Very preliminary distribution maps for. Scathophagidae. Nanna tibiella SGB

Transcription

1 Very preliminary distribution maps for Scathophagidae Nanna tibiella SGB Stuart Ball Feb 2014

2 Coverage Records collated by Stuart Ball From 1980 onwards Page 2 Before 1980 Additional records from the NBN Gateway From 1980 onwards Before 1980 Questionable?

3 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. Page 3

4 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 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 Page 4

5 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 Page 5

6 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 Page 6

7 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 Local frequency as a key to interpreting species occurrence data when recording effort is not known. Methods in Ecology and Evolution, 3, Phillips, S. J., Anderson, R. P. & Schapire, R. E Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, Page 7

8 Acanthocnema glaucescens (Fallén, 1819) Page 8

9 Acanthocnema nigrimana Becker, 1894 Page 9

10 Ceratinostoma ostiorum Collin, 1958 Page 10

11 Chaetosa punctipes Fallén, 1819 Page 11

12 Cleigastra apicalis Zetterstedt, 1846 Page 12

13 Conisternum decipiens Meigen, 1826 Page 13

14 Conisternum obscurum Rondani, 1866 Page 14

15 Conisternum tinctinerve Meigen, 1826 Page 15

16 Cordilura aemula Loew, 1864 Page 16

17 Cordilura albipes (Linnaeus, 1758) Page 17

18 Cordilura atrata Meigen, 1826 Page 18

19 Cordilura ciliata Meigen, 1826 Page 19

20 Cordilura hyalinipennis (Ringdahl, 1936) Page 20

21 Cordilura impudica Zetterstedt, 1838 Page 21

22 Cordilura picipes (Zetterstedt, 1838) Page 22

23 Cordilura picticornis (Fallén, 1819) Page 23

24 Cordilura pubera (Zetterstedt, 1838) Page 24

25 Cordilura pudica (Fallén, 1819) Page 25

26 Cordilura rufimana (Fallén, 1826) Page 26

27 Cordilura ustulata (Fabricius, 1794) Page 27

28 Cosmetopus dentimanus Zetterstedt, 1838 Page 28

29 Delina nigrita (Fallén, 1819) Page 29

30 Ernoneura argus (Zetterstedt, 1838) Page 30

31 Gimnomera tarsea (Zetterstedt, 1846) Page 31

32 Gonatherus planiceps (Zetterstedt, 1838) Page 32

33 Hydromyza livens (Meigen, 1826) Page 33

34 Leptopa filiformis (Fallén, 1819) Page 34

35 Megaphthalma pallida (Becker, 1894) Page 35

36 Microprosopa pallidicauda (Hackman, 1956) Page 36

37 Nanna armillata (Zetterstedt, 1838) Page 37

38 Nanna brevifrons (Meigen, 1826) Page 38

39 Nanna fasciata (Wiedemann in Meigen, 1826) Page 39

40 Nanna flavipes (Loew, 1864) Page 40

41 Nanna inermis (Fallén, 1819) Page 41

42 Nanna multisetosa Hering, 1923 Page 42

43 Nanna tibiella (Meigen, 1826) Page 43

44 Norellia spinipes (Zetterstedt, 1838) Page 44

45 Norellisoma lituratum Haliday in Curtis, 1832 Page 45

46 Norellisoma opacum (Say, 1823) Page 46

47 Norellisoma spinimanum Meigen, 1826 Page 47

48 Parallelomma paridis (Fallén, 1819) Page 48

49 Parallelomma vittatum (Fabricius, 1794) Page 49

50 Pogonota barbata Oldenberg, 1923 Page 50

51 Scathophaga calida (Linnaeus, 1758) Page 51

52 Scathophaga furcata (Linnaeus, 1758) Page 52

53 Scathophaga inquinata (Fabricius, 1794) Page 53

54 Scathophaga litorea Rondani, 1866 Page 54

55 Scathophaga lutaria (Fallén, 1819) Page 55

56 Scathophaga pictipennis (Meigen, 1826) Page 56

57 Scathophaga scybalaria Page 57

58 Scathophaga stercoraria Robineau-Desvoidy, 1830 Page 58

59 Scathophaga suilla Zetterstedt, 1838 Page 59

60 Scathophaga taeniopa Strobl, 1894 Page 60

61 Spaziphora hydromyzina Becker, 1894 Page 61

62 Trichopalpus fraternus Meade, 1885 Page 62