞留区,而背风面凹形口后部会增加风影区和回流涡旋出现的几率。（3）不同地形格局对单个地形的风场具有强化和减弱效果。"三面环山"的相对封闭的地形格局有利于形成稳定的风场,并提高风感舒适度。在人居环境的风感营造和优化中,需要避开风感敏感区域,即风速激增区、回流涡旋区、无固定风向的强烈湍流区、气流不流通的静风区和气流死循环涡旋区等风感敏感区,并利用植被或者人工构筑物来消除敏感区或削弱这一影响。并根据不同的气候类型和城市特点进行选址、地形改造或者进行内部地形格局调整和优化,以提高风感舒适度。选择开放型地形格局和低坡度、平行风向的流线型地形能够加强通风,而塑造封闭性地形格局和垂直风向的陡坡地形能够减小风速。     

The temperature sensitivity along elevational gradients is more stable in maximum latewood density than tree-ring width

Tree ring-based temperature reconstructions are preferably derived from maximum latewood density (MXD) compared to tree-ring width (TRW). Although temperature signals in MXD are less dependent on site ecology, systematic analyses of the effects of elevation and slope aspect on ring formation are still lacking. Here, we assess the climate sensitivity of MXD and TRW chronologies from six larch (Larix decidua Mill.) sites across the Simplon valley in the southwestern Swiss Alps, representing elevations from 1400 to 2150 m asl on both north- and south-facing slopes. We find decreasing temperature signals with decreasing elevation in MXD and TRW, though correlation coefficients are generally higher for MXD and on the warmer and dryer south exposed slopes. While the greatest temperature signals are found for MJJA at highest elevations with r = 0.71 for MXD and r = 0.57 for TRW (both p < 0.05 and for the 1928–2009 common period), MXD still correlates significantly positive at the lowest elevation site that is ~750 m below the treeline. Our findings indicate the suitability of MXD over TRW for temperature reconstructions when using historical wood sources of unknown origin.     

四川羚牛春季地形选择特征的初步研究

地形是动物栖息地中非常稳定的环境因素。了解有蹄类特殊时期对地形的偏好,既有助于揭示动物行为策略形成的机制,又有助于我们实施保护和管理。本文对羚牛(Budorcas taxicolor tibetana)春季地形选择特征进行了初步探讨,数据来自于4只佩戴GPS无线电颈圈的羚牛3月中旬至4月中旬的定位数据。通过对羚牛活动位点与可选择地形的7个地形因素(坡度、坡向、坡位、海拔、地形起伏度、距峭壁距离、距山脊距离)的比较分析,发现羚牛在春季对地形存在选择。通过因子分析发现,影响羚牛春季地形选择的因素可以分为地形复杂度因子(坡度、地形起伏度),反捕食因子(海拔、距峭壁距离)和坡位因子(坡位)三类因素。与可供选择地形相比,羚牛利用的地形更偏离峭壁或陡坡、坡度更缓、海拔更低、明显偏离山脊、地形起伏程度较低。羚牛显著倾向于选择平坡和中位坡,且主要选择阴坡和阳坡。雌雄个体在7个地形因素的偏好上存在显著的差异,但雌性在距离峭壁和距离山脊的距离以及坡位的选择上与可供选择地形均无显著的差异。