Overexpression of cloned genes using recombinant Escherichia coli regulated by a T7 promoter: II. Two-stage continuous cultures and model simulations

A two-stage culture strategy was studied for continuous high-level production of a foreign protein in the chemically inducible T7 expression system. The first stage is dedicated to the maintenance of plasmid-bearing cells and the second stage to the target protein synthesis by induction of cells coming from the first stage. On entering the second stage, recombinant cells undergo a gradual induction of the target gene expression. These plasmid-bearing cells experience dynamic changes in intracellular compositions and specific growth rates with their individual residence times. Therefore, the overall cultural characteristics in the production stage are really averages of the contributions from the various cells with different residence times. The behavior of the two-stage culture is described by a model, which accounts for dynamic variations of cell growth and protein synthesis rates with cell residence times. Model simulations were compared with experimental results at a variety of operating conditions such as inducer concentration and dilution rate. This model is useful for understanding the behavior of two-stage continuous cultures. (c) 1993 John Wiley & Sons, Inc.     

A population model for the alkali fly at Mono Lake: depth distribution and changing habitat availability

The densities of alkali fly larvae and pupae were measured in relation to depth and substrate type at six locations around Mono Lake. Samples representing a mixture of different bottom features were taken to a depth of 10 m (33 ft) using SCUBA. This is at or near the depth limit of fly larvae and pupae. The biomass of larvae and pupae on hard substrate were maximum and approximately equal at depths of 0.5 m and 1 m, substantially lower at intermediate depths of 3 m and 5 m, and over an order of magnitude further reduced at 10 m. Densities of flies on hard or rocky substrates (mainly calcareous tufa deposits), were significantly greater than those found on soft substrates such as mud or sand, at all but the greatest depth surveyed.Bathymetric maps of the areas of hard and soft substrate occurring at different lake depths were used to estimate the fly population size over the whole lake, based on the density distribution of larvae and pupae with depth on different substrates. The mapped areas of soft and hard substrates were also calculated for different lake levels, and applying the same procedure, a population model comparing the abundance of flies at different lake levels was developed. This habitat-based population model predicts that the abundance of the alkali fly is maximized at 6380 ft (1945 m) lake surface elevation. Most of the tufa substrate submerged at this lake level will become exposed and unavailable as habitat as the lake declines to 6370 ft (1942 m). In late 1991, the lake level was just over 6374 ft (1943 + m).     

DNA fingerprint bands applied to linkage analysis with quantitative trait loci in chickens

Summary
An efficient approach to detect association between quantitative traits and bands of DNA fingerprint patterns uses intra-family tail analysis, which compares fingerprints of DNA mixes from individuals at the two tails of a phenotypic distribution. In analysis of 67 paternal half-sibs of a meat-type chicken family, of 57 sire bands generated by two probes, one sire-specific band (S6–6) was associated with abdominal fat deposition. The band effect was estimated by a linear model analysis to be 0–88 standard deviations, or about 30% of the family mean. The association between band S6–6 and abdominal fat was further examined by testing progeny of paternal half-sibs of the chickens which were used in the tail analysis, establishing genetic linkage between the DNA marker and a genetic locus affecting abdominal fat deposition.     

Pulmonary gas exchange kinetics during exercise: physiological inferences of model order and parameters

1. 1. The ventilatory and pulmonary gas exchange responses during moderate exercise can be appropriately modelled with first-order dynamics.

2. 2. A delay term, reflecting tissue-to-lung transit time, is needed for accurate characterization, however.

3. 3. The O₂ uptake time constant ( reflects the enzymatically controlled tissue O₂ utilization.

4. 4. is appreciably longer than , consequent to the tissue CO₂ capacitance.

5. 5. As typically longer than , transient errors in alveolar and arterial blood gas tensions are predicted: small for P_CO2 but much larger for P_O2.

6. 6. At work rates above the lactate threshold, a slow and delayed component of V̇_O2 induces an additional V̇ component (“excess” V̇_O2), leading to more rapid fatigue.

7. 7. The ventilatory compensation for the metabolic acidemia at these work rates is slow, with compensation being poor for rapid-incremental exercise.

8. 8. A justifiable control model of the coupling of ventilation to metabolism must cohere with these demonstrable physiological characteristics.

Ecological and methodological drivers of non-stationarity in tree growth response to climate

Radial tree growth is sensitive to environmental conditions, making observed growth increments an important indicator of climate change effects on forest growth. However, unprecedented climate variability could lead to non-stationarity, that is, a decoupling of tree growth responses from climate over time, potentially inducing biases in climate reconstructions and forest growth projections. Little is known about whether and to what extent environmental conditions, species, and model type and resolution affect the occurrence and magnitude of non-stationarity. To systematically assess potential drivers of non-stationarity, we compiled tree-ring width chronologies of two conifer species, Picea abies and Pinus sylvestris, distributed across cold, dry, and mixed climates. We analyzed 147 sites across the Europe including the distribution margins of these species as well as moderate sites. We calibrated four numerical models (linear vs. non-linear, daily vs. monthly resolution) to simulate growth chronologies based on temperature and soil moisture data. Climate–growth models were tested in independent verification periods to quantify their non-stationarity, which was assessed based on bootstrapped transfer function stability tests. The degree of non-stationarity varied between species, site climatic conditions, and models. Chronologies of P. sylvestris showed stronger non-stationarity compared with Picea abies stands with a high degree of stationarity. Sites with mixed climatic signals were most affected by non-stationarity compared with sites sampled at cold and dry species distribution margins. Moreover, linear models with daily resolution exhibited greater non-stationarity compared with monthly-resolved non-linear models. We conclude that non-stationarity in climate–growth responses is a multifactorial phenomenon driven by the interaction of site climatic conditions, tree species, and methodological features of the modeling approach. Given the existence of multiple drivers and the frequent occurrence of non-stationarity, we recommend that temporal non-stationarity rather than stationarity should be considered as the baseline model of climate–growth response for temperate forests.     

Non-linear loss of suitable wine regions over Europe in response to increasing global warming

Evaluating the potential climatic suitability for premium wine production is crucial for adaptation planning in Europe. While new wine regions may emerge out of the traditional boundaries, most of the present-day renowned winemaking regions may be threatened by climate change. Here, we analyse the future evolution of the geography of wine production over Europe, through the definition of a novel climatic suitability indicator, which is calculated over the projected grapevine phenological phases to account for their possible contractions under global warming. Our approach consists in coupling six different de-biased downscaled climate projections under two different scenarios of global warming with four phenological models for different grapevine varieties. The resulting suitability indicator is based on fuzzy logic and is calculated over three main components measuring (i) the timing of the fruit physiological maturity, (ii) the risk of water stress and (iii) the risk of pests and diseases. The results demonstrate that the level of global warming largely determines the distribution of future wine regions. For a global temperature increase limited to 2°C above the pre-industrial level, the suitable areas over the traditional regions are reduced by about 4%/°C rise, while for higher levels of global warming, the rate of this loss increases up to 17%/°C. This is compensated by a gradual emergence of new wine regions out of the traditional boundaries. Moreover, we show that reallocating better-suited grapevine varieties to warmer conditions may be a viable adaptation measure to cope with the projected suitability loss over the traditional regions. However, the effectiveness of this strategy appears to decrease as the level of global warming increases. Overall, these findings suggest the existence of a safe limit below 2°C of global warming for the European winemaking sector, while adaptation might become far more challenging beyond this threshold.     

How drought events during the last century have impacted biomass carbon in Amazonian rainforests

During the last two decades, inventory data show that droughts have reduced biomass carbon sink of the Amazon forest by causing mortality to exceed growth. However, process-based models have struggled to include drought-induced responses of growth and mortality and have not been evaluated against plot data. A process-based model, ORCHIDEE-CAN-NHA, including forest demography with tree cohorts, plant hydraulic architecture and drought-induced tree mortality, was applied over Amazonia rainforests forced by gridded climate fields and rising CO₂ from 1901 to 2019. The model reproduced the decelerating signal of net carbon sink and drought sensitivity of aboveground biomass (AGB) growth and mortality observed at forest plots across selected Amazon intact forests for 2005 and 2010. We predicted a larger mortality rate and a more negative sensitivity of the net carbon sink during the 2015/16 El Niño compared with the former droughts. 2015/16 was indeed the most severe drought since 1901 regarding both AGB loss and area experiencing a severe carbon loss. We found that even if climate change did increase mortality, elevated CO₂ contributed to balance the biomass mortality, since CO₂-induced stomatal closure reduces transpiration, thus, offsets increased transpiration from CO₂-induced higher foliage area.     

Identifying historical and future global change drivers that place species recovery at risk

Ecosystem management in the face of global change requires understanding how co-occurring threats affect species and communities. Such an understanding allows for effective management strategies to be identified and implemented. An important component of this is differentiating between factors that are within (e.g. invasive predators) or outside (e.g. drought, large wildfires) of a local manager's control. In the global biodiversity hotspot of south-western Australia, small- and medium-sized mammal species are severely affected by anthropogenic threats and environmental disturbances, including invasive predators, fire, and declining rainfall. However, the relative importance of different drivers has not been quantified. We used data from a long-term monitoring program to fit Bayesian state-space models that estimated spatial and temporal changes in the relative abundance of four threatened mammal species: the woylie (Bettongia penicillata), chuditch (Dasyurus geoffroii), koomal (Trichosurus vulpecula) and quenda (Isoodon fusciventor). We then use Bayesian structural equation modelling to identify the direct and indirect drivers of population changes, and scenario analysis to forecast population responses to future environmental change. We found that habitat loss or conversion and reduced primary productivity (caused by rainfall declines) had greater effects on species' spatial and temporal population change than the range of fire and invasive predator (the red fox Vulpes vulpes) management actions observed in the study area. Scenario analysis revealed that a greater extent of severe fire and further rainfall declines predicted under climate change, operating in concert are likely to further reduce the abundance of these species, but may be mitigated partially by invasive predator control. Considering both historical and future drivers of population change is necessary to identify the factors that risk species recovery. Given that both anthropogenic pressures and environmental disturbances can undermine conservation efforts, managers must consider how the relative benefit of conservation actions will be shaped by ongoing global change.     

Evolutionary rescue under demographic and environmental stochasticity

Populations suffer two types of stochasticity: demographic stochasticity, from sampling error in offspring number, and environmental stochasticity, from temporal variation in the growth rate. By modelling evolution through phenotypic selection following an abrupt environmental change, we investigate how genetic and demographic dynamics, as well as effects on population survival of the genetic variance and of the strength of stabilizing selection, differ under the two types of stochasticity. We show that population survival probability declines sharply with stronger stabilizing selection under demographic stochasticity, but declines more continuously when environmental stochasticity is strengthened. However, the genetic variance that confers the highest population survival probability differs little under demographic and environmental stochasticity. Since the influence of demographic stochasticity is stronger when population size is smaller, a slow initial decline of genetic variance, which allows quicker evolution, is important for population persistence. In contrast, the influence of environmental stochasticity is population-size-independent, so higher initial fitness becomes important for survival under strong environmental stochasticity. The two types of stochasticity interact in a more than multiplicative way in reducing the population survival probability. Our work suggests the importance of explicitly distinguishing and measuring the forms of stochasticity during evolutionary rescue.     

Defining null expectations for animal site fidelity

Site fidelity—the tendency to return to previously visited locations—is widespread across taxa. Returns may be driven by several mechanisms, including memory, habitat selection, or chance; however, pattern-based definitions group different generating mechanisms under the same label of ‘site fidelity’, often assuming memory as the main driver. We propose an operational definition of site fidelity as patterns of return that deviate from a null expectation derived from a memory-free movement model. First, using agent-based simulations, we show that without memory, intrinsic movement characteristics and extrinsic landscape characteristics are key determinants of return patterns and that even random movements may generate substantial probabilities of return. Second, we illustrate how to implement our framework empirically to establish ecologically meaningful, system-specific null expectations for site fidelity. Our approach provides a conceptual and operational framework to test hypotheses on site fidelity across systems and scales.