Foraging success under uncertainty: search tradeoffs and optimal space use

Understanding the structural complexity and the main drivers of animal search behaviour is pivotal to foraging ecology. Yet, the role of uncertainty as a generative mechanism of movement patterns is poorly understood. Novel insights from search theory suggest that organisms should collect and assess new information from the environment by producing complex exploratory strategies. Based on an extension of the first passage time theory, and using simple equations and simulations, we unveil the elementary heuristics behind search behaviour. In particular, we show that normal diffusion is not enough for determining optimal exploratory behaviour but anomalous diffusion is required. Searching organisms go through two critical sequential phases (approach and detection) and experience fundamental search tradeoffs that may limit their encounter rates. Using experimental data, we show that biological search includes elements not fully considered in contemporary physical search theory. In particular, the need to consider search movement as a non‐stationary process that brings the organism from one informational state to another. For example, the transition from remaining in an area to departing from it may occur through an exploratory state where cognitive search is challenged. Therefore, a more comprehensive view of foraging ecology requires including current perspectives about movement under uncertainty.     

Room Temperature Processed Highly Efficient Large‐Area Polymer Solar Cells Achieved with Molecular Engineering of Copolymers

The room temperature (RT) processability of the photoactive layers in polymer solar cells (PSCs) from halogen‐free solvent along with their highly reproducible power conversion efficiencies (PCEs) and intrinsic thickness tolerance are extremely desirable for the large‐area roll‐to‐roll (R2R) production. However, most of the photoactive materials in PSCs require elevated processing temperatures due to their strong aggregation, which are unfavorable for the industrial R2R manufacturing of PSCs. These limiting factors for the commercialization of PSCs are alleviated by synthesizing random terpolymers with components of (2‐decyltetradecyl)thiophen‐2‐yl)naphtho[1,2‐c:5,6‐c′]bis[1,2,5]thiadiazole and bithiophene substituted with methyl thiophene‐3‐carboxylate (MTC). In contrast to the temperature‐dependent PNTz4T polymer, the resulting random terpolymers (PNTz4T‐MTC) show better solubility, slightly reduced crystallinity and aggregation, and weaker intermolecular interaction, thus enabling PNTz4T‐MTC to be processed at RT from a halogen‐free solvent. Particularly, the PNTz4T‐5MTC‐based photoactive layer exhibits an excellent PCE of 9.66%, which is among the highest reported PCEs for RT and ecofriendly halogen‐free solvent processed fullerene‐based PSCs, and a thickness tolerance with a PCE exceeding 8% from 100 to 520 nm. Finally, large‐area modules fabricated with the PNTz4T and PNTz4T‐5MTC polymer have shown 4.29% and 6.61% PCE respectively, with an area as high as 54.45 cm² in air.     

Integrating life history traits into predictive phylogeography

Predictive phylogeography seeks to aggregate genetic, environmental and taxonomic data from multiple species in order to make predictions about unsampled taxa using machine‐learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive frameworks due to difficulties inherent to the scoring of trait data across a taxonomically broad set of taxa. We refine predictive frameworks from two North American systems, the inland temperate rainforests of the Pacific Northwest and the Southwestern Arid Lands (SWAL), by incorporating a number of organismal trait variables. Our results indicate that incorporating life history traits as predictor variables improves the performance of the supervised machine‐learning approach to predictive phylogeography, especially for the SWAL system, in which predictions made from only taxonomic and climate variables meets only moderate success. In particular, traits related to reproduction (e.g., reproductive mode; clutch size) and trophic level appear to be particularly informative to the predictive framework. Predictive frameworks offer an important mechanism for integration of organismal trait, environmental data, and genetic data in phylogeographic studies.     

Breeding habitat and nest‐site selection by an obligatory “nest‐cleptoparasite”, the Amur Falcon Falco amurensis

The selection of a nest site is crucial for successful reproduction of birds. Animals which re‐use or occupy nest sites constructed by other species often have limited choice. Little is known about the criteria of nest‐stealing species to choose suitable nesting sites and habitats. Here, we analyze breeding‐site selection of an obligatory “nest‐cleptoparasite”, the Amur Falcon Falco amurensis. We collected data on nest sites at Muraviovka Park in the Russian Far East, where the species breeds exclusively in nests of the Eurasian Magpie Pica pica. We sampled 117 Eurasian Magpie nests, 38 of which were occupied by Amur Falcons. Nest‐specific variables were assessed, and a recently developed habitat classification map was used to derive landscape metrics. We found that Amur Falcons chose a wide range of nesting sites, but significantly preferred nests with a domed roof. Breeding pairs of Eurasian Hobby Falco subbuteo and Eurasian Magpie were often found to breed near the nest in about the same distance as neighboring Amur Falcon pairs. Additionally, the occurrence of the species was positively associated with bare soil cover, forest cover, and shrub patches within their home range and negatively with the distance to wetlands. Areas of wetlands and fallow land might be used for foraging since Amur Falcons mostly depend on an insect diet. Additionally, we found that rarely burned habitats were preferred. Overall, the effect of landscape variables on the choice of actual nest sites appeared to be rather small. We used different classification methods to predict the probability of occurrence, of which the Random forest method showed the highest accuracy. The areas determined as suitable habitat showed a high concordance with the actual nest locations. We conclude that Amur Falcons prefer to occupy newly built (domed) nests to ensure high nest quality, as well as nests surrounded by available feeding habitats.     

pr2-primers: An 18S rRNA primer database for protists

Metabarcoding of microbial eukaryotes (collectively known as protists) has developed tremendously in the last decade, almost solely relying on the 18S rRNA gene. As microbial eukaryotes are extremely diverse, many primers and primer pairs have been developed. To cover a relevant and representative fraction of the protist community in a given study system, an informed primer choice is necessary, as no primer pair can target all protists equally well. As such, a smart primer choice is very difficult even for experts and there are very few online resources available to list existing primers. We built a database listing 285 primers and 83 unique primer pairs that have been used for eukaryotic 18S rRNA gene metabarcoding. In silico performance of primer pairs was tested against two sequence databases: PR² version 4.12.0 for eukaryotes and a subset of silva version 132 for bacteria and archaea. We developed an R -based web application enabling browsing of the database, visualization of the taxonomic distribution of the amplified sequences with the number of mismatches, and testing any user-defined primer or primer set ( https://app.pr2-primers.org ). Taxonomic specificity of primer pairs, amplicon size and location of mismatches can also be determined. We identified universal primer sets that matched the largest number of sequences and analysed the specificity of some primer sets designed to target certain groups. This tool enables guided primer choices that will help a wide range of researchers to include protists as part of their investigations.     

Forest Fragmentation Reduces Seed Dispersal of Duckeodendron cestroides, a Central Amazon Endemic

Fragmentation that alters mutualistic relationships between plants and frugivorous animals may reduce the seed dispersal of trees. We examined the effects of forest fragmentation on the distributions of seeds and seedlings of a Central Amazon endemic tree, Duckeodendron cestroides . In the dry seasons of 2002–2004, seeds and first-year seedlings were counted within wedge-shaped transects centered around Duckeodendron adults in fragments and nearby continuous forests at the Biological Dynamics of Forest Fragmentation Project. Analyses showed that fragmentation reduced seed dispersal quantity and quality. The percent and distance of dispersed seeds were both twice as great in continuous forest as in fragments. The distances of each tree's five furthest dispersed seeds were three times greater in continuous forest than fragments. Over the 3-yr study, 20 times more seeds were dispersed more than 10 m from parent crowns in continuous forest than fragments. A regression analysis showed more dispersed seeds at all distances in continuous forest than fragments. Dispersal differences were strong in 2002 and 2004, years of large fruit crops, but weak or absent in 2003, when fruit production was low. As distance from parent crowns increased, the number of seedlings declined more rapidly in fragments than continuous forest. Distance-dependent mortality between the seed and seedling stages appeared to be more important in continuous forest than fragments. This research provides ample, indirect evidence demonstrating that forest fragmentation can result in the breakdown of a seed dispersal mutualism, potentially jeopardizing the reproduction of a rare, tropical tree.     

Microsatellites in the striped ground crickets,Allonemobius (Orthoptera: Gryllidae)

Polymorphic di‐, tri‐ and tetranucleotide repeats were examined in Allonemobius to determine whether they could serve as useful markers in studies of sperm precedence, population genetics and hybrid zone structure. Ten microsatellite DNA loci were sufficiently polymorphic to be used for paternity tests and showed no evidence of linkage disequilibrium or deviations from Hardy–Weinberg equilibrium in Allonemobius socius. Nine of 10 of these microsatellites can be amplified from three other Allonemobius species, suggesting that these markers will have widespread utility in this ground cricket genus.     

Isolation and characterization of microsatellite loci in a marine fish species,the tusk (Brosme brosme)

We developed polymerase chain reaction primers for nine dinucleotide microsatellite loci in the marine deep‐sea fish, the tusk (Brosme brosme). All markers were obtained from a partial genomic DNA library, and characterized in 100 unrelated individuals from one putative population. The number of alleles ranged from two to 60 with an average of 15/locus. The observed heterozygosity ranged from 0.020 to 0.826 (average 0.438). Several of the markers amplified multiple alleles from the two other gadoid species tested.     

海州湾春季短蛸的栖息分布特征及其与环境因子的关系

近年来,我国近海多种重要渔业资源处于不同程度的衰退状态,而短蛸具有生命周期短、生长迅速的特点,在我国近海经济渔获产量中占重要地位。然而,有关短蛸的栖息分布特征及其与环境因子的关系尚缺乏研究,不利于更好地保护和利用其资源。本研究根据2011年和2013—2017年春季海州湾的渔业资源和环境因子调查数据,采用随机森林模型、人工神经网络模型和广义提升回归模型3种机器学习方法分析了短蛸的栖息分布特征及其与环境因子的关系。结果表明: 随机森林模型的拟合效果和预测能力在3种模型中优势较大,选择该模型进行分析表明,底层水温、水深和底层盐度对短蛸的栖息分布有较大影响。短蛸的相对资源密度随底层水温、水深和底层盐度的增加均呈先上升后下降趋势。根据FVCOM模型模拟的环境数据,应用随机森林模型预测了短蛸在海州湾海域的栖息分布,发现短蛸主要分布在34.5°—35.8° N、119.7°—121° E之间的海域。