Population Ecology: Distribution & Abundance Please do not use the images in these PowerPoint slides without permission. K. Harms photos from north of Manaus, Brazil

Population A group of individuals of a species that occupy a given place at a given time Please do not use the images in these PowerPoint slides without permission. Photo of members of a tadpole population from http://www.whateats.com/what-eats-a-tadpole-2

Distribution Local distribution – generally patchy, not continuous (which reflects patchy character of habitat, dispersal history, etc.) Geographic distribution – the entire geographic range Canyon wren (red) Cerulean warbler (blue) “X’s denote [Breeding Bird Surveys] on which the focal species were never detected over this period [1993-2002], while filled circles indicate where the focal species were detected.” Please do not use the images in these PowerPoint slides without permission. Hurlbert, Allen H. & Ethan P. White. 2005. Disparity between range map- and survey-based analyses of species richness: patterns, processes and implications. Ecology Letters 8:319-327. “Figure 1 (a) Geographical ranges of the canyon wren (red) and cerulean warbler (blue) from Ridgely et al. (2003). Symbols represent Breeding Bird Survey (BBS) routes that have been surveyed every year from 1993 to 2002. X’s denote surveys on which the focal species were never detected over this period, while filled circles indicate where the focal species were detected. (b) Geographical pattern of avian richness based on the number of species ranges overlapping each point. (c) Geographical pattern of avian richness based on the number of species observed on each BBS route in 2002. (d) Geographical pattern of the ratio of survey to range map richness, showing the greatest concordance in the south-east and the greatest disparity in the west. Richness and concordance values in (b)–(d) are binned into quantiles. (e) Digital elevation model of North America at 1-km resolution. (f) Mean values for the normalized difference vegetation index in the month of June at 1-km resolution (see text).” Hurlbert & White (2005) Ecology Letters, Fig. 1

Abundance Population size – the number of indivs. in the pop. Population density – no. indivs. per unit area Please do not use the images in these PowerPoint slides without permission. Photo from http://vitalsignsme.org/observation/species-comptonia-peregrina-was-found-flaming-toast-2010-10-06

Human population density – 1994 Abundance Human population density – 1994 Please do not use the images in these PowerPoint slides without permission. Wikipedia “Population” page; 09/IX/2014 Image from Wikimedia Commons

Abundance & Geographic Range Puma (previously Felis) concolor Please do not use the images in these PowerPoint slides without permission. Wikipedia “Cougar” page; 07/IX/2014 Photo & geographic range map from Wikimedia Commons

Abundance & Geographic Range Dionaea muscipula Endemic to Carolinas; native range is within 60-mile radius of Wilmington, N. C. Please do not use the images in these PowerPoint slides without permission. Wikipedia “Venus flytrap” page; 07/IX/2014 Video & geographic range map from Wikimedia Commons

Habitat (niche) breadth Relative Abundance Most species are rare and geographically restricted Deborah Rabinowitz identified 7 forms of rarity “Species in the upper left cube at the front exhibit no component of rarity. Those at the lower back right have all three components of rarity: small geographic range, narrow habitat breadth and low local density” Habitat (niche) breadth Please do not use the images in these PowerPoint slides without permission. See also Fig. 23.18 in your textbook. Where would pumas and Venus flytraps fall on this figure? Rabinowitz, Deborah. 1981. Seven forms of rarity. Pp. 205-217 in H. Synge, ed. The Biological Aspects of Rare Plant Conservation, Wiley. Ricklefs, Robert E. 2000. Rarity and diversity in Amazonian forest trees. Trends in Ecology & Evolution 15:83-84. “Fig. 1. Rabinowitz’s scheme illustrating the seven forms of rarity. Species in the upper left cube at the front exhibit no component of rarity. Those at the lower back right have all three components of rarity: small geographic range, narrow habitat breadth and low local density.” Local abundance (somewhere common or everywhere rare – within the native geographic range) Geographic range Image from Ricklefs (2000) TREE, based on original concept in Rabinowitz (1981)

What is an Invidividual? Genets – single genetic indiv.; best focus for evolutionary questions Ramets – actually or potentially independent members of a genet; clones; best focus for how (semi-)independent physiological units compete Please do not use the images in these PowerPoint slides without permission. Wikipedia “Stolon” page; 07/IX/2014 See pg. 26 of Harper (1977) – a genet comprises the various parts that trace back to a single “original zygote” (i.e., no intervening zygotes, e.g., through descent). Photo of the many ramets of a single genet of a dune plant from Wikimedia Commons

Neither distributions nor abundances are static Dynamics Neither distributions nor abundances are static Burmese python was introduced from Southeast Asia into South Florida; its North American range (as an exotic, non-native, invasive species) has been expanding ever since Native range Please do not use the images in these PowerPoint slides without permission. Even though the chosen example (Burmese python) is an anthropogenically-driven range expansion, dynamism occurs in all native and exotic populations. Wikipedia “Burmese python” page; 09/IX/2014 Introduced range Maps & photo of American alligator consuming a Burmese python from Wikimedia Commons

Dynamics Neither distributions nor abundances are static Please do not use the images in these PowerPoint slides without permission. Extinction is an “absorbing state.” Even though this chosen example (passenger pigeon) is an anthropogenically-driven range extinction, dynamism occurs in all native and exotic populations. Passenger pigeons went extinct when Martha (the very last individual) died on Sept. 1, 1914 K. Harms photos taken at Smithsonian National Museum of Natural History, Washington, D. C.

Dispersal Links Populations Natal dispersal Other dispersal (among breeding sites, foraging patches, etc.) Migration Migratory black-throated blue warbler Please do not use the images in these PowerPoint slides without permission. Wikipedia “Black-throated blue warbler” page; 07/IX/2014 Rubenstein, D. R. et al. 2002. Linking breeding and wintering ranges of a migratory songbird using stable isotopes. Science 295:1062-1065. “Fig. 1. Temperate North American breeding range and Greater Antillean wintering range of the black-throated blue warbler. A few individuals also winter in the Florida everglades, on the coast of the Yucatan Peninsula, and in Belize (12). Sampling locations in the breeding grounds and wintering grounds are indicated by black circles. In the Greater Antilles, samples were collected from individuals wintering in Jamaica (six sites in central and western portions), in Cuba (one site on a small cay, Cayo Coco, 15 km off the north-central coast), in Hispaniola (two sites in the Dominican Republic near the border with Haiti), and in Puerto Rico (three sites near the eastern end).” “Fig. 2. Population means (SE) of d13C and dD in black-throated blue warbler feathers at different breeding latitudes and wintering longitudes. Sample sizes are indicated next to each site. (A) d13C values from the temperate North America breeding range decrease with increasing breeding latitude [F1,8 = 7.67, P = 0.024, r2 = 0.49, latitude = -19.35 - 0.11 (d13C)]. (B) dD values from the temperate North America breeding range decrease with increasing breeding latitude [F1,7 = 7.17, P = 0.032, r2 = 0.51, latitude=1.32 – 2.02(dD)]. (C) d13C values from the Greater Antillean wintering range decrease with increasing wintering longitude [F1,9 = 6.07, P = 0.036, r2 = 0.40, longitude = -18.81 - 0.07(d13C)]. (D) dD values from the Greater Antillean wintering range decrease with increasing wintering longitude [F1,7 = 22.93, P = 0.002, r2 = 0.77, longitude = 20.82 - 1.51(dD)].” Photo from Wikimedia Commons; Rubenstein et al. (2002) Science, Figs. 1 & 2

Distribution & Abundance are limited by Habitat Suitability, History & Dispersal Why are there no camelids in the Rain Forest Biome? Please do not use the images in these PowerPoint slides without permission. Wikipedia “Camelid” page; 09/IX/2014 Habitat suitability probably limits modern camelids from occupying Rain Forests; camelids are grassland, shrubland, and hot desert organisms. For a good discussion of these ideas, see: Hubbell & Foster (1986) Biology, chance & history. Range map & photos of extant camelids from Wikimedia Commons

Distribution & Abundance are limited by Habitat Suitability, History & Dispersal Why are there no camelids in North America? Eocene Epoch – 56 to 33.9 mya Examples of N. Am. Pleistocene Epoch megafauna (incl. Camelops) that went extinct ~ 10,000 yr ago Please do not use the images in these PowerPoint slides without permission. Wikipedia “Camelid” page; 09/IX/2014 Extinction history and limited dispersal probably resulted in a lack of camelids in modern N. Am. For a good discussion of these ideas, see: Hubbell & Foster (1986) Biology, chance & history. Map from Wikimedia Commons; image from http://www.jqjacobs.net/anthro/paleoamericans.html

cause each of these patterns? Dispersion Patterns What mechanisms could cause each of these patterns? Regular (over-dispersed) Clumped Random Please do not use the images in these PowerPoint slides without permission. Mapped individuals in 3 plots; in this case there is exactly the same density in each plot. Each individual is represented by a dot.

Index of Dispersion (Variance-to-Mean Ratio) Dispersion Patterns Index of Dispersion (Variance-to-Mean Ratio)  2 D =  D > 1 D  1 D < 1 Please do not use the images in these PowerPoint slides without permission. Count number of individuals per quadrat and calculate variance-to-mean ratio. R code to produce D for each figure: > C=c(5,1,6,1,0,1,7,0,7) > var(C)/mean(C) [1] 3.008929 > R=c(5,2,4,3,1,5,1,5,2) > var(R)/mean(R) [1] 0.9196429 > O=c(4,3,3,3,3,3,3,3,3) > var(O)/mean(O) [1] 0.03571429

Dispersion Patterns Scale of Focus At smaller scale D > 1 At larger scale D < 1 Please do not use the images in these PowerPoint slides without permission. In this case – at the larger scale of focus, the pattern becomes regular! So, the pattern of dispersion is very often scale-dependent.

Methods Area-based counts – random or stratified random placement of many replicate plots, quadrats or transects; (average count/area) * total area = population estimate Please do not use the images in these PowerPoint slides without permission. Photo of random quadrat placement from http://midlandsconservanciesforum.wordpress.com/2013/01/10/gareths-news-on-bsp/

Methods Distance methods – employ detection probability functions (one for each species or habitat) to weight observations & calculate population estimates E.g., line transect of length, L d2 d1 d3 Please do not use the images in these PowerPoint slides without permission. Each distance observation is weighted by the detection probability function. E.g., point sampling for a period of time, t d2 d3 d1

Mark-recapture studies Methods Mark-recapture studies M1 = # of individuals caught & marked on 1st occasion N = # of unknown individuals in the population R = # of marked individuals caught on 2nd occasion M2 = # of individuals caught on 2nd occasion Please do not use the images in these PowerPoint slides without permission. Wikimedia Commons file = “File:Wing tag Great Frigatebird.jpg” M1 / N = R / M2 N * (M1 / N) = N * (R / M2) M1 = (N * R) / M2 M2 * M1 = M2 * (N * R) / M2 M1 * M2 = N * R (M1 * M2) / R = (N * R) / R (M1 * M2) / R = N M1 / N = R / M2 N = (M1  M2) / R Photo of wing-tagged frigatebird from Wikimedia Commons

Ecological niche-modeling Methods Ecological niche-modeling An analysis with a sense of humor: ENMs for Bigfoot / Sasquatch 551 reported sightings & auditory detections; 95 reported footprints Maximum entropy niche modeling approach implemented in software MAXENT Environmental data layers for 9 BIOCLIM variables in WORLDCLIM data set: annual mean temp.; mean diurnal range; isothermality (mean diurnal range / annual range); temp. annual range; mean temp. of wettest quarter; mean temp. of driest quarter; precip. seasonality; precip. of warmest quarter; precip. of coldest quarter Please do not use the images in these PowerPoint slides without permission. Note: Bigfoot / Sasquatch does not exist. The paper was written to point out how mis-identification can mislead researchers who blindly employ ENMs. Lozier et al. 2009. Predicting the distribution of Sasquatch in western North America: anything goes with ecological niche modeling. Journal of Biogeography 36:1623-1627. “Figure 1. Map of Bigfoot encounters from Washington, Oregon and California used in the analyses. Points represent visual/auditory detection, and foot symbols represent coordinates where footprint data were available. Shading indicates topography, with lighter values representing lower elevations.” Lozier et al. (2009) J. Biogeogr.; Fig. 1

Ecological niche-modeling Methods Ecological niche-modeling Predicted range under current climate Predicted range under doubled [CO2] “convincing environmentally predicted distributions… can be generated from questionable site-occurrence data” (Lozier et al. 2009) Please do not use the images in these PowerPoint slides without permission. Note: Bigfoot / Sasquatch does not exist. The paper was written to point out how mis-identification can mislead researchers who blindly employ ENMs. Lozier et al. 2009. Predicting the distribution of Sasquatch in western North America: anything goes with ecological niche modeling. Journal of Biogeography 36:1623-1627. “Figure 2. Predicted distributions of Bigfoot constructed from all available encounter data using maxent (a) for the present climate and (b) under a possible climate change scenario involving a doubling of atmospheric CO2 levels. Results are presented for logistic probabilities of occurrence ranging continuously from low (white) to high (black). Differences between (a) and (b) are shown in (c), with whiter values reflecting a decline in logistic probability of occurrence under climate change, darker values reflecting a gain, and grey reflecting no change. A predicted distribution of Ursus americanus in western North America under a present-day climate is also shown (d). White points indicate sampling localities in California, Oregon and Washington taken from GBIF (n = 113 for training, 28 for testing; compare with Fig. 1) used for the maxent model with shading as in (a) and (b); black points indicate additional known records not included in the model.” Lozier et al. (2009) J. Biogeogr.; Fig. 2

Ecological niche-modeling Methods Ecological niche-modeling Predicted range of American black bear using the same procedure Predicted range under current climate “many [Bigfoot] sightings… may be cases of mistaken identity” (Lozier et al. 2009) Please do not use the images in these PowerPoint slides without permission. Note: Bigfoot / Sasquatch does not exist. The paper was written to point out how mis-identification can mislead researchers who blindly employ ENMs. Lozier et al. 2009. Predicting the distribution of Sasquatch in western North America: anything goes with ecological niche modeling. Journal of Biogeography 36:1623-1627. “Figure 2. Predicted distributions of Bigfoot constructed from all available encounter data using maxent (a) for the present climate and (b) under a possible climate change scenario involving a doubling of atmospheric CO2 levels. Results are presented for logistic probabilities of occurrence ranging continuously from low (white) to high (black). Differences between (a) and (b) are shown in (c), with whiter values reflecting a decline in logistic probability of occurrence under climate change, darker values reflecting a gain, and grey reflecting no change. A predicted distribution of Ursus americanus in western North America under a present-day climate is also shown (d). White points indicate sampling localities in California, Oregon and Washington taken from GBIF (n = 113 for training, 28 for testing; compare with Fig. 1) used for the maxent model with shading as in (a) and (b); black points indicate additional known records not included in the model.” Lozier et al. (2009) J. Biogeogr.; Fig. 2