Recent Changes

Tuesday, May 28

  1. page Gabrielle Nevitt edited ... Another focus of the Nevitt Lab relates to the issue of plastic pollution in the world’s ocean…
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    Another focus of the Nevitt Lab relates to the issue of plastic pollution in the world’s oceans. Plastics represents an anthropogenic-induced shift in the marine biosphere for which organisms need to adapt. Most major marine taxa including birds, sea turtles, marine mammals, and fish have been documented to consume marine plastic debris, mistaking it for food. We are using forensic chemistry techniques, coupled with behavioral experiments, to try and elucidate why tube-nosed seabirds consume so much plastic in the wild.
    Techniques Employed:
    ...
    and survival. The figure to the right depicts genotypic diversity at the DAB1 locus in a Leach's storm petrel colony on Bon Portage Island, Nova Scotia.
    High-resolution GPS tracking allows us to remotely ask and answer questions related to foraging in procellariiform seabirds. By taking a GPS data point every 5-10 seconds (instead of a few times a day using traditional low-resolution GPS) we can infer the track a bird used to approach a prey patch (see figure to right). By examining the way a bird approaches a prey item, we can determine whether it was using primarily visual or olfactory cues to locate prey. Since many of these seabirds are of conservation concern due to bycatch from fishing vessels, how these birds locate prey is an important
    {forgagingapproaches.gif} Taken from Nevitt et al. 2008problem to clarify.
    To answer odor related questions we use Gas Chromatography-Mass Spectrometry (GC-MS). This methodology is often used in forensics to aid in drug detection, explosives investigation, among many other applications. We use this technique to quantify the odors emanating from bird’s feathers and soil in the bird’s burrow and relate that back to its Mhc genotype. We also plan on using this method to quantify the odors arising from marine plastic debris.
    ...
    powerful behavioral assaysbioassays to examine
    Selected Publications:
    Bonadonna, F., & Nevitt, G. A. (2004). Partner-specific odor recognition in an Antarctic seabird. Science, 306(5697), 835.
    (view changes)
    12:33 pm
  2. page Gabrielle Nevitt edited ... Another focus of the Nevitt Lab relates to the issue of plastic pollution in the world’s ocean…
    ...
    Another focus of the Nevitt Lab relates to the issue of plastic pollution in the world’s oceans. Plastics represents an anthropogenic-induced shift in the marine biosphere for which organisms need to adapt. Most major marine taxa including birds, sea turtles, marine mammals, and fish have been documented to consume marine plastic debris, mistaking it for food. We are using forensic chemistry techniques, coupled with behavioral experiments, to try and elucidate why tube-nosed seabirds consume so much plastic in the wild.
    Techniques Employed:
    {Presentation2.jpg}
    Molecular techniques: Using PCR and sanger-based sequencing, we investigate the relationship between individual-specific odors,fitness, and genotypes in seabird colonies. We do this by isolating, amplifying, and sequencing genes of the major histocompatibility complex (MHC). MHC genes have been shown to influence individual-specific odors in other vertebrate species (Yamazaki et al. 1976, Penn 2002, Olsson et al. 2003, Milinski 2006), and are associated with immune function and adaptive selection in response to infectious diseases and pathogens (Penn and Potts, 1999). Consequently, the allelic diversity of MHC genotypes at a seabird colony may offer insights into the behavioral ecology of a population, and also illustrate adaptive responses to environmental forces affecting health and survival. The figure to the right depicts genotypic diversity at the DAB1 locus in a Leach's storm petrel colony on Bon Portage Island, Nova Scotia.
    High-resolution GPS tracking allows us to remotely ask and answer questions related to foraging in procellariiform seabirds. By taking a GPS data point every 5-10 seconds (instead of a few times a day using traditional low-resolution GPS) we can infer the track a bird used to approach a prey patch (see figure to right). By examining the way a bird approaches a prey item, we can determine whether it was using primarily visual or olfactory cues to locate prey. Since many of these seabirds are of conservation concern due to bycatch from fishing vessels, how these birds locate prey is an important
    (view changes)
    12:29 pm
  3. page Gabrielle Nevitt edited ... Techniques Employed: {Presentation2.jpg} ... in response toinfectious to infectious di…
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    Techniques Employed:
    {Presentation2.jpg}
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    in response toinfectiousto infectious diseases and
    ...
    right depicts genotypegenotypic diversity at
    ...
    on Bon PrtagePortage Island, Nova
    High-resolution GPS tracking allows us to remotely ask and answer questions related to foraging in procellariiform seabirds. By taking a GPS data point every 5-10 seconds (instead of a few times a day using traditional low-resolution GPS) we can infer the track a bird used to approach a prey patch (see figure to right). By examining the way a bird approaches a prey item, we can determine whether it was using primarily visual or olfactory cues to locate prey. Since many of these seabirds are of conservation concern due to bycatch from fishing vessels, how these birds locate prey is an important
    {forgagingapproaches.gif} Taken from Nevitt et al. 2008problem to clarify.
    (view changes)
    11:53 am
  4. page Gabrielle Nevitt edited ... Bonadonna, F., & Nevitt, G. A. (2004). Partner-specific odor recognition in an Antarctic s…
    ...
    Bonadonna, F., & Nevitt, G. A. (2004). Partner-specific odor recognition in an Antarctic seabird. Science, 306(5697), 835.
    Cunningham, G. B., & Nevitt, G. A. (2011). Evidence for olfactory learning in procellariiform seabird chicks. Journal of Avian Biology, 42(1), 85–88.
    ...
    211, 1706–13.
    Nevitt, G. A., Losekoot, M., & Weimerskirch, H. (2008). Evidence for olfactory search in wandering albatross, Diomedea exulans. Proceedings of the National Academy of Sciences of the United States of America, 105(12), 4576–81.
    Nevitt, G. A., Reid, K. & Trathan, P. (2004) Testing olfactory foraging strategies in an Antarctic seabird assemblage. Journal of Experimental Biology 207, 3537-3544
    (view changes)
    11:50 am
  5. page Gabrielle Nevitt edited ... Another focus of the Nevitt Lab relates to the issue of plastic pollution in the world’s ocean…
    ...
    Another focus of the Nevitt Lab relates to the issue of plastic pollution in the world’s oceans. Plastics represents an anthropogenic-induced shift in the marine biosphere for which organisms need to adapt. Most major marine taxa including birds, sea turtles, marine mammals, and fish have been documented to consume marine plastic debris, mistaking it for food. We are using forensic chemistry techniques, coupled with behavioral experiments, to try and elucidate why tube-nosed seabirds consume so much plastic in the wild.
    Techniques Employed:
    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loAKKTI9aWgAooooAKKKKAEyPUelGRzyOOKwvE+oXWmWFtJZyWkTy3CRPNeAmOJMEu5wR0VTxkD3pnhrUtQvm1CLUkQNbyKImS3MBZGUEFo2ZivXOCc46gHIAB0NFFFABRSbh6ijI45HNAC0UhIHU0ZGM5GKAFooooAKKTIzjIzRkeo9KAFoopCQOpoAWikyPUUZHHI5oAWkyPUUVyvi3xnpHhmKa3urtY9TNs01tA0TsHPIXJUYGSuOooA6rcOeRx1pa5LRdX1aXXYbHU3sWS5tZLiKKK2eGVUVowrOrSNtDbpMKecKM4O5R1hIHU0ALRSZGM5GKMj1oAWikBB6EGloAKKKKACiiigBCwHUijcOORzWR4oMo8MagLcOX8krtjBLAHhsY77c496yvDX9kf2/eHw0LUad9mj837Ft8nzdzY+7xux1xzjbnHGQDrMj1614b8audE8If9e8v/oMNe1zrcsB9mljjPfzIy/8A7MK4nXPA8fjDSdH/ALQv2gS0g/dLDDgjcqcNknP3R0xQBy/g3jwDoMfTOoW8vlW3Gc3qp51weP7vlovP3d3O391s/HrnwRZ89NRT/wBFyVs6d4H/ALN0ey0u21Irb2lwLr/UYaaVZFdWk2sN+NoXHTGO4Uq/xN4afxhYvpup3qwQ2t0rh4YMFyI/djx+8P5UAeYeCv3/AMLNft/+Pry/tEv2UfKkX7lf30rc5xj92uOXBPO3dH7L4yIPgjXsHP8AxLZ+P+2bVzmn/DqCy8PTaGmpSS2Fw0kjpLED87IqBuCMlQuVyCATuIJCleg1C0vdUgv9IuLmBYri12O6WxBxIHU4y55AHvQB4X8JVB8U3L+XCfJsml824k2wwbXQ+bIMjcq4yF/vBTlcb19v8Etu8Og+ZLLuvbs7502O3+kynLLgbSe4wMHjArnvDnwys/D2qC+tdQeeRV2hbmLcgOVYEqrLkgqCM5AIB6gEdFptjqGlCLTY7+OcSefcGea3O8s0gZshWA5aQ9AMUAfPnw648d6c4+ygReZJ5l5/qotsbt5jf7uNwGRyo+Zeo998G8trxH2oltRB3XnEr5toDuYfw56hcDaCBtXG0c9ofwpsNF1q21O3v5J57Zt6JcwK6ZwQCRkdOowRggHtXSWum3uixXLpqC3T3V3G8j3ELMxdgkZPD4A4BwAAOQAFwAAeC3knk/F+5l8+K3Ka8zefMMpHifO5hkcDqeRx3Fe4+GIynijWH+zzR+bZ2j+ZcH99P89x+8kGBtJxwv8ACoUYXGxccfC21Hig6/8A2pKbz7b9sK+UAnmb9+MZztzxjOfet+HR7nRf7Q1OK7jmupYF895ICTMY97biQw+Y7yOOAAoAAXFAHk3x6/5Hez/7Byf+jJK7Twx8n/CFxn9wXUTeSPneTNpIvnSvzjONsa5GFU+m2O/4t+HMPivVI9Q1HU5I544RCBbwhVwCzdyTnLHvWnYeFHsY9LS1vkCaaxdN9vuMzGPyt0jFskhCQACABgYwqgAHB/tCf8y9/wBvH/tKl8Hf8iN4fjGBnUIJvJtz1/0sL507cZ+7sRefu552/uur8SeDV8cWOmT6lfm38mNnRLeHGN4UsDknOCo9O9T6b4HGn6RY6bbajtt7K5FyP3GGllDBlaQhhuxjb6Yx3VSADF+PWP8AhCLP/sIp/wCi5K47wUfO+F+tQZNx5bTS/ZgNqRfu1/fSnnOMfu1xy4J527o/TvEvhqTxhYvpupXohhtbsOrwQYLkR+pY8fvCPwqlp/w9gsdAm0WLUnksZneV1lhBy7KqhuCOVCgqCCATuIJC4AOj8Zf8iTr4zz/Z0/H/AGzavCPhKv8AxU11J5cR8mzMvm3D7YINro3myDI3BcZC/wB4KcrjevuV/aXuqW19pE91AkM9rsd0t2ziQOpxlzggD3rmvDnwysvD2qi+tL955AuAtzFlMhgwJCsucFVIzkAgEcgEAHReCCf+EbjO+R83V0d8ybHb/SJOWXAwT1IwMHjAr59+HHHjnT3/ANFAiEknmXf+qi2xs3mN67cbgMjlRyv3h9BabY3+kJBpsV/HcK/nTtNLb/OzmTc2drActIegGMVzGhfCmx0TWbbU7e/kuJrdtyJcQK6E4wCQCOR1GDwQDQB0Pgv/AFOrN/pLFtQZt1yMSyfu4/mZf4c9duBtGBhcYHhN3cRWXxfuby4YpBb6400jAE7UWfLHA5PA7V71Yabe6OfLivkuWvroySyzwEsW8vknDjtHgAAAZwBgADnv+FXWqeKP7f8A7Tla7N59s2eUNm/cWxjOcZPr+NAHZ6dq9nqLzR2/nCWIAyJPbSQsAc4O11UkHB/I189/Fc4+KuqHIHzQcnoP3KV7dBpNxoceo6lHexXFxJCHnaWElpTGHIYndwSGx6AAAAABawtf+F9trviCXV7zVZUuZihZIoQEG1QowCSf4R3oA0dGG3xrGuGQy6fLL+AOPmXMkY86Ucbd23ATA2qgHy42Jxv7Qn/Mvf9vH/ALSr0Sy0C4tL1LyO+jkufKeOSWS3J80sVJdvnHPyADGABgAAAYx/Eng1fHFlpk+pX5g8mMuiW8OMbwpIOSc8r2x3oA5bwdx4M8ORcIGvoZvJt+/+kbfOnbj+7sRec7Secfuu78deKv8AhENEi1H7Ebwy3CweUJdnJDHOcH+7jpVXTfBH9m6VYadbajst7OcXAHkYaaQMGVpCGG7AG3HTGO6qQviLw23jPRUstTvlghgu2YeRBhtyb07seCDnp6UAcXZ60PEvhTXr02+PNmef7Er5WIiNB50r4+b7uI1xywJ527o/SfF2uf8ACN+G7zWDbC4+zbP3QfYW3MF64P8Ae9KwLD4exafoD6NFqbvYySNIyvEPmdgq7jggErt4ByM8kEhSNXxDo9z4jsLzQr28jjgljidpYYCG++WwMsf+eY/OgDhdF8T/APCXza5qP2E2/k20X7qSbdBFsEh86V9oztzlU7tz/Dvj9O8Pkf8ACN6UM8m0ix/3wK5Lw/8ADiDQYp4bbVJJoZiHeKeIFS652twRkrnIzkA84yFI6W1hv7H7HpsV1AyJbkB2tmJwm1Rn5+pzQB5pY/EEeL/EmnQ/2VbWQtDJcCe7uPMij2oT5jDaM7cbsZ6qOV+8O+8Fj/RdTYfaSG1CRt9yNsr/ACp8zDjaT124GOmFxgc94f8AhXZaFq8Go22oPcTQ8olzCGTPZiARkgjI54IB6iuksdNvtGIhiv0uWvbkySzTwFm8wpknhwMHZ90AAZ46AUAeFs+z4x3MvmQwiPWpX824H7uMiVjvbkcDr1HTqOo9r8KIF1vWnCTp5iwPvueJpeH+dxgbSey/wjAwuNi46fDC1TxQdf8A7Tdrs3bXexoh5e8sW6ZzgE8c/jW/baTd6JDqF/Fex3E8sYed5oCTKyBjuJ38ZzjHQYAAAAFAE/jTB8G6qHKgeQc7xlfTkelYfhews9O8V+TY2cVnE+ntIEMYjmlBlH72VQBt3HdtTHygYwv3F6PUtOvNS06aymvbdYp12sVtyDj2+eqljoF1Z332xL6N7kxlJJZLckzFipLthxz8oHGAAAoAAFAHRZHqK8qsLG0W50m6+yQJeHU9waGMGXa07AyzS9cEhkRM8gE84/d+g2b6lcWUE/2m1XzY1cL9lb5cjP8Az0rHj8KvFFbRR34jSC6N2QkGPOlLZDOd2Wx0Az0x3VcAEnjrxV/wiGhxaiLI3hluFh8oS7MZDNnOD/d9O9ZnhX4jWGuWElxeWc1hIkoXYsUs6Kh4V2kWPCgsGXn+7VzxH4ak8Z6KllqV6sEMN0zjyLfDFk3p3Y8EEnpVbT/AMen6Eujw6ixs1lM7KYuWclfmYhhu27eOMd8EhSADuMjOM81iaj4m0nTbi5hupJzLaxiWfyrSWYRIQSGZkUheAep7GrELanLNcJ9pth5MgTP2Vvm+VW/56f7VZt74anvLu4mnv0kE4G+DyMJlRhWxuySuSRkkAndjIXABqanqaWPh671WICeOC1e4VQcbwqluPTOK4/wH8Rv+Ev1qawOlGzMds0/mfafM3AMq4xtGPvdfat+7026n01tAe8j+z3NlJA0gtyGCBVT+/jdh89McdKxfCfw6h8J6pLqGnanJJPJC0LLcQgrtJVugI5yo70Ad5ketfNDrE/xfvlmFp5Z1W4Lm8QPCq723F1OAQBk4yOnUda+g521GKa3X7VanzZCmfsrfL8rN/wA9P9n9a5GH4ZWsfio69/aMr3Ruzd+W8A8reWLdM5wCcjnPTmgDR8D2dvYXer29laPa2oeJkSRAjvuQkuyADYWJztwNoIGFxtXxj4u/8lO1f/tj/wCiUr3Kz0m70X7Rcx36XM95LF9oeaElmOQm4/P6Hp0GMAKAAMDxH8LLXxFrlzqt7qsyXFxt3LDCAo2qF4ySei+tAHotefeO/iN/wiGtw2A0r7Z5lsJ9/wBp8vALMuMbTn7n612nl6nzi8tP/AVv/jlcV4g+H8XjS4s9W1LUHt5TaIgit4gFA5buTzlzQB2mj3w1PQ7G/EZjW7t45th52hlDY9+uKvZHrWPpum3mm6XaWMF7A0FrCkKM9sxJVAACcOBnjripLV9SuIi/2q1UiSRADav/AAuy/wDPT2oAqyeKtHjv5bJpp/OgdUlK2crJGWbaNzhdo+YEZzjIPoa3tw9RzXKT+E5JYpIjfqsUl013JHHBgPKWUgthsnG3AByPqQpGxC2pSz3CfabZfJkCZNq3zfKrZ/1n+1j8KANPI9aNw9RVLy9T/wCfu0/8BW/+OVC7akt7Fb/arU743fd9lbjaV4/1nfd+lAGnkeooyPUVS8vUv+fy0x/16t/8cqCZtShnt4/tVsxmkKf8ercfIzZ/1n+z+tAGZ4zOy20x820Zjv0cSXP+qiCq53sOMhcZxkdOo6hnhFQNR1thHcAvNE266/10mYx87D+EnsvG0YGFxtGhf6Tdagbb7Td2/wDo063EY+ynBdc4z8/I5z2OcHPFU7XTLzRRPPHfrcz3k0XnPNASXYlULcP6Hp0GAAFAAoA6bI9aMj1FU/L1P/n7tP8AwFb/AOOVXvG1K3sri4+1Wr+VGz7fszfNhc/89PagBPErEeFdXbcQRZTEHOOiHn2rkfDdjZaf4n0pLKzgszJYTsYxEq3Eikx/vJcAbQzbtqY4APAPyJ11/Y3t9YXNpNe2yx3EbRMy25BAYEcfP71SsvD9xZ3NtcR38RmgSRWd7ckzM+zLOd/JwigYwAOAAAAADN+IHjj/AIQsafjTftv2zzMfv/L2bdv+yc/e/Stnwnro8SeGrPWBbfZvtO/90X3ldrFeuB/d9O9YPibwcPGsNo+pX5g+xyTJGIIdu7L7STuJz9xfz71seHdBuPDuh22lWV9E9tb7tjS25LHcxbkhwOrHtQB0O4eo5oyPWsuF9SlmuE+02wMMgT/j1b5vkVv+en+1+lTmPU+f9MtB/wBurf8AxygBusX40zQ7+/2eaLS3efy843BVLY/SuN8CfEb/AIS/WprA6SbPy7Zp/M+0+ZkBlXGNo/vdfauj1C0vdTt7/SLm6hWKe02O6W7ZxJvU4y55AHvWD4S+HMXhPVJNQ07U5JZ5ITCyzwgrtJVuxHOVHegDvMj1FZWr67p+iop1CWWPcjyfu7eSXCJjcx2K2FGRkngZFLO2pRS26farY+dIUyLVvl+Utn/Weq4/Gqt7ok97qtne3NzbvJZh/KQ27bCzFGyw8zkjYCOwPPUDABpaff2+o2a3NoztGWZPnjaNgykqQVYBgQQfypuralZaPpk1/qM3kWsIBkkKk45AHTk8kCsy0sb/AEPTFgj1CO4DXO5nmt8OzSy5YkqwHVyeAPSrOoabeX9mIJbyAIJY5MrbHOY3Djq/TKj/AOtQBLp+sWWpXM0FuJ1miRXeO4tZICFYkKcSKpIyp59q8T+PGT43suABLk/wDRklesQ6PcaKL3VIbyOe5ktwZmkhOZym5gzEN1O7HHAGAAAABleLfhzD4q1SK/1LVJIpooRAogiCrgFmzySc/Me9AE2kceMNPXOwyWFxNtn/4+Ztzwjzpv7u/bhVx8qpjj7kbviB45Hgr+z/8AiW/bReeZj9/5ezbt/wBk5+9+ladn4fuLO7t7lb+J7iJJFaR7ckzFymXf5+T+7UDGABgAAAAY/ibwcPGsVrJqV8YDZyTJGLeDbuy+0k7if7g/PvQBveEtc/4STwzZ6wLb7N9o3/ui+8rtZl64HXb6d6PFuuf8I34ZvNY+z/afs2z93v2FtzKvXBx97PSofDug3Hh3Q7bSbK+ie3t9wVprZix3MzHOHA6se1Ra3o9z4m0nUNGvruOK3aRFdorchmxskyCWIHPHQ9KAKPw/8cDxr/aH/EtFkbPy+DN5u/du/wBkYxt/Wu0LKMZIGfeuN8HeBx4Q+2DTdS80Xezf9oh3Y2bsYww/vHP0rpbSS7N5NBcSRPsjRw6RFAdxbI5Y/wB0UAXqKKKACiiigBp57HpSc9e/oafRQAVQ1O+TTbFrmSOSUBljEceC7M7BVUZIGSWHU1fqvc20VzCIphlAwbAJHKnIORjkEA/hQBmwa9byTwW8kFxb3ks/lNbTKoaI7HcM3JBUiNgGUsCfoca2Nufr/n69q43Stasde12yaextBq1pMyqIrrfLboYsksNoIGW8tgRw3rXa9yDj6UAc4viy0+xPeXFneW8At2ubdpUT/SUClvkIY87QTtbacc4wDjoQMdiDjpXD69qemQtceG9R060e0SA/ZoJrsrLcEBSqou0kZLFVIJOUI4xXdemSKAMWXXEVU+zafd3crvKoigEasBE+xmyzgY3EYGcncOOuNO3njurSG5hYtDMgkRuRkEAg+30rjfEsmkWHia2/tBfssU6Em5OrzWgyQxbaikK3KLuOQcsuc11umOJNLtJPs/2YNEreQOPK4GFxgdOmMUAZ1/4gitL17YWF9cP5qwI0CoVeUrvCDLAg7fmJOFxn5s8Vo6beJf2UdzGkkYOVZJQAyMDtZTjjIII444rF8QanBoFxbTy2tr5NzcBpri4uPLWNhsjBXKkF9pJx8vyo3PWtPQZIJtJSW1hEUEkkrIA5YMDITvBPJDZ3D2YUAJe6tDZfagYJ5XgEfyIAS5kbairk45IxzgCptMvhqELyeRNbSwyGOSGcLvRhjg4JHIIIIODkVg+L1tNMiTWpLbzpo2TeXvpreEbNzKWC5XOeF3L1ZRnkVq6JeWt/HeXVkEaKS4OJ45N6zHYg3A9OOEwOMoaALk92tvNaxsrFriQxrjHBCFuf++SOKp6ZrMeoSqi2dzAJI/Ot3mCYnjyPmXaSRwynDbT8w464m1qNZNKuWe3knMUbSJHG7I5YA42MvzKe2RzzXO+C7zS55lj01UkkjikWQx6nJerAFkCqqs/3Q4G4Y25CDg4GADq7y7trC0e5vLmG2t0+9LM4RF7DJOB1rOh8T6LdX1vaWWp2l5cXDlUS3uI5GGEZiSAeBhSM/StC7torq1lguFLxuMEZOT9MYI9eK5rSPElvrWo21rLb263sFwSYY7sySQDyTl3G0EEb/LIPAY4yTxQB015cx2dpPdTZEcMbSvgZOFGT+grHh8So94baXTdQgKSJFO8qptgd/uBiHOc5Xldw+YZxzW3PDHc20tvOm+KVSjq38QPBrkf7es7jWptKurS1W5S6hMMIuz50hEhG9k2g5VUEnJYYI5waAOxA5zznHT/69c1J4hv/ALYLW10qOV53lS1ZrzYHERKyF/lJXnGAN2cjOOa6iuE8RNouna2sGpW0EEF6PMe7m1CS3KsfMJEQHTkfPtIJ8wZDZoA7CxulvtPtruMFUuIlkUN1AYA4rNn8R6fb3lxDfLNaQwyiM3cyfuCcAnMgyE+8B8+3OeM1oaW+7SbNhbm2BhT9wesfyjC/h0rI1vWIvDUkDmCBLe6m/fz3FyYlQkovHBBO05C5XhD6GgDfjdJ0SWJleNxuV1OQwI4IP0rPvNVitJ7iMxTO8KRuFjUEv5jMqqMnqWXvgcjnrS6HLBcaVHLaW0UFuzuYlhACMu84YYA4YYbp0bv1rH8cC1g0oXt3aecI35f7dLaKoUFhukTk/MoCg8bmXGDQBuadfC9jkJt5bWWKTZLBNt3Rtw2CVJByCp4J6+tM1PUl037OssFxOJ3KAQJvZQAWJK53NgDooJPYVW8NT2c9lO2nfPbLMVjuPtDT/aPlXL+YxJbBJXkn7uM4GBd1ILFbPerbtPLao0kUalgWO3GMDOSRkdDQAmnarY6qjmwuo5mjOJYwcSRE9nU/MhHPBANTXd0lqsbSBj5kqxDaB1Y4HXtWD4e1211y/R4YbGS7SKVZp7W4E4iAkAVd+0HD4LAHH3Tx0NbmoWMF/aG3uBIU3BgYpmiYEHIwykEdOxoApW+txzal9lFpdRxs7xRXTqvlSumcquG3A/KeoAO047Vd1C6Ww06a7ljklWFC5SPG5vYZOPzOK5Tw3rVleT2enR2kC3NtcOTCt+88sAMZZnfcobO5zG27oxxk12FzbxXVtJBOm+ORcMP7woAzrLXLC8uRZ+aba9Iz9juVMMp6/dVvvKOfmXKnBwa1doHQEe/sO1ck3iW2uNbm0q8s7I3UNzGLeF7gNK37xh5mwplSqr5gxkbTnIrr6AMFvEcKwwzR2d3JE9sl1M6bMW8TZwzgvk8Bs7Qx+X6Z3NvOefx/x/z0rz/VJ9I07xJd21xaCOQxFoIDq00f2kjBWMW/3CjM7KByCQ3y9a9CFAHN6h4gurW+a3h01Jl+0LawsbnYWmZVcAjacJtJO7JPyn5elaul3T31lHO8RgkDNHJEH3BXVijYPGRkHBx+ArnfFv8AZem3kF1fWcLR3TCOa4nvXgSL5kG5RyPNwdwI2ttQ/NxW54c+zNosP2KEQ2oLCIK5cOoc4fceW3DDZPJ3ZyetAFXWtdn0ud1Ww8+CGJGmZZgjgyMyxqqkYOWXB5GMjrir2k3txeRzpdWy29zbS+XKiS+YudqsCGIBI2sD0HcVi+M/sVlZrql1p0N20eVk8+4aGHbtY/PgEN/dXcOGcYIJzV7wu9g9hN/ZY3WYnOyYXLT+eSq7m3kktgkr1PK47UAWNX1eLS2Tzre4nBR5ZDCoPlxJjc5BIyBuHAyT2BpdL1ZdU3qbO5tZFVX8u5VQWjYfKwwSMHBGDgjByBTNekjtLJ9Qa3iuJIU2fvpDGgR2AYuwDYQAZJIOAKp+GdUs9akmvbKKDdJbwebJDN5i7vmPlZAABXv/AL3SgDU1W7ksbEzQwrNJ5iRxxs+xWZ2CjLYOBkjnBrL07Xrm8vUjn03yYHne1MouAxE6KWYBccp8rANnJI+6Ac1s3lpBeWzwTqxR/wC6SpHcEEEEEcEEEEdq4zw1faVc61AkFhbw38TtG0EV+8piXysmR4yBh8kRszDOeNxoA7K/u1sNPubxoyy28TylRwTgZIrEh8QXxvjb3GlJH9nljhvHS73iNpCNmwbRvHzLuJ243cZxXRSwxzwPDMgeKQbXRhwR0IrgrW40ePxB9gawiW+trlBBE2oyPPLmRgXkRhlioXzBuLAKQQQOaAO+xtyccZ5x/P8ALFcoPFV75W86RHt+zfbXxdji14wfu8v975fu/L9/kV13cjrXnmqSaHp+sXGm3GmwKyr5tur6hIktywCbYghHMZJ2qgLIShG0YoA9Bx35z71h33ijS7Ka8hf7ZNLZD98sFjNKFO3dyyoVBx71vduc1x/jiW0t0tjdxpbx3GYJL43P2do0ZlUqCVZX4Ytsb5SEJ6rkAHT2V0l7ax3MazIjjIEsTRt17qwBH5dPrWfd69a6ffSW93BcxxxxrJJciEvEmd2NxXJUDaSWYBR61b0i8F/p0dyqARsWEe1twZQxCsDgZBABB7gg1m+ItQHh+ym1SO2jlkchZnmuDEihVYgltrYOflHHJYAmgDYtrm2vbZLizmiuIX5SSJg6tz1BHB5FU9T1qy0u5t7e6M5nuFcxRwWskzELjcQEViMbl6+tM0K7s76O6uLGKBYHuDia3IK3BwuXyAMnPyk88r1pPEjRx6HNNNaxXEcZRwJJTEE+YDzPMAJTZnduAyAuc0ASaTrNtq0czW8N2ghcxt9ptZIc4JHG8DPT6jvirVzcpBLawsjMbmXyl4HBCs2T+C1heCtQgvtPZbOUTx7VmeYXAlxLIXd0JVVGVPtkgjIFa2tRrJpVy0ltJP5SNIkcbsjlgDjYy/Mp7ZHPNAEOl6ymoTKq2dzAskfnW8k2zbPHkfMu0kjhlOGCnkcdau3t3DYWE95dy7LeCNpJGIzhQMngcnFcr4Lu9KnmWPTUSSSOKRZDFqcl6tuFkCqqs/3VcDcMbchBwcDHZY5Hr6/zoAwovE9hcXttbRQakWuVPls2mzquMqMksg4O4c9B3IrbkYQxs5BwoycD/Oa4ax1GxtvFs1vHFHb3MchihsUuxyJJMPJ5JQFDtQPhSVKsWPJzXdsA6lW5B4IIoAw7HxNpt0YI5i9jcXIBihvU8oy5wQEJ+WTqPuFsZGa3CAeevH/6+a5DVPEFpp93PoN3Y2bQJbf6PBPcZe5ICbUEbKchi20HLHKNxwa7GgDEuNeSOOJ7ewvLuSYyYht1TeFjbazHc4GMkYwcncOOtaltPHc20VxEQ0UqB0bHDAjPT6GuSv7vTPDPiOHzFW3iuUbNzd6nKqruLMwjjbKYyi7tpBG5eORXT6VtOjWW23NsvkJiAnPljaPlOfQcUAQ3uqxWc1xGYpnkgSNwkagmQyMVVRk9Sy98Dkc9cS6ffC9jdjBLbyxSeXLDNt3xtgEAlSQchlPBPX1zWF45Fpb6WLy6tDMI3+ZzfSWgUAFxukTJ+8AFB43MuME1oeG57SeynbTcSWyzbY7g3DT/AGj5Vy/mMSWwSV5J+7jOBgAFjUtS+wNHHFZXN5OwZxFBs3bF+8xLsowNy98nI98JpOrR6rAZVgnt3Kq5hmwGCuPlbKkgggZ4PqOoxVbxVDbNpTXk8DSvb/ddbuS22KzAMWkj+YIBy3UYGecVB4V1Kx1XNzYQQqBawK7W85kjQ/MfKHAAK55wP4xnFAGjq97cWccK2dqlzc3MvlxxySmNThWYktg44U9vSqei65Lqs0ZawNva3MLTWkpmDFlVlVtygfIfmBGC3BOcHirev2sNxpFwbi2kuPJUyRxxSPG5YDgKyfMCenHqevSsHwjeaVfai8mm29olw0cgnNnetPFBtcBVUYCqH5fgLnacg4zQB1sssNvbvPcSJFDGpd3cgKo6kk9h3zWO3izQGaKO21ixuZpZUhSKC6jdyzsFGBnnrn6CtS+khgsp5blSYI42aQBCxZQOflAyfpXPvrelmztLWG21GWIzW6RedZXUaj94gVjI6Y4ODyecYoA6fGM/Xt/nntWCviMm2F3/AGPqI04Df9rIi2CP+/tEm/bjnGzOO1b5wAeM+ox1rgrm48Mrp0t3b2eszwRq0yW/k6gtq2OQNmPLCZHQjb7YoA7wL0I6dOP0rn5/FulReaVXUJvJmMEjw6dO6hw20jcE2nB9D9K6LmuK8VXunWfiG0W98myjl8t3vGu/IMu0s6qVK4kUGNcnOV8wY+8cgHXxSCaCORQ6rIocB1KsARxlTyPcHms651mOAMI7W5uZRcfZo4YlTc7hdxxkgAAAnJI6H2zesZ3urC2uJImheaNXaNjzGSM4P51zPiCax0DV7TVJIAPPn3STXGoSxQox2xkhOUL7GJwQOFbng0AdHpt5He2UdzGjxq+QUcYZGBwVPoQQQe1Utb1eTTGjMVsJ0EMk87NNs2RR43kcHc3zdOPqKn0OeG40tJrWIRxSSSumHLhwXY7wx6h87x7MKqeJYbZdNF7cWqTtasrKGnaFACwB8xl/5ZgfMwIZcLyDigCXRtWuNQMsd3Yi0kCRzIqzCUGOTOMnAw3ynI5HoTV+4ukgubaFwxa4Yqh4wCFLH9BXP+C7rTbqKebSoI0WSOKSRorozqjtuzECeBtwPlGB83QVpa/Yw3GmSSzQXE72qtLElvcSQOzbSMBoyDzyPx6UAGla1HqVyES0urcSRedA86qBPHnG5cMSByvDBT8w461Y1O/GnWvnm3muCZFRY4FXcxY4GMkDqfXpWH4X1ex1Sa1is47ZntLeSIm0vDcLCodVA3YGdwUEZAOFrpJ4I50QTJvCOJB25HIP14oAqafrOn6hLJDb3C/aY1LSW8qtFMg4wWjbDqDweR3FXpGEKM5BIUZOB7frXK6P4kttZ1K3hmsrH+0IZ2GyO4EstspiyXIKKyHJEZ6YJxk11rKHBRsEEYIoAw7HxNp139nim8yyuLkAxQ3qeWZc4wEY/LJ1H3S2MjNbRzwQSCfQZrkdU8QWdhdz6DeWFm8CW3+jwT3Hz3JUJtURspyCW2g5YkoeODXYigBaKKKACiiigAooooAKpXttLc2+yC+ns2B3B7dYyx9sOrDH4fjV2s3Wr2Wx0xp7dEednjiiDsQu93CLuI5xlhn8aAMPSLm8DaJczateXCaluJgka3IX92X52QqWxjBwRg4HNdPNG0kLokjwsykB0wWU+oyCM/UGucs7OXRvEcMt1b6Q8uqM8ZurOxNtLvCmQhss28MFPORyB1zx1BOMnr+FAHG3j6ha22sTNr+pEaYQNrNaL5g8tX/54cZ3bR1yR2rs/auIuHuLjT4fFd7ZaLNFBELlIpLQ+fFCPmGJyxw4HONmM5XP8VdvkZPNAHKywXyand2n/CRakghtVuA7m1UHJcYx5HAG3lvetzR7hrvRrG6dnJmt43JcgtkqCc4AGfXAA9hXPXltd+II5blrXRJre0mkjgt7+zMztsO1iX3AR7ip6I2AAeeg6PTLtNQ0y0vYhtW5hSVQeqhgGxQBj3lte/2/BapruowrcpLINotgsewr8igwkn7/AHOcDvV7w7cPc6RFJJK8zh5E8x2Ri21yuQUVVI44worN1O3utfu72yjh0s2tlKi7NQszdb5SgfIG5QgAcDPJPPTvq6BcC50iB1gjtvLLQ+TFgohjYoQvA+X5eOBx2FAFHWortL+z8vWL63ju7gQiOMW4ji+Rmzl4mJ+5wM9T2qxoUkji/t7i7mu3tbsxedM0ZJ+RGA/dog/iwRgnO4ZNQav9p1XUJNHgTT/IWBZpzfWxuFfcxCqIwyg/6snOT247iTw04SxnsPslpbvYXDW7R2abYSdofKr/AA5D5I7EkZPUgEniJZ49KnvIL+7tfssLylbcRfvMDOCZEfHTqMde9VtOa5t9chtZ9Wub5Z7NpQJWgKqQyA8JEp/i4OcHB44FXNYu7m2W0hsFiFzeXAgR5slE+VmLEAjOAjYGRk45FZ2hWo0bWZNOez0qJ7uAzibT7T7NuCMqkOmWzgyDB3HqeB3ANq9tpbi32QX1xZsDnfbrGX+mHVhjp2/Gue0i5vA2iXM2rXlwmpbiYJGtyF/dl+dkKlsYwcEYOBzW5rV5JY6Y01uiSTl0iiEjELvdwi7iOcbmFY9nZS6P4jhkurbSHl1NnjN1Z2Rtpd4VpCGyzbwwQknI5A654AOhuYZLi3aGO6ltnPSWIIWX/vpWH5g1y8E17DDFdPrV/Kn9o/YzBI9qN373y8nbADn+LGQcd810up3i2GmXd4ylxbwtLsHUhRn+lc21td2Gp2ms6na6JNNPLHDJLBZlJ4jJhBiUsxcAnb0XIOeOlAHYVykkF+mp3VoPEepIILVbgO/2RQclhjHkHAG3luetdVXIXtreeIIprlrbRJoLSaSOC31CzMztsO1iX3AR7ip6I2AAeegAOh0ac3WjWNyzOWmt43JcgtkqCc4AGfXAA9hWTd294dfgtY9d1GFLmOWQbBbbY9pXCKGhJb7/AHOcDvWzpt4moaZaXsQKJcwpKqnqAwDAGsLU7e61+7vbKOHSza2UqLs1CzN1vlKB8gblCABwM8k89O4BpeHrl7rSIpJJnmcPInmOyMW2uy5BRVUjjjCiqmtxXaX9mY9YvreO7uBCI4xbiOL5GbOXiYn7vAz1Par2gXAudIgdYI7byy0PkxYKIY2KELwPl+XjgcdhVLV/tOq6hJo8Caf5CwLNOb62Nwr7mIVRGGUH/Vk5ye3HcAE+hSSOL+2uLua7e1uzF5sxjyfkRv8AlmiD+LBGCc5GSKPEQnj0me9t767tTaQvKUtxDmTAzgmRHx07Y696Z4bcJYT2BtLS3ewna3eOzTbCTtD5Vf4ch8kdiSMnqZ9Yu7q1W0hsVi+0XlwIEebJRPlZixAIzhUPGRk45FAFPTzc2+uw20+q3N+s9m0v71oCq4ZRwEiU87uDnBweOBWre201zb7IL24tGBz5lusZf/dw6sMfh+NYuh239j6zLp0lnpUT3cDTrNYWn2beEKqQ6ZbODICDuPU8Dvq61eyWWmvPbojzl44ohISF3u4RdxHOMsM0AYekXN4G0S5m1a8uE1LcTBI1uQv7svzshUtjGDgjBwOa6W5hkuLd4o7qW2duksQQsvrwysPzBrnrOzl0bxHDJdW+kSS6ozxm5s7E20u8KZCGyzbwwViTkcgdc8b2p3i2GmXd467/ALPC0pQdSAM4H5UAc1BPeQwxXUmt38qf2j9jMEjWo3fvfLydsAOf4sZBx3rqpo2kgdEd4WZSA6YLKfUZBGfqDXLNbXdhqdprOp2uiTTTyxwySwWZSeIyYQYlLMXAJ29FyDnjpXXE4z/KgDjbt9QtbbWJjr+pEaYR8rNaAyfu1f8A59+M7to65I7V2YriLh7i40+HxXe2WizRQRC5SKS0PnxQj5hicscOBzjZjOVz/FXb9/f2oA5u7trz+3oLWPXdRhS5jkkG0W21NhXCKGhJb7/c5wO9XvD1w9zpETyyvM6vKnmSMjFtsjLkFFVSOOMKKzdTt7rX7u9so4dLNrZSouzULM3W+UoHyBuUIAHAzyTz076ugXAudIgdYI7byy0PkxYKIY2KELwPl+XjgcdhQBR1uG8S/szHrF9bR3dwIRHF9nEcXyM2cvExP3OBnqe1WdCkkcX9vcXc129rdmLzZjGSfkRv+WaIP4sEYJzkZIqvq/2nVdQk0eBNP8hYFmnN9bG4V9zEKojDKD/qyc5PbjuJPDbhLCewNpaW72E7W7x2abYSdofKr/DkPkjsSRk9SAN8RLdQwC8g1O7tfnjjMUPkKvzOE3EyRuRgH1xxT9IaeHVtQsZ9Qub3yUhffMYfl378jEcaYPy988EYxzRrMt1JdW2lWa2oa7ilaR7uEyx7FCgrsBXcTvA5I4z16VB4bjFhNf6QbXT4JLfZMTYQeTHIJCwUmPJ2t+7IPJyADnsADWvbaW4t9kF9cWbA5326xl/ph1YY6dvxrntIubwNolzNq15cJqW4mCRrchf3ZfnZCpbGMHBGDgc1ua3ey2OmvNbojzs6RRCRiF3u4RdxHOMsKx7Ozl0bxHDJdW+kSS6ozxm5s7E20u8KZCGyzbwwViTkcgdc8AHRXMMlxbvFHdS2zt0liCFl/BlYfmDXLQT3sUMV1JreoSoNR+xGCRrYbv3vl5O2AH/awCDjvmul1O8Ww0u7vGTf9mhaUoOp2jOB+Vc29tdWGp2ms6na6JNNPLHDJLBZlJ4jIQikSlmLgE7ei5Bzx0oA6maNpIXRJHhZlIDpgsp9RkEZ+oNcleSaha22sTNr+pEaYR8pa0UyfIr/APPDjO7A65I7V2ROM9/auJuHuLjT4fFd7ZaLNFBELlIpLQ+fFCPmGJyxw4HONmM5XP8AFQB24wPpXN3dveHX4LWPXdRhS5SWQBRbBY9hX5FDQkn73c5wO9dJ64rl9Tt7rX7u9so4dLNrZSouzULM3W+UoHyBuUIAHAzyTz07gGl4euHudIieSV5nV5U8xyhLbXZSQUVVI44wo4xVTW4rtL+z8vWL63ju7gQiOMW4ji+Rmzl4mJ+7wM9T2q9oFwLnSIHWCO28stD5MWCiGNihC8D5fl44HHYVS1f7TquoSaPAlgIFgWac31sbhZNzEKoQMoP+rJJye3HcAE+hSSOL+3uLua7e1uzF5szR5PyI2P3aIP4sEYJzkZIqHxEt1Dbi7g1O7tf3kaGKHyFX5nCbiXjcjAPrjin+GnCWM9h9ktLd7C4a3aOzTbCTtD5Vf4ch8kdiSMnqV1mW7ku7bSrRbQNdxStI13EZY/LUKCuwFdxO9RyQMZ69KADSWuINXv7GfULm+MMcLh5jD8u/fkYjjTB+XvngjGOad4jE8WlT3lvf3dqbWGSUpbiLMmBnBMiPjp2x171X8NoLC4vtI+yWEElvsmJ0+DyY5FfcATHk7W/dkHk5ABz2FzWLu6tktIbFYhcXlwII3myUT5WYsQCM4VDxkZOORQBT083VvrkVtNqtzfrPZtKBK0BVSGUcBIlPO7g5wcHjitq5hkuLd4Y7qW2ZuksQQuv4MrD8wawNDtv7H1mXTpLPSonu4GnWawtPs28IVUh0y2cGQEHcep4Hfb1S8Ww0y7vGTf8AZ4Wl2AcnaM/0oA5qCe9ihhupNbv5U/tH7GYJHtRu/e+Xk7YAc/xbcg4711U0bywuqO0LMCA6YyvuMgjP1Brlmtrqw1S01nU7XRZ5p5Y4ZJYLMpPEZCIxiUsxcAnb0XIORj7tdcSQCfyxzQBxt49/a22sTNr+pEaYQNrNaAy/u1f/AJ9+M7to65I7V2fXqK4i4e4uNPh8VXllos0UEQuUie0Jnih+8MTljhwOcBMZyuf4q7fv1FAHKyQ36apd2o8RakghtVuA7/ZVByXGMeRwBt5b3rc0edrrRbG5dnzNbxuTJgtyoJyQAM+uAB6AVz15bXfiCOW5a10Sa3tJpI4Le/szM7bDtYl9wEe4qeiNgAHnoOj0y7TUNMtL2IbVuYUlUHqoYBsUAZWtRXaX9n5esX1vHd3AhEcYtxHF8jNnLxMT9zgZ6ntVjQpJHF/bXF3Ndva3Zi82Yx5PyI3/ACzRB/FgjBOcjJFQav8AadV1CTR4E0/yFgWac31sbhX3MQqiMMoP+rJzk9uO4k8NuEsJ7A2lpbvYTtbvHZpthJ2h8qv8OQ+SOxJGT1IA3xEt3DbreQaleWo3xxmKEQKuWdV3M0kbkYDeuOKfpDTw6tqFjPqFze+SkL75jD8u/fkYjjTB+XvngjGOaNZlupLu20qzS13XcUrSvdxGVBGu0FdgK7id4HLAYz16VB4bjFhPf6R9ksIJLcJMf7Pg8mORXLAEx5O1v3ZB5OQAc9gAWvEQni0ue9gvrq1NrC8pW3EX7zAzgmRHx06jHXvVbTzdW+tw20+q3N+s9m0wErQYUhkHASJTzu4OcHB44q5rF3c2qWkNgsQuLy4ECPNkonyszMQCM4CNgZGTjkVm6Fbf2PrMmnPZaVC93A06zafafZt4RlUh0y2cGQYO49TwO4B0xAwQRx39DXIwX+opqkukyaYggjmiW2VdOkEUcayHJMufLOI1VhjbgkLjIxXT3Vul1bvBK0qK/LNFO0ZH0ZSGH4EVxkL2MF7FAt7cf2smoiP7DJqd3I/leZgMUMpyNnz7iNuKAO7yPUelcjqd/qNpqt7p8WmpLZ3ETmCNNNlkSSRgpHmOp2AMzSA7tuMZJwa6meETQvGxfDqVJVyp/Aggj8CK4XVf7P099Tt5b66jvkKjT7WTV7wvdZRSML5uXy5ZflHBHegDvxXKyw36and2g8RaightVuA7/ZFByWGMeRwBt5bnGa6r155rkLy2u/EEcty1rok1vaTSRwW9/ZmZ22HaxL7gI9xU9EbAAPPQAHQ6PObrRrG6dnJlt43JcgtkqCckADPrgAewrJvLa9/t+C1TXdRhW5SWQbRbBY9hX5FBhJP3+5zgd62NMu01DTLS9iG1bmFJVB6qGAbFYep291r93e2UcOlm1spUXZqFmbrfKUD5A3KEADgZ5J56dwDS8PXMlzpEUkkzzOHlTzJCjFtrsucoqqRxxgCq/iNbqGAXcGp3driSOMxQ+QqfM6puJkjcjGfXHFW/D84udHgdYI7YRloPKiwUQxsUIXgfL8vHA47Cq+sy3Ul1baVZi0zdxStI93EZY/LUKGXYCu4neo5IGM9elABpLTw6tf2NxqFzfeTHC4aYw/Lv35GI40wfl754IxjmneIxPHpU97b391am0hklKWwizJgZwTIj46dvXvVfw2gsLi+0j7JYQSW+yYnT4PJjkV9wBMeTtb92QeTkAHPYXNYu7q2W0hsRCLi8uPIR5gxRPlZixAIzhUbAyMnHIoAp6ebm312G1n1W5v1ns2mxI0GEIZR0SJTzu4OcHB44rVvbaW4t9kF7PZuDnzLdYy/f5cOrDH4fjWLodt/Y+sy6c9npUT3cDTibT7T7NvCMqkOmWzgyDB3HqeB31davJLHTHmt0SSdnSOISMQu93CLuI5xlh+tAGHpNzeK2iXU2rXlwmpBiYJWtyF/dl+dkKlsYwcEYOBzXTzRPJC6JI0LMCA6YyvuMgjP1BrnLOzl0bxHDJdW+kSS6ozxm5s7E20u8KZCGyzbwwViTkcgdc8dQTgH2oA4y8e/tbbWJW1/UiNMIGxmtAZfkV/8An34zuIHXJHau0FcRcPcXGnw+K72y0WaKCIXKRSWh8+KEfMMTljhwOcbMZyuf4q7Y89ifocUAOooooAKKKKACiiigArK1m0uLzT3gt7ezuY5PlmtrzIWVTxjcAduOudrZxjjqNWsvW7a5utMaG0aRJGkjDGJ/LfZvXeAwIwdu7GD+NAGJYNpuk3qzahY6hZXAGxLm+uJLqFQSM7ZSzLGCQPvbCeBjpXT3KzvBILZ40nKnY0sZdAfcAgn8xWF/Z+rWWsadFaTS3GkrM8khmnLSx/upBsJbmRCxUjJJBHORjb0lAHF/2dbWciPqmgXccYk83bYXM13aK+cj9wpBzu+biLGec5rrLa6gvbNLixnjlhkHySIQyn8q52e38XXGjXK/btOiuTFIipFZOrZ5A2v5/GexI4444rqOcZIPSgDj7rS9sssms6NNNFMxNxJpV1L5UvGC0tuGXJbjgCUkZBJwM9Lpt7Z31qHsZFeNDsKBSpjI/gZTyjD+6cEVjppmpw/ab63uZ21EzykQzXDNBLGWO1QvIj+Tb8wAOeu4cHU0NLuLQdPj1DcbtLaNZtzbz5gUbstkg855oAw9Q064N7LdX2lSXOflNxo97JbSuozjzIwyZCjIHzucngDOBsaJdabLaC20rEUdqAhtjE0LwjHyho2AZcgZGRyOaqTaTfT6pfXi3txBMkimzPmloNoQDa8W7BG7dk4Dc8MO1rw6moppKjVUMd40szNH53mbA0rFQG7jaVA4GAMYHSgDP1nTrm4vjPLpovIlBCSWF49rdqp6p95Q67hu5dR/skjm14futLWL7BYRy2kqAyPbXSOkxJPLnfy+WyC4JBPc0X+lXN7rUkjXl5bQJboLZ7ecqqy7m3Fkzh+NnDKRwfWn6DHq6/2idYVBI91mIRuWQxiNBlQfugsGO09Cep6kANes7q9hWGO1s7uDPzwzyvC4YEFXSRckMD04B5zuGOaOkS6Xp94Uls7/AE++uNsedRleUuByqCYu6HkkhA+evFamrnVPs0Z0drfzRIu8zxFwEPBwA6cjg8npkVXs7fW11uGTUL22ntlgkBFtbvCN5ZMZBlbdwGwccc+tAE+tW093YPbwQWVxHJlZra8yqSrjGNwB2kdc7W6Y46jGsW03Sb4TahY6hZXCgxpc31xJdQoCQDtlLOqAkD72wngYrf1b+0BpszaWIjegAxiZCynB5GAy5OM45AzjJrPFr4g/tHT5Lm+s7i1WZjMkFo8DY8t8EkytkbtvGPftQBo6hHcSWTrZrbtL/cuFOxx3U46ZHGcHHoelczb29hpE8T6lpF7aC2/1Ui3Ut3ZwnGMoMnywFJG5o0AGQDjr1l0s7Wsws2jW4KHymmVmUNjjcAQSM9eawXg8UTW1q095ZjMsDzQQ2jRuq+Ypcb/PI6bs8HIBHegDoBIs0AkhkR1dQUcHKnPfjrXJXWl7ZZZNZ0aaWKZiZ5NJupvKlGMF5bcMuSwxwBKSMgk4Gewx7d65xNL1SH7RfQXM7aibiUiGa4YwTRljtULyI/k24YAEEc7hwQDZ029tL21D2MitGp2FFBUxkdVZDyhHQg4IrntQ064N7LdX2lSXOflNxo97JbSuozjzIwyZCjIHzucngDOBuaGl1FoOnRagWN2lrGs2597GQKN2W6HnPNUJdJvp9Tvbtb25gmSRTZnzWaDaEA2vFuww3bsnAbnhh2ALeiXWmy2gttKxFHagIbYxNC8Ix8oaNgGXIGRkcjms7WdOubi+M8umi8hXISSwvHtbpVPVPvKHXcN3LqP9kkc6Hh1NRTSF/tVDHeGaZmj87zNgaVioDdxtKgcDAGMDpVPxBDqiSytYwXd1DcJEhS2uFjaMK5LkFmULuVtu5TuGB9QATeH7nS1hNjp8UtrJHmR7a6R0myTksd/L85y4JBPc0/XrO7vYUiitrS7gz88M8rwurAgq6SrkhgenAPOdwxy/QIrmGzkWaO5jQyEwxXc3nSxpgcM+5s/NuI+Y8EDPGBJq/wDagtozpDW4lEq7jPEXGw8HaA6cjg9egIoAytIl0vT7wpLZ32n31xtjDalI8pcD7qCYu6nkkhA+evFaetWtxd6e8EMFncxyZE1veZCzL0xuAO0jrna3THHUQWdvra63DJf3ttcWwgkBFtbtCA5ZMbgZW3cBsHHHPrVzVv7QGmzNpYiN6oBjEyFlPPIwGXJxnHIGSM0AYNg2m6TerNqFjqFlcKDGlze3El3CgJGdspZljBIA+bYTgDHSug1CO4kspFtFtzLgfJcKdjjoVOOmRxnBxnoelZwtfEA1LT3ur6zuLVJmMyQWjwHHlvgkmVsjdt4x79q1NSgnuNNuoLeUxTSxMkcisRtYjAORyMH0oA5e3t7DSJoX1LSL60FtzDKt1Nd2cJxjKDJ8sBSRuaNABkA469TKz3Foz2E0O90zDK6+ZHz0OAQSD7EVzUcWr3WumaXT9StmE8flyPeIbdYQF8xWjWU7i2HwShPK5Ixx1mOOB270Acb/AGdbWciPqmgXccYk83bYXM13aK+cj9wpBzu+biLGec5rrrS7t7y3S4tJ0mgkGVdGDA/iK5NtB1UWBuFv783i2oZYBfsB9r/icnOCpIX5DlAN2FGa7E5PUDNAHJ6jp1x9tkur7SpLjPym40i9ktpXUdPMj3JkKMgfO5yeAM4GzolxpslmLXSv3UVqAn2cxNE8Qx8oaNgGGQMjI561DcR+In1K4W1urCCyAVojJZvKzf3gSJl5yPTGCOeDVjRYb2LTtmpSia6E0pZ1GAwMjbcAsxA24wM8UAZes6bc3F8Z5tNF5EgwklhePa3aqcZT7yh13fNy6j/ZJHNrw/c6WsJsbCKW0kQGR7a6R0myTkud/L8k5cEgnuaj1jSr/Ub6ZoL26tQsMYhkiuGQKd7eZlRwxKYAJBx1GDzVvRrSe0S7glaZoFuD9nM8xlfZtXqxyT827GSTj8qAKmu6fdXU0bGyivYIjvXyrl7a5hPOfLdSN2703IB3JB4boVxpltI1lFb3NjezMXeO/wB5llYDn96xIlwAPus2AB2qfW9PvL6WFbW5mt1jilKSRTGMJP8AL5ZYA/Mo+b5SCDxkGjRbC5066uYWmuZrUxxFHuLhpmMvzCQjdkqPucdOuAKAJ9atbi8sJILeCyuI5PlmtrvISVTxjcAduOv3WzjHHUY1g2m6TfLLqNjqFjcqCiXF9cSXUKAkZ2ylmWMMQPvbCcAY6Vv6pFcSWbC0LeYskb7Q5TeFcMy57ZAI984PFYejw6q+src3NnqVoxllaY3N4jwvEc7EWNZGCsPkOQq8K3JJ5AN3UI7iSydbNbdpf7lwp2OO6nHTI4zg49D0rmre3sNImhfUtIvrQW3MMq3U13ZwnGMoMnywFJG5o0AGQDjr0espdPo92tirtcmI+WEfYxPoGyMHpzmseO11O6vW1Ro7+1uBdRrFbSXKhBBhQ+5EdkPWQ5OWzt9KAN6RnubMvYTQ73TMUrr5kfPfggkfQiuU/s62s5EfVNAu44xJ5u2wuZru0V85H7hSDnd83EWM85zXXzKxhcRg79p2/XHGPSsCz03W7GztzbakZ2EaebaagfMG7AyFlX5hzu5bzO2MUAb1pdW97bJc2s8c0DjKujBgfxFcxqGn3BvZLq90uS5z8puNHvZLeV0GceZGGTIUZA+dz6AZwOr5PauevNFvb/UppWvbu3jNwgIiu3RXt9gLIoU/K3mDJYYbHGcHFAF7RLnTJLMW2lYiitQENuYmieEY+UNGwDDPbI5696ztZ065nvzPLpovYk4SSwu3tbpVPVPvKrru+bl1H+ySOdXRobqDTEivDI0iM6r5jh38vedm5ucnZtyfXqT1qhrGlX+oX0rW97dWgWGMQyRTsgU728zKjhiUwASDjqMHmgCTw/c6YsJsbCOS1kjBke2uUdJjk5Lnfy/Ocvkgnuaj12wurueNjZRXtvEd6+VcvbXMRGc+W64DFvTcgGOSQeLejWk9mt3bytO0Czk25mnMz+XtUnLHJPzFsZJOPyqLV9Ol1DULRDNdw2axy+Z9luDEfMO0ISQQSMbuORkjIoAg0O40y3keyjgurK9mcu8V9vaWVgOf3rE+bhQPus2AAKsa9Z3d7CkUVraXcGfminleFwwOVdJVyQwI44B5zuXHMekQ6zDq98NSkE1usMUdvKsgPmkGQsxTgI2GQHAwccYHAsa7bajc2cY0i/8Asc6ybmO1P3i4Py7mRwvJBztJ4oAzNIm0uwvCktnfaffXG2MNqMrylwD8qCYu6nknCB89eK29QjuZLKQWYt2mP8Nwp2P6qcdMjIzg4z0PSsjw1FqH2q/mvb3VXUSBI7e+jhXHyJkjy0AOOR8pK9ep5rduluGs5haNGtwUIiaVSy7scbgCDjPvQByltb2GkXEL6jpF7afZj+6kW5lvLOE4xlBk+WApI3NGgAyAcdeod3uLPzLCeHc6ZhmZfNj56HgjI+hFYj2/iia2tWnvLP5pYHnggtGjdVEilxv88jpnPByAR3royuQdvBI9Py60Acb/AGdbWciPqmgXccYk83bYXM13aK+cj9wpBzu+biLGec5rrLa6gvbNLixnjlhkHySIQyn8q5EWPiGO/sbW81vVZHM/zXVtDbiFl2tkkCLKHIHDEjkYLHgdqMntz2NAHHXemBJZZNa0eaWOZiZ5NKupfKlHQtJbhlJLccASkjIJOBnpdOvbO9tBJZSI0akJtAKmMj+FkOChHTBwRWG3h+7uLh5bi9v442kn86GG+dPMG4+Tt2kbAFPQbckjduxW5pf2kaVaC+wbwQqJiD/Hgbunv6UAY2tadczXxuJ9NF3CoIjksLx7S6VT1T7yq67hu5dR/skjm34eudLEX2DT4pbWVAZHtrlHSY5PLnfy/wAxILgkE9zVfVU1WXUZ7W2trz7LdeQPtMM0aLEoc+b/ABhwSvdVzz1HUaGkWs9nFdW8kk0kKTn7O00plfyyoOCxOT8xbGSTgCgClrthc3c8ZNjDe28XzqIrl7a5hPOTG4xuLdMbkAxySDwmh3GmW8j2UcF1ZXszl2ivt7SysBz+9YnzcKB91mwMCptb0+8vpYltbma3WOKUpJFMYwk+V8ssAfmUfN8pBBzyDRothc6ddXMLT3M1qY4ijXFw0zGX5hIRuyVH3OOnXAFADtes7u8hSKO1tLqDOWinleFwwIKukq5IYHpwDzncMc0dIl0zT7wpJZX+n39ztjB1GR5WcD7qLMXdTySQgfPXirfieya9sbcfYBqEEc++W0LKvmrsYD7xA4YqeT/DkcgVneF9HvdO1LN1Z+VItuy3d4Jt322QsCrdSx2jcPmAxuwMigDoNWuns9HvruFPNkt4HkWP1ZVJA/SsEzXthHpl5/wkD6kt5PFD5TwxeXMJCMtFsUMMDLcs2FBznrXQ3sM81qVtbpraYEFH2BxkHOCD1B6HBB9COtc9bWb6LeNdv4bsJ5CTvvdKhRJTnli0bfMB3wruSR07UAdUW4JGPb3ri/t+ojwwPEY1x2fZ5rWXlReSWJ/1HC79/RAd+d3b+GusdTdWREMs1u0iZWRUw6574cHn2Irnf7NuLK/GoT6Bpep3Wd32yygWC43EY+65IPufMHB6UAdQ+4qQmA/QEjODXIXWmBZZZNZ0eaaOZj58mk3UvlS8YLS2wZSSwxwBKSMgk4GertLgXVtHOiSorDOJY2jYfVWGRXJatZ+IIZ2Q6vqkkE9yhhayih2xIZB8jqYy4AU/eywO07gvAIB0+m3tpe2gkspFaNDsKKpUxkfwsp5Qjupwa5/UNPuDey3V9pclzn5TcaPeyW0rqM48yMMmQoyB87nPQDOB08KtHDGjSvMwUKZH25YjHJAAGT14AH0rlvE1rr0X2+e31PUWtHibyYbGKHfAwTAyDGXcEg8qdwyABjJABtaJc6bJaC10rEUVqAv2YxNE8Ix8oaNgGGRyMjnrVTXbC5u5o2NjFe20fzr5Vy9tcxHnJjcYDFvTcgGOSQeNaxhlhsoopbqW5dQd0s4Xeee+0KOOnA/PrWZr1rq0xhm0u+mhjh3edBCsW+bOPutIjAEYOBgA7vvCgCPQp9Mt5Hso7e6sr2Zi7xXwdpZSAAf3rE+bgAfdZsDAqxrtnd30KxQ21pdwZBeKaV4XVgcq6SrkggjjgHnO4Y5h8LxXi2M0t5eX9y8k77EvUVGRVdgOAinkYPcdMcVY1mS9hlsZ7K0uLyNJGM0UEiJkFCATvZQRkjjNAGfpEul6febJbO+0++uSsYbUpHlLgZKoJi7qerEIHz14rT1m1uLyweC3t7K4jkyJra7yFlXpjcAduOudrZxjjqKehaffWVzbSzz3UpuLTN4s9yZQJ8qflBJCdXBC/L09BV7Wvta2Mb2ME08iTxM0cLKrOoYFgNzAdPU0AYdi2m6TerNqNjqFjcKDGlzfXEl1CoJGdspZljDED72wnAGOldPcLO0Di1eOOcj920qF1B9wCCfzFYWm2OoreW2oym8jmnnm+0W81zuRIjvKDYGZAwxGMpzy2ScmugnVmglWPIcqQCPXFAHH/wBnW1nIj6poF3HGJPN22FzNd2ivnI/cKQc7vm4ixnnOa622u4by2S5spknhkGVeMhgfxzWFZ6brdjZ25tdTM7BF8201A+YN2BkLKvzDndy3mdsYrowA33gD9aAHUUUUAFFFFABRRRQAVUv9RstNtxPqN7BaRFtokmkVFz6ZNW6hd0jjdpHCKFyzk42j6n8aAOH8L2ujW+qx29h4j0e5jErTQWlosayM3lbMsQ53nYCThRk88Diu6lmigheWaRI40BZndgAoHUknpXH+Gyt5cadbW19o1xaaQDiWxvPOklypRdyAAJkfMfmbLL+Ndjjr9DxigDz7Uf8AhHLzW7i+t/FWhQi8iMNxvaJ5mUhVYLIJBgYQYyGwSTyCAPQ+p+lcXqbR3Gp6no9pqGjyS6m4EqS3uLmEiNUIWIA7iAu4fMuCT9a7T2oA4TWrnQb7WrbU7XxToNteQLszctHMQMMMAiRSoIdsjoeOODnr9Mjgh0q0jtZvOt44EEUm/fvQDhge+Rjn3rn9cvUtNekFve6M95d2yW7WuoX3ksvLFdqhWLBt5yMDOBye3Q6Zamw0u0szIZDbwrFvII3bQBnGT6etAHLeKptBv7u23eItFtb7T5eBdtHL5ZDKx+XepVsoBkHoWHcY3/D6266RCbO9hvY2LuZ4CCjsWJbbjIA3E8c46ZPWs/xJewabqdjeG+0uK4iSRBBqN8LcOrFSWU7WOQVA6HgnpWlodm9lpUMM7xs7FpGEOdgLMW2rnkqN2B6jHA6UAYvjKTQtQs30zUNb0qzuIzuEd40b7SUK5MZYHOGyCCMEA9Mg6Pho28tjcTWuqWmpNNPumntMCMPtUbQoZsYVV4JPXPemeKLi3tY7G5mvbC2lt7jzYkvrkQJKdjIRuweQHznB5Aqbw7HKbSe8kltnN/ObgLaSGSJVICja5xuyFyTgAknjuQCTXrvS4LCW11bUoLCO7jeNWluFiLZGCVLEcjP8qwfCMOnR3his9e0i+MMchittNRYxGskgZiVEjZGdoHQAeua6LW1gk0O+ju7lLWGSBkeZ22rGGGCSSR61leHppNUvxqXnaS8VvAbZf7MujcBmJVvmOFC4wMLg/ePPqAbt/qFjp0Am1G8gtIS20STyqik+mSa4vwva6NbarHb6f4j0e5jEjTQWtosays3lbMsVc7jsBLYUZPPTiu4kdI43aRwiKpJZjjaPXJ/HmuR8N4vLjT7a1vtGuLXSA2JbG8M0kgKlE3IAAmR8x+Zssv40AdbdXdtZWz3F5cRW8CfeklcIq/UniuGtI9BfxDI9n4n0Vory5jle3j8rz5ZBIZFG8Pyd7Y+7kqAvvXek9R0P8q4y0eO91H+yrPUNGuYY7/7a0sV75l0MSbypiA4IPybt33e3agDtq4PWrjQb3WbfU7XxVoNteW67M3LRzkDDDAIkUgEO2R0Py8cHPeVyWuXsdpr0gt73RnvLu2S3a11C98ll5YrtUKxIbecjAJwOfQA6HS44IdKtIrWbzrdIEWKQPv3oBwwI65GDXK+Kp9Bv7q2LeItFtb7T5cqLt45fLIZWPy71KtlAMg9Cw7jHU6Zamw0u0szIZGt4Vj3kEbtoAzjJPb1rG8R3sGm6nY3hvtLiuYkkjEGo3otwysVJZThuQUA6dCelAGh4fW3XR4TZ3sF9GzO5ngIKOxYsxXGQBuJ45I6ZPWsfxk+hX9o2l6hrel2VxGd4S8aN9pKEZMbMOcNkEEYIB6ZB2dEs3stJhhneNnJaRhDnYCzFtq9yo3YHqMcDpVTxRcW9pHY3Mt7p9vLb3PmxJfXIgjlOxkI3YPID5zg9BQA/w2beWynmt9Us9SaafdNNZ48oPtUbVUM2MKq8Enrnvip9eu9KgsJbbVtRgsY7xHjDTXCxFsjB27iORmo/DscptZ7yWW2c385uAtpIZIlUqFG1zjdkLknABJJx3NjW1gk0K+ju7hLSGSB0ed22rHuGMk8cc+ooA53whDp0d2YrTXtIvzDHJ5Vvp0axiNZJA7ZUSNxkKB0AHrmupv8AULHT7fztRvLe0hLbRJPKqLn0yaw/D00mqX41LztJeK3gNsv9mXRuAzEq3zHChcYGFwfvHn16GR0jjdpHCIqklmONo9cn8eaAOH8L2ujW+qxwWHiPR7mMStNBaWixrIzeVsyxVzuOwEnCjJ54HFdvdXdtZWz3F5cRW8CfeklcIq/UniuS8OYvLjT7a1vtGuLXSA2JbG886SQFSi70AATI+Y/M2WX8a7E9+ADQBwVnHoL+IHktPE2itFeXMcr28flGeWQSGRRvD/Md7Y+7kqAvvXeSzRQxPLNIkcaKWZ3YAKB1JPYVx1o6X2pHSrPUdGuYY783rSxXvmXIxJvIMQHBB+Tdu+727V2RXIORxjpQB59qP/CO3mt3F9b+KtDhF5EYbgO0TyspCqwWQSDHCDGQ20ljyCAPQ89x0ri9TeO41PU9HtNR0eSTU3CypLe4uYSEVCFiAO4gLuHzLg/nXaZ+mKAOK8Uz6DqF1blvEWiWt9YSnAu2jl2EMrH5d6lXygGQehb1GOg8Prbro8JtL2C+jZndp4CCjsWLNtwSANxPGSR0yetZ3iO+g03U7G8N9pcVxEkkYg1G9FuHVipLKdrHIKAdDwT0rS0Ozey0mGKdo2clpGEOdgLOzbVzyVG7A9RjgdKAMbxk+hahaNpmoa5pVncRneEvHjfaSpXJjZhzhsg5GCFPIyDpeGjby2VxPbanZ6k8026aa0x5Qfaq7QAzY+UL1J6574qPxRcW9pHY3E19YW8tvc+bEl9ciCOX5GQjdg8gPnOD0FS+HY5Taz3kkls5v5zcBbSQyRKpAUbXON2QuScAEseO5AIvE1zo32N9P1XVrCzeUK6pdyJtbDZw0bEbkJXBGeRkZB5qt4Njso4HW01qw1R4YYrcmy2qscaBtgIDvyctyT9AMVe8T+QNEkNzeWtqqvE6veShIiyMGCMT2JXB68E9elQ+HTJeTXmrPLYNHdCONBYXJnjIQt85cgZbLEHjoq8nsAa1/qNlpsAn1C9gtIS20STSKi59MmuM8MWujW+qx2+n+I9HuYxKZoLS0WNZWbytmWIc7vkBLYUZPJ44ruHdI0dpHCIqkl2ONo9efxrkfDZF7cafa219o1xa6OGAlsbszSygqyLuQABMj5j8zfMv40AdbdXdtZWz3F5cRW8CfeklcIq/UniuGtI9Bk8QPJaeJtFaK8uY5Xt4zF58siyGRR5gk+Y7mx90kqAvvXe5+gOPyrjbN477UTpVlqGjXMMd/wDbWlivfMuQBJvIMQHHOE3bvu9u1AHYyzRQxPLNIkcaKWZ3YAKB1JPYV5/qX/COXmt3F9b+KtDhF5EYrne0TzMpCqwWQSDHCDGQ2CWPcAeglcg5HGOlcbqbx3Gp6no9pqOjySaowEqS3uLmE+WqkLEAd2Au4fMvJ/GgDtP157VxXiqfQdQurbd4i0W1vrCX5RdvHL5ZDKfu71KtlAMg9Cw7jHa+uMVzXiS9g03U7G8N9pcVxEkiCDUb4W4dWKksp2scgqB0PBPSgDQ0BbZdIhNpew3sbM7meDBR2LlmK4JAG4njJx0yTzWP4yk0LULRtM1DW9Ks7iM7wl40b7SVK5MbMMnDZByMEA8jIOzodnJZaVDFM8bSMzSHySdgLOzbVJ52jdge2OB0qp4ouLe0jsbia+sLeW3ufNiS+uRBHL8jIRuweQHznB6CgCTw0beWyuJ7bU7PUnmm3TTWmPKD7VXaAGbHyhepPXPfFR+JrnRjZvp2q6tYWbyBXVLyRNrYYH5o2I3ISMEZ5GeQeam8OxyG1nvJJLZzfTm4AtJDJEqkBRtc43Z25JwASx47lPE/kDRJDc3lraqrxOr3koSIsjBgjE9iVwevBPXpQBR8Gx2UUDraa1Yao8MMVuTZbVWONAwQEB35OW5J/DitPXrvS7ewktdX1G3sY7xGjDSzrEWyMEruPbP8qqeHS95Nd6s8unsl0EjQWFyZ4yE3ZcuQuWySDx0Qcntf1tYJNDvo7u5S0hkgZHmdtqxhhgkkkevtQBzvhCLTorwxWevaRftDHJ5VvpqLGI1kkDsdqyNxkKB0wPXNdbdXdtZ2z3F5cRW8CfeklcIq/UngVz/h6WTVL8aj52ktFbwG2X+zLo3CsxKsdx2qFxgYXB+8efXpMjHvjv2/zigDgrSLQW8QvJZ+J9FaK8uY5Ht4/LM8rrIXUeYJPmO5sfcyQAue9d5LNFBC8s0iRxoCzO7ABQOpJPSuNs2jvtS/sqy1HRrmGO/N60kV75lyMSbyDEBwQfk3bvu9u1dnjrx26CgDz7Uf+EdvNbuL638VaHEL2IxXAZonmZSFUhZBINvCDGQ2CWPcAeh9fcVxepvHcapqej2eoaPI+qOFkWW9xcwnYqELEAd2AoYcr/Wu0xkc0AcJrVzoF9rNtqdp4q0G3u7ddm65McxAwwwD5ikAh2yOh44GDnsNLjgh0u0itJvOt0gQRyb929QOGyOuRg5rntcvUtNekFve6M95d2yW7WuoX3ksvLFdqhWJDFzkcZwOfToNMtTYaXaWZkMht4Vi8wgjdtAGcZJ7dM0Ac94yk0PULNtM1DXNKs7iI7hHeNG+wlSMmNmGThiQQRghTyMg6Xho28tlcT22p2epPNNummtMeUH2qu0AM2PlC9Seue+Kj8UXEFnHY3E17YW8tvc+bEl/ciBJfkZSN2DyA+c4PQVN4djkNrPeSSWzm+nNwBaSGSJVICja5xuztyTgAljx3IBD4mudG+xvp2q6tYWbyBXWO8kTawDA8oxG5CRgjPIyAQeareDY7KOCRbTWrDVHhhigJstqrHGgYICA78nLc5/AYq94n8gaJIbm8tbVVeJ1e8lCRFkYMEYnsSuD14J69Kh8O77ya71Z5bBkuljjQWFyZ4yE3ZcuQuWyxB46IvJ7AFvXrvSrewlttW1KCxjvI3jDTXCxE5GCVLEcjIrB8IQ6dFdmK017SL8wxyeVb6cixiNZJA7EqsjZGQoHTA9c10WtrBLoV9Fd3KWkMsDI8zsFWMMMEkkj1rK8PzPqmoDUvO0loreA2y/2Zdm4VmJVvmOFC4wMLg/ePPqAb11FLNaSxwTmCWRCqTKAxQkcEAgg/iK5dbZ7kRQzeLGubq0ubc3VqZbYojCRTtO2JWBJU4HGSPrXUXdxHaWzzSJMyL1EULyt6fdUEn8BXG21xoMuuCaLUNZEct0qC1fT5Eg84SFwpYwggh2ZsFu/pxQB3Rz0zg1wMvh/Ro1mtzdaamrQWIJRpceTKMFrrHUMTtJfGTtAyK7mZxDC8jI7KqliEQuTj0AGSfauH1K78P3N/cXUl9rdtGo2XcCabMI23BAd+6Esu5VQcFeAMYJJIB3vcVwmtXGg3us2+p2virQba8t12ZuWjnIGGGARIpAIdsjofl44Oe7PfPQ1yeuXsdpr0gt73RnvLu2S3a11C98ll5YrtUKxO4ucjAJwOfQA6HTEgh0q0jtpvOt0gQRy79+9AOGz3yMGuV8Uz6Df3dtu8RaLa32nynAu2jk2EMrfd3qVfMYGQehYdxjqtMtTYaXaWZkMht4Vi3kEbtoAzjJ9PWsXxJewabqdjeNfaXFcRJIiwajfC3DK5UllO1jkFAOnQnpQBoeH1t10eE2l5BexszuZ4MFHYsWYrgkAbieMkjpknmqvie40b7FJp+q6tYWbyqrql3KmGw2eY2I3ISuCM8jPIPNW9Ds3s9JihnaNpCWkbySdgLOzbVzztG7A9gOB0qLxP5C6JJ9pvLW1VZI3V7yUJEWRwwRmPYlcHrwT16UAUPBsdnHBILTWrDVHhhigJstqrHGgbYCA78nLc5/AYrT1670qCwlttW1KCwjvEeNWluFiLZGCVLEcjI6VU8Ol7yW81Z5bB47pY40FhcmePCbsuXIGWJYg8cBF5Pa/rawSaFfR3dylpDJAyPM7bVj3DBJJI459qAOd8Iw6dHdmK017SL4wpJ5VtpqLGI1kkDNlRI2RkKB0AHrmupv9RstNt/P1G8gtId20STSqgJ9MmsPw9NJql+NS87SXit4DbL/Zl0bgMxKt8xwoXGBhcH7x59ehd0jR2kcIiqSXY42j15/GgDh/DFro1vqsdvp/iPR7mMSmaC0tFjWVm8rZliHO75AS2FGTyeOK7qWaKCF5ZpEjjQFmd2ACgdSSelcf4bIvLjTra2vtGuLXRwwWWwuzNLKCrIu5AAEyPmPLZZePWuxxwePwoA8+1H/hHbzW7i+t/FWhwreRGG5DtE8zKQqkLIJBjhBjIbBLHkEAeh5ri9TaO41PU9HtNQ0eSXU3AlSW9xcwkRqhCxAHcQF3D5lwSfrXaCgBaKKKACiiigAooooAKyvEFjLqGjT28EUcjlkbypThJQrKxRjg8HBHQ9a1aKAOcUXupa9p93Jo82nLZiQyTXDxM7hlx5a+WzHGfmOSOVXg546I5wRz9aWigDiTp+pt4XXw5/YeJFXyxfGSIwA5z5/Xfuz82Nn3u/8AFXanvwaWigDkzb39lBqVh/wj51EXc80gmWSERSiQnAlDMGGBhThW4UYz0rf0q2ls9ItLW4k86SGBI5H/AL7BQCefUg/nV2igDnGW+0zWdSnj0WXUY74owmt5Ig4CoF2OJGXgEEjBP3m4He74esZtO0OG2mSOORS7COLlYwzFginAyFB25wOnStaigDBvY7yz8QnUoNMe/jktlgxC8ayxEMzHG8qCrZXOG6qOD1D/AA9ZXNtb3clxbi1N3dPOtsrA+SCBwdvGSQWOM8seT1O3RQBja/aTzpZTW9qt0bO6WdrdmA80bWHy543AkMM45XqOtQWEN5d+Izqk2mvp8aWpgKzGIyzEsGBOxmAVQCB83V24HfoKKAMrxDYy6ho09tBFHI5ZG8qU4SUKwYo3B4OMHg9TVFVvdT17T7uTR5tOWz3tJNcPEzuGXHlr5bscZIY5I+4ODnjo6KAKWrWsl5pF5ZwSCOSeB40c/wADFSAePQ1gvDf36aZaDQH08Wc8UhmaSFooVjxlYtrFvmA2DKr8rHp0PV0UAFcmbe/srfUrA+HzqIu55ZBMskIilEhOBKGYMMAhThW+VRjPQdZRQBT0q2ltNJtLW4k82WGFI3f++wUAnn1IP51kMt9pms6nPHosmoR3zIyy27xBgFQL5bCR14GCQQTyzcDv0dFAGV4dsZtO0WG2nSON1Lt5cRysQZiwRTjkKDtzgdOlVr2K8s/EJ1OHTX1BJLZYMQvGssRDMxxvKja2Vz83VRweo3qKAMXw9Z3Ntb3clxbram7unnW2VlPkggcHHGSQWOM8seT1K6/aTzx2U1vai7NndLO1uzAeaArD5Sfl3AkMM45XqOtbNFAHP2EN5d+Izqk+nPp8aWpgKzNG0sxLAgnYzAKoBA+bq7cDvb8Q2MuoaNPbQRRyOWRvKlOElCsGKNweDjB4PU1q0UAc4q3up69p93Jo82nJZh2kmuHiZ3DLgRr5bsduTuOccqvB7a2rWsl5pF5ZwuI5J4HjSTnCMVIB/A1dooA5N4b+/j0y0/sBtPFnPFIZneFooljxlYtrFvmA2DKr8rHp0PVEZBA/WnUUAcS2n6m3hhfDv9hkSBREL7zIWgDZz5/J37s/PjZ97v8AxV2vfvS0UAc4VvtM1nUp49Gl1GO9KMJbeSIMAqBdjCRl4yCQQT948Dve8O2M2naLDbTpHG6l28uI5WIMxYIpxyFB25wOnStWigDBvYryz8QnU4dNfUEktlgxC8ayxEMzHG8qNrZXPzdVHB6h/h6yuba3u5Li3Fr9runnW2VgfJBAGDt4ySCxxnljyep26KAMPWbe6XVNP1K3sjfi1WVDCjIsgL7cOm7AyApXlhw569CaLbXR1PUtRuLH7Al35arbsylyU3AyPtJXcQVHBPCDnsNyigDK8Q2M2oaPNbwRRSOWRxFKcJKFcMUbg4BxjoetUVW91LXtPu5NHm09bMSGSa4eFncMuPLXy3Y4zhjkjlV4Pbo6KAKWrWsl5pF5Zwv5clxA8aP/AHGKkA/gawHhv7+PTLT+wW08Wc8UhmaSFooljxlYtrFvmA2DKr8rHp0PWUUAIe+OD61xTafqbeGF8O/2GRIFEQvvMhaANnPn8nfuz8+Nn3u/8VdtRQAneucK3umaxqc0eiy6hHelGWa3eJXAVAvlsJGXgYJBBP3m4HfpKKAMrw9Yz6fosNtOkcbqXby4jlYgzFginjIUHaDgdOlVr2O8s/EJ1KHTW1BJLZYMQPGssRDMxxvKgq2Vzhuqjg9RvUUAYvh6yuLe3u5Li3Fp9runnW2VlPkggcHHGSQWOM8seT1LNYt7tdU0/U7eyN+LVZEMCsiyAvtw6bsDIAZfvDhj16HdooAw9Et7o6pqWoz2JsFu/LVbdmVnJXcDI+wldxBUcE8IMnsH6/azzx2M1vai7NndLO1uxA80BWHy7uNwLBhkjlRyOtbNFAHP2EN5d+Izqk+nPp8aWpgKzNG0sxLAgnYzAKoBA+bq7cDvp6tayXukXlnA4ikngeNJD/AxUgHj0NXaKAOUeG/v00y0/sBtPFnPFIZnkhaKJY8ZWLaxb5gNnKr8rHp0PVc0tFAHFNYam3hdfDn9hkSBREL7zYjADnPn8tv3Z+fGz73f+Ku07/1paKAOT+z39nb6lYHQP7QW7nmkE6yQ+VKJCcCUMwYYBCnCt8qjGeg6DSraWz0mztbiTzZYYUjd/wC+QoBPPqc1cooAwb2K8svEJ1OHTW1BJLZYMQPGssRDMxxvKja2Vz83VRweok8PWVxb293JcW4tPtd0862ysp8kEDg44ySCxxnljyep2qKAMLWLe7XVNP1K3sjfi1WRDArIsgL7cOm7AyApXlhwx69Cui290dT1LUZ7L+z1u/LVbdmVnJXcDI+wldxBUcE8IMnsNyigDG1+1nnSymt7UXZs7pZ2t2IHmgKw+XPy7gSGGccqOR1qCwhvLvxEdUn019PjS1MBEzRNLMSwYE7GYBVAIHzdXbgd+gooAbJIkaM8jqiqMszHAA9TXFWs9rd31vaQ6oyaZNd/aoIptLliMrB/OCpO+EYbgWAAyVzz3rrNTsxqGmXVk7lVuYWiLDqAwIyPzrGay16/+yW+oR6fDBBNHK89vM7PLsIYAIUGzLKpPzNgZHPUAHSVw+oXVld3V7Bb6x9n0/UZRHdO+mytGzYEbBLjiMZChed3P5V2zDIIPSuVOka2dD/4R/Fh9hEYtxeiR/NEXTPlbcb8cZ39fmx/DQB1feuUNvfWVvqVh/wj51AXk8snnLLCIpRISQJQzBhgEKcK3yqMZ6Dq+/8AWloApaVbS2ekWlrcSedJDAkcj/32CgE8+pB/OsllvdM1nUp49Fl1GO+KMJrd4gwCoF2OJGXgYJBBPLNwO/R0UAZXh6xn0/RYbadI45FLt5cZysQZiwRTgZCg7c4HTpVfWLe6XVNP1K3sTfC1WRDAjIsgL7fnTdgZGGX7w4c9eh3aKAMPRbe5OqalqNxY/YEu/LVbdmVnJTdmR9hK7iCo4J4QZPYP1+1nnjsZoLUXZs7pZ2t2IHmgKw+XdxuBIYZI5UcjrWzRQBz9hDeXfiM6pPpz6fGlqYCszRtLMSwIJ2MwCqAQPm6u3A72/EFjLqGjT28EUcjlkbypThJQrKxRjg8HBHQ9a1aKAOcVb3Ute0+7k0ebT1sxIZJrh4Wdwy48tfLdjjOGOSOVXg9uiOcHBOaWigDiW0/U28ML4d/sMiQKIhfeZC0AbOfP5O/dn58bPvd/4q7Ru3BP0OKdRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFJkeopar3ccktnPHC+2V42VGI6H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width="471" height="334" align="right"]]
    Molecular
    {Presentation2.jpg}
    Molecular
    techniques: Using
    ...
    and survival. The figure to the right depicts genotype diversity at the DAB1 locus in a Leach's storm petrel colony on Bon Prtage Island, Nova Scotia.
    High-resolution GPS tracking allows us to remotely ask and answer questions related to foraging in procellariiform seabirds. By taking a GPS data point every 5-10 seconds (instead of a few times a day using traditional low-resolution GPS) we can infer the track a bird used to approach a prey patch (see figure to right). By examining the way a bird approaches a prey item, we can determine whether it was using primarily visual or olfactory cues to locate prey. Since many of these seabirds are of conservation concern due to bycatch from fishing vessels, how these birds locate prey is an important
    {forgagingapproaches.gif} Taken from Nevitt et al. 2008problem to clarify.
    (view changes)
    11:48 am
  6. 11:42 am
  7. page Gabrielle Nevitt edited ... Another focus of the Nevitt Lab relates to the issue of plastic pollution in the world’s ocean…
    ...
    Another focus of the Nevitt Lab relates to the issue of plastic pollution in the world’s oceans. Plastics represents an anthropogenic-induced shift in the marine biosphere for which organisms need to adapt. Most major marine taxa including birds, sea turtles, marine mammals, and fish have been documented to consume marine plastic debris, mistaking it for food. We are using forensic chemistry techniques, coupled with behavioral experiments, to try and elucidate why tube-nosed seabirds consume so much plastic in the wild.
    Techniques Employed:
    Molecular 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width="471" height="334" align="right"]]
    Molecular techniques: Using PCR and sanger-based sequencing, we investigate the relationship between individual-specific odors,fitness, and genotypes in seabird colonies. We do this by isolating, amplifying, and sequencing genes of the major histocompatibility complex (MHC). MHC genes have been shown to influence individual-specific odors in other vertebrate species (Yamazaki et al. 1976, Penn 2002, Olsson et al. 2003, Milinski 2006), and are associated with immune function and adaptive selection in response toinfectious diseases and pathogens (Penn and Potts, 1999). Consequently, the allelic diversity of MHC genotypes at a seabird colony may offer insights into the behavioral ecology of a population, and also illustrate adaptive responses to environmental forces affecting health and survival.

    High-resolution GPS tracking allows us to remotely ask and answer questions related to foraging in procellariiform seabirds. By taking a GPS data point every 5-10 seconds (instead of a few times a day using traditional low-resolution GPS) we can infer the track a bird used to approach a prey patch (see figure to right). By examining the way a bird approaches a prey item, we can determine whether it was using primarily visual or olfactory cues to locate prey. Since many of these seabirds are of conservation concern due to bycatch from fishing vessels, how these birds locate prey is an important
    {forgagingapproaches.gif} Taken from Nevitt et al. 2008problem to clarify.
    ...
    Nevitt, G. A., Losekoot, M., & Weimerskirch, H. (2008). Evidence for olfactory search in wandering albatross, Diomedea exulans. Proceedings of the National Academy of Sciences of the United States of America, 105(12), 4576–81.
    Nevitt, G. A., Reid, K. & Trathan, P. (2004) Testing olfactory foraging strategies in an Antarctic seabird assemblage. Journal of Experimental Biology 207, 3537-3544
    ...
    seabirds. Nature, 376,376//, 680–682.
    Current Lab Members:
    Gabrielle Nevitt (P.I.)
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    11:40 am

Sunday, May 26

  1. page Louis Botsford edited ... White, J. W., Botsford, L. W., Baskett, M. L., Barnett, L. A. K., Barr, R. J. and Hastings, A.…
    ...
    White, J. W., Botsford, L. W., Baskett, M. L., Barnett, L. A. K., Barr, R. J. and Hastings, A. 2011. Linking models with monitoring data for assessing performance of no-take marine reserves. Frontiers in Ecology and the Environment 9: 390-399.
    O'Farrell, M. R. and L. W. Botsford. 2006. Estimating the status of nearshore rockfish (Sebastes spp.) with length frequency data. Ecological Applications 16: 977-986.
    ...
    16: 2248-2263.
    Kaplan, D. M. and Botsford, L. W. 2005. Effects of variability in spacing of coastal marine reserves on fisheries yield and sustainability. Canadian Journal of Fisheries and Aquatic Sciences 62: 905-912.
    ...
    13: S25-S31.
    Botsford, L. W., Hastings, A. and Gaines, S. D. 2001. Dependence of sustainability on the configuration of marine reserves and larval dispersal distance. Ecology Letters 4: 144-150.
    Links
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    12:49 pm
  2. page Louis Botsford edited Research Interests Loo’s laboratory primarily uses population models to investigate aspects of th…
    Research Interests
    Loo’s laboratory primarily uses population models to investigate aspects of the population dynamics of marine species. His research aims generally focus on the application of population dynamics to fisheries conservation biology and the impact of management tools such as marine protected areas (MPAs). The underlying principles of reserve design are investigated in the context of predicting the sustainability of populations. Loo is also interested in the consequences of movement, such as larval transport and dispersal, on population structure and yield. Additionally, he works on how environmental variables influence population dynamics, and how environmental fluctuations may impact the sustainability of marine populations.
    Study Systems
    Loo’s work focuses chiefly on a diverse array of different marine populations. These range from invertebrates such as urchin, crab and planktonic species, to commercially important fish species such as rockfishes and Pacific salmon species.
    Techniques
    Various types of population models are used in concert with existing data sets on survival, growth rates, age, size, structure and spatial distributions of a population to answer questions about population dynamics or predict the effects of MPA design. Some models also include aspects of behavior, such as movement rates or dispersal, as well as various aspects about environmental conditions or habitat changes to better inform predictions.
    Selected Publications
    White, J. W., Botsford, L. W., Baskett, M. L., Barnett, L. A. K., Barr, R. J. and Hastings, A. 2011. Linking models with monitoring data for assessing performance of no-take marine reserves. Frontiers in Ecology and the Environment 9: 390-399.
    O'Farrell, M. R. and L. W. Botsford. 2006. Estimating the status of nearshore rockfish (Sebastes spp.) with length frequency data. Ecological Applications 16: 977-986.
    Kaplan, D.M., Botsford L. W. and Jorgensen, S. 2006 Dispersal per recruit: an efficient method for assessing sustainability in marine reserve networks. Ecological Applications 16: 2248-2263.
    Kaplan, D. M. and Botsford, L. W. 2005. Effects of variability in spacing of coastal marine reserves on fisheries yield and sustainability. Canadian Journal of Fisheries and Aquatic Sciences 62: 905-912.
    Botsford, L. W., Micheli, F. and Hastings, A. 2003. Principles for the design of marine reserves. Ecological Applications 13: S25-S31.
    Botsford, L. W., Hastings, A. and Gaines, S. D. 2001. Dependence of sustainability on the configuration of marine reserves and larval dispersal distance. Ecology Letters 4: 144-150.
    Links
    http://meep.ucdavis.edu/researchers/botsford.html
    http://wfcb.ucdavis.edu/people/faculty/botsford.php

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    12:47 pm

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