20230207 16245900 1.0 TRUE TRUE DominantForestHost Provides a discrete dataset showing the FIA species code and text description for most prevalent species based on basal area for each pixel. These data were derived from source data developed for the 2013-2027 National Insect and Disease Forest Risk Assessment (Krist et. al. 2014; https://www.fs.fed.us/foresthealth/applied-sciences/mapping-reporting/gis-spatial-analysis/national-risk-maps.shtml) and the National Individual Tree Species Atlas (Ellenwood et. al, 2015; https://www.fs.fed.us/foresthealth/applied-sciences/mapping-reporting/remote-sensing). basal area stocking forest parameters host maps cubist host model FHTET modeled Dominant basal area species. 240 meter pixel resolution. Data represents forest conditions circa 2002. The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly. /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3+iii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooqvcXMNnA01zMkUSAlnkYKoAGSST7AmgCxRVT 7ba/aRb/AGmLziQPL3DdyGI469Ef/vk+hqrJ4g0eOR0k1exRoxlw1wgK/XnjqKFrsNJvZGrRWV/b mlGGWYanZmGEK0r/AGhcRhvuljngHtnrV+GaO4hSaF1kjdQyOjZDA8ggjqKBE1FFFABRRRQAUU1m CqWYgADJJ7Ux5EQZZgBkDJ9ScAfnQBLRTSwA5IA6c1FC7ywo7xPCzAExuQWUnscEjI9iRQBPRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAGPrd1eafpcl5Z28Vz JCN7wSSiIOvf94xwmPvZOeAR3yPPvF2u3WveAptShsUiVJTHHcRs7gxtGyykF0TaCG2cg5bIAyFN epTmYQOYFR5QpKK7FVLY4BIBwM98H6GvIb1LU6Vpku+Kzt5IBNhomRTK5f8AeyQNG0ZOwEhQVJwy ozBVxSaPRwEYN3a1T/zuvw+6/lba8J6Jb3mr6jOuprcW8TBFjtLmRPKYqP8AVmNwBEVVFAIONm3J 2bml1bwU93Z5vbpBFbz3EgZ7k7I4XO4yfMhO/AGQSQdpbcGYtXV+G7Q2XhvT4DcLcFYEHmKQVI2j 7pAHygYA9gO9Ok1+xi1OexlmjRoIlklleRAilgxCHLZ3bUZsY+6M5qU3umQ8TU9q/Z7L/hvxv+J4 34ft4FvbvS9Va0tpY5RFI88wBkKhswsxJCxYRhuUblcxEZ2jHbfD69uIJbjTZ7WO1hif7L5aqiBZ 4o1DncAPMZ/nY4JKhOeCDXI6tYx6deWtijl/t1r5UsbnzLqMF90augG4OIxCAgKqWUc4Bz3MjW0u lT3avZNqDOJbGa6YDzkMpmgQEsrAfLtCkryp4IXJutK23U7cbCnL34r4vu7X+9fh2bR3lJkZxnn0 rlLfR4NM1eE2iRo7EqfKG14ImO8JtCsuwtGwz8nfBLsS3QwqkKx26tuMajG9yz46ZOeT069+axcj yJwUdmW6ikcJGzEEgAk7QSfwA5NAkVyQhDY689OMipAc1SknsZi0UUUwM7UfnsZ4hcNCZIyvmLjc gPBIB7jP544PSuI8nWY7m3iW6jWKUm2iRL1rdHj8slVSER5jOcNnJYKpAJWu1vkL6ZOl2ks6sTuF qGRthbjGG3ZC4ztOTg4GSFrD1qGeXTLudIJpNRtChh8qXy/Mbdw5AYExcnKscHa2OzHObtqL3Npd Nf6/4Bc07VZ21G40mZWuJbQoj3KDAfKAksMABuQSBx8wxzkDa810gMkwjj25LfP8oGeuSB25/wA5 rir7W7rRob2GG0wkYa55k2LEwDSMGIAZy2FcqByWk+YgEinrGp308EserS27QGcyLBbLIxAi++v3 CrYyrHflcqQQMgrHtlrcylXir2W39f1uehwzLLCsihwrqGAdCpAPqCAQfY81PXF2+sa+Q1vBbQXc sbyAzSfuvMOyRlQJ0UhggILFsckc5Gp4fuddmjkj1u1ghmB3BoCdgHAAGScnIYnpjIGO9bJ3NlfZ rb+v6sdBRRRTAKKKKACiiuc8SzM8EOnxySxS3RL+YmCESPDMWHUqeARjBztJXdmplJRV2TKXKrs6 Oiue8OyWRhmSy2xhW3G3z80ILN8pGTjDiRcDgFSv8PHQ0QlzRuVr1CiiiqAKKKKACiiigAooooAK KKKACiiigCnqFx9j065uAjuYo2k2xjLNgE4HvXmfiK8l1mfwxp0dxJPZ3bmSXyvM8iWMyAiL5QCx QKVyQCOGO3Jx2/i66Fn4U1GU+Ww8rYRKrFWDELtO0gjOcZyMZz2rzDwtau3ijSvssNp5dmJEnmhl 813PlEksO6h22hgu3oNzcEt+7CU1ukz1cBTSpSr9Y3t/4C/80erXbubWSLMq24CKZYZxv+9tcEnl QO7A7vvYwQM49h4ZElhNi+uIrlp5ZFnj+RssymRGZVQupkjzuG1iuACBW9bXEM5e3xKWjA3B0YKR 1GGI2n3wTjoa0WO1ScE4GcDqawpOTXNc8+M5U9I6PQ8t1cagnit4FlQWsey3mllXzfKiJQE5dTuY RszM75VRMVyCRu7Wws3s4haxGWd4YJEiuiqCIDd8sZjVlBKgKOFA4PIJIq5faXZahhr2ESooOUdi EYHH3lzhsYBG4HBGRg1Zt4RbWkNsZZZfLjC+ZKdzNgAZY9yf15rRRVkrbGtXEKcIpK1t/wDh/wBP +HOUuGvrL7KbwMNR8pIrmawtBPMY8gb4ywGFDAF1CPjeMAcMd9QbuziurGZoHmWGQHIlBQNuK4DF csCwLA9wcnArMNgdV1iG+ba8VoXAlYo3myBztGzYdvlncA2Q6ncCCCS27amZ1LzweVLudfvA7lDE K3HqMNjtux60o22X9XOeo3zeX9beX4hbhDbo6wvb+Z8zREAFS2Sc7cjOWJJB696dbs21kaPByTuV NqnJyOCc555981PvGQBznPQZHFOx82cnGMY7UuXW6JIoYhEhVS5Bdn+dyxySSeSTxk8DoBgDAAqe oWyWTDMADk4xzx0P5549KVGLA5RkwSMNjn34PeruBLTWBIwCRz1FRGVVuFhIfc6lgQpK4BAOWxgH kYBOTzjocMSIx3EzAHY5D5MrMd2MEBTwowF6dSScZ5LA4/Xbayl0ySCC1t7h1SPZbyWknmyIoCqN +4MSpLEnOQMg4wxJa+HHutLt4rZpNPeNyJLU3Lu1upGxlRizYO1nKsNoIK5XoV6S5t5LnUI8iIxi MqRIgOVbO/HOc8IOgA3H73QQWGmPZ20j2ksiyvCBFHcZKREKAu5QcseFySc8YBA4GHK+bXY5vZLm 2/T+tySbOk6HO8McayRRkoNrMuQMLu6sQAFBPoO3Qc5Daw22uteSatL5t+0SR+d+7LzKqna4AXBx /BkZ5BHSullihsdDt4LiaZ0iEMXmXDB5HbcqqWP8TFsZxySeOcVlvd6bo8EU1qjeWs32RriGF5UC hxhCA2XOT5akbtrsRgfMtE25PV2Np3lK7OrorPsUmSW8MsRjBnyh89pA67F5AP3BnI2jA4z3pL3U bexUea4MsgYwwjl5SBkhQMk/gO9bX0uU2kaNcHrnjuG3321kSszR5EzR7jGxIG0p1DY3cNgggBgO aafGxvLXyFlttPvhFL57E/aBBIkTOQAmQ3GxweQQHH3lxXIvfadbQ3bRSTPDNbOZJDcySSXLOFKf aAEAjw7qpKnq+0ElXxjUlKSTgYVJyl7sP69DqbjxBf8A9l6eIb+5a6uIFWK4igjMM0+XUZO1iAdr O3yjAQfcJKnPTVPEmoNPbWCve20zOsNxcRowZYvMBXGFDLIUwWzhRIoOSc1kSae9lqy+H/ten2ap DbLPdBQ3lnl3h/upllml2kYIbBIX5T6homm29hbFrcybJQCiuSoROSqqhxsABA2gDAAHas/elNL+ v6/ruatWai91+PXb+vyMvSfDs1hfeYnkxQxSDarwK7yELtEhlzksVZx0XGcYIGW66iiumMeVF3b3 YUUUVQBRRRQAUUUUAFFFFABRRRQAUUUUAYXim6gtPCmrT3LqsS2kgbdznKkAYyuSSQAMjJOMivO9 CudQ0uCCDTLWJpVvYre5WJN7xjapfO4goWZZQzMpGBgMAiV61dW0N7aTWtwgkhmRo5EboykYIP4G uM8G6ZJBY3thqKRx3CnymSGCSIIMEExSMcsjFS4Ixhix9KmTZ1UaqhTknqtNOnX8TqdOlSe1RoGV oMDYykEEYBGMDBHPXvV/HzA5OMdK43wzJPZyG3mjnO9iZ5pT1dUiRWBP3g6jdkEgEHk8V1ckjI68 AhsgAdScE/Tt3xWFGaULXvY55pX0d0PaQghQMlvTHHv16dPzp+QpCk8noD3rNuGuHj82zRGkdk3Z BGVDgOM8HO3dt6DPWrEs+yB3CyO6AkxxY3MR/CM4HPbOM1aqJ63BK5h6TryTW8xlf7VdRTeVK1vG M7TIQDtB3BFyeT2UnrkV0glVoi43YGf4Tnj261i2sMkbTz2SsweQ5ikwiMS/zuAFyD1787QTyxYs v7u+gtjDaQtLNym6Dy0WAHgMVduQv45x0AIqFVaaX9f1/VxKNl6f15lm31WB5IxJcoDdufssZ+Ri FUBgMn58EE5AwQwxnqdmuFuPEd1YxR3UNopgS5mSVVXfKYYmlErhMqF5jTk9N4GDgbu6rWnzW94S Ta5uj/4H+Y1jtUkAsQOg6mgHJPBGD+dOorQCNE2DaNoUcKAMYGOlUpyszxRtG7FJVZo/kPGTtZgT 0yAwxzlR6EVPLJJGrOdxT5flRMsOefqMY7Z6/g37UFtzLJ5Q2xB2CyAjoe5wMccE4z7VLaWhL1K7 yyvCxt0kSVyYkeSHn2Yjj5Vy3BxnHHUEyWsplVkjVtigFZmAxITk5GMA9jkcHd6ggZt9LJb292mn wxxSBVWNAnlt5h+SN85wV3Kq4IHC9xgG4bgwW8Mr2pit0YLsCAmMHAV+o2qASGGOOewyYW+5CnqS y3aWwETIRKscksccauwKJgfwr1+ZflwTzwDiqsKJZWNlOkV18sccAhUNIwDsgBZnHmYXnJOMDcSM gYzrjVb60D3dvFZ3FrNcJN5kUof/AEfaoLZwoBxsYEswAY5IVQams9etNWkRXt9ts481Tc44dTGV AA3KxBZTnIwSoALBtpzRBVE5cuxdudQcalJpsCr9o+zrKjBgSMuVJZCVyo6/KScBh8p27uD1VbnV ZJYxebLu1xYxTWLbluBIpIjl3lmxvTbl8g7u2S1as+uvqhupooZo0j3CEPwSu0A5+YgZYFe3Dofm ziqV5rE/9o3NrCJ5PPMkTw5AMUm7MUirt3CTIJzyD8uCMBV55V1KVui/E5K1VS1T/r+vvKV7bXW4 3F1qsgSVEKXEI80Blfy/k8xi2E8zerAbmO7kbl3suLIf8JlaW1wb4GWItFHFKGkkUSYDOTtMQLHd uK5JUkEuc102nWkFlPbyy2pivZLgEv5aKVACx+X8vzFRuyowAAQTkAk6SWUF9eMGSPZnzMhHilAL fMpUkMFZ03Z6MFxj5QTCUpL3f6/r/glRpQdrr+vMxoPAjSahDe3N+p8pwwiW1EZxtxjejAkqpCq3 bGAMcV2Nvbm2ml2svlSNuWNUC7WJJYk9ySf0+pq7RXZGnGOx1QpRht+v6hRRRWhoFFFFABRRRQAU UUUAFFFFABRRRQAUUUUAFUbudLcxs0EkpG4r5cZdgwUnjAwMgMMkjkgdWFXqrzwJPEySDKn8x3BB 7EHkHtSYmZGp2JDJdxLLmEtKqRBcbsEnjYzfNkgsuX/u9TWrE4niEnyOrqPmUggjH45HJqVA4jAc hnwMlRgE+w5xVe03vCWlBVmkY4DcY3HGD6EAH3z+FZONpK3mO+iRNKgZG6njGAcZ9vxrMmgmkt3h f7RCQygzpIA7EDIYEdgeMMACQcjb97ZxzmqErwssiOu9Rl2wu48EYIHOSCOnXI6VFWKTUupcZNCx RXEdoI3laaXaFd5NvPYtgADnrjgVhatZ6hFEVs4d9u7nzo4T5cmzaScP1+ZwuSo3AFto3YrokHmR JJj94B1x37j9MVHE4TbFICxctzgEE556duT1rN8vMpP+v6v+Qulkctpd7dRaaZdSuJlu4boWkzvI m996/uztClFYmWM4U8ADc7bStdorBgOxwDg9RXPvpd0L21MN0i20Nw7sscOxypj2qhYHBC5/u8hV HUEnoFBA5OTmuiMryehOvX+vvH00EkkEEYPBPem+YnmbNy78Z255x9KYW/fKu05wecHgcd8Y9OPr 6Vpe+wDdzF1yrcMVOOg7gnOCew4zyfbIz9Sklt4HkWdI2wFSSSPGwsTnL5CgcL1HbkMSBReTuYSw gvZBl1KIwjwQflJIIYAleCMjDZbjkY97ZtPC8sV3AjSq8kKeWHaTPzMqsMFlyWABHO45B4rnq1LK xlOTs7GdcTDTbl7OG5V4ZA8TQW7SJggkDltxDFtwwOOATwTXQw3V3Ja2b2qT+RKQ5keFP3UaAZUo CCd4DYK5wWXjFRafpwh1FJppFZocosittJJPCsBkYIdWGTuJ5Oez76Xz7cQF3uYZGdZIy4R5AXGF GABt+ZACTyrc5JzWNO0U5PQzgnG7b+Rn6hEb2S3gtoL+JI3PlRwR4jAXKK25iEUbdzLsIPKngqMx eJr2IWclykkSyqiysI2R5TBhQyY5OSJH5UEdDnoDJZIwsF3TWq2wzbzQ3EDSZ2yEvgcBXbdwhUk4 U84xWbZxf2JG1/aQO/mnbFawu3lNECm534XdtU4BKg8sWLcEJy0u+pnzWs++/wAvIyGuLmaGUJNd OpxHGhLyxPOAw2DacgkbUwGyB83AzWx4d024sNOWWSRm+eI+ZHKznJj2k7S2ScMqnHzdQuMgi/Zp JfXUTXEd0qxsqG28sxeXubO4AYONy4yckqSematTaZbT3UTSQjZbyM9uqRj924cDgt0yFC7RgHf3 BG3GOiT/AK7CjT5nz/8AA/r+vmzT2dBG9y0a2KlAvnkjC4UJld5XklMHB53Hg9eoihSFSI1RQWZs KuBkkkn6kkk+pqksTRSp8mV2BNzOxGPURjgcsQTxgY7cDRRQqhRngY5OT+dduHi4po64R5dB9FFF dJYUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAEUiLLGUdQyMCGBGQR6GlIJJ+bAI4wOQ f84oooaAcDkA+vrQyhlwRkHtRRSWq1AzLiKdJIxbMEJYH52OD1JAHc8d8evOMVLIZlXlMsxyqhgF z23HHHb16d+5RXJKko3tpqNO5K1wq3McBYB3DMqg8kDGT9AWH5irdFFdUd2NrRFad0R487tznYpU ZxkZ/p/kZqqbmdVkKwmbBwuzIx1BznsGB+7k4I49SisXJ8zREm9ihdW0N1IL2WdlEa5cRr5oUDax 2tt3L8yxtgcMEBxyTVaCOG2mt5f7IaJxLIjNFtaOHBC7s5BYsFXDBSRwG2/NRRXNWlpfyM7Lcvwt aRQqjmNIWkZNpAVCEDE/Kcjgg88HgZ6DLLqyhvl2zTNMjs6rjhdrccc8gc85yOduOMFFKo7JRtt/ wP8AMdk3ymeI7qD/AEOOJ5rOIBtk8agTLvxgbiANqhc8Lyc5JJFFvE6zSXMgtpDlpUEXJwSuwkbl y27k57r14XBRWDb3fn+GpDgtC6zJLJBZywCbdtDYTKDnJOQD/EDngLlQDjIq2IpJZ4WGIrqMBmYl mXYxAYYyMsQnBI49Ooooropx2LjruWbGyWzt0TCF1XZvAOSBwMkkk8AdT2q9RRXfFJKyNErKwUUU VQBRRRQAUUUUAFFFFABRRRQB/9k=