Submitted 1 October 2014Accepted 5 February 2015Published3 March 2015Corresponding authorAmanda Roe, aroe@csm.eduAcademic editorJuan Riesgo-EscovarAdditional Information andDeclarations can be found onpage 12DOI 10.7717/peerj.803Copyright2015 Roe and HigleyDistributed underCreative Commons CC-BY 4.0OPEN ACCESSDevelopment modeling of Luciliasericata (Diptera: Calliphoridae)Amanda Roe1and Leon G. Higley21Biology Program, College of Saint Mary, Omaha, NE, United States2School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE, United StatesABSTRACTThe relationship between insect development and temperature has been well estab-lished and has a wide range of uses, including the use of blow ies for postmortem(PMI) interval estimations in death investigations. To use insects in estimating PMI,we must be able to determine the insect age at the time of discovery and backtrackto time of oviposition. Unfortunately, existing development models of forensicallyimportant insects are only linear approximations and do not take into account thecurvilinear properties experienced at extreme temperatures. A series of experimentswere conducted with Lucilia sericata, a forensically important blow y species, thatmet the requirements needed to create statistically valid development models. Exper-iments were conducted over 11 temperatures (7.5 to 32.5C, at 2.5C) with a 16:8L:D cycle. Experimental units contained 20 eggs, 10 g beef liver, and 2.5 cm of pineshavings. Each life stage (egg to adult) had ve sampling times. Each sampling timewas replicated four times, for a total of 20 measurements per life stage. For each sam-pling time, the cups were pulled fromthe chambers and the stage of each maggot wasdocumented morphologically through posterior spiracle slits and cephalopharyngealskeletal development. Data were normally distributed with the later larval stages(L3f, L3m) having the most variation within and transitioning between stages. Thebiological minimum was between 7.5C and 10C, with little egg development andno egg emergence at 7.5C. Temperature-induced mortality was highest from 10.0to 17.5C and 32.5C. The development data generated illustrates the advantages oflarge datasets in modeling Lucilia sericata development and the need for curvilinearmodels in describing development at environmental temperatures near the biologicalminima and maxima.SubjectsDevelopmental Biology, EntomologyKeywordsBlow y, Forensic entomology, Forensic science, EcophysiologyINTRODUCTIONIn the past, insect development research has focused on agriculture pests and diseasevectors, with temporal accuracy levels of days (or weeks) considered acceptable sincethe focus was on economic thresholds and vector prevention (Higley & Haskell, 2010).In the last 50 years, however, there has been a growing interest in the developmentof necrophagous insects. Unfortunately, unlike agricultural and medically importantinsects, whose biology had been studied down to eye color during pupal stages andmode of infection from digestive track to mouthparts, necrophagous ies had no suchHow to cite this article Roe and Higley (2015), Development modeling of Lucilia sericata (Diptera: Calliphoridae). PeerJ 3:e803;DOI 10.7717/peerj.803fervor surrounding them and their development data was relegated to a few ecologicalstudies (e.g., Mackerras, 1933; Fuller, 1934; Kamal, 1958). Interest in necrophagous insects,specically blow ies (Diptera: Calliphoridae) continued (and continues) to rise with the(re)discovered usefulness of their development for postmortem interval estimations (PMIor time since death) (Greenberg, 1991).The blow y, Lucilia sericata, is a species among that group of necrophagous insects.They are ubiquitous, covering a broad range of landscapes, and may be one of the mostcommon blow y species in the world (Hall, 1948; Greenberg, 1991; Byrd & Castner, 2010).As such, this species is at the forefront of biological and development studies because ofits role in maggot therapy, animal (including human) myiasis, and postmortem intervalestimations.When found on a human body, the developing eggs, larvae, or pupae of L. sericatacan be used as an index pointing to the postmortem interval (PMI). Estimating thePMI is crucial in most human death investigations because time since death is neededto properly reconstruct events before and after death. Using development in estimatingPMI is dependent on determining the insect age at the time of discovery and backtrackingto time of oviposition. Consequently, understanding temperature-specic developmentrates is essential, yet development rate concepts from agricultural pest developmentdata sets/models are being applied to postmortem interval estimations, implyinglevels of precision greater than the data allow (e.g., see discussion in Higley & Haskell,2010). Among the most substantial studies on Lucilia sericata development (in terms oftemperatures examined and overall citations) are those of Kamal (1958), Ash & Greenberg(1975), Greenberg (1991), Anderson (2000) and Grassberger & Reiter (2001) (Table 5).However, many methodological problems exist in these studies relative to determiningdevelopment rates, including insucient replication, inconsistent temperature rangesor too few temperatures, no indication of temperature variability, non-life stage specicresults, and unspecied or inconsistent sampling intervals. In total, limitations withexisting data make it dicult to apply error rates or condence intervals. These arekey problems, not only in L. sericata data, but in most blow y developmental data.Generally, there is little consistency between studies making it dicult to pool data ormake comparisons.Although various procedures exist for measuring development rates, the simplestand most common is regression (either linear or curvilinear). However, data for use inregressions must meet specic criteria (Snedecor & Cochran, 1989). Independent variables(temperatures in development regressions) must be equally spaced, otherwise values atthe ends of the examined range have a disproportionate inuence on the relationship.Additionally, independent variables are assumed to have zero or negligible variation,otherwise systematic error can occur in the calculated relationship.Perhaps the most cited aw in regression analyses is to t a linear model to curvilineardata (Snedecor & Cochran, 1989). This issue is especially pertinent for blow y develop-ment, because degree-day models are based on linear regression, yet it is well establishedthat development is curvilinear (Higley, Pedigo & Ostlie, 1986; Higley & Haskell, 2010).Roe and Higley (2015), PeerJ, DOI 10.7717/peerj.803 2/14The solution is to explicitly limit the temperature range for which a degree-day model isvalid to linear portions of the development curve (Nabity, Higley &Heng-Moss, 2007).Another pertinent methodological point is how to replicate temperature treatments.By denition, an experimental unit is the thing to which a treatment is applied, andexperimental units must have independent replication. Because temperatures are appliedin growth chambers, the chamber is (by denition) the experimental unit (Snedecor &Cochran, 1989). Measurements of within growth chamber temperature variations andsystematic dierences between experienced and nominal chamber temperatures (Nabity,Higley & Heng-Moss, 2007) demonstrate that chamber replication and/or temperaturemeasurements within chamber locations are necessary to provide proper estimates ofexperimental error and to avoid systematic measurement errors. Richards & Villet (2008)discuss how deciencies in development data can reduce the accuracy of PMI estimations.In particular, sampling errors and models based on too few temperatures directly impactstatistical validity and error rates. Besides the obvious reason of unknown or high errorrates making it dicult to reach conclusions, known error rates are a requirement forFederal Rules of Evidence (Rule 702: Testimony by Expert Witnesses) under the Daubertstandard. Judges can use the the known or potential rate of error of the technique ortheory when applied as an assessment of reliability of the evidence being presented.Many of the issues associated with current data sets likely relates to the sheer amountof resources required to establish a complete, statistically valid development model.Preparatory work averages between 15 and 18 h per temperature. These hours includecutting weighed liver, labeling and organizing experimental units, counting eggs, andputting all units together before they go in the chambers. After set up, the hours requiredfor actual sampling can easily exceed 120 h (at an average of one hour per sampling time).A considerable time (not included in the hours above) is required for colony maintenance.Multiple colonies are required to for high egg production and to prevent time loss fromlossof a colony.Thus, although the experiments are time and labor intensive, we conducted a series ofexperiments that cover a broad range of temperatures, have large sample sizes, and have theconsistent sampling times required to create a statistically valid development model.METHODS AND MATERIALSFliesLucilia sericata were obtained from colonies maintained at the University of Nebraska-Lincoln (Lincoln, Nebraska). Colonies were established in October 2010, from eld-collected insects from Morgantown, West Virginia. At research time, the colonies hadachieved 100 generations without addition of new ies to reduce genetic variation withinthe colony. Adult ies were maintained in screen cages (46 cm46 cm46 cm) (BioquipProducts, California) in a rearing roomat 27.5C(3C), with a 16:8 (L:D) photoperiod.Multiple generations were maintained in a single cage, and ca. 1,000 adult ies wereintroduced every 12 weeks. Adults had access to granulated sugar and water ad libitum,and raw beef liver for protein and as an ovipositional substrate. After egg laying, eggs andRoe and Higley (2015), PeerJ, DOI 10.7717/peerj.803 3/14liver were placed in an 89 ml plastic cup, which was surrounded by pine shavings in a 1.7 Lplastic box. The pine shavings served as a pupation substrate. The 1.7 L box was placed ina I30-BLL Percival biological incubator (Percival Scientic, Inc., Perry, Iowa, USA) set at26C(1.5C). After eclosion, adults were released into the screened cages.IncubatorsIncubator information has been previously discussed in Lein (2013). Pertinent in-formationhasbeenrevisitedhere.IncubatorswerecustomizedmodelSMY04-1DigiThermCirKinetics Incubators (TriTech Research, Inc., Los Angeles, California,USA). The DigiThermCirKinetics Incubator have microprocessor controlled temper-ature regulation, internal lighting, recirculating air system (to help maintain humidity),and use a thermoelectric heat pump (rather than coolant and condenser as is typical withlarger incubators and growth chambers). Customizations included the addition of a dataport, vertical lighting (so all shelves were illuminated), and an additional internal fan.The manufacturers specications indicate an operational range of 1060 C 0.1 C.It is worth noting that a range of 0.1 C is an order of magnitude more precise thanis possible in conventional growth chambers. Although growth chambers have beenshown to display substantial dierences between programmed temperatures and actualinternal temperatures (Nabity, Higley & Heng-Moss, 2007), we tested the customizedDigiThermCirKinetics incubators in a replicated study and found internal temperatureson all shelves within incubators did not vary more than 0.4 C from the programmedtemperature (data not shown). Given this measured accuracy, the incubators could be usedwithout the need for additional internal temperature measurements or risk of systematicerror (as there was