Rock Chick Scat

Rock Chick Scat

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Underlined bases in PCR Round 1 are the Miseq tag primer. Bolded bases in PCR Round 2 are an example of the unique tags attached to each sample. A full list can be found in Appendix S1.

Total sequence reads obtained and categorised using the SILVA SSU data base. Contaminants included insects (31 628 reads), ectoparasites (31 578 reads) and human DNA from handling (5168 reads).

DNA amplification was analysed using binomial GLMs, the proportion of food DNA using quasibinomial GLMs. Superscript symbols indicate significantly different values (Tukey's multiple comparison test) * P < 0·05, #+ P < 0·001.

Generalised Linear Model fitted plots for: (a) sample freshness (fresh, recent or dry) and (b) substrate (dirt or rock). All scat samples collected during chick rearing, with only fresh scats included in the analysis of substrate. Points represent means, and bars show 95% confidence intervals.
DNA proportions for each: (a) sample freshness (fresh, recent and dry) and (b) substrate (dirt, rock and vegetation). All samples collected during chick rearing, with only fresh scats included in the analysis of substrate. To improve readability, the category ‘contaminant’ was excluded from the graph as it contained a very small proportion of DNA sequences.
Generalised Linear Model fitted plots of the (a) amplification success and (b) proportion of food for each breeding stage (incubation, brood and chick rearing); and (c) the amplification success and (d) the proportion of food for each age cohort within each breeding stage. Incubation samples included only scats collected randomly where incubation length was unknown. Points represent means, and bars show 95% confidence intervals.
DNA proportions for each: (a) breeding stage (incubation, brood and chick rearing); (b) developmental stage during brood (breeder, chick and non-breeder); and (c) incubation length (random, <1 day, 1–2 days and >2 days). Only fresh scats were analysed. To improve readability, the category ‘contaminant’ was excluded from the graph as it contained a very small proportion of DNA reads. The incubation category in ‘A’ included scats collected randomly where incubation length was unknown.

Collect fresh scats where the animal is seen defecating. If this is not possible, try to collect only scats that still have moisture or develop species-specific proxies that correlate to sample age.

Give serious consideration to the scat substrate type, as contamination from substrate can overwhelm the food DNA signal. Ideally, collect scats from surfaces with minimal sources of DNA contamination (e.g. rocks or ice). If collecting from dirt or vegetation, try to minimise the collection of foreign material and record the substrate (and species where applicable) to cross-check and validate results.

Take into consideration, the seasonal behaviour and feeding ecology of the study animal prior to sample collection.

Avoid collections from animals that may not have fed recently, such as periods of fasting.

Collect from animals that are directly feeding themselves and avoid secondary feeding where possible (including suckling young). Samples from young animals that are being fed by regurgitation may be problematic due to partially digested food passed on by the parents or large amounts of parental DNA. For such species, collection from older animals may be preferable.

If only a single collection is available and the seasonal timing and cohort are not the focus of the study, target the time period with the shortest time since feeding and focus on adult animals.

If multiple study sites are used, keep collection protocols and timing consistent between sites

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Institute for Marine and Antarctic Studies, University of Tasmania, Private Bag 129, Hobart, TAS, 7001 Australia
Australian Antarctic Division, 203 Channel Highway, Kingston, TAS, 7050 Australia
Department of Primary Industries, Parks, Water and Environment, 134 Macquarie Street, Hobart, TAS, 7000 Australia
Australian Antarctic Division, 203 Channel Highway, Kingston, TAS, 7050 Australia
Institute for Marine and Antarctic Studies, University of Tasmania, Private Bag 129, Hobart, TAS, 7001 Australia
Institute for Marine and Antarctic Studies, University of Tasmania, Private Bag 129, Hobart, TAS, 7001 Australia
Australian Antarctic Division, 203 Channel Highway, Kingston, TAS, 7050 Australia
Australian Antarctic Division, 203 Channel Highway, Kingston, TAS, 7050 Australia
CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Vairão, 4485-661 Portugal
Institute for Marine and Antarctic Studies, University of Tasmania, Private Bag 129, Hobart, TAS, 7001 Australia
Australian Antarctic Division, 203 Channel Highway, Kingston, TAS, 7050 Australia
Department of Primary Industries, Parks, Water and Environment, 134 Macquarie Street, Hobart, TAS, 7000 Australia
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Scat samples provide an important source of DNA that can be utilised in a wide range of molecular ecology studies (e.g. Davison et al . 2002 ; Prugh et al . 2005 ). Food DNA present in scats provides a non-invasive and increasingly popular tool for studying vertebrate diet and can be applied to both predators and herbivores (e.g. Deagle, Kirkwood & Jarman 2009 ; Zeale et al . 2011 ; Bowser, Diamond & Addison 2013 ; Kartzinel et al . 2015 ). Dietary DNA metabarcoding uses high-throughput sequencing of small, highly variable DNA regions that survive digestion to identify food species (Pompanon et al . 2012 ). This may involve identification of a particular food species using species-specific markers (Jarman & Wilson 2004 ); food within a taxonomic group using group-specific markers (Jarman, Deagle & Gales 2004 ; Murray et al . 2011 ; Zeale et al . 2011 ); identification of all food taxa using universal metazoan markers (O'Rorke et al . 2012 ; Jarman et al . 2013 ); or a combination of these approaches (Deagle, Kirkwood & Jarman 2009 ; Bowser, Diamond & Addison 2013 ). However, characterising the entire diet requires ‘universal’ markers that are capable of amplifying DNA from any food species (King et al . 2008 ; Jarman et al . 2013 ).
Universal metazoan polymerase chain reaction (PCR) primers amplify from all eukaryotic DNA, but will inevitably also amplify unwanted DNA from non-food items (Deagle, Kirkwood & Jarman 2009 ; O'Rorke et al . 2012 ). Non-target DNA within the scat may originate from the animal being sampled, its parasites, gut flora or contamination from external organisms such as insects and vegetation. These sources of DNA can dominate the sequences amplified from a sample, making detection of DNA from food items less effective. Sample sizes must consequently be increased to address the underlying questions of a study, increasing processing costs. In some cases, non-target DNA amplification can be reduced using a blocking primer to suppress amplification of specific DNA types, such as DNA of the defecating animal (O'Rorke, Lavery & Jeffs 2012 ). However, development of blocking primers is challenging and food sequences may be inadvertently blocked with this approach. The use of blocking primers becomes more complex when there are multiple non-target DNA groups present. Improved sampling procedures are another approach for increasing the proportion of food DNA identified in a scat.
Selective scat sampling to improve DNA amplification success in genotyping studies has been investigated (Lucchini et al . 2002 ; Piggott 2004 ; Panasci et al . 2011 ; Vynne et al . 2012 ), but studies to optimise scat collections for DNA dietary analysis are rare (Oehm et al . 2011 ). Genotyping studies have investigated how the age of scats (Farrell, Roman & Sunquist 2000 ; Lucchini et al . 2002 ; Piggott 2004 ; Panasci et al . 2011 ; Vynne et al . 2012 ), habitat type (Vynne et al . 2012 ) and season (Lucchini et al . 2002 ; Piggott 2004 ) affect DNA detection and genotyping accuracy. Fresh scats collected in dry and cool conditions typically provided the highest amplification success and lowest genotyping error rate. However, the time since an animal defecated is seldom known and proxies for scat age are often required. For example, in maned wolf Chrysocyon brachyurus scats, higher moisture content and odour were found to be positively correlated with amplification success (Vynne et al . 2012 ). Similarly in brush-tailed rock-wallaby scats Petrogale penicillata , colour, consistency and odour correlated well with DNA amplification success (Piggott 2004 ).
Only one dietary DNA study has examined how field conditions can influence the detection of food DNA. In carrion crow Corvus corone corone scats, exposure to sunlight and rain over a 5-day period caused significantly lower amplification success of food DNA (Oehm et al . 2011 ). This was exacerbated by dirt, which may increase the degradation of extracellular DNA (Levy-Booth et al . 2007 ). This study used species-specific markers, which do not amplify non-food DNA. There are currently no studies that investigate whether targeted sample collections improve the detection of food DNA by universal metazoan markers.
We used shy albatross Thalassarche cauta as a model to develop optimised field protocols for dietary DNA metabarcoding of scats. Albatross are a good example as they follow predictable behavioural patterns, where they return to the colony after feeding and fast on the nest during incubation. This makes scat samples accessible and tests of fasting effects possible. Albatross are known to eat a diverse range of food items, including jellyfish, cephalopods, fish and carrion (Cherel & Klages 1998 ). Universal metazoan PCR primer sets which amplify from all potential prey groups are therefore needed to screen for all food items. Albatross colonies present far from ideal laboratory conditions. Colonies are typically exposed to extremes of weather, with little or no vegetation cover. Sample degradation by UV and rain is likely to reduce PCR amplification success of exposed scats (Oehm et al . 2011 ). Contamination from non-food DNA, such as insects, parasites and fungi, will also reduce the proportion of food DNA detected. Colonies are often remote and expensive to access, on trips that are generally short and/or infrequent, so effective scat collection is imperative.
The optimised field protocols that we developed increase the detection of food DNA by considering the effect of sample freshness; the substrate it was collected from; the bird's breeding and developmental stage; and fasting time. The effects that these factors have on the detection of food DNA are significant enough to be an important consideration when designing dietary DNA studies of vertebrates.
Shy albatross lay one egg from early September to early October. The egg is incubated for 10 weeks (incubation stage), and the hatched chicks are brooded for 3–4 weeks (brood stage). During these two breeding stages, parents alternate nest attendance and foraging trips. After brooding, chicks are left unattended while both parents forage independently at sea to complete chick rearing (chick-rearing stage; Hedd & Gales 2005 ). During incubation, foraging trips may last from 1 to 10 days, with an average of 3 days (Hedd, Gales & Brothers 2001 ); therefore, an incubating bird could be fasting for this period or longer. Foraging trip durations during the brood stage are short at around 1 day and increase slightly during chick rearing to 2–3 days (Brothers et al . 1998 ; Hedd & Gales 2005 ).
Shy albatross scat samples were collected at Albatross Island, Tasmania, Australia (40°23′S, 144°39′E). Scat samples were collected during the breeding period over two seasons: 2013/2014 austral summer, chick rearing (late March) only; and 2014/2015 austral summer: incubation (late September), brood stage (mid December) and chick rearing (late March). Samples were collected during the daytime from albatross observed defecating. A small fragment of the non-uric acid portion of the scat (dark part) was collected using tweezers or a plastic straw. The sample was stored in 80% ethanol and shaken on collection to mix with the ethanol. The only time fresh scats were not collected was when sample freshness was investigated.
To determine the effect of sample freshness on DNA amplification rates and the proportion of food DNA detected, scats were collected during the chick-rearing period in 2013/2014 and 2014/2015. The amount of time a scat had been present was unknown when a scat was found. Consequently, we wanted to provide a proxy measure for freshness to allow selection of higher quality dietary material. To test this, scat samples were categorised as follows: (i) ‘Fresh’ when the bird was seen defecating, (ii) ‘Recent’ when the scat was still wet but the bird was not seen defecating (there was often a skin forming on these scats) or (iii) ‘Dry’ when scats were old and had no apparent moisture.
The dominant substrate from which the scat was collected was recorded for all fresh scats collected during chick rearing. Substrate categories included the following: dirt, rock and vegetation.
To determine whether collecting at different stages of breeding affected the results, we randomly collected from birds in the colony that we saw defecating during incubation, brood guard and chick rearing of the 2014/2015 breeding season.
When known, the breeding cohort of the bird was recorded as either ‘breeder’ a bird on an active nest or seen feeding a chick; ‘non-breeder’ a bird at an empty nest; or ‘chick’ which could have been a brooded chick <2 weeks old, or a pre-fledged chick c. 3·5 months old.
To test the effect that fasting had on dietary results, additional scats were collected during incubation. Two study sites within the colony were set up, each containing c. 100 nests. Each bi
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