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Previous issue date: 2016-02-26 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Coral reefs are of extreme importance to both nature and society, due to being
responsible for several services and harbouring hundreds of species. Despite such critical
importance, reef corals current suffered heavy losses since the Anthropocene, with 20% of
world´s corals damaged beyond recovery due to human pressure and coastal development. This
scenario is even worse, since corals are especially vulnerable to climate change and the entire
ecosystem could go extinct by 2050. In this study we focus on comparing the already
established impacts from human development and the yet happen losses from climate change
on Brazilian corals, a unique fauna that still have gaps in knowledge. We created environmental
suitability models for 24 species and quantified individual losses from both climate change and
human activities. From the individual results we derived an overall pattern, in which we found
out that future losses from climate alteration are equivalent to current losses from human
activities. We then used the spatial distribution of those activities and key areas for
conservation, determined with software Zonation, to select six areas in the Brazilian exclusive
economic zone where proactive and reactive conservation strategies should be implanted, given
its importance to biodiversity and concentrated anthropogenic impacts. Overall suitability
losses were of approximately 30% for both sources and 60% of the areas will continue to be
suitable in the future. Therefore, Brazilian corals will experience heavy losses from climate,
especially the loss of highly suitable areas, which are compared to effects from human
economic activities. Coral situation is likely to be even worse, if we were to consider bleaching,
ocean acidification and diseases, events expected to increase with the rising temperature. / Ecological Niche Modelling (ENM) is widely used for conservation purposes, predicting
species invasion, evolutionary aspects and a whole array of applications. However, for most
cases, evaluating the efficiency of those models poses as problematic, as commonly used
methods (i.e. random methods) do not assure the required independence between data used to
create the model and data used to evaluate the model. We developed a new transferabilitybased
framework that ensures the much-needed independence between subsets. We created an
alternate approach that geographically splits occurrence datasets, while intrinsically controls
issues related to previous transferability approaches, such as overfitting, extrapolation and
sampling bias. We used 26 Atlantic coral species to perform three different geographical
divisions quantifying the effect of different splits on model predictive efficiency. We
demonstrate that transferability should be used as an effective method to evaluate ENMs.
Geographical split of the area in deciles proved as a reliable evaluation method, assuring
independence between datasets and being less prone to common transferability issues. Our
odds-and-evens framework provides improvements to the ongoing debate of ENMs evaluating
by its transferability. This new method corrects the issue of artificiality causing sampling bias
and overfitting, common in previous methodologies, while also is less prone to extrapolation
issues, a common problem in transferability approaches. Moreover, the framework appears as
a feasible and useful alternative to the problematic and commonly used random partition of
datasets evaluation.
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.bc.ufg.br:tede/5592 |
| Date | 26 February 2016 |
| Creators | Andrade, André Felipe Alves de |
| Contributors | De Marco Junior, Paulo |
| Publisher | Universidade Federal de Goiás, Programa de Pós-graduação em Ecologia e Evolução (ICB), UFG, Brasil, Instituto de Ciências Biológicas - ICB (RG) |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Format | application/pdf |
| Source | reponame:Biblioteca Digital de Teses e Dissertações da UFG, instname:Universidade Federal de Goiás, instacron:UFG |
| Rights | http://creativecommons.org/licenses/by-nc-nd/4.0/, info:eu-repo/semantics/openAccess |
| Relation | -5361682850774351271, 600, 600, 600, 600, -3872772117827373404, 4714165126587508770, 2075167498588264571 |
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