A framework for adapting urban forests to climate change

Planting urban trees and expanding urban forest canopy cover are often considered key strategies for reducing climate change impacts in urban areas. However, urban trees and forests can also be vulnerable to climate change through shifts in tree habitat suitability, changes in pests and diseases, and changes in extreme weather events. We developed a three-step framework for urban forest vulnerability assessment and adaptation that scales from regional assessment to local on-the-ground action. We piloted this framework in the Chicago region in 10 locations representing an urban-exurban gradient across a range of socioeconomic capacities. The majority of trees across a seven-county region had low to moderate vulnerability, but many of the least vulnerable species were nonnative invasive species. Urban forests in the 10 pilot locations ranged in vulnerability largely due to differences in economic and organizational adaptive capacity. Adaptation actions selected in these locations tended to focus on increased biodiversity and restoration of natural disturbance regimes. However, adaptation actions in more developed sites also included incorporating new species or cultivars. Lessons learned from the pilot area can be used to inform future efforts in other urban areas.     

A macroeconomic analysis of adaptation to climate change impacts on forests in India

We examine the potential for adaptation to climate change in Indian forests, and derive the macroeconomic implications of forest impacts and adaptation in India. The study is conducted by integrating results from the dynamic global vegetation model IBIS and the computable general equilibrium model GRACE-IN, which estimates macroeconomic implications for six zones of India. By comparing a reference scenario without climate change with a climate impact scenario based on the IPCC A2-scenario, we find major variations in the pattern of change across zones. Biomass stock increases in all zones but the Central zone. The increase in biomass growth is smaller, and declines in one more zone, South zone, despite higher stock. In the four zones with increases in biomass growth, harvest increases by only approximately 1/3 of the change in biomass growth. This is due to two market effects of increased biomass growth. One is that an increase in biomass growth encourages more harvest given other things being equal. The other is that more harvest leads to higher supply of timber, which lowers market prices. As a result, also the rent on forested land decreases. The lower prices and rent discourage more harvest even though they may induce higher demand, which increases the pressure on harvest. In a less perfect world than the model describes these two effects may contribute to an increase in the risk of deforestation because of higher biomass growth. Furthermore, higher harvest demands more labor and capital input in the forestry sector. Given total supply of labor and capital, this increases the cost of production in all the other sectors, although very little indeed. Forestry dependent communities with declining biomass growth may, however, experience local unemployment as a result.     

Regional efforts to mitigate climate change in China: a multi-criteria assessment approach

The task of mitigating climate change is usually allocated through administrative regions in China. In order to put pressure on regions that perform poorly in mitigating climate changes and highlight regions with best-practice climate policies, this study explored a method to assess regional efforts on climate change mitigation at the sub-national level. A climate change mitigation index (CCMI) was developed with 15 objective indicators, which were divided into four categories, namely, emissions, efficiency, non-fossil energy, and climate policy. The indicators’ current level and recent development were measured for the first three categories. The index was applied to assess China’s provincial performance in climate protection based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Empirical results show that the middle Yangtze River area and southern coastal area perform better than other areas in mitigating climate change. The average performance of the northwest area in China is the worst. In addition, climate change mitigation performance has a negative linear correlation with energy self-sufficiency ratio but does not have a significant linear correlation with social development level. Therefore, regional resource endowments had better be paid much more attention in terms of mitigating climate change because regions with good resource endowments in China tend to perform poorly.     

Integrated modelling approaches to analysis of climate change impacts on forests and forest management

This paper reviews integrated economic and ecological models that address impacts and adaptation to climate change in the forest sector. Early economic model studies considered forests as one out of many possible impacts of climate change, while ecological model studies tended to limit the economic impacts to fixed price-assumptions. More recent studies include broader representations of both systems, but there are still few studies which can be regarded fully integrated. Full integration of ecological and economic models is needed to address forest management under climate change appropriately. The conclusion so far is that there are vast uncertainties about how climate change affects forests. This is partly due to the limited knowledge about the global implications of the social and economical adaptation to the effects of climate change on forests.     

Impact of climate change at species level: a case study of teak in India

In this study, we model the long-term effect of climate change on commercially important teak (Tectona grandis) and its productivity in India. This modelling assessment is based on climate projections of the regional climate model of the Hadley Center (HadRM3) and the dynamic vegetation model, IBIS. According to the model projections, 30% of teak grids in India are vulnerable to climate change under both A2 and B2 SRES scenarios because the future climate may not be optimal for teak at these grids. However, the net primary productivity and biomass are expected to increase because of elevated levels of CO₂. Given these directions of likely impacts, it is crucial to further investigate the climate change impacts on teak and incorporate such findings into long-term teak plantation programs. This study also demonstrates the feasibility and limitations of assessing the impact of projected climate change at the species level in the tropics.     

Impact of climate change: an empirical investigation of Malaysian rice production

This paper examines the possible impact of climate change on Malaysian rice production. Using the Ricardian Method and farm household data, we have examined the effects on rice producers focusing on sharecropper adaptations and ecological causes. The principle goal of this research paper is to investigate the impact of climate variables such as temperature, rainfall and precipitation on rice production during main and off seasons, in Kedah, Malaysia. The main purpose of this paper is to examine how climate change affects the net income of paddy farmers in the study area. The statistically significant results show that temperature, rainfall, farm size, educational knowledge, land area and value of labour input have an impact on rice production per hectare revealing potential impacts of climate vulnerability on Malaysian agriculture. The results showed that net revenue increased by Ringgit Malaysia (RM 1= $0.3277) 4.78 per hectare throughout the main seasons as a result of minimal increase in the temperature while there is a decrease of RM 3.02 in the net revenue per hectare during off seasons. During the off season, rainfall increased revenue per hectare by RM 1.32 and during the main season it reduced revenue per hectare by RM 1.01. The evidence from this study may be useful for Malaysian policymakers to facilitate greater preventive measures during the main and off-seasons to counteract climate uncertainty and vulnerability.     

Institutional adaptive capacity and climate change response in the Congo Basin forests of Cameroon

Climate change presents additional challenges to a diverse country like Cameroon that shares the Congo Basin rainforest. Not only is the population vulnerable to the direct effects of climate change, forest-dependent communities are also vulnerable to changing environmental policy that may affect their access to forest resources. Using a qualitative approach to data collection through semi-structured interviews and content analysis of relevant documents, the perception of decision-makers within, and the response of the institutions of the state, the private sector and civil society to the complex challenges of climate change in the Congo Basin forest of Cameroon were analysed. Results indicate that while decision-makers’ awareness of climate change is high, a concrete institutional response is at a very early stage. Cameroon has low adaptive capacity that is further constrained by weak linkages among government institutions nationally and between different levels of government and with communities. Civil society institutions play a role in enhancing government capacity to respond, particularly in relation to new international policies on climate change and forests. Adaptive capacity would be further enhanced by facilitating institutional linkages and coordinating multilevel responses across all boundaries of government, private sector and civil society. A collaborative capacity builder could foster the transfer, receipt and integration of knowledge across the networks, and ultimately build long-term collaborative problem-solving capacity in Cameroon.     

Impact of climate change on regional irrigation water demand in Baojixia irrigation district of China

Water scarcity in China would possibly be aggravated by rapid increase in water demand for irrigation due to climate change. This paper focuses on the mechanism of climate change impact on regional irrigation water demand by considering the dynamic feedback relationships among climate change, irrigation water demand and adaptation measures. The model in implemented using system dynamics approach and employed in Baojixia irrigation district located in Shaanxi Province of China to analyses the changes in irrigation water demand under different climate change scenarios. Obtained results revealed that temperature will be the dominant factor to determine irrigation water demand in the area. An increase of temperature by 1 °C will result in net irrigation water demand to increase by about 12,050?×?10⁴ m³ and gross water demand by about 20,080?×?10⁴ m³ in the area. However, irrigation water demand will not increase at the same rate of temperature rise as the adaptation measures will eventually reduce the water demand increased by temperature rise. It is expected that the modeling approach presented in this study can be used in adopting policy responses to reduce climate change impacts on water resources.     

Potential effects of climate change and rising CO2 on ecosystem processes in northeastern U.S. forests

Forest ecosystems represent the dominant form of land cover in the northeastern United States and are heavily relied upon by the region’s residents as a source of fuel, fiber, structural materials, clean water, economic vitality, and recreational opportunities. Although predicted changes in climate have important implications for a number of ecosystem processes, our present understanding of their long-term effects is poor. In this study, we used the PnET-CN model of forest carbon (C), nitrogen (N) and water cycling to evaluate the effects of predicted changes in climate and atmospheric carbon dioxide (CO₂) on forest growth, C exchange, water runoff, and nitrate ( $ {\text{NO}}^{ - }_{3} $ ) leaching at five forest research sites across the northeastern U.S. We used four sets of statistically downscaled climate predictions from two general circulation models (the Hadley Centre Coupled Model, version 3 and the Parallel Climate Model) and two scenarios of future CO₂ concentrations. A series of model experiments was conducted to examine the effects of future temperature, precipitation, CO₂, and various assumptions regarding the physiological response of forests to these changes. Results indicate a wide range of predicted future growth rates. Increased growth was predicted across deciduous sites under most future conditions, while growth declines were predicted for spruce forests under the warmest scenarios and in some deciduous forests when CO₂ fertilization effects were absent. Both climate and rising CO₂ contributed to predicted changes, but their relative importance shifted from CO₂-dominated to climate-dominated from the first to second half of the twenty-first century. Predicted runoff ranged from no change to a slight decrease, depending on future precipitation and assumptions about stomatal response to CO₂. Nitrate leaching exhibited variable responses, but was highest under conditions that imposed plant stress with no physiological effects of CO₂. Although there are considerable uncertainties surrounding predicted responses to climate change, these results provide a range of possible outcomes and highlight interactions among processes that are likely to be important. Such information can be useful to scientists and land managers as they plan on means of examining and responding to the effects of climate change.     

Contexualising the tool development process through a knowledge brokering approach: The case of climate change adaptation and agriculture

This article applies a ‘knowledge brokering’ approach to contextualise the development of an integrated computer modelling tool into the real world policy context of adaptation of agriculture to climate change at the EU level. In particular, the article tests a number of knowledge brokering strategies described and theorised in the literature, but seldom empirically tested. The article finds that while the policy context can be used to identify a theoretically informed knowledge brokering strategy, in practice a strategy's ‘success’ is more informed by practical considerations, such as whether the tool development process is knowledge or demand driven. In addition, in practice the knowledge brokering process is found to be dynamic and messy, which is not always apparent in the literature. The article goes on to question the perception that there is always a need (or a desire) to bridge the gap between researchers and policy makers in the tool development process. Rather than a problem of design and communication, the science policy interface may be characterised more by a high level of competition between researchers and research organisations to have their tool legitimised by its use in the policy making process.     

Building regional priorities in forests for development and adaptation to climate change in the Congo Basin

Indentifying common priorities in shared natural resource systems constitutes an important platform for implementing adaptation and a major step in sharing a common responsibility in addressing climate change. Predominated by discourses on REDD + (Reduced Emissions from Deforestation and Forest Degradation and conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries) with little emphasis on adaptation there is a risk of lack of policy measures in addressing climate change in the Congo Basin. Forest products and ecosystem services provide security portfolios for the predominantly rural communities, and play major roles in national development programmes in both revenue and employment opportunities. Thus, raising the profile of forests in the policy arena especially in the twin roles of addressing climate change in mitigation and adaptation and achieving resilient development is crucial. Within the framework of the Congo Basin Forests and Climate Change Adaptation project (COFCCA) project, science policy dialogue was conducted to identify and prioritize forest based sectors vulnerable to climate change but important to household livelihoods and national development. The goal of the prioritization process was for the development of intervention in forest as measures for climate change adaptation in Central Africa. Participants constituted a wide range of stakeholders (government, Non Governmental Organizations, research institutions, universities, community leaders, private sectors etc.) as representatives from three countries directly involved in the project: Cameroon, Central African Republic and Democratic Republic of Congo. Building on national priorities, four forest related sectors were identified as common priorities at the regional level for focus on climate change adaptation. These sectors included: (1) energy with emphasis on fuel wood and Charcoal; (2) Water principally quality, quantity, accessibility, etc.; (3) Food with emphasis on Non Timber Forest Products, and (4) Health linked to healthcare products (medicinal plants). Using these prioritized sectors, the project focused on addressing the impacts of climate change on local communities and the development of adaptation strategies in the three pilot countries of the Congo Basin region. The four sectors constitute the key for development in the region and equally considered as priority sectors in the poverty reduction papers. Focused research on these sectors can help to inject the role of forests in national and local development and their potentials contributions to climate change adaptation in national and public discourses. Mainstreaming forest for climate change adaptation into national development planning is the key to improve policy coherence and effectiveness in forest management in the region.     

Adaptation options in agriculture to climate change: a typology

Adaptation in agriculture to climate change is important for impact andvulnerability assessment and for the development of climate change policy. A wide variety of adaptation options has been proposed as having thepotential to reduce vulnerability of agricultural systems to risks related toclimate change, often in an ad hoc fashion. This paper develops atypology of adaptation to systematically classify and characterize agriculturaladaptation options to climate change, drawing primarily on the Canadiansituation. In particular, it differentiates adaptation options in agricultureaccording to the involvement of different agents (producers, industries,governments); the intent, timing and duration of employment of theadaptation; the form and type of the adaptive measure; and the relationshipto processes already in place to cope with risks associated with climatestresses. A synthesis of research on adaptation options in Canadianagriculture identifies four main categories: (i) technological developments,(ii) government programs and insurance, (iii) farm production practices,and (iv) farm financial management. In addition to these `directadaptations', there are options, particularly information provision, that maystimulate adaptation initiatives. The results reveal that most adaptationoptions are modifications to on-going farm practices and public policydecision-making processes with respect to a suite of changing climatic(including variability and extremes) and non-climatic conditions (political,economic and social). For progress on implementing adaptations to climatechange in agriculture there is a need to better understand the relationshipbetween potential adaptation options and existing farm-level andgovernment decision-making processes and risk management frameworks.     

Influence of tree species composition,thinning intensity and climate change on carbon sequestration in Mediterranean mountain forests: a case study using the CO2Fix model

Prediction of future forest carbon (C) stocks as influenced by forest management and climate is a crucial issue in the search for strategies to mitigate and adapt to global change. It is hard to quantify the long-term effect of specific forest practices on C stocks due to the high number of processes affected by forest management. This work aims to quantify how forest management impacts C stocks in Mediterranean mountain forests based on 25 combinations of site index, tree species composition and thinning intensity in three different climate scenarios using the CO2Fix v.3.2 model Masera et al. (Ecol Modell 164:177–199, 2003). The study area is an ecotonal zone located in Central Spain, and the tree species are Scots pine (Pinus sylvestris L.) and Pyrenean oak (Quercus pyrenaica Willd.). Our results show a strong effect of tree species composition and a negligible effect of thinning intensity. Mixed stands have the highest total stand C stocks: 100 % and 15 % more than pure oak and pine stands respectively, and are here suggested as a feasible and effective mitigation option. Climate change induced a net C loss compared to control scenarios, when reduction in tree growth is taken into account. Mixed stands showed the lowest reduction in forest C stocks due to climate change, indicating that mixed stands are also a valid adaptation strategy. Thus converting from pure to mixed forests would enhance C sequestration under both current and future climate conditions.     

Plant trees for the planet: the potential of forests for climate change mitigation and the major drivers of national forest area

Forests are one of the most cost-effective ways to sequester carbon today. Here, I estimate the world’s land share under forests required to prevent dangerous climate change. For this, I combine newest longitudinal data of FLUXNET on forests’ net ecosystem exchange of carbon (NEE) from 78 forest sites (N?=?607) with countries’ mean temperature and forest area. This straightforward approach indicates that the world’s forests sequester 8.3 GtCO₂year^?1. For the 2 °C climate target, the current forest land share has to be doubled to 60.0% to sequester an additional 7.8 GtCO₂year^?1, which demands less red meat consumption. This afforestation/reforestation (AR) challenge is achievable, as the estimated global biophysical potential of AR is 8.0 GtCO₂year^?1 safeguarding food supply for 10 billion people. Climate-responsible countries have the highest AR potential. For effective climate policies, knowledge on the major drivers of forest area is crucial. Enhancing information here, I analyze forest land share data of 98 countries from 1990 to 2015 applying causal inference (N?=?2494). The results highlight that population growth, industrialization, and increasing temperature reduce forest land share, while more protected forest and economic growth generally increase it. In all, this study confirms the potential of AR for climate change mitigation with a straightforward approach based on the direct measurement of NEE. This might provide a more valid picture given the shortcomings of indirect carbon stock-based inventories. The analysis identifies future regional hotspots for the AR potential and informs the need for fast and forceful action to prevent dangerous climate change.

     

The neurobiology of climate change

Directional climate change (global warming) is causing rapid alterations in animals’ environments. Because the nervous system is at the forefront of animals’ interactions with the environment, the neurobiological implications of climate change are central to understanding how individuals, and ultimately populations, will respond to global warming. Evidence is accumulating for individual level, mechanistic effects of climate change on nervous system development and performance. Climate change can also alter sensory stimuli, changing the effectiveness of sensory and cognitive systems for achieving biological fitness. At the population level, natural selection forces stemming from directional climate change may drive rapid evolutionary change in nervous system structure and function.     

A multi-criteria geographic information systems approach for the measurement of vulnerability to climate change

A flexible procedure for the development of a multi-criteria composite index to measure relative vulnerability under future climate change scenarios is presented. The composite index is developed using the Weighted Ordered Weighted Average (WOWA) aggregation technique which enables the selection of different levels of trade-off, which controls the degree to which indicators are able to average out others. We explore this approach in an illustrative case study of the United States (US), using future projections of widely available indicators quantifying flood vulnerability under two scenarios of climate change. The results are mapped for two future time intervals for each climate scenario, highlighting areas that may exhibit higher future vulnerability to flooding events. Based on a Monte Carlo robustness analysis, we find that the WOWA aggregation technique can provide a more flexible and potentially robust option for the construction of vulnerability indices than traditionally used approaches such as Weighted Linear Combinations (WLC). This information was used to develop a proof-of-concept vulnerability assessment to climate change impacts for the US Army Corps of Engineers. Lessons learned in this study informed the climate change screening analysis currently under way.     

The potential of behavioural change for climate change mitigation: a case study for the European Union

Mainstream literature on climate change concentrates overwhelmingly on technological solutions for this global long-term problem, while a change towards climate-friendly behaviour could play a role in emission reduction and has received little attention. This paper focuses on the potential climate mitigation by behavioural change in the European Union (EU) covering many behavioural options in food, mobility and housing demand which do not require any personal up-front investment. We use the Global Change Assessment Model (GCAM), capturing both their direct and indirect implications in terms of greenhouse gas emissions. Our results indicate that modest to rigorous behavioural change could reduce per capita footprint emissions by 6 to 16%, out of which one fourth will take place outside the EU, predominantly by reducing land use change. The domestic emission savings would contribute to reduce the costs of achieving the internationally agreed climate goal of the EU by 13.5 to 30%. Moreover, many of these options would also yield co-benefits such as monetary savings, positive health impacts or animal wellbeing. These results imply the need for policymakers to focus on climate education and awareness programs more seriously and strategically, making use of the multiple co-benefits related with adopting pro-environmental behaviour. Apart from that, the relevance of behavioural change in climate change mitigation implies that policy-informing models on climate change should include behavioural change as a complement or partial alternative to technological change.     

Land use change and forestry climate project regional baselines: a review

Climate change programs have largely used the project-specific approach for estimating baseline emissions of climate mitigation projects. This approach is subjective, lacks transparency, can generate inconsistent baselines for similar projects, and is likely to have high transaction costs. The use of regional baselines, which partially addresses these issues, has been reported in the literature on forestry and agriculture projects, and in greenhouse gas (GHG) mitigation program guidance for them (e.g., WRI/WBCSD GHG Project Protocol, USDOE’s 1605(b) registry, UNFCCC’s Clean Development Mechanism). This paper provides an assessment of project-specific and regional baselines approaches for key baseline tasks, using project and program examples. The regional experience to date is then synthesized into generic steps that are referred to as Stratified Regional Baselines (SRB). Regional approaches generally, and SRB in particular explicitly acknowledge the heterogeneity of carbon density, land use change, and other key baseline driver variables across a landscape. SRB focuses on providing guidance on how to stratify lands into parcels with relatively homogeneous characteristics to estimate conservative baselines within a GHG assessment boundary, by applying systematic methods to determine the boundary and time period for input data.