wildlife surveys chapter 6: light trap surveys for moths ... · moths with a conservation score...

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RSPB/NE Countdown 2010: Bringing Reedbeds to Life Project

Wildlife surveys

CHAPTER 6: Light trap surveys for moths

C J Hardman

With helpful comments on draft by Mark Parsons (Butterfly Conservation)

Contents

Summary ............................................................................................................................................. 1

METHODS ............................................................................................................................................... 2

Light trap survey field methods .......................................................................................................... 2

Analysis methods ................................................................................................................................ 5

RESULTS ................................................................................................................................................ 10

What moth species were found on the three reedbed reserves? ........................................................ 10

Species composition ......................................................................................................................... 13

What habitat variables were reedbed specialist moths associated with? ....................................... 14

What habitat were internal reed-feeding moths associated with? .................................................. 19

What habitat were wetland specialist moths associated with? ....................................................... 24

How did the number of reedbed and wetland specialist Lepidoptera compare between the

wettest and driest areas? ................................................................................................................. 29

How did the number of reedbed and wetland specialist Lepidoptera compare between old and

new areas? ........................................................................................................................................ 30

What reedbed habitat conditions were associated with maximum number of Lepidoptera species

at the survey sites? ........................................................................................................................... 35

What habitat variables were associated with moths with a conservation status? .......................... 46

Composite habitat variables ................................................................................................................. 49

References ............................................................................................................................................ 50

Summary

Twelve light traps were set at each of three key reedbed sites (Hickling Broad in Norfolk, Ham Wall in Somerset and Stodmarsh in Kent). Each trap was set three times, at intervals of three weeks between June and August 2010. Over all surveys at all sites 5 524 individuals and 202 species were trapped.

Of the 202 species trapped, 16 species were classified as reedbed specialists and 47 as wetland specialists, according to expert opinion based on agreed definitions.

Two Endangered (RDB 1) species were trapped (Clostera anachoreta and Pelosia obtusa) three Vulnerable (RDB 2 & pRDB 2) species (Cnephasia genitalana, Monochroa divisella and

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Phragmataecia castaneae), three Rare (RDB 3 & pRDB 3) species (Chortodes brevilinea, Pelosia muscerda and Yponomeuta rorrella) and 12 Nationally Scarce species.

20 UK BAP moth species were trapped: one being a reedbed specialist: Chortodes brevilinea (Fenn’s Wainscot) and 19 being widespread but rapidly declining species.

In total, 135 moth species were caught at Hickling Broad, 78 at Ham Wall and 128 at Stodmarsh. Hickling Broad not only had higher overall species diversity, but also had a higher number of species of conservation interest and reedbed specialists. Stodmarsh had high numbers of wetland specialist moths. Ham Wall was lower than the other two sites for all measures of moth diversity.

Habitat variables measured around the traps were tested to see which best explained variation in number of species caught in traps.

Because of the differences in moth diversity between sites and differences in geography between sites, general conclusions are sometimes constrained by site differences overriding trends in other habitat variables. These habitat associations should be interpreted with caution due to the site differences and the small sample size (12 traps at each site). However they provide a good starting point indicating which potential relationships would be interesting to investigate further. A study with more traps at sites in a similar geographic area (e.g. only the Broads) would be an interesting next step.

Traps that had a high overall diversity of moth species tended to be in places where the litter was not fully submerged in the four months before trapping and where there was a high diversity of plants.

Moths with a conservation score tended to be trapped at points with high plant species richness and litter that was not fully submerged before surveys.

• Higher numbers of wetland specialists were trapped at points with fully submerged litter, more standing water, deeper litter and greater stem densities. Higher numbers of reedbed specialists were trapped at points with deeper litter, standing water, further from scrub, with high stem densities. Higher numbers of internal reed feeders were trapped at points with deeper litter, standing water and thicker reed.

Areas of reedbed at Hickling and Stodmarsh that were restored in 1998 had similar numbers of reedbed and wetland specialist moth species to much older areas of the sites. Small Dotted Footman, Pelosia obtuse, (Endangered), Reed Leopard, Phragmataecia castaneae, (Vulnerable) and Fenn’s Wainscot, Chortodes brevilinea, (UK BAP Priority Species, Rare) were all trapped in the Hundred Acre reedbed (12 years old) at Hickling Broad along with 8 other Rare or Nationally Scarce moth species.

METHODS

Light trap survey field methods

A subset of water trap points were surveyed for moths in 2010 using light traps. 12 points out of the 21 water trap points at each site were randomly selected and the final selection was adjusted to ensure all hydrological categories had been covered. Since hydrological data had already been collected in 2009 at the sampling points, these data were used to ensure a mix of hydrological strata were sampled. Surveys were spread over three sessions, detailed below.

Session 1: 21-25 June (Stodmarsh); 28 June – 2 July (Hickling); 5-9 July (Ham Wall)

Session 2: 12-16 July (Stodmarsh); 19-23 July (Hickling); 26-30 July (Ham Wall)

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Session 3: 2-6 August (Stodmarsh); 9 – 13 August (Hickling); 16-20 August (Ham Wall)

Four traps were set up each night before dusk and checked at 6 am the following morning. The groups of four were changed each week with a mixture of hydrological strata being surveyed each week. Trapping was only done on suitable nights without high wind or heavy rain as these conditions can affect catches.

Heath type 15 W actinic traps were used, supplied by Anglia Lepidopterist Supplies. They were fitted with rain-guards and used 12 Amp hour batteries, attached to the poles to stay dry. One large egg box tray (roughly 30cm square) ripped into six pieces lined the base of the trap. Traps were fitted firmly to platforms on top of wooden poles as in the water trap survey and the height of the pole was recorded in order to account for this in analysis. Traps were turned on by a light sensor and this mechanism was tested during every set up. The reed in 1 m radius around the trap was flattened at each location to standardise immediate habitat influence.

Figure 6.1: Moth trap in situ (Chris Nall)

The following morning, moths were identified in situ by ecological contractors (Hickling Broad: Jon Clifton and Jim Wheeler, Stodmarsh: Sean Clancy, Ham Wall: James McGill). Only moths found inside the trap were recorded. All species were identified and the number of individuals of each species was counted. Each morning a basic habitat survey was carried out. This involved recording live and dead reed height, whether there was standing water in the vicinity and the standing water level in the core. Weather reports were completed after trap set up and before and after trap checking each morning. Donna Harris, Chloe Hardman, Chris Nall and Stephen Gregory carried out surveys with the ecological contractors. Surveys were designed by Donna Harris with advice from Mark Parsons (Butterfly Conservation).

Further habitat surveys

During the first trapping session, litter was measured 0.5m into reeds from the core edge, in each of NE, SE, SW, NW directions. In the same directions, 1 m into reeds, standing water level (surface to boot sole) was measured. Plant species were recorded in four 50 x 50cm quadrats 2m from the core edge. On the second trapping session, at 1m into reeds from core edge, in each of N, E, S, W directions, standing water level (surface to boot sole) was measured. Then, also at 1m into reeds, using a 50 x 50cm quadrat, number of live and dead stems (above chest height) and the number of panicles was measured. Four randomly selected stem base diameters from within the quadrat were measured using callipers. On the third trapping session, at 1.5m from core edge, in each of N, E, S,

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W directions water height (surface to boot sole) was measured. All survey equipment was collected up in this session.

Locations of the survey points

Figure 6.2: Map of moth trap locations at Ham Wall

Figure 6.3: Map of moth trap locations at Hickling Broad

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Figure 6.4: Map of moth trap locations at Stodmarsh

Analysis methods

Invertebrate species data

The three trapping sessions were combined to produce a list of species and individuals caught at each trapping point over all three trap nights. All invertebrate identifications were checked for taxonomic consistency using MapMate. Taxa were included as ‘species’ if they were identified to species level, or if they were the only member of a higher taxa, e.g. the only record of a particular genus. Lists of reedbed and wetland specialists were compiled by Mark Parsons (Butterfly Conservation), Tony Prichard (Suffolk Moths), and the ecological consultants who carried out the surveys. The following definitions of reedbed and wetland specialists were used:

Reedbed specialist: a species that is dependent on reed, reared from reed, or only found in reedbed habitats

Wetland specialist: a species that is generally found in wetlands

All reedbed specialists were also classified as wetland specialists. For lists of the species that met these definitions, see appendix.

ISIS (the Invertebrate Species-habitat Information System) was also used to classify species as wetland or reedbed specialists. ISIS classifies habitats as broad assemblage types (BATs) and specific assemblage types (SATs). BATs are “a comprehensive series of assemblage types that are characterised by more widespread species” whereas SATs are “characterised by ecologically restricted species and are generally only expressed in lists from sites with conservation value”. The freshwater wetland BATs were: W1 - flowing water, W2 - mineral marsh and open water and W3 - permanent wet mire. For this project, wetland specialists within reedbeds were best represented by the BAT categories W2 and W3. Reedbed specialists were represented by the SAT category W314 (reedfen and pools). However, when compared to the lists compiled by moth experts, these lists

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were not considered as comprehensive so were not used. Some moth families had been omitted and the reedbed specialist category also includes fen species which was less appropriate for our purposes.

Raw species richness was calculated as the number of species in each trap. All species in traps were identified except one micro moth at Stodmarsh. The total abundance of all invertebrates in each trap was also calculated. The abundance of individuals in each trap will vary depending on how effective the trap was at catching invertebrates. For example, moth light traps surrounded by tall reed will attract moths from a smaller radius than light traps in an open area that are visible from further away. A more effective trap is likely to catch more individuals and hence more species, regardless of whether the habitat is better quality. Two methods were used to try to account for this in analysis.

Firstly the pole height at each point was measured and included as a variable in models to see how far it explained variation in the number of species caught and whether taller poles caught more moth species. Secondly, abundance of individuals trapped was controlled for to just look at the variation in number of species in traps. A variable called “bootstrapped number of species” was calculated. This is similar to rarefaction, which is a necessary ecological technique when comparing species richness of samples of different sizes. R code was written to take a random sample of 42 individuals from each trap and calculate how many species were in that sample (this was the maximum sample size that could be taken based on the number of individuals in the traps). The sampling was repeated 100 times (with replacement) and the average number of species was calculated. Bootstrapped number of species was used rather than a species diversity index, because it was considered more transparent and suitable for the purposes of this study.

A conservation score for each trap was calculated based on the following criteria:

Score of 10 for: Vulnerable, Endangered, Rare

Score of 5 for: Nationally Scarce, UK BAP

These scores were assigned to numbers of species in the traps and not multiplied up by numbers of individuals in the traps.

For each trap, the following response variables were available: raw number of species, bootstrapped number of species, abundance of individuals, number of wetland specialists, number of reedbed specialists, number of internal reed feeding species and conservation scores. All of these were analysed except abundance of individuals which was considered less informative.

Habitat data

From the habitat variables recorded in the field, the following set of explanatory variables was derived. Averages were calculated for habitat variables that were measured at more than one point around the sampling location.

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Table 6.1: Explanatory variables used in models relating habitat variables to moth species diversity

Variable Type of variable Units Description

Litter saturation 2009

(wet.dry.09)


(wet.dry.10)

Explanatory categorical 2 categories; dry and wet

Data from May-August 2009 for litter saturation 2009 and April – June 2010 for litter saturation 2010. Dry if predicted water level never exceeds litter depth. Wet if predicted water level exceeds litter depth at any point in these periods.

Litter depth 2009

Litter depth 2010

Explanatory continuous cm Average of 4 litter depth measurements in 1 m radius of trap point.

Total stem density

(stems)

Explanatory continuous Stems per m2

Average of 4 counts of number of stems in 50 x 50 cm quadrat, in 1 m radius of trap point, multiplied by four to get stems per m2.

Dead stems percentage Explanatory continuous % Percentage of stems that were dead.

Pole height Explanatory continuous m Height of pole on which Heath trap was mounted.

Mean reed height Explanatory continuous m Height of live reed, average of 4 measures in 1m radius of trap point.

Stem diameter Explanatory continuous mm Stem diameter at base, average of 4 measures in 1m radius of trap point.

Distance to scrub Explanatory continuous m Distance to nearest patch of scrub/trees calculated from aerial photos by CDMU using an add on tool in MapInfo 6.5.

Plant species richness Explanatory continuous Total number of plants (excluding Phragmites australis) found over 4 quadrats in 1 m radius of trap point.

Standing water level

summer 2010

Explanatory continuous cm Average standing water level from four points in the untrampled reed 1m from the pole.

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Water level data

Data on the temporal variation in water levels was available for each point. This was based on topography measurements and seasonal readings of gauge boards. Gauge boards were read periodically throughout the project by survey staff, site staff and volunteers. At Hickling Broad, data on the broad-side sampling points was available from the Environment Agency tidal site (NGR: TG4107822508) which records daily mean water levels. In October 2009, a Topcon device (GRS 1 TOPCON – uses OSTN(O2) co-ordinate system) was hired to make precise altitude readings. It was used to get the elevation AOD at the water trap, pitfall trap and gauge board locations. The levels of a number of gauge boards at Stodmarsh were corrected based on this data (gauge boards 1, 4, 6c, 6a).

Water levels were recorded periodically, by hydrological unit, at each site and converted to AOD water levels in order to predict water levels for each of our survey points throughout the year, for any dates on which gauge boards were read by either site staff or us. Predicted water level was calculated as:

Predicted water level = Gauge board water level at AOD – altitude at survey point AOD

The accuracy of these predictions was checked through a comparison with actual water levels. During the various wildlife surveys, water levels were measured using a ruler at the actual survey points from the same “ground” baseline (i.e. the base of the surveyors wader when surveyor in normal standing position) as the altitude AOD was taken using the Topcon. Such data are available from a few occasions – October (water trap and pitfall points, when ground elevations were measured, November (bittern locations, when ground elevations were measured) and January (water levels only during water vole surveys).

Only water measurements from the untrampled reed were used in water level prediction calculations. Error of prediction was calculated as the difference between predicted and actual water level. Where error was larger than could be realistically explained by variation in microtopography, factors such as hydrological blockages may be present, so the predicted values were not used. Average error across all sites was 0.0639 m (for error calculations see water trap survey chapter 4, appendix table 4C).

Data was only ever used for the time period before sampling took place. Since moth surveys were carried out in 2010 (the second year of surveying for this project), data from both 2009 and 2010 was available. The data from 2009 was from May-August, since this was the time period over which gauge boards had been read most regularly to allow water levels to be predicted. In 2010, the most similar period we had data for was April-July. For each of these periods, the litter level was compared to the predicted water level to put the point into a category: wet or dry. Points where the predicted water level exceeded the litter level at any point in the period specified were classed as wet. It is important to note that these litter saturation categories only reflect one season of the year and water levels are likely to vary throughout the rest of the year, which was not able to be captured here due to lack of available data. Also the litter saturation categories varied between 2009 and 2010, showing that data from one year is only a snapshot.

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Multivariate analysis

Before analysis began, scatter plots of response variables against explanatory variables and explanatory against explanatory were created. Data exploration was carried out in the way recommend by Zuur et al (2010), checking for outliers and normality.

The R function DREDGE from the MuMIn package was used to examine all possible models and examine the model with the lowest AICc. We used glm with poisson errors here as glm.nb did not seem compatible with this function. We stated that the data contained NAs. Then we took the best model and ran it as a prediction. By testing the linear regression between actual and predicted values we can check how good the fit of the model is. The best model explained only 53 % of the variance. An algorithmic modelling technique, called Random forest, was tried in comparison. This technique produced a model that explained 93% of the variance, so seems to be a powerful way of analysing our dataset. Random forest is a machine learning algorithm that builds an ensemble of regression trees (a forest) (Breiman et al 1984). Random forest models are suited to this type of exploratory analysis where we do not have specific hypotheses but want to explore the relative importance of all variables and their potential interactions (Hochachka 2007). This technique can deal with a large number of predictor variables. It automatically includes all interactions and it doesn’t matter if the variables are not normally distributed. The technique copes well with missing values, outliers and irrelevant predictor variables.

500 regression trees were constructed, using a random subset of four variables at each split, with replacement sampling. Random forest (Breiman 2001) uses a subset of 63% the data to build the model then the remaining 37% to test the model (out of bag data). At each node, it tries four variables and chooses the one which best splits the data into two. Then for these two groups it repeats the process and so on until the data points are predicted by this series of rules. An example of such a tree is given in figure 6.5.

Figure 6.5: example of one regression tree within a “random forest”

|diameter < 0.35875

litsat2009:ab

livestems < 43.75

plantrich < 4.5

maxreedheight < 1.495

118.8

238.6 183.8

115.4 71.8

155.1

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To find out the importance of each variable, the function permutes the values (rearranges the data for example by replacing the 3rd row with the 5th). Then it checks if the mean squared error increases or not. If it does increase this shows that the variable is important. A few variables actually reduce the mean squared error when permuted so this shows they are not important at all (negative values). Each random forest model was run 10 times, and the % Increase in Mean Squared Error was calculated for each habitat variable. This process was carried out for each of the response variables for each of the three datasets. For habitat variables which were of high importance, the direction of the relationship was investigated further using partial plot and plots of the raw data. For the moth dataset the separate site results cannot stand alone as they are based on a sample size of twelve.

A number of habitat variables were associated with each other, due to the nature of reedbed successional habitat. This does not affect the predictive performance of random forest models but can affect the variable importance. If variables are correlated the model can use either variable at splits in the regression tree, so the variable importance of both can be reduced. To test if this was the case for the correlated habitat variables models were run separately with each variable alone, and then together, to check whether the variable importance scores of the correlated variables were always higher alone than together. For variables where this was the case, either an average was taken (e.g. for live height and dead height) or one variable was excluded.

In addition, a principle component analysis was carried out for each of the three invertebrate datasets. This creates composite habitat variables that best explains variation in habitat between the invertebrate survey points. The correlation between each of the top four principle components and bootstrapped species richness was tested to see which composite environmental gradients best explained variation in species diversity. These results were compared to the results of random forest analyses and consistent messages were drawn out.

RESULTS

What moth species were found on the three reedbed reserves?

Over all surveys at all sites 5 524 individuals and 202 species were trapped. In total, 135 moth species were caught at Hickling Broad, 78 at Ham Wall and 128 at Stodmarsh.

Lepidoptera of conservation importance

There were two Endangered (RDB 1), three Vulnerable (RDB 2 & pRDB 2), three Rare (RDB 3 & pRDB 3) and 13 Nationally Scarce moth species, as listed below.

Table 6.2: Lepidoptera species of conservation concern found in surveys

Number of records

Family Species latin name

Species common name

Higher taxon

Conservation status

HB HW SM Total

Arctiidae Pelosia obtusa

Small dotted footman Lepidoptera Endangered 17 0 0 17

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Arctiidae Spilosoma urticae

Water Ermine Lepidoptera

Nationally Scarce 9 0 1 10

Arctiidae Pelosia muscerda

Dotted Footman Lepidoptera Rare 4 0 0 4

Cossidae Phragmataecia castaneae

Reed Leopard Moth Lepidoptera Vulnerable 58 0 0 58

Gelechiidae Monochroa divisella

A micro moth Lepidoptera Vulnerable 7 0 0 7

Gelechiidae Brachmia inornatella

A micro moth Lepidoptera


Gelechiidae Monochroa palustrella



Noctuidae Mythimna flammea

Flame Wainscot Lepidoptera


Noctuidae Archanara sparganii

Webb's Wainscot Lepidoptera


Noctuidae Macrochilo cribrumalis

Dotted Fan-foot Lepidoptera


Noctuidae Simyra albovenosa

Reed Dagger Lepidoptera


Noctuidae

Chortodes brevilinea

Fenn’s Wainscot

Lepidoptera

UK BAP Priority Species, Rare 5 0 0 5

Notodontidae Clostera anachoreta

Scarce Chocolate Tip moth Lepidoptera Endangered 0 0 1 1

Pyralidae Nascia cilialis A micro moth Lepidoptera


Pyralidae Calamotropha paludella



Pyralidae Schoenobius gigantella



Tortricidae Cnephasia genitalana

A micro moth Lepidoptera Vulnerable 1 0 0 1

Tortricidae Phalonidia manniana



Since Yponomeuta rorrella and Itame brunneata are immigrant species, they were not included in the conservation score analysis. However they do have conservation statuses which are listed below.

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Table 6.3: Numbers of immigrant species with conservation statuses trapped.

Number of records

Family Species latin name

Species common name

Higher taxon

Conservation status

HB HW SM Total

Geometridae Itame brunneata

Rannoch Looper Lepidoptera

Nationally Scarce, Immigrant, resident only in Scotland 0 0 1 1

Yponomeutidae Yponomeuta rorrella

Willow Ermine Lepidoptera

Rare (possibly an immigrant) 0 0 1 1

UK BAP species

All the UK BAP species recorded are designated as Species “of principal importance for the purpose of conserving biodiversity” covered under section 41 (England) and 42 (Wales) of the NERC Act (2006), except Fenn’s Wainscot which is only on the English list. Of the 20 UK BAP moth species encountered, one is a reedbed specialist, Fenn’s Wainscot (Chortodes brevilinea), which was given its status due to substantial threat to its highly specialised habitat. Fenn’s Wainscot is also a Red Data Book species, designated as Rare (RDB 3). The other 19 species are widespread but rapidly declining (see table 6.4). These species have declined markedly over the last 35 years (with declines ranging between 71% to 95%, see appendix). None of these species are reedbed specialists and only two were wetland specialists (Celaena leucostigma and Orthonama vittata).

Table 6.4: Number of UK BAP widespread but rapidly declining species trapped at each site

Family Species latin name Species common name

Higher taxon HB HW SM Total

Noctuidae Acronicta rumicis Knot Grass Lepidoptera 1 0 0 1

Noctuidae Amphipoea oculea Ear Moth Lepidoptera 1 0 0 1

Noctuidae Amphipyra tragopoginis

Mouse Moth Lepidoptera 4 0 0 4

Noctuidae Apamea remissa Dusky

Brocade Lepidoptera 9 0 0 9

Arctiidae Arctia caja Garden

Tiger Lepidoptera 148 66 14 228

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Noctuidae

Brachylomia viminalis

Minor Shoulder-Knot Lepidoptera 1 0 0 1

Noctuidae Caradrina morpheus Mottled

Rustic Lepidoptera 0 0 2 2

Noctuidae Celaena leucostigma Crescent

Lepidoptera 62 26 23 111

Noctuidae Hoplodrina blanda Rustic Lepidoptera 0 0 6 6

Noctuidae Hydraecia micacea Rosy

Rustic Lepidoptera 0 2 3 5

Lasiocampidae Malacosoma neustria

Lackey Lepidoptera 0 2 0 2

Noctuidae Melanchra pisi Broom

Moth Lepidoptera 2 0 0 2

Noctuidae

Mythimna comma Shoulder-striped Wainscot Lepidoptera 2 0 1 3

Geometridae Orthonama vittata Oblique

Carpet Lepidoptera 31 16 0 47

Geometridae Pelurga comitata Dark

Spinach Lepidoptera 0 1 0 1

Arctiidae Spilosoma lubricipeda

White Ermine Lepidoptera 0 0 1 1

Arctiidae Spilosoma luteum Buff

Ermine Lepidoptera 6 8 8 22

Geometridae Timandra comae Blood-vein Lepidoptera 0 3 0 3

Drepanidae Watsonalla binaria Oak Hook-

Tip Lepidoptera 4 0 3 7

Species composition

There were more macro moths than micro moths at all sites. Hickling Broad had the highest number of macro moth individuals, whereas Stodmarsh had the highest number of micro moth species. In terms of numbers of individuals, Ham Wall was not far behind Stodmarsh, however in terms of numbers of species, Ham Wall was lower than the other two sites. To investigate how far the differences in numbers of species between sites are due to geography, the NBN species database (www.nbn.org.uk) was used to look up the species ranges. There were 50 more species caught at Stodmarsh compared to Ham Wall and 57 more species caught at Hickling Broad compared to Ham Wall. 20 of the 187 species found at Hickling Broad and Stodmarsh combined, would not be expected to occur in the SW. Therefore the lower species diversity at Ham Wall can be partly attributed to geographical location but not entirely.

http://www.nbn.org.uk/

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Table 6.5: Number of individuals of macro and micro moths at each site

Totals over 12 traps set 3 times (36 trap nights)

Ham Wall Hickling Broad Stodmarsh

Macro Number of individuals 956 1894 948

Number of species 59 91 79

Micro Number of individuals 514 328 625


Total Number of individuals 1470 2222 1573


What habitat variables were reedbed specialist moths associated with?

Random Forest models were used to find out which habitat variables measured around the moth trap points best explained the number of reedbed specialist moth species trapped at each point (not abundances as considered too unreliable). This was based on lists of reedbed specialists defined by moth experts using agreed definitions. Many of the trends were affected by Ham Wall having lower species diversity and different habitat variables to the other sites. Therefore Hickling Broad and Stodmarsh were also analysed alone for comparison.

Figure 6.6: Relative importance of habitat variables in describing variation in number of reedbed specialist species per trap. These models explained 92 % of the variance.

Site

Ham Wall had fewer reedbed specialist moths on average per trap than the other two sites (Hickling Broad and Stodmarsh had 12 reedbed specialist moth species trapped in total across all traps whereas Ham Wall had 7). Six of the sixteen reedbed specialist moths identified across all three sites would not be expected to occur at Ham Wall due to geographical ranges not extending to this region Chortodes brevilinea, Mythimna flammea, Pelosia obtuse, Phragmataecia castaneae, Schoenobius

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gigantella, Simyra albovenosa (www.nbn.org.uk). Therefore considering the age of the site and its geographic location, the number of reedbed specialist moths at Ham Wall is encouraging.

Figure 6.7: Relationship between site and number of reedbed specialists in moth traps

Mean reed height

Since site was such an important factor, ideally we would have analysed each site separately, however there was not enough data to do this (n=12 traps at each site, less than 5 unique values for number of reedbed specialists at Hickling Broad). Instead, the scatter plots have been coloured to indicate which site the points are from. The negative relationship between reed height and number of reedbed specialist moth species appears to be a product of Ham Wall having taller reed and a lower number of reedbed specialist moth species from the scatter plot.

1.5 2.0 2.5

7.0

7.1

7.2

7.3

7.4

7.5

7.6

Partial Plot

Mean reed height

1.5 2.0 2.5

45

67

89

10

11

Raw Data

Mean reed height

Ere

ed

be

d N

o. S

pe

cie

s

0 10 20 30 40

45

67

89

10

11

standing.water.summer.2010

Ere

ed

be

d

HW

HB

SM

Figure 6.8: Relationship between mean reed height around each trap and the number of reedbed specialist moths caught in the trap

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Scrub distance

This relationship was not clear since each site showed a different trend. When Hickling Broad and Stodmarsh were analysed without Ham Wall, points further from scrub were associated with more reedbed specialist moths.

0 50 100 150 200 250 300

7.2

7.3

7.4

7.5

Partial Plot

Distance to Scrub

0 50 100 150 200 250 300

45

67

89

10

11

Raw Data

Distance to Scrub

Ere

ed

be

d N

o. S

pe

cie

s

Litter depth 2009

Trap points with deeper litter (measured the year before) were associated with a greater number of reedbed specialist moths. Litter depth measured in 2010 was less important, but also showed a positive relationship with the number of reedbed specialist moths. Four of the 16 reedbed specialist moths overwinter as either pupae or larvae in reed litter (Pelosia obtuse, Mythimna obsolete, Mythimna straminea and Simyra albovenosa). At least 2 of these litter-dwelling species were found in all traps. If we assume these litter-dwellers pupated near where they were trapped, deeper litter in 2009 could have promoted a higher larval/pupal survival rate because it is less likely to get inundated with water. This was true when Ham Wall was excluded from analysis.

0 10 20 30 40

45

67

89

10

11

standing.water.summer.2010E

ree

db

ed

HW

HB

SM

Figure 6.9: Relationship between scrub distance and number of reedbed specialist species

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0 10 20 30 40

7.2

07

.25

7.3

07

.35

7.4

0

Partial Plot

Litter Depth 2010

0 10 20 30 40

45

67

89

10

11

Raw Data

Litter Depth 2010R

ee

db

ed

sp

ecia

lists

Figure 6.10: Relationship between litter depth 2009 and number of reedbed specialist moths

Stems

The random forest model indicates that points with over 280 stems per square metre were associated with more reedbed specialist moths. However this appears to be confounded by Ham Wall having low stem densities and a low number of reedbed specialist moths. When Ham Wall points were removed from analysis this variable was no longer important.

100 200 300 400 500

7.1

07

.20

7.3

07

.40

Partial Plot

Stems per square metre

100 200 300 400 500

45

67

89

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Re

ed

be

d s

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Figure 6.11: Relationship between stem density and number of reedbed specialist moths

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Points where the litter had not totally flooded in May-August 2009 were associated with higher numbers of reedbed specialist moths. However litter saturation 2010 was not so important. Perhaps some of these reedbed specialists did pupate in the litter in 2009, hence not being flooded offered a survival advantage.

Figure 6.12: Relationship between litter saturation 2009 and reedbed specialist moths

Standing water level

Points with lower levels of standing water (0-10 cm) were associated with the highest numbers of reedbed specialist moths trapped. We would expect reedbed specialists to be able to survive in shallow standing water, because generally they are internal feeders often pupating in situ.

19

0 10 20 30 40

7.2

07

.25

7.3

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.35

7.4

0Partial Plot

Standing Water

0 10 20 30 40

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67

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Raw Data

Standing Water

Ere

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Figure 6.13: Relationship between standing water during surveys and number of reedbed specialist moths

What habitat were internal reed-feeding moths associated with?

A subset of reedbed specialist moths, those that feed internally on Phragmites australis (see appendix), were analysed separately. The number of these internal reed-feeding moths was calculated for each trap and the analysis below shows how these numbers related to habitat variables. In the other models, stem diameter was not included together with mean reed height because the two variables are correlated. Just mean reed height was used and inferences about diameters were made in interpretations. However for internal feeders, diameter was used in the models instead of mean reed height because it is more directly related to the feeding and life history of these moths.

Points that trapped high numbers of internal reed feeding moths tended to:

Be at Hickling Broad or Stodmarsh, not at Ham Wall

Have thicker stem diameters if at Hickling Broad or Stodmarsh

Have deeper litter

Have litter that was not fully saturated between May and August 2009

When Hickling Broad and Ham Wall were analysed alone, internal reed feeders were trapped more at points with more standing water, taller reed and shallower litter and thicker stem diameters and deeper litter 2009

0 10 20 30 40

45

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Figure 6.14: Importance of habitat variables in explaining variation in number of internal reed-feeding moths in traps. These models explained 90 % of the variance.

Site

The most important factor in explaining variation in number of internal reed-feeding moths in traps was site. Hickling Broad had the highest number of internal reed-feeding moths of the three sites. This is not surprising as some of these internal feeding species have distributions restricted to the Norfolk Broads. Three of the ten internal reed feeding species identified across all surveys would not be expected to occur at Ham Wall (Chortodes brevilinea, Phragmataecia castaneae, Schoenobius gigantella).

21

Diameter

Ham Wall has much thicker reed stem diameters (and taller reed) than the other two sites and also the lowest number of internal reed feeding moths. This explains why the thickest diameters were associated with lower numbers of internal feeders. At Hickling Broad and Stodmarsh alone, scatter plots showed points with thicker stems (and hence taller reed) were associated with greater numbers of internal reed feeding specialists.

2 3 4 5 6 7

3.8

4.0

4.2

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Diameter

2 3 4 5 6 7

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34

56

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Diameter

Inte

rna

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lists

Figure 6.16: Relationship between reed stem diameters and number of internal reed feeding moths

Figure 6.15: Relationship between number of internal reed-feeding moths and site

0 10 20 30 40

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Scrub distance

The relationship between internal feeders and scrub was unclear. Although this variable can reflect successional stage, it is not directly relevant to these moths in question that feed on reed.

0 50 100 150 200 250 300

4.0

54

.15

4.2

54

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Partial Plot

Distance to Scrub

0 50 100 150 200 250 300

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Raw Data

Distance to Scrub

Inte

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Figure 6.17: Relationship between distance to scrub and number of internal reed feeding moths

Litter depth 2009

Litter depth was also important in explaining variation in the number of internal reed-feeding moths. Over all sites, a tendency for points with deeper litter to be associated with a greater number of internal reed-feeding moths was seen. Looking at a scatter plot with each site coloured differently, this trend only appears evident at Stodmarsh on an individual site level. In our dataset it is unclear what type of reedbed deep litter is associated with. Both wet and dry points had deep litter recorded. Further investigation of litter depths along hydrological gradients would be interesting.

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10 20 30 40 50

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Litter depth 2009

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Litter depth 2009

Inte

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mo

ths.

Figure 6.18: Relationship between internal reed feeding moths and litter depth 2009


Litter saturation in 2009 and 2010 was of low importance in explaining variation in internal reed-feeding moths. Points where the litter did not entirely flood between May and August 2009 were associated with higher numbers of internal reed feeding moths. Dry here means points where the litter was either totally dry or partly wet but the water level did not exceed the litter level.

Figure 6.19: Relationship between litter saturation 2009 and number of internal reed specialist moth species

0 10 20 30 40

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Standing water

This variable was of low importance, however points with standing water did trap internal feeders. We would expect internal feeders to be able to survive shallow inundation more than litter feeders.

0 10 20 30 40

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Partial Plot

Standing Water 2010

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Standing Water 2010

Inte

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Figure 6.20: Relationship between standing water 2010 and number of internal feeding moth species.

What habitat were wetland specialist moths associated with?

In summary:

Points at Stodmarsh and Hickling had greater numbers of wetland specialists than Ham Wall

Points with deeper litter were associated with more wetland specialist moth species (when measured both in 2009 and 2010) (true for Hickling and Stodmarsh alone)

Points with more standing water were associated with more wetland specialist moth species (true for Hickling and Stodmarsh alone)

Both wet and dry points in 2009 had high numbers of wetland specialists but wetter points in 2010 had higher numbers (true for Hickling and Stodmarsh alone)

Points with greater stem densities were associated with more wetland specialist moth species

Points with shorter pole heights were associated with more wetland specialist moth species

0 10 20 30 40

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Ere

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Figure 6.21: Importance of habitat variables in explaining variation in number of wetland specialist moth species in traps. These models explained 93 % of the variance.

Litter depth 2009

Points with deeper litter in 2009 were associated with greater numbers of wetland specialist moth species. (This was also true for litter measured in 2010, but not to the same extent). In our dataset wet points tended to have deep litter measured, whereas dry points had both deep and shallow litter. Therefore the points here with deep litter may have also been wet points. This fits in with the relationship between standing water level and number of wetland specialist moth species.

10 20 30 40 50

14

.01

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Partial Plot

Litter Depth 2009

10 20 30 40 50

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Litter Depth 2009

We

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Figure 6.22: Relationship between litter depth 2009 and wetland specialist moths trapped in 2010 0 10 20 30 40

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Site

In contrast to number of reedbed specialist moth species and internal feeding species, site was not the most important factor in explaining variation in number of wetland specialist moths. Stodmarsh had the greatest number of wetland specialist moth species, followed by Hickling Broad and then Ham Wall. Ham Wall is the wettest site, but has a lower overall moth diversity than the other two sites. At these survey points in 2010, Stodmarsh had on average more standing water than Hickling Broad which fits in with Stodmarsh points trapping more wetland specialist species than Hickling points.

Figure 6.23: Relationship between number of wetland specialist species and site


When points were classed as having totally saturated (wet) litter or partly saturated or dry (dry) litter in the year before surveys, dry points were associated with a greater number of wetland specialist species. It is not clear why dry points were associated with more wetland specialists in 2009 but wet points were associated with more wetland specialist moth species in 2010. The great range of moth life cycles included in analysis makes it difficult to explain.

27

Figure 6.24: Relationship between litter saturation 2009 and number of wetland specialist moths

Stems

Points with stem densities over 300 stems per square metre tended to be associated with greater numbers of wetland specialist moth species.

100 200 300 400 500

14

.21

4.4

14

.61

4.8

15

.0

Partial Plot


100 200 300 400 500

10

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We

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Figure 6.25: Relationship between stem density and number of wetland specialist moth species

Pole height

Points with shorter poles were associated with greater numbers of wetland specialist moth species. At least this shows tall pole height did not have an overwhelming influence on the effectiveness of

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the trap. Perhaps shorter traps tended to trap species within the reeds rather than species from the wider habitat around.

1.0 1.2 1.4 1.6 1.8

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Pole Height

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01

52

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Raw Data

Pole Height

We

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Figure 6.26: Relationship between pole height and number of wetland specialist moth species

Standing Water

Points with higher levels of standing water during surveys tended to trap greater numbers of wetland specialists. This fits with expectations since in wetter areas, wetland specialists would be expected to outcompete species without adaptations to living near water.

0 10 20 30 40

14

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14

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Standing Water

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Standing Water

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Figure 6.27: Relationship between standing water and number of wetland specialist moths

29


There were more wetland specialist moths trapped at points where the litter had been fully saturated between April and July 2010 (the months preceding surveys). This ties in with the standing water finding above.

Figure 6.28: Relationship between number of wetland specialist moths and litter saturation category 2010

How did the number of reedbed and wetland specialist Lepidoptera compare between the wettest and driest areas?

Since there is much debate over the relationship between wetness of reedbed and moth diversity, further analyses were attempted to investigate this. However the analysis options were found to be limited by the data and no further analysis better than the random forest models was satisfactory.

Firstly an attempt to separate out the points on litter saturation categories was made. However, points where the water level fully flooded the litter were much more prevalent than points where the litter was dry or partially saturated (Wet=24 points, Partial=5 points, Dry=6 points). Another way to summarise the hydrological data was to classify the points according to whether they had a dry/wet summer and/or dry/wet winter (using data from Sept 09 to Aug 10). However, these categories were confounded by site, since not all categories were found at all sites. The only site with all categories was Stodmarsh and there were not enough data points in each category for analysis.

Since different months of data were missing from different sites the analysis options are limited. The original hydrological categorisations assigned to sampling points at the design stage could not be used as they were not found to reflect actual hydrology and they were not consistent in definition between sites. In order to investigate the diversity of reedbed/wetland specialist moths along hydrological gradients in reedbeds, further trapping is needed, along defined hydrological gradients, on one (or more) sites, preferably over multiple years. Future studies on the importance of dry reedbed for certain species such as Fenn’s Wainscot and Small Dotted Footman are worth further investigation.

30

How did the number of reedbed and wetland specialist Lepidoptera compare between old and new areas?

Stodmarsh has a newer area of reedbed (Grove Ferry) that was restored from grazing marsh with a few reed lined ditches to full reedbed in 1998. Hickling Broad has an area of reedbed (Hundred Acre) which was restored between 1997 and 1999. These areas were restored with funding from the EU LIFE project with a view to providing more habitat for bitterns. The moth catches in the restored areas were compared with the rest of each site which is known to be much older. T-tests were used to compare differences in number of reedbed specialists and wetland specialist moth species between old and new areas within Stodmarsh and Hickling Broad.

Comparing Grove Ferry reedbeds with those at the rest of Stodmarsh, there were no significant differences in the number of reedbed specialist moths or wetland specialist moths in terms of numbers of species and numbers of individuals (see table). There were no significant differences in the number of reedbed and wetland specialist species between Hundred Acre and Hickling Broad. However for reedbed specialist individuals, there were more at Hundred Acre than at Hickling Broad (see table). The ability to detect effects was limited by the small sample size at each site (12 traps per site). However the initial results are encouraging in showing that moths have colonised the reedbed after substantial restoration work took place. Comparisons of species lists and numbers of individuals of species of conservation concern are used to investigate further.

Table 6.6: Differences in reedbed and wetland specialist moths at Grove Ferry and rest of Stodmarsh tested with 2 sample T – tests with unequal variances. (5 traps in new reedbed at Grove Ferry, 7 in older reedbed at Stodmarsh)

Mean number per trap at Grove Ferry

Mean number per trap at Stodmarsh

Degrees of freedom

T value P value

Reedbed specialist species

7.4 7.7 8 -0.34 0.744

Wetland specialist species

17.2 16.1 9 0.37 0.719

Reedbed specialist individuals

39.8 54.3 9 -1.06 0.315

Wetland specialist individuals

84.8 84.9 9 <0.001 0.998

Table 6.7: Differences in reedbed and wetland specialists between Hundred Acre and rest of Hickling Broad tested with 2 sample T – tests with unequal variances. Hickling Broad: 5 traps in old reedbed around the Broad, 7 in new Hundred Acre reedbed.

31

Mean number per trap at Hundred Acre

Mean number per trap at Hickling Broad

Degrees of freedom

T value P value

Reedbed specialist species

9.14 8.4 9 -1.03 0.329

Wetland specialist species

16.4 16.0 5 -0.24 0.823

Reedbed specialist individuals

58 42.2 9 -2.73 0.023 *

Wetland specialist individuals

86.6 68.6 7 -1.82 0.112

Comparison of specialist moth species lists at Stodmarsh in old and new reedbeds

When all traps in the area were considered together, Stodmarsh traps only had two more reedbed specialist species and four more wetland specialist species than Grove Ferry. It was surprising that Archanara dissolute and Archanara geminipuncta were absent from Grove Ferry. They are both internal feeders, but differences in reed diameters did not explain these results. Further trapping would reveal if these species had colonised Grove Ferry.

Table 6.8: Reedbed specialist moths found at new reedbed (Grove Ferry) and older reedbed (Stodmarsh). Species found at both are highlighted with an asterisk, species with conservation status are in bold.

Stodmarsh Grove Ferry

Family Species Family Species

Noctuidae Archanara dissoluta 6 Gelechiidae Brachmia inornatella

2

Noctuidae Archanara geminipuncta 3 Noctuidae Arenostola phragmitidis *

11

Noctuidae Arenostola phragmitidis * 23 Noctuidae Chilodes maritimus *

32

Noctuidae Chilodes maritimus * 50 Noctuidae Mythimna obsoleta *

19

Noctuidae Mythimna obsoleta * 44 Noctuidae Mythimna straminea *

39

Noctuidae Mythimna straminea * 184 Noctuidae Simyra albovenosa *

3

Noctuidae Simyra albovenosa * 21 Pyralidae Chilo phragmitella *

23

Pyralidae Chilo phragmitella * 27 Pyralidae Donacaula forficella *

30

Pyralidae Donacaula forficella * 2 Pyralidae Schoenobius gigantella *

40

Pyralidae Donacaula mucronellus 1

Pyralidae Schoenobius gigantella * 19

32

Table 6.9: Wetland specialist moths found at new reedbed (Grove Ferry) and older reedbed (Stodmarsh). Species found at both are highlighted with an asterisk, species with a conservation status are in bold.

Stodmarsh Grove Ferry

Family Species No. of inds

Family Species No. of inds

Arctiidae Spilosoma urticae 1 Arctiidae Thumatha senex * 39

Arctiidae Thumatha senex * 11 Cosmopterigidae Limnaecia phragmitella * 2

Cosmopterigidae Limnaecia phragmitella * 5 Gelechiidae Brachmia inornatella 2

Geometridae Pterapherapteryx sexalata 4 Glyphipterigidae Orthotelia sparganella 5

Noctuidae Apamea ophiogramma * 3 Noctuidae Apamea ophiogramma * 1

Noctuidae Apamea unanimis 1 Noctuidae Arenostola phragmitidis * 11

Noctuidae Archanara dissoluta 6 Noctuidae Celaena leucostigma * 13

Noctuidae Archanara geminipuncta 3 Noctuidae Chilodes maritimus * 32

Noctuidae Arenostola phragmitidis * 23 Noctuidae Macrochilo cribrumalis * 28

Noctuidae Celaena leucostigma * 10 Noctuidae Mythimna obsoleta * 19

Noctuidae Chilodes maritimus * 50 Noctuidae Mythimna straminea * 39

Noctuidae Macrochilo cribrumalis * 10 Noctuidae Nonagria typhae * 1

Noctuidae Mythimna obsoleta * 44 Noctuidae Parastichtis ypsillon * 1

Noctuidae Mythimna straminea * 184 Noctuidae Schrankia costaestrigalis * 1

Noctuidae Nonagria typhae 2 Noctuidae Simyra albovenosa * 3

Noctuidae Parastichtis ypsillon * 1 Pyralidae Acentria ephemerella * 22

Noctuidae Schrankia costaestrigalis * 2 Pyralidae Calamotropha paludella * 11

Noctuidae Simyra albovenosa * 21 Pyralidae Cataclysta lemnata * 39

Pyralidae Acentria ephemerella * 79 Pyralidae Chilo phragmitella * 23

Pyralidae Calamotropha paludella * 3 Pyralidae Donacaula forficella * 30

Pyralidae Cataclysta lemnata * 43 Pyralidae Elophila nymphaeata * 13

Pyralidae Chilo phragmitella * 27 Pyralidae Parapoynx stratiotata * 29

Pyralidae Donacaula forficella * 2 Pyralidae Phlyctaenia perlucidalis * 4

Pyralidae Donacaula mucronellus 1 Pyralidae Schoenobius gigantella * 40

Pyralidae Elophila nymphaeata * 19 Tortricidae Bactra furfurana * 6

Pyralidae Nascia cilialis 2 Tortricidae Phalonidia manniana 1

Pyralidae Parapoynx stratiotata * 10

Pyralidae Phlyctaenia perlucidalis * 2


Tortricidae Bactra furfurana * 3

33

Overall, the species diversity of specialist moths in newer reedbeds was not as far behind that of older reedbeds at Stodmarsh as we would have expected, in terms of reedbed and wetland specialists and moths with a conservation status.

Comparison of specialist moth species lists at Hickling Broad in old and new reedbeds

Table 6.10: Reedbed specialists in old and new reedbed at Hickling Broad. Species found in both areas are highlighted with an asterisk. Species with a conservation status are highlighted in bold.

Broad Hundred Acre

Family Species

No. of inds Family Species

No. of inds

Arctiidae Pelosia obtusa * 11 Arctiidae Pelosia obtusa * 6

Cossidae Phragmataecia castaneae * 42 Cossidae Phragmataecia castaneae * 16

Noctuidae Archanara dissoluta * 2 Noctuidae Archanara dissoluta * 21

Noctuidae Arenostola phragmitidis * 30 Noctuidae Arenostola phragmitidis * 42

Noctuidae Chilodes maritimus * 5 Noctuidae Chilodes maritimus * 25

Noctuidae Chortodes brevilinea * 3 Noctuidae Chortodes brevilinea * 2

Noctuidae Mythimna flammea * 6 Noctuidae Mythimna flammea * 9

Noctuidae Mythimna straminea * 53 Noctuidae Mythimna straminea * 98

Noctuidae Simyra albovenosa * 10 Noctuidae Simyra albovenosa * 48

Pyralidae Chilo phragmitella * 23 Pyralidae Chilo phragmitella * 54

Pyralidae Schoenobius gigantella * 14 Pyralidae Donacaula forficella 1

Pyralidae Schoenobius gigantella 51

The only difference in reedbed specialists trapped in the two areas at Hickling was that Hundred Acre had one more species (Donacaula forficella) which was not captured in these surveys around the Broad.

Six Small Dotted Footman individuals were trapped in Hundred Acre reedbed and eleven in the reed around the Broad (Traps: HB1, HB12, HB13, HB16, HB17, HB19, HB5, HB7, HB8). 16 Reed Leopard were trapped in Hundred Acre reedbed and 42 in the reed surrounding the Broad (Traps: HB1, HB11, HB12, HB13, HB16, HB17, HB19, HB5, HB7, HB8, HB9). Note: actinic traps were used to try to reduce the area over which moths could have flown in from, however we can still not be entirely sure that these moths were feeding/living in Hundred Acre just from evidence that adults were trapped there. Larval searches will be needed to confirm this and the GPS coordinates of trapping locations here could be used as a starting point.

Also, note that there has been reed on Hundred Acre for 40 years (before that it was arable land). However this evidence does suggest that the bittern-focused management and cutting regimes on Hundred Acre have not been detrimental for these moths. Further work would be needed to confirm this, by looking at changes over time in the moths of Hundred Acre.

34

Table 6.11: Wetland specialists in old and new reedbed at Hickling Broad

Broad Hundred Acre

Family Species Family Species

Arctiidae Pelosia muscerda * 2 Arctiidae Pelosia muscerda * 2

Arctiidae Pelosia obtusa * 11 Arctiidae Pelosia obtusa * 6

Arctiidae Spilosoma urticae * 3 Arctiidae Spilosoma urticae * 6

Arctiidae Thumatha senex * 1 Arctiidae Thumatha senex * 2

Coleophoridae Coleophora follicularis 1 Cossidae Phragmataecia castaneae * 16

Cosmopterigidae Limnaecia phragmitella 2 Geometridae Orthonama vittata * 2

Cossidae Phragmataecia castaneae * 42 Glyphipterigidae Orthotelia sparganella 1

Gelechiidae Monochroa divisella 7 Noctuidae Archanara dissoluta * 21

Geometridae Orthonama vittata * 29 Noctuidae Archanara sparganii * 1

Geometridae Pterapherapteryx sexalata 3 Noctuidae Arenostola phragmitidis * 42

Noctuidae Archanara dissoluta * 2 Noctuidae Celaena leucostigma * 44

Noctuidae Archanara sparganii * 1 Noctuidae Chilodes maritimus * 25

Noctuidae Arenostola phragmitidis * 30 Noctuidae Chortodes brevilinea * 2

Noctuidae Celaena leucostigma * 18 Noctuidae Mythimna flammea * 9

Noctuidae Chilodes maritimus * 5 Noctuidae Mythimna pudorina * 32

Noctuidae Chortodes brevilinea * 3 Noctuidae Mythimna straminea * 98

Noctuidae Macrochilo cribrumalis 1 Noctuidae Nonagria typhae * 5

Noctuidae Mythimna flammea * 6 Noctuidae Schrankia costaestrigalis 1

Noctuidae Mythimna pudorina * 11 Noctuidae Simyra albovenosa * 48

Noctuidae Mythimna straminea * 53 Pyralidae Acentria ephemerella 1

Noctuidae Nonagria typhae * 5 Pyralidae Calamotropha paludella * 1

Noctuidae Plusia festucae 1 Pyralidae Cataclysta lemnata * 16

Noctuidae Simyra albovenosa * 10 Pyralidae Chilo phragmitella * 54

Pterophoridae Adaina microdactyla 1 Pyralidae Donacaula forficella 1

Pyralidae Calamotropha paludella * 1 Pyralidae Eudonia pallida * 10

Pyralidae Cataclysta lemnata * 2 Pyralidae Nascia cilialis * 1

Pyralidae Chilo phragmitella * 23 Pyralidae Parapoynx stratiotata 7

Pyralidae Elophila nymphaeata 1 Pyralidae Phlyctaenia perlucidalis 2

Pyralidae Eudonia pallida * 3 Pyralidae Schoenobius gigantella * 51

Pyralidae Nascia cilialis * 2

35


Tortricidae Phalonidia manniana 3

There were 29 wetland specialist moth species found in the Hundred Acre reedbed and 32 in the reedbed around the Broad. The two areas had 23 wetland specialist species in common. Hundred Acre had higher abundances of wetland specialists than the reedbed around the Broad.

What reedbed habitat conditions were associated with maximum number of Lepidoptera species at the survey sites?

Number of species

Firstly raw number of species per trap was analysed in relation to the different habitat variables. Then this analysis was repeated on bootstrapped number of species (examining average diversity within a fixed number of individuals in each trap).

Figure 6.29: Relative importance of habitat variables in explaining variation in number of moth species per trap. These models explained 94 % of the variance.

Site

Differences between sites were more important than habitat variation within sites in explaining moth species diversity in traps. Hickling Broad and Stodmarsh had higher moth species diversity per trap than Ham Wall. Since site differences were more important than other habitat variables, and sites cannot be analysed separately since there are only 12 traps per site, these results may be confounded by differences in habitat variables between sites.

36

Figure 6.30: Relationship between number of species in moth traps and site


Points where the litter did not flood entirely in the summer season before surveys tended to trap more moth species than points where the litter did flood.

Figure 6.31: Relationship between number of species in moth traps and litter saturation 2009

37


Points where the litter did not flood entirely in the season of surveys tended to trap more moth species than points where the litter did flood.

Figure 6.32: Relationship between number of moth species in traps and litter saturation 2010

Mean reed height

Traps with shorter reed tended to trap more moth species. However this appears to be a product of Ham Wall trap locations having short reed and low numbers of moths trapped.

1.5 2.0 2.5

33

34

35

36

37

Partial Plot

Mean Reed Height

1.5 2.0 2.5

20

30

40

50

60

70

Raw Data

Mean Reed Height

No

. S

pe

cie

s

Figure 6.33: Relationship between number of species in moth traps and mean reed height

38

Litter depth 2010

Traps with deeper litter tended to trap more moth species.

0 10 20 30 40

34

.53

5.0

35

.53

6.0

36

.53

7.0

Partial Plot

Litter Depth 2010

0 10 20 30 40

20

30

40

50

60

70

Raw Data

Litter Depth 2010

No

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Figure 6.34: Relationship between number of species in moth traps and litter depth 2010

Pole height

Surprisingly points with shorter poles tended to trap more moth species, which was the opposite of expectations. We expected traps mounted on taller poles to draw species in from a larger area. By including this variable in models along with reed height, we have taken into account the interaction between pole height and reed height.

1.0 1.2 1.4 1.6 1.8

33

34

35

36

Partial Plot

Pole Height

1.0 1.2 1.4 1.6 1.8

20

30

40

50

60

70

Raw Data

Pole Height

No

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Figure 6.35: Relationship between number of species in moth traps and pole height

39

Plant species richness

Points with greater plant species richness were associated with greater numbers of moth species.

0 5 10 15

34

.53

5.0

35

.53

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36

.53

7.0

37

.5

Partial Plot

Plant richness

0 5 10 15

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Raw Data


No

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Figure 6.36: Relationship between number of species in moth traps and plant species richness

Bootstrapped number of species

Important habitat variables in explaining variation in moth species diversity

Points closer to scrub tended to trap a greater diversity of moth species.

Points with short reed (and this was correlated with thinner reed) tended to trap a higher diversity of moths. This was not necessarily because these points were more exposed because pole height was included in the model.

Points where the litter had not fully saturated in the four months preceding the survey were associated with a higher overall diversity of moths.

However points with standing water during surveys trapped only a slightly lower species diversity of moths than points without standing water.

Points with high plant species richness tended to be associated with a high diversity of moth species.

Ham Wall had a lower overall moth diversity than the other two sites.

Points with deeper litter tended to trap a higher diversity of moth species but this may be a product of the sites sampled.

40

Figure 6.29: The relative importance of habitat variables in explaining variation in bootstrapped number of moth species. These models explained on average 92% of the variance.

Distance to Scrub

Points that were closer to scrub tended to trap a more diverse array of moth species. This would be expected since more plant species will support a greater range of species, such as those associated with carr or other plants linked with a later stage in plant succession. However traps along a gradient of increasing distance from scrub would be good to confirm this trend.

41

0 50 100 150 200 250 300

18

.01

8.2

18

.41

8.6

18

.81

9.0

19

.2

Partial Plot

Distance to Scrub

0 50 100 150 200 250 300

14

16

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Raw Data

Distance to Scrub

Bo

ots

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Figure 6.37: Relationship between distance to scrub and bootstrapped number of moth species

Mean reed height

Points with shorter reed tended to have a more diverse array of species caught in traps. There is the possibility that points where reed was taller than the trap were not able to attract moths over such a large area as points where reed was below the trap. This factor probably had some effect. However when pole height was included in models it was much less important than mean reed height in explaining bootstrapped number of species. Also by bootstrapping, we are measuring the diversity of moths within a set number of individuals, so this reduces the effect of traps that trap more individuals trapping more species.

1.0 1.2 1.4 1.6 1.8

18

.70

18

.80

18

.90

Partial Plot

Pole height

1.0 1.2 1.4 1.6 1.8

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16

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Raw Data

Pole height

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Figure 6.38: Relationship between pole height and bootstrapped number of species

0 10 20 30 40

45

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11


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If pole height had a major effect, we would expect it to have been an important factor in the model and for taller poles to be linked to higher moth species richness. In fact, shorter poles were linked with higher moth species richness and this was true even when the outlier of the extremely tall pole with low moth species diversity was removed.


Litter saturation in 2010 was much more important than in 2009. Points where the litter was never fully saturated were associated with higher moth species diversity. When all species are considered there is a greater range of life cycles, so perhaps this is why both litter saturation in 2009 and 2010 are important in explaining overall diversity.

Figure 6.39: Relationship between litter saturation and bootstrapped number of moth species.

Standing water

Points with lower levels of standing water during surveys tended to trap a more diverse array of moth species. However points with higher levels of standing water trapped almost as many moth species. Perhaps this reflects wet and dry areas supporting a different suite of species.

43

0 10 20 30 40

18

.41

8.6

18

.81

9.0

19

.2

Partial Plot

Standing Water

0 10 20 30 40

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16

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Raw Data

Standing Water

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Figure 6.40: Relationship between standing water around the trap during surveys and bootstrapped number of moth species trapped

Site

Figure 6.41: Relationship between site and bootstrapped number of species

Hickling Broad had the greatest number of moth species and the greatest abundance of individuals. This could be because Hickling Broad is the largest site. When abundance was accounted for by bootstrapping, Stodmarsh had equal bootstrapped number of species per trap to Hickling Broad. Stodmarsh had the greatest variance of number of species between traps. Ham Wall had the lowest

0 10 20 30 40

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abundance and diversity of moths, but abundance was not far behind Stodmarsh. The lower diversity at Ham Wall is likely to be a combination of its newer age and western location. 20 of the 187 species found at Hickling Broad and Stodmarsh combined would not be expected to occur in the SW which accounts for the lower species diversity at Ham Wall to some extent.

Table 6.12: Number of species and abundance of moths at each site

Hickling Broad Ham Wall Stodmarsh

Number of traps (n=12) (n=12) (n=12)

Total number of moth species 135 78 128

Total abundance of moth individuals

2222 1470 1573

Average of number of moth species

42.08 27.25 37.17

Variance of number of moth species

105.90 71.84 141.06

Average of abundance of moth individuals

185.17 122.50 131.08


This variable was included because it may have affected moths that pupated in the litter the previous year. Again points where the litter did not totally flood were associated with a higher overall moth species diversity.

Figure 6.42: Relationship between litter saturation 2009 and bootstrapped number of moth species.

45

Plant richness

Points with higher plant diversity had a higher diversity of moths trapped at them, as expected.

0 5 10 15

18

.81

9.0

19

.21

9.4

Partial Plot

Plant richness

0 5 10 151

41

61

82

02

22

42

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Raw Data

Plant Richness

Bo

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Figure 6.43: Relationship between plant species richness and bootstrapped number of moth species

Litter depth 2010

Points with deeper litter were associated with greater overall moth diversity. However this may be a product of the sites surveyed. Further surveys would reveal more about this trend.

0 10 20 30 40

18

.61

8.8

19

.01

9.2

19

.4

Partial Plot

Litter Depth 2010

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16

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Raw Data

Litter Depth 2010

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Figure 6.44: Relationship between litter depth 2010 and bootstrapped number of species

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What habitat variables were associated with moths with a conservation status?

This analysis relates the conservation score of each moth trap to the habitat variables measured in

the vicinity.

Figure: Relative importance of habitat variables in explaining variation in conservation scores

between traps. These models explained 95% of the variance.

Site

Hickling Broad had a higher number of species of high conservation importance than the other two

sites.

Figure: Relationship between conservation score in moth traps and site

47

Mean reed height

Traps with tall reed were associated with lower numbers of moths of conservation status. However

from the scatter plot this appears to be a product of the sites surveyed. Ham Wall had taller reed

and fewer moths with a conservation status that the other sites.

1.5 2.0 2.5

38

40

42

44

46

Partial Plot

Mean Reed Height

1.5 2.0 2.5

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40

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Raw Data

Mean Reed Height

Co

nse

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Figure: Relationship between conservation score in moth traps and mean reed height


Points with higher plant species richness tended to trap more moths with a conservation status. This

reflects the range of food plants within the UK BAP widespread but declining species.

0 5 10 15

42

43

44

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46

Partial Plot

Plant richness

0 5 10 15

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Raw Data

Plant richness

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Figure: Relationship between conservation score in moth traps and plant species richness

48


Points where the litter was not fully saturated in the summer season 2009 tended to trap more

species of conservation status. This may be because some moths pupated in this litter the year

before, or it may reflect more general habitat preferences for areas that tend to have dry periods.

Figure: Relationship between conservation score in moth traps and litter saturation 2009


Points where the litter was not fully saturated in the summer season 2010 tended to trap more

species of conservation status.

Figure: Relationship between conservation score in moth traps and litter saturation 2010

49

Standing water 2010

The highest conservation scores in moth traps were at dry points. However points with standing

water did also trap species with conservation statuses.

0 10 20 30 40

40

.54

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41

.54

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42

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Partial Plot

Standing Water

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Standing Water

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Figure: Relationship between conservation score in moth traps and standing water 2010

Composite habitat variables

A number of the measured habitat variables are associated with each other, due to the nature of reedbed successional habitat. Although this inter-correlation was controlled for in random forest models, a separate principle component analysis (PCA) was carried out to see if similar results were found when composite habitat variables were used.

Summary of tests correlating principle components for each survey dataset with bootstrapped number of species in moth traps

The first four principle components explained 81% of the data. Principle component 1 was most strongly negatively correlated with bootstrapped number of species in moth traps. PC1 represents a gradient of increasing reed height, increasing stem diameter and decreasing stem density. Shorter, thinner reed at higher stem densities was correlated with higher bootstrapped species number of moth species in this dataset. Random forest analysis also found shorter, thinner reed to be associated with greater moth species diversity. Plant species richness was important in random forest models, which is less evident here with only a weak correlation between PC2 and bootstrapped number of species. This may be because wetter points tended to have high stem density and high plant species richness. Stem density was a large contributor to PC1 so may have already explained some of the variation associated with plant diversity, leading to a reduced effect of plant diversity.

50

Table 6.13: Principle components (rotated varimax) for the moth dataset habitat variables

PC1 PC2 PC3 PC4

Standing Water 0.140 -0.501 0.490 -0.200

Litter depth -0.369 -0.290 0.443 -0.333

Reed height 0.512 -0.336 -0.141 -0.207

Diameter 0.557 -0.163 0.043 0.059

Plant species richness -0.004 0.490 0.022 -0.750

Stem density -0.405 -0.358 -0.141 -0.132

Dead stems (%) 0.036 -0.277 -0.642 -0.430

Distance to scrub 0.326 0.285 0.333 -0.193

Standard Deviation 1.581 1.350 1.178 0.878

Proportion of variance 0.312 0.228 0.174 0.096

Cumulative proportion of variance

0.312 0.540 0.714 0.810

Table 6.14: Results of Pearson’s correlation test between the first four principle components and bootstrapped number of species in moth traps

Component Pearsons df t p

PC1 -0.541 34 -3.75 0.000657 ***

PC2 0.24 34 1.439 0.1594

PC3 -0.068 34 -0.397 0.6937

PC4 -0.139 34 -0.820 0.418

These Pearson’s tests show what composite habitat variables correlate most strongly with bootstrapped number of species. In other words, the environmental gradients that are most strongly associated with differences in diversity of moths. The results validate the outcomes of the random forest models, since many of the same trends were seen. It is interesting to note that the principle components varied between the three invertebrate datasets, showing that the key environmental gradient results are very dependent on where the sampling points were placed.

References

Breiman, L. (2001). Random forests. Machine Learning J. 45 5- 32.

Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees.

Monterey, CA: Wadsworth & Brooks/Cole Advanced Books & Software.

Hochachka WM, Caruana R, Fink D, Kelling S, Munson A, Riedewald M, Sorokina D (2007) Data

mining for discovery of pattern and process in ecological systems. e Journal of Wildlife Management,

71: 2427–2437

51

UK BAP (2007) UK Priority Species data collation Chortodes brevilinea version 2 updated on 15/12/2010. Available at http://www.jncc.gov.uk/_speciespages/2169.pdf. [Accessed 26.01.11].

Zuur AF, Ieno EN, Elphick CS (2010) A protocol for data exploration to avoid common statistical

problems. Methods Ecol Evol 1: 3–14.

Appendix

Table 6A: List of reedbed specialist moths trapped in these surveys with internal feeders highlighted in bold (as defined by experts)

Family Species Notes

Arctiidae Pelosia obtusa External feeder, probably on algae on reed litter.

Cossidae Phragmataecia castaneae Internal feeder, pupates in stem, Common reed

Gelechiidae Brachmia inornatella probably an internal feeder, pupating in the stem, Common reed

Noctuidae Archanara dissoluta Internal feeder, pupates in stem, Common reed

Noctuidae Archanara geminipuncta Internal feeder, pupates in stem, Common reed

Noctuidae Arenostola phragmitidis Internal feeder, pupates in stem, Common reed

Noctuidae Chilodes maritimus Internal feeder, probably pupates in stem, Common reed

Noctuidae Chortodes brevilinea Internal feeder, pupates in plant debris, Common reed

Noctuidae Mythimna flammea External feeder. Hides in broken stem by day, pupates in stem, Common reed

Noctuidae Mythimna obsoleta External feeder. Hides in dead or fallen stems, pupating in situ, Common reed

Noctuidae Mythimna straminea

External feeder. Hides by day in old stems or leaf litter. Probably pupates on the ground. Common reed and Reed canary-grass

Noctuidae Simyra albovenosa External feeder. Pupates on or near the ground. Mainly on Common reed.

Pyralidae Chilo phragmitella Internal feeder, pupates in stem, Common Reed or Reed Sweet-grass

Pyralidae Donacaula forficella External feeder, pupating in a spinning. Common Reed, Reed Sweet-grass, bur-reed and sedges.

Pyralidae Donacaula mucronellus

Internal feeder, pupates in stem, Common Reed, Reed Sweet-grass, Greater Pond Sedge and other sedges

52

Pyralidae Schoenobius gigantella Internal feeder, pupates in stem, Common Reed and Reed Sweet-grass.

Table 6B: List of wetland specialist moths trapped in these surveys (wetland specialists as defined by experts)

Family Species Notes

Arctiidae Pelosia obtusa Reedbed specialist

Arctiidae Spilosoma urticae External feeder, pupates in plant debris, Water mint, Water dock etc.

Arctiidae Thumatha senex External feeder. Prob. mosses and lichens, pupating on ground

Coleophoridae Coleophora follicularis

External feeder, pupating in a case often on or near the foodplant. Hemp agrimony, common fleabane.

Cosmopterigidae Limnaecia phragmitella In the flower-spike, pupating therein. Bulrush or Lesser bulrush

Cossidae Phragmataecia castaneae Reedbed specialist

Gelechiidae Brachmia inornatella Reedbed specialist

Gelechiidae Monochroa divisella Not known, poss. on Iris

Geometridae Orthonama vittata External feeder, prob. pupating on the ground, Marsh bedstraw, Heath bedstraw

Geometridae Pterapherapteryx sexalata Carr, external feeder, prob. pupating in plant debris, sallows etc.

Glyphipterigidae Orthotelia sparganella Internal feeder, pupating in the stem. Burr-reed, Iris spp. or Reed sweet-grass.

Noctuidae Apamea ophiogramma Internal feeder, pupates on the ground or in leaf litter. Reed Canary-grass, Reed sweet-grass

Noctuidae Archanara dissoluta Reedbed specialist

Noctuidae Archanara geminipuncta Reedbed specialist

Noctuidae Archanara sparganii Internal feeder, pupating in the stem. Bulrush, Lesser bulrush, Yellow Iris etc.

Noctuidae Arenostola phragmitidis Reedbed specialist

Noctuidae Celaena leucostigma Internal feeder, pupating in leaf litter. Yellow iris and Great fen-sedge

Noctuidae Chilodes maritimus Reedbed specialist

Noctuidae Chortodes brevilinea Reedbed specialist

Noctuidae Coenobia rufa Internal feeder, pupating in the stem. Jointed rush, , Sharp-flowered rush, Soft-rush

Noctuidae Macrochilo cribrumalis External feeder, pupating in plant debris. Poss.

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on Wood sedge, Hairy wood-rush etc.

Noctuidae Mythimna flammea Reedbed specialist

Noctuidae Mythimna obsoleta Reedbed specialist

Noctuidae Mythimna pudorina External feeder, pupates close to the ground. Broad-leaved grasses

Noctuidae Mythimna straminea Reedbed specialist

Noctuidae Nonagria typhae Internal feeder, pupating in the stem. Bulrush and occ. Lesser bulrush

Noctuidae

Plusia festucae

External feeder, pupating between leaves of rushes etc. Tufted sedge, Glaucous sedge etc.

Noctuidae Schrankia costaestrigalis Larva unknown in the wild

Noctuidae Simyra albovenosa Reedbed specialist

Pterophoridae Adaina microdactyla Internal feeder, pupating in the stem. Hemp agrimony.

Pyralidae Acentria ephemerella

Aquatic, pupating under the water. Canadian Waterweed, pondweeds, stoneworts, filamentous algae and possibly other water-plants.

Pyralidae Calamotropha paludella Internal feeder, pupating in the stem. Bulrush and occ. Lesser bulrush

Pyralidae Cataclysta lemnata Aquatic, pupating just below water surface. Duckweed, including Greater Duckweed.

Pyralidae Chilo phragmitella Reedbed specialist

Pyralidae Donacaula forficella Reedbed specialist

Pyralidae Donacaula mucronellus Reedbed specialist

Pyralidae Elophila nymphaeata Aquatic, pupating just below water surface. Polyphagous on a range of water plants

Pyralidae Eudonia pallida In a spinning, probably pupating therein. Poss. on range of mosses and lichens on the ground

Pyralidae Nascia cilialis

External feeder, prob. pupating amongst sedge litter. Great Fen-sedge, Greater-pond Sedge and other sedge species

Pyralidae Parapoynx stratiotata

Aquatic, pupating near water surface. Pondweeds, Canadian Waterweed, Hornwort and other water-plants.

Pyralidae Phlyctaenia perlucidalis

External feeder, prob. pupating near the ground. Creeping Thistle, Marsh Thistle and probably other thistle species

Pyralidae Schoenobius gigantella Reedbed specialist

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Tortricidae Bactra furfurana Internal feeder, pupating in the stem. Common club-rush and Sharp-flowered rush

Tortricidae Phalonidia manniana Internal feeder, pupating in the stem. Water mint and Gipsywort

Arctiidae Pelosia muscerda

Carr, pupation site not known. Prob. on algae and lichens on bushes etc. This was on ISIS list, but not the Experts list!

Noctuidae Apamea unanimis

External feeder. Pupates in leaf litter or in a dead stem. Grasses inc. Reed canary-grass. This was on ISIS list, but not the Experts list!

Noctuidae Parastichtis ypsillon Carr. External feeder, pupates under bark or on the ground, sallow, willow, poplars.

Fenn’s Wainscot, Chortodes brevilinea

Table 6C: Records of Fenn’s Wainscot at Hickling Broad

Trap number Grid Reference Date Number of individuals

Trap 17 TG4364021000 21/07/2010 2

Trap 11 TG4367121320 09/08/2010 1

Trap 8 TG4334021209 09/08/2010 1

Trap 1 TG4277120996 20/07/2010 1

Points 8 and 11 were in the newer reedbed “100 Acre” whereas points 17 and 1 were in the older reedbed fringing the broad.

55

Figure 6A: Hydrology of the points where Fenn’s Wainscott was recorded.

Table 6D: The habitat variables measured at moth trapping points

Trap number

Fenn’s points All Hickling Points

Habitat Variable HB1 HB8 HB11 HB17 max mean min max mean min

Live Reed Height 0.57 0.45 0.3 0.17 0.57 0.37 0.17 0.67 0.34 0

Dead Stems % 0.75 0.51 0.44 0.51 0.75 0.55 0.44 0.75 0.4 0

Dead Reed Height 0.8 0.64 0.67 0.34 0.8 0.61 0.34 0.89 0.62 0.15

Maximum Reed Height 0.8 0.64 0.67 0.34 0.8 0.61 0.34 0.89 0.58 0.14

Diameter 3.57 3.11 2.52 1.91 3.57 2.78 1.91 3.57 2.88 1.91

Standing Water 0 8.67 5.67 0 8.67 3.58 0 9.5 3.38 0

Plant Richness 12 0 4 6 12 5.5 0 18 6.58 0

Litter Depth 2010 19.5 12.5 15.25 2.25 19.5 12.38 2.25 38.25 17.96 2.25

56

Litter Depth 2009 23.5 44.75 47 15.75 47 32.75 15.75 51.5 32.83 6.5

Live Stem Density 54 256 127 102 256 134.76 54 388 154.08 54

Dead Stem Density 206 307 107 121 307 185.24 107 307 120.08 0

Total Stem Density 260 563 234 223 563 320 223 563 274.16 79

Litter Saturation

2009 W W W W * * * * * *

Litter Saturation

2010 P W W P * * * * * *

Scrub distance(m) 47 47 126 86 126 76.5 47 218 93.5 25

Table 6E: Recorded declines in the UK BAP widespread but rapidly declining moth species trapped during reedbed surveys

Species Common name Reason for BAP status

Acronicta rumicis Knot Grass Declined by 80% over the last 35 years

Amphipoea oculea Ear Moth Declined by 71% over the last 35 years.

Amphipyra tragopoginis Mouse Moth Declined by 73% over the last 35 years

Apamea remissa Dusky Brocade Declined by 76% over the last 35 years

Arctia caja Garden Tiger Declined by 89% over the last 35 years.

Brachylomia viminalis Minor Shoulder-Knot Declined by 73% over the last 35 years.

Caradrina morpheus Mottled Rustic Declined by 73% over the last 35 years

Celaena leucostigma Crescent Declined by 82% over the last 35 years

Hoplodrina blanda Rustic Declined by 75% over the last 35 years

Hydraecia micacea Rosy Rustic Declined by 86% over the last 35 years.

Malacosoma neustria Lackey Declined by 90% over the last 35 years.

Melanchra pisi Broom Moth Declined by 77% over the last 35 years

Mythimna comma Shoulder-striped Wainscot Declined by 72% over the last 35 years.

Orthonama vittata Oblique Carpet Declined by 83% over the last 35 years

Pelurga comitata Dark Spinach Declined by 95% over the last 35 years.

Spilosoma lubricepeda White Ermine Declined by 77% over the last 35 years

Spilosoma luteum Buff Ermine Declined by 73% over the last 35 years

Timandra comae Blood-vein Declined by 79% over the last 35 years

57

Watsonalla binaria Oak Hook-Tip Declined by 81% over the last 35 years

Table 6F: GPS coordinates of moth trap locations

Site Trap code Easting Northing

HB HB1 642771 320996

HB HB11 643671 321320

HB HB12 643628 321411

HB HB13 643117 320887

HB HB16 643420 320870

HB HB17 643640 321000

HB HB19 643572 320772

HB HB3 642978 321354

HB HB5 643270 321420

HB HB7 643143 321107

HB HB8 643340 321209

HB HB9 643441 321093

HW HW1 346500 140150

HW HW10 346424 139867

HW HW12 345978 140463

HW HW13 346310 140120

HW HW14 346378 139815

HW HW20 346620 140420

HW HW21 346827 140256

HW HW3 345739 140545

HW HW4 345995 140182

HW HW7 346034 139844

HW HW8 346546 140362

HW HW9 346546 140175

SM SM1 621570 161560

SM SM11 622820 161820

SM SM12 622770 161790

SM SM13 623184 162533

SM SM16 623400 162505

SM SM17 623472 162790

SM SM19 623719 162684

58

SM SM2 621590 161180

SM SM21 623949 162720

SM SM6 622230 161170

SM SM8 622160 161890

wildlife surveys chapter 6: light trap surveys for moths ... · moths with a conservation score...

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