What drives farmers to make top-down or bottom-up adaptation to climate change and fluctuations?:A comparative study on 3 cases of apple farming in Japan and South Africa

Agriculture is one of the most vulnerable sectors to climate change. Farmers have been exposed to multiple stressors including climate change, and they have managed to adapt to those risks. The adaptation actions undertaken by farmers and their decision making are, however, only poorly understood. By studying adaptation practices undertaken by apple farmers in three regions: Nagano and Kazuno in Japan and Elgin in South Africa, we categorize the adaptation actions into two types: farmer initiated bottom-up adaptation and institution led top-down adaptation. We found that the driver which differentiates the type of adaptation likely adopted was strongly related to the farmers' characteristics, particularly their dependence on the institutions, e.g. the farmers' cooperative, in selling their products. The farmers who rely on the farmers' cooperative for their sales are likely to adopt the institution-led adaptation, whereas the farmers who have established their own sales channels tend to start innovative actions by bottom-up. We further argue that even though the two types have contrasting features, the combinations of the both types of adaptations could lead to more successful adaptation particularly in agriculture. This study also emphasizes that more farm-level studies for various crops and regions are warranted to provide substantial feedbacks to adaptation policy

Arctic climate change with a 2 ∘C global warming: Timing, climate patterns and vegetation change

The signatories to United Nations Framework Convention on Climate Change are charged with stabilizing the concentrations of greenhouse gases in the atmosphere at a level that prevents dangerous interference with the climate system. A number of nations, organizations and scientists have suggested that global mean temperature should not rise over 2 ∘C above preindustrial levels. However, even a relatively moderate target of 2 ∘C has serious implications for the Arctic, where temperatures are predicted to increase at least 1.5 to 2 times as fast as global temperatures. High latitude vegetation plays a significant role in the lives of humans and animals, and in the global energy balance and carbon budget. These ecosystems are expected to be among the most strongly impacted by climate change over the next century. To investigate the potential impact of stabilization of global temperature at 2 ∘C, we performed a study using data from six Global Climate Models (GCMs) forced by four greenhouse gas emissions scenarios, the BIOME4 biogeochemistry-biogeography model, and remote sensing data. GCM data were used to predict the timing and patterns of Arctic climate change under a global mean warming of 2 ∘C. A unified circumpolar classification recognizing five types of tundra and six forest biomes was used to develop a map of observed Arctic vegetation. BIOME4 was used to simulate the vegetation distributions over the Arctic at the present and for a range of 2 ∘C global warming scenarios. The GCMs simulations indicate that the earth will have warmed by 2 ∘C relative to preindustrial temperatures by between 2026 and 2060, by which stage the area-mean annual temperature over the Arctic (60-90∘N) will have increased by between 3.2 and 6.6 ∘C. Forest extent is predicted by BIOME4 to increase in the Arctic on the order of 3 × 106 km2 or 55% with a corresponding 42% reduction in tundra area. Tundra types generally also shift north with the largest reductions in the prostrate dwarf-shrub tundra, where nearly 60% of habitat is lost. Modeled shifts in the potential northern limit of trees reach up to 400 km from the present tree line, which may be limited by dispersion rates. Simulated physiological effects of the CO2 increase (to ca. 475 ppm) at high latitudes were small compared with the effects of the change in climate. The increase in forest area of the Arctic could sequester 600 Pg of additional carbon, though this effect is unlikely to be realized over next centur

Healthcare Management Primer

This primer was written by students enrolled in HMP 721.01, Management of Health Care Organizations, in the Health Management & Policy Program, College of Health and Human Services, University of New Hampshire. This course was taught by Professor Mark Bonica in Fall 2017

Collaboration Relations in Climate Information Production and Dissemination to Subsistence Farmers in Namibia

Although climate information can aid farmers' capacity to adapt to climate change, its accessibility and adoption by subsistence farmers hinge on the collaboration between farmers and climate information providers. This paper examines collaborations among actors in the process of climate information production and dissemination in the Namibian agricultural sector. The aim is to investigate the extent to which subsistence farmers are integrated into the collaboration process and the impact of the collaboration on the nature and accessibility of disseminated information. Key informant interviews and a questionnaire survey were used for data collection. Using network analysis, we estimated the networks' density, clustering coefficient, and degree centrality. The study found that both the climate information production and dissemination networks have a high overall clustering coefficient (78% and 77%, respectively) suggesting a high rate of collaboration among the actors in the networks. However, the frequency of interactions between the actors in both the information production and dissemination networks and subsistence farmers remains very low. Nearly all surveyed farmers reported that they meet with information providers only once in a year. The effect of this poor interaction is reflected in the poor occurrence of feedback learning, which is needed to optimize channels of information dissemination to subsistence farmers and enhance the robustness of disseminated information. We recommend innovative communication means via mobile phone, promotion of peer-to-peer learning, flexible collaboration relations with more space for feedback from the users of climate information, and more attention to long-term forecasts and their implications for adaptive actions

Evaluating the Effectiveness and Efficiency of Climate Information Communication in the African Agricultural Sector: A Systematic Analysis of Climate Services

The use of climate services (CS) for the provisioning of climate information for informed decision-making on adaptation action has gained momentum. However, a comprehensive review of the literature to evaluate the lessons and experiences of CS implementation in the African agriculture sector is still lacking. Here, we present a systematic review (mapping) of 50 pieces of literature documenting lessons and experiences of CS adoption in the agriculture sector of 20 African countries. The qualitative analysis of the reviewed literature revealed: (1) CS implementation overwhelmingly relied on a participatory process through workshops and participatory scenario planning meetings to connect users with actors along the CS value chain of forecast production, translation, integration, and application. Additionally, innovations such as mobile phones and internet service are increasingly being integrated with CS to strengthen the relationship between CS providers and users. They are, however, mostly at the trial stage and tend to have a varying impact depending on available facilities and infrastructure in the community. (2) Although there is a growing recognition of the need for the integration of indigenous and scientific knowledge systems in the production of climate information, such integration is currently not happening. Rather, indigenous knowledge holders are engaged in a participatory process for insight on modalities of making scientific climate information locally relevant and acceptable. Given the aforementioned findings, we recommend further research on modalities for facilitating indigenous knowledge mainstreaming in climate information production, and investigation of options for using innovations (e.g., mobile) to enhance the interactions between CS users and CS providers. Such research will play a great role in scaling up the adoption of CS in the African agricultural sector

Observed and modelled trends in rainfall and temperature for South Africa: 1960-2010

Observed trends in seasonal and annual total rainfall, number of rain days and daily maximum and minimum temperature were calculated for a number of stations in South Africa for the period 1960-2010. Statistically significant decreases in rainfall and the number of rain days are shown over the central and northeastern parts of the country in the autumn months and significant increases in the number of rain days around the southern Drakensberg are evident in spring and summer. Maximum temperatures have increased significantly throughout the country for all seasons and increases in minimum temperatures are shown for most of the country. A notable exception is the central interior, where minimum temperatures have decreased significantly. Regionally aggregated trends for six water management zones covering the entire country are not evident for total rainfall, but there are some significant trends for the number of rain days. Temperature in these zones has increased significantly for most seasons, with the exception of the central interior. Comparison of the observed trends with statistically downscaled global climate model simulations reveals that the models do not represent the observed rainfall changes nor the cooling trend of minimum temperature in the central interior. Although this result does not rule out the possibility of attributing observed local changes in rainfall to anthropogenically forced global change, it does have major implications for attribution studies. It also raises the question of whether an alternative statistical downscaling method or dynamical downscaling through the use of a regional climate model might better represent regional and local climatic processes and their links to global change

The Effect of Inter-Organisational Collaboration Networks on Climate Knowledge Flows and Communication to Pastoralists in Kenya

In Kenya, pastoralists have utilized natural grasslands using practices that often result in overgrazing, low productivity and low income. Such practices have caused environmental problems, which could be exacerbated by climate change. Although knowledge on practices that increase pastoralists’ capacity to adapt to climate and environmental challenges is currently available, the adoption rate remains poor. Hence, there is growing interest in understanding how cross-scale inter-organizational collaboration process either facilitates or hinders climate knowledge communications to and uptake by pastoralists. This study used network analysis to identify how inter-organizational collaborations in knowledge production and dissemination shape knowledge flow and communication to pastoralists in Kenya. A knowledge mapping workshop, key informant interviews and questionnaire surveys were used to identify the key organizations involved in the generation, brokering, and dissemination of adaptation knowledge to pastoralists. Two networks of configurations were explored: (i) relations of collaboration in knowledge production and (ii) relations of collaboration in knowledge dissemination. Measure of clustering coefficient, density, core-periphery location, and degree centrality were used to analyze the network structure and cohesion, and its influence on knowledge flow and adoption. Findings revealed a strong integration across the network with research institutes, NGOs (Non-governmental organizations), and CBOs (Community based organizations) identified as among the central actors, based on their degree centrality. Further, we observed a higher density of ties among actors in the knowledge production network than the dissemination network. The lower density of the dissemination network indicates there are not that many activities by key organizations aimed at ensuring that knowledge reaches the users, compared to activities related to knowledge generation. This also results in poor feedback processes from local pastoralists to knowledge generators and brokers. Knowledge transfer and uptake could therefore be enhanced by improving dissemination activities and feedback mechanisms in the dissemination network as a means of capturing pastoralist perspectives on the relevance, reliability, and usability of knowledge for action. Reflection and revision can be used to improve knowledge so that it is more in sync with a pastoralist context

Southern African summer-rainfall variability, and its teleconnections, on interannual to interdecadal timescales in CMIP5 models

23 pagesInternational audienceThis study provides the first assessment of CMIP5 model performances in simulating southern Africa (SA) rainfall variability in austral summer (Nov–Feb), and its teleconnections with large-scale climate variability at different timescales. Observed SA rainfall varies at three major timescales: interannual (2–8 years), quasi-decadal (8–13 years; QDV) and interdecadal (15–28 years; IDV). These rainfall fluctuations are, respectively, associated with El Niño Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO), interacting with climate anomalies in the South Atlantic and South Indian Ocean. CMIP5 models produce their own variability, but perform better in simulating interannual rainfall variability, while QDV and IDV are largely underestimated. These limitations can be partly explained by spatial shifts in core regions of SA rainfall variability in the models. Most models reproduce the impact of La Niña on rainfall at the interannual scale in SA, in spite of limitations in the representation of ENSO. Realistic links between negative IPO are found in some models at the QDV scale, but very poor performances are found at the IDV scale. Strong limitations, i.e. loss or reversal of these teleconnections, are also noted in some simulations. Such model errors, however, do not systematically impact the skill of simulated rainfall variability. This is because biased SST variability in the South Atlantic and South Indian Oceans strongly impact model skills by modulating the impact of Pacific modes of variability. Using probabilistic multi-scale clustering, model uncertainties in SST variability are primarily driven by differences from one model to another, or comparable models (sharing similar physics), at the global scale. At the regional scale, i.e. SA rainfall variability and associated teleconnections, while differences in model physics remain a large source of uncertainty, the contribution of internal climate variability is increasing. This is particularly true at the QDV and IDV scales, where the individual simulations from the same model tend to differentiate, and the sampling error increase

Temperature and precipitation extremes under current, 1.5°C and 2.0°C global warming above pre-industrial levels over Botswana, and implications for climate change vulnerability

Climate extremes are widely projected to become more severe as the global climate continues to warm due to anthropogenic greenhouse gas emissions. These extremes often cause the most severe impacts on society. Therefore, the extent to which the extremes might change at regional level as the global climate warms from current levels to proposed policy targets of 1.5 and 2.0 °C above preindustrial levels need to be understood to allow for better preparedness and informed policy formulation. This paper analysed projected changes in temperature and precipitation extremes over Botswana at 1.0, 1.5 and 2.0 °C warming, a country highly vulnerable to the impacts of climate change. Projected changes in temperature extremes are significantly different from each other at the three levels of global warming. Specifically, at 2.0 °C global warming, relative to preindustrial, for the ensemble median: (a) country average Warm Spell Duration Index (WSDI) ensemble median increases ensemble range by 80, 65, 62 days per year across different climatic zones, approximately three times the change at 1.0 °C and twice the change at 1.5 °C; (b) cold night (TN10P) and cold day (TX10P) frequencies decrease by 12 and 9 days per year across all regions, respectively, while hot nights (TN90P) and hot days (TX90P) both increase by 8-9 days across all regions. Projected changes in drought related indices also distinct at different warming levels. Specifically: (a) projected mean annual precipitation decreases across the country by 5-12% at 2°C, 3-8% at 1.5 °C and 2-7% at 1.0 °C; (b) the dry spell length (ALTCDD) increases by 15-19 days across the three climatic zones at 2.0 °C, about three (two) times as much as the increase at 1.0 (1.5) °C. Ensemble mean projections are for increases in heavy rainfall indices, but not statistically significant. The implications of these changes for key socio-economic sectors are explored, and reveal progressively severe impacts, and consequent adaptation challenges for Botswana as the global climate warms from its present temperature of 1.0 °C above preindustrial levels to 1.5, and then 2.0 °C

The flora of Plum Island, Essex County, Massachusetts, Station Bulletin, no.513

The Bulletin is a publication of the New Hampshire Agricultural Experiment Station, College of Life Sciences and Agriculture, University of New Hampshire, Durham, New Hampshire