To test the hypothesis whether a lower metabolic rate is expected in cave organisms compared to surface ones due to an adaptation to food scarcity in subterranean environments, we measured the oxygen consumption rates of individuals from hypogean (i.e. subterranean) and epigean (i.e. surface) populations of the troglophilic newt Calotriton asper. We found that epigean individuals exhibit higher rates than hypogean ones and showed that when we acclimated epigean C. asper to cave conditions, these individuals reduced their oxygen consumption. We compared the metabolic levels of hypogean and epigean C. asper acclimated and non-acclimated to the cave, with the obligate cave salamander Proteus anguinus as wells as two epigean species: an urodel (Ambystoma mexicanum) and a fish (Gobio occitaniae). As predicted, we find differences between hypogean and epigean species, and that the troglophilic C. asper exhibited in-between performances. We argue then that this shift of the metabolic level observed between epigean C. asper non-acclimated and acclimated to the cave is not directly due to the food availability in our experiments but to a stasis of the temperature. However we then discuss that this adjustment of the metabolic level under a temperature close to the thermal optimum may secondarly allow individuals to cope with the food limitations of the subterranean environement.
Abstract: The commercialised genetically modified papaya ‘Huanong No. 1’ has been utilised to successfully control the destructive virus-Papaya ringspot virus (PRSV) in South China since 2006. However, another new emerging virus, Papaya leaf-distortion mosaic virus (PLDMV), was found in some PRSV-resistant transgenic plants in Guangdong and Hainan provinces through a field investigation from 2012 to 2019. The genetic diversity of the isolates is not clear. In the present study, 20 representative isolates were selected to inoculate ‘Huanong No. 1’, and all of the inoculated plants showed obvious disease symptoms similar to those in the field, indicating that PLDMV is a new threat to widely cultivated transgenic papaya in South China. Phylogenetic analysis of the Coat protein genes of 111 PLDMV isolates from Guangdong and Hainan showed that PLDMV can be divided into two groups. The Japan and Taiwan isolates belong to group I, whereas the Guangdong and Hainan isolates belong to group II and can be further divided into two subgroups. The Guangdong and Hainan isolates were far from the isolates of Japan and Taiwan and belong to a new lineage. Further analysis showed that the Guangdong and Hainan isolates had a high degree of genetic differentiation, and no recombination was found. These isolates deviated from neutral evolution and experienced population expansion events in the past, which might still be unstable. The results of this study provide a theoretical basis for clarifying the evolutionary mechanism and population genetics of the virus and for preventing and controlling the viral disease.
The contribution of wild insects to crop pollination is becoming increasingly important as global demand for crops dependent on animal pollination increases. If wild insect populations are to persist in agricultural landscapes, there must be sufficient floral resources (FR) over time and space. The temporal, within-season component of FR availability has rarely been investigated, despite growing recognition of its likely importance for pollinator populations. Here, we examined the visitation rates of common bee genera and the spatiotemporal availability of FR in agroecosystems over one season to determine whether local bee activity was limited by the abundance of landscape FR, and if so, whether it was limited by the present or past abundance of landscape FR. Visitation rates and landscape FR were measured in 27 agricultural sites in Ontario and Québec, Canada, across four time periods and three spatial scales. Landscape FR at varying spatial scales predicted visits for the seven most commonly observed bee genera. Bombus visitation rates were higher in landscapes that had greater cumulative seasonal abundance of FR, suggesting the importance of early-season FR for this taxon. Visits from Halictus and Lasioglossum were higher in landscapes that provided either a stable or increasing amount of FR over the season and were lower in landscapes that experienced a decrease in FR over the course of a season. Andrena, Augochlorella, Megachile, and Peponapis visits were not measurably influenced by FR in previous months but were lower in landscapes that had a higher present abundance of FR, perhaps reflecting pollinator movement or dilution. Our research provides insight into how seasonal fluctuations in floral resources affect bee activity, and by examining each bee genus separately, we could observe how differences in foraging periods, foraging ranges, and the number of broods per season influence how bee taxa respond to food availability within agroecosystems.
1. Quantitative PCR (qPCR) has been commonly used to measure gene expression in a number of research contexts, but the measured RNA concentrations do not always represent the concentrations of active proteins which they encode. This can be due to transcriptional regulation or post-translational modifications, or localisation of immune environments, as can occur during infection. However, in studies using free-living non-model species, such as in ecoimmunological research, qPCR may be the only available option to measure a parameter of interest, and so understanding the quantitative link between gene expression and associated effector protein levels is vital. 2. Here we use qPCR to measure concentrations of RNA from mesenteric lymph node (MLN) and spleen tissue, and multiplex ELISA of blood serum to measure circulating cytokine concentrations in a wild population of a model species, Mus musculus domesticus. 3. Few significant correlations were found between gene expression levels and circulating cytokines of the same immune genes or proteins, or related functional groups. Where significant correlations were observed, these were most frequently within the measured tissue (i.e. the expression levels of genes measured from spleen tissue were more likely to correlate with each other rather than with genes measured from MLN tissue, or with cytokine concentrations measured from blood). 4. Potential reasons for discrepancies between measures, including differences in decay rates and transcriptional regulation networks are discussed. We highlight the relative usefulness of different measures under different research questions, and consider what might be inferred from immune assays.
Macroinvertebrates have been recognized as key ecological indicators of environmental and biodiversity assessment in aquatic ecosystems. However, species identification of macroinvertebrates (especially aquatic insects) proves to be very difficult due to lack of expertise. In this study, we evaluated the feasibility of DNA barcoding for the classification of benthic macroinvertebrates and investigated the genetic differentiation in nine taxonomic groups (Ephemeroptera, Plecoptera, Trichoptera, Diptera, Hemiptera, Coleoptera, Odonata, Mollusca and Annelida) from four large transboundary rivers of northwest China, and further explored its potential application to environment and biodiversity assessment. A total of 1227 COI sequences, belonging to 189 species, 122 genera and 59 families were obtained. The barcode gap analysis supported species status using the barcode gap approach. Meanwhile, NJ phylogenetic trees showed that all species group into single-species representing clusters whether from the same population or not, except two species (Polypedilum. laetum and Polypedilum. bullum). The ABGD analysis divided into 190 OTUs (P = 0.0599) and BIN analysis generated 201 different BINs. Phylogenetic diversity (PD) metrics can reflect environmental stress and serve as a metrics of Index of Biotic Integrity (IBI) to reflect the degree of disturbance in river systems.
A research study on morphometrics of Kalophrynus palmatissimus (known as Lowland Grainy Frog) at Ayer Hitam Forest Reserve (AHFR), Selangor and Pasoh Forest Reserve (PFR), Negeri Sembilan was carried out from 12 November 2016 to 13 September 2017. The study was conducted to examine data on the morphometric traits of K. palmatissimus at the two forest reserves. 15 morphometric traits of K. palmatissimus were taken by using vernier calipers. Frog surveys were done by using 15 and 18 nocturnal 400 m transect lines at AHFR and PFR, respectively. In addition, five climatic data were recorded. The results showed that most of the morphometric traits in AHFR (n = 34) and PFR (n = 31) were positively correlated within each other. General Linear Model (GLM) analysis, showed that snout-vent length (SVL) influenced most morphometric traits, except for hand length. Later, it was found that the snout-vent length of K. palmatissimus in AHFR were slightly larger than PFR. From PCA analysis, morphometric traits were grouped into two components for AHFR and PFR, respectively. In AHFR, head length, eye diameter, head width, internarial distance, interorbital distance, forearm length, tibia length, foot length, and thigh length were strongly correlated while snout length and eye-nostril distance were strongly correlated. In PFR, eye diameter, head width, internarial distance, interorbital distance, foot length and thigh length were strongly correlated, while snout length and eye-nostril distance were strongly correlated; hence, suggesting that all morphometric traits grow simultaneously in K. palmatissimus with eye-nostril distance (EN), and snout length (SL) were closely growing simultaneously at AHFR and PFR. To conclude, the data collections showed the 15 different morphometric traits of K. palmatisssimus between AHFR and PFR with K. palmatissimus at AHFR were slightly larger than at PFR. Key words: Kalophrynus palmatissimus, forest reserve, morphometrics, climatic factors, transect lines
Geographical gradients in species diversity have long fascinated biogeographers and ecologists. However, the extent and generality of the positive/negative effects of the important factors governing functional diversity (FD) patterns are still debated, especially for the freshwater domain. We examined lake productivity and functional richness (FRic) of waterbirds sampled from 35 lakes and reservoirs in northern China with a geographic coverage of over 5 million km2. We used structural equation modelling (SEM) to explore the causal relationships between geographic position, climate, lake productivity and waterbirds FRic. We found unambiguous altitudinal and longitudinal gradients in lake productivity and waterbirds FD, which were strongly mediated by local environmental factors. Specifically, we found 1) lake productivity increased northeast but decreased with altitude, and the observed gradients were driven by climate and nutrient availability, with 93% of variation explained in the individual SEM; 2) waterbirds FD showed similar geographic and elevational gradients.; the environmental factors which had direct and/or indirect effects on these geographic and elevational gradients included climate, lake productivity and morphology, which collectively explained more than 56% of the variation in waterbirds FD; and 3) a significant (P = 0.029) causality between lake productivity and waterbirds FD was confirmed. Nevertheless, the causality link was relatively weak in comparison with climate and lake area (standardized path coefficient was 0.65, 0.21, and 0.17 for climate, area, and productivity, respectively). Through articulating the dominant causality paths, our results could contribute to the mechanistic explanations underlying the observed broad–scale biodiversity gradients.
A universal attribute of species is that their distributions are limited by numerous factors that may be difficult to quantify. Furthermore, climate change-induced range shifts have been reported in many taxa, and understanding the implications of these shifts remains a priority and a challenge. One approach is to employ species distribution models which correlates species presence data with a set of predictor variables. Here, we use MAXENT to predict current suitable habitat and to project future distributions of two closely related Phymata species in light of anthropogenic climate change. Using species occurrence data from museum databases and environmental data from WorldClim, we identified environmental variables maintaining the distribution of Phymata americana and Phymata pennsylvanica, and created binary suitability maps of current distributions for both species on ArcMap. We then predicted future distributions using the same environmental variables under different Representative Concentration Pathways (RCP), created binary suitability maps for future distributions, and calculated the degree of overlap between the two species. We found that the strongest predictor to P. americana ranges was precipitation seasonality, while precipitation of the driest quarter and mean temperature of the coldest quarter were strong predictors of P. pennsylvanica ranges. Future ranges for P. americana are predicted to increase northwestward and southward at higher CO2 concentrations. Suitable ranges for P. pennsylvanica are initially predicted to increase, but eventually decrease with slight fluctuations around range edges. There is an increase in overlapping ranges in all future predictions. These differences in optima provide evidence for different environmental requirements for P. americana and P. pennsylvanica, accounting for their distinct ranges. Because these species are ecologically similar and can hybridize, climate change has potentially important eco-evolutionary ramifications. Overall our results are consistent with effects of climate change that is highly variable across species, geographic regions and over time.
Target-site insensitive mutations and overexpression of detoxification genes are two major mechanisms conferring insecticide resistance. Many molecular assays were applied to detect these two kinds of resistance genetic markers in insect populations. Unfortunately, these assays are time-consuming and have high false-positive rates. RNA-Seq data, which contains information on the variation within expressed regions of the genome and expression information of detoxification genes, provides us a valuable resource to detect resistance-associated markers. At present, there is no corresponding method at present. Here, we collected 66 reported resistance mutations of four main insecticide targets (AChE, VGSC, RyR, and nAChR) of 82 insect species. Next, we obtained 403 sequences of the four target genes and 12,665 sequences of three kinds of detoxification genes including P450, GST, and CCE. Here, we developed a Perl program, FastD, to detect insecticide target-site insensitive mutations and overexpressed detoxification genes from RNA-Seq data, and constructed a web server for FastD (http://www.insect-genome.com/fastd). FastD program was then applied to detect two kinds of resistant markers in five populations of two insects, Plutella xylostella and Aphis gossypii. Results showed that RyR mutation G4946E was detected in all P. xylostella populations, with higher frequencies in two resistant populations, ZZ (66.1%) and CHR (94.55%), than a susceptible population CHS (2.32%). CYP6a2 was overexpressed 10.82-fold in ZZ population. As to A. gossypii, nAChR mutation R81T was detected in resistant population KR with 49.85% frequency, but not in susceptible population NS. CYP6CY22 and CYP6CY13 were overexpressed 39.61- and 22.04-fold respectively in KR population. FastD is a program using RNA-Seq data to detect two types of resistance markers to estimate resistance level of insect populations. Generally, resistance level estimated by FastD were consistent with previous reports, confirming the reliability of this program in predicting population resistance at omics-level.
Accurately estimating abundance is a critical component of monitoring and recovery of rare and elusive species. Spatial capture-recapture (SCR) models are an increasingly popular method for robust estimation of ecological parameters. We provide a maximum likelihood analytical framework to assess results from empirical studies to inform SCR sampling design, using both simulated and empirical data from non-invasive genetic sampling of seven boreal caribou populations (Rangifer tarandus caribou) which varied in range size and estimated population density. We use simulated population data with varying levels of clustered distributions to quantify the impact of non-independence of detections on density estimates, and empirical datasets to explore the influence of varied sampling intensity on the relative bias and precision of density estimates. Simulations revealed that clustered distributions of detections did not significantly impact relative bias or precision of density estimates. The empirical genotyping success rate was 95.1%. Empirical results indicated that reduced sampling intensity had a greater impact on density estimates in smaller ranges. The number of captures and spatial recaptures were strongly correlated with precision, but not relative bias. The best sampling designs did not differ with estimated population density but differed between large and small ranges. We provide an efficient framework implemented in R to estimate the detection parameters required when designing SCR studies. The framework can be used when designing a monitoring program to minimize effort and cost while maximizing effectiveness, which is critical for informing wildlife management and conservation.
Participatory approaches such as community photography can engage the public in questions of societal and scientific interest. We combined data extracted from community-sourced, spatially-explicit photographs with research findings from 2018 fieldwork in the Yukon, Canada, to evaluate winter coat moult patterns and phenology in mountain goats (Oreamnos americanus), a cold-adapted, alpine mammal. Leveraging the community science portals iNaturalist and CitSci, in less than a year we amassed a database of several hundred unique photographs spanning some 4500 kms between latitudes 37.6°N and 61.1°N from 0m to 4333m elevation. Using statistical methods accounting for incomplete data, a common issue in community science datasets, we evaluated effects of intrinsic (sex and presence of offspring) and environmental (latitude and elevation) factors on moult onset and rate and compared our findings with published data. Shedding occurred over a 3-month period, May 29-September 6. Effects of sex and offspring on the timing of moult were consistent between the community-sourced and our Yukon data and with findings on wild mountain goats at a long-term research site in west-central Alberta, Canada. Males moulted first followed by females without offspring (6.4 days later in the coarse-grained, geographically-wide community science sample; 23.7 days later in our fine-grained Yukon sample) and lastly females with new kids (5.5; 17.9, respectively). Shedding was later at higher than at lower elevations. Northern latitudes had slightly later but shorter shedding periods. We detected a possible shift in moult timing in recent years (2015-2018) that warrants additional investigation. Despite data limitations, such as bias towards recent photographs, our findings establish a basis for employing community photography to examine broad-scale questions about the timing of ecological events, as well as sex differences in response to possible climate drivers. As such, community photography can inspire public participation in environmental and outdoor activities with reference to iconic wildlife.
Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion-activated trail-cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail-cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy are poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online: Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photo was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answer for each photo using a plurality algorithm. Subsequently, a subset of these images underwent expert review and were compared to the citizen scientist results. Classification errors were categorized by the nature of the error (e.g. false species or false empty), and reason for the false classification (e.g. misidentification). Our results show that Snapshot Serengeti had the highest accuracy (97.9%), followed by AmazonCam Tambopata (93.5%), then Wildwatch Kenya (83.4%). Error type was influenced by habitat, with false empty images more prevalent in open-grassy habitat (27%) compared to woodlands (10%). For medium to large animal surveys across all habitat types, our results suggest that to significantly improve accuracy in crowdsourced projects, researchers should use a trail-camera set up protocol with a burst of three consecutive photos, a short field of view, and consider appropriate camera sensitivity. Accuracy level comparisons such as this study can improve reliability of future citizen science projects, and subsequently encourage the increased use of such data.
Abstract Phenotypic plasticity allows organisms to cope with variable environmental conditions increasing both performance and fitness. We studied within-generation plasticity and transgenerational effects of thermal conditions on temperature tolerance and demographic parameters in Drosophila melanogaster. We employed a fully factorial design, in which both parental (P) and offspring generations (F1) were reared in a constant or a variable thermal environment. Thermal variability during ontogeny increased heat tolerance in P, but with demographic cost as this treatment resulted in substantially lower survival, fecundity and net reproductive rate. The adverse effects of thermal variability (V) on demographic parameters were less drastic in flies from the F1, which exhibited higher net reproductive rates than their parents. These compensatory responses could not totally overcome the challenges of the thermally variable regime, contrasting with the offspring of flies raised in a constant temperature (C) that showed no reduction in fitness with thermal variation. Thus, the parental thermal environment had effect on thermal tolerance and demographic parameters in fruit-fly. These results demonstrate how transgenerational effects of environmental conditions on heat tolerance, as well as their potential costs on other fitness components, can have a major impact on populations’ resilience to warming temperatures and more frequent thermal extremes.
The host-associated microbiome plays a significant role in health. However, the roles of factors such as host genetics and microbial interactions in determining microbiome diversity remain unclear. We examined these factors using amplicon-based sequencing of 175 Thoropa taophora frog skin swabs collected from a naturally fragmented landscape in southeastern Brazil. Specifically, we examined (1) the effects of geography and host genetics on microbiome diversity and structure; (2) the structure of microbial eukaryotic and bacterial co-occurrence networks; and (3) co-occurrence between microeukaryotes with bacterial OTUs known to affect growth of the fungal frog pathogen Batrachochytrium dendrobatidis (including anti-Bd bacteria commonly referred to as “antifungal”). Microbiome structure correlated with geographic distance, and microbiome diversity varied with both overall host genetic diversity and diversity at the frog MHC IIB immunity locus. Our network analysis showed the highest connectivity when both eukaryotes and bacteria were included, implying that ecological interactions occur among Domains. Lastly, anti-Bd bacteria did not demonstrate broad negative co-occurrence with fungal OTUs in the microbiome, indicating that these bacteria are unlikely to be broadly antifungal. Our findings emphasize the importance of considering both Domains in microbiome research, and suggest that probiotic strategies for amphibian disease management should be considered with caution.
This paper documents a mass en route mortality event of adult summer chum salmon (Oncorhynchus keta) returning to the Koyukuk River, Alaska in the Yukon River watershed. In response to reports from local communities, researchers (including the author) surveyed ca. 315 km of river on July 26 and 27, 2019 and counted 1,364 dead individuals, but this likely reflects a small fraction of the true number of fish that died. We sampled 73 carcasses to confirm death occurred prematurely prior to complete maturation and spawning, to quantify sex and length. Visual inspection revealed a substantial fraction exhibited patterns of fungal growth consistent with secondary infections of skin lesions caused by the ubiquitous natural bacterial pathogen Flavobacterium columnare. Water temperatures during the survey averaged 17.1°C and the water was approximately 85% saturated with oxygen (ca. 8.5 mg/L), which likely contributed to the stress for upstream migrants. Evidence suggests size-selective en route mortality as female migrants that died were 2% and male migrants 5% shorter than individuals that survived to their spawning grounds on Henshaw Creek. This translates to very strong estimates of natural selection using standardized selection differentials, though randomization tests of size data revealed this observed outcome of selection was expected to occur 25% of the time due to chance alone. It is unclear whether selection acts on body size directly or indirectly through correlated phenotypic traits such as run timing. The mortality event likely underpins the below average returns of summer chum salmon to the Koyukuk in 2019, suggesting an impact on spawner abundance. The future consequences of this, or potentially increasingly frequent, en route mortality events for population productivity and the extent to which genetic adaptation or adaptive phenotypic plasticity of migration behavior may facilitate persistence of these populations is unknown.
Cricket Velarifictorus micado is widely distributed in East Asia and colonized North America since 1959. It has been reported that they had two modes of life cycle and distributed in southern and northern Asia respectively. Aimed to investigate the biogeographic boundary between the two groups and the causes of differentiation, mitochondrial fragments including COI and CytB were used for phylogenetic analysis, time estimation and demographic analysis. The results showed that, (i) Haplotype network indicated that V. micado has diversified to three lineages based on COI. Individuals with egg diapause lived in northern Asia, whereas those with egg and nymph diapause lived in southern Asia, and the populations colonized North America belongs to the egg diapause group from both North and South Asia. (ii) The molecular chronograms indicated that the first diversification between individuals in the northern and southern Asia occurred during ~0.79 Ma BP in the Middle Pleistocene Transition. The second event occurred in southern individuals during ~0.49 Ma BP, when the glaciers developed in Yulong mountain (Yunnan province). (iii) V. micado has diversified to two main clades based on CytB. The individuals distributed in southern China have not been differentiated. Haplotype network indicated that the egg diapause lived in southern China most possibly originated from Yunnan, where lies at the foot of the Tibetan plateau. Our study suggested that the twice divergence of V. micado co-occurred with tendency of cooling climatic in Asia after the Mid-Pleistocene.
To study the genetic diversity and structure of the forest species Pterocarpus erinaceus Poir., seventeen polymorphic nuclear microsatellite markers were isolated and characterized, using Illumina MiSeq sequencing technology. Three hundred and sixty five (365) individuals were analysed within fifteen (15) West Africa populations. The alleles’ number for these loci varied from 4 to 30 and 0.23 to 0.82 for the heterozygosity. The seventeen primers designed here will be useful to analyse ecology population and mechanisms of population differentiation of this threaten species.
1. Accurate differential expression of microbial metatranscriptomes based on Next Generation Sequencing depends partly on the depth of the libraries used to perform the analysis. Therefore, estimating the sequencing depth required to sample the metatranscriptome of interest using RNA-seq effectively is an essential first step to both obtain robust results in further analysis and avoiding over-expending once the information contained in the library reaches saturation. 2. Here we present a method to calculate the effort in saturation curves and a priori genes prediction using a simulated series of metatranscriptomic/metagenomic matrices. This method is based on the extrapolation rarefaction curve using a Weibull growth model to estimate the maximum number of genes/OTUs as a function of sequencing depth using a machine learning approach. This approach allows us to compute the effort at different confidence intervals and to obtain an approximate a priori effort using based on an initial fraction of sequences. 3. The accuracy of the results obtained with simulations and real samples (15 datasets of metatranscriptomes from the oral cavity, RNA sequences consist of vectors of 105-1.5x107 reads depth with a 10000 and 600000 genes size) allows one to use an initial shallowly sequenced sample (in this case 20% of the total amount of reads sampled; accuracy R2>0.99 simulated samples and 60-93% for real samples) to estimate the expected sequencing effort needed to cover the whole metatranscriptome/ metagenome from the same sample, so can be used to estimate the estimate the sample size. The algorithm containing the proposed method was saved as a function for R. 4. This proposed method of estimation of the maximum number of gene/OTUs, reads to reach 90, 95 and 99% of maximum number of gene/OTUs, is efficient to help researchers to know if the sampling is sufficient or otherwise need to be increased.