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Agrarian communities in different regions develop diverse coping strategies to address the environmental changes they face. In this work, we test how to stimulate farmers’ social learning across diverse regions to promote informed responses to soil degradation. We invited 117 randomly selected members of 16 randomly selected Sumatran communities to three 3-day networking and training events in regions with diverse socio-environmental histories. One event was held in the respondents’ remote rural district (Tanggamus), the second was held in a more densely populated region on Sumatra Island (Kalianda), and the third was held in a heavily populated region on Java Island (Garut and Ciamis). Eighteen months later, we surveyed the information-sharing networks and agricultural practices of 370 members of these communities. The participants had become popular sources of agricultural advice, but the strength of this impact depended on the region in which their networking intervention was conducted. The participants in the event on Java had become the most central members of their communities. Although all the participants received the same formal information, those who interacted with the farmers in a region with the longest history of population pressure and land degradation management were more likely to adopt the recommended practices. The participants in this intervention doubled their odds of adopting organic fertilizers compared with those who networked only with peers in their local environment. Environmental memory of coping with change can be shared between regions through social learning, which can be stimulated by simple interventions.

There is a consensus within the international community that replacing traditional fossil energy with renewable energy, such as photovoltaic energy, will help mitigate climate change. However, the literature addressing the rapid development issues of the photovoltaic industry and related carbon dioxide abatement costs is limited. China is currently the largest photovoltaic producer and consumer in the world, hence suitable as our research object. In this paper, a fixed effect panel model with provincial panel data during the period 2012–2016 is applied to study the factors that influence China’s photovoltaic industry. The empirical results indicate that carbon dioxide emission mitigation requirements, government subsidies, technological progress, energy substitution, economic growth, and illumination resources promote the development of the photovoltaic industry. We further adapt the cost estimation model to estimate the average carbon dioxide abatement cost of photovoltaic electric power in China at 679.72 yuan/ton in 2015 and 681.88 yuan/ton in 2016. Compared with wind power and biomass energy, photovoltaic electric power is currently less economical for carbon dioxide emission reduction. Moreover, the future carbon dioxide abatement cost is predicted using a scenario analysis at 118.94–259.42 yuan/ton in 2025 and 42.63–171.95 yuan/ton in 2030. Since the carbon dioxide abatement cost in 2030 is in line with the future price level of the carbon trading market, it will be both economical and feasible to use photovoltaic electric power to decrease carbon dioxide emissions in the future.

Vegetation indices are calculated from reflectance data of discrete spectral bands. The reflectance signal in the visible spectral range is dominated by the optical properties of photosynthetic pigments in plant leaves. Numerous spectral indices have been proposed for the estimation of leaf pigment contents, but the efficacy of different indices for prediction of pigment content and composition for species-rich communities is unknown. Assessing the ability of different vegetation indices to predict leaf pigment content we identify the most suitable spectral indices from an experimental dataset consisting of field-grown high light exposed leaves of 33 angiosperm species collected in two sites in Mallorca (Spain) with contrasting leaf anatomy and pigment composition. Leaf-level reflectance spectra were recorded over the wavelength range of 400 – 900 nm and contents of chlorophyll a, chlorophyll b, total carotenoids, and anthocyanins were measured in 33 species from different plant functional types, covering a wide range of leaf structures and pigment content, five-fold to more than 10-fold for different traits. The best spectral region for estimation of leaf total chlorophyll content with least interference from carotenoids and anthocyanins was the beginning of near-infrared plateau well beyond 700 nm. Leaves of parallel-veined monocots and pinnate-veined dicots had different relationships between vegetation indices and pigments. We suggest that the nature and role of “far-red” chlorophylls which absorb light at longer wavelengths than 700 nm constitute a promising target for future remote sensing studies.

Climate change affects the reproductive life cycles of plants, including pollen production, which has consequences for allergic respiratory diseases. We examined climatic trends at eight locations in Bavaria, Southern Germany, with pollen time series of at least 10 years (up to 30 years in Munich). Climate change in Bavaria was characterized by a rise in temperature, but not during the winter. There is also a trend towards a more continental climate in Bavaria, which is significant in the Alps in the south of the territory. The influence of climate change depended on pollen type. Wind-pollinated arboreal species (e.g. Alnus, Betula and Cupressaceae/Taxaceae) showed advances in the start and end dates of pollen seasons and an increase in pollen load. These changes correlated negatively with late-winter (February) and spring temperatures (April). For herbaceous species, like Poaceae and Urticaceae, an earlier season was observed. Although precipitation is not a limiting factor in Southern Germany, water availability in the spring did influence the magnitude of grass pollen seasons. The effect of climatic change on the characteristics of pollen seasons was also more pronounced at higher altitudes, significant at > 800 m above sea level. Our results show that trends for start, end dates and intensity were similar at all locations, but only statistically significant at some. If we assume that earlier and more intense pollen seasons result in increases in prevalence and severity of allergic diseases, then the effect of climate change on public health in Bavaria may be significant.

Agricultural large-scale land acquisition (LSLA) is a process that is currently not captured by land change models. We present a novel land change modeling approach that includes processes governing LSLAs and simulates their interactions with other land systems. LSLAs differ from other land change processes in two ways: (1) their changes affect hundreds to thousands of contiguous hectares at a time, far surpassing other land change processes, e.g., smallholder agriculture, and (2) as policy makers value LSLA as desirable or undesirable, their agency significantly affects LSLA occurrence. To represent these characteristics in a land change model, we allocate LSLAs as multi-cell patches to represent them at scale while preserving detail in the representation of other dynamics. Moreover, LSLA land systems are characterized to respond to an explicit political demand for LSLA effects, in addition to a demand for various agricultural commodities. The model is applied to simulate land change in Laos until 2030, using three contrasting scenarios: (1) a target to quadruple the area of LSLA, (2) a moratorium for new LSLA, and (3) no target for LSLA. Scenarios yield drastically different land change trajectories despite having similar demands for agricultural commodities. A high level of LSLA impedes smallholders’ engagement with rubber or cash crops, while a moratorium on LSLA results in increased smallholder involvement in cash cropping and rubber production. This model goes beyond existing land change models by capturing the heterogeneity of scales of land change processes and the competition between different land users instigated by LSLA.

Social-ecological changes, brought about by the rapid growth of the aquaculture industry and the increased occurrence of climatic stressors, have significantly affected the livelihoods of coastal communities in Asian mega-deltas. This paper explores the livelihood adaptation responses of households of different wealth classes, the heterogeneous adaptation opportunities, barriers and limits (OBLs) faced by these households and the dynamic ways in which these factors interact to enhance or impede adaptive capacities. A mixed methods approach was used to collect empirical evidence from two villages in coastal Bangladesh. Findings reveal that households’ adaptive capacities largely depend on their wealth status, which not only determine their availability of productive resources, but also empower them to navigate social-ecological change in desirable ways. Households operate within a shared response space, which is shaped by the broader socio-economic and political landscape, as well as their previous decisions that can lock them in to particular pathways. While an adaptive response may be effective for one social group, it may cause negative externalities that can undermine the adaptation options and outcomes of another group. Adaptation OBLs interact in complex ways; the extent to which these OBLs affect different households depend on the specific livelihood activities being considered and the differential values and interests they hold. To ensure more equitable and environmentally sustainable livelihoods in future, policies and programs should aim to expand households’ adaptation space by accounting for the heterogeneous needs and complex interdependencies between response processes of different groups.

How should we measure a household’s resilience to climate extremes, climate change or other evolving threats? As resilience gathers momentum on the international stage, interest in this question continues to grow. So far, efforts to measure resilience have largely focused on the use of ‘objective’ frameworks and methods of indicator selection. These typically depend on a range of observable socio-economic variables, such as levels of income, the extent of a household’s social capital or its access to social safety nets. Yet while objective methods have their uses, they suffer from well-documented weaknesses. This paper advocates for the use of an alternative but complementary method: the measurement of ‘subjective’ resilience at the household level. The concept of subjective resilience stems from the premise that people have an understanding of the factors that contribute to their ability to anticipate, buffer and adapt to disturbance and change. Subjective household resilience therefore relates to an individual’s cognitive and affective self-evaluation of their household’s capabilities and capacities in responding to risk. We discuss the advantages and limitations of measuring subjective household resilience and highlight its relationships with other concepts such as perceived adaptive capacity, subjective well-being and psychological resilience. We then put forward different options for the design and delivery of survey questions on subjective household resilience. While the approach we describe is focused at the household level, we show how it has the potential to be aggregated to inform sub-national or national resilience metrics and indicators. Lastly, we highlight how subjective methods of resilience assessment could be used to improve policy and decision-making. Above all, we argue that, alongside traditional objective measures and indicators, efforts to measure resilience should take into account subjective aspects of household resilience in order to ensure a more holistic understanding of resilience to climate extremes and disasters.

Mangroves are highly productive and changing forests located in the intertidal zone of tropical regions. Leaf litter decomposition represents a substantial part of their carbon sink abilities. Little is known about the potential effect of climate change on this key process of ecosystem functioning. This study compared leaf litter microbial decay between fringe and riverine Avicennia germinans stands. A direct and reciprocal transplant experiment using litterbags was setup in French Guiana to test 3 hypotheses: (i) the activities and abundance of microbial decomposers are lowest in the fringe mangroves due to exposure to saline water and tidal immersion; (ii) for these reasons, litter decomposes faster in riverine stands; and (iii) according to the home-field advantage hypothesis, litter decomposes more rapidly in the environment from which it originates. Remaining litter masses, abundance of litter microbial community (phospholipid fatty acid signatures (PLFA)), and their functional capability (enzyme activities and Biolog) were assessed. Litter directly transplanted in riverine stands showed higher enzymatic activity (+ 77%), catabolic diversity (+ 10%), and microbial biomass (+ 60%) than litter transplanted directly in fringe stands. In contrast, both riverine and fringe derived litter showed faster decay at the fringe (14% mass loss) than riverine site (4% mass loss) between 30 and 45 days. Here, environmental conditions associated with different distances from the sea such as salinity and inundation regimes, rather than microbial features are suggested as main factors affecting decomposition process. Expected sea level rise in the coastal Guianas may therefore modify the mangroves productivity in the coming decades.