Site-specific N-glycosylation regulates the GPS auto-proteolysis of CD97

Auto-proteolysis at the G protein-coupled receptor (GPCR) proteolytic site (GPS) is a hallmark of adhesion-GPCRs. Although defects in GPS auto-proteolysis have been linked to genetic disorders, information on its regulation remains elusive. Here, we investigated the GPS proteolysis of CD97, a human leukocyte-restricted and tumor-associated adhesion-GPCR. We found that CD97 is incompletely processed, unlike its close homolog, epidermal growth factor-like module-containing mucin-like hormone receptor 2. A unique pattern of N-glycosylation within the GPS motif of related adhesion-GPCRs was identified. The use of N-glycosylation inhibitors and mutants confirm site-specific N-glycosylation is an important determinant of GPS proteolysis in CD97. Our results suggest that N-glycosylation may regulate the processing of adhesion-GPCRs leading to the production of either cleaved or uncleaved molecules.     

高山峡谷地区无线电遥测与GPS 空间定位的比较:野外放归大熊猫的跟踪定位

以佩戴具有无线电发射功能的GPS 颈圈(Lotek GPS_ 4400M) 的放归大熊猫“祥祥”作为目标动物, 2006 年4 月至2007 年2 月,采用无线电遥测技术(RT)和GPS 跟踪技术在卧龙自然保护区的“五一棚”区域, 每日监测大熊猫在野外环境下的生存状况、移动规律和觅食行为。为了比较RT 和GPS 在高山峡谷地区空间定位的可行性和有效性,我们引入空间定位率、地形特征、空间定位差、巢域大小和日移动距离等指标来分析RT 和GPS 之间的定位差异。结果表明:RT 的空间定位效率明显高于GPS 的自动定位(P < 0. 001),分别是54.1%(绘图法)和45. 2% (≧ 2D);不同月份RT 和GPS 的空间定位率之间具有显著性差异(P < 0. 05),这与大熊猫不同月份的海拔活动范围和觅食行为特性密切相关。RT 位点的地形指数中坡度高于GPS,坡向和海拔高度较GPS 定位点低,两种无线电遥测方法(两点直接计算法和绘图法)之间没有显著性差异(P > 0.05);同一天位点之间的距离(空间定位差)平均450 ～ 660 m 左右;RT 与GPS 所估测的大熊猫巢域大小,除5 月、9 月和12月RT 低于GPS 外,其余月份为前者高于后者,但无显著性差异(P > 0. 05);日移动距离除12 月份RT 小于GPS 外,其余月份都呈现出RT 大于GPS 的格局,统计检验结果两者之间差异显著(P < 0. 05);两种无线电遥测方法所测指数之间都无明显差异(P > 0. 05)。这说明RT 遥测和GPS 定位都可以应用于高山峡谷地区野生动物的生态学研究,而且GPS 无线电颈圈在亚高山和高山森林中具有可行性和有效性。     

Boat-based videographic monitoring of an Adriatic lagoon indicates increase in seagrass cover associated with sediment deposition

Within the scope of a seagrass monitoring program in the Novigrad Sea, Central Croatian Adriatic, we predicted that the annual variability in coverage of seagrasses (Zostera marina, Zostera noltii, and Cymodocea nodosa) can be partially explained by the annual variability in sediment translocation. From 23 fixed DGPS-referenced monitoring video transects followed over three years (June 2007-2009), we calculated annual (i) changes in interior bed seagrass coverage, (ii) gain in seagrass at the lower edge of the bed and seagrass bed expansion, and (iii) accumulation of sediment, its depth dependence, and the associated changes in transect slope. We found that in 2007 to 2008, the year with net sediment accumulation, seagrass coverage increased and the bed expanded. In both years seagrass cover within the seagrass bed increased with increasing sediment accumulation, while seagrass bed expansion was highest under intermediate sedimentation rates. Boat-based videographic monitoring can document both natural sediment movement along the depth gradient, and species-specific responses necessary for informed management of submerged aquatic vegetation in the Adriatic Sea.     

Implications of ignoring telemetry error on inference in wildlife resource use models

Global Positioning System (GPS) and very high frequency (VHF) telemetry data redefined the examination of wildlife resource use. Researchers collar animals, relocate those animals over time, and utilize the estimated locations to infer resource use and build predictive models. Precision of these estimated wildlife locations, however, influences the reliability of point-based models with accuracy depending on the interaction between mean telemetry error and how habitat characteristics are mapped (categorical raster resolution and patch size). Telemetry data often foster the assumption that locational error can be ignored without biasing study results. We evaluated the effects of mean telemetry error and categorical raster resolution on the correct characterization of patch use when locational error is ignored. We found that our ability to accurately attribute patch type to an estimated telemetry location improved nonlinearly as patch size increased and mean telemetry error decreased. Furthermore, the exact shape of these relationships was directly influenced by categorical raster resolution. Accuracy ranged from 100% (200-ha patch size, 1- to 5-m telemetry error) to 46% (0.5-ha patch size, 56- to 60-m telemetry error) for 10 m resolution rasters. Accuracy ranged from 99% (200-ha patch size, 1- to 5-m telemetry error) to 57% (0.5-ha patch size, 56- to 60-m telemetry error) for 30-m resolution rasters. When covariate rasters were less resolute (30 m vs. 10 m) estimates for the ignore technique were more accurate at smaller patch sizes. Hence, both fine resolution (10 m) covariate rasters and small patch sizes increased probability of patch misidentification. Our results help frame the scope of ecological inference made from point-based wildlife resource use models. For instance, to make ecological inferences with 90% accuracy at small patch sizes (≤5 ha) mean telemetry error ≤5 m is required for 10-m resolution categorical rasters. To achieve the same inference on 30-m resolution categorical rasters, mean telemetry error ≤10 m is required. We encourage wildlife professionals creating point-based models to assess whether reasonable estimates of resource use can be expected given their telemetry error, covariate raster resolution, and range of patch sizes. © 2011 The Wildlife Society.     

Estimating utilization distributions with kernel versus local convex hull methods

Estimates of utilization distributions (UDs) are used in analyses of home-range area, habitat and resource selection, and social interactions. We simulated data from 12 parent UDs, representing 3 series of increasingly intense space-use patterns (clustering of points around a home site, restriction of locations to a network of nodes and corridors, and dominance of a central hole in the UD) and compared the ability of kernel density estimation (KDE) and local convex hull (LCH) construction to reconstruct known UDs from samples of 10, 50, 250, and 1,000 location points. For KDE, we considered 4 bandwidth selectors: the reference bandwidth, least-squares cross-validation (LSCV), direct plug-in (DPI), and solve-the-equation (STE). For the sample sizes and UD patterns tested here, KDE achieved significantly higher volume-of-intersection (VI) scores with known parent UDs than did LCH; KDE also provided less biased home-range area estimates under many conditions. However, LCH minimized the UD volume that occurred outside the true home range boundary (V_out). Among the KDE bandwidth estimators, relative performance depended on the type and intensity of space use patterns, sample size, and the metric used to evaluate performance. Biologists should use KDE for UD and home range estimation within a probabilistic context, unless their objective is to exclude potentially unused areas by defining the area delimited by data. © 2011 The Wildlife Society.     

Using a resource selection approach to predict the suitability of alpine habitats for a common herbivore

Climate change models predict that Australia's alpine areas will experience major declines in snow cover, which, in turn, may provide suitable habitat for species presently restricted to lower altitudes. As a result, there are concerns among land managers that many species will invade alpine areas and have a detrimental impact on fragile alpine ecosystems. However, species survival in such areas, irrespective of snow cover, is greatly dependent on the availability of suitable resources. This study investigated the selection of resources by common wombats Vombatus ursinus, which are currently restricted to, but widespread throughout, the subalpine zone of the Snowy Mountains. Our objectives were to identify habitat choices, and build a model of habitat suitability over the broader landscape, to investigate the likelihood of this common herbivore inhabiting the alpine zone. Global positioning system data were obtained from collared wombats, which were tracked for up to a year, to examine resource selection. Resource selection within the home range of individual wombats revealed that topographic position, vegetation cover, drainage, past fire disturbance, and roads were important predictors of locations. A global model showed that wombats selected locations with mid‐elevations, moderate slopes, closer to water courses and roads, and with a lower proportion of grassland, which are discussed in relation to foraging and burrowing requirements. Mapping of the global model illustrated that alpine areas had a low relative probability of use by this species. Consequently, wombats are unlikely to inhabit alpine areas under given climate change scenarios of less snow cover, because the area (presently) does not contain suitable resources necessary for a wombat to maintain a home range. Researchers and managers need to be mindful of how the spatial distribution of resources, in addition to species climatic tolerances, will influence potential range shifts.     

Challenges and prospects in the telemetry of insects

Radio telemetry has been widely used to study the space use and movement behaviour of vertebrates, but transmitter sizes have only recently become small enough to allow tracking of insects under natural field conditions. Here, we review the available literature on insect telemetry using active (battery‐powered) radio transmitters and compare this technology to harmonic radar and radio frequency identification (RFID) which use passive tags (i.e. without a battery). The first radio telemetry studies with insects were published in the late 1980s, and subsequent studies have addressed aspects of insect ecology, behaviour and evolution. Most insect telemetry studies have focused on habitat use and movement, including quantification of movement paths, home range sizes, habitat selection, and movement distances. Fewer studies have addressed foraging behaviour, activity patterns, migratory strategies, or evolutionary aspects. The majority of radio telemetry studies have been conducted outside the tropics, usually with beetles (Coleoptera) and crickets (Orthoptera), but bees (Hymenoptera), dobsonflies (Megaloptera), and dragonflies (Odonata) have also been radio‐tracked. In contrast to the active transmitters used in radio telemetry, the much lower weight of harmonic radar and RFID tags allows them to be used with a broader range of insect taxa. However, the fixed detection zone of a stationary radar unit (< 1 km diameter) and the restricted detection distance of RFID tags (usually < 1–5 m) constitute major constraints of these technologies compared to radio telemetry. Most of the active transmitters in radio telemetry have been applied to insects with a body mass exceeding 1 g, but smaller species in the range 0.2–0.5 g (e.g. bumblebees and orchid bees) have now also been tracked. Current challenges of radio‐tracking insects in the field are related to the constraints of a small transmitter, including short battery life (7–21 days), limited tracking range on the ground (100–500 m), and a transmitter weight that sometimes approaches the weight of a given insect (the ratio of tag mass to body mass varies from 2 to 100%). The attachment of radio transmitters may constrain insect behaviour and incur significant energetic costs, but few studies have addressed this in detail. Future radio telemetry studies should address (i) a larger number of species from different insect families and functional groups, (ii) a better coverage of tropical regions, (iii) intraspecific variability between sexes, ages, castes, and individuals, and (iv) a larger tracking range via aerial surveys with helicopters and aeroplanes equipped with external antennae. Furthermore, field and laboratory studies, including observational and experimental approaches as well as theoretical modelling, could help to clarify the behavioural and energetic consequences of transmitter attachment. Finally, the development of commercially available systems for automated tracking and potential future options of insect telemetry from space will provide exciting new avenues for quantifying movement and space use of insects from local to global spatial scales.