方氏云(鱼尉)的排空率研究

在实验室内约 15℃水温下 ,投喂以细长脚 (Themisto gracilip es)为主要成分的天然饵料 ,对成体方氏云 (Enedrias fangi)进行了排空率研究。对 3种排空模型拟合效果的分析显示 ,平方根模型最符合方氏云的排空。在不摄食阶段 ,全消化道内含物的量 (CDW)随时间 (TIME)的变化可以下式描述 :CDW0 .5=3.890 - 0 .175· TIME(R2 =0 .939,p<0 .0 0 0 1)。方氏云的排空率为 0 .175g/10 0 g wet· h。     

Modelling changes in the length–frequency distributions of fish larvae using field estimates of predator abundance and size distributions

The goal of this study is to determine if an individual-based size-dependent model can realistically simulate changes in the length–frequency distributions of several species of fish larvae collected in Conception Bay in 1993 and 1994, using field estimations of growth and predator abundance. We first model the length–frequency distribution of field samples with the best possible estimates of mean growth rate. Then, we add predation mortality given the characteristics of the predator community observed during our surveys, which was composed of macrozooplankton and adult capelin. The larval fish community is generally not affected by predation by macrozooplankton, as the average instantaneous mortality rate predicted by the model was 0.004 day^–1. Fish larvae appear to be more vulnerable to predation by the population of adult capelin. We estimate that an abundance of adult capelin ranging between 0.2 and 1.0 individuals per 1000 m^–3 may have a substantial impact on the larval fish community. The predictions of an individual-based model are directly related to the accuracy of estimates of the mean growth rates of the larval fish cohorts. We find that it is difficult to differentiate size-selective removal of individuals from random selection by analysing changes of the length–frequency distributions of the larval fish community.     

基于四大家鱼产卵需求的汉江中下游生态流量研究

针对汉江中下游梯级电站开发后水文节律变化造成四大家鱼栖息地生境质量降低的问题,分别通过几种常用水文学法和栖息地模型计算了汉江中下游河道最小生态流量和四大家鱼产卵适宜生态流量,并在最小生态流量的基础上,结合四大家鱼产卵适宜生态流量以及生态水文特征在5-8月进行了脉冲设计,综合确定出了满足四大家鱼产卵需求的生态流量过程。结果表明,Lyon法和7Q10法最适宜汉江中下游最小生态流量的计算,流量为294~863 m3/s;通过栖息地模型计算,彭市和仙桃江段四大家鱼产卵适宜生态流量为1233~3950 m3/s;流量日涨幅在139.1~534.8 m3/s,持续5 d的涨水过程可为四大家鱼产卵提供良好的条件。该研究从考虑四大家鱼产卵需求的角度,为汉江中下游梯级电站的生态调度提供科学参考。     

Machine learning highlights the importance of primary and secondary production in determining habitat for marine fish and macroinvertebrates

1. Species distribution models for marine organisms are increasingly used for a range of applications, including spatial planning, conservation, and fisheries management. These models have been constructed using a variety of mathematical forms and drawing on both physical and biological independent variables; however, what might be called first-generation models have mainly followed the form of linear models, or smoothing splines, informed by data collected in the context of fish surveys.
2. The performance of different classes of variables were tested in a series of species occurrence models built with machine learning methods, specifically evaluating the potential contribution of lower trophic level data. Random forest models were fitted based on the classification of the absence/presence for fish and macroinvertebrates surveyed on the US Northeast Continental Shelf.
3. The potential variables included physical, primary production, secondary production, and terrain variables. For accepted model fits, six variable importance measures were computed, which collectively showed that physical and secondary production variables make the greatest contribution across all models. In contrast, terrain variables made the least contribution to these models.
4. Multivariable analyses that account for all performance measures reinforce the role of water depth and temperature in defining species presence and absence; however, chlorophyll concentration and some specific zooplankton taxa, such as Metridia lucens and Paracalanus parvus, also make important contributions with strong seasonal variations.
5. Our results suggest that lower trophic level variables, if available, are valuable in the creation of species distribution models for marine organisms.

     

Numerical modeling of chaotic behavior for small-scale movements of demersal fishes in coastal water

ABSTRACT:   The presented model involves the application of chaos theory to generate fish movements resulting from environmental stimuli. The model uses three steps within a model neural network such as input stimuli, central decision making and response output resulting in fish movements. The stimuli in the first step include the main abiotic and biotic factors, which could be quantified as an intensity parameter that was then normalized as a ratio between 0 and 1. The decision-making process can be generated using chaos dynamics with the stimuli parameters. The response of fish movements from the output signal representing movement speed and direction of fish can be re-regulated as main movement pattern depending on physiological state or life cycle by third response filtering. The simulation results seen as a movement pattern for sea bream and flounder using this neural chaotic model fitted very well to the observations of fish tracked in the sea by ultrasonic tracking methods. It was also revealed that the fish movement components generated as movement velocity and direction when in tidal flow had similar patterns to those patterns seen in field observations with similar irregular and chaotic variations with time.     

河套灌区畦田内不同位置土壤入渗特性及影响因素分析

为明确河套灌区畦田田块不同位置土壤的入渗特性,通过野外试验和室内检测对试验区田块不同位置土壤理化性质和入渗过程进行分析,并基于土壤入渗模型对试验区田块不同位置的土壤入渗过程进行拟合,同时探讨影响土壤入渗过程的影响因素.研究结果表明:试验区田块内不同位置土壤理化性质及入渗特性具有一定差异性且不同位置土壤入渗特性与土壤理化...     

Analysis of series of variety trials with perennial crops

Field trials with perennial crops give rise to repeated measurements taken on the same plot on several occasions. It is important to account for serial correlation among repeated measurements in such trials. This study illustrates the use of mixed models for this purpose. We consider the analysis of trials conducted at several locations and the combination of trials with different starting years. A key issue in the analysis is the distinction between effects of calendar years, which are associated with external environmental variation, and harvest years, which represent internal yield formation processes of the perennial crop. Two methods of two‐stage analysis are compared with single‐stage analysis. It is shown that results of two‐stage analysis are very similar to those of single‐stage analysis, if serial correlation is properly taken into account. Program code for the MIXED procedure of the SAS system is given in an Appendix S1 for all considered cases.     

A temperature-based phenology model for predicting development,survival and population growth potential of the mealybug,Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae)

The temperature-dependent population growth potential of Phenacoccus solenopsis Tinsley, a highly polyphagous and invasive mealybug species, was studied on sprouted potatoes under laboratory conditions at six constant temperatures (15–40 °C). Several non-linear equations were fitted to the obtained data to model temperature-dependent population growth and species life history. The established equations for each life age/stage of the species were compiled to obtain an overall temperature-dependent phenology model. The life table parameters of P. solenopsis were estimated using stochastic simulation centred on a rate summation and cohort up-dating approach. The theoretical lower development threshold temperatures estimated using linear regressions applied to mean development rates were 11.2, 8.9, 9.8 and 12.7 °C, and the thermal constants for development were 93.7, 129.8, 97.1 and 100.0 degree days (DD) for nymph 1, nymph 2, nymph 3 and male pupa stages, respectively. The developed phenology model predicted temperatures between 25 and 35 °C as the favourable range for P. solenopsis development, survival and reproduction. P. solenopsis population attained a maximum net reproductive rate (107–108 females/female/generation) and total fecundity (216.6–226.5 individuals/female/generation) at temperatures between 25 and 30 °C. Mean length of generations decreased from 75.6 days at 15 °C to 21 days at 40 °C. The maximum finite rate of increase (1.12–1.16 females/female/day) and shortest doubling time (4.3–6.1 days) were also observed at temperatures between 25 and 35 °C. The simulation of phenology model at fluctuating temperatures indicated that P. solenopsis populations might potentially increase with a finite rate of 1.06 females/female/day with an average generation time of 58.7 days and a doubling time of 12.1 days. The obtained life table parameters were reasonably similar when compared with literature data. The present model can be simulated spatially for estimating the pest risk and undertaking agro-ecoregion specific pest management strategies.     

云南天然橡胶“走出去”与“替代种植”结合的模式——以云橡公司老挝琅南塔省南塔县梭都村替代搬迁种植务工示范项目为例

着重介绍云橡投资有限公司实施天然橡胶“走出去”与“替代种植”结合的发展模式,在此基础上研究和总结了模式实施的特点,为进一步的深化发展提供理论支持。     

Quantifying and simulating carbon and nitrogen mineralization from diverse exogenous organic matters

The potential contributions of exogenous organic matters (EOMs) to soil organic C and mineral N supply depend on their C and N mineralization, which can be assessed in laboratory incubations. Such incubations are essential to calibrate decomposition models, because not all EOMs can be tested in the field. However, EOM incubations are resource-intensive. Therefore, easily measurable EOM characteristics that can be useful to predict EOM behaviour are needed. We quantified C and N mineralization during the incubation of 663 EOMs from five groups (animal manures, composts, sewage sludges, digestates and others). This represents one of the largest and diversified set of EOM incubations. The C and N mineralization varied widely between and within EOM subgroups. We simulated C and N mineralization with a simple generic decomposition model. Three calibration methods were compared. Individual EOM calibration of the model yielded good model performances, while the use of a unique parameter set per EOM subgroup decreased the model performance, and the use of two EOM characteristics to estimate model parameters gave an intermediate model performance (average RMSE-C values of 32, 99 and 65 mg C g⁻¹ added C and average RMSE-N values of 50, 126 and 110 mg N g⁻¹ added N, respectively). Because of the EOM variability, individual EOM calibration based on incubation remains the recommended method for predicting most accurately the C and N mineralization of EOMs. However, the two alternative calibration methods are sufficient for the simulation of EOMs without incubation data to obtain reasonable model performances.