Agricultural adaptation to climate change: insights from a farming community in Sri Lanka

The vulnerability of smallholder farmers to climate change and variability is increasingly rising. As agriculture is the only source of income for most of them, agricultural adaptation with respect to climate change is vital for their sustenance and to ensure food security. In order to develop appropriate strategies and institutional responses, it is necessary to have a clear understanding of the farmers’ perception of climate change, actual adaptations at farm-level and what factors drive and constrain their decision to adapt. Thus, this study investigates the farm-level adaptation to climate change based on the case of a farming community in Sri Lanka. The findings revealed that farmers’ perceived the ongoing climate change based on their experiences. Majority of them adopted measures to address climate change and variability. These adaptation measures can be categorised into five groups, such as crop management, land management, irrigation management, income diversification, and rituals. The results showed that management of non-climatic factors was an important strategy to enhance farmers’ adaptation, particularly in a resource-constrained smallholder farming context. The results of regression analysis indicated that human cognition was an important determinant of climate change adaptation. Social networks were also found to significantly influence adaptation. The study also revealed that social barriers, such as cognitive and normative factors, are equally important as other economic barriers to adaptation. While formulating and implementing the adaptation strategies, this study underscored the importance of understanding socio-economic, cognitive and normative aspects of the local communities.     

An Integrated Assessment of Climate Change and the Accelerated Introduction of Advanced Energy Technologies - An Application of MiniCAM 1.0

We report results from the application of an integrated assessment model, MiniCAM 1.0. The model is employed to explore the full range of climate change implications of the successful development of cost effective, advanced, energy technologies. These technologies are shown to have a profound effect on the future magnitude and rate of anthropogenic climate change. We find that the introduction of assumptions developed by a group of ‘bottom-up’ modelers for the LEESS scenarios into a ‘top-down’ model, the Edmonds-Reilly-Barns Model, leads to ‘top down’ emissions trajectories similar to those of the LEESS. The cumulative effect of advanced energy technologies is to reduce annual emissions from fossil fuel use to levels which stabilize atmospheric concentrations below 550 ppmv. While all energy technologies play roles, the introduction of advanced biomass energy production technology is particularly important. The consideration of all greenhouse related anthropogenic emissions, and in particular sulfur dioxide, is found to be important. We find that the consideration of sulfur dioxide emissions coupled to rapid reductions in carbon dioxide emissions leads to higher global mean temperatures prior to 2050 than in the reference case. This result is due to the short-term cooling impact of sulfate aerosols, which dominates the long-term warming impact of CO₂ and CH₄ in the years prior to 2050. We also show that damage calculations which use only mean global temperature and income may be underestimating damages by up to a factor of five. Disaggregating income reduces this to a factor of two, still a major error. Finally, the role of the discount rate is shown to be extraordinarily important to technology preference.     

Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.     

Energy-dispersive X-ray fluorescence systems as analytical tool for assessment of contaminated soils

To determine the heavy metal content in soil samples at contaminated locations, a static and time consuming procedure is used in most cases. Soil samples are collected and analyzed in the laboratory at high quality and high analytical costs. The demand by government and consultants for a more dynamic approach and by customers requiring performances in which analyses are performed in the field with immediate feedback of the analytical results, is growing. Especially during the follow-up of remediation projects or during the determination of the sampling strategy, field analyses are advisable. For this purpose four types of ED-XRF systems, ranging from portable up to high performance laboratory systems, have been evaluated. The evaluation criteria are based on the performance characteristics for all the ED-XRF systems such as limit of detection, accuracy and the measurement uncertainty on one hand, and also the influence of the sample pretreatment on the obtained results on the other hand. The study proved that the field portable system and the bench top system, placed in a mobile van, can be applied as field techniques, resulting in semi-quantitative analytical results. A limited homogenization of the analyzed sample significantly increases the representativeness of the soil sample. The ED-XRF systems can be differentiated by their limits of detection which are a factor of 10 to 20 higher for the portable system. The accuracy of the results and the measurement uncertainty also improved using the bench top system. Therefore, the selection criteria for applicability of both field systems are based on the required detection level and also the required accuracy of the results.     

Soil nitrogen transformations under elevated atmospheric CO₂ and O₃ during the soybean growing season

We investigated the influence of elevated CO₂ and O₃ on soil N cycling within the soybean growing season and across soil environments (i.e., rhizosphere and bulk soil) at the Soybean Free Air Concentration Enrichment (SoyFACE) experiment in Illinois, USA. Elevated O₃ decreased soil mineral N likely through a reduction in plant material input and increased denitrification, which was evidenced by the greater abundance of the denitrifier gene nosZ. Elevated CO₂ did not alter the parameters evaluated and both elevated CO₂ and O₃ showed no interactive effects on nitrifier and denitrifier abundance, nor on total and mineral N concentrations. These results indicate that elevated CO₂ may have limited effects on N transformations in soybean agroecosystems. However, elevated O₃ can lead to a decrease in soil N availability in both bulk and rhizosphere soils, and this likely also affects ecosystem productivity by reducing the mineralization rates of plant-derived residues.     

Contaminants in the coastal karst aquifer system along the Caribbean coast of the Yucatan Peninsula, Mexico

Intensive land development as a result of the rapidly growing tourism industry in the “Riviera Maya” region of the Yucatan Peninsula, Mexico may result in contamination of groundwater resources that eventually discharge into Caribbean coastal ecosystems. We deployed two types of passive sampling devices into groundwater flowing through cave systems below two communities to evaluate concentrations of contaminants and to indicate the possible sources. Pharmaceuticals and personal care products accumulated in the samplers could only have originated from domestic sewage. PAHs indicated contamination by runoff from highways and other impermeable surfaces and chlorophenoxy herbicides accumulated in samplers deployed near a golf course indicated that pesticide applications to turf are a source of contamination. Prevention and mitigation measures are needed to ensure that expanding development does not impact the marine environment and human health, thus damaging the tourism-based economy of the region.     

Emission factors for high-emitting vehicles based on on-road measurements of individual vehicle exhaust with a mobile measurement platform

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO(x)), and particle mass with aerodynamic diameter below 2.5 microm (PM2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO(x), black carbon (BC), PM2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO(x) and CO fleet-average emission factors and more than 60% of PM2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM2.5, and NO(x) tended to cluster among the same vehicles.     

To preserve or to develop? East Bay dredging project,South Caicos,Turks and Caicos Islands

The Turks and Caicos Islands are currently in the midst of an economic revolution from a marine-based provisional economy to a tourism economy. East Bay, South Caicos, is currently under construction with plans for a 160-unit condominium complex. Included in the project plan is removal of seagrass beds in front of the development to make a sandy beach for tourists. The aims of this study were to (i) describe the bathymetry and benthic habitat coverage of East Bay before dredging takes place and (ii) perform an economic valuation on the turtle grass beds that will be dredged using ecosystem valuation and emergy analysis techniques. The bathymetry survey revealed shallow waters (<1.5 m) until the reef drop off (～650 m offshore). Benthic habitat exhibits zonation following the general progression: sand plain, algal plain, seagrass, coral rubble and seagrass, rock and turf algae, and reef flat. Ecosystem services valued the proposed dredging area at USD $28,807 per year, compared to emergy analysis, which valued the proposed dredging site at USD $32,060 per year. The baselines presented in the study may facilitate a quantitative assessment of dredging impacts on turtle grass once dredging is complete and an economical cost-benefit-analysis of the dredging project to see whether the economic gains outweigh the ecological costs of dredging in front of the East Bay development.     

Metapopulation dynamics in the butterfly Hipparchia semele changed decades before occupancy declined in The Netherlands

The survival of many species in human-dominated, fragmented landscapes depends on metapopulation dynamics, i.e., on a dynamic equilibrium of extinctions and colonizations in patches of suitable habitat. To understand and predict distributional changes, knowledge of these dynamics can be essential, and for this, metapopulation studies are preferably based on long-time-series data from many sites. Alas, such data are very scarce. An alternative is to use opportunistic data (i.e., collected without applying standardized field methods), but these data suffer from large variations in field methods and search intensity between sites and years. Dynamic site-occupancy models offer a general approach to adjust for variable survey effort. These models extend classical metapopulation models to account for imperfect detection of species and yield estimates of the probabilities of occupancy, colonization, and survival of species at sites. By accounting for detection, they fully correct for among-year variability in search effort. As an illustration, we fitted a dynamic site-occupancy model to 60 years of presence-absence data (more precisely, detection-nondetection) of the heathland butterfly Hipparchia semele in The Netherlands. Detection records were obtained from a database containing volunteer-based data from 1950-2009, and nondetection records were deduced from database records of other butterfly species. Our model revealed that metapopulation dynamics of Hipparchia had changed decades before the species' distribution began to contract. Colonization probability had already started to decline from 1950 onward, but this was counterbalanced by an increase in the survival of existing populations, the result of which was a stable distribution. Only from 1990 onward was survival not sufficient to compensate for the further decrease of colonization, and occupancy started to decline. Hence, it appears that factors acting many decades ago triggered a change in the metapopulation dynamics of this species, which ultimately led to a severe decline in occupancy that only became apparent much later. Our study emphasizes the importance of knowledge of changes in survival and colonization of species in modern landscapes over a very long time scale. It also demonstrates the power of site-occupancy modeling to obtain important population dynamics information from databases containing opportunistic sighting records.     

Long-term dynamics of biotic and abiotic resistance to exotic species invasion in restored vernal pool plant communities

Invasion of native ecosystems by exotic species can seriously threaten native biodiversity, alter ecosystem function, and inhibit conservation. Moreover, restoration of native plant communities is often impeded by competition from exotic species. Exotic species invasion may be limited by unfavorable abiotic conditions and by competition with native species, but the relative importance of biotic and abiotic factors remains controversial and may vary during the invasion process. We used a long-term experiment involving restored vernal pool plant communities to characterize the temporal dynamics of exotic species invasion, and to evaluate the relative support for biotic and abiotic factors affecting invasion resistance. Experimental pools (n=256) were divided among controls and several seeding treatments. In most treatments, native vernal pool species were initially more abundant than exotic species, and pools that initially received more native seeds exhibited lower frequencies of exotic species over time. However, even densely seeded pools were eventually dominated by exotic species, following extreme climatic events that reduced both native and exotic plant densities across the study site. By the sixth year of the experiment, most pools supported more exotics than native vernal pool species, regardless of seeding treatment or pool depth. Although deeper pools were less invaded by exotic species, two exotics (Hordeum marinum and Lolium multiflorum) were able to colonize deeper pools as soon as the cover of native species was reduced by climatic extremes. Based on an information-theoretic analysis, the best model of invasion resistance included a nonlinear effect of seeding treatment and both linear and nonlinear effects of pool depth. Pool depth received more support as a predictor of invasion resistance, but seeding intensity was also strongly supported in multivariate models of invasion, and was the best predictor of resistance to invasion by H. marinum and L. multilorum. We conclude that extreme climatic events can facilitate exotic species invasions by both reducing abiotic constraints and weakening biotic resistance to invasion.