Guava (Psidium guajava) is one of the most aggressive invasive plants in the Galapagos Islands. Determining its provenance and genetic diversity could provide valuable information for its control. With this purpose, we analyzed 11 SSR markers in guava individuals collected from Isabela, Santa Cruz, San Cristobal and Floreana islands in the Galapagos, as well as from mainland Ecuador. The mainland guava population appeared genetically differentiated from the Galapagos populations, with higher genetic diversity levels found in the former. By using different approaches for data analysis, we consistently found that the Central Highlands region of mainland Ecuador is one of the most likely origins of the Galapagos populations. Moreover, the guavas from Isabela and Floreana show a potential genetic input from southern mainland Ecuador, while the population from San Cristobal would be linked to the coastal mainland regions. Interestingly, the proposed origins for the Galapagos guava coincide with the first human settlings of the archipelago. By employing Approximate Bayesian Computation, we propose a model where San Cristobal was the first island to be colonized by guava from the mainland, from which it would have spread to Floreana and finally to Santa Cruz; Isabela would have been seeded from Floreana. An independent trajectory could also have contributed in the invasion of Floreana and Isabela. The pathway shown in our model agrees with the human colonization history of the different islands in the Galapagos. Our model, in conjunction with the clustering patterns of the guava individuals (based on genetic distances), suggests that guava introduction history in the Galapagos archipelago was driven predominantly by a single event (or events in rapid succession) instead of several independent introductions. We thus show that genetic analyses supported by historical sources can be used to answer questions on the variability and history of guava in the Galapagos Islands.
Adaptations to anthropogenic domestic habitats contribute to the success of mosquito Aedes aegypti as a major global vector of several arboviral diseases. The species inhabited African forests before expanding into domestic habitats and spreading to the rest of the world. Despite a well-studied evolutionary history, how this species initially moved into human settlements in Africa remains unclear. During this initial habitat transition, Ae. aegypti switched from using natural containers like tree holes as larval breeding sites to using artificial containers like clay pots. Little is known about how these natural versus artificial containers differ in their environments, or whether Ae. aegypti in forest versus domestic habitats evolved any corresponding incipient behavioral divergence, such as in oviposition. To address these gaps, we first characterized physical characteristics, larval density, microbial density, bacterial composition, and volatile profiles of natural versus artificial containers used as mosquito larval breeding sites. We focused on two localities in Africa, La Lopé, Gabon and Rabai, Kenya. In both localities, our data showed that the two habitat-specific container types had significantly different characteristics. We then examined whether such containers differed in their attractiveness for oviposition, a key behavior affecting larval distribution. Forest Ae. aegypti readily accepted artificial containers in our field experiments, and laboratory choice experiments did not find distinct oviposition preference between forest and village Ae. aegypti colonies. These results suggested that African Ae. aegypti were likely generalists in their oviposition site choice. This flexibility to accept different containers might play a vital role during the initial domestication of Ae. aegypti, allowing the mosquitoes to use human-stored water as fallback breeding sites during dry seasons. Although ovipositional changes were not present initially, after longer domestic habitat breeding, the mosquitoes did evolve divergence oviposition preference, as suggested by previous comparisons of African Ae. aegypti and human-specialized non-African Ae. aegypti.
Both cognitive abilities and dispersal tendencies can vary strongly between individuals. Since cognitive abilities may help dealing with unknown circumstances it is conceivable that dispersers may rely more heavily on learning abilities than residents. However, cognitive abilities are costly and leaving a familiar place might result in losing the advantage of having learned to deal with local conditions. Thus, individuals which invested in learning to cope with local conditions may be more reluctant to leave their natal place. In order to disentangle the complex relationship between dispersal and learning abilities we implemented individual-based simulations. By allowing for developmental plasticity, individuals could either develop a ‘resident´ or ‘dispersal´ cognitive phenotype. In line with our expectations, the correlation between learning abilities and dispersal could take any direction, depending how much time individuals had to recoup their investment in cognition. Both, longevity and the timing of dispersal within lifecycles determine the time individuals have to recoup that investment and thus crucially influence this correlation. We therefore suggest that species´ life-history will strongly impact the expected cognitive abilities of dispersers, relative to their resident conspecifics, and that cognitive abilities might be an integral part of dispersal syndromes.
To contain transmission of COVID-19, lockdown or strict restriction of people’s mobility outside their residence was imposed worldwide. In Nepal, the first phase of nationwide lockdown was observed from March 24 to July 21, 2020. This sudden halt in human activities brought positive and negative impacts on forests and wildlife. We undertook a study was undertaken to know the impact of the CoViD-19 lockdown on wildlife and forests in the protected areas (PAs) of Nepal. The study was carried in July and September 2020, data of illegal activities recorded by the PAs and also those reported by media were obtained and analyzed. Key Informant Interview (KII) was done with the park officers and security personnel by virtual communication that included telephone, messenger app, and ZOOM video meeting to collect detailed information and for verification. The collected data were categorized into four groups: i) wildlife killed, ii) wildlife injured, iii) arrest incidents related to forest crime, and iv) arrest incidents related to wildlife crime. Data from the fiscal year 2019-2020 were analyzed, comparing before lockdown and after. The study found trends of substantial increases in. wildlife death in two PAs, Banke National Park and Bardia National Park out of 20 during the lockdown. Similarly, Chitwan National Park (CNP) and Shivapuri Nagarjun National Park (SNNP) witnessed a rise in wildlife poaching. CNP and SNNP are located close to highly populated cities and also having human settlements in their peripheries. Interestingly, wildlife was easily sighted inside PAs during the lockdown, presumably because the absence of visitors and human activities during the lockdown decreased disturbance. Thus, a paradoxical situation was observed with the wildlife enjoying the freedom of movement on the one hand, but with poachers, many of them laid off from other activities, taking advantage of the lapse in security.
Large-scale patterns of biodiversity and the underlying mechanisms that regulate these patterns are central topics in biogeography and macroecology. The Qinghai-Tibetan Plateau (QTP) is a natural laboratory for studying these issues. However, most previous studies have focused on the entire QTP, and the independent physical geographical subunits in the region are not well understood. We studied the current plant diversity on the Kunlun Mountains, an independent physical geographical subunit located in northwest China, on the northern edge of the QTP. We integrated measures of species distribution, geological history, and phylogeography, and analyzed the taxonomic richness, origin time, and community phylogenetic structure of the plants present in the area. The distribution patterns of 1,911 seed plants highlighted that species were located mainly in the eastern regions of the Kunlun Mountains. Chinese endemic species of seed plants accounted for 29.8% of the total species on the Kunlun Mountains. The biodiversity patterns and mean divergence times (MDT) indicated that the eastern region of the Kunlun Mountains was the center for biodiversity conservation, particularly in the southeastern region, which has served as a museum for plant diversity on the Kunlun Mountains. According to the MDT, the origin time of the Kunlun Mountains’ flora (KMF) was early Miocene (19.40 Ma), and the KMF is ancient. The biogeographical roles of the Kunlun Mountains were corridor and sink, and the corresponding key processes were species immigration and extinction. The extant biodiversity on the Kunlun Mountains has occurred through species recolonization after climatic fluctuations and glaciations during the Quaternary. The Kunlun Mountains also formed a barrier, representing a boundary among multiple floras, and converted the QTP into a closed physical geographical unit. The nearest taxon index indicated that habitat filtering may have played an important role in biodiversity patterns.
1. The COVID-19 pandemic has highlighted the importance of efficient sampling strategies and statistical methods for monitoring infection prevalence, both in humans and reservoir hosts. Pooled testing can be an efficient tool for learning pathogen prevalence in a population. Typically pooled testing requires a second phase follow up procedure to identify infected individuals, but when the goal is solely to learn prevalence in a population, such as a reservoir host, there are more efficient methods for allocating the second phase samples. 2. To estimate pathogen prevalence in a population, this manuscript presents an approach for data integration with two-phased testing of pooled samples that allows more efficient estimation of prevalence with less samples than traditional methods. The first phase uses pooled samples to estimate the population prevalence and inform efficient strategies for the second phase. To combine information from both phases, we introduce a Bayesian data integration procedure that combines pooled samples with individual samples for joint inferences about the population prevalence. 3. Data integration procedures result in more efficient estimation of prevalence than traditional procedures that only use individual samples or a single phase of pooled sampling. 4. The manuscript presents guidance on implementing the first phase and second phase sampling plans using data integration. Such methods can be used to assess the risk of pathogen spillover from reservoir hosts to humans, or to track pathogens such as SARS-CoV-2 in populations.
Many organisms can reproduce both asexually and sexually. For cyclical parthenogens, periods of asexual reproduction are punctuated by bouts of sexual reproduction, and the shift from asexual to sexual reproduction has large impacts on fitness and population dynamics. We studied populations of Daphnia dentifera to determine the amount of investment in sexual reproduction as well as the factors associated with variation in investment in sex. To do so, we tracked host density, infections by nine different parasites, and sexual reproduction in 15 lake populations of D. dentifera for three years. Sexual reproduction was seasonal, with male and ephippial female production beginning as early as late September and generally increasing through November. However, there was substantial variation in the prevalence of sexual individuals across populations, with some populations remaining entirely asexual throughout the study period and others shifting almost entirely to sexual females and males. We found strong relationships between density, prevalence of infection, parasite species richness, and sexual reproduction in these populations. However, strong collinearity between density, parasitism, and sexual reproduction means that further work will be required to disentangle the causal mechanisms underlying these relationships.
Plant-plant interactions can vary depending on the severity of the environment. Positive interactions, such as facilitation, are important in early life stages while negative interactions, such as competition, predominate in later stages. Through succession, plant-plant interactions often change from facilitative to competitive. In northern temperate rainforests, gap dynamics result in tree falls that facilitate tree regeneration (nurse logs) as well as bryophyte succession. While the importance of nurse logs for tree seedlings is known, how the interactions of bryophyte communities and tree seedlings vary through succession of the log remains unclear. We examined the relationships of tree seedlings, bryophyte community composition, bryophyte depth, and percent canopy cover in 166 plots on nurse logs and the forest floor in the Hoh rainforest in Washington, USA. Tree seedling density was highest on young logs with early-colonizing bryophyte species (e.g., Rhizomnium glabrescens), and lowest on decayed logs with Hylocomium splendens, a long-lived moss that reaches depths >20 cm. As a result, bryophyte depth increased with nurse log decay and was negatively associated with tree seedling density. Tree seedling density was 4.6x higher on nurse logs than on the forest floor, which was likely due to competitive exclusion by H. splendens. Nurse logs had 17 species of bryophytes while the forest floor had six, indicating that nurse logs contribute to maintaining bryophyte diversity. Nurse logs are essential for forest dynamics as they enable both tree seedlings and smaller bryophyte species to avoid competition with the dominant forest floor bryophyte, H. splendens. Given that H. splendens has a global distribution and is often dominant in forested systems across the northern hemisphere, it is likely a widespread driver of plant community structure. Our findings indicate that plant-plant interactions shift with succession on nurse logs from facilitative to competitive and, thus, influence forest community structure and dynamics.
1. Environmental soundscapes are increasingly being used as descriptors of ecosystem health and vocal animal biodiversity. Soundscape data can quickly become very expensive and difficult to manage, so data compression or temporal down-sampling are sometimes employed to reduce data storage and transmission costs. These parameters vary widely between experiments, with the consequences of this variation remaining mostly unknown. 2. We analyse field recordings from North-Eastern Borneo across a gradient of historical land-use. We quantify the impact of experimental parameters (mp3 compression, recording length and temporal subsetting) on soundscape descriptors (Analytical Indices and a convolutional neural net derived AudioSet Fingerprint). Both descriptor types were tested for their robustness to parameter alteration and their usability in a landscape classification task. 3. We find that compression and frame size both drive considerable variation in calculated index values. However, we find that the effects of this varaiation and temporal subsetting on the performance of classification models is minor: performance is much more strongly determined by acoustic index choice, with Audioset fingerprinting offering substantial (12-16%) increases in all of classifier accuracy, precision and recall. 4. We advise using the AudioSet Fingerprint in soundscape analysis, demonstrating its superior and consistent performance even on small pools of data. If data storage is a bottleneck to a study, we recommend Variable Bit Rate encoded compression (quality=0, 23% file size) to reduce file size without affecting most Analytical Index values. The AudioSet Fingerprint can be confidently compressed further to a Constant Bit Rate encoding of 64kb/s (8% file size) without any detectable effect. These recommendations balance the efficient use of restricted data storage against the comparability of results between different studies.
Point 1: Camera traps have become an extensively utilized tool in ecological research, but the processing of images created by a network of camera traps rapidly becomes an overwhelming task, even for small networks. Point 2: We used transfer training to create convolutional neural network (CNN) models for identification and classification. By utilizing a small dataset with less than 10,000 labeled images the model was able to distinguish between species and remove false triggers. Point 3: We trained the model to detect 17 object classes with individual species identification, reaching an accuracy of 92%. Previous studies have suggested the need for thousands of images of each object class to reach results comparable to those achieved by human observers; however, we show that such accuracy can be achieved with fewer images. Point 4: Additionally, we suggest several alternative metrics common to computer science studies to accurately evaluate the performance of such camera trap image processing models, as well as methods to adapt the model building process to two targeted purposes.
1. The receiver operating characteristic (ROC) and precision-recall (PR) plots have been widely used to evaluate the performances of species distribution models. Plotting ROC/PR curves requires a traditional test set with both presence and absence data (namely PA approach), but species absence data are usually not available in reality. Plotting ROC/PR curves from presence-only data while treating background data as pseudo absence data (namely PO approach) may provide misleading results. 2. In this study we propose a new approach to calibrate the ROC/PR curves from presence and background data with user-provided information on a constant c, namely PB approach. An estimate of c can also be derived from the PB-based ROC/PR plots given that a model with good ability of discrimination is available. We used three virtual species and a real aerial photography to test the effectiveness of the proposed PB-based ROC/PR plots. Different models (or classifiers) were trained from presence and background data with various samples sizes. The ROC/PR curves plotted by PA approach were used to benchmark the curves plotted by PO and PB approaches. 3. Experimental results show that the curves and areas under curves by PB approach are more similar to that by PA approach as compared with PO approach. The PB-based ROC/PR plots also provide highly accurate estimations of c in our experiment. 4. We conclude that the proposed PB-based ROC/PR plots can provide valuable complements to existing model assessment methods, and they also provide an additional way to estimate the constant c (or species prevalence) from presence and background data.
Research on species abundance patterns and the advanced elevational Rapoport rule (ERR) has been widespread in recent years; however, for the temperate mountainous regions in northeast Asia, such research is lacking. Here, we collected plant species from the Seorak Mountain in northeast Asia through field surveys. The species were divided into 11 groups according to the life-form types and phytogeography affinities of each species. The ERR was tested using Steven’s method and by examining the species abundance patterns of each group. The species abundance patterns revealed a positive multimodal pattern along the elevation gradient, but phytogeography affinities (increasing trend) and life-form (unimodal) exhibited different patterns. The elevation gradients (1350 m for the mean elevation-range relationships), which are affected by the boundary effect and different life-forms, did not consistently support the ERR. However, herbs as well as rare, endemic, and red list species showed consistent support for the ERR, which can be influenced by phytogeography affinities. Thus, the results from Seorak Mountain showed that the ERR was not consistent for different plant life-forms in the same area. The result of our field survey revealed that life-forms in the plant species did not support ERR, whereas phytogeography affinities could support and explain ERR.
1. Fruit bats (Family: Pteropodidae) are animals of great ecological and economic importance, yet their populations are threatened by ongoing habitat loss and human persecution. A lack of ecological knowledge for the vast majority of Pteropodid bat species presents additional challenges for their conservation and management. 2. In Australia, populations of flying-fox species (Genus: Pteropus) are declining and management approaches are highly contentious. Australian flying-fox roosts are exposed to management regimes involving habitat modification, either through human-wildlife conflict management policies, or vegetation restoration programs. Details on the fine-scale roosting ecology of flying-foxes are not sufficiently known to provide evidence-based guidance for these regimes and the impact on flying-foxes of these habitat modifications is poorly understood. 3. We seek to identify and test commonly held understandings about the roosting ecology of Australian flying-foxes to inform practical recommendations and guide and refine management practices at flying-fox roosts. 4. We identify 31 statements relevant to understanding of flying-fox roosting structure, and synthesise these in the context of existing literature. We then contribute contemporary data on the fine-scale roosting structure of flying-fox species in south-eastern Queensland and north-eastern New South Wales, presenting a 13-month dataset from 2,522 spatially referenced roost trees across eight sites. 5. We show evidence of sympatry and indirect competition between species, including spatial segregation of black and grey-headed flying-foxes within roosts and seasonal displacement of both species by little red flying-foxes. We demonstrate roost-specific annual trends in occupancy and abundance and provide updated demographic information including the spatial and temporal distributions of males and females within roosts. 6. Insights from our systematic and quantitative study will be important to guide evidence-based recommendations on restoration and management and will be crucial for the implementation of priority recovery actions for the preservation of these species into the future.
Across the globe, ecological communities are confronted with multiple global environmental change drivers, and they are responding in complex ways ranging from behavioural, physiological, and morphological changes within populations to changes in community composition and food web structure with consequences for ecosystem functioning. A better understanding of global change-induced alterations of multitrophic biodiversity and the ecosystem-level responses in terrestrial ecosystems requires holistic and integrative experimental approaches to manipulate and study complex communities and processes above and below the ground. We argue that mesocosm experiments fill a critical gap in this context, especially when based on ecological theory and coupled with microcosm experiments, field experiments, and observational studies of macroecological patterns. We describe the design and specifications of a novel terrestrial mesocosm facility, the iDiv Ecotron. It was developed to allow the setup and maintenance of complex communities and the manipulation of several abiotic factors in a near-natural way, while simultaneously measuring multiple ecosystem functions. To demonstrate the capabilities of the facility, we provide a case study. This study shows that changes in aboveground multitrophic interactions caused by decreased predator densities can have cascading effects on the composition of belowground communities. The iDiv Ecotrons technical features, which allow for the assembly of an endless spectrum of ecosystem components, create the opportunity for collaboration among researchers with an equally broad spectrum of expertise. In the last part, we outline some of such components that will be implemented in future ecological experiments to be realized in the iDiv Ecotron. Key words: food webs, biodiversity and ecosystem functioning, mesocosms, biotic interactions, lysimeters, climate chambers
Vector-borne parasites often manipulate hosts to attract uninfected vectors. For example, parasites causing malaria alter host odor to attract mosquitoes. Here we discuss the ecology and evolution of fruit-colonizing yeast in a tripartite symbiosis – the so-called “killer yeast” system. “Killer yeast” consists of Saccharomyces cerevisiae yeast hosting two double stranded RNA viruses (M satellite dsRNAs, L-A dsRNA helper virus). When both dsRNA viruses occur in a yeast cell, the yeast converts to lethal toxin‑producing “killer yeast” phenotype that kills uninfected yeasts. Yeasts on ephemeral fruits attract insect vectors to colonize new habitats. As the viruses have no extracellular stage, they depend on the same insect vectors as yeast for their dispersal. Viruses also benefit from yeast dispersal as this promotes yeast to reproduce sexually, which is how viruses can transmit to uninfected yeast strains. We tested whether insect vectors are more attracted to killer yeasts than to non‑killer yeasts. In our field experiment, we found that killer yeasts were more attractive to Drosophila than non-killer yeasts. This suggests that vectors foraging on yeast are more likely to transmit yeast with a killer phenotype, allowing the viruses to colonize those uninfected yeast strains that engage in sexual reproduction with the killer yeast. Beyond insights into the basic ecology of the killer yeast system, our results suggest that viruses could increase transmission success by manipulating the insect vectors of their host.
We developed a nonbreeding period continental-scale energetics-based model of daily waterfowl movement to predict year-specific migration and overwinter occurrence. The model approximates energy-expensive movements and energy-gaining stopovers as functions of metabolism and weather, in terms of temperature and frozen precipitation (i.e., snow). The model is a Markov process operating at the population level and is parameterized through a review of literature. We examined model performance against 62 years of non-breeding period daily weather data. The average proportion of available habitat decreased as weather severity increased, with mortality decreasing as the proportion of available habitat increased. The most commonly used nodes during the course of the nonbreeding period were generally consistent across years, with the most inter-annual variation present in the overwintering area. Our model revealed that the distribution of birds on the landscape changed more dramatically when the variation in daily available habitat was greater. The main routes for avian migration in North America were predicted by our simulations: the Eastern, Central, and Western flyways. Our model predicted an average of 77.4% survivorship for the nonbreeding period across all years (range = 76.4 – 78.4%), with lowest survivorship during the fall, intermediate survivorship in the winter, and greatest survivorship in the spring. We provide the parameters necessary for exploration within and among other taxa to leverage the generalizability of this migration model to a broader expanse of bird species, and across a range of climate change and land use/land cover change scenarios.
Recent taxonomic and molecular phylogenetic studies have shown that Gymnosphaera should be recognized as an independent taxonomic unit at the genus level under the family Cyatheaceae. In this study, the complete chloroplast genomes of the eight species of Cyatheaceae were sequenced, and their phylogenetic relationships were reconstructed using the maximum likelihood, Bayesian inference, maximum parsimony, and neighbor-joining methods, and the characteristics of their simple sequence repeats (SSRs) were compared and analyzed for the first time. The results showed that when Cyatheaceae was divided into three genera,the number, relative abundance, relative density, and GC content of all SSRs and of SSRs of certain unit lengths in the chloroplast genomes of the eight species of Cyatheaceae were genus specific in the whole chloroplast genomes and in their different regions (large single-copy, small single-copy, inverted repeat, intergenic spacer, intron, rRNA gene, and coding sequence regions). The SSRs overall and the single-nucleotide SSRs had significant differences in number, relative abundance, relative density, and GC content between the chloroplast genomes, their intergenic regions, and large single-copy regions. When Cyatheaceae was divided into two genera, only the difference in GC content was significant. Therefore, our results support the restoration of the hierarchical status of Gymnosphaera. This study provides an important basis for the identification of the phylogenetic relationship of Cyatheaceae plants.