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Citation: B˘al˘acenoiu, F.; Toma, D.;
Net
,oiu, C. From Field Data to
Practical Knowledge: Investigating
the Bioecology of the Oak Lace
Bug—An Invasive Insect Species in
Europe. Insects 2023,14, 882. https://
doi.org/10.3390/insects14110882
Academic Editors: Muhammad
Haseeb and Lambert H.B. Kanga
Received: 13 October 2023
Revised: 7 November 2023
Accepted: 15 November 2023
Published: 15 November 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
insects
Article
From Field Data to Practical Knowledge: Investigating the
Bioecology of the Oak Lace Bug—An Invasive Insect Species
in Europe
Flavius Bălăcenoiu 1, * , Dragos
,Toma 1,2 and Constantin Net
,oiu 1
1National Institute for Research and Development in Forestry “Marin Dracea”, Eroilor 128,
077190 Voluntari, Romania; dragost93@gmail.com (D.T.); c_netoiu@yahoo.com (C.N.)
2Faculty of Silviculture and Forest Engineering, Transilvania University of Bras
,ov, Sirul Beethoven 1,
500123 Bras
,ov, Romania
*Correspondence: flavius.balacenoiu@icas.ro
Simple Summary:
In a world filled with diverse ecosystems, understanding the behaviour of invasive
species is crucial for maintaining balance and health. This study delves into the bioecology of the
invasive oak lace bug in Europe, shedding light on its life cycle through a degree day-based model
and presenting insights gathered from field-based life tables. Our research addresses key knowledge
gaps, offering valuable information for effective pest control in forest ecosystems. By bridging the
gap between scientific exploration and practical implications, we aim to empower the public with
accessible knowledge on how to protect European forests and maintain the delicate equilibrium of
natural environments.
Abstract:
Corythucha arcuata, commonly known as the oak lace bug (OLB), is an insect species
originally native to North America that has become an invasive species of significant concern in
Europe. This invasive pest has been observed in various European countries, raising concerns about
its impact on forest ecosystems. In 2015, it was first documented in Romania, further highlighting
the need for research on its bioecology and life cycle. This study investigated the bioecology of the
OLB in the southern region of Romania, focusing on its life cycle, development, and population
dynamics. The results indicated that the OLB has three generations per year and overwinters
in the adult stage in sheltered locations. Temperature significantly influenced the timing of egg
hatching, nymph appearance, and adult development, with variation observed between generations.
Additionally, a life table analysis provided insights into the population dynamics of the OLB in
its natural environment, revealing variation in egg laying trends across generations. This research
contributes to a better understanding of the OLB’s bioecology and provides essential data for forest
managers developing science-based management strategies to mitigate its impact. By elucidating
the life cycle and development patterns of the OLB in southern Romania, this study aids in the
development of predictive models and life tables tailored to the region. These findings empower forest
managers with the knowledge needed to make informed decisions for effective OLB management,
ultimately preserving the health of forest ecosystems.
Keywords: biological invasions; insect pests; development model; degree days; forest management
1. Introduction
A species that is introduced to a new territory by human activities, whether deliber-
ately or unintentionally, is considered an alien species [
1
–
4
]. If such a species manages to
reproduce, spread rapidly (at considerable distances from the introduction site), and have
a negative impact on the newly occupied territory, it becomes an invasive alien species,
and the phenomenon is defined as a biological invasion [
1
–
8
]. These invasive alien species
Insects 2023,14, 882. https://doi.org/10.3390/insects14110882 https://www.mdpi.com/journal/insects
Insects 2023,14, 882 2 of 18
can cause a wide range of negative effects on the environment, economy, and human
health [5,8–16].
Furthermore, invasive alien species are considered a major factor in the extinction of
certain species, posing a significant threat to biodiversity [
17
,
18
]. Kenis & Branco [
19
] argue
that, although European forest ecosystems are less affected by invasive species than forests
in other continents, a wide variety of potentially harmful invasive species has recently
become established in European forests. They have a substantial impact on society and
the bioeconomy, posing challenges to sustainable forest management and necessitating
effective management strategies.
Corythucha arcuata (Say, 1832) (Hemiptera, Tingidae), commonly known as the oak
lace bug (OLB), is an insect of North American origin that is considered an invasive alien
species in Europe. Its natural range extends across the southern part of Canada and several
states in the eastern USA [
20
,
21
]. According to studies conducted in the Nearctic region of
North America [
20
,
21
], it develops on host plants such as Quercus alba L., Quercus macrocarpa
Michaux, Quercus montana Willdenow, Quercus muehlenbergii Engelmann, Quercus prinoides
Willdenow, Quercus rubra L., and other species of Quercus (Fagaceae). Additionally, the insect
has occasionally been observed on host species from the genera Acer,Malus, and Rosa.
In Europe, the OLB was first observed in northern Italy in 2000 [
22
]. Two years
later, in 2002, it was documented in southern Switzerland in flight interception traps
set between April and July [
23
]. In the same year (2002), the OLB was also detected in
Turkey, approximately 200 km east of Istanbul [
24
]. In 2005, a specimen of this species
was identified in Iran [
25
]. For several years, the OLB was not reported in new countries,
but in 2012, it was observed for the first time in Bulgaria [
26
], followed by sightings in
Hungary [
27
], Croatia [
28
], and Serbia [
29
,
30
] in 2013. In 2015, the insect was first observed
in Russia, in Krasnodar [
31
]. Additionally, in August 2015, it was reported for the first time
in Romania [
32
,
33
]. In the following year, 2016, Corythucha arcuata was observed for the
first time in several countries, including Albania [
34
] and Slovenia [
35
]. In 2017, it appeared
in three new countries: Bosnia and Herzegovina [
36
], France [
37
], and Ukraine [
34
,
38
]. In
May 2018, the OLB was first reported in northeastern Greece [
34
], and, in June 2018, in
southern Slovakia [
39
]. A study in 2019 confirmed the presence of the insect in 21 locations
in Austria [40].
In the context of biological invasions caused by insects in forest ecosystems, under-
standing pest behaviour can contribute to identifying favourable conditions for outbreak
initiation, enabling forest managers to make science-based decisions regarding species
control. To manage a pest effectively and scientifically, it is necessary to identify the feed-
back processes that regulate its population [
41
,
42
]. In the implementation of integrated
pest management, obtaining information regarding pest population abundance and the
environmental conditions in which a pest thrives is essential, as is understanding the factors
that influence population development [43,44].
Based on the aforementioned considerations, we believe that in-depth research on the
bioecology of the OLB is necessary. Hence, our primary objective was to contribute to the
advancement of the scientific understanding of the bioecology of this invasive forest insect
species. The expected outcomes of this work included obtaining a definitive description
of the insect’s life cycle, the generation of an insect development prediction model based
on degree days, and the development of life tables in the natural environment of the OLB.
Using our new insights into the bioecology of the OLB, forest managers will be able to
make informed decisions regarding the management of forests and this invasive species
based on Romania-specific scientific foundations.
2. Materials and Methods
2.1. Study Area and Data Collection
To achieve our objectives, an intensive monitoring approach was employed to track
the hatching and development of individuals, transitions between stages, and temporal
variation in the number of individuals at each stage across all three generations. Con-
Insects 2023,14, 882 3 of 18
sequently, during the 2020–2021 vegetation seasons, we set up an experiment based on
controlled growth of C. arcuata, spanning from egg to adult, covering the progression from
the first generation to the third generation at the conclusion of the cycle.
Although the experiment was centred around the controlled growth of insects, to
ensure the monitored individuals could develop under favourable conditions, they were
reared in a natural setting. To fulfil this objective, within the National Institute for Research
and Development in Forestry “Marin Drăcea” Nursery (NIRDF), two identical plots were
selected (Figure 1). In Plot 1, insects from the first and third generations were reared, while
in Plot 2, insects from the second generation were reared. These plots were positioned ap-
proximately 50 metres apart and exclusively featured common oak saplings (approximately
10 years old), which greatly facilitated the monitoring process (Figure 2a).
Insects2023,14,xFORPEERREVIEW3of18
variationinthenumberofindividualsateachstageacrossallthreegenerations.Conse-
quently,duringthe2020–2021vegetationseasons,wesetupanexperimentbasedoncon-
trolledgrowthofC.arcuata,spanningfromeggtoadult,coveringtheprogressionfrom
thefirstgenerationtothethirdgenerationattheconclusionofthecycle.
Althoughtheexperimentwascentredaroundthecontrolledgrowthofinsects,to
ensurethemonitoredindividualscoulddevelopunderfavourableconditions,theywere
rearedinanaturalseing.Tofulfilthisobjective,withintheNationalInstituteforRe-
searchandDevelopmentinForestry“MarinDrăcea”Nursery(NIRDF),twoidentical
plotswereselected(Figure1).InPlot1,insectsfromthefirstandthirdgenerationswere
reared,whileinPlot2,insectsfromthesecondgenerationwerereared.Theseplotswere
positionedapproximately50metresapartandexclusivelyfeaturedcommonoaksaplings
(approximately10yearsold),whichgreatlyfacilitatedthemonitoringprocess(Figure2a).
Figure1.Mapsofthelocationsofthestudyandexperimentalplots(Esri,Maxar,EarthstarGe-
ographics,andtheGISUserCommunity).
(a)(b)
Figure2.Experimentalgrowthenvironmentandinsectisolation:(a)Controlledgrowthenviron-
mentinexperimentalplots;(b)clothbagsdesignedforcontrolledgrowthofinsects.
Figure 1.
Maps of the locations of the study and experimental plots (Esri, Maxar, Earthstar Geograph-
ics, and the GIS User Community).
Insects2023,14,xFORPEERREVIEW3of18
variationinthenumberofindividualsateachstageacrossallthreegenerations.Conse-
quently,duringthe2020–2021vegetationseasons,wesetupanexperimentbasedoncon-
trolledgrowthofC.arcuata,spanningfromeggtoadult,coveringtheprogressionfrom
thefirstgenerationtothethirdgenerationattheconclusionofthecycle.
Althoughtheexperimentwascentredaroundthecontrolledgrowthofinsects,to
ensurethemonitoredindividualscoulddevelopunderfavourableconditions,theywere
rearedinanaturalseing.Tofulfilthisobjective,withintheNationalInstituteforRe-
searchandDevelopmentinForestry“MarinDrăcea”Nursery(NIRDF),twoidentical
plotswereselected(Figure1).InPlot1,insectsfromthefirstandthirdgenerationswere
reared,whileinPlot2,insectsfromthesecondgenerationwerereared.Theseplotswere
positionedapproximately50metresapartandexclusivelyfeaturedcommonoaksaplings
(approximately10yearsold),whichgreatlyfacilitatedthemonitoringprocess(Figure2a).
Figure1.Mapsofthelocationsofthestudyandexperimentalplots(Esri,Maxar,EarthstarGe-
ographics,andtheGISUserCommunity).
(a)(b)
Figure2.Experimentalgrowthenvironmentandinsectisolation:(a)Controlledgrowthenviron-
mentinexperimentalplots;(b)clothbagsdesignedforcontrolledgrowthofinsects.
Figure 2.
Experimental growth environment and insect isolation: (
a
) Controlled growth environment
in experimental plots; (b) cloth bags designed for controlled growth of insects.
To isolate the insects, cloth bags designed for controlled growth were crafted, allowing
individuals to develop under favourable conditions. Each bag contained a pair comprising
one male and one female, and the bag was subsequently sealed and attached to a tree
Insects 2023,14, 882 4 of 18
(Figure 2b). Following the numbering and marking of the bags, they were monitored every
1–3 days; we documented any changes relative to the previous observation.
For each generation, a minimum of 35 bags (70 male–female pairs) were installed, with
their placement occurring at different times depending on the generation (Table 1).
Table 1. Installation dates of cloth bags.
Year Generation Date
2020
I 5 May 2020
II 7 July 2020
III 6 August 2020
2021
I 1 May 2021
II 1 July 2021
III 1 August 2021
To monitor the development of Generation I, pairs of adults from the overwintering
generation were selected. These adults were isolated after they emerged from hibernation,
immediately upon becoming active, in the plot designated for Generation I. Subsequently,
each bag was intensively monitored until the emergence of the adults. Among the adults
resulting from the first generation, additional pairs were selected to develop Generation II.
In early July, these pairs were transferred and isolated in the plot designated for Generation
II. As with the previous generation, each bag was intensively monitored until the indi-
viduals of Generation II reached adulthood. Finally, among the adults resulting from the
first generation, additional pairs were selected, and in early August, they were transferred
and isolated in the plot designated for Generation III. The process continued as with the
previous generations, with each pair being intensively monitored until the individuals of
Generation III reached adulthood. The selection of male–female pairs from one generation
to the next was conducted to avoid inbreeding.
Climatic data were obtained from the meteorological station at the NIRDF, which is
located approximately 100 metres from the plots where the monitoring was conducted.
Initially, we collected a comprehensive set of climatic data, including minimum and maxi-
mum temperatures, as well as average values. Subsequently, we focused on specific factors
relevant to our research objectives.
2.2. Developing the Insect Development Prediction Model Based on Degree days
The degree day calculation was conducted using the mean method (1) [
45
–
48
], which inte-
grates both the daily minimum and maximum temperatures, along with the base temperature.
DD =Tmax +Tmin
2−Tb (1)
where:
DD = accumulated degree days for a day;
Tmax = maximum temperature of the respective day;
Tmin = minimum temperature of the respective day;
Tb = base temperature specific to the pest.
Insect development occurs within the climatic range between the lower and upper
temperature thresholds (characteristic each species) and halts when the temperature drops
below this lower limit. In the calculation of degree days, the temperature corresponding
to the lower threshold is used as the “base temperature”. Considering that a specific
base temperature for the pest C. arcuata was not identified upon reviewing the specialized
literature, a value of 50
◦
F, equivalent to 10
◦
C, was adopted. This value is recommended
for species for which the lower threshold has not been determined [48].
Therefore, if the daily average temperature is one degree above the base temperature
of 10
◦
C, it means that one degree day has accumulated on that day. Negative results (when
Insects 2023,14, 882 5 of 18
the daily average temperature is below 10
◦
C) are disregarded. At the beginning of the
season, degree days accumulate slowly, but as the daily average temperature starts to rise,
the degree day value increases exponentially [
48
]. Data for calculating degree days were
collected starting from 1 January.
For example, in the conditions of the year 2020, until 2 February, no daily average
temperature exceeded the threshold of 10
◦
C. On 2 February, the daily average temperature
was 11.78
◦
C, and on 3 February, it was 11.95
◦
C. Applying the mean method (1), starting
from 1 January 2020 to 3 February, 3.73 degree days were accumulated.
Using the mean method (1), during the period from 2020 to 2021, the number of degree
days accumulated until the appearance of each developmental stage of each monitored pair
was observed for all three developed generations. Thus, by considering all the resulting data,
it was possible to create a predictive model for insect development based on degree days.
2.3. Constructing the Life Table of the Insect Population in a Natural Environment
We employed the “age-specific” life table method to construct the life table, also
known as the “horizontal table”. This method involves tracking the development of a real,
controlled cohort of individuals within the population, all belonging to the same generation
and age group, without overlapping with other generations [
49
]. Given that many insects
exhibit discrete generations and non-stationary populations (as is the case with OLB), the
age-specific life table is more widely applicable than the time-specific life table [50].
For each of the three generations, the construction of the life table started with the
total number of pairs established and introduced into the experiment (N
0
). Additionally, in
designing the life table, only the number of successful pairs was considered. The number of
successful pairs (N) is represented by the number of pairs that successfully completed the
development cycle of the respective generation. For example, if one of the pairs encountered
developmental issues in the later nymph stages or even in the adult stage due to abiotic
factors, it was excluded from the final calculation so as not to negatively influence the
construction of the life table.
Furthermore, in designing the life table, for each developmental stage and generation,
the completion criteria developed by Harcourt [
51
] were considered. The aim was to
determine the average number of eggs per pair (lx
eggs
), the mortality and infertility of the
eggs (dx
eggs
), the average number of nymphs (lx
nymphs
), the mortality of nymphs (dx
nymphs
),
the average number of adults (lx
adults
), the sex ratio (lx
female
), and the generation survival
(GS). However, it is important to emphasize that we adapted this methodology to align
it with the specific developmental cycle of OLB, as outlined in Table A1. By doing so, we
aimed to tailor the methodology to the unique characteristics of this insect species, ensuring
that the life table reflects the intricacies of its life stages and development.
To determine the gender and age of OLB individuals, we relied on the well-documented
morphology studied and described extensively, both in its native habitat of North Amer-
ica since the early 20th century [
21
,
52
] and in regions recently invaded in Europe and
Asia [22,53].
2.4. Data Analyses
As an initial step, the normality of the distribution of the count data was verified
using Shapiro–Wilk tests, while homogeneity of variance was assessed using Levene’s test.
Given that the results of these tests confirmed the assumptions of a normal distribution and
homogeneity of variance, the data met the requirements for parametric tests. We proceeded
to the second step, in which a two-way analysis of variance (ANOVA) was applied.
Data analysis was performed using Statistica 8.0 software (StatSoft Inc, 2007).
3. Results
3.1. Life Cycle and Number and Durations of Generations
According to the observations conducted in the climatic conditions of southern Roma-
nia, the OLB had three generations per year and overwintered in the adult stage in sheltered
Insects 2023,14, 882 6 of 18
locations. The observations made on the insect in the controlled growth experiment in a
natural environment allowed for the construction of a phenogram that represents the life
cycle of the OLB in the forests of southern Romania (Figure 3).
1
Figure 3.
Insect phenology in the environmental context of southern Romania. A= overwintering
adults; A = active adults; E = eggs; N = nymphs. Green = the first generation; blue = the second
generation; red = the third generation.
Overwintered adults, originating from the previous year, became active in the second
week of April, when they emerged from sheltered locations (such as cracks in bark) and
flew to reach the newly developed leaves of host trees. They fed until the end of May, when
females laid their first eggs. Females continued to lay eggs in multiple batches until the
end of June, when the first nymphs of the first generation, originating from the first-laid
eggs, appeared at the beginning of June. Although the nymphs developed very quickly,
they continued to emerge until the end of July, hatching from eggs laid later. In late June,
the first adults of the first generation had already appeared, and this emergence process
continued until mid-July. Adults of the first generation could survive until October.
The second generation began in early July, with the first eggs being laid by adults of
the first generation. Females continued to lay eggs until the beginning of August. The
first nymphs of the second generation started emerging at the end of July and continued
to appear until the beginning of August. In the first part of August, adults of the second
generation appeared; this process continued until the end of August. Our observations
showed that adults of the second generation could survive until the end of the growing
season, with the hardiest individuals overwintering along with those of the third generation.
The third generation began in the second half of August, when the first eggs were laid
by adults of the second generation. Egg laying continued until the middle of September.
Nymphs appeared at the end of August, coinciding with the hatching of the first eggs,
and continued to emerge until second half of September. It is important to note that not
all nymphs developed into adults, and some persisted until early November. Adults
of the third generation appeared in the second half of September and were active for a
month, after which they withdrew for overwintering before resuming the development
cycle described above in the following year.
3.2. Using Degree Days to Predict Insect Development
According to the model developed, the hatching of eggs, appearance of nymphs, and
development of adults were influenced by temperature and showed significant variation
between generations (Figure 4).
Insects 2023,14, 882 7 of 18
Insects2023,14,xFORPEERREVIEW7of18
3.2.UsingDegreeDaystoPredictInsectDevelopment
Accordingtothemodeldeveloped,thehatchingofeggs,appearanceofnymphs,and
developmentofadultswereinfluencedbytemperatureandshowedsignificantvariation
betweengenerations(Figure4).
Figure4.Insectdevelopmentpredictionmodelbasedondegreedays.A=adults;E=eggs;N=
nymphs.Green=thefirstgeneration;blue=thesecondgeneration;red=thethirdgeneration.
Fortheappearanceofeggsgivingrisetothefirstgeneration,aminimumof135de-
greedayswasrecorded,buteggscontinuedtoappearforupto517degreedays(both
valuesrecordedin2021).Untiltheappearanceofthefirstnymphs,aminimumof317and
amaximumof762degreedayswererecorded(bothin2021).Adultsofthefirstgeneration
requiredaminimumof408degreedays,buttheycontinuedtoappearuntilnearly900
degreedays(observationsfrom2021).
Fortheappearanceofeggsofthesecondgeneration,aminimumof604degreedays
wasnecessary,buteggscontinuedtoappearforuptoalmost1100degreedays.Nymphs
appearedfrom762degreedaysto1354degreedays(bothvaluesrecordedin2021).The
firstadultsofthesecondgenerationappearedstartingaftertheaccumulationof931de-
greedaysandcontinuedtoappearuntil1500degreedays(accordingtodatafrom2021).
Fortheappearanceofeggsgivingrisetothethirdgeneration,1180degreedayswere
required(recordedin2021),buteggscontinuedtoappearforuptonearly1600degree
days(recordedin2020).Nymphsneededaminimumof1190degreedaysbutcontinued
toappearforuptoalmost1700degreedays(observationsfrom2020).Thefirstadultsof
thethirdgenerationappearedaftertheaccumulationof1346degreedays(recordedin
2021),andthelastadultsappearedafter1733degreedays(accordingtodatafrom2020).
3.3.LifeTab leoftheInsectPopulationinaNaturalEnvironment
Ourstatisticalanalysisofthedatafromthe2020observations,aspresentedinFigure5
andTab le2,showedthatadultsfromtheoverwinteredgenerationgavebirthtothefirst
generation,layinganaverageof38.9eggsperpair.Thesuccessrateofthefirstegglaying
was56%,resultinginanaverageof21.6first-instarnymphsperpairfromeachegglaying.
Afterprogressingthroughthefivenymphalstages,anaverageof14.1adultsemerged,
with40%ofthembeingfemales.In2021,adultsfromtheoverwinteredgenerationlaidan
averageof25.9eggsperpair,whichgaveriseto24.3nymphsonaverage(asuccessrate
of94%),resultingin21.1adults,withhalfofthembeingfemales.
Figure 4.
Insect development prediction model based on degree days. A = adults; E = eggs;
N = nymphs. Green = the first generation; blue = the second generation; red = the third generation.
For the appearance of eggs giving rise to the first generation, a minimum of 135 degree
days was recorded, but eggs continued to appear for up to 517 degree days (both values
recorded in 2021). Until the appearance of the first nymphs, a minimum of 317 and a
maximum of 762 degree days were recorded (both in 2021). Adults of the first genera-
tion required a minimum of 408 degree days, but they continued to appear until nearly
900 degree days (observations from 2021).
For the appearance of eggs of the second generation, a minimum of 604 degree days
was necessary, but eggs continued to appear for up to almost 1100 degree days. Nymphs
appeared from 762 degree days to 1354 degree days (both values recorded in 2021). The
first adults of the second generation appeared starting after the accumulation of 931 degree
days and continued to appear until 1500 degree days (according to data from 2021).
For the appearance of eggs giving rise to the third generation, 1180 degree days were
required (recorded in 2021), but eggs continued to appear for up to nearly 1600 degree
days (recorded in 2020). Nymphs needed a minimum of 1190 degree days but continued to
appear for up to almost 1700 degree days (observations from 2020). The first adults of the
third generation appeared after the accumulation of 1346 degree days (recorded in 2021),
and the last adults appeared after 1733 degree days (according to data from 2020).
3.3. Life Table of the Insect Population in a Natural Environment
Our statistical analysis of the data from the 2020 observations, as presented in Figure 5
and Table 2, showed that adults from the overwintered generation gave birth to the first
generation, laying an average of 38.9 eggs per pair. The success rate of the first egg laying
was 56%, resulting in an average of 21.6 first-instar nymphs per pair from each egg laying.
After progressing through the five nymphal stages, an average of 14.1 adults emerged,
with 40% of them being females. In 2021, adults from the overwintered generation laid an
average of 25.9 eggs per pair, which gave rise to 24.3 nymphs on average (a success rate of
94%), resulting in 21.1 adults, with half of them being females.
After isolating other pairs obtained from the first generation in 2020, an average of
58.4 eggs per pair was found; this number was significantly higher than the number of eggs
from the previous generation in the same year (p= 0.047). The success rate of egg laying
was 66%, resulting in an average of 38.4 first-instar nymphs per pair from a single egg
laying. After passing through the five nymphal stages, the nymphs produced an average
of 27.4 adults per pair, with 50% of them being females; this number was significantly
higher than in the previous generation from the same year (p= 0.049). In 2021, for the
development of a new generation, the first generation laid an average of 94.6 eggs; this was
Insects 2023,14, 882 8 of 18
significantly higher than in the previous generation (p< 0.001). Furthermore, an average
of 75.3 nymphs was found, from which an average of 70.1 adults developed, with half of
them being females; this number was significantly higher than in the previous generation
(p< 0.001).
Insects2023,14,xFORPEERREVIEW8of18
Figure5.Trendsintheinsectpopulationacrossgenerations.Thedifferencesbetweenthemeans
(markedwithleersA,B,C,andD)werestatisticallysignificant(p<0.05),accordingtoatwo-way
ANOVA.
Tab le2.Developmentalprogressiontablefortheoaklacebugpopulation.
IndexTheGenerationof2020TheGenerationof2021
GIGIIGIIIGIGIIGIII
N′ 40130110707070
N284844464818
𝑙𝑥38.9±558.4±5.855±4.225.9±4.294.6±10.352.1±8.9
𝑑𝑥44.5%34.3%4.7%6.2%20.5%34.3%
𝑙𝑥 21.6±2.838.4±5.552.4±4.424.3±5.275.3±8.734.2±10.6
𝑑𝑥 17.9%11.6%4.5%6.3%5.1%9.1%
𝑙𝑥 17.7±2.630.7±4.550.5±4.622.7±5.171.4±8.731.1±10.4
𝑑𝑥 10.1%9.6%3.6%5.4%0.9%10.4%
𝑙𝑥 15.9±2.629.2±4.348.2±4.621.5±570.7±8.627.9±10.5
𝑑𝑥 6.3%4.6%1.6%1.2%0.5%8.4%
𝑙𝑥 14.9±2.728.2±4.247.5±4.721.3±570.4±8.625.6±10.6
𝑑𝑥 3.3%3.6%1.3%0.4%0.2%2.2%
𝑙𝑥 14.6±2.727.4±4.246.8±4.821.2±570.2±8.625±10.7
𝑑𝑥 2%3%0.6%0.4%0.2%32.4%
𝑙𝑥14.1±2.827.4±4.246.5±4.821.1±570.1±8.616.9±11.5
𝑑𝑥0.40.50.50.50.50.5
GS36%47%85%81%74%32%
Afterisolatingotherpairsobtainedfromthefirstgenerationin2020,anaverageof
58.4eggsperpairwasfound;thisnumberwassignificantlyhigherthanthenumberof
eggsfromthepreviousgenerationinthesameyear(p=0.047).Thesuccessrateofegg
layingwas66%,resultinginanaverageof38.4first-instarnymphsperpairfromasingle
egglaying.Afterpassingthroughthefivenymphalstages,thenymphsproducedanav-
erageof27.4adultsperpair,with50%ofthembeingfemales;thisnumberwassignifi-
cantlyhigherthaninthepreviousgenerationfromthesameyear(p=0.049).In2021,for
thedevelopmentofanewgeneration,thefirstgenerationlaidanaverageof94.6eggs;this
wassignificantlyhigherthaninthepreviousgeneration(p<0.001).Furthermore,anav-
erageof75.3nymphswasfound,fromwhichanaverageof70.1adultsdeveloped,with
Figure 5.
Trends in the insect population across generations. The differences between the means (marked
with letters A, B, C, and D) were statistically significant (p< 0.05), according to a two-way ANOVA.
Table 2. Developmental progression table for the oak lace bug population.
Index The Generation of 2020 The Generation of 2021
G I G II G III G I G II G III
N040 130 110 70 70 70
N 28 48 44 46 48 18
lxeggs 38.9 ±5 58.4 ±5.8 55 ±4.2 25.9 ±4.2 94.6 ±10.3 52.1 ±8.9
dxe ggs 44.5% 34.3% 4.7% 6.2% 20.5% 34.3%
lxnymphs 121.6 ±2.8 38.4 ±5.5 52.4 ±4.4 24.3 ±5.2 75.3 ±8.7 34.2 ±10.6
dxnymphs 117.9% 11.6% 4.5% 6.3% 5.1% 9.1%
lxnymphs 217.7 ±2.6 30.7 ±4.5 50.5 ±4.6 22.7 ±5.1 71.4 ±8.7 31.1 ±10.4
dxnymphs 210.1% 9.6% 3.6% 5.4% 0.9% 10.4%
lxnymphs 315.9 ±2.6 29.2 ±4.3 48.2 ±4.6 21.5 ±5 70.7 ±8.6 27.9 ±10.5
dxnymphs 36.3% 4.6% 1.6% 1.2% 0.5% 8.4%
lxnymphs 414.9 ±2.7 28.2 ±4.2 47.5 ±4.7 21.3 ±5 70.4 ±8.6 25.6 ±10.6
dxnymphs 43.3% 3.6% 1.3% 0.4% 0.2% 2.2%
lxnymphs 514.6 ±2.7 27.4 ±4.2 46.8 ±4.8 21.2 ±5 70.2 ±8.6 25 ±10.7
dxnymphs 52% 3% 0.6% 0.4% 0.2% 32.4%
lxadults 14.1 ±2.8 27.4 ±4.2 46.5 ±4.8 21.1 ±5 70.1 ±8.6 16.9 ±11.5
dx f em ale 0.4 0.5 0.5 0.5 0.5 0.5
GS 36% 47% 85% 81% 74% 32%
To continue the observations of the development of the third generation, other pairs
of adults obtained from the second generation were isolated and grown under controlled
conditions in a natural environment. In 2020, we recorded an average of 55 eggs per pair, sig-
nificantly more than those laid by the overwintered generation (p= 0.048) but not significantly
different from those laid by the second generation (p> 0.05). From the eggs laid, an average of
52.4 nymphs emerged, resulting in a hatching success rate of 95%. Finally, after progressing
through the five nymphal stages, the nymphs produced an average of 46.5 adults; this number
Insects 2023,14, 882 9 of 18
was significantly higher than in the previous generations (first generation: p< 0.001; second
generation: p= 0.001). Like in the previous generation, females accounted for 50% of the adult
population. In 2021, we recorded an average of 52.1 eggs per pair, significantly less than the
number of eggs laid by the previous generation (p= 0.004) but not significantly more than
those laid by the overwintered generation (p> 0.005). These pairs produced 34.2 nymphs
and, ultimately, 16.9 adults, with half of them being females. The number of adults in the
third generation was significantly lower than in the second generation (p< 0.001) but not
significantly lower than in the first generation (p> 0.005).
3.4. Analysis of Differences in Egg Laying Trends among Generations
Females’ fertility varied among generations. A female could lay her eggs in
1–9 clusters on the undersides of leaves. The number of eggs in a cluster ranged from 1 or
2 to a maximum of 125. Average values and other statistical parameters for clusters per
female and eggs per cluster per generation are presented in Table 3.
Table 3. Statistical metrics for egg laying trends across generations.
Characteristics Statistical Parameters
Generation
I II III
2020 2021 2020 2021 2020 2021
Clusters/female
Mean 2.65 2.17 1.95 3.65 1.55 2.33
Minimum 1 1 1 2 1 1
Maximum 7 3 6 9 3 5
Standard deviation 1.64 0.77 1.08 1.67 0.74 1.41
Coefficient of variation (%) 62.68 35.77 56.09 45.67 48.07 60.61
Number of
eggs/cluster
Mean 11.5 11.9 24.62 26.79 31.84 22.90
Minimum 1 2 4 2 6 7
Maximum 46 51 72 125 84 64
Standard deviation 10.74 10.80 15.27 23.11 21.50 15.34
Coefficient of variation (%) 94.10 90.71 62.02 86.27 67.23 66.97
According to our data analysis, in 2020, the average number of clusters per female
significantly increased from one generation to the next (p< 0.001 for Generation I compared
to Generation II; p= 0.041 for Generation II compared to Generation III). In 2021, the
significant increasing trend in the number of clusters persisted between the first and second
generations (p< 0.001), but for the third generation, the change was no longer statistically
significant (p> 0.05).
We observed different dynamics in 2020 and 2021 for the average number of eggs per
cluster of different generations. In 2020, Generation I laid significantly fewer eggs per cluster
compared to Generation II (p= 0.002). Between Generation II and Generation III, we did not
observe a significant difference (p> 0.05). In 2021, we noted that the number of eggs per
cluster significantly increased between Generation I and Generation II (p< 0.001). Then, we
observed a significant decrease between Generation II and Generation III (p= 0.006).
4. Discussion
This study aimed to understand the life cycle and adaptive responses of the OLB in
the context of its invasion in Europe, with a focus on Romania. The main objective of this
study was to make a significant contribution to the understanding of the OLB’s biology
and ecology in a new environment and emphasize the importance of this knowledge for
the sustainable management of oak forest ecosystems.
Insects 2023,14, 882 10 of 18
4.1. Life Cycle and Number and Durations of Generations
Based on our observations, the OLB has three generations per year, with hibernation of
the adult stage in sheltered locations. Adults have a high potential to withstand short-term
exposure to low temperatures [54].
The results of studies from Italy [
55
] and Hungary [
56
] confirm that the findings
presented in this paper are consistent with the biology of the insect in the invaded area of
Europe. There are many similarities between our data and those from previous studies,
suggesting uniformity in the development of this species in various geographical regions.
However, in the native range of this pest in the state of Delaware (USA), the insect has
two complete generations per year plus a third partial generation [
20
]. One explanation
for this difference could be the milder and more temperate climate in Europe, which can
provide favourable conditions for the development of three complete generations of the
insect. In contrast, in its native area in the USA, more pronounced climatic variation and
different environmental conditions could limit the complete development of generations,
leading to shorter and incomplete life cycles. Additionally, pressures from natural enemies
in the USA, such as parasitic wasps, predatory assassin bugs, lacewing larvae, lady beetles,
jumping spiders, pirate bugs, and mites [
57
], may play a role in determining the number
of complete or incomplete generations. This difference in life cycles could represent an
adaptation of the species to the specific environment and climatic conditions of each region.
4.2. Using Degree Days to Predict Insect Development
The data discussed in the previous subsection originate from observations in Romania,
with comparisons to research conducted in the USA [
20
,
21
], Northern Italy [
55
], and
Hungary [
56
]. These comparisons reveal that climatic and biological factors likely shape the
species’ life cycle. Insects are poikilothermic, meaning their body temperature is influenced
by ambient temperature, and meteorological factors significantly impact their biology,
including their metabolic activity, abundance, and dispersal [
58
,
59
]. Among the myriad
environmental factors, air temperature holds a paramount status in influencing insect
behaviour [
60
]. It plays a pivotal role in metabolic processes, metamorphosis, mobility,
and host accessibility, which consequently can lead to fluctuations in their population and
dynamics [
61
]. These notations were not far-fetched; even in the case of the OLB, its diurnal
and seasonal dynamics are directly influenced by temperature [62].
These findings suggest that degree day-based development is an efficient method for
monitoring and managing insect populations, regardless of regional or climatic variation.
The use of calendar-based data to predict the biological cycle of insect pests is considered
rudimentary and inefficient [
48
]. Given that insects are ectothermic, with their body
temperatures and development affected by external temperature, a phenological model
based on degree days is considered much more suitable for integrated pest management
than one based on calendar days [
46
]. According to the degree day model, each insect
species needs to accumulate a certain amount of heat to progress through its life stages,
such as egg laying and hatching or adult flight. When considering specific activities related
to insect control, such as detection or control at a certain stage of development, the degree
day prediction model is much more efficient than the calendar-based model.
Our findings regarding the OLB’s degree day-based life cycle offer a detailed view of
this complex process. Data collected directly in natural environments have provided insight
into critical moments in the species’ development across its generations. Field-based degree
day models are crucial because laboratory-based models are rarely accurate predictors of
insect development under natural conditions [
63
,
64
]. Through comparing our data with
studies conducted in the native habitat of the Corythucha spp. in the United States, we
observed significant differences in temperature requirements for insect development. In
the U.S., lace bugs developed two generations per year, requiring between 239–363 degree
days and 1266–1544 degree days, respectively, at a base temperature of 50
◦
F, calculated
from 1 March [
65
–
67
]. In contrast, in southeastern Romania, we observed that the OLB
undergoes three generations per year and exhibits different temperature requirements
Insects 2023,14, 882 11 of 18
for development. While these results contribute to our understanding of regional or
interannual variation in degree day-based development, the lack of detailed data on the
OLB’s degree day requirements in Europe limits direct comparisons. The model above
cannot replace field observations but can aid in predicting phenological events. Parallel
field observations could help to confirm the reliability of the prediction model, especially
for the OLB, an invasive species that can alter its lifestyle across years.
4.3. Life Table of the Insect Population in a Natural Environment
Life tables are often used by ecologists to monitor changes occurring in various
stages of a studied population. In entomology, they are considered an important tool for
understanding changes in the populations of pest insects throughout different stages of
their development [49–51].
Considering previous research, such as the study conducted by Hosseini-Tabesh et al. [
68
],
which highlighted significant differences in the survival rates, fecundity, and longevity of
insects based on their rearing environment (laboratory vs. field), and considering that the OLB
is an invasive insect that can exhibit different behaviours in natural environments than under
laboratory conditions, we chose to collect field data to obtain a more realistic and applicable
understanding of the biology and ecology of this species.
Based on the data from the life table developed for the OLB, differences in the popula-
tion dynamics of the insect between the first and second years of the study were notable.
In the first year, there was a clear increase in vitality and prolificacy as the generations
progressed, whereas in the second year of research, variation in vitality and prolificacy was
observed between generations (with an increase from the first to the second generation,
followed by a decrease from the second to the third generation). Both the increase in the
first year and the variation in the second year could result from more complex and unpre-
dictable environmental factors, such as optimal climatic conditions/climatic fluctuations,
sufficient/insufficient food resources, and interactions with other biotic factors. Factors
like high and low temperature thresholds, fluctuating humidity, or wavelength can affect
ovulation, fecundity rate, development, survival, or reproduction [69].
To accurately assess the influence of these factors, it is essential to compare our
results with that of previous studies that have investigated insect development at con-
stant temperatures. However, to date, we have not identified any such studies for the
OLB. Nonetheless, the results of a study that developed a life table for Corythucha ciliata
(Say, 1832) (Heteroptera, Tingidae) at five constant temperatures indicate that, as the air tem-
perature increased from 19
◦
C to 30
◦
C, both the average fecundity and rate of successfully
completing all developmental stages significantly increased [70].
Interestingly, the sex ratio remained approximately 1:1 in all three generations in both
years of the study. This constancy may suggest that OLB populations have developed
adaptations to maintain this sexual balance. However, the sex ratio is often affected by
both intrinsic and extrinsic factors, including genetics, behaviour, physiology, intracellular
endosymbionts, and biotic and abiotic factors like temperature, photoperiod, humidity,
light conditions, and host or prey quality and quantity [71,72]. A study on the sex ratio of
Nysius huttoni (White, 1878) (Hemiptera, Lygaeidae), conducted both in the laboratory and
using samples from the natural environment [
73
], revealed that, in the natural environment,
the sex ratio remained constant at around 1:1. In contrast, in the laboratory environment, a
combination of short photoperiods and low temperatures produced the highest proportion
of males. Additionally, Ju et al. [
68
] showed that the sex ratio of C. ciliata, a species similar
to the one in this study, could be influenced by air temperature.
Significant variation in the survival of generations (the proportion of individuals that
successfully reached the adult stage) was observed between generations and between
study years. In the first year, there was a clear increasing trend from the first to the third
generation, suggesting positive adaptation to environmental conditions. In contrast, in
the second year, we witnessed a reversal of this trend. The causes of this phenomenon
remain unknown. It is interesting to note that previous studies, such as the one conducted
Insects 2023,14, 882 12 of 18
by Bernardinelli [
74
], indicated that the proportion of insects reaching the adult stage
can vary depending on the host plant, with preferences for species like Quercus robur L.,
Q.pubescens,Q. petraea,Quercus cerris L. (Fagaceae), Rubus ulmifolius Schott, and Rubus
idaeus L. (Rosaceae).
These findings suggest that fluctuating climates may play a crucial role in the dynamics
of OLB populations and could be an important factor in explaining the observed variation.
Thus, further investigations are necessary to gain a deeper understanding of how the
environment and climatic conditions affect this insect and contribute to the development of
more effective management and conservation strategies.
4.4. Analysis of Differences in Egg Laying Trends among Generations
Our analysis of statistical parameters revealed that, from one generation to the next,
females tended to lay a greater number of eggs per cluster. However, there was also a
tendency to concentrate those eggs in a smaller number of clusters. The OLB exhibited vari-
ation in the number of eggs laid, with a range between one and nine clusters per female and
between 1 and 125 eggs per cluster, depending on the generation. In contrast, Bernardinelli
& Zandiagiacomo [
22
] indicated that the eggs of these insects were arranged in variable
clusters, with numbers ranging from 15 to 100. This difference could be explained by the
fact that, in this study, we tracked isolated pairs of insects and each generation separately,
allowing for the observation of different behavioural responses to the environment and
resource availability. These notable differences in the reproductive strategies of the OLB
suggest that adaptation to environmental conditions, including access to food resources,
plays a crucial role in shaping these behaviours.
In general, fecundity can be significantly influenced by the nutrition, quality, and quantity
of food consumed by an insect both during its larval life and in adulthood [
75
]. The quality of
host plant components, such as carbon, nitrogen, and defensive metabolites, directly affects
the potential and fecundity of herbivorous insects [
76
]. Additionally, Ju et al. [
68
] found
that temperature can have a significant impact on average fecundity in C. ciliata. Given the
similarities between this species and the OLB, it is plausible that temperature could also
influence the fecundity of the OLB.
These results lead us toward a deeper understanding of the complexity of adaptation
in invasive species like the OLB to their new environments and to changes in resource
availability. They also underscore the importance of continuing research to thoroughly
examine how nutritional factors and the environment affect the reproductive behaviour
of these insects, thus contributing to the development of more effective strategies for
managing invasive insect populations
4.5. Practical Implications and Future Research Directions
Our results regarding the life cycle and degree day prediction model provide a compre-
hensive perspective on the evolution of this species. This information is essential for forest
managers dealing with integrated pest management. The degree day prediction model
offers a more precise method for anticipating critical moments in the development of this
pest than alternative models, such as the calendar method. In general, it provides valuable
information to crop managers regarding when a particular generation of pests reaches
critical stages of development, allowing them to plan the timing of pesticide applications
more efficiently [
77
]. Moreover, our prior study [
78
] highlighted challenges in chemically
controlling the OLB due to its unique biology. These insights have the potential to improve
chemical control efficacy by enabling more precise and efficient pesticide applications.
Developing a life table of the insect population in a natural environment for the climatic
conditions in Romania serves as a foundation for the development of a pest forecasting
method. This life table not only enriches our knowledge of the species but also provides a
solid basis for estimating how it can impact the environment [49,65].
From a pest management perspective, it is extremely valuable to identify when and
under what circumstances a pest population experiences significant mortality, as this is
Insects 2023,14, 882 13 of 18
the time when it becomes more susceptible to control measures [
49
,
79
]. Understanding
critical moments in the life cycle of the OLB can lead to a reduction in the excessive use
of pesticides. By focusing control treatments during periods when the OLB population is
most vulnerable, the amount of pesticide required to keep the pest in check can be reduced.
This not only reduces costs but also minimizes the negative effect of pesticides on the
surrounding environment. This will help promote more sustainable forest management
and protect fragile ecosystems.
Considering the invasive nature of the OLB, with a confirmed impact both in Romania
and other European states, and the significant level of damage it can cause, continued,
in-depth research is essential, especially given increasingly evident climate change. Thus,
we believe that future research could take the following directions:
•
Continuing periodic observations of the insect’s biology to refine and improve our
degree day–based prediction model;
•
Gaining a deeper understanding of how climatic conditions affect the life cycle and
population density of the OLB;
•Developing advanced forecasting methods based on newly acquired knowledge;
•
Assessing the potential risk of mass infestation in various ecosystems and geographic areas.
Acting on these research directions would help to contribute to a more comprehensive
understanding of the interactions between the OLB and the environment and the develop-
ment of more effective strategies for managing and mitigating the impact of the species
on ecosystems and human activities. Additionally, such research could help adapt control
measures to anticipated climate changes and support efforts to conserve forest ecosystems
threatened by the invasion of the OLB.
5. Conclusions
In the climatic conditions of southeastern Romania, the OLB has three generations per
year and overwinters in the adult stage, preferring sheltered locations. The first generation
begins in the second half of May, followed by the second generation, which develops
starting in July. Both the second and third generations conclude in November, coinciding
with the withdrawal of adults for overwintering.
Our developed prediction model for the species, designed based on degree days, has
the potential to significantly contribute to the development of a comprehensive population
control program by forecasting key events in the biological cycle. It provides a valuable
tool for the efficient management of this invasive species.
The life table developed for the insect population in the climatic conditions of Romania,
based on indicators such as the number of adult pairs, proportion of females, number of
eggs, and number of nymphs at various stages, along with the percentage of mortality at
each developmental stage, explains the population dynamics of the insect across the three
generations. This life table can serve as a valuable resource for the further development of
more effective forecasting and management methods.
Author Contributions:
Conceptualization, F.B. and C.N.; methodology, F.B. and C.N.; software, F.B.;
validation, F.B., D.T. and C.N.; formal analysis, F.B.; investigation, F.B. and D.T.; resources, F.B., D.T.
and C.N.; data curation, F.B. and D.T.; writing—original draft preparation, F.B.; writing—review
and editing, F.B., D.T. and C.N.; visualization, F.B. and C.N.; supervision, F.B. and C.N.; project
administration, F.B.; funding acquisition, C.N. All authors have read and agreed to the published
version of the manuscript.
Funding:
This work was supported by the projects PN 23090102, and 34PFE./30.12.2021 “Increasing the
institutional capacity and performance of INCDS ‘Marin Drăcea’ in the activity of RDI—CresPerfInst”
funded by the Ministry of Research, Innovation and Digitalization of Romania.
Data Availability Statement:
No new data were created or analysed in this study. Data are contained
within the article.
Conflicts of Interest: The authors declare no conflict of interest.
Insects 2023,14, 882 14 of 18
Appendix A
Table A1. Methodology for constructing the life table of the oak lace bug.
Index Description Method of Determination Formula
N0The total number of pairs established
and introduced into the experiment.
Directly counting the actual
number of the pairs
established and introduced
into the experiment.
N/A (directly counted).
N
The number of pairs that successfully
completed the development cycle of
the respective generation.
Directly counting the actual
number of pairs that
successfully completed the
development cycle.
N/A (directly counted).
lxeggs The average number of eggs per pair.
Directly counting the actual
number of eggs produced by
each pair at the end of
oviposition and calculating
the average for a pair.
N/A (directly counted).
dxe ggs The mortality and infertility of
the eggs.
Determining the percentage of
eggs that were non-viable due
to natural enemies or other
unknown biological causes
and did not result in the
development of
first-instar nymphs.
dxe ggs =l xnym phs 1
lxe ggs ×100
lxnymphs 1The average number of
first-instar nymphs.
Directly counting the number
of nymphs resulting from the
total number of eggs for each
pair that survived until the
end of the first stage of
development and calculating
the average for a pair.
N/A (directly counted).
dxnymphs 1The mortality of first-instar nymphs.
Determining the percentage of
first-instar nymphs that did
not survive until the end of
the first instar due to natural
enemies or other unknown
biological causes.
dxnymphs 1=lxn ymphs 2
lxn ymphs1×100
lxnymhs 2The average number of
second-instar nymphs.
Directly counting the number
of nymphs resulting from the
first-instar nymphs that
survived until the end of the
second instar and calculating
the average for a pair.
N/A (directly counted).
dxnymphs 2The mortality of second-instar
nymphs.
Determining the percentage of
nymphs derived from
first-instar nymphs that did
not survive until the end of
the second instar due to
natural enemies or other
unknown biological causes.
dxnymphs 2=lxn ymphs 3
lxn ymphs 2×100
lxnymphs 3The average number of
third-instar nymphs.
Directly counting the number
of nymphs resulting from
second-instar nymphs that
survived until the end of the
third instar and calculating
the average for a pair.
N/A (directly counted).
Insects 2023,14, 882 15 of 18
Table A1. Cont.
Index Description Method of Determination Formula
dxnymhs 3
The mortality of third-instar nymphs.
Calculating the percentage of
nymphs originating from
second-instar nymphs that
did not survive until the end
of the third instar due to
natural enemies or other
unknown biological causes.
dx nym phs 3=l xnym phs 4
lxn ymphs 3×100
lxnymphs 4The average number of fourth-instar
nymphs.
Directly counting the number
of nymphs resulting from
third-instar nymphs that
survived until the end of the
fourth instar and calculating
the average for a pair.
N/A (directly counted).
dxnymphs 4The mortality of fourth-instar
nymphs.
Calculating the percentage of
nymphs originating from
third-instar nymphs that did
not survive until the end of
the fourth instar due to
natural enemies or other
unknown biological causes.
dxnymphs 4=lxn ymphs 5
lxn ymphs 4×100
lxnymphs 5The average number of fifth-instar
nymphs.
Directly counting the number
of nymphs resulting from
fourth-instar nymphs that
survived until the end of the
fifth instar and calculating the
average for a pair.
N/A (directly counted).
dxnymphs 5The mortality of fifth-instar nymphs.
Determining the percentage of
nymphs derived from
fourth-instar nymphs that did
not survive until the end of
the fifth instar due to natural
enemies or other unknown
biological causes.
dxnymphs V5=lxadults
lxn ymphs V 5×100
lxadults The average number of adults.
Directly counting the number
of adults resulting from
fifth-instar nymphs and
calculating the average for
a pair.
lx f e male The sex ratio.
The ratio of the number of
females to the number
of adults dx f emal e =lx f emal e
lxadults ×100
GS The survival of the generation.
the population trend index.
Without the effects of fertility
and mortality of individuals
after reaching adulthood.
GS =lxadults
lxe ggs
×100
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