1. Some small mammals exhibit Dehnel’s phenomenon, a drastic decline in body mass, braincase and brain size from summer to winter, followed by a regrowth in spring. This is accompanied by a reorganization of the brain and changes in other organs. The evolutionary link between these changes and seasonality remains unclear, although the magnitude of change varies between locations as the phenomenon is thought to lead to energy savings during winter. 2. Here we explored geographic variation of the intensity of Dehnel’s phenomenon in Sorex araneus. We compiled the literature on seasonal changes in braincase size, brain and body mass, supplemented by our own data from Poland, Germany and Czech Republic. 3. We analysed the effect of geographic and climate variables on the magnitude of change and patterns of brain reorganization. 4. From summer to winter the braincase height decreased by 13%, followed by 10% regrowth in spring. For body mass the changes were -21%/+82%, respectively. Changes increased along the north-east axis. Several climate variables were correlated with these transformations, confirming a link of the magnitude of the changes with environmental conditions. This relationship differed for the brain mass decline vs. regrowth, suggesting that they may have evolved under different selective pressures. 5. We found no geographic trends explaining variability in the brain mass changes although they were similar (-21%/+10%) to those of the braincase size. Underlying patterns of change in brain organisation in North-Eastern Poland were almost identical to the pattern observed in Southern Germany. This indicates that local habitat characteristics may play a more important role in determining brain structure than broad scale geographic conditions. 6. We discuss the techniques and criteria used for studying this phenomenon, as well as its potential presence in other taxa and the importance of distinguishing it from other kinds of seasonal variation.
ABSTRACT Aim Invasive species are one of the main causes of biodiversity loss world-wide. As introduced populations increase in abundance and geographical range, so does the potential for negative impacts on native communities. As such, there is a need to better understand the processes driving range expansion as species become established in recipient landscapes. We investigated the potential for population growth and range expansion of introduced populations of a non-native lizard (Podarcis muralis), considering multi-scale factors influencing growth and spatial spread. Location England, UK Methods We collated records of P. muralis presence through field surveys and a citizen science campaign. We used presence-only models to predict climate suitability at a national scale (5km resolution), and fine-scale habitat suitability at the local scale (2m resolution). We then integrated local models into an individual-based modelling platform to simulate population dynamics and forecast range expansion for 10 populations in heterogeneous landscapes. Results National-scale models indicated climate suitability restricted to the southern parts of the UK, limited by a latitudinal cline in overwintering conditions. Patterns of population growth and range expansion were related to differences in local landscape configuration and heterogeneity. Growth curves suggest populations could be in the early stages of exponential growth. However, annual rates of range expansion are predicted to be low (5-16 m). Conclusions We conclude that extensive nationwide range expansion through secondary introduction is likely to be restricted by currently unsuitable climate beyond southern regions of the UK. However, exponential growth of local populations in habitats providing transport pathways is likely to increase opportunities for regional expansion. The broad habitat niche of P. muralis, coupled with configuration of habitat patches in the landscape, allows populations to increase locally with minimal dispersal.
1. Fire and frost represent two major hurdles for the persistence of trees in open grassy biomes and have both been proposed as drivers of grassland-forest boundaries in Africa. 2. We assess the response of young tree seedlings, which represent a vulnerable stage in tree recruitment, to traumatic fire and frost disturbances. 3. In a greenhouse experiment, we investigated how seedling traits predicted survival and resprouting ability in response to fire vs frost; we characterised survival strategies of seedlings in response to the two disturbances, and we documented how the architecture of surviving seedlings is affected by fire vs frost injury. 4. Survival rates were similar under both treatments. However, different species displayed different levels of sensitivity to fire and frost. Seedling survival was higher for older seedlings and seedlings with more basal leaves. Survivors of a fire event lost more biomass than the survivors of a frost event. However, the architecture of recovered fire and frost treated seedlings were mostly similar. Seedlings that recovered from fire and frost treatments were often shorter than those that had not been exposed to any disturbance, with multiple thin branches, which may increase vulnerability to the next frost or fire event. 5. Synthesis. Fire caused more severe aboveground damage compared to frost, suggesting that trees in these open grassland systems may be subjected to a seedling release bottleneck maintained by fire. However, the woody species composition will almost certainly be influenced by phenomena that affect the timing and frequency of seedling exposure to damage, as mortality was found to be dependent on seedling age. Therefore, changes in fire regime and climate (esp. changes that bring about less frost and reduced fire intensity and frequency) are likely to result in changes in the composition and the structure of the woody components of these systems.
Population genomics is a useful tool in the integrated pest management toolbox for elucidating population dynamics, demography, and histories of invasion. However, next-generation sequencing approaches can be hampered by low DNA input from small organisms, such as insect pests. Here, we use a restriction-site associated DNA sequencing approach combined with whole-genome amplification to assess genomic population structure of a newly described pest of canola, the diminutive canola flower midge, Contarinia brassicola. We find that whole-genome amplification prior to library preparation caused a reduction in the overall number of loci sequenced and an increase in overall sequencing depth but had no discernable impact on genotyping consistency for population genetic analysis. Clustering analyses recovered little geographic structure across the main canola production region, but differentiated several geographically disparate populations at edges of the agricultural zone. Given a lack of alternative hypotheses for this pattern, we suggest these data support alternative hosts for this species and thus our canola-centric view of this midge as a pest has limited our understanding of its biology. These results speak to the need for increased surveying effort across multiple habitats and other potential hosts within Brassicaceae, to elucidate both our ecological and evolutionary knowledge of this species as well as potential management implications.
Most herbivorous insects are diet specialists in spite of the apparent advantages of being a generalist. This conundrum might be explained by fitness trade-offs on alternative host plants, yet evidence of such trade-offs has been elusive. Another hypothesis is that specialization is non-adaptive, evolving through neutral population genetic processes and within the bounds of historical constraints. Here we report on a striking lack of evidence for the adaptiveness of specificity in tropical canopy communities of armored scale insects. We show that specialists abound and that host-use is phylogenetically conservative, but in comparison to generalists, specialists occur on fewer of their potential hosts, and are no more abundant where they do occur. Of course local communities might not reflect regional diversity patterns. But based on our samples, comprising hundreds of species of hosts and armored scale insects at two widely separated sites, host-use specialists do not appear to outperform generalists.
1. Deep roots have long been thought to allow trees to coexist with shallow-rooted grasses. Due to the difficulties of working belowground, data demonstrating water uptake and niche partitioning are uncommon. 2. We describe tree and grass root distributions using a depth-specific tracer experiment in a subtropical savanna, Kruger National Park, South Africa. The depth-specific tracer experiment was conducted three times during each of two growing seasons. These point-in-time measurements (i.e., tracer-defined root distributions) were then used in a soil water flow model to estimate continuous water uptake by depth and plant growth form (trees and grasses) across the two growing seasons. 3. Most active tree and grass roots were in shallow soils: the mean depth of water uptake was 22 cm for trees and 17 cm for grasses. However, slightly deeper rooting distributions provided trees with 5% more soil water than the grasses in a drier precipitation year, but 13% less water in a wet year. Small differences in rooting distributions also provided both trees and grasses with depths and times at which each rooting distributions (tree or grass) could extract more soil water than the other (i.e., unique hydrological niches of 4 to 13 mm water). 4. The effect of rooting distributions has long been inferred. By quantifying the depth and timing of water uptake, this research demonstrated that even though rooting distributions appeared similar, they provided trees and grasses with more total water, access to a unique hydrologic niche, or both. This approach demonstrated how even small differences in rooting distributions can provide plants with resource niches that can contribute to species coexistence.
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.