Habitat suitability and nest survival of white-headed woodpeckers in unburned forests of Oregon

We evaluated habitat suitability and nest survival of breeding white-headed woodpeckers (Picoides albolarvatus) in unburned forests of central Oregon, USA. Daily nest-survival rate was positively related to maximum daily temperature during the nest interval and to density of large-diameter trees surrounding the nest tree. We developed a niche-based habitat suitability model (partitioned Mahalanobis distance) for nesting white-headed woodpeckers using remotely sensed data. Along with low elevation, high density of large trees, and low slope, our habitat suitability model suggested that interspersion–juxtaposition of low- and high-canopy cover ponderosa pine (Pinus ponderosa) patches was important for nest-site suitability. Cross-validation suggested the model performed adequately for management planning at a scale >1 ha. Evaluation of mapped habitat suitability index (HSI) suggested that the maximum predictive gain (HSI = 0.36), where the number of nest locations are maximized in the smallest proportion of the modeled landscape, provided an objective initial threshold for identification of suitable habitat. However, managers can choose the threshold HSI most appropriate for their purposes (e.g., locating regions of low–moderate suitability that have potential for habitat restoration). Consequently, our habitat suitability model may be useful for managing dry coniferous forests for white-headed woodpeckers in central Oregon; however, model validation is necessary before our model could be applied to other locations. © 2011 The Wildlife Society.     

Effects of spatial disturbance on common loon nest site selection and territory success

The common loon (Gavia immer) breeds during the summer on northern lakes and water bodies that are also often desirable areas for aquatic recreation and human habitation. In northern New England, we assessed how the spatial nature of disturbance affects common loon nest site selection and territory success. We found through classification and regression analysis that distance to and density of disturbance factors can be used to classify observed nest site locations versus random points, suggesting that these factors affect loon nest site selection (model 1: Correct classification = 75%, null = 50%, K = 0.507, P < 0.001; model 2: Correct classification = 78%, null = 50%, K = 0.551, P < 0.001). However, in an exploratory analysis, we were unable to show a relation between spatial disturbance variables and breeding success (P = 0.595, R² = 0.436), possibly because breeding success was so low during the breeding seasons of 2007–2008. We suggest that by selecting nest site locations that avoid disturbance factors, loons thereby limit the effect that disturbance will have on their breeding success. Still, disturbance may force loons to use sub-optimal nesting habitat, limiting the available number of territories, and overall productivity. We advise that management efforts focus on limiting disturbance factors to allow breeding pairs access to the best nesting territories, relieving disturbance pressures that may force sub-optimal nest placement. © 2011 The Wildlife Society     

A Bayesian multinomial logistic exposure model for estimating probabilities of competing sources of nest failure

Understanding causes of nest loss is critical for the management of endangered bird populations. Available methods for estimating nest loss probabilities to competing sources do not allow for random effects and covariation among sources, and there are few data simulation methods or goodness‐of‐fit (GOF) tests for such models. We developed a Bayesian multinomial extension of the widely used logistic exposure (LE) nest survival model which can incorporate multiple random effects and fixed‐effect covariates for each nest loss category. We investigated the performance of this model and the accompanying GOF test by analysing simulated nest fate datasets with and without age‐biased discovery probability, and by comparing the estimates with those of traditional fixed‐effects estimators. We then exemplify the use of the multinomial LE model and GOF test by analysing Piping Plover Charadrius melodus nest fate data (n = 443) to explore the effects of wire cages (exclosures) constructed around nests, which are used to protect nests from predation but can lead to increased nest abandonment rates. Mean parameter estimates of the random‐effects multinomial LE model were all within 1 sd of the true values used to simulate the datasets. Age‐biased discovery probability did not result in biased parameter estimates. Traditional fixed‐effects models provided estimates with a high bias of up to 43% with a mean of 71% smaller standard deviations. The GOF test identified models that were a poor fit to the simulated data. For the Piping Plover dataset, the fixed‐effects model was less well‐supported than the random‐effects model and underestimated the risk of exclosure use by 16%. The random‐effects model estimated a range of 1–6% probability of abandonment for nests not protected by exclosures across sites and 5–41% probability of abandonment for nests with exclosures, suggesting that the magnitude of exclosure‐related abandonment is site‐specific. Our results demonstrate that unmodelled heterogeneity can result in biased estimates potentially leading to incorrect management recommendations. The Bayesian multinomial LE model offers a flexible method of incorporating random effects into an analysis of nest failure and is robust to age‐biased nest discovery probability. This model can be generalized to other staggered‐entry, time‐to‐hazard situations.     

Laying sequence,diploid males,and nest usurpation in the leafcutter bee,Megachile rotundata (Hymenoptera: Megachilidae)

Variations from the normal female-male sequence of eggs in nests of the leafcutter bee,Megachile rotundata, were examined. Three alternatives were considered: Out-of-sequence males (i) were diploids, (ii) were the result of supersedure of nests or intraspecific brood parasitism, or (iii) were the result of females occasionally laying a male-female sequence. Electrophoretic data provided definitive evidence of diploid males and of multiple females laying in 7 of 18 nests. In the others, the remaining explanation is that females occasionally lay male eggs before female eggs in a nest.     

Bird's nest fungi (Nidulariales: Nidulariaceae) in Baltic and Dominican amber

Nidula baltica sp. nov. and Cyathus dominicanus sp. nov. are described from Cenozoic Baltic and Dominican amber. These are the first fossil members of the Family Nidulariaceae and show that the basic characteristics of this group were already established some 40–50 million years ago.     

Bridging of anions by hydrogen bonds in nest motifs and its significance for Schellman loops and other larger motifs within proteins

The nest is a protein motif of three consecutive amino acid residues with dihedral angles 1,2‐α_Rα_L (RL nests) or 1,2‐α_Lα_R (LR nests). Many nests form a depression in which an anion or δ‐negative acceptor atom is bound by hydrogen bonds from the main chain NH groups. We have determined the extent and nature of this bridging in a database of protein structures using a computer program written for the purpose. Acceptor anions are bound by a pair of bridging hydrogen bonds in 40% of RL nests and 20% of LR nests. Two thirds of the bridges are between the NH groups at Positions 1 and 3 of the motif (N1N3‐bridging)—which confers a concavity to the nest; one third are of the N2N3 type—which does not. In bridged LR nests N2N3‐bridging predominates (14% N1N3: 75% N2N3), whereas in bridged RL nests the reverse is true (69% N1N3: 25% N2N3). Most bridged nests occur within larger motifs: 45% in (hexapeptide) Schellman loops with an additional 4 → 0 hydrogen bond (N1N3), 11% in Schellman loops with an additional 5 → 1 hydrogen bond (N2N3), 12% in a composite structure including a type 1β‐bulge loop and an asx‐ or ST‐ motif (N1N3)—remarkably homologous to the N1N3‐bridged Schellman loop—and 3% in a composite structure including a type 2β‐bulge loop and an asx‐motif (N2N3). A third hydrogen bond is a previously unrecognized feature of Schellman loops as those lacking bridged nests have an additional 4 → 0 hydrogen bond. Proteins 2014; 82:3023–3031. © 2014 Wiley Periodicals, Inc.     

The risks of learning: confounding detection and demographic trend when using count‐based indices for population monitoring

Theory recognizes that a treatment of the detection process is required to avoid producing biased estimates of population rate of change. Still, one of three monitoring programmes on animal or plant populations is focused on simply counting individuals or other fixed visible structures, such as natal dens, nests, tree cavities. This type of monitoring design poses concerns about the possibility to respect the assumption of constant detection, as the information acquired in a given year about the spatial distribution of reproductive sites can provide a higher chance to detect the species in subsequent years. We developed an individual‐based simulation model, which evaluates how the accumulation of knowledge about the spatial distribution of a population process can affect the accuracy of population growth rate estimates, when using simple count‐based indices. Then, we assessed the relative importance of each parameter in affecting monitoring performance. We also present the case of wolverines (Gulo gulo) in southern Scandinavia as an example of a monitoring system with an intrinsic tendency to accumulate knowledge and increase detectability. When the occupation of a nest or den is temporally autocorrelated, the monitoring system is prone to increase its knowledge with time. This happens also when there is no intensification in monitoring effort and no change in the monitoring conditions. Such accumulated knowledge is likely to increase detection probability with time and can produce severe bias in the estimation of the rate and direction of population change over time. We recommend that a systematic sampling of the population process under study and an explicit treatment of the underlying detection process should be implemented whenever economic and logistical constraints permit, as failure to include detection probability in the estimation of population growth rate can lead to serious bias and severe consequences for management and conservation.     

Enhancing Bioinformatics and Genomics Courses: Building Capacity and Skills via Lab Meeting Activities

Reading, writing, publishing, and publicly presenting scientific works are vital for a young researcher's profile building and career development. Generally, the traditional educational curricula do not offer training possibilities to learn and practice how to prepare, write, and present scientific works. These are rather a part of lab meeting activities in research groups. The lack of such training is more critical in some developing countries because this adds to the rare opportunities to discuss and become involved in the exchanges on state of the art scientific literature. Here the authors relate their experience in introducing a weekly 1-day lab meeting in the framework of two previously organized 3-month courses on “Bioinformatics and Genome Analyses”. The main activities which are developed during these lab meetings include scientific literature follow up as well as preparing and presenting oral and written scientific reviews. These activities prove to be useful for a student's self-confidence building, for enhancing their active participation during the lectures and practical sessions, as well as for the positive impact on running the whole course program. Incorporation of such lab meeting activities in the course program significantly improves the capacity building of the participants, their analytical and critical reading of scientific literature, as well as communication skills. In this work it is shown how to proceed with the different steps involved in the implementation of lab meeting activities, and to recommend their regular institution in similar courses.     

Experiments with artificial nests provide evidence for ant community stratification and nest site limitation in a tropical forest

Ants are dominant in tropical forests and many species nest in hollow cavities. The manner in which species are vertically stratified in these complex habitats is not known, with lack of nest sites being proposed to limit ant populations. Here, we assess ant community stratification and nest site limitation in a lowland rainforest in New Guinea using experimental addition of artificial bamboo nests of two cavity sizes (small: ~12 mm large: ~32 mm diameter) placed at ground level, in the understorey, and in the canopy. We also conducted a pilot experiment to test the utility of nest translocation. Nests were checked for occupancy after 10 weeks and half of the occupied nests were then translocated between forest plots, while keeping same vertical position. Occupancy of small nests was much higher in the understorey and canopy than at ground level (~75% vs. ~25%). Translocation was successful, as a majority of nests was inhabited by the same species before and after translocation and there was no impact of translocation to a different plot compared to the control, except for a reduction in colony size at ground level. Our experiment demonstrates a vertical stratification in community composition of ants nesting in hollow dead cavities and shows that these ants are more nest site limited in the higher strata than at ground level. Use of small artificial cavities has great potential for future experimental studies, especially for those focused on arboreal ants, as occupancy is high and translocation does not negatively affect their colony size. Abstract in Tok Pisin is available with online material.     

城市建筑屋顶光伏发电潜力评估方法和模型

建筑屋顶作为闲置的土地资源已成为光伏发电重要的潜在空间,屋顶光伏发电是脱碳电力供应的主要方式,将在实现城市碳中和进程中发挥重要作用。对建筑屋顶光伏发电潜力进行精确评估将有助于分布式光伏的科学规划和合理布局,提升土地利用效率。旨在对建筑屋顶光伏发电潜力影响因素和评估方法,以及光伏发电潜力主要评估模型进行系统性阐述,比较分析不同评估方法的优缺点,总结未来研究的重点方向。现有研究表明,建筑屋顶光伏发电潜力评估已从经验取值发展为定量空间分析,评估尺度、评估精度和评估成本已经成为不同评估方法综合权衡的重点。现有三种评估方法中,采样法计算成本和数据成本较低,但评估结果不确定性较大、精度较低;全面评估法评估精度较高,但数据获取成本和计算成本较高;机器学习法能够高效挖掘大数据潜力,且算法性能显著提升,因而相较于其他方法更适宜大尺度建筑屋顶光伏发电潜力评估。当前建筑屋顶光伏发电潜力评估仍然存在大尺度精细评估缺乏、评估结果不确定性大以及评估模型计算量大等问题。未来研究重点应关注三个方面：1)建立适宜不同区域的高精度简化模型并完善技术潜力评估模型;2)阐明建筑屋顶光伏发电潜力的影响因素,为代表性建筑分类体系...