Modeling Climate Resilient Planting Locations of Culturally Significant Plants for Musqueam on UBC’s Vancouver Campus
department or school: Forestry, Faculty of
data provider: DSpace
contributor: University of British Columbia. Campus and Community Planning
contributor: University of British Columbia. Faculty of Forestry
creator: Mes, Johic
issued: 2025-09-15T20:56:17Z
issued: 2025-04-05
description: Urban greenspaces provide essential ecosystem services, enhance biodiversity, and hold cultural significance, particularly for Indigenous communities. However, these areas are increasingly threatened by climate change, urbanization, and invasive species. While greenspace planning and species distribution modeling are established tools for supporting ecological resilience, few studies integrate future climate suitability into site-specific planting guidelines. This represents a key gap in designing adaptive urban landscapes. Remote sensing offers a distinct advantage in this context by enabling fine-scale, spatially continuous assessment of environmental conditions, such as precipitation and shade, that are difficult to capture through ground-based methods alone. This study addressed this gap by assessing habitat suitability and future climate impacts at a local scale. Specifically, it identified future habitat suitability and optimal planting locations for culturally significant plants of the Musqueam people on the University of British Columbia Vancouver campus. To achieve this, the study combined iNaturalist occurrence data, future climate projections from ClimateBC, and local environmental variables derived from LiDAR within a MaxEnt modeling framework. The analysis focused on two species: Salmonberry (Rubus spectabilis) and Sword Fern (Polystichum munitum), evaluating their suitability under different climate scenarios. The resulting suitability maps highlighted optimal planting locations based on projected climate conditions and environmental factors such as slope, aspect, and shade. Shade emerged as the most influential variable across all models, contributing between 74% and 92%. Other environmental variables had a limited effect on model outcomes, likely due to the study’s small geographic scope. Overall, the model outputs aligned closely with the known ecological preferences of the studied species. These findings can inform climate-resilient planting strate…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/92325
note: Modeling Climate Resilient Planting Locations of Culturally Significant Plants for Musqueam on UBC’s Vancouver Campus Final Research Project April 5, 2025 Author: Johic Mes BASc Computer Engineering Topical Mentor: Georgia Stanley Climate Resilience & Biodiversity Applied Research Coordinator, SEEDS Sustainability Program 1 Table of Contents Land Acknowledgment ................................................................................................................ 2 Disclaimer .................................................................................................................................... 2 Executive Summary ................................................................................................................................... 3 1. Introduction ..................................................................................................................................... 4 2. Study Site and Data Summary ............................................................................................................... 6 2.1 Study Site Area – University of British Columbia Vancouver Campus .................................. 6 2.2 iNaturalist Occurrence Data .................................................................................................. 7 2.3 LiDAR Derived Models (DSM, DEM, CHM) ............................................................................ 8 2.4 Generating Future Climate Data (ClimateBC) ..................................................................... 10 3. Methods .............................................................................................................................................. 11 3.1 Preparing Data for MaxEnt ...................................................................................................... 12 3.2 Running the MaxEnt Model ................................................................................................ 12 3.3 Generating Suitabili…
has type: Report
is shown at: 10.14288/1.0450135
language: eng
peer review status: Unreviewed
provider: Vancouver : University of British Columbia Library
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
is part of: UBC Social Ecological Economic Development Studies (SEEDS) Student Report
is part of: University of British Columbia. FCOR_V 599
subject: Greenspace
subject: Species Distribution Modelling
subject: Salmonberry
subject: Sword Fern
subject: Culturally Significant Plants
subject: Climate Change Adaptation
subject: Biodiversity
subject: Climate
subject: Food
subject: Land
type: Text
identifier URI: http://hdl.handle.net/2429/92325