very preliminary distribution maps for...

Very preliminary distribution maps for

Scathophagidae

Nanna tibiella ♂ SGB

Stuart Ball Feb 2014

Coverage

Records collated by Stuart Ball From 1980 onwards Before 1980

Additional records from the NBN Gateway From 1980 onwards Before 1980

Questionable ?

Predicted number of species

Explanation The main distribution map uses the symbols shown below the

coverage map (page 2). It includes records collated by Stuart

Ball and records downloaded from the NBN Gateway on

29/01/2014.

Potential distribution

Two attempts have been made to predict the potential

distribution and are shown to the right of the main distribution

map. These are rescaled frequency maps made using Frescalo

and a species distribution model made using Maxent.

Frescalo maps

The Frescalo (FREquency SCaling LOcal) method of Hill

(2012) corrects for recording effort by considering the

proportion of the commonest species that have been recorded

Main distribution

map Frequency corrected for

recording effort using

Frescalo

Potential distribution

according to a Maxent

model

Phenology - number of

records per week

Wing lengths

in a “neighbourhood” around a target location. If a high

proportion of the commonest species in the neighbourhood

have been recorded, then the locality is considered well

recorded. Neighbourhoods are defined as a set of locations that

are both physically close to the target locality and also similar

in terms of the environment they offer. Essentially, the

observations in a neighbourhood are pooled and used to

estimate the frequency of a species and then this estimate is

rescaled depending on the amount of recording. The maps

used here show the rescaled frequencies of species.

The notion here is that, if a species is known to occur at some

location, then one would expect it to occur in similar places

nearby. Frescalo is taking the known occurrences and

“spreading them out” over neighbourhoods of nearby and

similar grid squares. This can be seen very clearly when there is

an isolated record (e.g. Ernoneura argus in Northumberland –

page 30) which gets spread out into a blob around that

location. Where there are a reasonable number of records,

these blobs coalesce filling in the gaps between the scattered

records.

These maps appear to work quite well when there are

reasonable numbers of records and the results are often quite

compelling. They don’t work very well when records are very

sparse or isolated.

Frescalo also produces an estimate of the expected number of

species per grid square and this is mapped on page 3.

Maxent

Maxent (maximum entropy modelling) takes the known points

of presence of a species and a series of “environmental layers”

– maps of things like land cover, climate, topography, soil, etc

and asks the question – what environmental conditions are

common to the places where the species is known to occur? It

then looks for other places where this combination of

environmental conditions prevail – and these are the places it

predicts that the species is likely to occur. The modelling was

actually carried out at 1km square resolution, but the results

have been aggregated to 10km squares to make them visible.

The map shows the maximum predicted probability in each

10km square.

The method requires at least 20 1km square occurrences to

make modelling possible and really needs rather more than

that to get reasonable results. There was sufficient data to

model 41 of the species. Clearly, the results depend on the

environmental layers providing appropriate information that

describes the species’ habitat. If factors that are important to

the species are not represented in the available environmental

variables, then the model cannot be expected to work well.

However, surprisingly good results are sometimes achieved by

this method despite quite sparse distribution information.

Phenology

The histogram shows the number of records falling in each

week of the year. Ideally, only field records of adult flies are

used but, in most cases, the relevant information is not given in

the original record so this is not certain. Thus, it is likely that

some records for species such as Parallelomma paridis (page

48) may actually be for larval mines or the emergence date of

reared adults. Also bear in mind that the data represents all

years combined. Some species may have quite short emergence

periods, but the date of the peak will vary from year to year

depending on the weather. By pooling records over all years,

the expected sharp peak becomes spread out.

Wing length

The box plots show a summary of measurements of the wing

length of male and female specimens on a common scale. In

each case, the central black bar shows the average, the grey box

the standard deviation, the whiskers 5 and 95 percentile and

circles show outliers. The position of the boxes within the plot

gives a visual indication of whether the species is large or small

and the width of the grey box indicates how variable a species

is in size. For example, Scathophaga stercoraria (page 58) is

very variable in size, so the boxes in the wing length plot are

wide.

Coverage

At the time of writing, there were records from 1,701 10km

squares (60% of the 10km squares including land in GB)

although of the 15,775 unique records (i.e. unique

combinations of species grid reference and date) 6,160 (39%)

were for Scathophaga stercoraria and a further 2,189 (14%)

for S. furcata. Thus these two common dung flies account for

53% of the records! Records for many other species are very

much more sparse than I would expect and cannot be taken as

a reasonable representation of their status.

Reference

Hill, M. O. 2012. Local frequency as a key to interpreting

species occurrence data when recording effort is not known.

Methods in Ecology and Evolution, 3, 195–205.

Phillips, S. J., Anderson, R. P. & Schapire, R. E. 2006.

Maximum entropy modeling of species geographic

distributions. Ecological Modelling, 190, 231-259.

Acanthocnema glaucescens (Fallén, 1819)

Acanthocnema nigrimana Becker, 1894

Ceratinostoma ostiorum Collin, 1958

Chaetosa punctipes Fallén, 1819

Cleigastra apicalis Zetterstedt, 1846

Conisternum decipiens Meigen, 1826

Conisternum obscurum Rondani, 1866

Conisternum tinctinerve Meigen, 1826

Cordilura aemula Loew, 1864

Cordilura albipes (Linnaeus, 1758)

Cordilura atrata Meigen, 1826

Cordilura ciliata Meigen, 1826

Cordilura hyalinipennis (Ringdahl, 1936)

Cordilura impudica Zetterstedt, 1838

Cordilura picipes (Zetterstedt, 1838)

Cordilura picticornis (Fallén, 1819)

Cordilura pubera (Zetterstedt, 1838)

Cordilura pudica (Fallén, 1819)

Cordilura rufimana (Fallén, 1826)

Cordilura ustulata (Fabricius, 1794)

Cosmetopus dentimanus Zetterstedt, 1838

Delina nigrita (Fallén, 1819)

Ernoneura argus (Zetterstedt, 1838)

Gimnomera tarsea (Zetterstedt, 1846)

Gonatherus planiceps (Zetterstedt, 1838)

Hydromyza livens (Meigen, 1826)

Leptopa filiformis (Fallén, 1819)

Megaphthalma pallida (Becker, 1894)

Microprosopa pallidicauda (Hackman, 1956)

Nanna armillata (Zetterstedt, 1838)

Nanna brevifrons (Meigen, 1826)

Nanna fasciata (Wiedemann in Meigen, 1826)

Nanna flavipes (Loew, 1864)

Nanna inermis (Fallén, 1819)

Nanna multisetosa Hering, 1923

Nanna tibiella (Meigen, 1826)

Norellia spinipes (Zetterstedt, 1838)

Norellisoma lituratum Haliday in Curtis, 1832

Norellisoma opacum (Say, 1823)

Norellisoma spinimanum Meigen, 1826

Parallelomma paridis (Fallén, 1819)

Parallelomma vittatum (Fabricius, 1794)

Pogonota barbata Oldenberg, 1923

Scathophaga calida (Linnaeus, 1758)

Scathophaga furcata (Linnaeus, 1758)

Scathophaga inquinata (Fabricius, 1794)

Scathophaga litorea Rondani, 1866

Scathophaga lutaria (Fallén, 1819)

Scathophaga pictipennis (Meigen, 1826)

Scathophaga scybalaria

Scathophaga stercoraria Robineau-Desvoidy, 1830

Scathophaga suilla Zetterstedt, 1838

Scathophaga taeniopa Strobl, 1894

Spaziphora hydromyzina Becker, 1894

Trichopalpus fraternus Meade, 1885

very preliminary distribution maps for...

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