title: Between the borders

authors: Apiata, Hāwea

abstract: Ekphrasis in response to the artwork 'Taniko Border 6' by Ngāti Raukawa artist, John Bevan Ford.

text: Between the borders Ekphrasis in response to the artwork 'Taniko Border 6' by Ngāti Raukawa artist, John Bevan Ford.

year: 2023-11-30

title: Kia whakatōmuri te haere whakamua – A Māori framework for coastal climate change adaptation

authors: Bailey-Winiata, Akuhata

subjects: Climate Change Adaptation

abstract: Current climate change adaptation frameworks do not sufficiently represent or acknowledge the intricacies and complex nature of climate adaptation for all communities. This thesis contributes a Māori (Indigenous peoples of Aotearoa New Zealand (A-NZ)) climate adaptation framework that is informed by Te Ao Māori world views, mātauranga Māori (Māori knowledge), Te Tiriti o Waitangi (Treaty of Waitangi) and research at the interface of Western knowledge and mātauranga Māori. This is needed to promote a more equitable and culturally sensitive approach to the current climate change adaptation process for hapū (sub-tribes) and iwi (tribes). To achieve this, this thesis is rooted in the whakataukī (proverb) “Kia whakatōmuri te haere whakamua – I walk backwards into the future with my eyes fixed on my past”, which exemplifies the power of acknowledging Māori history and intergenerational knowledge, while moving forward to a prosperous future. This thesis had four key aims. First, I looked to the past to understand ways Māori ancestors adapted and relocated in response to natural hazards to inform a future climate adaptation or relocation process. Second, I took stock of the contemporary risk to coastal marae (Māori meeting grounds) from sea level rise. Third, I looked internationally at other Indigenous communities' adaptation challenges and how they have overcome them as a mutual learning opportunity. And finally, I developed a conceptual Māori climate adaptation framework based on existing models and informed by a wānanga (workshop) with over 100 Māori participants. This two-part framework emphasises the importance of fostering Te Tiriti-centric relationships and partnerships that are essential for climate adaptation with hapū and iwi. In addition, it serves as a guide to support adaptation decision-making for hapū and iwi Māori. This thesis took a multidisciplinary approach to achieve these aims, incorporating historical and archival analyses, semi-structured interviews, a systematic review, coastal flooding and exposure analyses using spatial information, and wānanga. The findings highlighted that relocation due to natural hazards is not uncommon for Māori, as this thesis identified 51 examples of where relocation was completed or discussed in response to natural hazards. Furthermore, in a case study with Tūhourangi and Ngāti Rangitihi, this thesis identified vital aspects that enabled their relocation following the 1886 Tarawera eruption, the most influential being tuku whenua – the gifting of land to relocate to. This thesis also identified that by 2150, under shared socio-economic pathway (SSP) 5-8.5, 27% and 28% of coastal marae (total of 186 nationally) are exposed to a 100–year and 1000–year annual recurrence interval (ARI) extreme sea level events, respectively. Overall, this thesis contributes to our understanding of the requirements to support hapū and iwi Māori in climate adaptation, with parallels to other Indigenous communities. Requirements include resourcing, partnerships, autonomy, intergenerational planning, recognition, respect and redress. In Chapter 8 – the discussion of this thesis, we focus on four overall contributions this thesis has made, which are: 1) Hapū and iwi Māori are at risk of climate change, 2) We’ve done it before we can do it again, 3) Adaptation approach cannot be one-size-fits-all, and 4) Adaptation in Aotearoa needs a Te Tiriti-centric approach. Ultimately, this thesis underscores the urgent need for inclusive climate adaptation strategies that honour Indigenous knowledge systems, ensuring that hapū and iwi Māori are not only heard but are actively supported in navigating the impacts of climate change.

text: Kia whakatōmuri te haere whakamua – A Māori framework for coastal climate change adaptation Current climate change adaptation frameworks do not sufficiently represent or acknowledge the intricacies and complex nature of climate adaptation for all communities. This thesis contributes a Māori (Indigenous peoples of Aotearoa New Zealand (A-NZ)) climate adaptation framework that is informed by Te Ao Māori world views, mātauranga Māori (Māori knowledge), Te Tiriti o Waitangi (Treaty of Waitangi) and research at the interface of Western knowledge and mātauranga Māori. This is needed to promote a more equitable and culturally sensitive approach to the current climate change adaptation process for hapū (sub-tribes) and iwi (tribes). To achieve this, this thesis is rooted in the whakataukī (proverb) “Kia whakatōmuri te haere whakamua – I walk backwards into the future with my eyes fixed on my past”, which exemplifies the power of acknowledging Māori history and intergenerational knowledge, while moving forward to a prosperous future. This thesis had four key aims. First, I looked to the past to understand ways Māori ancestors adapted and relocated in response to natural hazards to inform a future climate adaptation or relocation process. Second, I took stock of the contemporary risk to coastal marae (Māori meeting grounds) from sea level rise. Third, I looked internationally at other Indigenous communities' adaptation challenges and how they have overcome them as a mutual learning opportunity. And finally, I developed a conceptual Māori climate adaptation framework based on existing models and informed by a wānanga (workshop) with over 100 Māori participants. This two-part framework emphasises the importance of fostering Te Tiriti-centric relationships and partnerships that are essential for climate adaptation with hapū and iwi. In addition, it serves as a guide to support adaptation decision-making for hapū and iwi Māori. This thesis took a multidisciplinary approach to achieve these aims, incorporating historical and archival analyses, semi-structured interviews, a systematic review, coastal flooding and exposure analyses using spatial information, and wānanga. The findings highlighted that relocation due to natural hazards is not uncommon for Māori, as this thesis identified 51 examples of where relocation was completed or discussed in response to natural hazards. Furthermore, in a case study with Tūhourangi and Ngāti Rangitihi, this thesis identified vital aspects that enabled their relocation following the 1886 Tarawera eruption, the most influential being tuku whenua – the gifting of land to relocate to. This thesis also identified that by 2150, under shared socio-economic pathway (SSP) 5-8.5, 27% and 28% of coastal marae (total of 186 nationally) are exposed to a 100–year and 1000–year annual recurrence interval (ARI) extreme sea level events, respectively. Overall, this thesis contributes to our understanding of the requirements to support hapū and iwi Māori in climate adaptation, with parallels to other Indigenous communities. Requirements include resourcing, partnerships, autonomy, intergenerational planning, recognition, respect and redress. In Chapter 8 – the discussion of this thesis, we focus on four overall contributions this thesis has made, which are: 1) Hapū and iwi Māori are at risk of climate change, 2) We’ve done it before we can do it again, 3) Adaptation approach cannot be one-size-fits-all, and 4) Adaptation in Aotearoa needs a Te Tiriti-centric approach. Ultimately, this thesis underscores the urgent need for inclusive climate adaptation strategies that honour Indigenous knowledge systems, ensuring that hapū and iwi Māori are not only heard but are actively supported in navigating the impacts of climate change.

year: 2024-05-28

title: A comparison of methods for estimating prediction intervals in NIR spectroscopy: Size matters

authors: Bouckaert, Remco R.

subjects: NIR

abstract: In this article we demonstrate that, when evaluating a method for determining prediction intervals, interval size matters more than coverage because the latter can be fixed at a chosen confidence level with good reliability. To achieve the desired coverage, we employ a simple non-parametric method to compute prediction intervals by calibrating estimated prediction errors, and we extend the basic method with a continuum correction to deal with small data sets. In our experiments on a collection of several NIR data sets, we evaluate several existing methods of computing prediction intervals for partial least-squares (PLS) regression. Our results show that, when coverage is fixed at a chosen confidence level, and the number of PLS components is selected to minimize squared error of point estimates, interval estimation based on the classic ordinary least-squares method produces the narrowest intervals, outperforming the U-deviation method and linearization, regardless of the confidence level that is chosen.

text: A comparison of methods for estimating prediction intervals in NIR spectroscopy: Size matters In this article we demonstrate that, when evaluating a method for determining prediction intervals, interval size matters more than coverage because the latter can be fixed at a chosen confidence level with good reliability. To achieve the desired coverage, we employ a simple non-parametric method to compute prediction intervals by calibrating estimated prediction errors, and we extend the basic method with a continuum correction to deal with small data sets. In our experiments on a collection of several NIR data sets, we evaluate several existing methods of computing prediction intervals for partial least-squares (PLS) regression. Our results show that, when coverage is fixed at a chosen confidence level, and the number of PLS components is selected to minimize squared error of point estimates, interval estimation based on the classic ordinary least-squares method produces the narrowest intervals, outperforming the U-deviation method and linearization, regardless of the confidence level that is chosen.

year: 2011