Wildlife Applications “Visualizing the distribution of rare or threatened species is necessary for effective implementation of conservation initiatives.” “With the purpose of refining existing maps, we used survey results, radio-telemetry locations and GIS data to construct resource selection functions (RSF) that quantified the habitat affinities and predicted the relative probability of occurrence of mountain caribou at two spatial scales.” Johnson, Seip and Boyce 2004 Very rapid shift from the old-school 1:20,000 scale maps to modern GIS

Movie Screening Probably some GIS involved Pre-Register Here

Visualizing Human Impact Raster analysis combining built environment, cropland, pasture, population density, night-time lights, railways, roads and navigable waterways Conclusion: impact slower than economic growth (doing more on less land)

Visualizing Endangered Species But what’s wrong with this picture? The great plains looks empty…

Visualizing Extinctions

Underlying Tabular Data Recent mammal extinctions (1500 AD to present) Common name\scientific name Extinction date Range Antillean giant rice rat 1902 France (Martinique) Megalomys desmarestii[1] Anthony's woodrat 1926 Mexico (only on Isla Todos Santos) Neotoma anthonyi[2] Banks Island wolf 1920 Canada Canis lupus bernardi Barbados raccoon 1964 Barbados Procyon lotor gloveralleni Bunker's woodrat 1932 Mexico (Coronados Islands) Neotoma bunkeri[3] California golden bear 1922 California Ursus arctos californicus Caribbean monk seal 1952 Caribbean Sea Monachus tropicalis[5] Cascade mountain wolf 1940 Canada and USA Canis lupus fuscus Cuban coney 1500s Cuba Geocapromys columbianus[6] Eastern cougar Unknown (declared in 2011) Eastern Canada and USA Puma concolor couguar Eastern elk 1887 Cervus canadensis canadiensis Goff's pocket gopher 1955 Florida Geomys pinetis goffi Gull Island vole 1897 Gull Island, New York Microtus pennsylvanicus nesophilus Hispaniolan edible rat Hispaniola Heteropsomys insulans [7] Insular cave rat 1600s Puerto Rico Heteropsomys insulans[8] Imposter hutia Hexolobodon phenax[9] Jamaican monkey Jamaica Xenothrix mcgregori[10] Jamaican rice rat 1870s Oryzomys antillarum[11] Little Swan Island hutia Swan Islands, Honduras Geocapromys thoracatus[12] Marcano's solenodon Solenodon marcanoi[13] Merriam's elk 1906 Southwestern USA Cervus canadensis merriami Mexican grizzly bear Mexico and Southwestern USA Ursus arctos nelsoni A subset of mammalian extinctions

North American Species Richness What’s up with BC? There’s blue there…. Suggesting positive? Crappy symbology. http://www.cof.orst.edu/rangecontractions/maps.php

Extinction vs. Richness

Impact vs. Species Richness This impact assessment does not consider species richness or anthropogenic extinctions http://www.cof.orst.edu/rangecontractions/maps.php

Extinction: Stratification by Biome Bars indicate means, numbers following means indicate maxima. The proportion of North American land that each biome constitutes is shown as a percentage after the biome’s name. http://www.cof.orst.edu/rangecontractions/maps.php

Visualizing Ocean Habitats

BC Salmon Farms Interactive map: spatial locations connected to database The same effect as “info” button in ArcMap Dekstop Living Oceans advocacy group

Invasive Aquatic Species http://www.env.gov.bc.ca/soe/indicators/plants-and-animals/invasive-species.html

Invasive Fish Over Time

Angler’s Atlas

Wildlife meets Planning Buffer! http://www.wildlifeinfometrics.com/WII_Gallery/gallery_pages/gallery7.html These guidelines are for building homes and other permanent structures, not timber harvest http://www.pfla.bc.ca/forest-management-tips/managing-wildlife-habitat-the-northern-goshawk-part-2/

Common Buffering Application Harvest block falls within 600m buffer but not 500m buffer All access roads go through both buffers Road is established; best to wait until nesting complete

Vernal Pools http://www.northwoodscenter.org/wordpress/wp-content/uploads/2014/07/Vernal-Pool-Map-1024x614.png

Visualizing Home Range Defined as the space an animal uses, containing the essential requirements for life (food, water, cover) (Vs. defended territory)

Minimum Convex Polygon vs. Kernel Density Estimate http://gis4geomorphology.com/home-range-kernel/

95 % Kernel Density (Red) vs. 50% Kernel Density (Blue) Home range (95%) vs core range (50%) http://gis4geomorphology.com/home-range-kernel/

Wolves Captured in Washington Each color is one wolf (others may be tagging along); data is from 2013 only What’s wrong with this map? At least two commenters concerned that wolves are in their neighborhoods How might this backfire?

Geog300 Projects

Risk determined by road size, surface and density Might have been better to divide polygons into smaller pieces or use raster as distant overlaps affect the entire area.

Visualizing Interactions Assumptions: Collared caribou cover the same ground as the whole herd. The sampled herds are the only herds in the region.

Spatial Joins Attaching the attributes of underlying features to a point layer In this case, I am joining the pop_places layer to its nearest lake over 40 hectares, so I know the nearest place to go swimming

Result of Many Spatial Joins Each point has: Number of years moderately or severely defoliated Number of years defoliated Year of most recent fire, if any Cause of fire, if any Size of fire, if any Mean annual temperature Mean annual precipitation Elevation Fundamental to analysis

Rea, Johnson, Emmons 2014 “Characterizing Moose-Vehicle Collision Hotspots in Northern British Columbia” Study Area

What’s the difference between areas with high moose collisions and no moose collisions?

Experimental Design Result: Single, averaged attribute per feature 29 hotspots (four or more collisions per km, 2000-2005) 15 control sites with no collisions recorded 0.5-3km segments of road 500m and 5km buffers for fine + coarse scale attributes Faked example: Selected two random road segments that happened to be next to each other. Buffer acts only on the selected features—good thing, too, or I would still be watching it buffer. Elevation, aspect, rivers, at 500m and 5km distance Result: Single, averaged attribute per feature

Reading Confidence Intervals What is the null value (in this figure, it is 1.0; it is often 0) Do the upper and lower confidence intervals contain the null value? If yes, nonsignificant. If no, significant. http://sphweb.bumc.bu.edu/otlt/MPH-Modules/EP/EP713_RandomError/EP713_RandomError6.html

Look for… Big coefficients = big effect 95% CI that does NOT include 0 (both positive or both negative) Conclusion: time to move the signs

Expert-Based Habitat Modeling Ask a trapper where he sees bears spring Identify key characteristics Distance to roads Distance to eskers Distance to old forest Distance to swamp Extrapolate to the landscape

Work-Through Lacking experts, any parameters will do ‘Twas brillig, and the slithy toves     Did gyre and gimble in the wabe; All mimsy were the borogoves,     And the mome raths outgrabe. “Beware the Jabberwock, my son     The jaws that bite, the claws that catch! Beware the Jubjub bird, and shun     The frumious Bandersnatch!” He took his vorpal sword in hand;     Long time the manxome foe he sought— So rested he by the Tumtum tree,     And stood awhile in thought. And, as in uffish thought he stood,     The Jabberwock, with eyes of flame, Came whiffling through the tulgey wood,     And burbled as it came! One, two! One, two! And through and through     The vorpal blade went snicker-snack! He left it dead, and with its head     He went galumphing back. “And hast thou slain the Jabberwock?     Come to my arms, my beamish boy! O frabjous day! Callooh! Callay!”     He chortled in his joy.

Objective Identify routes that the Jabberwocky is likely to use as it travels from Purden to Aleza Lake and prioritize them according to the % of the landscape that may be devoted to Jabberwocky conservation

Toolset: Corridor Design Assumption: animal movement follows path of least risk (food, water, cover) Food, water, cover differ by species By finding routes that provide food, water, cover, we can maintain a travel corridor between patches

Jabberwocky will prefer to be Parameters During the summertime, when adventure-seeking knights (and graduate students) roam the countryside, the Jabberwocky tends to avoid travelled roads. Rivers and swamps are its preferred haunts, where Bandersnatches and Jubjub birds are present to keep watch for would-be heroes. Finally, the creature is easily scared off by its arch nemesis the feller-buncher, and does not return to a stand until the area has been successfully regenerated. Jabberwocky will prefer to be 100m or more from roads Less than 50m from a river Less than 100m from a swamp More than 500m from an not-successfully regenerated block

Coding the Parameters 100 = preferred habitat 75 = good but not great Road 0 50 : 12 50 100 : 45 100 500 : 64 500 15000 : 100   River 0 50 : 100 50 100 : 60 100 500 : 40 500 15000 : 10 Swamp 0 100 : 100 100 500 : 66 500 15000 : 15 NSR 0 100 : 10 100 500 : 50 100 = preferred habitat 75 = good but not great 50 = acceptable 25 = avoided 0 = terrible Distance Range (m): Weight

% of Landscape Devoted to Corridor Under Different Constraints

Summary Modern wildlife management is GIS-heavy Statistics are becoming more complex Output maps are getting better More interactive applications Online, Google Earth Check out the movie screening on the 25th Next slides: midterm!

Midterm Exam: October 11 Multiple choice/short answer Samples from last year (not this year): 2. In an attribute table, a field containing the total number of trees in each polygon, would be which data type: a. Text b. Date c. Integer d. Float e. Double 30. If GIS software gave us a distance of 3405.397865 metres, should this answer be described as ‘accurate’ or ‘precise’ (or both) ? Why ?

Fast Assignment Work When you forget where in the labs we covered converting .e00 files Open lab PDF>Ctrl+F>.e00

Google Earth Safari