scholarly journals Comparing methods for detecting multilocus adaptation with multivariate genotype-environment associations

2017 ◽  
Author(s):  
Brenna R. Forester ◽  
Jesse R. Lasky ◽  
Helene H. Wagner ◽  
Dean L. Urban
Keyword(s):  
Local Adaptation ◽  
Effective Means ◽  
Environmental Data ◽  
Multivariate Methods ◽  
Weak Selection ◽  
Detection Rates ◽  
Gray Wolves ◽  
Constrained Ordination ◽  
Adaptive Processes ◽  
Constrained Ordinations

AbstractIdentifying adaptive loci can provide insight into the mechanisms underlying local adaptation. Genotype-environment association (GEA) methods, which identify these loci based on correlations between genetic and environmental data, are particularly promising. Univariate methods have dominated GEA, despite the high dimensional nature of genotype and environment. Multivariate methods, which analyze many loci simultaneously, may be better suited to these data since they consider how sets of markers covary in response to environment. These methods may also be more effective at detecting adaptive processes that result in weak, multilocus signatures. Here, we evaluate four multivariate methods, and five univariate and differentiation-based approaches, using published simulations of multilocus selection. We found that Random Forest performed poorly for GEA. Univariate GEAs performed better, but had low detection rates for loci under weak selection. Constrained ordinations showed a superior combination of low false positive and high true positive rates across all levels of selection. These results were robust across the demographic histories, sampling designs, sample sizes, and levels of population structure tested. The value of combining detections from different methods was variable, and depended on study goals and knowledge of the drivers of selection. Reanalysis of genomic data from gray wolves highlighted the unique, covarying sets of adaptive loci that could be identified using redundancy analysis, a constrained ordination. Although additional testing is needed, this study indicates that constrained ordinations are an effective means of detecting adaptation, including signatures of weak, multilocus selection, providing a powerful tool for investigating the genetic basis of local adaptation.

Establishment of local adaptation in partly self-fertilizing populations

Genetics ◽  
2021 ◽  
Author(s):  
Bogi Trickovic ◽  
Sylvain Glémin
Keyword(s):  
Local Adaptation ◽  
Pollen Dispersal ◽  
Theoretical Background ◽  
Weak Selection ◽  
Dominance Level ◽  
Self Fertilization ◽  
Protected Polymorphism ◽  
And Migration ◽  
Closed Form Approximation ◽  
Selfing Species

Abstract Populations often inhabit multiple ecological patches and thus experience divergent selection, which can lead to local adaptation if migration is not strong enough to swamp locally adapted alleles. Conditions for the establishment of a locally advantageous allele have been studied in randomly mating populations. However, many species reproduce, at least partially, through self-fertilization, and how selfing affects local adaptation remains unclear and debated. Using a two-patch branching process formalism, we obtained a closed-form approximation under weak selection for the probability of establishment of a locally advantageous allele (P) for arbitrary selfing rate and dominance level, where selection is allowed to act on viability or fecundity, and migration can occur via seed or pollen dispersal. This solution is compared to diffusion approximation and used to investigate the consequences of a shift in a mating system on P, and the establishment of protected polymorphism. We find that selfing can either increase or decrease P, depending on the patterns of dominance in the two patches, and has conflicting effects on local adaptation. Globally, selfing favors local adaptation when locally advantageous alleles are (partially) recessive, when selection between patches is asymmetrical and when migration occurs through pollen rather than seed dispersal. These results establish a rigorous theoretical background to study heterogeneous selection and local adaptation in partially selfing species.

scholarly journals Trend detection of atmospheric time series

Elem Sci Anth ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Kai-Lan Chang ◽  
Martin G. Schultz ◽  
Xin Lan ◽  
Audra McClure-Begley ◽  
Irina Petropavlovskikh ◽  
...  
Keyword(s):  
Time Series ◽  
Atmospheric Chemistry ◽  
Surface Ozone ◽  
High Surface ◽  
Effective Means ◽  
Environmental Data ◽  
Model Specification ◽  
Trend Detection ◽  
Detection Methods ◽  
Sources Of Uncertainty

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to (1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry, (2) describe a range of trend-detection methods, and (3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short and long term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to (1) review trend detection methods for addressing different levels of data complexity in different chemical species, (2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability, (3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates, and (4) present an advanced method of quantifying regional trends based on the inter-site correlations of multisite data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

scholarly journals Survey techniques for determining distribution, abundance, and occupancy of the carnivore guild in the Apostle Islands National Lakeshore (2014-2017)

2018 ◽  
Author(s):  
Maximilian L Allen ◽  
Morgan J Morales ◽  
Mike Wheeler ◽  
John D Clare ◽  
Marcus Mueller ◽  
...  
Keyword(s):  
Negative Correlation ◽  
Community Dynamics ◽  
Temporal Dynamics ◽  
Camera Traps ◽  
Ecological Communities ◽  
Demographic Stochasticity ◽  
Red Foxes ◽  
Island Size ◽  
Detection Rates ◽  
Gray Wolves

Carnivores are important components of ecosystems with wide-ranging effects on ecological communities. These effects are complex and vary with carnivore size, natural history, and hunting tactics, and researchers and managers must understand the ecological roles of carnivores and their interactions with their local environment. We studied the carnivore guild in the Apostle Islands National Lakeshore (APIS), where the distribution, abundance, and occupancy of carnivores was largely unknown. This knowledge was needed to understand island-level variation in carnivore communities and how this variation affects the community-level ecology of APIS. We developed a systematic method to deploy a grid of camera traps while targeting fine-scale features to maximize carnivore detection and for organizing and tagging the resulting photograph data. In this report, we document our findings from deploying 160 camera traps on 19 islands and mainland Wisconsin from 2014-2017. We collected 203,385 photographs across 49,280 trap nights, with 7,291 total wildlife events and 1,970 carnivore events. We had a mean 7.68 functioning camera traps per island (range 1-30), and our camera trap density averaged 1.89 (range 0.75-12.50) camera traps/ km2. We detected 10 terrestrial carnivores among 21 unique species detected, including unanticipated detections of American martens (Martes americana) and gray wolves (Canis lupus). The mean richness of carnivores on an island was 3.10 (range 0-10) species/island. The most supported single variable to explain carnivore richness on the Apostle Islands was island size, while the most supported model was island biogeography, which included island size (positive correlation), distance to mainland (negative correlation), and distance to nearest island (negative correlation). The relative abundance of a species was significantly correlated with the number of islands on which they were found. Mean carnivore occupancy across islands ranged from 0.24 for gray wolves to a high of 0.93 for black bears (Ursus americanus). Detection rates for species were generally higher in summer than winter, with the exception of coyotes (Canis latrans) and red foxes (Vulpes vulpes). Low levels of human activity and development in APIS may play a role in supporting carnivore species that tend to avoid human disturbance. However, none of the islands in the archipelago are likely large enough to sustain populations of mammalian carnivores in the face of demographic stochasticity or the genetic effects of small population size. Therefore, one important area for future study is determining how carnivores colonize and move between islands, as well as how the carnivore guild interacts and affects each other. Fuller understanding of APIS ecology will require on-going monitoring of carnivores to evaluate temporal dynamics as well as related ecological evaluations (e.g. small mammal dynamics, plant community dynamics) to understand trophic effects.

scholarly journals Separate the wheat from the chaff: genomic scan for local adaptation in the red coralCorallium rubrum

2018 ◽  
Author(s):  
M. Pratlong ◽  
A. Haguenauer ◽  
K. Brener ◽  
G. Mitta ◽  
E. Toulza ◽  
...  
Keyword(s):  
Local Adaptation ◽  
Environmental Gradient ◽  
Environmental Gradients ◽  
High Rate ◽  
Corallium Rubrum ◽  
Red Coral ◽  
Geographical Regions ◽  
Adaptive Processes ◽  
Tests Of Association ◽  
Candidate Loci

ABSTRACTGenomic data allow an in-depth and renewed study of local adaptation. The red coral (Corallium rubrum, Cnidaria) is a highly genetically structured species and a promising model for the study of adaptive processes along an environmental gradient. Here, we used RAD-Sequencing in order to study the vertical genetic structure of this species and to search for signals of local adaptation to depth and thermal regime in the red coral. Previous studies have shown different thermotolerance levels according to depth in this species which could correspond to genetic or environmental differences. We designed a sampling scheme with six pairs of ‘shallow vs deep’ populations distributed in three geographical regions as replicates. Our results showed significant differentiation among locations and among sites separated by around 20 m depth. The tests of association between genetics and environment allowed the identification of candidate loci under selection but with a potentially high rate of false positive. We discuss the methodological obstacles and biases encountered for the detection of selected loci in such a strongly genetically structured species. On this basis, we also discuss the significance of the candidate loci for local adaptation detected in each geographical region and the evolution of red coral populations along environmental gradients.A colony of red coral,Corallium rubrum, near Marseille. Photo: F. Zuberer / OSU Pythéas / CNRS

scholarly journals Examining the relationships between phenotypic plasticity and local environments with genomic structural equation models

2019 ◽  
Author(s):  
Malachy T. Campbell ◽  
Haipeng Yu ◽  
Mehdi Momen ◽  
Gota Morota
Keyword(s):  
Local Adaptation ◽  
Environmental Conditions ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Common Garden ◽  
Local Environment ◽  
Equation Model ◽  
Environmental Data ◽  
Association Analyses ◽  
Common Qtl

AbstractEnvironmental association analyses (EAA) seek to identify genetic variants associated with local adaptation by regressing local environmental conditions at collection sites on genome-wide polymorphisms. The rationale is that environmental conditions impose selective pressure on trait(s), and these traits are regulated in part by variation at a genomic level. Here, we present an alternative multivariate genomic approach that can be utilized when both phenotypic and environmental data are available for the population. This framework utilizes Bayesian networks (BN) to elucidate interdependancies between local environmental conditions and empirical phenotypes, and jointly estimates the direct and indirect genetic covariances between empirical phenotypes and environmental conditions using a mixed-effects structural equation model (SEM). Direct genomic covariance between empirical phenotypes and environmental conditions may provide insight into whether QTL that affect adaptation to an environmental gradient also affects the observed phenotype. To demonstrate the utility of this approach, we leveraged two existing datasets consisting of 55 climate variables for 1,130 Arabidopsis accessions and empirical phenotypes for fitness and phenology collected on 515 accessions in two common garden locations in Europe. BN showed that plasticity for fitness and phenology was highly dependant on local environmental conditions. Moreover, genomic SEM revealed relatively high positive genomic correlation between plasticity in fitness and environmental variables that describe the favorability of the local environment for plant growth, indicating the presence of common QTL or independent QTL that are tightly linked. We believe the frameworks presented in this manuscript can provide new insights into the genetic basis of local adaptation.

scholarly journals The geography of parasite local adaptation to host communities

2021 ◽  
Author(s):  
Emily Bellis ◽  
Chloee McLaughlin ◽  
Claude DePamphilis ◽  
Jesse Lasky
Keyword(s):  
Local Adaptation ◽  
Crop Production ◽  
Scale Up ◽  
Spatial Dynamics ◽  
Host Community ◽  
Environmental Data ◽  
Striga Hermonthica ◽  
Combining Data ◽  
Local Host ◽  
Experimental Trials

Fitness responses to environment can shape species distributions, though opposing eco-evolutionary processes can obscure environmental effects. For example, host specificity influences parasite dynamics, but is unclear how adaptation of parasites to local host communities may scale up to continental distributions. Here, we develop a macroecological framework to determine how host community structure affects the distribution of specialist and generalist populations of Striga hermonthica, an African parasitic plant of cereal crops. Combining data from global crop production and parasite experimental trials, we find that parasites perform best on the host species that is most common in their location of origin. Moreover, niche model contrasts predict parasite specialization on two hosts that evolved alongside Striga during domestication (pearl millet and sorghum), indicating that specialist parasites may be most likely to occur where host niches differ most in multivariate environmental space.  Our study demonstrates that patterns of parasite local adaptation to host communities can emerge at continental scales and that differential environmental tolerances of hosts indirectly shape the distribution of specialist and generalist parasites.  By predicting spatial dynamics of parasite specialization versus generalization directly from environmental data, our approach may help inform current and future management of pests and disease.

Population differentiation in Pacific salmons: local adaptation genetic drift, or the environment?

1995 ◽  
Vol 52 (12) ◽  
pp. 2762-2777 ◽  
Author(s):  
Milo D. Adkison
Keyword(s):  
Local Adaptation ◽  
Genetic Drift ◽  
Pacific Salmon ◽  
Genetic Homogeneity ◽  
Biological Research ◽  
Weak Selection ◽  
Selective Pressures ◽  
Population Sizes ◽  
Founder Events ◽  
Stable Populations

Morphological, behavioral, and life-history differences between Pacific salmon (Oncorhynchus spp.) populations are commonly thought to reflect local adaptation, and it is likewise common to assume that salmon populations separated by small distances are locally adapted. Two alternatives to local adaptation exist: random genetic differentiation owing to genetic drift and founder events, and genetic homogeneity among populations, in which differences reflect differential trait expression in differing environments. Population genetics theory and simulations suggest that both alternatives are possible. With selectively neutral alleles, genetic drift can result in random differentiation despite many strays per generation. Even weak selection can prevent genetic drift in stable populations; however, founder effects can result in random differentiation despite selective pressures. Overlapping generations reduce the potential for random differentiation. Genetic homogeneity can occur despite differences in selective regimes when straying rates are high. In sum, localized differences in selection should not always result in local adaptation. Local adaptation is favored when population sizes are large and stable, selection is consistent over large areas, selective differentials are large, and straying rates are neither too high nor too low. Consideration of alternatives to adaptation would improve both biological research and salmon conservation efforts.

scholarly journals Hierarchical structure of ecological and non-ecological processes of differentiation shaped ongoing gastropod radiation in the Malawi Basin

2017 ◽  
Vol 284 (1862) ◽  
pp. 20171494 ◽  
Author(s):  
Bert Van Bocxlaer
Keyword(s):  
Reproductive Isolation ◽  
Hierarchical Structure ◽  
Large Scale ◽  
Environmental Data ◽  
Ecological Processes ◽  
Complex Interactions ◽  
Main Driver ◽  
Adaptive Processes ◽  
Adaptive Radiations ◽  
Evolutionary Radiations

Ecological processes, non-ecological processes or a combination of both may cause reproductive isolation and speciation, but their specific roles and potentially complex interactions in evolutionary radiations remain poorly understood, which defines a central knowledge gap at the interface of microevolution and macroevolution. Here I examine genome scans in combination with phenotypic and environmental data to disentangle how ecological and non-ecological processes contributed to population differentiation and speciation in an ongoing radiation of Lanistes gastropods from the Malawi Basin. I found a remarkable hierarchical structure of differentiation mechanisms in space and time: neutral and mutation-order processes are older and occur mainly between regions, whereas more recent adaptive processes are the main driver of genetic differentiation and reproductive isolation within regions. The strongest differentiation occurs between habitats and between regions, i.e. when ecological and non-ecological processes act synergistically. The structured occurrence of these processes based on the specific geographical setting and ecological opportunities strongly influenced the potential for evolutionary radiation. The results highlight the importance of interactions between various mechanisms of differentiation in evolutionary radiations, and suggest that non-ecological processes are important in adaptive radiations, including those of cichlids. Insight into such interactions is critical to understanding large-scale patterns of organismal diversity.

scholarly journals Wildfire early warning system based on wireless sensors and unmanned aerial vehicle

2019 ◽  
Vol 7 (1) ◽  
pp. 76-91 ◽  
Author(s):  
Songsheng Li
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Early Warning ◽  
Early Warning System ◽  
State Of The Art ◽  
Effective Means ◽  
Warning System ◽  
Environmental Data ◽  
Loss Of Life ◽  
Aerial Vehicle ◽  
Exchange Data

Wildfires erupt annually around the world causing serious loss of life and property damage. Despite the rapid progress of science and technology, there are no effective means to forecast wildfires. Various wildfire monitoring systems are deployed in different countries, most depend on photos or videos to identify features of wildfire after the first outbreak, while the delay of confirmation varies with technology. An autonomous forest wildfire early warning system is presented in this paper, which employs a state-of-the-art unmanned aerial vehicle (UAV) to fly around a forest regularly according to established routes and strict procedures, to collect environmental data from sensors installed on trees, to monitor and predict wildfire, then provide early warning before eruption if a danger emerges. Bluetooth Low Energy (BLE) is employed to exchange data between UAV and the host of sensors. The collected monitoring data, such as temperature and humidity, is effective to reflect the real condition of the forest, which could result in early warning of wildfires. The application of this system in the environment will enhance the ability of wildfire prediction for the community.

Mapping Invasive Plant Distributions in the Florida Everglades Using the Digital Aerial Sketch Mapping Technique

2014 ◽  
Vol 7 (2) ◽  
pp. 360-374 ◽  
Author(s):  
LeRoy Rodgers ◽  
Tony Pernas ◽  
Steven D. Hill
Keyword(s):  
Invasive Plants ◽  
Large Scale ◽  
Invasive Plant ◽  
Effective Means ◽  
Florida Everglades ◽  
Mapping Technique ◽  
Detection Accuracy ◽  
Positional Accuracy ◽  
Detection Rates ◽  
Old World

AbstractThe management of exotic, invasive plants is among the most challenging undertakings of natural resource managers, particularly in large, remote landscapes. The availability of information on the distribution and abundance of invasive plants is vital for effective strategic planning yet is often unavailable because of high costs and long procurement times. This paper presents results of a large-scale invasive plant mapping effort in the Florida Everglades utilizing digital aerial sketch mapping (DASM) and evaluates its utility for guiding management decisions. The distribution and abundance (cover) of four priority invasive plant species—Australian pine, Brazilian pepper, melaleuca, and Old World climbing fern—were mapped over 728,000 ha in the Everglades during 2010 to 2012. Brazilian peppertree was the most widely distributed and abundant species, occupying 30,379 ha. Melaleuca was also widely distributed and occupied 17,802 ha. Old World climbing fern occupied only 7,033 ha but its distribution was generally concentrated in heavy infestations in the northern Everglades. Australian pine was the least abundant of the mapped species and tended to be limited to the southeastern Everglades region. DASM proved to be a cost-effective means of obtaining region-wide distribution and abundance information for these species at broad scales (> 500 m), but detection rates and positional accuracy declined at finer scales. Both canopy type (forested vs. unforested) and distance from flight transect appear to be important factors for detection accuracy.

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