The effects of hurricanes on the stochastic population growth of the endemic epiphytic orchid Broughtonia cubensis living in Cuba

We carried out a posthurricane evaluation of Broughtonia cubensis (Lindl.) Cogn., an endemic Cuban epiphytic orchid, after Hurricane Ivan (2004). We studied the transient responses in the stochastic dynamics of the species at three different sites over 13 successive years (2006–2019), monitored plot inventories (464 individuals in 10 transects) and built stochastic population models. The deterministic stochastic growth rate values () did not significantly differ (F = 2.76; p > 0.076) among the three sites over the 2006–2019 period. The long-term stochastic growth rate was 0.973 [0.932, 1.034]. The matrix elements that had the largest effect on were the transition to and stasis within the largest size class. Transient responses explained an average of 86% of the variation in the observed population growth rates , compared to 4% of the variation in the vital rates . Because transient dynamics are dependent on the population size composition, we ran extinction risk analyses under two scenarios: a population composed mainly of juveniles and another composed mainly of adults. There was little risk of falling below the quasi-extinction threshold before 25 year for both juveniles and adults. However, the risk of quasi-extinction was almost certain for both size classes by 80 year. We also simulated the effect of increasing the hurricane occurrence probability over 80 year on the population. There was little risk of extinction before 20 year in the baseline model, but there was a significant risk of extinction within 5 year when 90% of the individuals were affected by a new hurricane event.     

Estimating the distribution of heterogeneous treatment effects from treatment responses and from a predictive biomarker in a parallel-group RCT: A structural model approach

When the objective is to administer the best of two treatments to an individual, it is necessary to know his or her individual treatment effects (ITEs) and the correlation between the potential responses (PRs) and under treatments 1 and 0. Data that are generated in a parallel-group design RCT does not allow the ITE to be determined because only two samples from the marginal distributions of these PRs are observed and not the corresponding joint distribution. This is due to the “fundamental problem of causal inference.” Here, we present a counterfactual approach for estimating the joint distribution of two normally distributed responses to two treatments. This joint distribution of the PRs and can be estimated by assuming a bivariate normal distribution for the PRs and by using a normally distributed baseline biomarker functionally related to the sum . Such a functional relationship is plausible since a biomarker and the sum encode for the same information in an RCT, namely the variation between subjects. The estimation of the joint trivariate distribution is subjected to some constraints. These constraints can be framed in the context of linear regressions with regard to the proportions of variances in the responses explained and with regard to the residual variation. This presents new insights on the presence of treatment–biomarker interactions. We applied our approach to example data on exercise and heart rate and extended the approach to survival data.     

Inverse problem approach to regularized regression models with application to predicting recovery after stroke

Regression modelling is a powerful statistical tool often used in biomedical and clinical research. It could be formulated as an inverse problem that measures the discrepancy between the target outcome and the data produced by representation of the modelled predictors. This approach could simultaneously perform variable selection and coefficient estimation. We focus particularly on a linear regression issue, , where is the parameter of interest and its components are the regression coefficients. The inverse problem finds an estimate for the parameter , which is mapped by the linear operator to the observed outcome data . This problem could be conveyed by finding a solution in the affine subspace . However, in the presence of collinearity, high-dimensional data and high conditioning number of the related covariance matrix, the solution may not be unique, so the introduction of prior information to reduce the subset and regularize the inverse problem is needed. Informed by Huber's robust statistics framework, we propose an optimal regularizer to the regression problem. We compare results of the proposed method and other penalized regression regularization methods: ridge, lasso, adaptive-lasso and elastic-net under different strong hypothesis such as high conditioning number of the covariance matrix and high error amplitude, on both simulated and real data from the South London Stroke Register. The proposed approach can be extended to mixed regression models. Our inverse problem framework coupled with robust statistics methodology offer new insights in statistical regression and learning. It could open a new research development for model fitting and learning.     

Evidence for Depressed Reproduction of Golden Eagles in Washington

Beginning in 1977 the Washington Department of Fish and Wildlife conducted annual surveys to determine statewide golden eagle (Aquila chrysaetos) occupancy and productivity. Current interest in the regional and national status of the species prompted our investigation to determine utility of historical data in assessing trends in reproduction, and to test efficacy of a sampling protocol that surveyed randomly selected territories and also accounted for detection probability. We found evidence indicating poor reproduction from 38 annual surveys conducted at 301 known territories statewide between 1977 and 2014. At 256 territories in eastern Washington, USA, apparent occupancy was low ( = 50.9%) and nesting success declined by 22%. All reproductive parameters were higher than at 45 territories in western Washington. We tested efficacy of a sampling protocol in 2013 and 2014 by surveying 108 randomly selected eastern territories. Probability of detecting eagles for these years from ground (= 89%) was greater than from air (= 66%). Our estimate of territory occupancy, corrected by probability of detection, was lower in 2013 (= 56.7%, 95% CI = 46.3–66.7%) than in 2014 (= 73.7%, 95% CI = 64.8–81.7%), as was the estimated number of breeding pairs (2013: = 158, 95% CI = 151–164; 2014: = 187, 95% CI = 182–192). Higher productivity (young/occupied territory) in 2013 (= 0.59, 95% CI = 0.40–0.82) than in 2014 (= 0.41, 95% CI = 0.27–0.59) and lower proportions of ≥1 immature eagle among nesting pairs in 2013 (16%) than in 2014 (31%), suggested higher immature pairing among sampled pairs contributed to inter-year differences in these reproductive parameters. Current and historical evidence for depressed golden eagle nesting in Washington is consistent with documented effects from habitat conversion, prey declines, lead contamination, and wind power development. We recommend future surveys in eastern Washington adhere to the random sampling protocol and conduct surveys at regular intervals to allow for trend analysis of reproductive parameters to better monitor golden eagle status. Surveys in western Washington, conducted exclusively from ground at all nests, will improve detection and cost efficiency. © 2020 The Wildlife Society.     

Estimating the decision curve and its precision from three study designs

The decision curve plots the net benefit of a risk model for making decisions over a range of risk thresholds, corresponding to different ratios of misclassification costs. We discuss three methods to estimate the decision curve, together with corresponding methods of inference and methods to compare two risk models at a given risk threshold. One method uses risks (R) and a binary event indicator (Y) on the entire validation cohort. This method makes no assumptions on how well-calibrated the risk model is nor on the incidence of disease in the population and is comparatively robust to model miscalibration. If one assumes that the model is well-calibrated, one can compute a much more precise estimate of based on risks R alone. However, if the risk model is miscalibrated, serious bias can result. Case–control data can also be used to estimate if the incidence (or prevalence) of the event () is known. This strategy has comparable efficiency to using the full data, and its efficiency is only modestly less than that for the full data if the incidence is estimated from the mean of Y. We estimate variances using influence functions and propose a bootstrap procedure to obtain simultaneous confidence bands around the decision curve for a range of thresholds. The influence function approach to estimate variances can also be applied to cohorts derived from complex survey samples instead of simple random samples.     

Anthropogenic Disturbance and Population Viability of Woodland Caribou in Ontario

One of the most challenging tasks in wildlife conservation and management is to clarify how spatial variation in land cover due to anthropogenic disturbance influences wildlife demography and long-term viability. To evaluate this, we compared rates of survival and population growth by woodland caribou (Rangifer tarandus caribou) from 2 study sites in northern Ontario, Canada that differed in the degree of anthropogenic disturbance because of commercial logging and road development, resulting in differences in predation risk due to gray wolves (Canis lupus). We used an individual-based model for population viability analysis (PVA) that incorporated adaptive patterns of caribou movement in relation to predation risk and food availability to predict stochastic variation in rates of caribou survival. Field estimates of annual survival rates for adult female caribou in the unlogged ( 0.90) and logged ( 0.76) study sites recorded during 2010–2014 did not differ significantly (P > 0.05) from values predicted by the individual-based PVA model (unlogged: = 0.87; logged: 0.79). Outcomes from the individual-based PVA model and a simpler stage-structured matrix model suggest that substantial differences in adult survival largely due to wolf predation are likely to lead to long-term decline of woodland caribou in the commercially logged landscape, whereas the unlogged landscape should be considerably more capable of sustaining caribou. Estimates of population growth rates (λ) for the 2010–2014 period differed little between the matrix model and the individual-based PVA model for the unlogged (matrix model = 1.01; individual-based model = 0.98) and logged landscape (matrix model = 0.88; individual-based model = 0.89). We applied the spatially explicit PVA model to assess the viability of woodland caribou across 14 woodland caribou ranges in Ontario. Outcomes of these simulations suggest that woodland caribou ranges that have experienced significant levels of commercial forestry activities in the past had annual growth rates <0.89, whereas caribou ranges that had not experienced commercial forestry operations had population growth rates >0.96. These differences were strongly related to regional variation in wolf densities. Our results suggest that increased wolf predation risk due to anthropogenic disturbance is of sufficient magnitude to cause appreciable risk of population decline in woodland caribou in Ontario. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.     

Optimal Strategies for Managing Wildlife Harvest Under System Change

Wildlife populations are experiencing shifting dynamics due to climate and landscape change. Management policies that fail to account for non-stationary dynamics may fail to achieve management objectives. We establish a framework for understanding optimal strategies for managing a theoretical harvested population under non-stationarity. Building from harvest theory, we develop scenarios representing changes in population growth rate () or carrying capacity () and derive time-dependent optimal harvest policies using stochastic dynamic programming. We then evaluate the cost of falsely assuming stationarity by comparing the outcomes of forward projections in which either the optimal policy or a stationary policy is applied. When declines over time, the stationary policy leads to an underharvest of the population, resulting in less harvest over the short term but leaving the population in a higher-value state. When declines over time, the stationary policy leads to overharvest, resulting in greater harvest returns in the short term but leaving the population in a lower and potentially more vulnerable state. This work demonstrates the basic properties of time-dependent harvest management and provides a framework for evaluating the many outstanding questions about optimal management strategies under climate change. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.     

Application of the\mathop m\limits^* - m method to the analysis of spatial patterns by changing the quadrat sizemethod to the analysis of spatial patterns by changing the quadrat size

A method for the analysis of spatial pattern using quadrats of different sizes is developed on the basis of the relationship of mean crowding () to mean density (m). The -on-m regression obtained by successive changes in quadrat size in a single population (unit-size relation) shows a characteristic pattern according to the type of distribution. By aid of the ρ-index proposed here, we can distinguish the random, aggregated and uniform distributions of the basic components (individual or group of individuals). The ρ serves as an index of spatial correlation between neighbouring quadrats, and it also provides information on the approximate area occupied by clump (colony), distribution pattern of individuals within clumps, and possibly the distribution pattern of clumps themselves. Even in a specified type of distribution, the unit-size relation is not necessarily identical with the relation for a series of populations at a particular quadrat size (series relation). The changes in the series relationship with successive changes of quadrat sizes are also considered for some basic patterns of distributions. The combined use of the unit-size and the series relations for a set of populations of the species under study may provide a satisfactory picture of the spatial pattern characteristic of the species. Application of the method is illustrated by using distribution data of several species of animals and plants. The advantage of the present method over other methods are discussed, and the formulae for determining the optimum quadrat unit in sampling surveys are given.     

Mortality process in relation to aggregation in the southern green stink bug

A simple experiment of simulation was done to analyze the natural mortality process of young larval colonies and egg masses of the southern green stink bug. In this experiment, a degree of contagiousness was allowed in regard to the action of a mortality factor, and was defined as the mean number killed per a colony or an egg mass by the mortality factor within a unit time and the number killed per a colony was assumed to follow the Poisson series with the mean . Thus each component of the Poisson series was opposed to each colony or egg mass which was taken at random from 162 egg masses, 135 and 117 colonies of the first and the second instar larvae, respectively. It was revealed that mortality factors in the field did not act with a small degree of contagiosness, e. g., on all colonies or egg masses, but acted with a large degree of contagiousness, e. g., on some of the colonies or egg masses. Thus differential survival somewhat in all or none way occurred among the insect colonies irrespective of their initial sizes. These results were well explained by taking actual mortality factors into account.     

A new proposal for measurement of the adjusted mean crowding through consideration of size variability in habitat units

The mean crowding has previously been measured under the assumption that all quadrats or habitat units have the same size, even though the actual habitat units such as seeds or leaves are generally variable in size. A new index, ‘adjusted mean crowding’, which is adjusted for this variability can be given as where Q is the total number of habitat units in the whole area, x_j the number of individuals in the jth habitat unit, and a_j is defined as the ‘relative size’ of the jth habitat unit, i.e. a_y=y_y/(∑y_j/Q) where y_j is the actually measured size of the jth habitat unit. It is expected that and for the uniform distribution and the random distribution ‘per unit size’, respectively. The comparison between and regressions ( analysis) for the egg distribution pattern of Callosobruchus chinensis or C. maculatus proved that the regression is biased by a positive correlation between the egg number per seed and seed size rather than by a density-dependent change in the ovipositional behavior.     

Another chemolithotrophic metabolism missing in nature: sulfur comproportionation

Chemotrophic microorganisms gain energy for cellular functions by catalyzing oxidation–reduction (redox) reactions that are out of equilibrium. Calculations of the Gibbs energy ( ΔG _r ) can identify whether a reaction is thermodynamically favourable and quantify the accompanying energy yield at the temperature, pressure and chemical composition in the system of interest. Based on carefully calculated values of ΔG _r , we predict a novel microbial metabolism – sulfur comproportionation (3H₂S + + 2H⁺ ⇌ 4S⁰ + 4H₂O). We show that at elevated concentrations of sulfide and sulfate in acidic environments over a broad temperature range, this putative metabolism can be exergonic ( ΔG _r <0), yielding ~30–50 kJ mol⁻¹. We suggest that this may be sufficient energy to support a chemolithotrophic metabolism currently missing from the literature. Other versions of this metabolism, comproportionation to thiosulfate (H₂S + ⇌ + H₂O) and to sulfite (H₂S + 3 ⇌ 4 + 2H⁺), are only moderately exergonic or endergonic even at ideal geochemical conditions. Natural and impacted environments, including sulfidic karst systems, shallow-sea hydrothermal vents, sites of acid mine drainage, and acid–sulfate crater lakes, may be ideal hunting grounds for finding microbial sulfur comproportionators.     

Intuitive and broadly applicable definitions of niche and fitness differences

Explaining nature’s biodiversity is a key challenge for science. To persist, populations must be able to grow faster when rare, a feature called negative frequency dependence and quantified as ‘niche differences’ () in modern coexistence theory. Here, we first show that available definitions of differ in how link to species interactions, are difficult to interpret and often apply to specific community types only. We then present a new definition of that is intuitive and applicable to a broader set of (modelled and empirical) communities than is currently the case, filling a main gap in the literature. Given , we also redefine fitness differences () and illustrate how and determine coexistence. Finally, we demonstrate how to apply our definitions to theoretical models and experimental data, and provide ideas on how they can facilitate comparison and synthesis in community ecology.     

Analysis of spatial association between two species based on the interspecies mean crowding

The measurement of spatial association between two species is considered on the basis of interspecies mean crowding. Two indices of overlapping, γ and C_p, are derived as geometric and weighted arithmetic means of the same component ratios related to inter-and intraspecies mean crowdings. Both indices behave in a similar way, ranging from 1 when the distributions of two species are completely overlapped to 0 when they are completely exclusive with each other. The former is essentially identical with indices proposed byKuno (1968) andPianka (1973), and the latter is a modified form ofMorisita's (1959)C_σ index. Indices to measure the degree of spatial correlation between species, Ω and R_μ, are then derived for both kinds of overlapping indices, which vary from 1 in complete overlapping, through 0 in independent occurrence, to −1 in complete exclusion. Various kinds of interspecies association are analyzed using these indices and an extended form of the regression graph which provides a convenient way of indicating the spatial interrelation between two species as well as distribution patterns of respective species. The method presented in this paper may also be applicable to compare temporal distribution patterns between species, similarity between communities, etc. For such a wider application which includes continuous as well as discrete distributions, the interpretation of intra-and interspecies mean crowdings is not necessarily appropriate, and hence the concept of mean concentration with the symbols and for intraspecies relation and and for interspecies relation is suggested.     

An estimator of the Opportunity for Selection that is independent of mean fitness

Variation among individuals in number of offspring (fitness, k) sets an upper limit to the evolutionary response to selection. This constraint is quantified by Crow's Opportunity for Selection (I), which is the variance in relative fitness (I = σ²_k/(u_k)²). Crow's I has been widely used but remains controversial because it depends on mean offspring number in a sample (). Here, I used a generalized Wright-Fisher model that allows for unequal probabilities of producing offspring to evaluate behavior of Crow's I and related indices under a wide range of sampling scenarios. Analytical and numerical results are congruent and show that rescaling the sample variance (s²_k) to its expected value at a fixed removes dependence of I on mean offspring number, but the result still depends on choice of . A new index is introduced, Δ_I = Π– E(Î_drift) = Π– 1/, which makes Î independent of sample without the need for variance rescaling. Δ_I has a straightforward interpretation as the component of variance in relative fitness that exceeds that expected under a null model of random reproductive success. Δ_I can be used to directly compare estimates of the Opportunity for Selection for samples from different studies, different sexes, and different life stages.     

Apparent annual survival of staging ruffs during a period of population decline: insights from sex and site-use related differences

The ruff Philomachus pugnax, a lekking shorebird wintering in Africa and breeding across northern Eurasia, declined severely in its western range. Based on a capture-mark-resighting programme (2004–2011) in the westernmost staging area in Friesland (the Netherlands), we investigated changes in apparent annual survival in relation to age and sex to explore potential causes of decline. We also related temporal variation in apparent survival to environmental factors. We used the Capture-Mark-Recapture multievent statistical framework to overcome biases in survival estimates after testing for hidden heterogeneity of detection. This enabled the estimation of the probability to belong to high or low detectability classes. Apparent survival varied between years but was not related to weather patterns along the flyway, or to flood levels in the Sahel. Over time, a decline in apparent survival is suggested. Due to a short data series and flag loss in the last period this cannot be verified. Nevertheless, the patterns in sex-specific detectability and survival lead to new biological insights. Among highly detectable birds, supposedly most reliant on Friesland, males survived better than females ( = 0.74, range 0.51–0.93; = 0.51, range 0.24–0.81). Among low detectable birds, the pattern is reversed ( = 0.64, range 0.37–0.89; = 0.73, range 0.48–0.93). Probably the staging population contains a mixture of sex-specific migration strategies. A loss of staging females could greatly affect the dynamics of the western ruff population. Further unravelling of these population processes requires geographically extended demographic monitoring and the use of tracking devices.     

Tiller population dynamics of reciprocally transplanted Eriophorum vaginatum L. ecotypes in a changing climate

Moist tussock tundra, dominated by the sedge Eriophorum vaginatum L., covers approximately 3.36 × 10⁸ km² of arctic surface area along with large amounts of subarctic land area. Eriophorum vaginatum exhibits ecotypic differentiation along latitudinal gradients in Alaska. While ecotypic differentiation may be beneficial during periods of climate stability, it may be detrimental as climate changes, causing adaptational lag. Following harvest of a 30-year reciprocal transplant experiment, age-specific demographic data on E. vaginatum tillers were collected to parameterize a Leslie matrix. Yellow Taxi analysis, based on Tukey's Jackknife, was used to determine mean pseudovalues of tiller population growth rate () for four source populations of E. vaginatum tussocks that were transplanted to each of three gardens along a latitudinal gradient. Source populations responded differentially along the latitudinal gradient. Survival and daughter tiller production influenced differences seen at the mid-latitude garden, and the overall tiller population performance was generally improved by northward transplanting relative to southward transplanting. A comparison of home-source and away-source within the same transplant garden indicates no home-site advantage. Although populations were still growing when transplanted to home-sites ( = 1.056), tiller population growth rate increased as ΔGDD became more negative relative to the home site (i.e., as tussocks were transplanted north). These results imply that populations are affected by climate gradients in a manner consistent with adaptational lag. This study documenting the response of high-latitude ecotypes to climate gradients may be an indication of the possible future effects of climate shift in more southern latitudes.     

Respirometer in a box: development and use of a portable field respirometer for estimating oxygen consumption of large-bodied fishes

This study developed a portable, low-cost field respirometer for measuring oxygen consumption rates of large-bodied fishes. The respirometer performed well in laboratory tests and was used to measure the oxygen consumption rates ( O₂) of bull sharks Carcharhinus leucas (mean: 249.21 ± 58.10 mg O₂ kg⁻¹ h⁻¹ at 27.05°C). Interspecific comparisons and assessments of oxygen degradation curves indicated that the respirometer provided reliable measurements of O₂. This system presents a field-based alternative to laboratory respirometers, opening opportunities for studies on species in remote localities, increasing the ability to validate physiological field studies.     

The design heatmap: A simple visualization of -optimality design problems

Optimal experimental designs are often formal and specific, and not intuitively plausible to practical experimenters. However, even in theory, there often are many different possible design points providing identical or nearly identical information compared to the design points of a strictly optimal design. In practical applications, this can be used to find designs that are a compromise between mathematical optimality and practical requirements, including preferences of experimenters. For this purpose, we propose a derivative-based two-dimensional graphical representation of the design space that, given any optimal design is already known, will show which areas of the design space are relevant for good designs and how these areas relate to each other. While existing equivalence theorems already allow such an illustration in regard to the relevance of design points only, our approach also shows whether different design points contribute the same kind of information, and thus allows tweaking of designs for practical applications, especially in regard to the splitting and combining of design points. We demonstrate the approach on a toxicological trial where a -optimal design for a dose–response experiment modeled by a four-parameter log-logistic function was requested. As these designs require a prior estimate of the relevant parameters, which is difficult to obtain in a practical situation, we also discuss an adaption of our representations to the criterion of Bayesian -optimality. While we focus on -optimality, the approach is in principle applicable to different optimality criteria as well. However, much of the computational and graphical simplicity will be lost.     

Population dynamics of the chestnut gall-wasp,Dryocosmus kuriphilus Yasumatsu (Hymenoptera: Cynipidae) IV. Further analysis of the distribution of eggs and young larvae in buds using the truncated negative binomial series

Distribution pattern of eggs and the first instar larvae of the chestnut gall-wasp, Dryocosmus kuriphilus, per bud of the chestnut tree was re-examined using the truncatedPoisson and the truncated negative binomial series. The results are as follows:

1. About sixty percent of the distribution are approximated by the truncated negative binomial and another thirty percent by the truncatedPoisson . When the distribution has been approximated by the truncated negative binomial, the show scattered values, some of which are near thePoisson , but the mean value of is about 4 both in eggs and in the first instar larvae.
2. The number of buds which have not been infested by gall-wasps is resulted from various factors as follows: (a) Buds formed after the laying activity of gall-wasps has ceased; (b) Old and shrunk buds which were avoided in laying; (c) Buds in which eggs have died by the time of sampling; and (d) Buds escaping ovipositions by chance. Most of the gall-wasp-free buds located in the middle part of the shoot are accounted for the zero-class expected by the negative binomial series.
3. Brass (1958) moment method for estimating parameters of the truncated negative binomial give good precision within the range of from 1 to 10 and of from 1 to 6.
4. It is concluded that the truncated distributions used are useful for the purpose of analysis of the distribution pattern of the chestnut gall-wasp.