Evaluating uncertainty when applying the trait-based protocol for climate-change vulnerability in

179 Pages·2017·3.95 MB·English

by  Md Anwar Hossain

Evaluating uncertainty when applying the trait-
based protocol for climate-change vulnerability

in freshwater crayfish

Md Anwar Hossain
ORCID: 0000-0002-0199-4380

Master of Philosophy

March 2018

School of BioSciences
Faculty of Science
University of Melbourne

Submitted in total fulfilment of the requirements of the degree

Abstract
Climate change has been recognized as one of the greatest threats to the persistence of biodiversity.
Several approaches have been used to assess species’ vulnerability to climate change such as
correlative niche models, mechanistic models, trait-based models, and combination of these model
outputs. The trait-based protocol for climate-change vulnerability assessment (TVA) is
increasingly used in a variety of taxa due to its suitability for assessing data-poor species. Yet,
TVA has thus far remained unevaluated for potential uncertainties. In TVA, climate change-
relevant traits are selected and scored against three dimensions: sensitivity, adaptive capacity, and
exposure to climate change. In this thesis, I applied TVA to assess climate-change vulnerability in
a data-poor invertebrate taxon (freshwater crayfish; 574 species) and explored the potential sources
of uncertainty in TVA. I found that climate-change vulnerable crayfish are distributed globally
with high concentrations in the USA and Australia, reflecting global pattern of crayfish richness.
Ninety-one species are already identified as vulnerable to climate change in the IUCN Red List. I
identified hotspots of species vulnerable to climate change that require additional conservation
action. I assessed multiple sources of uncertainty including trait selection, the use of arbitrary
thresholds for quantitative traits, and climate model choices. I quantified that in TVA, it is likely
that as more trait variables are included in the study, more species are identified as vulnerable to
climate change. The use of arbitrary thresholds in TVA was relatively robust to produce species’
vulnerability ranking. However, I found that the number of species identified as vulnerable to
climate change varied greatly (79-156) depending on which individual climate model was used.
TVAs are an effective tool to understand climate change vulnerabilities of data-poor species,
however, assessors applying the protocol should be aware of these uncertainty sources and perform
sensitivity analyses to better understand their impact on TVA results.
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Declaration

This is to certify that:
i. the thesis comprises only my original work towards the MPhil;
ii. due acknowledgement has been made in the text to all other material used;
iii. the thesis is less than 50,000 words in length, exclusive of tables, maps,
bibliographies and appendices.

Md Anwar Hossain
March 2018

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Preface
I am the primary author of all materials in this thesis. I have conducted the whole analysis of this
thesis under the guidance of my supervisors. This thesis work has been funded by Melbourne
University’s postgraduate research scholarship.
The data chapters (i.e., chapter 2 and 3) in this thesis were written as standalone manuscript for
publication. As a result, there is unavoidable repetition in the text (i.e., introduction, methods and
discussion). Each chapter ends with its own list of references, and Appendix. References are
formatted using the guidelines provided by the journal of Global Change Biology. The data
chapters have been written as ‘we’ (because of multiple co-authors), but the general introduction
(chapter 1) and general synthesis (chapter 4) use ‘I’. Tables and figures have been re-numerated
to facilitate navigation throughout the thesis.
The findings of chapter 2 have been presented in the International Congress for Conservation
Biology (ICCB) 2017, held in Cartagena, Colombia for both oral and poster; and the BioSciences
Symposia 2017 held in the University of Melbourne. The findings of chapter 3 have been presented
in Victorian Biodiversity Conference 2018, and accepted for oral presentation in the Society for
Freshwater Science (SFS) Annual Meeting to be held during May 20-24, 2018 in Detroit,
Michigan, USA.

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Acknowledgements

First and foremost, I would like to express sincere gratitude to my five supervisors, Mark Burgman,
Lucie Bland, José Lahoz-Monfort, Monika Böhm, Heini Kujala; and my committee member Yung
En Chee, and committee chair Peter Vesk. I have been blessed by your generous guidance and the
sharing of your knowledge to help me grow as a scientist. Thank you very much.
Mark Burgman, I am very grateful to your support during the commencement of my study here.
You have been always open for sharing any important ideas to be an independent researcher. Your
inspiration meant a lot to me through the whole duration of my study here. I am very glad to have
had this chance of working with you.
Lucie Bland, thank you for guiding me so closely throughout my candidature. I am so indebted to
you for assisting me with the programming knowledge during my initial stage and encouraging
me to analyze ecological complexity at bigger picture. I am grateful to you for spending your
invaluable times to guide and review my crazy early versions of the manuscripts. Thank you very
very much.
José Lahoz-Monfort, I am so blessed to have you as my primary supervisor. I am overwhelmed by
your expertise on statistical modeling. You have always been so friendly to me. It was so excellent
to share any ideas with you. You always had time to help me out and I am glad to have you as a
co-supervisor for my PhD coming next.
Heini Kujala, I am privileged to have you as one of my supervisors during the second half you my
candidature. You have been so much encouraging to me and so nice. I feel how much my academic
writing skills have developed after you have involved into my project. I am so grateful to you.
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Monika Böhm, you are one of so friendly people I have ever met. You have always been
encouraging and helpful to discuss important ideas related to my analysis. My early struggle with
coding has completely vanished after your nice explanations. Thank you so much.
Young En Chee, I am amazed by your critical thinking on how to improve the chapter results. You
have been always inspiring to me on how to improve my skills on presentation and analyses. You
are such a nice person. Thank you so so much.
Peter Vesk, I am blessed to have you as a chair of my supervisory committee. You have been
always nice to me and co-operated during any ideas discussion. Thank you so much.
Natalie Briscoe, I am so happy to have you as my mentor. It was so excellent to discuss with you
for ideas and relieve some stress. Thank you very very much.
QAEco coding club, this was my secret source of base coding skills. Thank you all the people who
have conceived the idea of forming this club and all other voluntary presenters.
David Wilkinson, Roozbeh Valavi, Casey Visintin, Darren Southwall, Els Van Burm, Bronwyn
Hradwsky, Jane Elith, Jane Carey, Elizabeth Martin, Chūng-Huèy, and all other members in my
lab: thank you so much for your support in one way or the other and being so nice to me. I am so
happy to have so many nice people around me. You people are angel.
Finally, I am grateful to my family members for your love and care all the time. Shraboni, thank
you so much for your love and affection. You meant the world to me. Love you.

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Table of Contents

Chapter 1: General Introduction ................................................................................................ 1
Climate change impacts on biodiversity ................................................................................................... 2
Climate change impacts on freshwater species ......................................................................................... 3
Assessing species’ vulnerability to climate change .................................................................................. 4
Correlative niche models .......................................................................................................................... 4
Mechanistic models .................................................................................................................................. 5
The IUCN Red List Criteria ...................................................................................................................... 6
Trait-based protocol for climate change vulnerability assessment (TVA) ............................................... 6
Uncertainties in TVA ................................................................................................................................ 8
Freshwater crayfish: a lesser known taxon for TVA ................................................................................ 9
Thesis questions and outline ................................................................................................................... 11
References ............................................................................................................................................... 12
Chapter 2: Assessing the vulnerability of freshwater crayfish to climate change ................ 25
Abstract ................................................................................................................................................... 26
Introduction ............................................................................................................................................. 27
Methods .................................................................................................................................................. 30
Results ..................................................................................................................................................... 43
Discussion ............................................................................................................................................... 51
Acknowledgements ................................................................................................................................. 58
References ............................................................................................................................................... 59
Appendix S2.1......................................................................................................................................... 68
Chapter 3: Assessing the impacts of uncertainty in climate change vulnerability assessments
................................................................................................................................. 106
Abstract ................................................................................................................................................. 107
Introduction ........................................................................................................................................... 108
Methods ................................................................................................................................................ 113
Results ................................................................................................................................................... 117
Discussion ............................................................................................................................................. 123
Acknowledgements ............................................................................................................................... 129
References ............................................................................................................................................. 130
Appendix S3.1....................................................................................................................................... 136

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Chapter 4: General synthesis ................................................................................................... 153
Overview ............................................................................................................................................... 154
Vulnerability of freshwater crayfish to climate change ........................................................................ 155
Uncertainty in trait-based protocol (TVA) ............................................................................................ 157
Trait selection .................................................................................................................................... 157
Threshold setting ............................................................................................................................... 160
Choosing climate models .................................................................................................................. 160
Future directions ................................................................................................................................... 161
References ............................................................................................................................................. 163

List of Tables
Table 2.1. Species traits and thresholds included in this study for three dimensions of sensitivity,
exposure and adaptive capacity.. .................................................................................................. 37
Table 3.1: List of selected traits and their scoring pattern used for TVA in this study. ............ 114

List of Figures
Figure 1.1. Summary of some potential impacts of climate change on species and their
surrounding environment… ........................................................................................................... .3
Figure 2.1. Summary of climate change vulnerability in freshwater crayfish using RCP6.0 for
2050............................................................................................................................................... 44
Figure 2.2. Richness map of climate change vulnerable species (87) using intermediate RCP6.0
in 2050, when species with missing data were considered (a) as not vulnerable or (b) vulnerable
to climate change, and (c) richness of climate vulnerable species (68) when traits with mostly
unknown values were excluded. ................................................................................................... 45
Figure 2.3. Trait-based vulnerability scores, broken down for the different dimensions, under
varying threshold values for quantitative traits.. ........................................................................... 46
Figure 2.4. Climate change vulnerability under different emission scenarios for 2050 and 2070.
....................................................................................................................................................... 47
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Figure 2.5. (a) Richness map of species (n = 91) predicted to be vulnerable to climate change in
the IUCN Red List, and (b) richness map of our climate change vulnerable species (n = 18) which
are also predicted to be vulnerable to climate change in the IUCN Red List. .............................. 51
Figure 3.1. Conceptual model of trait-based climate change vulnerability analysis ................. 110
Figure 3.2. Rank of (a) sensitivity, (b) adaptive capacity, and (c) exposure traits for vulnerability
to climate change. ....................................................................................................................... 119
Figure 3.3. Mean number of species predicted to be vulnerable based on the application of 25%
threshold under randomized quantitative data ............................................................................ 120
Figure 3.4. Species’ vulnerability to climate change based on different global climate models and
scenarios of (a) 2050, and (b) 2070. ........................................................................................... 120
Figure 3.5a. Range in the number of climate change vulnerable species and the coefficient of
variation in temperature and precipitation among individual climate models under different
scenarios of 2050. ....................................................................................................................... 122
Figure 3.5b. Range in the number of climate change vulnerable species and the coefficient of
variation in temperature and precipitation among individual climate models under different
scenarios of 2070. ....................................................................................................................... 123

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