Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/16546
Title: Conservation of plant species under future climate and land- use change
Authors: GIAM XINGLI
Keywords: plant biodiversity, conservation, governance, land-use change, species-area relationships, species assessments
Issue Date: 21-Aug-2009
Citation: GIAM XINGLI (2009-08-21). Conservation of plant species under future climate and land- use change. ScholarBank@NUS Repository.
Abstract: Habitat loss resulting from human land-use change and climate change threatens plant biodiversity on Earth. I assessed the vulnerability of globally threatened plant biodiversity to future habitat loss over the first half of this century by testing country-level associations between threatened plant species richness and future habitat loss owing to, separately, land-use and climate changes. In countries that overlap with biodiversity hotspots, plant species endangerment increases with climate change-driven habitat loss. The same pattern was observed among tropical countries. This association suggests that many currently threatened plant species may become extinct owing to anthropogenic climate change in the absence of potentially mitigating factors such as natural and assisted range shift, and physiological and genetic adaptations. Countries ranked the highest in future plant species endangerment are concentrated around the equator. The current conservation assessment effort by IUCN was positively correlated with future plant species endangerment, suggesting that the conservation assessment program is generally efficient in targeting the most threatened countries. Because poverty and poor governance can compromise conservation, I considered the economic condition and quality of governance with future plant species endangerment to prioritize countries based on conservation need. I identified Angola, Cuba, Democratic Republic of Congo, Ethiopia, Kenya, Laos, Madagascar, Myanmar, Nepal, Tajikistan, and Tanzania as the countries in greatest need of conservation assistance in terms of financial aid and/or improving political institutions.
Conservation assessments aid in planning by providing valuable information about the geographic range and population numbers of species. However, less than 5% of all plant species have been assessed. I therefore aimed to provide a template to guide conservation assessments at the ecoregion level. First, I identified the worldb s ecoregions that contain the highest plant species richness after controlling for area using species-area relationship (SAR) models within a Bayesian multi-model framework. While all previous studies have assumed that species richness is normally distributed and most applied the power function SAR, I found that species richness was log-normally distributed across ecoregions in most biomes and no SAR model was the best in all biomes. My results highlight the importance of considering a wide variety of SAR models with different error distributions to identify species-rich hotspots. Using quantitative thresholds, ecoregions with the highest plant species richness, historical habitat loss, and projected increase in human population density were allocated the highest relative need for conservation assessments. My template managed to identify some important ecoregions excluded from the Global 200 and Biodiversity Hotspots templates. Using generalized linear models, I showed that countries overlapping with high-priority ecoregions are poorer than the other countries. Therefore I urge international aid agencies and botanic gardens to cooperate with local scientists to fund and implement conservation assessment programs.
Overall, my study showed that plant biodiversity remains vulnerable to climate change driven habitat loss, and socioeconomic factors. The international community must consider both global and local strategies that aim to improve governance and economic condition for conservation endeavours to be truly effective.
URI: https://scholarbank.nus.edu.sg/handle/10635/16546
Appears in Collections:Master's Theses (Open)

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