Alpha and beta diversity patterns of macro-moths reveal a breakpoint along a latitudinal gradient in Mongolia

Abstract

Little is known about the diversity and distribution patterns of moths along latitudinal gradients. We studied macro-moths in Mongolia along an 860 km latitudinal climatic gradient to gain knowledge on community composition, alpha, beta, and gamma diversity as well as underlying factors, which can be used as baseline information for further studies related to climate change. We identified 236 species of moths of ten families. Our study shows that the diversity of moths increased with the latitude, i.e., low species richness in the south and higher richness in the north. Moth community composition changed along the gradient, and we revealed a breakpoint of beta diversity that divided grassland and desert communities. In the desert, beta diversity was driven by species loss (i.e., nestedness), and few tolerant species existed with high abundance. In contrast, in the grassland, beta diversity was driven by species replacement with more unique species, (i.e., species which occurred only in one site). We found the lowest species diversity in the transitional zones dominated by few generalist species such as Agrotis ripae and Anarta trifolii. Low precipitation and an increasing number of grazing goats are drivers of species loss. We suggest different conservation strategies regarding the contrasting patterns of beta diversity in desert and grassland.

Full text

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
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Alpha and beta diversity
patterns of macro‑moths reveal
a breakpoint along a latitudinal
gradient in Mongolia
Khishigdelger Enkhtur1*, Gunnar Brehm2, Bazartseren Boldgiv3,4 & Martin Pfeier1
Little is known about the diversity and distribution patterns of moths along latitudinal gradients. We
studied macro‑moths in Mongolia along an 860 km latitudinal climatic gradient to gain knowledge on
community composition, alpha, beta, and gamma diversity as well as underlying factors, which can be
used as baseline information for further studies related to climate change. We identied 236 species
of moths of ten families. Our study shows that the diversity of moths increased with the latitude,
i.e., low species richness in the south and higher richness in the north. Moth community composition
changed along the gradient, and we revealed a breakpoint of beta diversity that divided grassland and
desert communities. In the desert, beta diversity was driven by species loss (i.e., nestedness), and few
tolerant species existed with high abundance. In contrast, in the grassland, beta diversity was driven
by species replacement with more unique species, (i.e., species which occurred only in one site). We
found the lowest species diversity in the transitional zones dominated by few generalist species such
as Agrotis ripae and Anarta trifolii. Low precipitation and an increasing number of grazing goats are
drivers of species loss. We suggest dierent conservation strategies regarding the contrasting patterns
of beta diversity in desert and grassland.
Biodiversity loss has become a pressing global issue in the last decades1. Since biodiversity is crucial to maintain
ecosystem functions, it is important to study the distribution of organisms and their response to climate change
and human disturbance. Recently, a preponderance of studies reported strong declines in insect diversity2–5. For
example, in Germany’s protected areas ying insect biomass declined by more than 75% within only 27years,
however, the cause is still unclear6.
As Simmons etal.3 stated, some “global” studies on insect decline should be cautiously interpreted because
results based on particular locations do not represent a global scale. Robust insect diversity data representing all
major biomes of the world are required7. However, data availability is strongly biased across the world towards
Europe and North America, especially regarding systematically collected long-term data. Tropical regions are
poorly studied. e same is true for the most parts of central and eastern Asia, especially in regard to the diversity
and distribution patterns of moths in eastern Russia, northern China and Mongolia. During a previous literature
review of studies on geometrid moths, we found that long-term data were unavailable from these regions8. is
study is an important ”puzzle piece” in lling this gap for future research.
ere are approximately 1550 species of Lepidoptera reported in Mongolia9; however, there is no complete
checklist available. In geometrid moths, a recent checklist reported 388 observed species, but species richness was
estimated to be 663 ± 568. Recently, 21 new species have been recorded from western and central Mongolia10 and
the family Alucitidae was rst time reported for Mongolian fauna in 2015 in the Mongolian Altai Mountains11.
Moreover, several species new for the fauna of Mongolia were reported in Sphingidae, Noctuidae, Cossidae,
and Ypsolophidae12–16. In the Global Biodiversity Information Facility (GBIF), 919 species of 30 families of
Lepidoptera are recorded for Mongolia17. is is certainly an underestimate, and not all occurrence data in the
literature have been uploaded in GBIF. To summarize, data have been collected incompletely, non-continuously
OPEN
         
Germany. Phyletisches Museum, Institut für Zoologie und Evolutionsbiologie, Friedrich‐Schiller‐Universität, Vor
 Ecology Group, Department of Biology, National University of Mongolia,
       Academy of Natural Sciences of Drexel University,
 *

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with dierent eorts, at specic locations, published, and scattered in the literature, thus rendering it impossible
to investigate the changes of moth diversity at temporal and spatial scales.
In response to this need, our study focuses on moth diversity and species composition across a latitudinal
gradient. Biodiversity across latitudinal gradients is especially important to study as they are the largest and
strongest climatic gradients globally. Alpha diversity is the diversity of local communities, while beta diversity is
the spatial change in composition between local communities18. Beta diversity links alpha and gamma diversity,
i.e., large-scale diversity. To measure alpha diversity, we used Hill numbers: species richness, Shannon diversity
and Simpson diversity. Hill numbers are a linear measure of diversity, which traditional indices are not, they
have the same units and are comfortable to compare sites19,20. ey account for dierent levels of diversity and
mirror species richness and evenness.
Measuring alpha diversity is vital for conservation purposes since it quanties the biodiversity of a particular
habitat through the baseline measure of species presence and abundance within a local community. Species rich-
ness (number of species present) of moths can reect habitat quality and be an indicator of species sensitivity
to environmental changes21,22. Pronounced declines of species richness along the latitudinal gradient from the
equator to the poles have been demonstrated for almost all taxa in dierent regions of the world23–26. is gen-
eral trend of declining diversity and richness across latitudes is accompanied by environmental factors such as
temperature along altitudinal gradients, land use, and precipitation27. As precipitation increases with latitude in
most parts of Central Asia27,28, this could regionally superimpose patterns of moth richness and diversity patterns.
One crucial question is how species composition changes along latitudinal gradients, i.e., whether the change
is due to species replacement or species loss/gain. Dierent types of measures for beta diversity are available29–32.
We applied the widely used method by Baselga etal.33, which partitions beta diversity into turnover and nested-
ness. Doing so enables us identifying the leading causes for the dierentiation and is further useful for imple-
menting better conservation strategies. Turnover reects the process of environmental ltering, while nestedness
reects colonization, such as the eects of a lack of available resources34.
In Mongolia, on the one hand, a latitudinal or climatic gradient can be one type of environmental ltering.
Mongolia is located between 41°35′ and 52°06′ N. is climatic gradient is characterized by higher rainfall and
lower temperature in the north and lower precipitation and higher temperature in the south35.
On the other hand, grazing patterns represent another type of environmental ltering. In Mongolia, the domi-
nant land use type in the country is free-ranging livestock grazing, thus overgrazing can be the cause of coloniza-
tion or extinction from one habitat to another36. Recently, the number of livestock is increasing, and nowadays,
herders tend to be more sedentary than former herders, which causes local to regional pasture degradation.
Moreover, the eects of climate change and overgrazing are accelerating each other in a positive feedback loop36.
We tested the hypothesis that species diversity and species richness declines with latitude in Mongolia.
Moreover, we hypothesized that precipitation positively inuences diversity and richness, and that (over-) grazing
negatively inuences diversity and richness. ese (and possibly other environmental variables) could region-
ally superimpose the expected large-scale latitudinal patterns, resulting in inverse latitudinal gradient patterns
and/or breakpoints.
In addition, we investigated (without an a priori hypothesis), how moth species composition or beta diversity
diered between sites, and if beta diversity was mainly inuenced by spatial turnover (species replacement) or
nestedness (species loss or gain). Moreover, our study provides new data on the regional species pool of Mongolia,
i.e., how many and which moth species are present, and explores the gamma diversity of moths in Mongolia.
is is the rst comprehensive study on macro-moths over large geographic scales in Mongolia and it forms
the baseline for future studies. It is necessary to gain knowledge of moth diversity and distribution patterns at
local and large-scale level (i.e., alpha and gamma diversity) and how local diversities are organized and vary at
large-scale (beta diversity)37,38 to develop an eective conservation strategy for the Mongolian moth species and
their habitats. Dierent conservation strategies are required depending on the beta diversity patterns (nestedness
or turnover). For the areas with species loss, it is recommended to protect certain species-rich sites; in contrast,
for the areas with species replacement, several large dierent types of sites are needed to be protected33. Species-
poor sites usually hold only a subset of species-rich sites39. In a study of birds and snails, habitat homogeneity was
responsible for the nestedness of the animal communities40,41. However, it must be noted that habitat simplica-
tion can reduce local species richness, and the whole community would be similar, leading to homogenization42,43.
us, it is vital to see both, the smaller more detailed picture as well as the bigger picture in order to consider the
fragmentation between the sites and successfully implement conservation plans, both locally and regionally. If the
temperature keeps rising and livestock numbers keep increasing, even species-rich sites would be transformed
into species-poor sites, making the whole community unable to sustain itself. Some species will disappear due to
the loss of suitable habitat, and only species which have tolerance to the disturbance will be le39,44. Moreover, in
the face of climate change northern sites have the potential of becoming more similar to current day ecological
conditions in southern sites. is could lead to homogenization, resulting in a less diverse assemblage. By tracking
moth biodiversity along a latitudinal gradient, this study is using a space-for-time substitution (e.g., southern sites
could predict future results for northern sites). us, our results not only provide necessary baseline reference
data, but also essential insights on the future of biodiversity change in a warming world.
Results
Alpha diversity. In total, we caught 11,115 macro-moth individuals of 236 species of ten families: 7 Cossi-
dae, 3 Drepanidae, 35 Erebidae, 58 Geometridae, 6 Lasiocampidae, 108 Noctuidae, 7 Notodontidae, 1 Sesiidae,
10 Sphingidae, and 1 Zygaenidae (see the full species list in TableS2 in the supplementary material). Estimated
species richness was 461 (iChao1, SE: 22.96, lower 95%: 392, upper 95%: 581), therefore, our samples cover
51% of the estimated species richness. e three most species-rich families were Noctuidae (45.8% of species),

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Geometridae (24.6%) and Erebidae (14.8%) (Fig.1). e other families together constituted 14.8% of all species
and we combined them into one group (“Other”).
Noctuidae had the highest abundance represented with 8839 specimens, with the commonest species Agro-
tis ripae Hübner, with 5986 individuals collected at nine out of ten sites, especially dominating the sites in the
desert. Moth family composition patterns changed along the latitudinal gradient. In the grassland sites, Erebidae,
Geometridae, and Noctuidae (and “Other”) shared similar proportions whereas Noctuidae heavily dominated
in all desert sites (Fig.1). K-means clustering separated all sites into two groups of southern “desert” (1–5) and
northern “grassland” (6–10) sites (see scree plot in Fig.S1 in supplementary material).
Overall, moth species richness (Fig.2a), species diversity (Fig.2b), and abundance (Fig.2c), of the grassland
sites (6–10) were signicantly higher (p < 0.005) than those of the desert sites (1–5). Among the desert sites,
species diversity at Site 2 was higher than in all other sites. e most species-rich site was site 8 (grassland),
and the most species poor-site was Site 3 (desert). We investigated which functional group of vegetation was
responsible for high species richness of moths. As a result of GLM, forb impacted the species richness of moths
(LM: R2 = 0.55, p = 0.012).
Hill numbers were positively correlated with precipitation and forb cover, and negatively correlated with
temperature, wind and number of goats (Table1).
Species abundance and richness pattern. e ten most abundant species responded dierently to
annual temperature and annual precipitation. Agrotis ripae and Anarta trifolii showed a decelerating exponential
response to increasing annual temperature (Fig.S3 in the appendix), whereas the abundance of Lithostege sp. 2
was increasing with increasing annual precipitation. Hyles gallii, Lygephila lubrica and Isturga arenacaria were
mainly present at the more humid northern sites. At low temperature and high precipitation all ten species coex-
isted, whereas at high temperature and low precipitation, only two species (Agrotis ripae, Anarta trifolii) formed
the community alone (Fig.3a,b). A linear regression model shows that species richness of moths was decreas-
ing with increasing annual temperature (R2 = 0.36, p < 0.001) and increasing with rising annual precipitation
(R2 = 0.57, p < 0.001). In the grassland sites, species richness was higher than in the desert sites (Kruskal–Wallis
Test: p < 0.001) (Fig.3c,d).
We found 96 unique species in total, i.e., species which occurred only in one site. Overall, the unique species
numbers of the grassland sites (n = 70) were higher than those of the desert sites (n = 26, Kruskal–Wallis Test:
p < 0.005). Site 3 had only one unique species, whereas Site 10 had 27 unique species (see Fig.S4 in supplemen-
tary material).
Beta diversity. According to K-means clustering we classied the ten sites into two groups and performed
a correspondence analysis based on the family matrix, which indicated clear distinction in the composition of
Figure1. Study area with pie charts showing the percentage species composition of the main moth families:
Erebidae, Geometridae, Noctuidae and all other families along the precipitation gradient. In group Other:
ese families are combined: Cossidae, Drepanidae, Lasiocampidae, Notodontidae, Sesiidae, Sphingidae,
and Zygaenidae. Pie sizes correspond to species richness of the site (legend on the lower le side) See species
richness and diversity of each site in TableS3 in supplementary material. Figure was produced using R soware
(version 3.6.3, R Core Team, https:// www.r- proje ct. org/).

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major families in two groups (Fig.4). Noctuidae and Cossidae were more abundant in the desert sites, while
other families were remarkably abundant in the grassland sites. Distinction between these groups was signicant
(Permanova: R2 = 0.37, p < 0.006).
Venn diagrams show the species overlap between the moth composition of the desert and the grassland sites
in four family groups. e highest overlap was in Noctuids, followed by Erebids and others, the lowest overlap
was in Geometrids (see Fig.S5 in supplementary material).
Mean beta diversity of macro-moth species among the sites as calculated with Jaccard’s index was intermedi-
ate; βj = 0.82 (range = 0.78–0.86). e outer sites of the gradient with the more extreme environmental conditions
had the highest average beta diversity, while sites in the middle had the lowest average beta diversity (Fig.5a). A
linear regression model indicated that with increasing distance Jaccard’s similarity decreases (R2 = 0.52 p < 0.001)
(see Fig.S6 in supplementary material).
We checked the contributions of spatial turnover and nestedness to the result of mean beta diversity. Taken
together, the contribution of spatial turnover (mean βt = 0.69; range = 0.60–0.77) was much higher than that of
nestedness (mean βt = 0.13; range = 0.08–0.27), which means that species replacement was higher than species
loss or gain.
Regarding pair-wise beta diversity, Sites 2 and 10 were signicantly higher than other sites in terms of turnover
(Fig.5b). Only Site 3 was signicantly higher in terms of nestedness (Fig.5c), all other sites, except Site 8 were
not signicantly dierent. e sites with the highest and lowest average species replacement were the same as
those with the highest and lowest beta diversity (Fig.5a).
We found a breakpoint at 46°N as a result of the piecewise regression of Jaccard’s beta diversity, spatial turno-
ver, and spatial nestedness versus latitude (Fig.6). e t of the piecewise regression models was signicantly
higher than the simple linear regression models for all components: R2 increased from 0.02 to 0.16 (Anova:
F2, 52 = 5.26, p < 0.001) for Jaccard beta diversity, from 0.01 to 0.19 (Anova: F2, 52 = 7.36, p < 0.001) for spatial
turnover, and from 0.05 to 0.26 (Anova: F2, 52 = 8.50, p < 0.001) for spatial nestedness.
Figure2. Species richness, Shannon diversity and abundance of ten sites along the latitudinal gradient.
Diversity metrics were compared with Wilcoxon test based on the sampling nights of each site. Dierent letters
show signicant dierences between sites. See the further comparison of species richness, species diversity and
abundance at the family level in Fig.S2, TablesS4, S5 and S6 of supplementary material.
Table 1. Pearson correlation coecients of Hill numbers with environmental variables.
Hill numbers Precipitation Temperature Forb cover Goat numb er Wind
Species richness 0.92*** −0.76*** 0.99*** −0.75*** −0.91***
Shannon diversity 0.89*** −0.73*** 0.96*** −0.80*** −0.87***
Simpson diversity 0.92*** −0.76*** 0.92*** −0.75*** −0.88***

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Jaccard’s beta diversity indices signicantly diered above (slope = 0.004) and below 46°N (slope = −0.09)
and showed an opposing trend (R2 = 0.16 p < 0.001). Moreover, spatial turnover and nestedness responded in
opposite directions with latitude and were signicantly dierent in the desert and the grassland biomes. In the
desert, species turnover showed a decreasing trend (slope = −0.54) (R2 = 0.19, p < 0.001); in contrast, nestedness
showed an increasing trend (slope = 0.45) (R2 = 0.26, p < 0.001). In the grassland, species turnover (slope = 0.03)
and nestedness (slope = −0.02) showed contrasting trends. In the desert sites, moth communities’ species loss or
gain was dominant, while for the grassland sites, species replacement played the dominant role. e breakpoint
Figure3. Species relative abundance and species richness impacted by environmental variables. X axes titles
are printed only for the lower graphs. GAM shows (a) the relative abundance vs. mean annual temperature and
(b) the relative abundance vs. mean annual precipitation. e general linear regression model demonstrates that
moth species richness is impacted by (c) mean annual temperature and (d) mean annual precipitation. Species
abbreviations: Agrotis ripae (Agroripa), Anarta trifolii (Anartrif), Biston betularia (Bistbetu), Euxoa ochrogaster
(Euxoochr), Hyles gallii (Hylegall), Ipimorpha retusa (Ipimretu) Isturgia arenacearia (Istuaren), Lithostege sp2
(Lithsp2), Lygephila lubrica (Lygelubr), Mythimna comma (Mythcomm).
Figure4. Correspondence analysis of the major families sampled from all sites separated markedly desert
(yellow polygon) and grassland (green polygon) sites. Noctuidae and Cossidae were more associated with desert
sites, whereas other families were associated with grassland sites. First two axes of the graph together explain
76.2% of the variation.

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of beta diversity pattern was matched by an RDA analysis of plant communities (see Fig.S7 in supplementary
material). We found also a breakpoint at 46° N as a result of the piecewise regression of precipitation (R2 = 0.96,
p < 0.001) and temperature (R2 = 0.89, p < 0.001).
e next step was to test the correlation between environmental variables and beta diversity components, and
environmental variables were aecting spatial turnover and spatial nestedness dierently. Precipitation and veg-
etation cover were positively correlated with turnover, whereas negatively correlated with nestedness. In contrast,
temperature, livestock number, and wind were negatively correlated with turnover, while positively correlated
with nestedness (Table2). In the desert, none of the environmental variables was signicant for nestedness.
Using procrustes analysis we compared the distance matrix of moth species with distance matrices of vegeta-
tion and livestock. e matrix of moth species was highly signicantly correlated with both matrices of vegetation
Figure5. Mean pair-wise (a) Jaccard beta diversity, (b) spatial turnover, (c) spatial nestedness of the ten study
sites. Diversity metrics were compared with Wilcoxon test based on the average diversity measures of each site.
Dierent letters show signicant dierences between sites.
Figure6. Beta diversity measures along the latitudinal gradient: (a) Jaccard’s beta diversity along latitude, (b)
spatial turnover along latitudinal gradient and (c) spatial nestedness along latitude. Desert sites (1–5), grassland
sites (6–10).

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(r = 0.74, P = 0.001) and livestock number (r = 0.80, P = 0.002), thus corroborating their strong inuence on moth
community patterns.
In addition, we analyzed if there existed an interaction between environmental variables and biome types
and the species richness and diversity of macro-moths (see the results of the negative binomial generalized
regression and linear regression in TableS8 in the supplementary material). Interaction eects were only found
for the livestock, wind, and elevation. Depending on the biome type species richness of macro-moths responded
to livestock, wind, and elevation dierently. In the grassland these factors aected the species richness of moths
negatively, whereas in the desert there was no eect (Fig.S8).
Discussion
We studied alpha and beta diversity of macro-moths and associated environmental variables along a large-scale
latitudinal gradient in Mongolia for the rst time. Against our expectation, we detected two distinct moth com-
munities along the latitudinal gradient, which signicantly changed between Site 5 (Dundgobi Aimag) and Site
6 (Tuv Aimag) at 46° N. We assume that this distinction is driven by the pronounced climatic gradient, namely
precipitation and temperature. In piecewise regression of diversity on the precipitation and temperature we dem-
onstrated this split at 46° N. As we hypothesized, we observed higher moth species richness and species diversity
in the grassland sites than in the desert sites. In contrast, moth abundance was lower at grassland sites than in
the desert sites. is contradicts with a study on darkling beetles in Mongolia in which species richness declined
gradually with latitude. is contrast between moths and beetles could be explained by a higher temperature
and desiccation tolerance observed in beetles’45. Our study results were in line with the study of Ahlborn etal.27,
who studied plant communities. In both studies, species richness was low in Site 3 (Tsogtovoo Soum, Khetsuu
khoshuu) indicating the need for extra conservation for these transitional sites. In terms of the moth population,
our observation of higher species richness and lower abundance in the grassland could be explained by the theory
of competitive exclusion. ere is higher plant heterogeneity in the grassland, which could ultimately reduce
competitive exclusion in the moth population, allowing for the maintenance of several species (high richness)
at a similar proportion (similar abundance across species/high evenness). In contrast, lower species richness
and higher abundance of certain tolerant species adapted to the few plant species growing in desert prevail2.
e dierentiating species richness and species diversity of moths between the desert and the grassland
sites could be explained by the biotic (plant species richness and livestock number) and abiotic (precipitation and
wind) variables, which were signicantly correlated with the diversity of moths as measured by Hill numbers.
Since herbivorous insects rely on plants, both in larval and adult stages, as their food and habitat, it is logical to
expect a higher moth species richness in areas with a higher plant species richness46. Indeed, variable Forb was
highly positively correlated with the Hill numbers. In contrast, variable Goat was the signicant factor among
all livestock types and negatively correlated with moth species richness. Herders raise high numbers of goats for
income from cashmere, especially in Gobi desert, as one of the common export products of Mongolia35. Water
and energy (i.e. temperature) availability are the important factors determining overall species richness along
the latitudinal gradient. Precipitation is the limiting factor for species diversity in the south, while temperature
Table 2. Pearson correlation coecients between environmental variables and beta diversity measurements
for total (along whole latitudinal gradient), above (> 46°) and below (< 46°) the 46° of latitude. Signicant
variables are shown in bold with stars indicating the level of signicance.
Turnover Nestedness
Precipitation
Tot a l 0.22 − 0.34**
> 46° 0.60*** − 0.56**
< 46° 0.18 − 0.19
Temperature
Tot a l −0.006 0.14
> 46° 0.22 − 0.27
< 46° 0.09 − 0.06
Vegetation cover
Tot a l 0.41** − 0.45***
> 46° 0.55** − 0.49**
< 46° 0.36* − 0.34
Livestock number
Tot a l − 0.40** 0.41**
> 46° − 0.54** 0.50**
< 46° − 0.23 0.22
Wind
Tot a l − 0.11 0.25
> 46° − 0.56** 0.52**
< 46° 0.40* − 0.37
Altitude
Tot a l − 0.05 0.18
> 46° − 0.57** 0.57**
< 46° 0.37 −0.36

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is the limiting factor in the north in several taxa24,25. In our study, only precipitation was a signicant variable,
positively correlated with the Hill numbers.
While variable Wind was negatively correlated with the Hill numbers and similar patterns were observed in
other studies related to wind on moth catches47. In the rst year of the sampling period, strong wind negatively
aected the southern sites’ catch successes.
In a study of moths in Finland48 the authors observed a contrasting pattern with species that were expanding
their ranges poleward due to global warming and were increasing in species richness and decreasing in abun-
dance over time in higher latitudes. e higher abundances in the desert sites in our case were, however, due to
only the two heavily dominant Noctuidae species, namely Agrotis ripae and Anarta trifolii.
At almost all sites, Agrotis ripae and Anarta trifolii occurred; they were the most abundant species. A. ripae,
which is called “sand dart moth”, lives mainly in sand dune areas; the caterpillars rest in the sand during the
daytime and come out to feed at night49. Habitats are characterized by bare ground with sparse vegetation. e
study of Spalding etal.50 showed that bare ground is an essential factor for the sand dune moth species, such
as Luperina nickerlii; disturbance could be helpful to create bare ground. Due to desertication and livestock
trampling, the soil becomes more sandy and loose; this will create more suitable living conditions for A. ripae.
Both A. ripae and A. trifolii can be regarded as generalists and highly migrant species. eir mobility increases
with temperature51. us, both species appear to be suitable indicators of global warming and desertication.
In the grassland sites, the number of unique species was higher than in the desert sites, which implies that in
suitable habitats, like grassland sites, more specialists occurred that were adapted to specic habitats. In contrast,
in harsher, more arid habitats like desert sites, more generalists occurred. Rabl etal.46 found only a small number
of unique species in a relatively species-poor rainforest area (i.e., in a creek habitat). Similarly, Beitzholtz and
Franzen51 reported that specialists prefer suitable habitats; they are prone to stick to their habitats and vulner-
able to extinction. Species, such as generalists, are even beneting disturbance, while specialists are declining1,4.
Moreover, the number of generalists and specialists are related to beta diversity. Beta diversity increases as the
number of specialists increase52,53.
Moth species’ host plant preferences could explain dierences in major family composition in the desert and
the grassland sites. In the desert sites, the moth assemblage composition mainly consists of Noctuids and Cossids,
while proportions of Geometrids, Erebids, and others were low. In contrast, family ratios were almost the same
in all grassland sites. Many Noctuids are not restricted to specic habitats and are generalists (or even cosmo-
politans) in comparison to members of other families (Common 1990). For example, A. ripae is polyphagous54
and usually, polyphagous species can better survive in disturbed areas.
Most adults of Sphingidae, Geometridae, and Arctiinae usually feed on ower nectar, while most caterpillars
of Notodontidae, Drepanidae, and Lasiocampidae mostly feed on the leaves of trees and shrubs49. Several spe-
cies whose larvae feed on trees and undergrowth were found in Sphingidae, Geometridae, and Arctiinae in the
grassland sites; thus, we suggest that surrounding forest and shrubs were also responsible for the higher species
richness of these families in the grassland sites. In addition, the species richness of Arctiinae is high in areas with
complex vegetation types55. is can explain the high richness of Erebidae in the grassland sites. Venn diagrams
(FigureS5) also showed that species overlap between the desert and the grassland sites of Noctuids, Erebids, and
others were similar in percentage (20–27%); in contrast, the species overlap of Geometrids was very low with
only four species in common (7.4%). Geometrid moths are sensitive to the environmental changes; thus, the low
overlap of Geometrids could indicate better habitat quality in the grassland sites compared to the desert sites.
Beta diversity was mainly driven by species replacement rather than species nestedness. Average pair-wise
beta diversity and spatial turnover were high in the external sites and gradually decreased towards the middle of
the gradient; in contrast, average nestedness was high in the middle and low in the outer parts. e macro-moth
assemblages at northern and southern sites were shaped by forest-steppe and desert, habitats that are distinct
from each other. Habitat dierences gradually decrease to the middle part, where the steppe runs in gently
undulating terrain and becomes a transition zone between these habitats resulting in less dierence among moth
assemblages. e higher beta-diversity in the outer parts results from high species turnover, while nestedness
or dierence in species numbers played a less critical role. A similar diversity pattern was reported by Paknia
etal.45 in Mongolian tenebrionid beetle communities. Generally, turnover is due to abiotic factors, while nested
patterns may be attributed to species loss caused by high livestock numbers and low precipitation.
Intensive land use transforms habitats, making them more similar. e more similar habitats become, the
less diverse species they can support. Relative to the larger pool of species found across more distinct habitats,
this more homogeneous subset of species becomes capable of dispersing further in more homogeneous habitats.
In addition to enhanced dispersal capabilities, more homogenous habitats can support more generalist species
that have broad niches. Overall, such traits can decrease beta diversity. However, there is a nuanced caveat. Due
to the homogeneity of the habitat, a few tolerant species may persist, leading to species loss which can result in
higher beta diversity due to nestedness37. In comparison, we observed species replacement happened in areas
with high precipitation and high vegetation cover which increases the beta diversity.
Average beta diversity along the latitudinal gradient had a breakpoint, which was revealed at 46° N, indicat-
ing a change in moth communities between desert and grassland sites. In arid areas south of 46° N, turnover
decreased, and nestedness increased. In contrast, in wet areas north of 46° N, turnover increased, and nested-
ness decreased. In arid areas species richness decreased, and beta diversity was due to species loss, indicating
lower productivity within a harsh environment. e decreasing turnover in the southern sites thus mirrors the
physical limiting factor (i.e., lower precipitation). is contrasting patterns of turnover and nestedness have been
documented in several studies23,52.
A breakpoint in both precipitation (mean annual precipitation: 193mm) and temperature (mean annual
temperature: 0.15°C) was also found at 46° N. Since the breakpoints are overlapping, we predict that as global

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temperatures continue to rise, the grassland sites will become more similar to desert sites. In turn, we predict
that this trend towards habitat homogenization will lead to a more nested pattern of moth diversity.
Temperature had no signicant eect on beta diversity patterns of moths along the latitudinal gradient, both
above and below 46°N. Higher precipitation rate, and higher vegetation cover and diversity were responsible
for the higher beta diversity in northern sites. Precipitation was also a signicant variable for species richness.
e results of Procrustes analysis showed that vegetation structure and livestock composition determined
the moth assemblage pattern. Along the whole gradient, the eects of precipitation, vegetation cover, and veg-
etation richness on the species richness and diversity of macro-moths did not change regardless of biome type.
However, livestock, altitude and wind aected the species richness and diversity of moths dierently, depending
on the biome type. In the desert, the vegetation is scarce even without livestock grazing, and the climatic eect
is stronger than the eect of livestock grazing. e dynamic equilibrium model could explain the insensitivity
of macro-moths of the desert to the number of livestock. In the arid environment, the impact of precipitation
overrides the inuence of disturbance (in our case, livestock grazing)56. In the desert, decreasing species richness
and diversity of moths with increasing altitude and wind speed can be attributed to their low ranges of thermal
tolerance compared to the moths in the grassland57. us, moths living in higher altitude arid environments are
in more danger of becoming extinct due to global warming.
Our study shows how moth diversity changes in Central Asia from south to north over a long latitudinal
transect and assesses the environmental factors responsible for those changes. Identifying the community com-
position pattern is useful for the conservation of not only moths, but also biodiversity in general. Our species list
represents 51% of all estimated moth species along the latitudinal gradient in Mongolia; this result is the most
up to date and systematically collected baseline data for future research.
Moths of the desert Site 3 were more vulnerable to a decrease in species diversity because of low precipitation
and high livestock numbers. e local reduction of alpha diversity may result in reduced gamma diversity on
regional level. Since 1940, the temperature in the area has increased by 2°C, while precipitation has decreased by
7%. At the same time the number of goats increased from four million to 20 million, and large-scale res occurred
repeatedly. As a result, the desert in the south is expanding more and more to the northern part of Mongolia58.
e most negative eect of livestock is due to the high number of goats. Although cashmere from goats is one of
the main export products of Mongolia, the government should stop its support of this unsustainable agricultural
practice. Doing so could at least slow down the future consequences of climate change37.
Moths are eective bioindicators22. eir contrasting patterns of spatial turnover and nestedness in desert
and grassland habitats imply that dierent conservation approaches are needed. erefore, we suggest that the
whole gradient of the grassland has conservation value. Decreasing the number of goats can improve the situ-
ation of pasture overall. However, local diversity patterns could scale up to regional; therefore, we recommend
abandoning this transitional zone from grazing for recovery. In addition, Site 1 that exists at the highest elevation
can function as a refuge area for biodiversity as mirrored by moths should deserve conservation management
by excluding livestock grazing.
In contrast, the species richness of the desert sites is similar except for Site 3 (species poor site) and one (spe-
cies rich site). us, there is no exceptional management required for desert Sites 2, 4, and 5.
e high abundances of A. ripae and A. trifolii indicate that the process of desertication has already intensi-
ed and even at those sites some specialists could have already been extirpated before our study. In the future, we
aim to study the co-eect of climatic variables and livestock grazing on moth communities at dierent latitudes.
Specically, we will aim to investigate whether A. ripae and A. trifolii are indicators of grazing. In addition, we
aim to reveal latitude level indicator species, which could be used as reference species to study the migration of
moths due to climate change.
Methods
Study area. Our study was conducted in the provinces of Umnugobi Aimag, Dundgobi Aimag, Tuv Aimag
and Selenge Aimag in Mongolia, at ten study sites located along the latitudinal gradient from the Gobi Desert in
the south to the Siberian forests in the north, covering various climatic zones36. e southernmost site (43° N,
104° E) is located in semidesert (annual precipitation 146mm, mean annual temperature −3.45°C), while the
northernmost site (50° N, 105° E) is located in forest steppe (annual precipitation 318mm, mean annual tem-
perature −0.56°C) (Fig.1). Livestock herding is one of the major economic sectors in Mongolia, with > 65 mil-
lion animals36. Detailed information on the study sites is given in supplementary material TableS1. We followed
the study design of Lang etal.59 and Ahlborn etal.27 and sampled seven of their original 15 study sites that were
spread at a south–north gradient of 600km. We added three further sites to this transect in northern direction,
totaling in a transect length of 860km.
Moth sampling. Moths were attracted with recently developed LED lamps (“LepiLED”, height ca. 88mm,
diameter ca. 62mm, with four UV LEDs (365nm), two blue (450nm), one green (530nm) and one cool white
LED)60 in combination with Bioform light “towers” (large R. Müller light trapping tower, mesh size 1mm, 70cm
diameter, 180cm high) and EasyAcc 26 Ah power bank batteries. For moth collection, killing jars lled with
CN were used. All samples were sorted to morphospecies level in the eld and kept in glassine envelopes. Moths
were sampled manually because the method usually better covers small species than automatic traps61. Sampling
took place from 9.00 to 12.00p.m. To avoid temporal eects, specimens were collected in two consecutive years
in 2018 (June–July) and in 2019 (July–August) at the peak of vegetation season leaving out nights dominated
by full moon. is period covers the ight season of most nocturnal moth species in Mongolia22. At each site
and in each year, we sampled with three replicates (ten sites × two years × three nights = 60 sampling nights).

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e southern ve sites are located in desert and xeric shrublands biome (desert), and the northern ve sites are
located in temperate grasslands, savannas & shrublands biome (grassland).
Due to adverse weather conditions ve catching nights were successful at some sites (Sites 1, 5, and 10). For
analyses, all night samples of each site were aggregated. We brought all samples to Germany and mounted and
identied specimens using identication keys49 and online identication web sites for moths and butteries62,63.
Aerwards, we submitted one or two specimens of each morphospecies for DNA barcoding to Canadian Centre
for DNA Barcoding (CCDB) to corroborate our identication of morphospecies. e results on the creation of a
DNA barcode library for the collected species will be published in a separate paper (in preparation). Superfamilies
of Mimallonoidea, Drepanoidea, Lasiocampoidea, Bombycoidea, Geometroidea, and Noctuioidea are included
in the clade of macroheterocera64. In this study we also included Sesiidae, Zygaenidae and Cossidae because of
their traditional assignment to the (non-monophyletic) macro-moths.
Environmental data. We included precipitation, temperature, wind, altitude, plant cover, plant species com-
position and the number of livestock as environmental variables. We obtained climatic variables from WorldClim
dataset65. To study vegetation structure, we measured vegetation cover and plant species richness in a 10m ×
10m area with ve replications per site. Livestock droppings were counted in the plots to assess grazing pressure.
We received vegetation data from Julian Ahlborn (Leibniz Centre for Agricultural Landscape Research) and
Christine Römermann (University of Jena) for comparison and easier identication of our samples in the eld.
Botanist Tungalag Radnaakhand (National University of Mongolia) veried the identication of plant species
from dried specimens of our herbarium. We obtained livestock abundance data for each site from the National
Statistical Oce of Mongolia66 (TableS6). We measured coordinates and elevation of the sites with a Garmin
Oregon 700 GPS.
Data analysis. Prior to analyses, we checked all variables for normal distribution by using QQ plot. Depend-
ing on these results we chose the appropriate statistical tests or applied log-transformation to normalize data for
calculation.
Alpha diversity. We quantied moth alpha diversity (Hill numbers) of each site, i.e., species richness (q = 0),
Shannon diversity, the exponential of Shannon entropy (q = 1), and the reciprocal Simpson’s diversity (q = 2)
using the R-package ‘vegan’67. We estimated species richness with iChao1 index using R-package SpadeR. is
index is an improved version of Chao1. To estimate species richness, it uses rare species or the number of sin-
gletons. To compare species richness, species diversity, and abundances of all macro-moths of each site along
the latitudinal gradient and explore the community pattern at the species and family levels, we used the non-
parametric Wilcoxon tests based on data from sampling nights. For comparison the number of unique species of
desert and grassland, we used the non-parametric Kruskal–Wallis Test. To study how species richness changes
along the climatic gradient, we applied two widely used climatic variables from WorldClim dataset65: mean
annual temperature (Bio1) and mean annual precipitation (Bio12). We determined niche structure of moth
communities along the climatic gradient by analyzing coenoclines of the ten most abundant species. We applied
generalized additive models (GAM) with Gaussian distribution and link function to produce the coenoclines.
For coenoclines, we used the method of Homann etal.32. A general linear model (GLM) was used to calculate
the relationship between species richness and climatic variables. Pearson correlation was applied to correlate the
Hill numbers of each site with environmental variables.
Beta diversity. To investigate the major family composition of communities we performed correspondence
analysis using the R-package ‘vegan’28. K-means clustering of unsupervised learning algorithm was applied to ten
sites to cluster them into groups based on their similarity. Clustering was conducted on major family matrices
with Hellinger transformation. To study species composition dierences between macro-moth communities, we
applied permanova on species composition matrix (log + 1 transformation with Bray–Curtis similarity) using
adonis function of the R-package ‘vegan’. To visualize species overlap between desert and grassland sites, we draw
Venn diagrams by using the ‘ggvenn’ package68. Southern sites in desert biome are shown in yellow, northern
sites in grassland biome are shown in green.
For calculating the pairwise beta diversity among sites and also species composition dierences along the
latitudinal gradient, we applied the Baselga’s33 approach with Jaccard’s dissimilarity index, which partitions beta
diversity into two components: spatial turnover and nestedness34,52. Partitioning beta diversity measurements
are essential to understand the dierences between communities; even if two sites have the same beta diversity,
the dierence can be due to species replacement or species loss or gain23.
Spatial turnover is the replacement of some species by other species from one site to the next. Nestedness
implies that the species assemblage of a species-poor site is the subset of a dierent species-rich site. We used the
R package ‘betapart’69 to calculate beta diversity and its respective partitions. Sampling nights with only one spe-
cies were excluded from the analysis. We used non-parametric Wilcoxon tests to compare Jaccard’s beta diversity,
spatial turnover and nestedness among sites based on data from sampling nights. Piecewise regressions were
used to reveal a breakpoint of beta diversity between macro-moth communities along the latitudinal gradient.
We examined breakpoints between 43° and 50° with a 1° interval and chose a breakpoint with the lowest residual
standard error70. We performed this procedure for the beta diversity components separately. We compared
piecewise regression models with corresponding simple linear regression models with ANOVA to estimate the
improvement of the model t. To check the model t, we also compared the R2 of piecewise regression models
with the R2 of the simple linear regression models.

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We used Procrustes analysis in R package ‘vegan’ to compare the distance matrix of the moth community with
distance matrices of the vegetation guild and livestock abundances at the sites. A signicant result demonstrates
the similarity of a matrix with a target matrix suggesting an interaction of the observed patterns. To study how
the interaction between biome type and environmental variables aect the species richness and the diversity of
macro-moths across the whole gradient, we applied generalized linear regression model with negative binomial
family and linear regression, respectively. Negative binomial distribution is applied to avoid overdispersion. To
t the negative binomial generalized model, we used glm.nb function of ‘MASS’ package and to t the linear
regression lm function of ‘stats’ package were used. Precipitation, vegetation cover, vegetation richness, livestock,
wind, and altitude were included in the model as a predictor variable, while species richness, Shannon diversity,
Simpson diversity were response variables. For additive and interaction models, biome was used as a categorical
variable. For each predictor variable we built three models: (1) using only a predictor variable without biome, (2)
additive model: predictor variable + biome, (3) interaction eect: predictor variable × biome. For choosing the
best model between these three models for each predictor variable, we used Akaike’s Information Criterion (AIC).
All analyses were performed using R version 3.6.371.
Data availability
Species list of all sites and other supporting information can be found in the Supplementary Material of this
article.
Received: 9 February 2021; Accepted: 12 July 2021
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Acknowledgements
We thank Julian Ahlborn, Christine Römermann, Birgit Lang, Munkhzul Oyunbileg for providing their study
design and vegetation data. We thank Badamnyambuu Iderzorig, Uujin Togtokh, Enkhtur Dambiijantsan, Byam-
basuren Munkhjargal, Temuujin B., Davaadorj Enkhtur for their eld assistance. We thank the local herders,
especially the family of Byambaa for their hospitality. We also thank Badamnyambuu Iderzorig and Erdenet-
setseg Batdelger, who helped with the transportation of moth samples to Germany. We are grateful to Tungalag
Radnaakhand for conrming the plant species. Special thank goes to Enkhmandal Orsoo for mounting most

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specimens for identications. We are grateful to Samuel Hofmann for his comments on an early dra. We thank
Aurora MacRae-Crerar from the Critical Writing Program at the University of Pennsylvania for her linguistic
review of the manuscript.
Author contributions
K.E., G.B., B.B. and M.P. designed research. K.E. performed research, analyzed data and wrote the paper with
inputs from M.P., G.B. and B.B. All authors have read and agreed to the published version of the manuscript.
Funding
Open Access funding enabled and organized by Projekt DEAL. K.E. funded by DAAD [Research Grants Doctoral
Programme in Germany, 2017/18 (57299294)]. Field work was supported by the Taylor Family-Asia Founda-
tion Endowed Chair in Ecology and Conservation Biology and the Department of Equal Chance Opportunity,
University of Bayreuth.
Competing interests
e authors declare no competing interests.
Additional information
Supplementary Information e online version contains supplementary material available at https:// doi. org/
10. 1038/ s41598- 021- 94471-3.
Correspondence and requests for materials should be addressed to K.E.
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