Enhancing adaptation outcomes for transformation: climate change in the Australian wine industry

Fleming, Aysha; Park, Sarah E.; Marshall, Nadine

doi:10.1080/09571264.2015.1031883

Cited by 22 publications

(27 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 6 describes the ANOVA results representing BM (between mean squares of all groups) and WM (within mean square of a group) and theirstatistics value for each dataset. We observed that the -test statistic exceeds the significance level of crit (0.05) in all cases except healthy voice data and heart rate variability data (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24). For example, for US Climate dataset as seen by the ANOVA test, the calculated -test statistic (5.10) is greater than -critical.…”

mentioning

confidence: 95%

“…It is done by grouping the CPR values into three categories as (a) strongly related (CT = 1), (b) moderately related (CT = 0), and (c) weakly related (CT = −1) using (13). CPR values are calculated using (4) along with the number of pairs for which the CPR value has to be calculated using (12).…”

Section: Connectivity Trend Analysismentioning

confidence: 99%

“…It has many applications to agriculture [2,3], fisheries, ecosystems, water resources, energy infrastructure, business [2,4], food industry [2,5,6], and disaster planning. In addition, climate impacts have also been assessed in potato [7], maize [8], coffee [9], rice [10], sugar [11], wine grape production [12], and so forth. For example, climate change eventually increases the additional price for the agricultural crops such as rice, wheat, maize, and soya beans, which tends to cause a higher substantial fall in cereals consumption.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, for regions of China, the result indicates that there exists a significant gap between the eight climate regions of China, which demonstrates the effectiveness and reliability of the recurrence based approach in significant climate change recognition in the US and China. In the case of healthy voice data and heart rate variability data (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24), the calculated -test statistic is less than -critical. This -value indicates similarity within a group (i.e., the same group of people have fewer changes in voice and heart rate).…”

mentioning

confidence: 99%

See 3 more Smart Citations

Recurrence Based Similarity Identification of Climate Data

Bai

Hira²,

Parag

2017

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

Climate change has become a challenging and emerging research problem in many research related areas. One of the key parameters in analyzing climate change is to analyze temperature variations in different regions. The temperature variation in a region is periodic within the interval. Temperature variations, though periodic in nature, may vary from one region to another and such variations are mainly dependent on the location and altitude of the region and also on other factors like the nearness of sea and vegetation.In this paper, we analyze such periodic variations using recurrence plot (RP), cross recurrence plot (CRP), recurrence rate (RR), and correlation of probability of recurrence (CPR) methods to find similarities of periodic variations between and within climatic regions and to identify their connectivity trend. First, we test the correctness of our method by applying it on voice and heart rate data and then experimentation is performed on synthetic climate data of nine regions in the United States and eight regions in China. Finally, the accuracy of our approach is validated on both real and synthetic datasets and demonstrated using ANOVA, Kruskal-Wallis, and z-statistics significance tests.

show abstract

mentioning

confidence: 95%

Section: Connectivity Trend Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Recurrence Based Similarity Identification of Climate Data

Bai

Hira²,

Parag

2017

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

show abstract

“…The latter has been found to impede pro-environmental behavior in certain circumstances (Gifford, 2011) and facilitate it in others (Devine-Wright, 2009;Scannell and Gifford, 2010), and may serve to support incremental strategies but act as a constraint to transformation. Marshall et al (2012Marshall et al ( , 2013 and Marshall and Stokes (2014) found that values of identity and place acted as significant barriers to transformative capacity in the Australian agricultural industry (see also Fleming et al, 2015). Where strong attachment to place exists, individuals are likely to assess transformative change as a threat to place identity and may resist unwanted change (DevineWright, 2009;Anton and Lawrence, 2016).…”

Section: Social and Cultural Barriersmentioning

confidence: 99%

Barriers to Transformative Adaptation: Responses to Flood Risk in Ireland

2016

View full text Add to dashboard Cite

Barriers to climate change adaptation have received increased attention in recent years as researchers and policymakers attempt to understand their complex and interdependent nature and identify strategies for overcoming them. To date however, there is a paucity of research on barriers to transformative adaptation. Using two case studies of flood risk management from Ireland we identify and characterize barriers to transformative adaptation. Qualitative semistructured interviews were conducted with key stakeholders connected to proposed transformative strategies in Skibbereen, County Cork and Clontarf, County Dublin. Across both case studies, where transformative strategies failed to materialize, we highlight three significant barriers that impede transformation including: i) social and cultural values, particularly place attachment and identity; ii) institutional reliance on technical expertise which fails to look beyond traditional technocratic approaches and; iii) institutional regulatory practices. Findings illustrate that where social or institutional barriers emerge, transformation may more likely succeed through a series of incremental changes, which culminate in transformation. This research has practical implications for future adaptation planning as facilitating transformation through incrementalism requires flexible adaptation strategies that are responsive to changing social values over time. While focused on flood risk management, our findings have applicability for other sectors adapting to climate change.

show abstract

Transformational adaptation of agricultural systems to climate change

Panda

2018

WIREs Climate Change

View full text Add to dashboard Cite

This study explores the increasing use of the concept of "transformational adaptation" (TA) in the context of agriculture, analyzing its conceptualization and applications. While TA is appealing as a concept that involves the implementation of adaptation actions in different ways through small adjustments from current technological and economic approaches, it also raises questions about the complexity of transforming agricultural systems. Although current scientific evidence finds some patterns of climate change impacts on agriculture in the future that can inform the analysis of where and when transformation is required, this evidence is not enough to fully inform practical decision-making at different scales. Part of the problem may be that there has been not enough empirical research focusing on transformational agriculture. For example, from 93 articles in the literature, 39% focus on understanding the concept of TA, 32% focus on analytical and applied aspects of TA, including studies applying global climate models to analyze TA at regional and global scales and to identify broad patterns of TA in agriculture, and only 16% have tried to understand TA from an empirical perspective. While the number of empirical studies of TA is still increasing, there are other issues of TA that have received limited attention, including uncertainty of climate change impacts, policy implications, the transition process, the role of technological innovations, and barriers to TA.

show abstract

Enhancing adaptation outcomes for transformation: climate change in the Australian wine industry

Cited by 22 publications

References 41 publications

Recurrence Based Similarity Identification of Climate Data

Recurrence Based Similarity Identification of Climate Data

Barriers to Transformative Adaptation: Responses to Flood Risk in Ireland

Transformational adaptation of agricultural systems to climate change

Contact Info

Product

Resources

About