Dörgeetal. Parasites Vectors (2020) 13:461
Incompletely observed: niche estimation
forsix frequent European horsey species
(Diptera, Tabanoidea, Tabanidae)
Dorian D. Dörge1*, Sarah Cunze1 and Sven Klimpel1,2
Background: More than 170 species of tabanids are known in Europe, with many occurring only in limited areas or
having become very rare in the last decades. They continue to spread various diseases in animals and are responsible
for livestock losses in developing countries. The current monitoring and recording of horseﬂies is mainly conducted
throughout central Europe, with varying degrees of frequency depending on the country. To the detriment of tabanid
research, little cooperation exists between western European and Eurasian countries.
Methods: For these reasons, we have compiled available sources in order to generate as complete a dataset as possi-
ble of six horseﬂy species common in Europe. We chose Haematopota pluvialis, Chrysops relictus, C. caecutiens, Tabanus
bromius, T. bovinus and T. sudeticus as ubiquitous and abundant species within Europe. The aim of this study is to esti-
mate the distribution, land cover usage and niches of these species. We used a surface-range envelope (SRE) model in
accordance with our hypothesis of an underestimated distribution based on Eurocentric monitoring regimes.
Results: Our results show that all six species have a wide range in Eurasia, have a broad climatic niche and can there-
fore be considered as widespread generalists. Areas with modelled habitat suitability cover the observed distribution
and go far beyond these. This supports our assumption that the current state of tabanid monitoring and the recorded
distribution signiﬁcantly underestimates the actual distribution. Our results show that the species can withstand
extreme weather and climatic conditions and can be found in areas with only a few frost-free months per year. Addi-
tionally, our results reveal that species prefer certain land-cover environments and avoid other land-cover types.
Conclusions: The SRE model is an eﬀective tool to calculate the distribution of species that are well monitored in
some areas but poorly in others. Our results support the hypothesis that the available distribution data underestimate
the actual distribution of the surveyed species.
Keywords: Tabanidae, Tabanus, Haematopota, Chrysops, Niche, Climate, Land cover, Surface range, Model, Envelope
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Parasites & Vectors
1 Institute for Ecology, Evolution and Diversity, Goethe-University,
Max-von-Laue-Str. 13, 60439 Frankfurt/Main, Germany
Full list of author information is available at the end of the article
Page 2 of 10
Dörgeetal. Parasites Vectors (2020) 13:461
Common throughout the world, tabanids are hematopha-
gous dipterans. Worldwide there are about 4400 known
species [1, 2] of which more than 170 occur in Europe .
Female horseﬂies can cause severe skin lesions [4, 5] and
are able to eﬀectively transmit diﬀerent diseases [6–8]
due to their excessive feeding behavior . ese include
the eye worm Loa loa (sausing loaiasis) [2, 7, 10, 11], the
equine infectious anemia virus [12–14], Trypanosoma
theileri [15, 16] and T. evansi (Surra) which mainly infect
livestock  but can also infect humans . Further
transmittable pathogens are Spiroplasma [18–20], Bacil-
lus tularensis (causing tularemia) , Bacillus anthrax
(Anthrax) , bovine mycoplasma , Elaeophora sch-
neideri (causing elk and deer ﬁlariosis)  as well as Bes-
noitia besnoiti (causing bovine besnoitiosis) .
Many species require slow ﬂowing or stagnant water
with shallow zones for egg-laying and for the migration of
larvae between land and water. e larvae live predatorily
or feed on detritus at the edge of the water, seeking dry
ground to pupate. Other species, however, are specialized
in drier areas and do not require bodies of water but only
moist soil or dung from grazing animals [2, 3, 25–27]. As
a result of the draining of many of Europe’s wetlands [28,
29], the number of susceptive horseﬂies has fallen sharply
. Current insecticide- and land-use changes are fur-
ther reducing the numbers [31–34]. However, especially
in poorer countries, cattle and other livestock continue to
suﬀer due to lack of protection or control options, result-
ing in anemia or severe skin damage to the aﬀected ani-
mals [2, 35, 36].
Recent research within Europe is focused mainly on
monitoring points within a few countries for the occur-
rence of horseﬂies and potential control measures 
as well as ecological and anthropogenic eﬀects on their
populations . To date, there are no standardized and
repeatedly executed monitoring protocols for horseﬂies
in Eurasia (and other continents as well), which makes
it diﬃcult to acquire, compile and utilize existing data
for calculations and projections. Due to the diﬀerent
monitoring schemes within diﬀerent countries, occur-
rences are either over- or underestimated and combin-
ing these datasets is complicated. Based on the lack of
monitoring in many countries, not much is known about
horseﬂy complete distribution. Finally, since only sites
in western Europe have been extensively recorded, the
distribution in the rest of Eurasia is most likely greatly
Six species commonly observed in central Europe were
used for our study: Chrysops relictus (Meigen 1820) and
the morphologically similar species Chrysops caecutiens
(Linnaeus, 1758), Haematopota pluvialis (Linnaeus,
1758), Tabanus bromius (Linnaeus, 1758), Tabanus
bovinus (Linnaeus, 1758) and Tabanus sudeticus (Zeller,
1842). Tabanus spp. and Haematopota spp. are relatively
eurytopic and do not require stagnant water but moist
soil for egg-laying and larval development [25, 39–43],
while Chrysops belongs to the hydrophilous ecological
group and depends on ponds, rivers or lakes .
To ﬁnd a realistic dispersal of the species, we calcu-
lated the climatic niche and the land cover allocation of
occurrence points using available literature and database
data ranging back to 1990. We used the ecological niche
model (ENM) with a surface-range envelope (SRE) to
project the potential distribution within Europe and Asia.
In order to counteract the present sampling bias, we used
this method, as it is particularly resistant to over- and
under-representation of species in databases and litera-
ture. We also compared the modelled niches (climatic
envelopes), as well as the preferred type of land cover and
the number of frost-free months required for the six spe-
cies to exist.
For our analysis, we compiled data collected from an
extensive literature research [37, 45–113] as well as
the GBIF-Database [114–120]. Occurrence data were
adjusted to the spatial resolution (5 arc-minutes) of the
environmental raster data and reduced to one occurrence
per grid cell.
Estimation ofthepotential distribution
For the niche range analysis, 8 bioclimatic variables pro-
vided by Worldclim  were downloaded at a spatial
resolution of 5 arc-minutes. e variables Bio5, Bio6,
Bio13, Bio14, Bio18 and Bio19 were used. We computed
SREs (as implemented in the biomod2 R-package 
for each tabanid species and considered three models:
the full model (yellow in the depictions), 95% (orange)
and 90% (red) of all occurrence points. Maps were cre-
ated in Esri ArcGIS .
Data were acquired from ESA GlobCover  for the
activity phases, as well as for the land-cover preference
comparisons. For the activity comparison, the amount of
frost-free months was derived from the monthly mini-
mum temperature, provided by Worldclim . e
type of land cover was obtained from GlobCover at the
respective sites for the land-cover comparison and the
relative frequencies of individual LC-types were com-
pared with the availability of the LC-type (relative fre-
quency in the study area). e range of the study area
is reduced to −10°W, 45°E, 79°N and 35°S based on the
lack of data from more eastern areas. Land cover cat-
egories were combined when adequate, resulting in 11
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Dörgeetal. Parasites Vectors (2020) 13:461
categories: Cropland > 50% (11, 14); Grass/Shrubland
(110, 120, 130, 140); Broadleaf Forest (40, 50, 60); Mixed
Forest (100); Dense Evergreens (70); Light Evergreens
(90); Mosaic Vegetation (20, 30); Sparse Vegetation (150);
Artiﬁcial (190); Water Bodies (210); and Other (160, 170,
180, 195, 215).
Figure1 shows three diﬀerent models of all six surveyed
species. e 90% and 95% models for C. caecutiens
showed a very fragmented distribution with the center of
these models lying in the northern part of Europe. e
full model extended from central Spain over all European
countries, including Turkey and Russia, as far as the east-
ern part of Siberia. A very similar picture emerged for C.
relictus and H. pluvialis, where only the areas in Spain
and Turkey are missing in the comparison. Incorporat-
ing the niches’ climatic variables (Fig.2), all three species
showed very similar patterns: the 90% and 95% model
mostly made up less than 50% of the full model and were
skewed in one direction. In climatic variable Bio18, C.
caecutiens showed a higher tolerance for low precipita-
tion than C. relictus and H. pluvialis.
For T. bovinus, T. bromius and T. sudeticus, the 90% and
95% models were closer to the full model. e full model
closed gaps in central Europe as well as added areas in
(northeastern) Finland and central Russia. For T. sudeti-
cus, the full model closed most gaps within the original
distribution. e climatic variables (Fig.2) were relatively
similar for these three species. For T. sudeticus, the 95%
model incorporated most of the niche when considering
only the variables.
Figure 3 shows that most species (except T. sudeti-
cus) occur in small numbers in areas with two frost-free
months. Most occurrences are within 9 months for C.
relictus, C. caecutiens and H. pluvialis. Haematopota plu-
vialis also had a slightly decreased occurrence rate of 11
months. e highest numbers of individuals of T. bovinus
occured at 5 and 6 months. Tabanus bromius showed a
steady distribution at 5, 6, 7, 9 and 11 months. Tabanus
sudeticus showed the most individual occurrences at 7
and 11 months. e data from 5 months on (except for 10
months) showed a slightly lower frequency. No species
demonstrated more than 3% of their occurrences in areas
with 10 frost-free months.
e comparison of land cover type and species occur-
rence (Fig.4) shows that in the Cropland category, all the
species occured at a frequency between half and a quar-
ter of the expected value. Tabanids occured in areas with
the category Grass/Shrubland between 2–3.5 times the
expected frequency, except for T. bovinus, which occured
only slightly more frequently. In Broadleaf Forest, there
were only minor deviations from the expected value,
with H. pluvialis occurring slightly less frequently and T.
bromius occurring slightly more frequently. Similarly, in
Mixed Forest there was only a slightly higher value for T.
bovinus. In the category Dense Evergreens, C. caecutiens,
C. relictus and T. bovinus showed a negative deviation
from the expected value between 60% and 90% while T.
bromius (30%) and T. sudeticus (80%) were more com-
mon. Except for the values, this eﬀect was exactly the
opposite in the category Light Evergreens. Mosaic veg-
etation shows no fundamental diﬀerence. Sparse Vegeta-
tion showed a slight increase in occurrence of T. bovinus,
but a reduction of the other species between 60–180%.
e Artiﬁcial category showed the largest deviations
from the expected value by far, with positive deviations
between 260% (2.6 times the expected value) and 510%
(5.1 times the expected value). In the Water Bodies cat-
egory, the values were slightly negative for C. caecutiens,
C. relictus and T. bovinus, while they are more pro-
nounced for the species T. bromius (130%) and T. sudeti-
cus (80%). e category Other showed medium to strong
negative deviations for all species except for T. bovinus.
We modelled the potential distribution of six common
horseﬂy species in Eurasia and compared their niches.
An SRE model was used because no extensive monitoring
with standardized methods exists. Hence, the available
data show a strong bias with large regions being severely
underrepresented or not considered at all. Due to the
very dense sampling in western Europe, a skewed picture
emerges, although several of the species also occur about
6000 km further east. e investigated species require
moist soil (Tabanus, Haematopota) or lakes, ponds and
rivers (Chrysops) for egg deposition and larval develop-
ment [25, 39–42]. In addition, the larvae are often detriv-
orous or can feed predatorily on small insects or worms
. e species are relatively common and widespread
in Europe and are therefore likely to appear in many sur-
veys, making them adequate examples for this methodol-
ogy. For the model, we counteracted the sampling bias as
much as possible by reducing the number of samples to
one per grid cell. It is therefore likely that all species can
truly ﬁll most of the niche (full model) calculated in the
When comparing the areas of the 90% model, it
becomes apparent that the distribution area is very
small due to a dense monitoring in western and central
Europe and a very similar distribution for all six spe-
cies could be expected. When taking the full model into
account, a diﬀerent picture emerges. ree species, i.e.
C. caecutiens, C. relictus and H. pluvialis, have a much
larger niche than evident from the data. Here, C. cae-
cutiens has the largest distribution and the distribution
Page 4 of 10
Dörgeetal. Parasites Vectors (2020) 13:461
Fig. 1 Modelled distribution of the six species. Key: yellow, full model; orange, 95% model (5% outliers removed); red, 90% model (10% outliers
removed). Figure created with Esri ArcGIS 
Page 5 of 10
Dörgeetal. Parasites Vectors (2020) 13:461
areas of the other three species overlap even in the
eastern areas, where only few surveys have been made.
Tabanus bovinus and T. bromius have similarly large
niches which are mostly overlapping and are supported
by data collection in Europe. Tabanus sudeticus has
the smallest distribution. e distribution of collected
sightings of T. bovinus and the results of our calculation
Fig. 2 Comparison of the modelled niches for the six species, Chrysops caecutiens, C. relictus, H. pluvialis, T. bovinus, T. bromius and T. sudeticus, in
diﬀerent climatic variables. Abbreviations: Bio5, maximum temperature of warmest month; Bio6, minimum temperature of coldest month; Bio13,
precipitation of wettest month; Bio14, precipitation of driest month: Bio18, precipitation of warmest quarter; Bio19, precipitation of coldest quarter.
Key: yellow, full model; orange, 95% quantile model; red, 90% quantile model
Fig. 3 Percentage occurrence as a function of the number of frost-free months. For each species, the sum of all categories equals 100%.
Abbreviation: mo, months
Page 6 of 10
Dörgeetal. Parasites Vectors (2020) 13:461
are very close to the known distribution which is shown
When comparing the frequency of occurrence as a
function of the number of frost-free months, it is
apparent that ﬁve of the six species can occur in areas
with only two frost-free months, albeit with only a few
individuals. is frequency gradually increases up to
ﬁve months, with T. sudeticus appearing in areas with
at least four frost-free months. e remaining numbers
show the direct inﬂuence of the sampling bias towards
central and western Europe. e extreme peak at nine
months is mainly due to heavy sampling in central
Europe, while the increased numbers at 11 months are
almost entirely due to the inclusion of England and Ire-
land. It is known that horseﬂies hibernate as larvae and
may require several years for their development .
In central Europe, development spans between one and
three years. However, assuming an area with only two
frost-free months per year, this number could increase
signiﬁcantly. e most cold-tolerant species are C. cae-
cutiens, C. relictus and H. pluvialis with occurrences in
areas that plunge below −58°C.
As expected, monoculture cropland was avoided by all
six species. is may be due to pesticide use, lack of hosts
and lack of areas for egg-laying and larval development
and lack of adequate sites for mating behavior, as well
as a shortage of sugar sources [127–129]. It is also not
surprising that grassland and scrubland are preferred.
Since Grasslands, or areas with some lowland scrub, are
mostly used as grazing land for livestock , taban-
ids can easily ﬁnd the hosts they need. Broadleaf forest,
mixed forest and mosaic vegetation show no particular
eﬀect on tabanid preference or aversion. However, Dense
Evergreen and Light Evergreen showed an interesting pat-
tern on preference and aversion, which largely balances
out when the two categories are combined. We remark
that C. relictus, C. caecutiens and T. bovinus avoid dense
evergreen, while at least T. sudeticus prefers it. Sparse
vegetation is avoided by all species except for T. bovinus.
is can be explained by the fact that within these areas,
signiﬁcantly fewer animals can serve as hosts. An inter-
esting result is that all species have an extreme prefer-
ence for Artiﬁcial areas category. is is most likely due
to the fact that populated areas harbor domestic animals,
grazing animals, livestock and, ultimately, people in the
immediate vicinity. It is important to note that although
the dataset has been adjusted and reduced to one point
per grid cell, a sampling bias is still present towards heav-
ily populated as well as frequently surveyed areas. is
would explain at least part of the extreme values of the
Artiﬁcial category. Baldacchino et al.  were able to
show parts of the current horseﬂy diversity of western
and southern European countries in a large-scale study of
almost 80,000 captured animals. In comparison to other
areas, a signiﬁcantly lower diversity of species could be
found on pastureland, with larger, well-ﬂying species pre-
ferring these areas for host searching. Another study by
Baldacchino etal.  also suggested a preference for
mosaic landscape and light forest. Our analysis cannot
Fig. 4 Deviation of occurrence of the species compared to available land cover. A positive value of 100% shows that the species occurs twice as
often as expected in the respective areas. Conversely, a negative value of 100% indicates an abundance that is only half as high as expected
Page 7 of 10
Dörgeetal. Parasites Vectors (2020) 13:461
conﬁrm this result since our dataset does not support any
preference for mosaic landscape. On the other hand, our
analyses show that forest cover presents mixed results
for aversion or preference by the examined species. e
land-cover analysis also shows that tabanids equally
colonize water bodies if they are available. However, the
numbers mostly show an underrepresentation, which is
explained by the fact that the available land cover is taken
with a resolution of 300 meters, so most water bodies
are not presented in the dataset. e category “Other”
consists of several land-cover types with very few occur-
rences and should therefore, be considered carefully if at
all. Overall, we have reduced the inﬂuence of sampling
biases as much as possible, but the eﬀects still shift our
results. A standardized monitoring programme is needed
to clarify these results and enable future calculations to
be more exact.
Our envelope model included Japan as a suitable area for
all species. is is highly unlikely, at least for the three
Tabanus species. According to the GBIF database, H. plu-
vialis occurs in Japan. However, this isolated occurrence
was not included in the calculation due to the extreme
distance to other sites but is a realistic occurrence point
for this species after calculating the model. Other remote
areas such as the Asian Highlands (Pamir, Hindukush,
Himalaya) were additionally estimated as suitable sites
by our model. We doubt that these mountain ranges are
actually suitable areas for tabanid habitation and that an
exclusionary factor is lacking in the model. For the three
Tabanus species speciﬁcally, it is very unlikely that they
can be found in these areas. For Chrysops species and H.
pluvialis, however, the areas are within the range of the
main distribution spectrum but are discontinuous. We
considered temperature and precipitation as important
climatic factors. ere can also be other factors that are
not considered in this study, but which locally exclude
the occurrence of these species (e.g. snow cover, humid-
ity). Our model is based on a continental scale, where
climatic factors are the most important to show rough
distribution patterns . Fine-scale models could go
into more detail and include microclimatic eﬀects, but
due to the continental scale and the lack of available data,
this is beyond the scope of this study. e delimited parts
of the model (e.g. southern China, mountain ranges of
Asia) in which some species could occur due to a cal-
culated suitable habitat, but either do not occur or it is
unknown, show possible distribution areas, which, how-
ever, have not been colonized due to dispersal barriers or
a missing limiting factor.
e distribution of most tabanids is not monitored
enough in many areas. e SRE model is an eﬀec-
tive tool to calculate the distribution of species that are
well monitored in some areas but poorly in others. Our
results support the hypothesis that the available distri-
bution data underestimate the actual distribution of the
surveyed species. Especially C. relictus, C. caecutiens and
H. pluvialis have a much larger calculated niche than the
collated observations represent. Our results also show
that ﬁve of the six species occur in areas with only two
frost-free months per year, revealing a strong resistance
against temperatures up to −58°C. We found that the
six species of horseﬂies strongly prefer populated areas,
as well as grassland and scrubland and avoid arable land
and regions of sparse vegetation. Our results reveal
that only the observed distribution of T. bovinus closely
resembles the calculated niche while the other species are
most likely not monitored enough. Both Chrysops spe-
cies have almost the same observed distribution and cal-
culated niche, as well as land-cover preferences. We also
suggest a standardized monitoring programme, which
can improve and validate this methodology for tabanids
and other species. With the help of predictions from this
model, further monitoring can be planned in areas where
few or no observations have been recorded to conﬁrm
and extend our model.
We thank Dr. Adrienne Jochum for proofreading the manuscript.
DDD designed and conceptualized the study, wrote the main manuscript text,
executed the statistical analysis, interpreted the data and prepared Figs. 2, 3,
4. SC executed the statistical analysis, interpreted the data and prepared Fig. 1.
SK designed and conceptualized the study. All authors read and approved the
Open access funding provided by Projekt DEAL. This research was funded
by the German Federal Ministry of Food and Agriculture (BMEL) through the
Federal Oﬃce for Agriculture and Food (BLE) (Grant Numbers 2819104415 and
2819105115) and by the Uniscientia Foundation (P 121-2017).
Availability of data and materials
The data are available through the cited references as stated in the Methods
Ethics approval and consent to participate
Consent for publication
The authors declare that they have no competing interests.
1 Institute for Ecology, Evolution and Diversity, Goethe-University,
Max-von-Laue-Str. 13, 60439 Frankfurt/Main, Germany. 2 Senckenberg Biodi-
versity and Climate Research Centre, Senckenberg Gesellschaft für Natur-
forschung, Senckenberganlage 25, 60325 Frankfurt/Main, Germany.
Page 8 of 10
Dörgeetal. Parasites Vectors (2020) 13:461
Received: 22 June 2020 Accepted: 24 August 2020
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