Dimensionless analysis of the microbial growth rate dependence on sub-optimal temperatures

The influence of sub-optimal temperatures (T) on the microbial growth rate (μ) has been assessed by means of dimensionless variables: T_dim = [T−T_min]/[T_opt−T_min] and μ_dim = μ/μ_opt. T_min represents the temperature at which there is no growth, T_opt the optimum temperature at which the growth rate, μ_opt, is maximum. Data sets, growth rate vs temperature, have been taken from the literature for 12 organisms (psychrotrophs, mesophiles and thermophiles). In order to compare these organisms, the power law function has been used: [μ_dim] = [T_dim]^α. The parameters μ_opt and T_opt are determined from direct readings whereas T_min and αare estimated by means of a non-linear regression. An accurate estimation of T_min is obtained providing low growth rate data are available. A wide range of optimal temperatures where the growth rate almost equals μ_opt prevents one from obtaining a narrow confidence interval forα. On the basis of the analysis hereafter developed, thermophiles are characterized by values of the power α less than mesophiles and psychrotrophs. Almost all of these values are significantly different from two, previously determined for Staphylococcus xylosus and widely used for predicting the microbial growth in foods. Received 15 May 1998/ Accepted in revised form 25 September 1998     

Diminished Confidence Levels in the Interval Estimation of an Unknown Regressor in Model I of Linear Regression

For the model y=β₀ + β₁ x + e (model I of linear regression) in the literature confidence estimators of an unknown position x₀ are given at which either the expectation of y is given (see FIELLER, 1944; FINNEY, 1952), or realizations of y are given (see GRAYBILL, 1961). These confidence regions with level 1—α need not be intervals. The occurrence of interval shape is a random event. Its probability is equal to the power of the t test for the examination of the hypothesis H: β₁ = 0. The papers mentioned above claim to provide confidence intervals with level 1 ? α. But because of the restriction of (1 —α)—confidence regions to intervals the true confidence probability is the conditional probability W_c: W_c = P (the confidence region covers x₀| the region has interval shape). Here this conditional probability is shown to be less than 1 —α. Evidence on the possible deviations from 1 —α has been obtained by simulations.     

Temperature‐dependent development of Neoseiulus barkeri (Acari: Phytoseiidae) on Tetranychus urticae (Acari: Tetranychidae) at seven constant temperatures

Abstract The effect of seven constant temperatures of 15, 20, 25, 27, 30, 35 and 37°C on developmental time of Neoseiulus barkeri Hughes were determined in laboratory conditions under 65%± 5% RH and a photoperiod of 12 : 12 (L : D) h on nymphal stages of Tetranychus urticae Koch. Total developmental time of females (from egg to adult emergence) at the above‐mentioned temperatures was 26.59, 14.43, 6.32, 5.64, 4.59, 3.98 and 4.67 days, respectively. Developmental rate of the N. barkeri increased as temperature increased from 15 to 35°C, but declined at 37°C. A linear and two nonlinear models were fitted to developmental rate of immature stages of N. barkeri to predict the developmental rate as a function of temperature, as well as to estimate the thermal constant (K) and critical temperatures (i.e., T_min, T_opt and T_max). The estimated values of the T_min and K for total developmental time using the linear model were 12.07°C and 86.20 degree‐days (DD), respectively. The T_min and T_max estimated by the Sharpe‐Schoolfield‐Ikemoto (SSI) model were 11.90°C and 37.41°C, respectively. The estimated T_opt for overall immature stage development of N. barkeri by the Lactin and SSI models were 33.89°C and 24.51°C, respectively. Based on the biological criteria of model evaluation, the linear and SSI models were found to be the best models for describing the developmental rate of overall immature stages of N. barkeri and estimating the temperature thresholds.     

Reduced diurnal temperature range does not change warming impacts on ecosystem carbon balance of Mediterranean grassland mesocosms

Daily minimum temperature (T_min) has increased faster than daily maximum temperature (T_max) in many parts of the world, leading to decreases in diurnal temperature range (DTR). Projections suggest that these trends are likely to continue in many regions, particularly in northern latitudes and in arid regions. Despite wide speculation that asymmetric warming has different impacts on plant and ecosystem production than equal‐night‐and‐day warming, there has been little direct comparison of these scenarios. Reduced DTR has also been widely misinterpreted as a result of night‐only warming, when in fact T_min occurs near dawn, indicating higher morning as well as night temperatures. We report on the first experiment to examine ecosystem‐scale impacts of faster increases in T_min than in T_max, using precise temperature controls to create realistic diurnal temperature profiles with gradual day–night temperature transitions and elevated early morning as well as night temperatures. Studying a constructed grassland ecosystem containing species native to Oregon, USA, we found that the ecosystem lost more carbon at elevated than ambient temperatures, but remained unaffected by the 3 °C difference in DTR between symmetric warming (constantly ambient + 3.5 °C) and asymmetric warming (dawn T_min = ambient + 5 °C, afternoon T_max = ambient + 2 °C). Reducing DTR had no apparent effect on photosynthesis, probably because temperatures were most different in the morning and late afternoon when light was low. Respiration was also similar in both warming treatments, because respiration temperature sensitivity was not sufficient to respond to the limited temperature differences between asymmetric and symmetric warming. We concluded that changes in daily mean temperatures, rather than changes in T_min/T_max, were sufficient for predicting ecosystem carbon fluxes in this reconstructed Mediterranean grassland system.     

Seasonally different response of photosynthetic activity to daytime and night‐time warming in the Northern Hemisphere

Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night‐time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in the response of NDVI to changes in day‐ vs. night‐time temperatures. For instance, while higher daytime temperature (T_max) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between T_max and NDVI is much larger in spring (41% of area in boreal zone – total area 12.6 × 10⁶ km²) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in T_max, increases in T_max tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night‐time temperature (T_min) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day‐ and night‐time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Understanding the seasonally different responses of vegetation photosynthetic activity to diurnal temperature changes, which have not been captured by current land surface models, is important for improving the performance of next generation regional and global coupled vegetation‐climate models.     

Short‐term survival and movements of Atlantic sharpnose sharks captured by hook‐and‐line in the north‐east Gulf of Mexico

Ultrasonic telemetry was used to compare post‐release survival and movements of Atlantic sharpnose sharks Rhizoprionodon terraenovae in a coastal area of the north‐east Gulf of Mexico. Ten fish were caught with standardized hook‐and‐line gear during June to October 1999. Atlantic sharpnose sharks were continuously tracked after release for periods of 0·75 to 5·90 h and their positions recorded at a median interval of 9 min. Individual rate of movement was the mean of all distance and time measurements for each fish. Mean ± s.e . individual rate of movement was 0·45 ± 0·06 total lengths per second (L_T s^?1) and ranged from 0·28 to 0·92 L_T s^?1 over all fish. Movement patterns did not differ between jaw and internally hooked Atlantic sharpnose sharks. Individual rate of movement was inversely correlated with bottom water temperature at capture (r² = 0·52, P ≤ 0·05). No consistent direction in movement was detected for Atlantic sharpnose sharks after release, except that they avoided movement towards shallower areas. Capture‐release survival was high (90%), with only one fish not surviving, i.e. this particular fish stopped movement for a period of 10 min. Total rate of movement was total distance over total time (m min^?1) for each Atlantic sharpnose shark. Mean total rate of movement was significantly higher immediately after release at 21·5 m min^?1 over the first 1·5 h of tracking, then decreased to 11·2 m min^?1 over 1·5–6 h, and 7·7 m min^?1 over 3–6 h (P ≤ 0·002), which suggested initial post‐release stress but quick recovery from capture. Thus, high survival (90%) and quick recovery indicate that the practice of catch‐and‐release would be a viable method to reduce capture mortality for R. terraenovae.     

Adaptation of soil microbial growth to temperature: Using a tropical elevation gradient to predict future changes

Terrestrial biogeochemical feedbacks to the climate are strongly modulated by the temperature response of soil microorganisms. Tropical forests, in particular, exert a major influence on global climate because they are the most productive terrestrial ecosystem. We used an elevation gradient across tropical forest in the Andes (a gradient of 20°C mean annual temperature, MAT), to test whether soil bacterial and fungal community growth responses are adapted to long‐term temperature differences. We evaluated the temperature dependency of soil bacterial and fungal growth using the leucine‐ and acetate‐incorporation methods, respectively, and determined indices for the temperature response of growth: Q₁₀ (temperature sensitivity over a given 10oC range) and T_min (the minimum temperature for growth). For both bacterial and fungal communities, increased MAT (decreased elevation) resulted in increases in Q₁₀ and T_min of growth. Across a MAT range from 6°C to 26°C, the Q₁₀ and T_min varied for bacterial growth (Q_10–20 = 2.4 to 3.5; T_min = ?8°C to ?1.5°C) and fungal growth (Q_10–20 = 2.6 to 3.6; T_min = ?6°C to ?1°C). Thus, bacteria and fungi did not differ significantly in their growth temperature responses with changes in MAT. Our findings indicate that across natural temperature gradients, each increase in MAT by 1°C results in increases in T_min of microbial growth by approximately 0.3°C and Q_10–20 by 0.05, consistent with long‐term temperature adaptation of soil microbial communities. A 2°C warming would increase microbial activity across a MAT gradient of 6°C to 26°C by 28% to 15%, respectively, and temperature adaptation of microbial communities would further increase activity by 1.2% to 0.3%. The impact of warming on microbial activity, and the related impact on soil carbon cycling, is thus greater in regions with lower MAT. These results can be used to predict future changes in the temperature response of microbial activity over different levels of warming and over large temperature ranges, extending to tropical regions.     

Strong impacts of daily minimum temperature on the green‐up date and summer greenness of the Tibetan Plateau

Understanding vegetation responses to climate change on the Tibetan Plateau (TP) helps in elucidating the land–atmosphere energy exchange, which affects air mass movement over and around the TP. Although the TP is one of the world's most sensitive regions in terms of climatic warming, little is known about how the vegetation responds. Here, we focus on how spring phenology and summertime greenness respond to the asymmetric warming, that is, stronger warming during nighttime than during daytime. Using both in situ and satellite observations, we found that vegetation green‐up date showed a stronger negative partial correlation with daily minimum temperature (T_min) than with maximum temperature (T_max) before the growing season (‘preseason’ henceforth). Summer vegetation greenness was strongly positively correlated with summer T_min, but negatively with T_max. A 1‐K increase in preseason T_min advanced green‐up date by 4 days (P < 0.05) and in summer enhanced greenness by 3.6% relative to the mean greenness during 2000–2004 (P < 0.01). In contrast, increases in preseason T_max did not advance green‐up date (P > 0.10) and higher summer T_max even reduced greenness by 2.6% K^?1 (P < 0.05). The stimulating effects of increasing T_min were likely caused by reduced low temperature constraints, and the apparent negative effects of higher T_max on greenness were probably due to the accompanying decline in water availability. The dominant enhancing effect of nighttime warming indicates that climatic warming will probably have stronger impact on TP ecosystems than on apparently similar Arctic ecosystems where vegetation is controlled mainly by T_max. Our results are crucial for future improvements of dynamic vegetation models embedded in the Earth System Models which are being used to describe the behavior of the Asian monsoon. The results are significant because the state of the vegetation on the TP plays an important role in steering the monsoon.     

Physiological mechanism governing slow and fast development in predatory ladybirds

Aphidophagous and coccidophagous ladybirds, similar to their prey, show marked differences in their pace of life (Dixon, 2000), in particular in their rate of development, with all stages of aphidophagous species developing much faster than those of coccidophagous species. Two hypotheses are proposed to account for the large difference in the pace of life of these two groups. These are that differences in the rate of development are a result of differences in lower temperature thresholds for development or the quality of their respective prey as food (Dixon et al., 2011). Analysis of published results on the rates of development of the eggs of ladybirds indicates that the inverse relationships between the number of day‐degrees required for development (K) and the lower temperature threshold for development (td_min) of these two groups are significantly different. In particular, the respective td_min overlap and K of the aphidophagous and coccidophagous species with a similar td_min are, on average, 38 and 117 day‐degrees (D^o). The relationship between the rate of development (R) and temperature (T) for aphids reared on poor‐ or high‐quality foods indicates that, although the value of td_min of a species depends on food quality, K does not, showing that it is unlikely that K is governed by food quality. Thus, there is little support for differences in either the td_min or food quality governing the difference in the pace of life of these two groups of ladybirds. The results indicate that the physiological mechanism that may govern the difference in the pace of life between these two groups is the number of day‐degrees (K) needed to complete their development. The possible evolutionary reason for this is discussed.     

Estimating the Effect of Cropland to Prairie Conversion on Peak Storm Run-Off

Much of the original U.S. grassland has undergone conversion to cropland. During the last few years, large first‐ and second‐order watershed scale projects have begun to reconstruct the native tallgrass prairie cover and biodiversity. The effect on watershed hydrological budget is largely unknown, especially concerning storm run‐off. Curve number variability is used to estimate the uncertainty of peak run‐off following the change in cover, given rainfall recurrence and watershed size. The method involves three steps: (1) estimate the time‐of‐concentration for many similar sized watersheds in the region, (2) define the probability distribution for time‐of‐concentration, curve numbers, and watershed area, (3) with these data, generate input variables for a Monte Carlo analysis, which can then be used to predict the mean and confidence interval of peak run‐off. As an example, spatial and hydrological characteristics of first‐ and second‐order watersheds ranging from 2 to 50 km² in the Red River of the North basin provide a log normal probability distribution for time‐of‐concentration. Using the range of watershed area and a β probability distribution for curve number uncertainty, the analysis predicts the change in peak run‐off from an ensemble of watershed realizations that characterize cropland to grassland conversion. Results suggest that given five‐ and 25‐year, 24‐hour rainfall recurrence, average reduction in peak run‐off will range from 50 to 55% and 40 to 45%, respectively, for the basin. A large range of uncertainty at the 80% confidence interval, however, indicates that an accurate prediction requires analysis for specific watersheds.     

Confidence Intervals of the Attributable Risk under Cross‐Sectional Sampling with Confounders

Since it can account for both the strength of the association between exposure to a risk factor and the underlying disease of interest and the prevalence of the risk factor, the attributable risk (AR) is probably the most commonly used epidemiologic measure for public health administrators to locate important risk factors. This paper discusses interval estimation of the AR in the presence of confounders under cross‐sectional sampling. This paper considers four asymptotic interval estimators which are direct generalizations of those originally proposed for the case of no confounders, and employs Monte Carlo simulation to evaluate the finite‐sample performance of these estimators in a variety of situations. This paper finds that interval estimators using Wald's test statistic and a quadratic equation suggested here can consistently perform reasonably well with respect to the coverage probability in all the situations considered here. This paper notes that the interval estimator using the logarithmic transformation, that is previously found to consistently perform well for the case of no confounders, may have the coverage probability less than the desired confidence level when the underlying common prevalence rate ratio (RR) across strata between the exposure and the non‐exposure is large (≥4). This paper further notes that the interval estimator using the logit transformation is inappropriate for use when the underlying common RR ≐ 1. On the other hand, when the underlying common RR is large (≥4), this interval estimator is probably preferable to all the other three estimators. When the sample size is large (≥400) and the RR ≥ 2 in the situations considered here, this paper finds that all the four interval estimators developed here are essentially equivalent with respect to both the coverage probability and the average length.     

A new mathematical model to simulate AVA cold-induced vasodilation reaction to local cooling

The purpose of this work was to integrate a new mathematical model with a bioheat model, based on physiology and first principles, to predict thermoregulatory arterio-venous anastomoses (AVA) and cold-induced vasodilation (CIVD) reaction to local cooling. The transient energy balance equations of body segments constrained by thermoregulatory controls were solved numerically to predict segmental core and skin temperatures, and arterial blood flow for given metabolic rate and environmental conditions. Two similar AVA–CIVD mechanisms were incorporated. The first was activated during drop in local skin temperature (<32 °C). The second mechanism was activated at a minimum finger skin temperature, T _{CIVD, min}, where the AVA flow is dilated and constricted once the skin temperature reached a maximum value. The value of T _CIVD,min was determined empirically from values reported in literature for hand immersions in cold fluid. When compared with published data, the model predicted accurately the onset time of CIVD at 25 min and T _CIVD,min at 10 °C for hand exposure to still air at 0 °C. Good agreement was also obtained between predicted finger skin temperature and experimentally published values for repeated immersion in cold water at environmental conditions of 30, 25, and 20 °C. The CIVD thermal response was found related to core body temperature, finger skin temperature, and initial finger sensible heat loss rate upon exposure to cold fluid. The model captured central and local stimulations of the CIVD and accommodated observed variability reported in literature of onset time of CIVD reaction and T _CIVD,min.     

BEHAVIORAL THERMOREGULATION OF THE NEW ZEALAND SEA LION (PHOCARCTOS HOOKERI)

Behavioral thermoregulation of New Zealand sea lions (Phocarctos hookeri) was studied at a male haul‐out ground at Papanui Beach, Otago Peninsula, New Zealand. The proportion of time spent by sea lions in each of five postures (prone, curled, oblique, ventral‐up, dorsal‐up) and also with the number of flippers exposed or tucked (hind and fore) at different black‐bulb temperature (T_bb°C) ranges was recorded. Use of prone and curled postures (0–1 flippers exposed) declined as T_bb increased, suggesting that these are adopted to conserve heat; oblique and dorsal‐up postures (3–4 flippers exposed) use increased with T_bb indicating a role in heat dissipation. The transition between heat conserving and heat dissipating postures occurred at about 14°–20°C (T_bb). Both foreflipper and hind flipper exposure increased with T_bb and the trends were similar, but overall hind flipper exposure was 89% of foreflipper exposure. The results show that surface area of flippers exposed to air is largely controlled by postural adjustment. The increase in flipper exposure with T_bb provides evidence of behavioral thermoregulation and that flippers are major sites for heat loss in the New Zealand sea lion, as observed for other otariid species. Nonpostural thermoregulatory behaviors such as flipper waving and sand flipping increased with T_bb, and may provide additional means of dissipating heat. Total body surface areas of six sea lions ranged from 1.72 to 3.39 m² (curvilinear length range from 1.60 to 2.35 m), and total flipper surface area averaged 22.7% of total body surface area. As otariids do not employ their hind limbs for aquatic propulsion, their role in behavioral thermoregulation may provide an explanation for the relatively large size of the hind flippers of the New Zealand sea lion.     

Relationships of microclimatic variables to colonization of rose debris by Botrytis cinerea and the biocontrol agent Clonostachys rosea

Biological control of Botrytis cinerea by Clonostachys rosea is an alternative to chemical control of rose Botrytis blight in greenhouses. Environmental conditions affect the colonization of senescing and dead tissues by both fungi. The contribution of microclimatic variables to debris colonization/sporulation by both fungi was estimated by path coefficient analysis. We monitored daily values of: maximum, average, and minimum temperatures (T _max, T _ave, and T _min), and relative humidity (RH_max, RH_ave, and RH_min); accumulated rainfall; vapour pressure deficit average; hours with RH?>?90% (RH₉₀); and average temperature during RH₉₀ (T _ave90). Association of variables accumulated between the first and seventh day before sampling explained colonization/sporulation variation: R ²=0.81–0.86 for B. cinerea and 0.91–0.96 for C. rosea. RH_max and RH₉₀ were the main factors that directly favoured colonization/sporulation of both fungi. Colonization/sporulation negatively correlated with RH_min, T _min, and T _ave for B. cinerea and T _min, T _ave, and T _ave90 for C. rosea. The antagonist can suppress B. cinerea colonization/sporulation on rose debris under a wide range of environmental conditions.     

Acute effect of thyroid hormones in mimicking photoperiodically induced release of gonadotropins in Japanese quail

Summary Photoperiodic induction occurs in Japanese quail after exposure to a single long day and this leads to a wave of pituitary LH secretion which lasts for up to 10 days. Pharmacological doses of thyroid hormones mimic this photoperiodic response if given to quail on short days, the magnitude and duration of the rise in LH and FSH output being dose-dependent. Thyroxine (T₄) is some 7 times more potent than tri-iodothyronine (T₃). There is no effect of T₄ on LH secretion in quail already on long days although such birds can increase LH output markedly if treated with Gn-RH. Testosterone prevents the initial rise in LH secretion following T₄ but does not block the long-term effect, suggesting that T₄ acts high in the photoneuroendocrine chain to mimic long days. The first rise in LH secretion following T₄ injection takes place about 24 h after the injection and the time-scale of secretion is quite similar to that seen when quail are exposed to a long day. T₄ elicits a rise in LH secretion even if the quail are maintained in darkness. However, T₄ does not act simply as light for if it is given at the exact time when birds are in a photoinducible state (i.e. 12–16 h after dawn) the rise in LH secretion still occurs 24 h later.Abbreviations FSH follicle stimulating hormone - Gn-RH gonadotropin releasing hormone - LH luteinizing hormone - T ₄ thyroxine - T ₃ tri-iodothyronine     

Triiodothyronine Stimulates the Expression of Sucrase–Isomaltase in Caco-2 Cells Cultured in Serum-Free Medium

In a previous study we have shown that triiodothyronine (T₃) added to a serum-free medium supplemented with insulin, transferrin, and selenous acid (ITS) can stimulate Caco-2 cell differentiation. In this study we have focused on the effects of T₃on sucrase activity. The results obtained demonstrate that T₃(50 nM) does not change Caco-2 cell proliferation but enhances sucrase activity from 50 to 80%. Similar increases were observed whether or not insulin was present in the culture medium, showing that there was no synergistic effect between T₃and insulin on sucrase activity. Moreover, T₃acts specifically during the differentiation period since addition of T₃to the defined TS medium before confluency is reached does not stimulate sucrase activity. Sucrase kinetic parameters were evaluated for the first time in Caco-2 cells under various culture conditions. The presence of a single enzyme was verified, with aK_mof about 7 mMand aV_maxaround 20 nmol of substrate hydrolyzed min⁻¹mg⁻¹of protein. Our results showed that T₃did not change the enzyme's affinity for sucrose but doubled theV_max. Moreover, immunoblotting using anti-sucrase–isomaltase (SI) antibodies revealed an approximately twofold increase in the relative amount of SI immunoreactive protein in T₃-stimulated cells compared to untreated cells. Results obtained by both Northern hybridization and RT-PCR amplification showed a significant increase in SI mRNA contents. These results suggest that T₃acts primarily on sucrase expression at the mRNA level.     

Determination of leaf heat resistance: comparative investigation of chlorophyll fluorescence changes and tissue necrosis methods

Summary Heat tolerance limits for a variety of vascular plant leaves were determined both with the conventional post-culture necrosis method and by measurements of the heat-induced increase in chlorophyll fluorescence (F-T curves). The reliability of the fluorescence test was improved with the addition of far-red background light which counteracts dark reduction of the Photosystem II acceptor pool by heat-stimulated endogenous electron donors. This was of particular importance in the case of xeromorphic leaves in which the diffusion barrier for oxygen is high. A satisfactory correlation was found between T _L50, the temperature at which a 30 min exposure results in 50% necrotic leaf area following post culture, and the critical temperature, T _c ,the temperature at which the dark fluorescence level begins to increase during slow heating of a leaf sample at a rate of 0.7 K min^-1, in the fluorescence test. The correlation can be described by a linear function, T _L50=1.12 T _c -5.37,with a correlation coefficient, r=0.87. Maximal deviation of the regression line from the line T _L50=T _c was 1.2 K, with 22 determinations for leaves with widely varying heat tolerance limits. This shows that heat-induced fluorescence changes within the thylakoid membrane may be connected with the irreversible leaf tissue damage which occurs following prolonged exposure to high temperature. On the basis of the heat dosage equation of Lepeschkin, a more general expression can be obtained which allows calculation of the accumulated heat dosage under the experimental conditions of the standard fluorescence test (slow heating, 0.7 K min^-1). Such calculations reveal that for a given species the fraction of critical dosage begins to increase, i.e. accumulating heat reaches an injurious level, at a temperature which approximately coincides both with T _L50, obtained with the necrosis method, and with T _c ,the critical temperature derived from the fluorescence test. Hence, the increase in fraction of critical dosage and the rise in chlorophyll fluorescence seem to concur. It is concluded that the fluorescence assay provides a rapid and reliable means of determining the heat tolerance limit of leaf tissue.     

Disentangling factors limiting diamondback moth,Plutella xylostella (L.), spatio‐temporal population abundance: A tool for pest forecasting

Data‐mining techniques play an important role in hyperparameter optimization of heterogeneous environmental factors and their relative contribution as determinants of incidences in insect pest ecological studies. A multidimensional field‐based surveillance was conducted in two seasons (24 months), July–June of each season (2015/2016 ‐ season 1 and 2016/2017 ‐ season 2) using sex‐pheromone‐baited traps and Thermocron i‐Buttons to identify key determinants of population abundance of diamondback moth, Plutella xylostella L., across spatial horticultural hotspots of Botswana. The moth is a notorious global brassica pest. Pearson's product moment correlation matrix showed month of the year (M), mean temperature (T_mean) and maximum temperature (T_max) as positively correlated (p < 0.001) to number of moths (N), while minimum temperature (T_min), minimum relative humidity (RH_min), mean relative humidity (RH_mean), maximum relative humidity (RH_max) and host plant (h) were negatively correlated (p < 0.001) to N. Using Waikato Environment for Knowledge Analysis (WEKA) data‐mining techniques, two models were developed: (a) M5P decision‐tree algorithm associated with nine linear models (LMs) and (b) principal component analysis (PCA) based on four principal components. Both approaches identified M as the major predictor of moth abundance, followed by h and farming region (R). However, R was a function of T_max (positive auto‐correlation) and RH_max (negative auto‐correlation). These results provide simplified relative contribution of heterogeneous factors in influencing P. xylostella spatio‐temporal abundance, essential for early warning systems in pest management. This is an important component of sustainable pest management aimed at managing insect pests and minimizing pesticides abuse in brassica production systems.     

A confidence interval for the unknown value of the regressor with given expectation of the regressand in model I of linear regression

In the case of model I of linear regression there is derived a confidence interval for that x_o where the “true line” will reach a given value y_o. The interval can be given by the intersections between the line y = y_o and the hyperbolas providing pointwise confidence intervals of the expectations of y.