Age and growth of mangrove red snapper Lutjanus argentimaculatus at its cool‐water‐range limits

This study investigates the age and growth of Lutjanus argentimaculatus at its southern (cooler) range limits in eastern Australia. Specimens were collected from New South Wales and southern Queensland between November 2011 and December 2013. Fork lengths (L_F) ranged from 190 to 1019 mm, and ages ranged from 2+ to 57+ years. Growth was described by the von Bertalanffy growth function with coefficients L_∞ = 874·92 mm, K = 0·087 year^?1 and t₀ = ?2·76 years. Estimates of the instantaneous natural mortality rate (M) ranged from 0·072 to 0·25. The L_F (mm) and mass (W; g) relationship was represented by the equation: . The maximum age of 57+ years is the oldest reported for any lutjanid and comparisons with tropical studies suggest that the age‐based demography of L. argentimaculatus follows a latitudinal gradient. High maximum ages and low natural mortality rates indicate considerable vulnerability to overexploitation at the species' cool‐water‐range limits. These results demonstrate the need to identify underlying processes driving latitudinal gradients in fish demography.     

Impacts of temperature on metabolic rates of adult Extatosoma tiaratum reared on different host plant species

Access to balanced nutrition enables optimum health and development, body repair, fat storage, increased fecundity and longevity. In the present study, we assessed the responses of a generalist leaf feeder (the phasmid Extatosoma tiaratum) reared continuously on one of three host plants, tree lucerne (Chamaecyisus palmensis), bramble (Rubus fruticosus) and Eucalyptus species, in a low fluctuating temperature environment until adulthood. Once all individuals reached adulthood, we exposed each individual to a ramping temperature event (starting at 25 °C and ramping the temperature at 0.25 °C min⁻¹) and assessed their metabolic rates () responses at specific temperature 'bins' (25, 30, 35, 40 and 42 °C). Sex but not diet influenced respiration and metabolic rate. Male individuals, on average, had a higher than females. Sex and diet were significant influences on at different temperatures. Metabolic rates at lower temperatures were not affected by sex or diet type. At 35 °C, metabolic rates were influenced by sex and diet, with males reared on bramble and tree lucerne having a higher metabolic rate than females reared on the same foodplant, whereas Eucalypt reared animals showing an opposite trend. Lifetime egg production by females was 150% higher on bramble compared with the other host plants. Incorporating fluctuating temperature ranges into experiments will further help to understand the impact that thermal stress will have on the growth, development, performance and survival of insects in a more variable climatic and nutritional landscape.     

Reproductive characteristics that favor invasiveness in Leonotis nepetifolia (L.) R. Br.

Reproductive systems are life attributes important in defining the demography and genetic constitution of invasive alien species populations. We describe the phenology, floral behavior and floral visitors in Mexican populations of Leonotis nepetifolia considered invasive in America, Asia and Oceania. The mating system was determined through pollination experiments and, with a morphological analysis of flowers (outcrossing index, OCI) and pollen/ovule ratio, the breeding system was evaluated. Germination of 1 and 2-year-old seeds was tested to assess the potential characteristics of germination. Leonotis nepetifolia was reproductive for 7 months (June to December) and tended towards a specific season during autumn. Anthesis lasted 36 hr with protogyny and no hercogamy, with floral visitors of Apodiformes, Hymenoptera, Lepidoptera and Thysanoptera. Pollination experiments indicated a mixed mating system, whereas the OCI and the pollen/ovule ratio pointed towards a facultative xenogamous breeding system. Seed production was high (1,445 ± 132 seeds/plant); the seeds had potential longevity and were neutral photoblastic. One-year-old seeds germinated slightly later ( = 2.6 ± 0.11 days) than 2-year-old seeds ( = 1.9 ± 0.02 days), both synchronously (IS_1yr = 0.88 ± 0.03 and IS_2yr = 0.82 ± 0.02). Germination percentage for 1-year-old seeds was lower (55.33 ± 4.40%) than that of 2-year-old seeds (94.18 ± 0.59%), suggesting a potential longevity of the seeds in an optimal environment. Reproductive characteristics, such as wide reproductive period, mixed breeding system, copious seed production, seeds with potential longevity, and quick and synchronic germination in different light conditions, favor the invasive capacity of Leonotis nepetifolia.     

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 occupancy of Chinese pangolin (Manis pentadactyla) in a protected and non‐protected area of Nepal

Chinese pangolin is the world's most heavily trafficked small mammal for luxury food and traditional medicine. Although their populations are declining worldwide, it is difficult to monitor their population status because of its rarity and nocturnal behavior. We used site occupancy (presence/absence) sampling of pangolin sign (i.e., active burrows) in a protected (Gaurishankar Conservation Area) and non‐protected area (Ramechhap District) of central Nepal with multiple environmental covariates to understand factors that may influence occupancy of Chinese pangolin. The average Chinese pangolin occupancy and detection probabilities were  ± SE = 0.77 ± 0.08;  ± SE = 0.27 ± 0.05, respectively. The detection probabilities of Chinese pangolin were higher in PA (  ± SE = 0.33 ± 0.03) than compared to non‐PA (  ± SE = 0.25 ± 0.04). The most important covariates for Chinese pangolin detectability were red soil (97%), food source (97.6%), distance to road (97.9%), and protected area (97%) and with respect to occupancy was elevation (97.9%). We recommended use of remote cameras and potentially GPS collar surveys to further investigate habitat use and site occupancy at regular intervals to provide more reliable conservation assessments.     

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.     

Genetic Characteristics of Restored Elk Populations in Kentucky

Translocations are a common management practice to restore or augment populations. Understanding the genetic consequences of translocation efforts is important for the long-term health of restored populations. The restoration of elk (Cervus canadensis) to Kentucky, USA, included source stocks from 6 western states, which were released at 8 sites in southeastern Kentucky during 1997–2002. We assessed genetic diversity in restored herds and compared genetic similarity to source stocks based on 15 microsatellite DNA loci. Genetic variation in the restored populations was comparable to source stocks ( allelic richness = 3.52 and 3.50; expected heterozygosity = 0.665 and 0.661 for restored and source, respectively). Genetic differentiation among all source and restored populations ranged from 0.000 to 0.065 for pairwise F_ST and 0.034 to 0.161 for pairwise Nei's D_A. Pairwise genetic differentiation and Bayesian clustering revealed that stocks from Utah and North Dakota, USA, contributed most to restored populations. Other western stocks appeared less successful and were not detected with our data, though our sampling was not exhaustive. We also inferred natural movements of elk among release sites by the presence of multiple genetic stocks. The success of the elk restoration effort in Kentucky may be due, in part, to the large number of elk (n = 1,548), repeated releases, and use of diverse source stocks. Future restoration efforts for elk in the eastern United States should consider the use of multiple stock sources and a large number of individuals. In addition, preservation of genetic samples of founder stock will enable detailed monitoring in the future. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.     

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.     

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.     

NO and N2O transformations of diverse fungi in hypoxia: evidence for anaerobic respiration only in Fusarium strains

Fungal denitrification is claimed to produce non-negligible amounts of N₂O in soils, but few tested species have shown significant activity. We hypothesized that denitrifying fungi would be found among those with assimilatory nitrate reductase, and tested 20 such batch cultures for their respiratory metabolism, including two positive controls, Fusarium oxysporum and Fusarium lichenicola, throughout the transition from oxic to anoxic conditions in media supplemented with . Enzymatic reduction of (NIR) and NO (NOR) was assessed by correcting measured NO- and N₂O-kinetics for abiotic NO- and N₂O-production (sterile controls). Significant anaerobic respiration was only confirmed for the positive controls and for two of three Fusarium solani cultures. The NO kinetics in six cultures showed NIR but not NOR activity, observed through the accumulation of NO. Others had NOR but not NIR activity, thus reducing abiotically produced NO to N₂O. The presence of candidate genes (nirK and p450nor) was confirmed in the positive controls, but not in some of the NO or N₂O accumulating cultures. Based on our results, we conclude that only the Fusarium cultures were able to sustain anaerobic respiration and produced low amounts of N₂O as a response to an abiotic NO production from the medium.     

Interferometric optical fiber sensor for optoacoustic endomicroscopy

Optical fiber sensors can offer robust and miniaturized detection of wideband ultrasound, yielding high sensitivity and immunity to electromagnetic interference. However, the lack of cost-effective manufacturing methods prevents the disseminated use of these sensors in biomedical applications. In this study, we developed and optimized a simple method to create optical cavities with high-quality mirrors for acoustic sensing based on micro-manipulation of UV-curable optical adhesives and electroless chemical silver deposition. This approach enables the manufacturing of ultrasound sensors based on Fabry-Pérot interferometers on optical fiber tips with minimal production costs. Characterization and high-resolution optoacoustic imaging experiments show that the manufacturing process yielded a fiber sensor with a small NEP () over a broad detection bandwidth (25 MHz), generally outperforming conventional piezoelectric based transducers. We discuss how the new manufacturing process leads to a high-performance acoustic detector that, due to low cost, can be used as a disposable sensor.     

Dryness limits vegetation pace to cope with temperature change in warm regions

Climate change leads to increasing temperature and more extreme hot and drought events. Ecosystem capability to cope with climate warming depends on vegetation's adjusting pace with temperature change. How environmental stresses impair such a vegetation pace has not been carefully investigated. Here we show that dryness substantially dampens vegetation pace in warm regions to adjust the optimal temperature of gross primary production (GPP) ($T_{\mathrm{opt}}^{\mathrm{GPP}}$) in response to change in temperature over space and time. $T_{\mathrm{opt}}^{\mathrm{GPP}}$ spatially converges to an increase of 1.01°C (95% CI: 0.97, 1.05) per 1°C increase in the yearly maximum temperature (T_max) across humid or cold sites worldwide (37^oS–79^oN) but only 0.59°C (95% CI: 0.46, 0.74) per 1°C increase in T_max across dry and warm sites. $T_{\mathrm{opt}}^{\mathrm{GPP}}$ temporally changes by 0.81°C (95% CI: 0.75, 0.87) per 1°C interannual variation in T_max at humid or cold sites and 0.42°C (95% CI: 0.17, 0.66) at dry and warm sites. Regardless of the water limitation, the maximum GPP (GPP_max) similarly increases by 0.23 g C m⁻² day⁻¹ per 1°C increase in $T_{\mathrm{opt}}^{\mathrm{GPP}}$ in either humid or dry areas. Our results indicate that the future climate warming likely stimulates vegetation productivity more substantially in humid than water-limited regions.     

Contrasting responses of peak vegetation growth to asymmetric warming: Evidences from FLUXNET and satellite observations

The peak growth of plant in summer is an important indicator of the capacity of terrestrial ecosystem productivity, and ongoing studies have shown its responses to climate warming as represented in the mean temperature. However, the impacts from the asymmetrical warming, that is, different rates in the changes of daytime (T_max) and nighttime (T_min) warming were mostly ignored. Using 60 flux sites (674 site-year in total) measurements and satellite observations from two independent satellite platforms (Global Inventory Monitoring and Modeling Studies [1982–2015]; MODIS [2000–2020]) over the Northern Hemisphere (≥30°N), here we show that the peak growth, as represented by both flux-based maximum primary productivity and the maximum greenness indices (maximum normalized difference vegetation index and enhanced vegetation index), responded oppositely to daytime and nighttime warming. $T_{\max }^{-}{T}_{\min }^{+}$ (peak growth showed negative responses to T_max, but positive responses to T_min) dominated in most ecosystems and climate types, especially in water-limited ecosystems, while $T_{\max }^{+}{T}_{\min }^{-}$ (peak growth showed positive responses to T_max, but negative responses to T_min) was primarily observed in high latitude regions. These contrasting responses could be explained by the strong association between asymmetric warming and water conditions, including soil moisture, evapotranspiration/potential evapotranspiration, and the vapor pressure deficit. Our results are therefore important to the understanding of the responses of peak growth to climate change, and consequently a better representation of asymmetrical warming in future ecosystem models by differentiating the contributions between daytime and nighttime warming.     

Mean growth rate when rare is not a reliable metric for persistence of species

The coexistence of many species within ecological communities poses a long‐standing theoretical puzzle. Modern coexistence theory (MCT) and related techniques explore this phenomenon by examining the chance of a species population growing from rarity in the presence of all other species. The mean growth rate when rare, , is used in MCT as a metric that measures persistence properties (like invasibility or time to extinction) of a population. Here we critique this reliance on and show that it fails to capture the effect of temporal random abundance variations on persistence properties. The problem becomes particularly severe when an increase in the amplitude of stochastic temporal environmental variations leads to an increase in , since at the same time it enhances random abundance fluctuations and the two effects are inherently intertwined. In this case, the chance of invasion and the mean extinction time of a population may even go down as increases.     

Simulated oxygen and glucose gradients as a prerequisite for predicting industrial scale performance a priori

Transferring bioprocesses from lab to industrial scale without loss of performance is key for the successful implementation of novel production approaches. Because mixing and mass transfer is usually hampered in large scale, cells experience heterogeneities eventually causing deteriorated yields, that is, reduced titers, productivities, and sugar-to-product conversions. Accordingly, reliable and easy-to-implement tools for a priori prediction of large-scale performance based on dry and wet-lab tests are heavily needed. This study makes use of computational fluid dynamic simulations of a multiphase multi-impeller stirred tank in pilot scale. So-called lifelines, records of 120,000 Corynebacterium glutamicum cells experiencing fluctuating environmental conditions, were identified and used to properly design wet-lab scale-down (SD) devices. Physical parameters such as power input, gas hold up, , and mixing time showed good agreement with experimental measurements. Analyzing the late fed-batch cultivation revealed that the complex double gradient of glucose and oxygen can be translated into a wet-lab SD setup with only few compartments. Most remarkably, the comparison of different mesh sizes outlined that even the coarsest approach with a mesh density of was sufficient to properly predict physical and biological readouts. Accordingly, the approach offers the potential for the thorough analysis of realistic industrial case scenarios.     

Excess post‐hypoxic oxygen consumption in Atlantic cod Gadus morhua

Atlantic cod Gadus morhua experienced oxygen deficit () when exposed to oxygen levels below their critical level (c. 73% of p_crit) and subsequent excess post‐hypoxic oxygen consumption (C_EPHO) upon return to normoxic conditions, indicative of an oxygen debt. The mean ± s.e . C_EPHO: was 6·9 ± 1·5, suggesting that resorting to anaerobic energy production in severe hypoxia is energetically expensive.     

Estimating average treatment effects with a double-index propensity score

We consider estimating average treatment effects (ATE) of a binary treatment in observational data when data-driven variable selection is needed to select relevant covariates from a moderately large number of available covariates $\mathbf{X}$. To leverage covariates among $\mathbf{X}$ predictive of the outcome for efficiency gain while using regularization to fit a parametric propensity score (PS) model, we consider a dimension reduction of $\mathbf{X}$ based on fitting both working PS and outcome models using adaptive LASSO. A novel PS estimator, the Double-index Propensity Score (DiPS), is proposed, in which the treatment status is smoothed over the linear predictors for $\mathbf{X}$ from both the initial working models. The ATE is estimated by using the DiPS in a normalized inverse probability weighting estimator, which is found to maintain double robustness and also local semiparametric efficiency with a fixed number of covariates p. Under misspecification of working models, the smoothing step leads to gains in efficiency and robustness over traditional doubly robust estimators. These results are extended to the case where p diverges with sample size and working models are sparse. Simulations show the benefits of the approach in finite samples. We illustrate the method by estimating the ATE of statins on colorectal cancer risk in an electronic medical record study and the effect of smoking on C-reactive protein in the Framingham Offspring Study.     

Sensitivity analysis and adaptive mutation strategy differential evolution algorithm for optimizing enzymes' turnover numbers in metabolic models

Genome-scale metabolic network model (GSMM) based on enzyme constraints greatly improves general metabolic models. The turnover number ($k_{\mathrm{cat}}$) of enzymes is used as a parameter to limit the reaction when extending GSMM. Therefore, turnover number plays a crucial role in the prediction accuracy of cell metabolism. In this work, we proposed an enzyme-constrained GSMM parameter optimization method. First, sensitivity analysis of the parameters was carried out to select the parameters with the greatest influence on predicting the specific growth rate. Then, differential evolution (DE) algorithm with adaptive mutation strategy was adopted to optimize the parameters. This algorithm can dynamically select five different mutation strategies. Finally, the specific growth rate prediction, flux variability, and phase plane of the optimized model were analyzed to further evaluate the model. The enzyme-constrained GSMM of Saccharomyces cerevisiae, ecYeast8.3.4, was optimized. Results of the sensitivity analysis showed that the optimization variables can be divided into three groups based on sensitivity: most sensitive (149 $k_{\mathrm{cat}}$c), highly sensitive (1759 $k_{\mathrm{cat}}$), and nonsensitive (2502 $k_{\mathrm{cat}}$) groups. Six optimization strategies were developed based on the results of the sensitivity analysis. The results showed that the DE with adaptive mutation strategy can indeed improve the model by optimizing highly sensitive parameters. Retaining all parameters and optimizing the highly sensitive parameters are the recommended optimization strategy.     

Quantitative genetics of temperature performance curves of Neurospora crassa

Earth's temperature is increasing due to anthropogenic CO emissions; and organisms need either to adapt to higher temperatures, migrate into colder areas, or face extinction. Temperature affects nearly all aspects of an organism's physiology via its influence on metabolic rate and protein structure, therefore genetic adaptation to increased temperature may be much harder to achieve compared to other abiotic stresses. There is still much to be learned about the evolutionary potential for adaptation to higher temperatures, therefore we studied the quantitative genetics of growth rates in different temperatures that make up the thermal performance curve of the fungal model system Neurospora crassa. We studied the amount of genetic variation for thermal performance curves and examined possible genetic constraints by estimating the G -matrix. We observed a substantial amount of genetic variation for growth in different temperatures, and most genetic variation was for performance curve elevation. Contrary to common theoretical assumptions, we did not find strong evidence for genetic trade-offs for growth between hotter and colder temperatures. We also simulated short-term evolution of thermal performance curves of N. crassa, and suggest that they can have versatile responses to selection.     

Satiation meal and the effects of meal and body sizes on gastric evacuation rate in brook trout Salvelinus fontinalis fed commercial pellets

Gastric evacuation (GE) experiments were performed on brook trout Salvelinus fontinalis fed commercial food pellets. The experiments included small fish (36 g; 15 cm total length, L_T) fed meals of 0·2, 0·4 and 0·8 g and large fish (152 g; 23 cm) fed meals of 0·8, 2·0 and 4·0 g at temperatures ranging from 15·1 to 18·2° C. The stomach contents were thereafter sampled and weighed at 3 h intervals until the first empty stomach was observed. The course of GE was examined by use of a general power function of the data that revealed that the square‐root function described the GE rate (GER) by the current stomach content mass independently of original meal size. Using the square‐root function, the relationship between GER and fish size was described by a power function of fish length, whereas the effect of temperature was described by a simple exponential function. GER of the commercial pellets fed to S. fontinalis could thus be described by (g h^?1), where S_t is stomach mass (g) at time t (h), L is total fish length (cm) and T is temperature (° C). The result of this study should provide a useful tool for planning of feeding regimes in production of S. fontinalis by optimizing growth and minimizing food waste.