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This chapter focuses on the evaluation of adaptive capacities of community-level human systems related to agriculture and food security. It highlights findings regarding approaches and domains to monitor and evaluate behavioral changes from CGIAR’s research program on climate change, agriculture and food security (CCAFS). This program, implemented in five West African countries, is intended to enhance adaptive capacities in agriculture management of natural resources and food systems. In support of participatory action research on climate-smart agriculture, a monitoring and evaluation plan was designed with the participation of all stakeholders to track changes in behavior of the participating community members. Individuals’ and groups’ stories of changes were collected using most significant change tools. The collected stories of changes were substantiated through field visits and triangulation techniques. Frequencies of the occurrence of characteristics of behavioral changes in the stories were estimated. The results show that smallholder farmers in the intervention areas adopted various characteristics of behavior change grouped into five domains: knowledge, practices, access to assets, partnership and organization. These characteristics can help efforts to construct quantitative indicators of climate change adaptation at local level. Further, the results suggest that application of behavioral change theories can facilitate the development of climate change adaptation indicators that are complementary to indicators of development outcomes. We conclude that collecting stories on behavioral changes can contribute to biophysical adaptation monitoring and evaluation.

Dataset compiled by Yushu Xia and Michelle Wander for the Soil Health Institute. Data were recovered from peer reviewed literature reporting results for three soil quality indicators (SQIs) (β-glucosidase (BG), fluorescein diacetate (FDA) hydrolysis, and permanganate oxidizable carbon (POXC)) in terms of their relative response to management where soils under grassland cover, no-tillage, cover crops, residue return and organic amendments were compared to conventionally managed controls. Peer-reviewed articles published between January of 1990 and May 2018 were searched using the Thomas Reuters Web of Science database (Thomas Reuters, Philadelphia, Pennsylvania) and Google Scholar to identify studies reporting results for: “β-glucosidase”, “permanganate oxidizable carbon”, “active carbon”, “readily oxidizable carbon”, and “fluorescein diacetate hydrolysis”, together with one or more of the following: “management practice”, “tillage”, “cover crop”, “residue”, “organic fertilizer”, or “manure”. Records were tabulated to compare SQI abundance in soil maintained under a control and soil aggrading practice with the intent to contribute to SQI databases that will support development of interpretive frameworks and/or algorithms including pedo-transfer functions relating indicator abundance to management practices and site specific factors. Meta-data include the following key descriptor variables and covariates useful for development of scoring functions: 1) identifying factors for the study site (location, year of initiation of study and year in which data was reported), 2) soil textural class, pH, and SOC, 3) depth and timing of soil sampling, 4) analytical methods for SQI quantification, 5) units used in published works (i.e. equivalent mass, concentration), 6) SQI abundances, and 7) statistical significance of difference comparisons. *Note: Blank values in tables are considered unreported data.

The Buxton Climate Change Impacts study was established in 1992 on a steep daleside of calcareous grassland outside Buxton, Derbyshire, UK. In five replicate blocks of 3 x 3 m plots, the vegetation has been subjected to climate treatments of winter heating (3C above ambient, Nov-April), summer drought (no rain, July-Aug), summer augmented rainfaill (20% above the long-term average, June-Sept), and two interaction treatments (heating-drought, heating-watered) in addition to replicated controls. The grassland is maintained in a short turf to simulate sheep and cattle grazing each autumn (Oct). In addition to annual point quadrat touches conducted at the whole-plot (9 m2) scale, permanent microsite quadrats were established within each plot in 2008 at the 100 cm2 scale. Species cover and environmental parameters have been monitored in microsites annually (2009-2011 controls only). This data package contains microsite soil depth and pH data; another package contains species cover data.

Dataset compiled by Yushu Xia and Michelle Wander for the Soil Health Institute. Data were recovered from peer reviewed literature reporting results for three ‘Tier 2’ indicators (β-glucosidase (BG), fluorescein diacetate (FDA) hydrolysis, and permanganate oxidizable carbon (POXC)) in terms of their relative response to management where soils under cover crops, grassland cover, organic amendments and residue return compared to conventionally managed controls. Peer-reviewed articles published between January of 1990 and December 2017 were searched using the Thomas Reuters Web of Science database (Thomas Reuters, Philadelphia, Pennsylvania) and Google Scholar to identify studies reporting results for: “β-glucosidase”, “permanganate oxidizable carbon”, “active carbon”, “readily oxidizable carbon”, and “fluorescein diacetate hydrolysis”, together with one or more of the following: “management practice”, “tillage”, “cover crop”, “residue”, “organic fertilizer”, or “manure”. Records were tabulated to compare SQI abundance in soil maintained under a control (conventional cropping with that found under soil health promoting practice) and soil aggrading practice with the intent to contribute to SQI databases that will support development of interpretive frameworks and/or algorithms including pedo-transfer functions relating indicator abundance to management practices and site specific factors. Meta-data include key descriptor variables and covariates useful for development of scoring functions which include: 1) identifying factors for the study site (location, year of initiation of study and year in which data was reported), 2) soil textural class and pH, 3) depth of sampling, 4) analytical methods for quantification (i.e.: loss on ignition, combustion), 5) units used in published works (i.e.: equivalent mass, concentration), 6) SOC class (L,M,H), and 7) statistical significance of difference comparisons.

1.Perennial bioenergy systems, such as switchgrass and restored prairies, are alternatives to commonly used annual monocultures such as maize. Perennial systems require lower chemical input, provide greater ecosystem services such as carbon storage, greenhouse gas mitigation, and support greater biodiversity of beneficial insects. However, biomass harvest will be necessary in managing these perennial systems for bioenergy production, and it is unclear how repeated harvesting might affect ecosystem services. 2.In this study, we examined how repeated production-scale harvesting of diverse perennial grasslands influences vegetation structure, natural enemy communities (arthropod predators and parasitoids), and natural biocontrol services in two states (Wisconsin and Michigan, USA) over multiple years. 3.We found that repeated biomass harvest reduced litter biomass and increased bare ground cover. Some natural enemy groups, such as ground-dwelling arthropods, decreased in abundance with harvest whereas others, such as foliar-dwelling arthropods increased in abundance. The disparity in responses is likely due to how different taxonomic groups utilize vegetation and differences in dispersal abilities. 4.At the community level, biomass harvest altered community composition, increased total arthropod abundance, and decreased evenness but did not influence species richness, diversity, or biocontrol services. Harvest effects varied with time, diminishing in strength both within the season (for total abundance and evenness), across seasons (for evenness), or were consistent throughout the duration of the study (for community composition). Greater functional redundancy and compensatory responses of the different taxonomic groups may have buffered against the potentially negative effects of harvest on biocontrol services. 5.Synthesis and applications. Our results show that in the short-term, repeated harvesting of perennial grasslands (when insect activity is low) consistently altered vegetation structure but had mixed effects on natural enemy communities and no discernable effects on biocontrol services. However, the long-term effects of repeated harvesting on vegetation structure, natural enemies, and other arthropod-derived ecosystem services such as pollination and decomposition remain largely unknown. Kim et al. 2017 Harvest effects on natural enemy communities and biocontrolData summary tables and site information used in Kim et al. 2017. Harvesting biofuel grasslands has mixed effects on natural enemy communities and no effects on biocontrol services. Journal of Applied Ecology.Kim et al-Harvest effects on natural enemy communities and biocontrol JAE.xlsx

The Marsh Ecology Research Program (MERP) was a long-term interdisciplinary study on the ecology of prairie wetlands. A scientific team from a variety of disciplines (hydrology, plant ecology, invertebrate ecology, vertebrate ecology, nutrient dynamics, marsh management) was assembled to design and oversee a long-term experiment on the effects of water-level manipulation on northern prairie wetlands. Ten years of fieldwork (1980 -1989), combines a routine long-term monitoring program and a series of short-term studies, generated a wealth of new and diverse information on the ecology and function of prairie wetlands (Murkin, Batt, Caldwell, Kadlec and van der Valk, 2000). This data set includes belowground macrophyte production data, collected as part of the vegetation section of MERP. Determination of aquatic macrophyte annual net primary production is vital to the understanding of the dynamics of freshwater marshes. Macrophyte biomass, both live and dead, is a major storage compartment for carbon, nitrogen and phosphorus in a marsh and a major potential energy and nutrient source for the faunal component of the marsh ecosystem. Macrophyte communities are also essential structural components of the habitat of both invertebrates and vertebrates. The major objective of the long-term monitoring of aquatic macrophytes was to determine the impact of the wet-dry cycle on macrophyte above and belowground net annual production. Standard harvest techniques were used because they were the most direct, simple and reliable techniques available for estimating net annual primary production of macrophytes per unit area (van der Valk, 1989). In order to estimate net annual belowground macrophyte production, core samples of the belowground biomass were harvested in the late spring and in the fall. Shoot initiation early in the growing season depletes most of the belowground standing crop, and therefore spring sampling was done quickly (within 2 weeks) to capture this state. Underground biomass then reaches its seasonal maxima in the fall and was captured with the fall sampling. The resulting differences between the fall and spring standing crop biomass provided an estimate of net belowground macrophyte production (van der Valk, 1989). References: Murkin, H.R., B.D.J. Batt, P.J. Caldwell, J.A. Kadlec and A.G. van der Valk. 2000a. Introduction to the Marsh Ecology Research Program. In Prairie Wetland Ecology: The Contribution of the Marsh Ecology Research Program. (Eds) H.R. Murkin, A.G. van der Valk and W.R. Clark. pp. 3-15. Ames: Iowa State University Press. van der Valk, A. 1989. Macrophyte production. In Marsh Ecology Research Program: Long-term Monitoring Procedures Manual. (Eds.) E.J. Murkin and H.R. Murkin, pp. 23-29. Manitoba, Canada: Delta Waterfowl Research Station.

We analyze past and anticipated future trends in crop yields, per capita consumption, and population to estimate agricultural land requirements globally by 2050 and 2100. Assuming “business as usual,” higher-income countries are expected to show little or no net growth in cropland by the end of the century, even in the face of moderate climate change. In contrast, in lower-income countries, we project that land requirements will grow dramatically, and climate change will likely double this expansion. Although economic growth is often considered to work in opposition to conservation, accelerating economic development in lower-income countries, which would help alleviate poverty and increase standards of living, would also greatly reduce potential cropland expansion in lower-income countries, even with climate change, owing to slower population growth and improved crop yields that more than offset increased per capita consumption. Combining economic development in low-income countries with reduced consumption in high-income countries could dramatically shrink global cropland requirements by the year 2100 even with moderate climate change. Such a remarkable reduction in cropland area would have enormous benefits for both biodiversity and global climate change.  All of the data files are analyzed using R.

Background and Aims: Associated with numerous metabolic and behavioral abnormalities, obesity is classified by metrics reliant on body weight (such as body mass index). However, overnutrition is the common cause of obesity, and may independently contribute to these obesity-related abnormalities. Here, we use dietary challenges to parse apart the relative influence of diet and/or energy balance from body weight on various metabolic and behavioral outcomes. Materials and Methods: Seventy male mice (mus musculus) were subjected to the diet switch feeding paradigm, generating groups with various body weights and energetic imbalances. Spontaneous activity patterns, blood metabolite levels, and unbiased gene expression of the nutrient-sensing ventral hypothalamus (using RNA-sequencing) were measured, and these metrics were compared using standardized multivariate linear regression models. Results: Spontaneous activity patterns were negatively related to body weight (p<0.0001) but not diet/energy balance (p=0.63). Both body weight and diet/energy balance predicted circulating glucose and insulin levels, while body weight alone predicted plasma leptin levels. Regarding gene expression within the ventral hypothalamus, only two genes responded to diet/energy balance (neuropeptide y [npy] and agouti-related peptide [agrp]), while others were related only to body weight. Conclusions: Collectively, these results demonstrate that individual components of obesity—specifically obesogenic diets/energy imbalance and elevated body mass—can have independent effects on metabolic and behavioral outcomes. This work highlights the shortcomings of using body mass-based indices to assess metabolic health, and identifies novel associations between blood biomarkers, neural gene expression, and animal behavior following dietary challenges. PerronIJ_PLOS_RawDataZip file containing 6 files and 2 folders (with 4 files and 9 files).

There is limited attention to impacts of climate change on pigs in Uganda by stakeholders, despite the potential vulnerability of pigs to climate change. Pigs are sensitive to heat-stress, as they do not have functioning sweat glands as other livestock species do, and have small lungs which reduces their ability to disseminate heat by panting. The objectives of the study were to i) determine the heat-stress status in pigs, ii) analyze factors influencing heat-stress, and iii) explore the heat-stress adaptation options in Lira District, Uganda. Lira was selected because of presence of both rural & urban areas and expected heat stress throughout the year in the district. The data including household demographics, management systems, age, color, breeds, body/skin temperature, rectal temperature and others were collected from 104 households and 259 pigs during the hot months in Ojwina and Barr sub-counties- Lira district. We collected data on adaptation options during the four gender disaggregated focus group discussions. Weather data was collected during the time of administering the questionnaire, and it was complemented with data from Ngetta Meteorological Station, Lira. STATA, 14