Taxonomic differences shape the responses of freshwater aerobic anoxygenic phototrophic bacterial communities to light and predation

Aerobic anoxygenic phototrophic (AAP) bacteria are a phylogenetically diverse and ubiquitous group of prokaryotes that use organic matter but can harvest light using bacteriochlorophyll a. Although the factors regulating AAP ecology have long been investigated through field surveys, the few available experimental studies have considered AAPs as a group, thus disregarding the potential differential responses between taxonomically distinct AAP assemblages. Here, we used sequencing of the pufM gene to describe the diversity of AAPs in 10 environmentally distinct temperate lakes, and to investigate the taxonomic responses of AAP communities in these lakes when subjected to similar experimental manipulations of light and predator removal. The studied communities were clearly dominated by Limnohabitans AAP but presented a clear taxonomic segregation between lakes presumably driven by local conditions, which was maintained after experimental manipulations. Predation reduction (but not light exposure) caused significant compositional shifts across most assemblages, but the magnitude of these changes could not be clearly related to changes in bulk AAP abundances or taxonomic richness of AAP assemblages during experiments. Only a few operational taxonomic units, which differed taxonomically between lakes, were found to respond positively during experimental treatments. Our results highlight that different freshwater AAP communities respond differently to similar control mechanisms, highlighting that in‐depth knowledge on AAP diversity is essential to understand the ecology and potential role of these photoheterotrophs.     

Fungal communities living within leaves of native Hawaiian dicots are structured by landscape‐scale variables as well as by host plants

A phylogenetically diverse array of fungi live within healthy leaf tissue of dicotyledonous plants. Many studies have examined these endophytes within a single plant species and/or at small spatial scales, but landscape‐scale variables that determine their community composition are not well understood, either across geographic space, across climatic conditions, or in the context of host plant phylogeny. Here, we evaluate the contributions of these variables to endophyte beta diversity using a survey of foliar endophytic fungi in native Hawaiian dicots sampled across the Hawaiian archipelago. We used Illumina technology to sequence fungal ITS1 amplicons to characterize foliar endophyte communities across five islands and 80 host plant genera. We found that communities of foliar endophytic fungi showed strong geographic structuring between distances of 7 and 36 km. Endophyte community structure was most strongly associated with host plant phylogeny and evapotranspiration, and was also significantly associated with NDVI, elevation and solar radiation. Additionally, our bipartite network analysis revealed that the five islands we sampled each harboured significantly specialized endophyte communities. These results demonstrate how the interaction of factors at large and small spatial and phylogenetic scales shapes fungal symbiont communities.     

基于BSA-seq法的油菜野芥胞质雄性不育恢复基因的分析

细胞质雄性不育是利用杂种优势创制油菜杂交种的重要途径之一。而恢复系的选育及恢复基因的研究有利于提高细胞质雄性不育系的应用价值。该研究以甘蓝型油菜细胞质雄性不育系1193A和恢复系15-R1为亲本,以F_2群体构建了2个极端性状混池,采用BSA-seq技术方法,对恢复基因进行定位分析。结果表明:(1)不育系1193A与恢复系15-R1之间共获得非同义突变的SNPs共33 883个,混池间共有7 996个非同义编码突变。(2)InDel检测与注释结果表明,亲本间引起移码突变的有2 918个,混池间引起移码突变的有840个。(3)综合SNP和InDel的关联分析结果,将恢复基因定位于C09染色体上的0～880000区域,总长度为880 kb。(4)对候选区域的SNP和InDel注释发现,亲本间存在非同义突变的SNP共40个,混池间存在非同义突变的SNP共65个,亲本间存在移码突变的InDel共7个,混池间存在移码突变的InDel共11个;对候选区间内的编码基因进行注释,结果共注释到162个基因,其中存在非同义突变基因11个,移码突变基因5个,这些基因可能与育性恢复有关。     

石灰碳铵熏蒸联合生物有机肥对香蕉枯萎病和细菌群落的影响

以连续种植的香蕉枯萎病高发病蕉园为试验点,通过实时定量PCR和高通量测序等方法,研究了田间条件下石灰碳铵熏蒸联合生物有机肥施用对香蕉枯萎病的防治效果,以及对土壤细菌群落结构和组成的影响。结果表明: 与不熏蒸施用有机肥(OF)相比,香蕉枯萎病发病率在施用有机肥前使用石灰碳铵进行熏蒸处理(LAOF)和施用生物有机肥前使用石灰碳铵进行熏蒸处理(LABF)中分别降低了13.3%和21.7%,病原菌的拷贝数分别降低了22.4%和33.0%。与OF处理相比,石灰碳铵熏蒸联合不同肥料施用均显著降低了细菌的丰富度和多样性,形成了明显不同的群落结构,且熏蒸对群落组成的差异产生了决定性的影响。LABF的细菌丰富度和多样性均低于其他处理,群落组成也与其他处理存在明显差异。与OF处理相比,熏蒸处理(LAOF和LABF)显著增加了土壤中水恒杆菌、布鲁式菌和漯河杆菌属的相对丰度,且在LABF中的相对丰度均高于LAOF,水恒杆菌和布鲁式菌的相对丰度差异显著。在田间条件下,施用生物有机肥之前使用石灰碳铵进行熏蒸处理能够显著降低病原菌数量,改变土壤细菌群落结构,激发土壤有益微生物,从而减少香蕉枯萎病的发生。     

Three critical factors affecting automated image species recognition performance for camera traps

Ecological camera traps are increasingly used by wildlife biologists to unobtrusively monitor an ecosystems animal population. However, manual inspection of the images produced is expensive, laborious, and time‐consuming. The success of deep learning systems using camera trap images has been previously explored in preliminary stages. These studies, however, are lacking in their practicality. They are primarily focused on extremely large datasets, often millions of images, and there is little to no focus on performance when tasked with species identification in new locations not seen during training. Our goal was to test the capabilities of deep learning systems trained on camera trap images using modestly sized training data, compare performance when considering unseen background locations, and quantify the gradient of lower bound performance to provide a guideline of data requirements in correspondence to performance expectations. We use a dataset provided by Parks Canada containing 47,279 images collected from 36 unique geographic locations across multiple environments. Images represent 55 animal species and human activity with high‐class imbalance. We trained, tested, and compared the capabilities of six deep learning computer vision networks using transfer learning and image augmentation: DenseNet201, Inception‐ResNet‐V3, InceptionV3, NASNetMobile, MobileNetV2, and Xception. We compare overall performance on “trained” locations where DenseNet201 performed best with 95.6% top‐1 accuracy showing promise for deep learning methods for smaller scale research efforts. Using trained locations, classifications with <500 images had low and highly variable recall of 0.750 ± 0.329, while classifications with over 1,000 images had a high and stable recall of 0.971 ± 0.0137. Models tasked with classifying species from untrained locations were less accurate, with DenseNet201 performing best with 68.7% top‐1 accuracy. Finally, we provide an open repository where ecologists can insert their image data to train and test custom species detection models for their desired ecological domain.     

Genetic diversity and population structure of Quercus fabri Hance in China revealed by genotyping‐by‐sequencing

Analysis of genetic diversity and population structure among Quercus fabri populations is essential for the conservation and utilization of Q. fabri resources. Here, the genetic diversity and structure of 158 individuals from 13 natural populations of Quercus fabri in China were analyzed using genotyping‐by‐sequencing (GBS). A total of 459,564 high‐quality single nucleotide polymorphisms (SNPs) were obtained after filtration for subsequent analysis. Genetic structure analysis revealed that these individuals can be clustered into two groups and the structure can be explained mainly by the geographic barrier, showed gene introgression from coastal to inland areas and high mountains could significantly hinder the mutual introgression of genes. Genetic diversity analysis indicated that the individual differences within groups are greater than the differences between the two groups. These results will help us better understand the genetic backgrounds of Q. fabri.     

In silico and empirical evaluation of twelve metabarcoding primer sets for insectivorous diet analyses

During the most recent decade, environmental DNA metabarcoding approaches have been both developed and improved to minimize the biological and technical biases in these protocols. However, challenges remain, notably those relating to primer design. In the current study, we comprehensively assessed the performance of ten COI and two 16S primer pairs for eDNA metabarcoding, including novel and previously published primers. We used a combined approach of in silico, in vivo‐mock community (33 arthropod taxa from 16 orders), and guano‐based analyses to identify primer sets that would maximize arthropod detection and taxonomic identification, successfully identify the predator (bat) species, and minimize the time and financial costs of the experiment. We focused on two insectivorous bat species that live together in mixed colonies: the greater horseshoe bat (Rhinolophus ferrumequinum) and Geoffroy's bat (Myotis emarginatus). We found that primer degeneracy is the main factor that influences arthropod detection in silico and mock community analyses, while amplicon length is critical for the detection of arthropods from degraded DNA samples. Our guano‐based results highlight the importance of detecting and identifying both predator and prey, as guano samples can be contaminated by other insectivorous species. Moreover, we demonstrate that amplifying bat DNA does not reduce the primers' capacity to detect arthropods. We therefore recommend the simultaneous identification of predator and prey. Finally, our results suggest that up to one‐third of prey occurrences may be unreliable and are probably not of primary interest in diet studies, which may decrease the relevance of combining several primer sets instead of using a single efficient one. In conclusion, this study provides a pragmatic framework for eDNA primer selection with respect to scientific and methodological constraints.     

Foliar fungal endophyte community structure is independent of phylogenetic relatedness in an Asteraceae common garden

Phylogenetic distance among host species represents a proxy for host traits that act as biotic filters to shape host‐associated microbiome community structure. However, teasing apart potential biotic assembly mechanisms, such as host specificity or local species interactions, from abiotic factors, such as environmental specificity or dispersal barriers, in hyperdiverse, horizontally transmitted microbiomes remains a challenge. In this study, we tested whether host phylogenetic relatedness among 18 native Asteraceae plant species and spatial distance between replicated plots in a common garden affects foliar fungal endophyte (FFE) community structure. We found that FFE community structure varied significantly among host species, as well as host tribes, but not among host subfamilies. However, FFE community dissimilarity between host individuals was not significantly correlated with phylogenetic distance between host species. There was a significant effect of spatial distance among host individuals on FFE community dissimilarity within the common garden. The significant differences in FFE community structure among host species, but lack of a significant host phylogenetic effect, suggest functional differences among host species not accounted for by host phylogenetic distance, such as metabolic traits or phenology, may drive FFE community dissimilarity. Overall, our results indicate that host species identity and the spatial distance between plants can determine the similarity of their microbiomes, even across a single experimental field, but that host phylogeny is not closely tied to FFE community divergence in native Asteraceae.