Using DNA-barcoded Malaise trap samples to measure impact of a geothermal energy project on the biodiversity of a Costa Rican old-growth rain forest.

We report one year (2013-2014) of biomonitoring an insect community in a tropical old-growth rain forest, during construction of an industrial-level geothermal electricity project. This is the first-year reaction by the species-rich insect biodiversity; six subsequent years are being analyzed now. The site is on the margin of a UNESCO Natural World Heritage Site, Área de Conservación Guanacaste (ACG), in northwestern Costa Rica. This biomonitoring is part of Costa Rica's ongoing efforts to sustainably retain its wild biodiversity through biodevelopmental integration with its societies. Essential tools are geothermal engineering needs, entomological knowledge, insect species-rich forest, government-NGO integration, common sense, DNA barcoding for species-level identification, and Malaise traps. This research is tailored for integration with its society at the product level. We combine an academic view with on-site engineering decisions. This biomonitoring requires alpha-level DNA barcoding combined with centuries of morphology-based entomological taxonomy and ecology. Not all desired insect community analyses are performed; they are for data from subsequent years combined with this year. We provide enough analysis to be used by both guilds now. This biomonitoring has shown, for the first year, that the geothermal project impacts only the biodiversity within a zone less than 50 m from the project margin.

Expedited assessment of terrestrial arthropod diversity by coupling Malaise traps with DNA barcoding 1.

Monitoring changes in terrestrial arthropod communities over space and time requires a dramatic increase in the speed and accuracy of processing samples that cannot be achieved with morphological approaches. The combination of DNA barcoding and Malaise traps allows expedited, comprehensive inventories of species abundance whose cost will rapidly decline as high-throughput sequencing technologies advance. Aside from detailing protocols from specimen sorting to data release, this paper describes their use in a survey of arthropod diversity in a national park that examined 21 194 specimens representing 2255 species. These protocols can support arthropod monitoring programs at regional, national, and continental scales.

Mammary tumour development is dose-dependently inhibited by n-3 polyunsaturated fatty acids in the MMTV-neu(ndl)-YD5 transgenic mouse model.

BACKGROUND: Breast cancer is attributable to modifiable risk factors including the intake of dietary n-3 polyunsaturated fatty acids (PUFA). A key piece of evidence, yet to be addressed, that would demonstrate a causal relationship between n-3 PUFA and breast cancer, is a dose-dependent effect of n-3 PUFA on tumour outcomes. Thus, the objective of the present study was to determine whether n-3 PUFA reduces mammary gland tumor outcomes in a dose-dependent manner in female MMTV-neu(ndl)-YD5 transgenic mice, an aggressive model of human breast cancer. METHODS: Harems were provided one of three experimental diets comprised of 0, 3 or 9% (w/w) menhaden fish oil containing n-3 PUFA. Female offspring were weaned onto the same parental diet and maintained on their respective diet for 20 weeks. Tumour onset, size and multiplicity were measured throughout the study. Fatty acid composition of mammary gland and tumours were determined by gas-liquid chromatography. RESULTS: Tumour size was significantly (p < 0.05) reduced in a dose-dependent manner. n-3 PUFA were also incorporated in a dose-dependent manner; differential incorporation was observed for eicosapentaenoic and docosapentaenoic acids into mammary gland tissue, while docosahexaenoic acid was preferentially incorporated into tumours. CONCLUSION: Overall, the present study provides fundamental knowledge about the dose-dependent effect of n-3 PUFA on tumour outcomes in a pre-clinical model and also sheds light on the differential role of individual n-3 PUFA on tumour outcomes.

Global arthropod beta-diversity is spatially and temporally structured by latitude.

Global biodiversity gradients are generally expected to reflect greater species replacement closer to the equator. However, empirical validation of global biodiversity gradients largely relies on vertebrates, plants, and other less diverse taxa. Here we assess the temporal and spatial dynamics of global arthropod biodiversity dynamics using a beta-diversity framework. Sampling includes 129 sampling sites whereby malaise traps are deployed to monitor temporal changes in arthropod communities. Overall, we encountered more than 150,000 unique barcode index numbers (BINs) (i.e. species proxies). We assess between site differences in community diversity using beta-diversity and the partitioned components of species replacement and richness difference. Global total beta-diversity (dissimilarity) increases with decreasing latitude, greater spatial distance and greater temporal distance. Species replacement and richness difference patterns vary across biogeographic regions. Our findings support long-standing, general expectations of global biodiversity patterns. However, we also show that the underlying processes driving patterns may be regionally linked.

Abundant, diverse, unknown: Extreme species richness and turnover despite drastic undersampling in two closely placed tropical Malaise traps.

Arthropods account for a large proportion of animal biomass and diversity in terrestrial systems, making them crucial organisms in our environments. However, still too little is known about the highly abundant and megadiverse groups that often make up the bulk of collected samples, especially in the tropics. With molecular identification techniques ever more evolving, analysis of arthropod communities has accelerated. In our study, which was conducted within the Global Malaise trap Program (GMP) framework, we operated two closely placed Malaise traps in Padang, Sumatra, for three months. We analyzed the samples by DNA barcoding and sequenced a total of more than 70,000 insect specimens. For sequence clustering, we applied three different delimitation techniques, namely RESL, ASAP, and SpeciesIdentifier, which gave similar results. Despite our (very) limited sampling in time and space, our efforts recovered more than 10,000 BINs, of which the majority are associated with "dark taxa". Further analysis indicates a drastic undersampling of both sampling sites, meaning that the true arthropod diversity at our sampling sites is even higher. Regardless of the close proximity of both Malaise traps (< 360 m), we discovered significantly distinct communities.

A revision of the parasitoid wasp genus Alphomelon Mason with the description of 30 new species (Hymenoptera, Braconidae).

The parasitoid wasp genus Alphomelon Mason, 1981 is revised, based on a combination of basic morphology (dichotomous key and brief diagnostic descriptions), DNA barcoding, biology (host data and wasp cocoons), and distribution data. A total of 49 species is considered; the genus is almost entirely Neotropical (48 species recorded from that region), but three species reach the Nearctic, with one of them extending as far north as 45° N in Canada. Alphomelon parasitizes exclusively Hesperiinae caterpillars (Lepidoptera: Hesperiidae), mostly feeding on monocots in the families Arecaceae, Bromeliaceae, Cannaceae, Commelinaceae, Heliconiaceae, and Poaceae. Most wasp species parasitize either on one or very few (2-4) host species, usually within one or two hesperiine genera; but some species can parasitize several hosts from up to nine different hesperiine genera. Among species with available data for their cocoons, roughly half weave solitary cocoons (16) and half are gregarious (17); cocoons tend to be surrounded by a rather distinctive, coarse silk (especially in solitary species, but also distinguishable in some gregarious species). Neither morphology nor DNA barcoding alone was sufficient on its own to delimit all species properly; by integrating all available evidence (even if incomplete, as available data for every species is different) a foundation is provided for future studies incorporating more specimens, especially from South America. The following 30 new species are described: cruzi, itatiaiensis, and palomae, authored by Shimbori & Fernandez-Triana; and adrianguadamuzi, amazonas, andydeansi, calixtomoragai, carolinacanoae, christerhanssoni, diniamartinezae, duvalierbricenoi, eldaarayae, eliethcantillanoae, gloriasihezarae, guillermopereirai, hazelcambroneroae, josecortesi, keineraragoni, luciarosae, manuelriosi, mikesharkeyi, osvaldoespinozai, paramelanoscelis, paranigriceps, petronariosae, ricardocaleroi, rigoi, rostermoragai, sergioriosi, and yanayacu, authored by Fernandez-Triana & Shimbori.

DNA barcodes reveal striking arthropod diversity and unveil seasonal patterns of variation in the southern Atlantic Forest.

The Atlantic Forest harbors 7% of global biodiversity and possesses high levels of endemism, but many of its component taxa remain unstudied. Due to the importance of tropical forests and the urgency to protect them, there is a compelling need to address this knowledge gap. To provide more information on its arthropod fauna, a Malaise trap was deployed for 12 months in a semi-degraded area of the southern Upper Paraná ecoregion of the Atlantic Forest. All specimens were DNA barcoded and the Barcode Index Number (BIN) system was employed to assign each specimen to a species proxy. DNA barcodes were obtained from 75,500 arthropods that included representatives of 8,651 BINs. Nearly 81% of these BINs were first records, highlighting the high rates of endemism and lack of study of arthropods from the Atlantic Forest. Diptera was the most abundant order, followed by Hemiptera, Lepidoptera and Hymenoptera. Diptera was also the most species-rich order, followed by Hymenoptera, Lepidoptera, and Coleoptera, a result consistent with studies in other biogeographic regions. Insects were most abundant in winter and most diverse in autumn and winter. This pattern, however, was caused mainly by the dynamics of dipteran diversity as other orders differed in their seasonal variation. The BIN composition of the insect community varied sharply through the year and also differed between the two consecutive summers included in the sampling period. The study of the 38 commonest BINs showed that seasonal patterns of abundance were not order-specific. Temperature had the strongest impact on seasonal abundance variation. Our results highlight the striking and understudied arthropod diversity of the highly fragmented Atlantic Forest, the predominance of dipterans, and the fact that abundance and richness in this insect community peak in the coolest months. Standardized studies like this generate fast and reliable biodiversity inventories and unveil ecological patterns, thus providing valuable information for conservation programs.

A DNA barcode survey of insect biodiversity in Pakistan.

Although Pakistan has rich biodiversity, many groups are poorly known, particularly insects. To address this gap, we employed DNA barcoding to survey its insect diversity. Specimens obtained through diverse collecting methods at 1,858 sites across Pakistan from 2010-2019 were examined for sequence variation in the 658 bp barcode region of the cytochrome c oxidase 1 (COI) gene. Sequences from nearly 49,000 specimens were assigned to 6,590 Barcode Index Numbers (BINs), a proxy for species, and most (88%) also possessed a representative image on the Barcode of Life Data System (BOLD). By coupling morphological inspections with barcode matches on BOLD, every BIN was assigned to an order (19) and most (99.8%) were placed to a family (362). However, just 40% of the BINs were assigned to a genus (1,375) and 21% to a species (1,364). Five orders (Coleoptera, Diptera, Hemiptera, Hymenoptera, Lepidoptera) accounted for 92% of the specimens and BINs. More than half of the BINs (59%) are so far only known from Pakistan, but others have also been reported from Bangladesh (13%), India (12%), and China (8%). Representing the first DNA barcode survey of the insect fauna in any South Asian country, this study provides the foundation for a complete inventory of the insect fauna in Pakistan while also contributing to the global DNA barcode reference library.

?Addendum to a minimalist revision of Costa Rican Braconidae: 28 new species and 23 host records.

Twenty-nine species are treated, most of which have host caterpillar and food plant records, and all but one are new to science. The first host record for the agathidine genus Amputoearinus is given. Gnathopleurajosequesadai Sharkey, sp. nov. is reported as a hyperparasitoid of fly larvae, the first such record for the genus. The following new species are diagnosed primarily using COI barcode data; Sharkey is the authority for all: Agathidinae: Aerophilusdavidwagneri, Aerophilusfundacionbandorum, Aerophilusnicklaphami, Lytopylusdavidstopaki, Lytopylusdavidschindeli; Alysiinae: Gnathopleurajosequesadai; Braconinae: Braconandreamezae, Braconfranklinpaniaguai, Braconrafagutierrezi, Braconguillermoblancoi, Braconoscarmasisi, Braconpauldimaurai, Braconshebadimaurae, Saciremakarendimaurae; Cheloninae: Chelonusminorzunigai; Homolobinae: Homolobusstevestroudi; Macrocentrinae: Macrocentrusmichaelstroudi; Orgilinae: Stantoniagilbertfuentesi; Rhysipolinae: Rhysipolisstevearonsoni; Rogadinae: Aleiodeskaydodgeae, Aleiodeskerrydresslerae, Aleiodesjosesolanoi, Aleiodesjuniorporrasi, Aleiodesrocioecheverri, Aleiodesronaldzunigai, Choreborogasjesseausubeli, Triraphisdoncombi, and Yeliconesmayrabonillae.

Minimalist revision and description of 403 new species in 11 subfamilies of Costa Rican braconid parasitoid wasps, including host records for 219 species.

Three new genera are described: Michener (Proteropinae), Bioalfa (Rogadinae), and Hermosomastax (Rogadinae). Keys are given for the New World genera of the following braconid subfamilies: Agathidinae, Braconinae, Cheloninae, Homolobinae, Hormiinae, Ichneutinae, Macrocentrinae, Orgilinae, Proteropinae, Rhysipolinae, and Rogadinae. In these subfamilies 416 species are described or redescribed. Most of the species have been reared and all but 13 are new to science. A consensus sequence of the COI barcodes possessed by each species is employed to diagnose the species, and this approach is justified in the introduction. Most descriptions consist of a lateral or dorsal image of the holotype, a diagnostic COI consensus barcode, the Barcode Index Number (BIN) code with a link to the Barcode of Life Database (BOLD), and the holotype specimen information required by the International Code of Zoological Nomenclature. The following species are treated and those lacking authorship are newly described here with authorship attributable to Sharkey except for the new species of Macrocentrinae which are by Sharkey & van Achterberg: AGATHIDINAE: Aerophiluspaulmarshi, Mesocoelusdavidsmithi, Neothlipsisbobkulai, Plesiocoelusvanachterbergi, Pneumagathiserythrogastra (Cameron, 1905), Therophilusbobwhartoni, T.donaldquickei, T.gracewoodae, T.maetoi, T.montywoodi, T.penteadodiasae, Zacremnopsbrianbrowni, Z.coatlicue Sharkey, 1990, Zacremnopscressoni (Cameron, 1887), Z.ekchuah Sharkey, 1990, Z.josefernandezi, Zelomorphasarahmeierottoae. BRACONINAE: Braconalejandromarini, B.alejandromasisi, B.alexamasisae, B.andresmarini, B.andrewwalshi, B.anniapicadoae, B.anniemoriceae, B.barryhammeli, B.bernardoespinozai, B.carlossanabriai, B.chanchini, B.christophervallei, B.erasmocoronadoi, B.eugeniephillipsae, B.federicomatarritai, B.frankjoycei, B.gerardovegai, B.germanvegai, B.isidrochaconi, B.jimlewisi, B.josejaramilloi, B.juanjoseoviedoi, B.juliodiazi, B.luzmariaromeroae, B.manuelzumbadoi, B.marialuisariasae, B.mariamartachavarriae, B.mariorivasi, B.melissaespinozae, B.nelsonzamorai, B.nicklaphami, B.ninamasisae, B.oliverwalshi, B.paulamarinae, B.rafamoralesi, B.robertofernandezi, B.rogerblancoi, B.ronaldzunigai, B.sigifredomarini, B.tihisiaboshartae, B.wilberthbrizuelai, Digonogastramontylloydi, D.montywoodi, D.motohasegawai, D.natwheelwrighti, D.nickgrishini. CHELONINAE: Adeliusadrianguadamuzi, A.gauldi Shimbori & Shaw, 2019, A.janzeni Shimbori & Shaw, 2019, Ascogastergloriasihezarae, A.grettelvegae, A.guillermopereirai, A.gustavoecheverrii, A.katyvandusenae, A.luisdiegogomezi, Chelonusalejandrozaldivari, C.gustavogutierrezi, C.gustavoinduni, C.harryramirezi, C.hartmanguidoi, C.hazelcambroneroae, C.iangauldi, C.isidrochaconi, C.janecheverriae, C.jeffmilleri, C.jennyphillipsae, C.jeremydewaardi, C.jessiehillae, C.jesusugaldei, C.jimlewisi, C.jimmilleri, C.jimwhitfieldi, C.johanvalerioi, C.johnburnsi, C.johnnoyesi, C.jorgebaltodanoi, C.jorgehernandezi, C.josealfredohernandezi, C.josefernandeztrianai, C.josehernandezcortesi, C.josemanuelperezi, C.josephinerodriguezae, C.juanmatai, C.junkoshimurae, C.kateperezae, C.luciariosae, C.luzmariaromeroae, C.manuelpereirai, C.manuelzumbadoi, C.marianopereirai, C.maribellealvarezae, C.markmetzi, C.markshawi, C.martajimenezae, C.mayrabonillae, C.meganmiltonae, C.melaniamunozae, C.michaelstroudi, C.michellevanderbankae, C.mingfangi, C.minorcarmonai, C.monikaspringerae, C.moniquegilbertae, C.motohasegawai, C.nataliaivanovae, C.nelsonzamorai, C.normwoodleyi, C.osvaldoespinozai, C.pamelacastilloae, C.paulgoldsteini, C.paulhansoni, C.paulheberti, C.petronariosae, C.ramyamanjunathae, C.randallgarciai, C.rebeccakittelae, C.robertoespinozai, C.robertofernandezi, C.rocioecheverriae, C.rodrigogamezi, C.ronaldzunigai, C.rosibelelizondoae, C.rostermoragai, C.ruthfrancoae, C.scottmilleri, C.scottshawi, C.sergioriosi, C.sigifredomarini, C.stevearonsoni, C.stevestroudi, C.sujeevanratnasinghami, C.sureshnaiki, C.torbjornekremi, C.yeimycedenoae, Leptodrepanaalexisae, L.erasmocoronadoi, L.felipechavarriai, L.freddyquesadai, L.gilbertfuentesi, L.manuelriosi, Phanerotomaalmasolisae, P.alvaroherrerai, P.anacordobae, P.anamariamongeae, P.andydeansi, P.angelagonzalezae, P.angelsolisi, P.barryhammeli, P.bernardoespinozai, P.calixtomoragai, P.carolinacanoae, P.christerhanssoni, P.christhompsoni, P.davesmithi, P.davidduthiei, P.dirksteinkei, P.donquickei, P.duniagarciae, P.duvalierbricenoi, P.eddysanchezi, P.eldarayae, P.eliethcantillanoae, P.jenopappi, Pseudophanerotomaalanflemingi, Ps.albanjimenezi, Ps.alejandromarini, Ps.alexsmithi, Ps.allisonbrownae, Ps.bobrobbinsi. HOMOLOBINAE: Exasticolusjennyphillipsae, E.randallgarciai, E.robertofernandezi, E.sigifredomarini, E.tomlewinsoni. HORMIINAE: Hormiusanamariamongeae, H.angelsolisi, H.anniapicadoae, H.arthurchapmani, H.barryhammeli, H.carmenretanae, H.carloswalkeri, H.cesarsuarezi, H.danbrooksi, H.eddysanchezi, H.erikframstadi, H.georgedavisi, H.grettelvegae, H.gustavoinduni, H.hartmanguidoi, H.hectoraritai, H.hesiquiobenitezi, H.irenecanasae, H.isidrochaconi, H.jaygallegosi, H.jimbeachi, H.jimlewisi, H.joelcracrafti, H.johanvalerioi, H.johnburleyi, H.joncoddingtoni, H.jorgecarvajali, H.juanmatai, H.manuelzumbadoi, H.mercedesfosterae, H.modonnellyae, H.nelsonzamorai, H.pamelacastilloae, H.raycypessi, H.ritacolwellae, H.robcolwelli, H.rogerblancosegurai, H.ronaldzunigai, H.russchapmani, H.virginiaferrisae, H.warrenbrighami, H.willsflowersi. ICHNEUTINAE: Oligoneuruskriskrishtalkai, O.jorgejimenezi, Paroligoneuruselainehoaglandae, P.julianhumphriesi, P.mikeiviei. MACROCENTRINAE: Austrozelejorgecampabadali, A.jorgesoberoni, Dolichozelegravitarsis (Muesebeck, 1938), D.josefernandeztrianai, D.josephinerodriguezae, Hymenochaoniakalevikulli, H.kateperezae, H.katherinebaillieae, H.katherineellisonae, H.katyvandusenae, H.kazumifukunagae, H.keithlangdoni, H.keithwillmotti, H.kenjinishidai, H.kimberleysheldonae, H.krisnorvigae, H.lilianamadrigalae, H.lizlangleyae, Macrocentrusfredsingeri, M.geoffbarnardi, M.gregburtoni, M.gretchendailyae, M.grettelvegae, M.gustavogutierrezi, M.hannahjamesae, M.harisridhari, M.hillaryrosnerae, M.hiroshikidonoi, M.iangauldi, M.jennyphillipsae, M.jesseausubeli, M.jessemaysharkae, M.jimwhitfieldi, M.johnbrowni, M.johnburnsi, M.jonathanfranzeni, M.jonathanrosenbergi, M.jorgebaltodanoi, M.lucianocapelli. ORGILINAE: Orgilusamyrossmanae, O.carrolyoonae, O.christhompsoni, O.christinemcmahonae, O.dianalipscombae, O.ebbenielsoni, O.elizabethpennisiae, O.evertlindquisti, O.genestoermeri, O.jamesriegeri, O.jeanmillerae, O.jeffmilleri, O.jerrypowelli, O.jimtiedjei, O.johnlundbergi, O.johnpipolyi, O.jorgellorentei, O.larryspearsi, O.marlinricei, O.mellissaespinozae, O.mikesmithi, O.normplatnicki, O.peterrauchi, O.richardprimacki, O.sandraberriosae, O.sarahmirandae, O.scottmilleri, O.scottmorii, Stantoniabillalleni, S.brookejarvisae, S.donwilsoni, S.erikabjorstromae, S.garywolfi, S.henrikekmani, S.luismirandai, S.miriamzunzae, S.quentinwheeleri, S.robinkazmierae, S.ruthtifferae. PROTEROPINAE: Hebichneutestricolor Sharkey & Wharton, 1994, Proteropsiangauldi, P.vickifunkae, Michenercharlesi. RHYSIPOLINAE: Pseudorhysipolisluisfonsecai, P. mailyngonzalezaeRhysipolisjulioquirosi. ROGADINAE: Aleiodesadrianaradulovae, A.adrianforsythi, A.agnespeelleae, A.alaneaglei, A.alanflemingi, A.alanhalevii, A.alejandromasisi, A.alessandracallejae, A.alexsmithi, A.alfonsopescadori, A.alisundermieri, A.almasolisae, A.alvarougaldei, A.alvaroumanai, A.angelsolisi, A.annhowdenae, A.bobandersoni, A.carolinagodoyae, A.charlieobrieni, A.davefurthi, A.donwhiteheadi, A.doylemckeyi, A.frankhovorei, A.henryhowdeni, A.inga Shimbori & Shaw, 2020, A.johnchemsaki, A.johnkingsolveri, A.gonodontovorus Shimbori & Shaw, 2020, A.manuelzumbadoi, A.mayrabonillae, A.michelledsouzae, A.mikeiviei, A.normwoodleyi, A.pammitchellae, A.pauljohnsoni, A.rosewarnerae, A.steveashei, A.terryerwini, A.willsflowersi, Bioalfapedroleoni, B.alvarougaldei, B.rodrigogamezi, Choreborogasandydeansi, C.eladiocastroi, C.felipechavarriai, C.frankjoycei, Clinocentrusandywarreni, Cl.angelsolisi, Cystomastaxalexhausmanni, Cy.angelagonzalezae, Cy.ayaigarashiae, Hermosomastaxclavifemorus Quicke sp. nov., Heterogamusdonstonei, Pseudoyeliconesbernsweeneyi, Stiropiusbencrairi, S.berndkerni, S.edgargutierrezi, S.edwilsoni, S.ehakernae, Triraphisbillfreelandi, T.billmclarneyi, T.billripplei, T.bobandersoni, T.bobrobbinsi, T.bradzlotnicki, T.brianbrowni, T.brianlaueri, T.briannestjacquesae, T.camilocamargoi, T.carlosherrerai, T.carolinepalmerae, T.charlesmorrisi, T.chigiybinellae, T.christerhanssoni, T.christhompsoni, T.conniebarlowae, T.craigsimonsi, T.defectus Valerio, 2015, T.danielhubi, T.davidduthiei, T.davidwahli, T.federicomatarritai, T.ferrisjabri, T.mariobozai, T.martindohrni, T.matssegnestami, T.mehrdadhajibabaei, T.ollieflinti, T.tildalauerae, Yeliconesdirksteinkei, Y.markmetzi, Y.monserrathvargasae, Y.tricolor Quicke, 1996. Y.woldai Quicke, 1996. The following new combinations are proposed: Neothlipsissmithi (Ashmead), new combination for Microdussmithi Ashmead, 1894; Neothlipsispygmaeus (Enderlein), new combination for Microduspygmaeus Enderlein, 1920; Neothlipsisunicinctus (Ashmead), new combination for Microdusunicinctus Ashmead, 1894; Therophilusanomalus (Bortoni and Penteado-Dias) new combination for Plesiocoelusanomalus Bortoni and Penteado-Dias, 2015; Aerophilusareolatus (Bortoni and Penteado-Dias) new combination for Plesiocoelusareolatus Bortoni and Penteado-Dias, 2015; Pneumagathiserythrogastra (Cameron) new combination for Agathiserythrogastra Cameron, 1905. Dolichozelecitreitarsis (Enderlein), new combination for Paniscozelecitreitarsis Enderlein, 1920. Dolichozelefuscivertex (Enderlein) new combination for Paniscozelefuscivertex Enderlein, 1920. Finally, Bassusbrooksi Sharkey, 1998 is synonymized with Agathiserythrogastra Cameron, 1905; Paniscozelegriseipes Enderlein, 1920 issynonymized with Dolichozelekoebelei Viereck, 1911; Paniscozelecarinifrons Enderlein, 1920 is synonymized with Dolichozelefuscivertex (Enderlein, 1920); and Paniscozelenigricauda Enderlein,1920 is synonymized with Dolichozelequaestor (Fabricius, 1804). (originally described as Ophionquaestor Fabricius, 1804).

A DNA Barcoding Survey of an Arctic Arthropod Community: Implications for Future Monitoring.

Accurate and cost-effective methods for tracking changes in arthropod communities are needed to develop integrative environmental monitoring programs in the Arctic. To date, even baseline data on their species composition at established ecological monitoring sites are severely lacking. We present the results of a pilot assessment of non-marine arthropod diversity in a middle arctic tundra area near Ikaluktutiak (Cambridge Bay), Victoria Island, Nunavut, undertaken in 2018 using DNA barcodes. A total of 1264 Barcode Index Number (BIN) clusters, used as a proxy for species, were recorded. The efficacy of widely used sampling methods was assessed. Yellow pan traps captured 62% of the entire BIN diversity at the study sites. When complemented with soil and leaf litter sifting, the coverage rose up to 74.6%. Combining community-based data collection with high-throughput DNA barcoding has the potential to overcome many of the logistic, financial, and taxonomic obstacles for large-scale monitoring of the Arctic arthropod fauna.

A reference library for Canadian invertebrates with 1.5 million barcodes, voucher specimens, and DNA samples.

The reliable taxonomic identification of organisms through DNA sequence data requires a well parameterized library of curated reference sequences. However, it is estimated that just 15% of described animal species are represented in public sequence repositories. To begin to address this deficiency, we provide DNA barcodes for 1,500,003 animal specimens collected from 23 terrestrial and aquatic ecozones at sites across Canada, a nation that comprises 7% of the planet's land surface. In total, 14 phyla, 43 classes, 163 orders, 1123 families, 6186 genera, and 64,264 Barcode Index Numbers (BINs; a proxy for species) are represented. Species-level taxonomy was available for 38% of the specimens, but higher proportions were assigned to a genus (69.5%) and a family (99.9%). Voucher specimens and DNA extracts are archived at the Centre for Biodiversity Genomics where they are available for further research. The corresponding sequence and taxonomic data can be accessed through the Barcode of Life Data System, GenBank, the Global Biodiversity Information Facility, and the Global Genome Biodiversity Network Data Portal.

Insect diversity in the Saharo-Arabian region: Revealing a little-studied fauna by DNA barcoding.

Although insects dominate the terrestrial fauna, sampling constraints and the poor taxonomic knowledge of many groups have limited assessments of their diversity. Passive sampling techniques and DNA-based species assignments now make it possible to overcome these barriers. For example, Malaise traps collect specimens with minimal intervention while the Barcode Index Number (BIN) system automates taxonomic assignments. The present study employs Malaise traps and DNA barcoding to extend understanding of insect diversity in one of the least known zoogeographic regions, the Saharo-Arabian. Insects were collected at four sites in three countries (Egypt, Pakistan, Saudi Arabia) by deploying Malaise traps. The collected specimens were analyzed by sequencing 658 bp of cytochrome oxidase I (DNA barcode) and assigning BINs on the Barcode of Life Data Systems. The year-long deployment of a Malaise trap in Pakistan and briefer placements at two Egyptian sites and at one in Saudi Arabia collected 53,092 specimens. They belonged to 17 insect orders with Diptera and Hymenoptera dominating the catch. Barcode sequences were recovered from 44,432 (84%) of the specimens, revealing the occurrence of 3,682 BINs belonging to 254 families. Many of these taxa were uncommon as 25% of the families and 50% of the BINs from Pakistan were only present in one sample. Family and BIN counts varied significantly through the year, but diversity indices did not. Although more than 10,000 specimens were analyzed from each nation, just 2% of BINs were shared by Pakistan and Saudi Arabia, 4% by Egypt and Pakistan, and 7% by Egypt and Saudi Arabia. The present study demonstrates how the BIN system can circumvent the barriers imposed by limited access to taxonomic specialists and by the fact that many insect species in the Saharo-Arabian region are undescribed.

Minimalist revision of Mesochorus Gravenhorst, 1829 (Hymenoptera: Ichneumonidae: Mesochorinae) from Área de Conservación Guanacaste, Costa Rica, with 158 new species and host records for 129 species / Revisión minimalista de Mesochorus Gravenhorst, 1829 (Hymenoptera: Ichneumonidae: Mesochorinae) del Área de Conservación Guanacaste, Costa Rica, con 158 especies nuevas y registros de hospedantes para 129 especies

Introduction: Species of Mesochorus are found worldwide and members of this genus are primarily hyperparasitoids of Ichneumonoidea and Tachinidae. Objectives: To describe species of Costa Rican Mesochorus reared from caterpillars and to a lesser extent Malaise-trapped. Methods: The species are diagnosed by COI mtDNA barcodes, morphological inspection, and host data. A suite of images and host data (plant, caterpillar, and primary parasitoid) are provided for each species. Results: A total of 158 new species of Mesochorus. Sharkey is the taxonomic authority for all. Conclusions: This demonstrates a practical application of DNA barcoding that can be applied to the masses of undescribed neotropical insect species in hyperdiverse groups.

Introducción: Las especies de Mesochorus se encuentran en todo el mundo y los miembros de este género son principalmente hiperparasitoides de las familias Ichneumonoidea y Tachinidae. Objetivos: Describir las especies de Mesochorus costarricenses obtenidas de orugas y en menor medida por trampas Malaise. Métodos: Las especies se diagnosticaron mediante el uso de código de barra molecular por COI del ADNmt, inspección morfológica y datos del huésped. Se proporciona un conjunto de imágenes y datos de los huéspedes (planta, oruga y parasitoide primario) para cada especie. Resultados: Se encontró un total de 158 nuevas especies de Mesochorus. Sharkey es la autoridad taxonómica para todas las especies. Conclusiones: Se demuestra una aplicación práctica del código de barras de ADN que se puede aplicar a grandes cantidades de especies de insectos neotropicales no descritas para grupos hiperdiversos.

Biodiversity inventories in high gear: DNA barcoding facilitates a rapid biotic survey of a temperate nature reserve.

BACKGROUND: Comprehensive biotic surveys, or 'all taxon biodiversity inventories' (ATBI), have traditionally been limited in scale or scope due to the complications surrounding specimen sorting and species identification. To circumvent these issues, several ATBI projects have successfully integrated DNA barcoding into their identification procedures and witnessed acceleration in their surveys and subsequent increase in project scope and scale. The Biodiversity Institute of Ontario partnered with the rare Charitable Research Reserve and delegates of the 6th International Barcode of Life Conference to complete its own rapid, barcode-assisted ATBI of an established land trust in Cambridge, Ontario, Canada. NEW INFORMATION: The existing species inventory for the rare Charitable Research Reserve was rapidly expanded by integrating a DNA barcoding workflow with two surveying strategies - a comprehensive sampling scheme over four months, followed by a one-day bioblitz involving international taxonomic experts. The two surveys resulted in 25,287 and 3,502 specimens barcoded, respectively, as well as 127 human observations. This barcoded material, all vouchered at the Biodiversity Institute of Ontario collection, covers 14 phyla, 29 classes, 117 orders, and 531 families of animals, plants, fungi, and lichens. Overall, the ATBI documented 1,102 new species records for the nature reserve, expanding the existing long-term inventory by 49%. In addition, 2,793 distinct Barcode Index Numbers (BINs) were assigned to genus or higher level taxonomy, and represent additional species that will be added once their taxonomy is resolved. For the 3,502 specimens, the collection, sequence analysis, taxonomic assignment, data release and manuscript submission by 100+ co-authors all occurred in less than one week. This demonstrates the speed at which barcode-assisted inventories can be completed and the utility that barcoding provides in minimizing and guiding valuable taxonomic specialist time. The final product is more than a comprehensive biotic inventory - it is also a rich dataset of fine-scale occurrence and sequence data, all archived and cross-linked in the major biodiversity data repositories. This model of rapid generation and dissemination of essential biodiversity data could be followed to conduct regional assessments of biodiversity status and change, and potentially be employed for evaluating progress towards the Aichi Targets of the Strategic Plan for Biodiversity 2011-2020.

Mammary tumor development is directly inhibited by lifelong n-3 polyunsaturated fatty acids.

INTRODUCTION: Despite the advocacy that diet may be a significant contributor to cancer prevention, there is a lack of direct evidence from epidemiological and experimental studies to substantiate such claims. Experimental studies suggest that n-3 polyunsaturated fatty acids (n-3 PUFA) from marine oils may reduce breast cancer risk, however, findings are equivocal. Thus, in this study, novel transgenic mouse models were employed to provide, for the first time, direct evidence for an anti-cancer role of n-3 PUFA in mammary tumorigenesis. METHODS: fat-1 Mice, which are capable of endogenous n-3 PUFA synthesis, were bred with mouse mammary tumor virus (MMTV)-neu(ndl)-YD5 mice, an aggressive breast cancer model. The resultant offspring, including novel hybrid progeny, were assessed for tumor onset, size and multiplicity as well as n-3 PUFA composition in mammary gland and tumor tissue. A complementary group of MMTV-neu(ndl)-YD5 mice were fed n-3 PUFA in the diet. RESULTS: Mice expressing MMTV-neu(ndl)-YD5 and fat-1 displayed significant (P<.05) reductions in tumor volume (~30%) and multiplicity (~33%), as well as reduced n-6 PUFA and enriched n-3 PUFA in tumor phospholipids relative to MMTV-neu(ndl)-YD5 control mice. The effect observed in hybrid progeny was similarly observed in n-3 PUFA diet fed mice. CONCLUSION: Using complementary genetic and conventional dietary approaches we provide, for the first time, unequivocal experimental evidence that n-3 PUFA is causally linked to tumor prevention.