Population Ecology Model Research Articles

Assessing the invasive potential of different source populations of ragweed (Ambrosia artemisiifolia L.) through genomically informed species distribution modelling.

The genetic composition of founding populations is likely to play a key role in determining invasion success. Individual genotypes may differ in habitat preference and environmental tolerance, so their ability to colonize novel environments can be highly variable. Despite the importance of genetic variation on invasion success, its influence on the potential distribution of invaders is rarely investigated. Here, we integrate population genomics and ecological niche models (ENMs) into a single framework to predict the distribution of globally invasive common ragweed (Ambrosia artemisiifolia) in Australia. We identified three genetic clusters for ragweed and used these to construct cluster-specific ENMs and characterize within-species niche differentiation. The potential range of ragweed in Australia depended on the genetic composition and continent of origin of the introduced population. Invaders originating from warmer, wetter climates had a broader potential distribution than those from cooler, drier ones. By quantifying this change, we identified source populations most likely to expand the ragweed distribution. As prevention remains the most effective method of invasive species management, our work provides a valuable way of ranking the threat posed by different populations to better inform management decisions.

Modeling emergence of Wolbachia toxin-antidote protein functions with an evolutionary algorithm.

Evolutionary algorithms (EAs) simulate Darwinian evolution and adeptly mimic natural evolution. Most EA applications in biology encode high levels of abstraction in top-down population ecology models. In contrast, our research merges protein alignment algorithms from bioinformatics into codon based EAs that simulate molecular protein string evolution from the bottom up. We apply our EA to reconcile a problem in the field of Wolbachia induced cytoplasmic incompatibility (CI). Wolbachia is a microbial endosymbiont that lives inside insect cells. CI is conditional insect sterility that operates as a toxin antidote (TA) system. Although, CI exhibits complex phenotypes not fully explained under a single discrete model. We instantiate in-silico genes that control CI, CI factors (cifs), as strings within the EA chromosome. We monitor the evolution of their enzymatic activity, binding, and cellular localization by applying selective pressure on their primary amino acid strings. Our model helps rationalize why two distinct mechanisms of CI induction might coexist in nature. We find that nuclear localization signals (NLS) and Type IV secretion system signals (T4SS) are of low complexity and evolve fast, whereas binding interactions have intermediate complexity, and enzymatic activity is the most complex. Our model predicts that as ancestral TA systems evolve into eukaryotic CI systems, the placement of NLS or T4SS signals can stochastically vary, imparting effects that might impact CI induction mechanics. Our model highlights how preconditions and sequence length can bias evolution of cifs toward one mechanism or another.

Out of East Asia: Early Warning of the Possible Invasion of the Important Bean Pest Stalk-Eyed Seed Bug Chauliops fallax (Heteroptera: Malcidae: Chauliopinae)

The short stay at the beginning of the invasion process is a critical time for invasive species identification and preventing invasive species from developing a wider distribution and significant economic impact. The stalk-eyed seed bug Chauliops fallax is an important agricultural pest of soybean and was first reported to occur outside East Asia. Here, we reported the native evolutionary history, recent invasion history, and potential invasion threats of C. fallax for the first time based on population genetic methods and ecological niche modelling. The results showed that four native East Asian genetic groups (EA, WE, TL, and XZ) were well supported, showing an east-west differentiation pattern consistent with the geographical characteristics of three-step landforms in China. Two main haplotypes existed: Hap1 might have experienced a rapid northwards expansion process after the LGM period, and Hap5 reflected local adaptation to the environment in southeastern China. The Kashmir sample was found to come from the recent invasion of populations in the coastal areas of southern China. Ecological niche modelling results suggested that North America has a high risk of invasion, which might pose a serious threat to local soybean production. In addition, with future global warming, the suitable habitat in Asia will move towards the higher latitude region and gradually deviate from the soybean planting area, which indicates the threat of C. fallax to soybean production in Asia will decrease in the future. The results could provide new insights into the monitoring and management of this agricultural pest in the early invasion stage.

Global maps of lake surface water temperatures reveal pitfalls of air‐for‐water substitutions in ecological prediction

In modeling species distributions and population dynamics, spatially‐interpolated climatic data are often used as proxies for real, on‐the‐ground measurements. For shallow freshwater systems, this practice may be problematic as interpolations used for surface waters are generated from terrestrial sensor networks measuring air temperatures. Using these may therefore bias statistical estimates of species' environmental tolerances or population projections – particularly among pleustonic and epilimnetic organisms. Using a global database of millions of daily satellite‐derived lake surface water temperatures (LSWT), I trained machine learning models to correct for the correspondence between air and LSWT as a function of atmospheric and topographic predictors, resulting in the creation of monthly high‐resolution global maps of air‐LSWT offsets, corresponding uncertainty measures and derived LSWT‐based bioclimatic layers for use by the scientific community. I then compared the performance of these LSWT layers and air temperature‐based layers in population dynamic and ecological niche models (ENM). While generally high, the correspondence between air temperature and LSWT was quite variable and often nonlinear depending on the spatial context. These LSWT predictions were better able to capture the modeled population dynamics and geographic distributions of two common aquatic plant species. Further, ENM models trained with LSWT predictors more accurately captured lab‐measured thermal response curves. I conclude that these predicted LSWT temperatures perform better than raw air temperatures when used for population projections and environmental niche modeling, and should be used by practitioners to derive more biologically‐meaningful results. These global LSWT predictions and corresponding error estimates and bioclimatic layers have been made freely available to all researchers in a permanent archive.

Differentiated historical demography and ecological niche forming present distribution and genetic structure in coexisting two salamanders (Amphibia, Urodela, Hynobiidae) in a small island, Japan.

BackgroundThe climatic oscillations in the Quaternary period considerably shaped the distribution and population genetic structure of organisms. Studies on the historical dynamics of distribution and demography not only reflect the current geographic distribution but also allow us to understand the adaption and genetic differentiation of species. However, the process and factors affecting the present distribution and genetic structure of many taxa are still poorly understood, especially for endemic organisms to small islands.MethodsHere, we integrated population genetic and ecological niche modelling approaches to investigate the historical distribution and demographic dynamics of two co-existing salamanders on Tsushima Island, Japan: the true H. tsuensis (Group A), and Hynobius sp. (Group B). We also examined the hypothesis on the equivalency and similarity of niches of these groups by identity and background tests for ecological niche space.ResultsOur result showed that Group A is considered to have undergone a recent population expansion after the Last Glacial Maximum while it is unlikely to have occurred in Group B. The highest suitability was predicted for Group A in southern Tsushima Island, whereas the northern part of Tsushima Island was the potential distribution of Group B. The results also suggested a restricted range of both salamanders during the Last Interglacial and Last Glacial Maximum, and recent expansion in Mid-Holocene. The genetic landscape-shape interpolation analysis and historical suitable area of ecological niche modelling were consistent, and suggested refugia used during glacial ages in southern part for Group A, and in northern part of Tsushima Island for Group B. Additionally, we found evidence of nonequivalence for the ecological niche of the two groups of the salamanders, although our test could not show either niche divergence or conservatism based on the background tests. The environmental predictors affecting the potential distribution of each group also showed distinctiveness, leading to differences in selecting suitable areas. Finally, the combination of population genetics and ecological modeling has revealed the differential demographic/historical response between coexisting two salamanders on a small island.

The effects of energy price, spatial spillover of CO2 emissions, and economic freedom on CO2 emissions in Europe: a spatial econometrics approach.

Since the European Union (EU)'s current goal of making its continent the world's first climate-neutral continent by 2050, the EU will need to set a path for new policies in the areas of Europe's economy, energy consumption, and agriculture. Thus, this paper analyzes the marginal impact of energy price and economic freedom on Europe's CO2 emissions grounded on the extended Stochastic Impacts by Regression on Population, Affluence and Technology ecology (STIRPAT) model together with the spatial econometric models. The results indicate the existence of spatial spillover effect of CO2 emissions among some countries in Europe. The Hausman test was also performed to select the best model between the random effects and the fixed effects. The findings suggest that increasing both economic freedom and energy price in a local country turns to reduce the country's own CO2 emissions and also reduces the emissions of its adjacent countries. Comparing the direct effect of economic freedom and energy price to that of the SDM fixed effect, a feedback of 12.77% and 23.53% of the direct effect was observed, respectively. The results also indicated that the turning point of economic freedom and economic growth was 6.714 and thus 9.083. Overall, the study spotlighted some policy suggestions for the energy market for the European commission in reducing the emissions of CO2.

The long-term effect of over-supplementation on recovered populations: why restraint is a virtue

AbstractWe present a long-term analysis of the results of the Apollo butterflyParnassius apollorecovery project in the Pieniny National Park, southern Poland, using a classical population ecology model. Six possible theoretical models of changes in population abundance were constructed and their predictions compared with current data. Models that did not take into account supplementation with captive-reared individuals provided the best fit to the population growth pattern during recovery. This was probably because of the introduction of captive-reared specimens to sites while habitat reconstruction was taking place. In addition, we provide data supporting the hypothesis that a significant reduction in the habitat's carrying capacity occurred during the restoration project, probably as a result of the population being over-supplemented with captive-reared individuals. Our analysis shows that for a recovery project to be successful, captive breeding and habitat restoration should be properly coordinated.

Inter-glacial isolation caused divergence of cold-adapted species: the case of the snow partridge.

Deciphering the role of climatic oscillations in species divergence helps us understand the mechanisms that shape global biodiversity. The cold-adapted species may have expanded their distribution with the development of glaciers during glacial period. With the retreat of glaciers, these species were discontinuously distributed in the high-altitude mountains and isolated by geographical barriers. However, the study that focuses on the speciation process of cold-adapted species is scant. To fill this gap, we combined population genetic data and ecological niche models (ENMs) to explore divergence process of snow partridge (Lerwa lerwa). Lerwa lerwa is a cold-adapted bird that is distributed from 4,000 to 5,500 m. We found 2 genetic populations within L. lerwa, and they diverged from each other at about 0.40–0.44 million years ago (inter-glacial period after Zhongliangan glaciation). The ENMs suggested that L. lerwa expanded to the low elevations of the Himalayas and Hengduan mountains during glacial period, whereas it contracted to the high elevations, southern of Himalayas, and Hengduan mountains during inter-glacial periods. Effective population size trajectory also suggested that L. lerwa expanded its population size during the glacial period. Consistent with our expectation, the results support that inter-glacial isolation contributed to the divergence of cold-adapted L. lerwa on Qinghai-Tibetan Plateau. This study deepens our understanding of how climatic oscillations have driven divergence process of cold-adapted Phasianidae species distributed on mountains.

Integrating Hierarchical Statistical Models and Machine-Learning Algorithms for Ground-Truthing Drone Images of the Vegetation: Taxonomy, Abundance and Population Ecological Models

In order to fit population ecological models, e.g., plant competition models, to new drone-aided image data, we need to develop statistical models that may take the new type of measurement uncertainty when applying machine-learning algorithms into account and quantify its importance for statistical inferences and ecological predictions. Here, it is proposed to quantify the uncertainty and bias of image predicted plant taxonomy and abundance in a hierarchical statistical model that is linked to ground-truth data obtained by the pin-point method. It is critical that the error rate in the species identification process is minimized when the image data are fitted to the population ecological models, and several avenues for reaching this objective are discussed. The outlined method to statistically model known sources of uncertainty when applying machine-learning algorithms may be relevant for other applied scientific disciplines.

Modelling the network economy: A population ecology perspective on network dynamics

Network platforms are increasingly important in current economic ecosystems. With industries, platforms and organizations integrating in many directions, the difficulties of defining the boundaries of organizational populations increase. Although population ecologists have frequently applied legitimation and competition mechanisms to analyze inside the organizational population, there is little understanding of the transition of such mechanisms across populations and whether competition mechanisms vary in mixed populations. This paper therefore builds on recent work in community ecology and proposes a Platform System Dependence Model, which involves a re-specification of these mechanisms and offers a theoretical framework that is suitable for heterogeneous organizational populations and sufficiently adapted to the dynamic nature of the network economy. Furthermore, in order to describe and analyze how different organizational populations interact within the ecosystem, we expand traditional population and community ecology models to time-related differential equations. This change makes it possible to perform a comprehensive density-trend analysis that can be applied within and across different categories of populations. We furthermore offer a simulation based on this framework, which supports the thesis that the density of a symbiotic organizational population and a competitive organizational population increases rapidly in the initial stage of organizational population growth, while, at the same time, the platform-based organizational population increases gradually. As the density of a symbiotic population decreases and the competitive population density remains stable, the density of the platform-based organizational population decreases after reaching its maximum. We discuss the implications of these findings for research on ecology and on the platform economy.

When phylogeography meets niche suitability to unravel the evolutionary history of a shrub from the Brazilian Atlantic Forest

Abstract The Brazilian Atlantic Forest (BAF) is one of the most impacted biomes in the world, and in this region, there are several examples of the effects of Pleistocene climate changes among the species found there. Athenaea fasciculata (Solanaceae) is a forest component distributed mainly throughout the BAF extension. Here, we investigated the genetic diversity and population structure of A. fasciculata based on plastid and nuclear markers, aiming to better understand the impact of Pleistocene climate changes on BAF vegetation. We used population genetics, demographic methods and ecological niche modelling coupled to an evolutionary approach to describe the species distribution across time. The phylogeographic analysis of A. fasciculata indicated that Pleistocene climate changes played an important role in its evolution. The species is structured in two groups of populations that emerged from different refugia and were under different climate influences, supporting previously proposed connections between the Atlantic and Amazon Forests, the two most important Neotropical rainforests.

Pilar Catalán.

Pilar Catalán.

Genetic structure of the endemic Papaver occidentale indicates survival and immigration in the Western Prealps

Climatic oscillations of the Quaternary rapidly compelled plant species to shift their geographical range. How alpine plant species responded to climate change, however, remains elusive and remnants of the cold-adapted flora that currently strive in restricted ranges as small, isolated populations have been particularly overlooked. To address the evolutionary history of such a ‘glacial relict’, we here sampled and genotyped all known native populations of a narrow endemic species from the northwestern Alps, Papaver occidentale, as well as closely related taxa with double digest restriction-site Associated DNA (ddRAD) sequencing. Spatial patterns of genetic variation across populations coupled with insights from climatic niche modelling through time address underpinings of the long-term persistence of the species in face of climate changes. Evidence from population genetics and ecological modelling indicates that P. occidentale likely persisted through the last glacial maximum outside of the Western Prealps and that a major lineage recolonized the area from lower elevation, external regions. Differentiated lineages at the Northern margins of the species distribution range highlight highly divergent and geographically restricted populations that include considerable share of private markers and may indicate local glacial survival in isolated conditions. Our data thus imply that processes having shaped intraspecific spatial genetic structure within the Alps can be complex and lead to mosaic of populations with a mixed-history of local survival and immigration. A better understanding of spatio-temporal aspects of range contraction–expansion is crucial to shed light on processes underlying the evolution of remnant populations of such endemic species and set conservation priorities considering current climate changes.

Cryptic speciation in gentoo penguins is driven by geographic isolation and regional marine conditions: Unforeseen vulnerabilities to global change

AbstractAimThe conservation of biodiversity is hampered by data deficiencies, with many new species and subspecies awaiting description or reclassification. Population genomics and ecological niche modelling offer complementary new tools for uncovering functional units of phylogenetic diversity. We hypothesize that phylogenetically delineated lineages of gentoo penguins (Pygoscelis papua) distributed across Antarctica and sub‐Antarctic Islands are subject to spatially explicit ecological conditions that have limited gene flow, facilitating genetic differentiation, and thereby speciation processes.LocationAntarctica and sub‐Antarctic area.MethodsWe identify divergent lineages for gentoo penguins using ddRAD‐seq and mtDNA, and generated species distribution models (SDMs) based on terrestrial and marine parameters.ResultsAnalyses of our genomic data supports the existence of four major lineages of gentoo penguin: (i) spanning the sub‐Antarctic archipelagos north of the Antarctic Polar Front (APF); (ii) Kerguelen Island; (iii) South America; and (iv) across maritime Antarctic and the Scotia Arc archipelagos. The APF, a major current system around Antarctica, acts as the most important barrier separating regional sister lineages. Our ecological analyses spanning both the terrestrial (breeding sites) and marine (feeding sites) realms recover limited niche overlap among the major lineages of gentoo penguin. We observe this pattern to correspond more closely with regional differentiation of marine conditions than to terrestrial macroenvironmental features.Main conclusionsRecognition of regional genetic lineages as discrete evolutionary entities that occupy distinct ecological niches and also differ morphologically should be considered a priority for conservation. Gentoo penguins provide a good example of how conservation policy can be directly impacted by new insights obtained through the integration of larger genomic datasets with novel approaches to ecological modelling. This is particularly pertinent to polar environments that are among the most rapidly changing environments on earth.

Consequences of ignoring group association in spatial capture–recapture analysis

Many models in population ecology, including spatial capture–recapture (SCR) models, assume that individuals are distributed and detected independently of one another. In reality, this is rarely the case – both antagonistic and gregarious relationships lead to non-independent spatial configurations, with territorial exclusion at one end of the spectrum and group-living at the other. Previous simulation studies suggest that grouping has limited impact on the outcome of SCR analyses. However, group associations entail not only spatial clustering of activity centers but also coordinated space use by group members, potentially impacting both ecological and observation processes underlying SCR analysis. We simulated SCR scenarios with different strengths of aggregation (clustering of individuals into groups with shared activity centers) and cohesion (synchronization of detection patterns of members of a group). We then fit SCR models to the simulated data sets and evaluated the effect of aggregation and cohesion on parameter estimates. Low to moderate aggregation and cohesion did not impact the bias and precision of estimates of density and the scale parameter of the detection function. However, non-independence between individuals led to high levels of overdispersion. Overdispersion strongly decreased the coverage of confidence intervals around parameter estimates, thereby increasing the probability of erroneous predictions. Our results indicate that SCR models are robust to moderate levels of aggregation and cohesion. Nonetheless, spatial dependence between individuals can lead to false inference. We recommend that practitioners 1) test for the presence of overdispersion in SCR data caused by aggregation and cohesion, and, if necessary, 2) correct their variance estimates using the overdispersion factor ĉ . Approaches for doing both are described in this paper. We also urge the development of SCR models that incorporate spatial associations between individuals not only to account for overdispersion but also to obtain quantitative information about social aspects of study populations.

Prospecting the enablers for adoption of e-recruitment practices in organisations: a proposed framework

The purpose of this paper is to provide a framework to understand and predict factors affecting the adoption of e-recruitment practices in organisations. By drawing up theoretical knowledge in human resource management (HRM) and information technology (IT), a framework is developed that delineates the enablers and outcome for the adoption of e-recruitment. It was quite interesting to introduce the population ecology model as the underpinning theory. The authors have identified following enablers of e-recruitment: - environmental factors, cost and time reduction, applicant pool, employer branding and ease of use for applicants and organisations. However, applicant attraction is figured out as one of the vital outcomes of e-recruitment. This study would contribute to the conceptualisation of e-recruitment. Managers may take up the mentioned ideas to develop innovative e-recruitment strategies for attracting future workforce and enhance organisational performance. We have suggested several directions for future research that provides a platform for further exploration.

Prospecting the enablers for adoption of e-recruitment practices in organisations: a proposed framework

The purpose of this paper is to provide a framework to understand and predict factors affecting the adoption of e-recruitment practices in organisations. By drawing up theoretical knowledge in human resource management (HRM) and information technology (IT), a framework is developed that delineates the enablers and outcome for the adoption of e-recruitment. It was quite interesting to introduce the population ecology model as the underpinning theory. The authors have identified following enablers of e-recruitment: - environmental factors, cost and time reduction, applicant pool, employer branding and ease of use for applicants and organisations. However, applicant attraction is figured out as one of the vital outcomes of e-recruitment. This study would contribute to the conceptualisation of e-recruitment. Managers may take up the mentioned ideas to develop innovative e-recruitment strategies for attracting future workforce and enhance organisational performance. We have suggested several directions for future research that provides a platform for further exploration.

Spatiotemporal dynamics of prehistoric human population growth: Radiocarbon ‘dates as data’ and population ecology models

Archaeologists now routinely use summed radiocarbon dates as a measure of past population size, yet few have coupled these measures to theoretical expectations about social organization. To help move the ‘dates as data’ approach from description to explanation, this paper proposes a new integrative theory and method for quantitative analyses of radiocarbon summed probability distributions (SPDs) in space. We present this new approach to ‘SPDs in space’ with a case study of 3571 geo-referenced radiocarbon dates from Wyoming, USA. We develop a SPD for the Holocene in Wyoming, then analyze the spatial distribution of the SPD as a function of time using a standard nearest-neighbor statistic. We compare population growth and decline throughout the Holocene with expectations for different Ideal Distribution Models from population ecology that predict the relationship between habitat quality and population density. Results suggest that populations in Wyoming were initially clustered and then became increasingly dispersed through the course of the Holocene. These results suggest that Allee-like benefits to aggregation, rather than ideal free-driven dispersion patterns, explain settlement decisions in response to growing populations. Our approach is a first step in constructing a method and theory for describing relationships between social organization and population growth trends derived from archaeological radiocarbon time-series.

Population Assessment and Ecological Niche Modelling of Carpinus Viminea Wall. ex Lindl. A Multipurpose Tree for Conservation in the Indian Himalayan Region

Population Assessment and Ecological Niche Modelling of Carpinus Viminea Wall. ex Lindl. A Multipurpose Tree for Conservation in the Indian Himalayan Region

Evolution model with time lag effects for the coal industrial symbiosis system: A case study of Ordos, China

Abstract Industrial metabolism and symbiotic coupling has become the base paradigm of green, low-carbon development of coal mining. In the coal industrial symbiosis system (CISS), stability is increasingly fragile because of its unique industrial links and growth environment. Referring to the classic Lotka-Volterra population ecology model, and synthesizing the periodicity and time lag effects of industrial development, two entirely novel and more generalized CISS evolution models with time lag effects in the competitive and reciprocal scenarios are constructed respectively. Moreover, the conditions of CISS stability are proven and discussed through mathematical analysis. Simulation and theorem validation were carried out by taking the largest Chinese coal city, Ordos, as the research object. The main results are as follows. First, the time lag effect is an important factor leading to CISS instability. The shorter the time lag within the CISS, the better the collaboration between industries, and the easier it is that the CISS will achieve a stable ecological balance. Second, when the power of competition dominates, the development of industries within CISS will be inhibited; when the power of cooperation dominates, the evolution of CISS will toward a positive direction. Third, a certain degree of self-inhibition will contribute to the stable development of the industrial symbiosis system. At last, the social service industry not only can boost the industrial diversity within CISS, but also can promote the co-evolution of original and exogenous industries, which plays a positive role in the healthy and stable development of CISS.