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DNA-based species delimitation may be compromised by limited sampling effort and species rarity, including \"singleton\" representatives of species, which hampers estimates of intra-versus interspecies evolutionary processes. In a case study of southern African chafers (beetles in the family Scarabaeidae), many species and subclades were poorly represented and 48.5% of species were singletons. Using cox1 sequences from >500 specimens and ~100 species, the Generalized Mixed Yule Coalescent (GMYC) analysis as well as various other approaches for DNA-based species delimitation (Automatic Barcode Gap Discovery (ABGD), Poisson tree processes (PTP), Species Identifier, Statistical Parsimony), frequently produced poor results if analyzing a narrow target group only, but the performance improved when several subclades were combined. Hence, low sampling may be compensated for by \"clade addition\" of lineages outside of the focal group. Similar findings were obtained in reanalysis of published data sets of taxonomically poorly known species assemblages of insects from Madagascar. The low performance of undersampled trees is not due to high proportions of singletons per se, as shown in simulations (with 13%, 40% and 52% singletons). However, the GMYC method was highly sensitive to variable effective population size (Ne), which was exacerbated by variable species abundances in the simulations. Hence, low sampling success and rarity of species affect the power of the GMYC method only if they reflect great differences in Ne among species. Potential negative effects of skewed species abundances and prevalence of singletons are ultimately an issue about the variation in Ne and the degree to which this is correlated with the census population size and sampling success. Clade addition beyond a limited study group can overcome poor sampling for the GMYC method in particular under variable Ne. This effect was less pronounced for methods of species delimitation not based on coalescent models.

Effective population size is a fundamental parameter in population genetics, evolutionary biology, and conservation biology, yet its estimation can be fraught with difficulties. Several methods to estimate Ne from genetic data have been developed that take advantage of various approaches for inferring Ne. The ability of these methods to accurately estimate Ne, however, has not been comprehensively examined. In this study, we employ seven of the most cited methods for estimating Ne from genetic data (Colony2, CoNe, Estim, MLNe, ONeSAMP, TMVP, and NeEstimator including LDNe) across simulated datasets with populations experiencing migration or no migration. The simulated population demographies are an isolated population with no immigration, an island model metapopulation with a sink population receiving immigrants, and an isolation by distance stepping stone model of populations. We find considerable variance in performance of these methods, both within and across demographic scenarios, with some methods performing very poorly. The most accurate estimates of Ne can be obtained by using LDNe, MLNe, or TMVP; however each of these approaches is outperformed by another in differing demographic scenario. Knowledge of the approximate demography of population as well as the availability of temporal data largely improves Ne estimates.

Frequency-dependent selection and demographic fluctuations play important roles in evolutionary and ecological processes. Under frequency-dependent selection, the average fitness of the population may increase or decrease based on interactions between individuals within the population. This should be reflected in fluctuations of the population size even in constant environments. Here, we propose a stochastic model that naturally combines these two evolutionary ingredients by assuming frequency-dependent competition between different types in an individual-based model. In contrast to previous game theoretic models, the carrying capacity of the population, and thus the population size, is determined by pairwise competition of individuals mediated by evolutionary games and demographic stochasticity. In the limit of infinite population size, the averaged stochastic dynamics is captured by deterministic competitive Lotka–Volterra equations. In small populations, demographic stochasticity may instead lead to the extinction of the entire population. Because the population size is driven by fitness in evolutionary games, a population of cooperators is less prone to go extinct than a population of defectors, whereas in the usual systems of fixed size the population would thrive regardless of its average payoff. This contribution breaks with the tradition to restrict stochastic evolutionary game dynamics to populations of constant size and introduces a theoretical framework to investigate relevant and natural changes arising in populations that vary in size according to fitness—a feature common to many real biological systems. Explicitly including ecological variation can result in significant effects on the stochastic evolutionary trajectories while providing a transparent link to the established, deterministic Lotka–Volterra systems.

Fragmentation of animal and plant populations typically leads to genetic erosion and increased probability of extirpation. Although these effects can usually be reversed by re-establishing gene flow between population fragments, managers sometimes fail to do so due to fears of outbreeding depression (OD). Rapid development of OD is due primarily to adaptive differentiation from selection or fixation of chromosomal variants. Fixed chromosomal variants can be detected empirically. We used an extended form of the breeders' equation to predict the probability of OD due to adaptive differentiation between recently isolated population fragments as a function of intensity of selection, genetic diversity, effective population sizes, and generations of isolation. Empirical data indicated that populations in similar environments had not developed OD even after thousands of generations of isolation. To predict the probability of OD, we developed a decision tree that was based on the four variables from the breeders' equation, taxonomic status, and gene flow within the last 500 years. The predicted probability of OD in crosses between two populations is elevated when the populations have at least one of the following characteristics: are distinct species, have fixed chromosomal differences, exchanged no genes in the last 500 years, or inhabit different environments. Conversely, the predicted probability of OD in crosses between two populations of the same species is low for populations with the same karyotype, isolated for <500 years, and that occupy similar environments. In the former case, we recommend crossing be avoided or tried on a limited, experimental basis. In the latter case, crossing can be carried out with low probability of OD. We used crosses with known results to test the decision tree and found that it correctly identified cases where OD occurred. Current concerns about OD in recently fragmented populations are almost certainly excessive. La fragmentación de poblaciones animales y vegetales típicamente lleva a la erosión genética y al incremento de la probabilidad de extirpación. Aunque estos efectos generalmente se pueden revertir mediante el restablecimiento del flujo genético entre los fragmentos de poblaciones, los manejadores a veces fallan debido al temor a la depresión exogámica (DEX). El rápido desarrollo de la DEX se debe principalmente a la diferenciación adaptativa de la selección o fijación de variantes cromosómicas. Las variantes cromosómicas fijadas pueden ser detectadas empíricamente. Utilizamos una forma extendida de la ecuación de criadores para predecir la probabilidad de DEX debido a la diferenciación adaptativa entre fragmentos de poblaciones aisladas recientemente como una función de la intensidad de selección, la diversidad genética, el tamaño poblacional efectivo y las generaciones en aislamiento. Los datos empíricos indicaron que poblaciones en ambientes similares no habían desarrollado DEX aun después de mil generaciones en aislamiento. Para predecir la probabilidad de DEX, desarrollamos un árbol dedecisiones basado en las 4 variables de la ecuación de criadores, el estatus taxonómico y el flujo génico durante los últimos 500 años. La probabilidad predicha de DEX es alta en cruzas entre dos poblaciones cuando las poblaciones tienen por lo menos una de las siguientes características: son especies diferentes, tienen diferencias en cromosomas fijados, no intercambiaron genes durante los últimos 500 años o habitan en ambientes diferentes. Por el contrario, la probabilidad predicha de DEX es baja en cruzas entre dos poblacionesde la misma especie cuando las poblaciones tienen el mismo cariotipo, han estado aisladas por <500 años y ocupan ambientes similares. En el primer caso, recomendamos evitar la cruza o probarla en un nivel limitado, experimental. En el segundo caso, la cruza puede llevarse a cabo con baja probabilidad de DEX. Utilizamos cruzas con resultados conocidos para probar el árbol de decisiones y encontramos que este identifico casos correctamente cuando ocurrió DEX. Las preocupaciones actuales sobre DEX en poblaciones fragmentadas recientemente con toda seguridad son excesivas.

In China, urbanization has been rapidly developing since the country began its economic reform in 1978. With the expansion of the urban population size and the corresponding urbanization and industrialization, the rapid increase in CO 2 emissions has become a major restraint on China’s economic growth. However, current studies have not paid sufficient attention to the impact of the urban population size on CO 2 emissions in China due to poor data availability. In this paper, we apply index decomposition analysis (IDA) to decompose CO 2 emissions into five elements, and we investigate both the direct and indirect impacts of the urban population size on total CO 2 emissions and per capita CO 2 emissions in China. Additionally, we empirically study the impact on 175 Chinese cities at the prefecture level and above for the first time. The results show that the urban population size significantly promotes total CO 2 emissions but curbs per capita CO 2 emissions in cities in China. A 1% increase in the urban population size will lead to a nearly 1% increase in total CO 2 emissions and a 0.3% decrease in per capita CO 2 emissions. Regarding heterogeneity, the expansion of the urban population size in the large city group drives a greater increase in CO 2 emissions than the expansion of the urban population size in other city groups. The main transmission pathways are through population density, economic agglomeration and energy intensity. Regarding the mechanism variables, high economic agglomeration leads to more CO 2 emissions, while an increase in population density and energy efficiency results in carbon mitigation. Moreover, public green areas, foreign direct investment (FDI) and technology innovation are conducive to reducing CO 2 emissions.

Approximately 50 ka, one or more subgroups of modern humans expanded from Africa to populate the rest of the world. Significant behavioral change accompanied this expansion, and archaeologists commonly seek its roots in the African Middle Stone Age (MSA; ∼200 to ∼50 ka). Easily recognizable art objects and “jewelry” become common only in sites that postdate the MSA in Africa and Eurasia, but some MSA sites contain possible precursors, especially including abstractly incised fragments of ocher and perforated shells interpreted as beads. These proposed art objects have convinced most specialists that MSA people were behaviorally (cognitively) modern, and many argue that population growth explains the appearance of art in the MSA and its post-MSA florescence. The average size of rocky intertidal gastropod species in MSA and later coastal middens allows a test of this idea, because smaller size implies more intense collection, and more intense collection is most readily attributed to growth in the number of human collectors. Here we demonstrate that economically important Cape turban shells and limpets from MSA layers along the south and west coasts of South Africa are consistently and significantly larger than turban shells and limpets in succeeding Later Stone Age (LSA) layers that formed under equivalent environmental conditions. We conclude that whatever cognitive capacity precocious MSA artifacts imply, it was not associated with human population growth. MSA populations remained consistently small by LSA standards, and a substantial increase in population size is obvious only near the MSA/LSA transition, when it is dramatically reflected in the Out-of-Africa expansion.

Applications of genetic-based estimates of population size are expanding, especially for species for which traditional demographic estimation methods are intractable due to the rarity of adult encounters. Estimates of breeding population size (𝑁𝑆) are particularly amenable to genetic-based approaches as the parameter can be estimated using pedigrees reconstructed from genetic data gathered from discrete juvenile cohorts, therefore eliminating the need to sample adults in the population. However, a critical evaluation of how genotyping and sampling effort influence bias in pedigree reconstruction, and how these biases subsequently influence estimates of 𝑁𝑆, is needed to evaluate the efficacy of the approach under a range of scenarios. We simulated a model system to understand the interactive effects of genotyping and sampling effort on error in genetic pedigrees reconstructed from the program COLONY. We then evaluated how errors in pedigree reconstruction influenced bias and precision in estimates of 𝑁𝑆 using three different rarefaction estimators. Results indicated that pedigree error can be minimal when adequate genetic data are available, such as when juvenile sample sizes are large and/or individuals are genotyped at many informative loci. However, even in cases for which data are limited, using results of the simulation analysis to understand the magnitude and sources of bias in reconstructed pedigrees can still be informative when estimating 𝑁𝑆. We applied results of the simulation analysis to evaluate 𝑁𝑆 for a population of federally endangered Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) in the Delaware River, USA. Our results indicated that 𝑁𝑆 is likely to be three orders of magnitude lower compared with historic breeding population sizes, which is a considerable advancement in our understanding of the population status of Atlantic sturgeon in the Delaware River. Our analyses are broadly applicable in the design and interpretation of studies seeking to estimate 𝑁𝑆 and can help to guide conservation decisions when ecological uncertainty is high. The utility of these results is expected to grow as rapid advances in genetic technologies increase the popularity of genetic population monitoring and estimation.

AIM: (1) To characterize the relationship(s) between species richness and area for alien plant and bird species on islands, and to identify commonalities and differences in those relationships for these different taxa, and between alien and native species; (2) to test whether area per se, native species richness or human factors related to area is the primary determinant of alien species richness; and (3) to explore the effects on alien island biogeography of isolation, productivity and the time since first European landfall. LOCATION: Islands around the world. METHODS: We used structural equation models (SEMs; supported by generalized linear models) to interrogate data on the alien and native species richness of birds and plants on islands. RESULTS: Alien plant and bird species richness were both strongly correlated with island area, with similar slopes on logarithmic axes. SEMs for both plants and birds revealed positive direct effects of native species richness and human population size, and positive indirect effects of area, on alien species richness. The models also identified indirect effects of temperature (positive) and isolation (negative) on alien species richness. Native plant and bird species richness were both predicted by direct effects of area (positive), temperature (positive) and isolation (negative). However, native plant richness was the only direct predictor of native bird species richness, and the strongest direct predictor of alien bird species richness, for islands with both plant and bird richness data. MAIN CONCLUSIONS: Our analyses recover the species–area, species–isolation and productivity relationships in native richness. Alien species richness was most strongly related to native species richness, with additional effects of human population size. Human population size most likely determines the number of alien species that arrive on an island, while the effect of native species richness may be driven by the influence of habitat heterogeneity on the likelihood that those populations persist (establishment success).