How Harmful are Adaptation Restrictions

The dominant assumption in economic models of climate policy remains that adaptation will be implemented in an optimal manner. There are, however, several reasons why optimal levels of adaptation may not be attainable. This paper investigates the effects of suboptimal levels of adaptation, i.e. adaptation restrictions, on the composition and level of climate change costs and on welfare. Several adaptation restrictions are identified and then simulated in a revised DICE model, extended with adaptation (AD-DICE). We find that especially substantial over-investment in adaptation can be very harmful due to sharply increasing marginal adaptation costs. Furthermore the potential of mitigation to offset suboptimal adaptation is investigated. When adaptation is not possible at extreme levels of climate change, it is cost-effective to use more stringent mitigation policies in order to keep climate change limited, thereby making adaptation possible. Furthermore not adjusting the optimal level of mitigation to these adaptation restrictions may double the costs of adaptation restrictions, and thus in general it is very harmful to ignore existing restrictions on adaptation when devising (efficient) climate policies.Integrated Assessment Modelling, Adaptation, Climate Change

The Role of Proactive Adaptation in International Climate Change Mitigation Agreements

This paper investigates the role of proactive adaptation in international mitigation coalition formation. Adaptation is introduced into a three stage cartel game of coalition formation. We analytically derive the optimal level of mitigation and proactive adaptation for the singletons and coalition members. We introduce the AD-STACO model which is constructed based on the STACO model, which is an applied three-stage cartel formation model with 12 heterogenous regions. Simulating all possible coalitions (4084) and checking for internal and external stability, we investigate how different levels of proactive adaptation will affect the payoffs in Grand coalition and the incentives to freeride. We examine which stable coalitions are found with different levels of proactive adaptation and whether regions can gain from overadaptation in the best performing stable coalition. We find that though payoffs increase in the Grand coalition with lower adaptation, incentives to leave increase. Coalition members can increase their payoffs through overadaptation.N/A

Sheep and wool industries need to improve their performance

Today in Western Australia, sheep are run at slightly higher stocking rates, are achieving greater lambing percentages (up JO per cent) and higher wool cuts per animal ( up 0. 6 kg greasy) than in the 1960s. When all components of production are considered, the productivity of sheep fanns has increased by 2. 7 per cent per year over the past 35 years. The challenge of the next decade is to achieve substantially greater rates of improvement than for past years if the sheep and wool industries are to maintain their significant place in Western Australian agriculture

New insights into the management of ewes over summer and autumn

Recent research in Western Australia has provided new information on the effects of liveweight and liveweight change on wool production and quality, as well as lamb survival and growth. Liveweight and liveweight change in sheep reflect the animals\u27 nutritional status, and this in turn directly influences their wool production and reproductive performance. The under-nutrition of sheep not only has an immediate effect on the animal\u27s performance, but the research showed that it also produces a significant carry-over effect on wool and lamb production, even if the ewes have returned to good feed. These findings suggest that for the efficient management of breeding ewes over the dry feed period, a representative sample of the flock (40 ewes or 10 per cent, whichever is the greater) should be weighed and condition scored regularly. Grazing management and/or supplements can then be adjusted to meet the production objectives for the ew

AD-DICE: an implementation of adaptation in the DICE model

Integrated Assessment Models (IAMS) have helped us over the past decade to understand the interactions between the environment and the economy in the context of climate change. Although it has also long been recognized that adaptation is a powerful and necessary tool to combat the adverse effects of climate change, most IAMs have not explicitly included the option of adaptation in combating climate change. This paper adds to the IAM and climate change literature by explicitly including adaptation in an IAM, thereby making the trade-offs between adaptation and mitigation visible. Specifically, a theoretical framework is created and used to implement adaptation as a decision variable into the DICE model. We use our new AD-DICE model to derive the adaptation cost functions implicit in the DICE model. In our set-up, adaptation and mitigation decisions are separable and AD-DICE can mimic DICE when adaptation is optimal. We find that our specification of the adaptation costs is robust with respect to the mitigation policy scenarios. Our numerical results show that adaptation is a powerful option to combat climate change, as it reduces most of the potential costs of climate change in earlier periods, while mitigation does so in later periods.integrated assessment modelling, adaptation, climate change

International Cooperation on Climate Change Adaptation from an Economic Perspective

This paper investigates the economic incentives of countries to cooperate on international adaptation financing. Adaptation is generally implicitly incorporated in the climate change damage functions as used in Integrated Assessment Models. We replace the implicit decision on adaptation with explicit adaptation in a multi-regional setting by using an adjusted RICE model. We show that making adaptation explicit will not affect the optimal mitigation path when adaptation is set at its optimal level. Sub-optimal adaptation will, however, change the optimal mitigation path. Furthermore this paper studies for different forms of cooperation what effects international adaptation transfers will have on (i) domestic adaptation and (ii) the optimal mitigation path. Adaptation transfers will fully crowd out domestic adaptation in a first best setting. Transfers will decrease overall mitigation in our numerical simulations. An analytical framework is used to analyse the most important mechanisms and a numerical model is used to assess the magnitude of effects.Climate Change, Adaptation Funding, Integrated Assessment Modeling

Relating satellite imagery with grain protein content

Satellite images, captured during the growing seasons of barley, sorghum and wheat were analysed to establish a relationship between the spectral response and the harvested grain protein content. This study was conducted near Jimbour (approx. 151°10’E and 27°05’S) in southern Queensland. Grain protein contents of the geo-referenced samples, collected manually during the harvest, were determined using a laboratory-based near-infrared spectrophotometer. Grain protein contents in grain varied between 7.4–15.2% in barley, 6.2– 10.6% in sorghum and 13.1–15.6% in wheat. The Landsat images of 18 September 1999 (a week after barley flowering), 5 March 2000 (three weeks before sorghum harvest), and 15 August 2001 (two weeks before wheat flowering) were analysed. Additionally, an ASTER image of 24 September 2001 (three weeks after wheat flowering) was also examined. Digital numbers, extracted from raw image bands and derived indices, were correlated with grain protein contents. The grain protein content in barley was correlated strongly (r>0.80) with bands 2, 4 and 5 of the Landsat scene, first principal component, and the tasselled cap brightness and greenness indices. Similarly, wheat protein content was well correlated (r>0.75) with the near infrared band (band 4) of the Landsat scene, first principal component, and the tasselled cap brightness, greenness and wetness indices. The band 3 (near infrared band) of the ASTER image, captured well after flowering, was moderately correlated (r<0.5) with the protein content of the wheat. However, the grain protein content in sorghum was found poorly correlated (r<0.20) with Landsat image bands and indices. Results indicate that it may be possible to use certain bands and indices of the satellite images, captured around the time of flowering, to predict grain protein content of barley and wheat crops