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CSS: Palos Verdes Nearest transect neighbor analysis Christine M. Rodrigue GEOG 442 (biogeography) GEOG/ES&P 330 (California ecosystems) Department of.

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Presentation on theme: "CSS: Palos Verdes Nearest transect neighbor analysis Christine M. Rodrigue GEOG 442 (biogeography) GEOG/ES&P 330 (California ecosystems) Department of."— Presentation transcript:

1 CSS: Palos Verdes Nearest transect neighbor analysis Christine M. Rodrigue GEOG 442 (biogeography) GEOG/ES&P 330 (California ecosystems) Department of Geography Environmental Science and Policy Program California State University, Long Beach

2 About these data For several years, Geography and Environmental Science and Policy courses have taken field trips to the Portuguese Bend Reserve on Palos Verdes The trips give students practice in using various field sampling techniques (transects, quadrats, sometimes quadratting along a transect) and identification of plants in the California sage scrub and grassland in preparation for their group research projects A large database has built up, and some classes now use parts of the database to learn statistical techniques for processing it The data here are those taken from near the intersection of Crenshaw Extension, Peacock Flats Trail, and Fire Station Trail, all done with 10 m transects, sampling at 1 m, during F/14, F/15, and S/16

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4 Processing Students in GEOG/ES&P330 (California ecosystems) in S/16 – cross-tabbed all the 10 m transects from F/14, F/15, and S/16 – for each species, the species found at the next sampling point on the transect – starting at the boundary with grassland or trail, moving into CSS – failsafes built in to validate each processed transect Table describes for each species what its nearest transect neighbors are – identifies regular associations among species – identifies species prone to forming monospecific patches – identifies CSS species that depend on other CSS species – identifies CSS species that are tolerant of exotic annuals

5 Visualization Graph creates an ecological "space" – built in Dia software – each species is color coded: □ native is shown with green background □ exotic is shown with pink background □ bare dirt or soil is shown with a beige background – each link is color coded, its thickness a measure of how common it is □ interspecific links are red □ intraspecific links are green – Dia allows nodes (species) and links to be moved around to minimize crossing of links □ monospecific patches in thick green bands □ tolerance of invasives in red links between natives and exotics

6 All transects

7 Crenshaw Extension

8 Peacock

9 Fire Trail

10 Field teams Fall2014 (GEOG 442, Biogeography) – J. Norico, D. Fiarillo,N. Savisky, C. Austin, D. Sanders, N. Beatty, J. Kim, E. Zvirbulis, C.Casapulla, S. Antu, N. Espinosa, G. Crethers, A. Tavasolian, H. Walker, K. Good, J. Chong, A. Shaffer, E. Carnahan, M. Romero, and a "mystery team" (anonymous) Fall 2015 (GEOG/ES&P 330, California ecosystems) – A. Burciaga, A. Butterworth, S. Craig, E. Critchfield, D. Daddow, S. Gonzalez, E. Hart, G. Hernandez, A. Iglesias, L. Leone, K. Linton, A. Ly, S. Palomera, J. Pinon, Y. San Pedro, A. Santamaria, A. Stack, I. Suriyavirun, B. Tinsley, M. Torio, M. Toscano, and N. Townsend Spring 2016 (GEOG/ES&P 330, California ecosystems) – J. Pulliam, S. Dideban, L. Henderson, C. Johnson, M. Billinghurst, M. Kelly, M. Parra-Aya, J. Tran, H. Heng, G. Orozco-Gomez, A. Hudson, T. Denofrio, L. Camacho, M. Briley, R. Douglass, C. Dominguez, J. Callanan, N. Voeun, D. Henderson, J. Monsanto, J. Bartz, K. DeCollibus, L. Freij – Further lab work: J. Kubani, V. Faria


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