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\begin{document}

\title{A New Formula for Calculating Species Dominance in the Case of
Mosquitoes}



\author[1]{Quanchao Liu}%
\author[2]{Yaming Zou}%
\author[1]{Hui Jin}%
\author[2]{Cejie Lan}%
\affil[1]{Southeast University}%
\affil[2]{Wuxi Center for Disease Control and Prevention}%


\vspace{-1em}



  
  \date{May 27, 2024}


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\selectlanguage{english}
\begin{abstract}
Objective: To explore the calculation method of dominance degree from
biomass, time scale and space scale, so as to provide a reference basis
for more realistic reflection of species dominance degree. Methods:
Excel was used for statistical analysis of mosquito monitoring data in
Wuxi from 2012 to 2021, and t-test was used to test the variability of
three calculation methods, namely Time-Space index, Berger Parker index
and McNaughton index. Results: The three indices of Culex pipiens
pallens and Aedes albopictus were basically consistent, and there was no
significant difference between them; Time-Space index of Culex
tritaeniorhynchus and Anopheles sinensis was significantly lower than
Berger-Parker index (P\textless{}0.05), and was close to the significant
level (P=0.0762, P=0.0621) lower than McNaughton index; The difference
of coefficient of variation among the three calculated results was
4.63\%, which was significantly lower than that of the other three
mosquitoes (P\textless{}0.05). Conclusion: Time-Space index can
significantly improve the resolution of species distribution
heterogeneity, and better reflect the true state of relative dominance
among species.%
\end{abstract}%



\sloppy


\section*{A New Formula for Calculating Species Dominance in the Case of
Mosquitoes}

{\label{a-new-formula-for-calculating-species-dominance-in-the-case-of-mosquitoes}}

\textbf{Objective:} To explore the calculation method of dominance
degree from biomass, time scale and space scale, so as to provide a
reference basis for more realistic reflection of species dominance
degree. \textbf{Methods:} Excel was used for statistical analysis of
mosquito monitoring data in Wuxi from 2012 to 2021, and t-test was used
to test the variability of three calculation methods, namely Time-Space
index, Berger Parker index and McNaughton index. \textbf{Results:} The
three indices of Culex pipiens pallens and Aedes albopictus were
basically consistent, and there was no significant difference between
them; Time-Space index of Culex tritaeniorhynchus and Anopheles sinensis
was significantly lower than Berger-Parker index (P\textless{}0.05), and
was close to the significant level (P=0.0762, P=0.0621) lower than
McNaughton index; The difference of coefficient of variation among the
three calculated results was 4.63\%, which was significantly lower than
that of the other three mosquitoes
(P\textless{}0.05).\textbf{Conclusion:} Time-Space index can
significantly improve the resolution of species distribution
heterogeneity, and better reflect the true state of relative dominance
among species.

Species dominance refers to the status and role of a species in a
biological community, which is used to quantify the dominance of a seed
set on the total abundance of a community \textsuperscript{{[}1{]}}.
Studying the species dominance of a community is helpful to determine
the evenness of species distribution in the community and determine the
dominant species. It is widely used in community ecology research and
species diversity protection. Species dominance is mainly reflected in
the individual number, biomass, volume, frequency and other aspects of
the species. Due to the differences in living conditions, activity types
and other characteristics, different species have different methods to
calculate the dominance. Simpson \textsuperscript{{[}2{]}},
Lloyd\textsuperscript{{[}3{]}}, Austin \textsuperscript{{[}4{]}}, etc.
calculate the species dominance based on the number of individuals and
species in the community; McNaughton index is used to determine the
dominant species of plankton according to the overall occurrence
frequency and individual number of species, and it is also widely used
at present \textsuperscript{{[}5{]}}. From the perspective of material
circulation and energy flow in the ecosystem, species dominance refers
to the degree to which a species in the community has an impact on the
material and energy flow of its niche relative to other species. This
includes three latitudes, one is the proportion of the total amount of
material and energy held by the species in the community, the other is
the scale of the impact of the species on the niche on the time scale,
and the third is the scale of the impact of the species on the niche on
the spatial scale. Due to the spatial and temporal heterogeneity of
species distribution, the species dominance can be better reflected only
when these three influence latitudes are fully considered.

Mosquitoes are important medical insects. Different mosquitoes transmit
different diseases, such as malaria transmitted by Anopheles mosquito,
Zika virus disease transmitted by Aedes mosquito, dengue fever, Japanese
encephalitis transmitted by Culex mosquito, etc. Generally, only when
the vector mosquitoes are in the dominant species can the infectious
diseases become widespread. Therefore, the assessment of mosquito
dominance has a strong early warning effect on the assessment of the
epidemic risk of potential mosquito borne infectious diseases within a
certain niche. At present, when the above two mainstream calculation
methods are used to evaluate the dominance of mosquitoes, the results
are inconsistent with the reality \textsuperscript{{[}6{]}}. This study
will discuss the calculation method of dominance from the above three
latitudes of biomass, time scale and space scale, and compare it with
the current commonly used methods, so as to provide a reference basis
for more realistic reflection of species dominance.

\subsection*{1.Materials and methods}

{\label{materials-and-methods}}

\subsubsection*{1.1 data sources}

{\label{data-sources}}

The research data are mosquito monitoring data of Wuxi from 2012 to
2021. From 2012 to 2015, 5 points will be set for residential areas,
parks and hospitals, 4 points for farmers and livestock sheds, 5 points
for each habitat in 2016, and 4 points for each habitat from 2017 to
2021. Mosquito traps are used to conduct mosquito surveys twice from
March to November per year, and the interval between surveys is more
than 10 days. Classify and count the mosquitoes captured. In this study,
urbanization rate was used to reflect the proportion of different
mosquito habitat types in spatial scale. The urbanization rate from 2012
to 2020 is 72.5, 73.4, 74.6, 76.9, 78.1, 79.8, 80.4, 82.0, 82.8\% and
82.9\% respectively {[}7{]}.

\subsubsection*{1.2 Dominance algorithm}

{\label{dominance-algorithm}}\begin{equation}
D_{i}=\frac{b_{i}}{B}\times\frac{t_{i}}{T}\times\frac{s_{i}}{S}\nonumber \\
 \end{equation}

Where:

D\textsubscript{i} -- relative dominance of species i

B -- Total biomass of all species in the community

b\textsubscript{i} -- total biomass of species i

T -- Total period of time

t\textsubscript{i} -- total time period of occurrence of species i

S --total space coverage

s\textsubscript{i} -- the total spatial coverage of species i

D\textsubscript{i} is the relative dominance of species i, and the value
range is (0,1{]}. When it is 1, it indicates that the material and
energy flow in the target niche is 100\% affected by a species in terms
of biology. T is the total period of time. The length of the specific
period is determined according to the time scale of the study.
t\textsubscript{i} represents the time frequency of species in the total
period. S is the total spatial coverage. According to the total area of
the niche, it is the total spatial coverage of the target area.
s\textsubscript{i} represents the total coverage of species in the area.

\subsubsection*{1.3 Statistical analysis}

{\label{statistical-analysis}}

The proportion of individual number of each mosquito species in each
year is calculated on an annual basis, which is expressed
by\(\frac{n_{i}}{N}\) . The annual occurrence time ratio of each mosquito
species is calculated according to the number of monitored time
sections, which is expressed by \(\frac{t_{i}}{T}\). The spatial coverage
ratio is calculated based on the percentage of points where species
occur, which is expressed by \(\frac{s_{i}}{S}\). Excel is used for
statistical analysis of data, and Adobe Illustrator is used for graphic
layout. \emph{T-test} was used to test the variability of different
calculation methods.

\subsection*{Results}

{\label{results}}

\subsubsection*{2.1 Population and distribution of
mosquitos}

{\label{population-and-distribution-of-mosquitos}}

From 2012 to 2021, the number of monitoring points set varies from 20 to
25, the number of time sections is 18 times a year, 27281 mosquitoes are
captured, and the average mosquito density is 0.6 ind./(lamp.hour).
Mosquitoes mainly include Culex pipiens pallens, Culex
tritaeniorhynchus, Aedes albopictus and Anopheles sinensis. Mosquito
monitoring results over the years are as follows.

Table1 Total number of individuals, number of occurrence points and
number of occurrence time sections of different mosquito species in each
year\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
\emph{Years} & & \emph{Cx. pipiens pallens} & \emph{Cx.
tritaeniorhynchus} & \emph{Aedes albopictus} & \emph{Anopheles sinensis}
& \emph{Armigeres subalbatus} & \emph{Others} &
\emph{Total}\tabularnewline
2012 & occurrences & 23 & 20 & 14 & 15 & 6 & 0 & 23\tabularnewline
& time sections & 17 & 16 & 15 & 15 & 11 & 0 & 18\tabularnewline
& mosquitoes & 3402 & 1759 & 118 & 419 & 42 & 0 & 5740\tabularnewline
2013 & occurrences & 23 & 16 & 8 & 12 & 7 & 0 & 23\tabularnewline
& time sections & 18 & 17 & 14 & 14 & 12 & 0 & 18\tabularnewline
& mosquitoes & 4348 & 4211 & 108 & 1315 & 82 & 0 & 10064\tabularnewline
2014 & occurrences & 23 & 20 & 8 & 11 & 9 & 3 & 23\tabularnewline
& time sections & 18 & 14 & 11 & 10 & 12 & 3 & 18\tabularnewline
& mosquitoes & 1102 & 942 & 34 & 212 & 81 & 5 & 2376\tabularnewline
2015 & occurrences & 22 & 11 & 5 & 7 & 8 & 0 & 23\tabularnewline
& time sections & 17 & 12 & 8 & 12 & 11 & 0 & 18\tabularnewline
& mosquitoes & 741 & 242 & 20 & 44 & 44 & 0 & 1091\tabularnewline
2016 & occurrences & 23 & 13 & 11 & 8 & 6 & 0 & 25\tabularnewline
& time sections & 17 & 15 & 14 & 12 & 8 & 0 & 18\tabularnewline
& mosquitoes & 1026 & 504 & 99 & 74 & 32 & 0 & 1673\tabularnewline
2017 & occurrences & 20 & 12 & 9 & 6 & 6 & 0 & 20\tabularnewline
& time sections & 15 & 15 & 12 & 7 & 11 & 0 & 18\tabularnewline
& mosquitoes & 648 & 486 & 58 & 100 & 48 & 0 & 1340\tabularnewline
2018 & occurrences & 20 & 9 & 11 & 5 & 5 & 2 & 20\tabularnewline
& time sections & 15 & 10 & 12 & 8 & 5 & 2 & 18\tabularnewline
& mosquitoes & 953 & 600 & 63 & 76 & 47 & 15 & 1754\tabularnewline
2019 & occurrences & 20 & 10 & 10 & 5 & 3 & 4 & 20\tabularnewline
& time sections & 17 & 13 & 6 & 8 & 2 & 4 & 18\tabularnewline
& mosquitoes & 1075 & 688 & 42 & 66 & 7 & 28 & 1906\tabularnewline
2020 & occurrences & 19 & 5 & 14 & 6 & 1 & 2 & 20\tabularnewline
& time sections & 18 & 9 & 9 & 8 & 1 & 2 & 18\tabularnewline
& mosquitoes & 496 & 182 & 52 & 29 & 1 & 3 & 763\tabularnewline
2021 & occurrences & 19 & 3 & 11 & 4 & 4 & 0 & 20\tabularnewline
& time sections & 18 & 5 & 13 & 7 & 5 & 0 & 18\tabularnewline
& mosquitoes & 410 & 53 & 83 & 22 & 6 & 0 & 574\tabularnewline
\bottomrule
\end{longtable}

\subsubsection*{2.2 Comparison of three dominance
indices}

{\label{comparison-of-three-dominance-indices}}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1 Comparison of three different dominance indices

Note: \textbf{a-d} represents the calculation results of three dominance
indexes of four mosquitoes in each year. \textbf{e} is the difference
comparison of three dominance indexes of each mosquito
species.\textbf{f} represents the difference of coefficient of variation
of three dominance indices among mosquito species from 2012 to 2021. *
P<0.05;** P<0.01; *** P<0.001.

The results of the three indexes showed that for Culex pipiens pallens
and Aedes albopictus, which were widely distributed in space and time,
the results of the three indexes were basically consistent, and there
was no significant difference between the indexes. For Culex
tritaeniorhynchus and Anopheles sinensis with high spatial and temporal
distribution heterogeneity, the Time-Space index is significantly lower
than Berger Parker index, which is close to the significance level and
lower than McNaughton index (Figure 1e). The difference analysis of
coefficient of variation showed that the three calculation results had
the least impact on Culex pipiens pallens, and the coefficient of
variation was 4.63\%, significantly lower than the other three
mosquitoes.

\subsection*{Discuss}

{\label{discuss}}

There is no significant difference among the three calculation results
of Culex pipiens pallens. The coefficient of variation is significantly
lower than that of other mosquitoes, which may be due to the relatively
uniform spatial and temporal distribution. The average spatial frequency
ratio is 97.8\%, and the temporal frequency ratio is 94.4\% (Table 1).
McNaughton index of Culex tritaeniorhynchus and Anopheles sinensis was
lower than Berger Parker index, but the difference was not significant.
The percentage of occurrence frequency introduced by McNaughton index
failed to significantly distinguish the spatial and temporal
heterogeneity of the distribution of Culex tritaeniorhynchus and
Anopheles sinensis and Culex pipiens pallens respectively. This may be
because McNaughton index uses the overall occurrence frequency. Although
the distribution heterogeneity is considered, the resolution is not
enough to distinguish. The Time-Space index is significantly lower than
Berger Parker index, which may be because the resolution of distribution
heterogeneity is improved after the spatio-temporal factors are
separated. There are also some problems in the application of
Time-Space. The balance of the survey point settings will affect the
index results.

\subsection*{Conclusion}

{\label{conclusion}}

The Time-Space index has significantly improved the resolution of
species distribution heterogeneity, and can better reflect the true
state of relative dominance among species.

{[}1{]} Fung T, Villain L, Chisholm R A. Analytical formulae for
computing dominance from species-abundance distributions {[}J{]}. J
Theor Biol, 2015, 386: 147-58.

{[}2{]} Simpson E H. Measurement of Diversity {[}J{]}. Nature, 1949,
163: 688.

{[}3{]} Ma Z, Ellison A M. A unified concept of dominance applicable at
both community and species scales {[}J{]}. Ecosphere, 2018, 9(11).

{[}4{]} Austin M P. Relationship among functional properties of
California grassland {[}J{]}. Nature, 1968, 217: 163.

{[}5{]} Sun P P, Pan Y L, Liu X, et al. Structure of Zooplankton
Community and Its Relation with Environmental Factors in Rongcheng
Adjacent Waters{[}J{]}. Modern Agricultural Science and Technology,
2019, 10: 6.

{[}6{]} Shen Y, Sun J, Lan C J, et al. Effects of different land use
types on mosquito community {[}J{]}. Chinese Journal of Ecology, 2012,
31(07): 1751-5.

{[}7{]} Wuxi Municipal Bureau of Statistics, Wuxi Survey Team of the
National Bureau of Statistics. Wuxi Statistical Yearbook, 2022 {[}M{]}.
China Statistics Press, 2022.

\textbf{Data Accessibility:}

Monitoring points, mosquito species, quantity and other data:Dryad
doi:10.5521/dryad.12311.

\textbf{Data Availability:}

The data that support the findings of this study are openly available in
Dryad, Dataset, \emph{https://doi.org/10.5061/dryad.rr4xgxdd5}

Conceptualization, L.C. and J.H.;

methodology, L.C.and L.Q.;

software, L.C. and L.Q.;

validation, L.C.;

formal analysis, L.C.;

investigation, L.Q., Z.Y., L.C. and J.H.;

data curation, L.C. and L.Q.;

writing---original draft preparation, L.C. and L.Q.;

writing---review and editing, L.C. and L.Q.;

visualization, L.Q., Z.Y., L.C. and J.H. ;

supervision, L.Q., and Z.Y. ;

project administration, L.C.;

funding acquisition, L.C. and J.H.;

All authors have read and agreed to the published version of the
manuscript.

\selectlanguage{english}
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