Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors

To perform landslide susceptibility prediction(LSP),it is important to select appropriate mapping unit and landslide-related conditioning factors.The efficient and automatic multi-scale segmentation(MSS)method proposed by the authors promotes the application of slope units.However,LSP modeling based on these slope units has not been performed.Moreover,the heterogeneity of conditioning factors in slope units is neglected,leading to incomplete input variables of LSP modeling.In this study,the slope units extracted by the MSS method are used to construct LSP modeling,and the heterogeneity of conditioning factors is represented by the internal variations of conditioning factors within slope unit using the descriptive statistics features of mean,standard deviation and range.Thus,slope units-based machine learning models considering internal variations of conditioning factors(variant slope-machine learning)are proposed.The Chongyi County is selected as the case study and is divided into 53,055 slope units.Fifteen original slope unit-based conditioning factors are expanded to 38 slope unit-based conditioning factors through considering their internal variations.Random forest(RF)and multi-layer perceptron(MLP)machine learning models are used to construct variant Slope-RF and Slope-MLP models.Meanwhile,the Slope-RF and Slope-MLP models without considering the internal variations of conditioning factors,and conventional grid units-based machine learning(Grid-RF and MLP)models are built for comparisons through the LSP performance assessments.Results show that the variant Slopemachine learning models have higher LSP performances than Slope-machine learning models;LSP results of variant Slope-machine learning models have stronger directivity and practical application than Grid-machine learning models.It is concluded that slope units extracted by MSS method can be appropriate for LSP modeling,and the heterogeneity of conditioning factors within slope units can more comprehensively reflect the relationships between conditioning factors and landslides.The research results have important reference significance for land use and landslide prevention.

Effects of In-Situ Cadmium Exposure on Morphometric Indices of Anabas testudineus

Anthropogenic activities have greatly affected water resources on a global scale where the world is experiencing water quality and resources issues. Heavy metal is a crucial group of pollutants that is toxic to the environment even at low concentrations due to its bioaccumulation and biomagnification capabilities in living organisms. The detrimental effects of heavy metals on living organisms are due to their bioaccumulation in the aquatic ecosystem. Cadmium may result in adverse health effects due to its high toxicity. The study is conducted to determine the cadmium exposure effects on the morphometric indices of Anabas testudineus which are the Scaling Coefficient (SC) and Condition Factor (K) of such species. Anabas testudineus is exposed to four different cadmium treatment groups namely the control group, cadmium treatment group of 0.005 mg/L, 0.010 mg/L, and 0.015 mg/L for 16 weeks. The findings of the study have reported inconsistent trends in the values of SC and a decrease in the value of K with increasing cadmium concentration. The trend for the average SC has shown an overall decrease in value while the pattern of the K value is inconsistent in each treatment group with exposure time. Collectively, no significant differences for SC and K of A. testudineus in different treatment groups as well as comparison between treatment groups with time exposure.

Length-weight Relationship and Condition Factor of Sarotherodon Melanotheron(Perciformes:cichlidae)from Forcados River Estuary,Niger Delta,Nigeria

Length-weight relationship(LWR),condition factor(k)of the black chin tilapia,Sarotherodon melanotheron(Rüppel,1852)from Forcados River estuary Nigeria was investigated.The fish were collected monthly from fishermen for a period of 24 months(between April 2012 and March 2014).699 specimens of the fish species were collected.The Length-weight relationship(LWR)of the fish was evaluated using the equation:W=a L^(b) while the condition factor of the fish was determined using the equation;K=100W L^(b).The standard length of sampled S.melanotheron ranged from 4.15 to 18.92 cm,total length 6.01 and 22.5 cm while the weight ranged from 7.85-286.71 g.The b value 2.1299 was less than 3 indicating that the growth pattern of the fish was allometric.The correlation co-efficient(r)value for S.melanotheron was 0.7528.The condition factor for the combined sexes fluctuated monthly.The length-weight relationships and condition factor of S.melanotheron in Forcados river estuary indicated that the fish were above average condition.

Impact of Water Deterioration on Growth Indices and Meat Quality of Tilapia zillii and Solea aegyptiaca Fish Inhabiting Lake Qaroun, Egypt

The present work studies water deterioration, fish survival and production as a result of effluents discharged directly without prior treatments into lake Qaroun at Fayoum governorate, Egypt. Lake Qaroun represents heavily polluted wild habitat for both studied fish species, Tilapia zillii and Solea aegyptiaca, the most abundant species. Results revealed deterioration in water quality (low dissolved oxygen but high ammonia, nitrite, copper, lead and cadmium) of Northeastern sector where El-Bats drain discharge its effluents without prior treatment followed by that of eastern sector at four km from the point of El-Bats discharge. Water salinity and dissolved oxygen values were in the following order: Western lake Qaroun sector > Eastern lake Qaroun sector > Northeastern lake Qaroun sector. However, Ammonia and nitrite readings were in the following order: Northeastern sector of Lake Qaroun is followed by the Eastern sector, then the Western sector. Moreover, results of the present field study revealed a decrease in fish production with the lowest condition factor and a deterioration in meat quality (an increase in muscle water content and ash but a decrease total protein and total lipids) in case of fish collected from the polluted sites along the lake (Northeastern and eastern sectors). However, fish collected from the unpolluted western sector of the lake showed condition factor and chemical muscle composition more or less similar to normal healthy fish.

Development of a region-partitioning method for debris flow susceptibility mapping

Debris flow susceptibility mapping(DFSM)has been reported in many studies,however,the irrational use of the same conditioning factor system for DFSM in regional-scale has not been thoroughly resolved.In this paper,a region-partitioning method that is based on the topographic characteristics of watershed units was developed with the objective of establishing multiple conditioning factor systems for regional-scale DFSM.First,watershed units were selected as the mapping units and created throughout the entire research area.Four topographical factors,namely,elevation,slope,aspect and relative height difference,were selected as the basis for clustering watershed units.The k-means clustering analysis was used to cluster the watershed units according to their topographic characteristics to partition the study area into several parts.Then,the information gain ratio method was used to filter out superfluous factors to establish conditioning factor systems in each region for the subsequent debris flow susceptibility modeling.Last,a debris flow susceptibility map of the whole study area was acquired by merging the maps from all parts.DFSM of Yongji County in Jilin Province,China was selected as a case study,and the analytical hierarchy process method was used to conduct a comparative analysis to evaluate the performance of the region-partitioning method.The area under curve(AUC)values showed that the partitioning of the study area into two parts improved the prediction rate from 0.812 to 0.916.The results demonstrate that the region-partitioning method on the basis of topographic characteristics of watershed units can realize more reasonable regional-scale DFSM.Hence,the developed region-partitioning method can be used as a guide for regional-scale DFSM to mitigate the imminent debris flow risk.

Some Aspects of Ecology of Chrysichthys nigrodigitatus (Lacepede) in River Niger, Nigeria

A study on the food and feeding habit of Chrysichthys nigrodigitatus （Lacepede） was conducted in River Niger within the region of Oshimili local government area of Delta State Nigeria. A total of 90 specimens were collected with the help of fishermen using gill net, cast net and traps. The fish samples were immediately taken to the laboratory for analysis. Morphometric characteristics such as weight, length, condition factor, egg weight, Gonado Somatic Index （GSI） and sex ratio were determined. The stomach content was analyzed using numerical method to determine the food content. The total length of the fish sampled ranged from 14.40-44.60 cm, while the standard length varied from 11.00 cm to 47.00 cm and the fish body weight ranged between 19.00 g to 503.20 g. Sex ratio 1 female to 1 male was observed. The mean condition factor for both male and female obtained was 1.67. Of all the 90 fishes sampled, none had empty gut representing 100%. The major food items were phytoplankton, plant part and Detritus. Out of 41 females sampled, only 17 had eggs and the eggs were matured at stage IV.

Abundance and Distribution,Growth Pattern,Sex Ratio and Gonadosomatic Index(GSI)of Liza falcipinnis(Valenciennes,1836)from Ojo Axis of Badagry Creeks,Lagos,Nigeria

A study on seasonal abundance,morphometric and meristic data,growth pattern,condition fector,sex ratio and gonadosomatic index of Liza falcip-innis(Wlenciennes,1836)from the Ojo axis of Badagry creek,Nigeria was conducted from May 2019 to March 2020.A total of 1012 species were randomly selected,having 499 females and 513 males.The length frequency analysis and length-weight relationships(LWR)were determined.Sex ratio was determined by Chi-square analysis.The results showed that morphometric data are:0.5-2.5 mm for ED,2.1-12 mm for HL,1.7-8.1 mm for HD,2.5-11.7 for BD,2.6-233.3 mm for TL and 9.23-1006 g for BW for the combined sexes.The slope(b)shows an allometric growth pattern.The intercept'a'and slope'b'of the LWR(LogW=a+bLogL)were Log W=15.39+0.34 LogL(r=0.54)for combined sexes,Log W=12.49+0.02 log L(r=0.38)for males and Log W=18.23+0.01 log L(r=0.16)for females.The length frequency distribution indicated that species were dominated by two year classes(Ages 1 and 2).Condition factors were generally low.The values ranged between 0.68-0.85 for combined sexes.The gonadosomatic index for female was highest in August,2019(17.77%)with Mean±SD of 2.88±0.75;which indicated the peak of spawning period in the study area.Sex ratio difference was significant(P<0.05).Sexual differences were significant;the females are phenotypically larger than the male.

Influence of the changing environment on food composition and condition factor in Labeo victorianus(Boulenger,1901)in rivers of Lake Victoria Basin,Kenya

Labeo victorianus(Boulenger,1901)is one of the endemic fishes in Lake Victoria Basin(LVB)but is now threatened by multiple stressors caused by human activities.We investigated spatial and temporal variability in food composition and condition of L.victorianus in influent rivers of Lake Victoria,Kenya.Sampling was done during the dry and wet seasons by electrofishing.Food composition analysis showed that L.victorianus is a benthophagus and omnivorous species whose diet is dominated by detritus,periphyton and insects.There were differences in food composition among rivers,with significant river X season interactions(PERMANOVA F=11.6,df=4,p=0.001),suggesting that the diet depended on prevailing environmental conditions.In turbid rivers,the diet was dominated by detritus while in less turbid rivers it was dominated by insects and periphyton.Sand and mud also formed a significant part of the diet,which was an indication of a limited occurrence of preferable food items.There were ontogenetic shifts in food composition(PERMANOVA F=4.6,df=3,p=0.001),but also with a spatial interaction(PERMANOVA F=5.6,df=7,p=0.001),further indicating the role of environmental conditions in determining the diet for different size classes.Interestingly,the fish condition did not differ among rivers.This study shows that turbidity and organic matter and nutrient loading determine the diet of L.victorianus in LVB rivers,and provides further justification for the maintenance of water quality as a conservation measure for threatened species.

On Maximal Abelian Self-adjoint Subalgebras of Factors of Type II_1

In this note, we show that if N is a proper subfactor of a factor M of type Ⅱ1 with finite Jones index, then there is a maximal abelian self-adjoint subalgebra （masa） A of N that is not a masa in ,M. Popa showed that there is a proper subfactor R0 of the hyperfinite type Ⅱ1 factor R such that each masa in R0 is also a masa in R. We shall give a detailed proof of Popa＇s result.

A multidisciplinary method to assess the reproductive biology of Mystus bleekeri

The study aims to afford a deeper knowledge on reproductive biology of Mystus bleekeri from Surma River,Bangladesh in a multidisciplinary way.Though,the species is in demand as food and ornamental fish in Bangladesh but still now comprehensive details on reproductive biology of this species is scanty.Total 600 fish samples were derived from commercial catches from July 2018 to June 2019.Periodic differences in sex ratio,size distribution,condition factor(Kn),fecundity,gonadosomatic index and gonadal maturation cycle were assessed.The results showed 384(64%)female and 216(36%)male with an overall sex ratio of 1.77:1(female:male).Mean total length(TL)and body weight(BW)of all fish studied were 14.85±3.38 cm TL and 27.54±15.76 g,respectively.The Kn varied with length groups,the highest(1.45±0.23)and lowest(0.89±0.18)values obtained in 16.0-16.9 and 10.0-10.9 cm TL groups,respectively.The highest Kn was documented in October while the lowest was in January.Monthly GSI values showed two peaks in July and November for both the sexes.The fecundity was found to vary from 1120 to 14790 eggs with average value of 4968±3047 with 14.4-18.3 cm in TL and 19.97-34.7g in BW.The relationship of fecundity with TL and BW was F=1.385TL13.405,r^(2)=0.885 and F=5.201BW^(4.827),r^(2)=0.944.Partial behavior of spawning together with allochronic oocytes development has also been found through histology.The results of this study could be used for predicting the response of populations of fish in Surma River and/or other where to human interferences and environmental change.

Uncertainties of landslide susceptibility prediction:Influences of different spatial resolutions,machine learning models and proportions of training and testing dataset

This study aims to reveal the impacts of three important uncertainty issues in landslide susceptibility prediction(LSP),namely the spatial resolution,proportion of model training and testing datasets and selection of machine learning models.Taking Yanchang County of China as example,the landslide inventory and 12 important conditioning factors were acquired.The frequency ratios of each conditioning factor were calculated under five spatial resolutions(15,30,60,90 and 120 m).Landslide and non-landslide samples obtained under each spatial resolution were further divided into five proportions of training and testing datasets(9:1,8:2,7:3,6:4 and 5:5),and four typical machine learning models were applied for LSP modelling.The results demonstrated that different spatial resolution and training and testing dataset proportions induce basically similar influences on the modeling uncertainty.With a decrease in the spatial resolution from 15 m to 120 m and a change in the proportions of the training and testing datasets from 9:1 to 5:5,the modelling accuracy gradually decreased,while the mean values of predicted landslide susceptibility indexes increased and their standard deviations decreased.The sensitivities of the three uncertainty issues to LSP modeling were,in order,the spatial resolution,the choice of machine learning model and the proportions of training/testing datasets.

Some aspects of the biology of the female blue crab Callinectes amnicola(De Rocheburne)from the Cross River estuary,Nigeria

Objective:To investigate some important aspects of the biology of Callinectes amnicola(C.amnicola)such as fecundity,carapace length-weight relationship,condition factor and carapace length frequency distribution from the Cross River estuary,Nigeria.Methods:A total of one hundred and twenty ovigerous females of C.amnicola,freshly caught with basket traps,lift net trap,and gill net were collected from the catches of the artisanal fisheries in the study area between June 2012 and May 2013.Fecundity,carapace length-weight relationship,condition factor and carapace length frequency distribution were determined and analyzed following standard methods.Results:Fecundity(F)ranged between 73090 eggs for crab of carapace length 8.1 cm and total weight 34 g and 809450 eggs for crab of carapace length 16.1 cm and total weight 395 g with a mean of 311808.93±17693.94 eggs.There was a positive significant relationship between fecundity and carapace length,total weight and condition factor as follows:F=6839.7CL^(1.4403)(r^(2)=0.2145,P<0.05),F=15302TW^(0.5798)(r^(2)=0.4079,P<0.05),F=147255K^(0.2788)(r=0.2717,r^(2)=0.0738,P<0.05).A significant linear relationship between carapace length and weight of C.amnicola is given by the equation:Log W=2.0447LogL–0.1389(r^(2)=0.3357,P<0.05).The crab exhibited a negative allometric growth pattern(b=2.0447).Condition factor ranged between 21.48 to 104.95 with a mean value of 47.21±2.17.The carapace length frequency distribution showed a unimodal class size distribution.Conclusions:Findings of this study is crucial in assessing the population dynamics and development of management strategies of the the Blue crab,C.amnicola from the estuary such as mesh size regulation,fishing season and fishing ground regulation in the Cross River estuary.Also,findings of this study will be useful in evaluation of the aquaculture potential of the Blue crab C.amnicola,which is a valuable shell fish for the inhabitants estuary.

Biometrics of the rare fish Rhinomugil corsula(Hamilton,1822)(Mugiliformes:Mugilidae)in the Ganges,Northwestern Bangladesh

Objective:To investigate biometrics of the Rhinomugil corsula(Hamilton,1822)(R.corsula),including length-weight relationships(LWRS),condition factors(Allometric,K_(A);Fulton's,K_(F);Relative,K_(R);Relative weight,W_(R)),and sex ratio and length-frequency distributions in the Ganges(Padma River),Northwestern Bangladesh.Methods:Monthly sampling was conducted using traditional fishing gears during June to August 2012.Total length was measured to the nearest 0.01 cm using digital slide calipers,and total body weight was measured using an electronic balance with 0.01 g accuracy.The LWR was calculated using the expression:W=a×L_(b),where the W is the body weight,L is the total length,a and b are the parameters of the regression.Results:A total of 350 specimens ranging from 8.59-15.71 cm in total length and 9.57-32.59 g in body weight were analyzed during this study.The overall sex ratio was not significantly different from the expected value of 1:1(X^(2)=2.57,P>0.05),but there was significant difference in the length-frequency distributions between the sexes(P=0.03).The allometric coefficient b for the LWR indicated negative allometric growth(b=3.00)in males,female and combined sexes.Results further indicated that Kr was not significantly different between the sexes(P=0.57).However,the mean W_(R)of R.corsula showed significant differences from 100 for males(P=0.03)and females(P<0.001)in this study,indicating the imbalance habitat with food availability relative to the presence of predators.Conclusions:This study reported the first description of biometric relationships for R.corsula,which would be useful for the sustainable conservation of this rear fishery in Bangladesh and also neighboring countries.