The data consists of identified exposed objects subject to flooding risk from the Tsho Rolpa Lake. The Tsho Rolpa Lake is the largest moraine-dammed proglacial lake in Nepal and was identified as one of the country’s most dangerous glacier lakes with a high possibility of outburst. Full details about this dataset can be found at https://doi.org/10.5285/3834d477-7a1d-4ad3-8a41-d38fc727dbd8

The dataset consists of the transcripts of expert inputs considering how the conceptual thinking for both ‘smart’ and ‘natural or biophilic’ cities could combine to inform future urban discourses and critically reviewed a set of emerging characteristics that described the interface between these alternative discourses. These inputs include informed practice-based perspectives on themes identified in the literature and comparative assessments, testing the integrating principles identified in the research against business as usual silo approaches, which helped refine the research outcomes. Expert inputs were used to inform the identification of new ways of integrating urban futures discourses, in particular shaping the Smart City – Natural City interface, using Birmingham, UK as a case study. The files include the underlying data provided by a cohort of multi-disciplinary [anonymised] experts who contributed to the research; • the record of the group or table outputs from the Innovation Workshop of 12th September 2017 • copies of photographs of the collective ‘stickies’ contributions at the workshop • the original transcript record of the semi-structured interview conversations • records of Group telephone or meeting conversations • ‘work in progress’ collations of comments received; generated to share with contributors and with co-authors Full details about this dataset can be found at https://doi.org/10.5285/474e090d-4502-432c-b8de-ce9f33571f8e

The products capture current land use/cover for four areas of interest in Corridor Ankeniheny Zahamena (CAZ) generated based on very high resolution imagery (SPOT 6). Field-based training and validation data were used and supervised classifications created using Random Forest classifier. Full details about this dataset can be found at https://doi.org/10.5285/ce535cef-842e-4875-ad80-26760900cec0

This dataset contains records for vegetation in 49 plots across 14 fragmented forest sites and 4 continuous forest sites in Sabah, Malaysian Borneo. Living vegetation and deadwood were surveyed in two or three 0.28-ha plots in each of the eighteen sites. In addition to vegetation data, the dataset contains topsoil parameters, measurements of forest structure, and metrics of the degree of forest fragmentation in the landscape surrounding the plots. These data were collected in order to conduct studies examining (1) the factors supporting invasion of exotic plant species into fragmented forest areas; and (2) the value of conservation set-asides for carbon storage and associated plant diversity in oil palm plantations. Full details about this dataset can be found at https://doi.org/10.5285/c67b06b7-c3f6-49a3-baf2-9fc3a72cb98a

The data describes future land use projections at 1 km^2 resolution developed by CRAFTY-GB. For each of six Shared Socioeconomic Pathways (SSP-RCP) scenarios, gridded land use maps for Great Britain are provided, each as a stacked raster file with seven bands representing land use at each decadal timestep, from 2020 to 2080. CRAFTY-GB is a new agent-based model of the British land system operating at a 1 km^2 resolution and based on a broad range of available land system data . The model is based on linked UK-RCP climate scenarios and UK-SSPs socio-economic pathway (SSP) scenarios, based on global SSPs developed by the Intergovernmental Panel on Climate Change (IPCC). It extrapolates the impact of these on the British Land system at decadal timesteps from 2020-2080. Full details about this dataset can be found at https://doi.org/10.5285/f9ab3051-4f85-415f-b691-371ff8e951f2

Projections of global changes in water scarcity with the current extent of maize, rice, wheat, vegetables, pulses and fruit production commodities were combined to identify the potential country level vulnerabilities of cropland land to water scarcity in 2050. The data relate to an analysis of the impact changes in water availability will have on maize, rice, wheat, vegetables, pulses and fruit production commodities availability in 2050. Full details about this dataset can be found at https://doi.org/10.5285/84b3b580-acbf-487d-bf44-c21bc2cf12ee

Repeat electrical resistivity tomography (ERT) measurements were conducted over four sites to capture the changing resistivity of the soil throughout the agricultural growing season, with measurements taken in Spring, Summer, and Autumn to detect the change between the construction, production, and post-harvest stages of the crop. Initial measurements were undertaken in April/May, Summer measurements in June/July, and final measurements in September 2021. Full details about this dataset can be found at https://doi.org/10.5285/7d09c677-134f-49ae-8128-6bc00784967a

This is a transdisciplinary dataset from ten smallholder farming villages in Patarasi Rural Municipality, Jumla District, Nepal collected during 2021 and 2022. The human component of the dataset includes fortnightly 24-hour dietary recall surveys and monthly anthropometry surveys of 721 participants (adult males, adult females, adolescent girls and children under five) from 200 smallholder households collected over a twelve-month period. For each household, there is also data on socioeconomic status, farming practices, cooking practices and beekeeping practices. The ecological component of the dataset includes plant-pollinator interaction data and flowering phenology data from the same ten farming villages as well as the results of a pollinator exclusion field experiment in fifteen replicate sites along an altitudinal gradient in this region. Taken together, these datasets enable us to understand more about: a) people’s diets, nutritional status and socioeconomic status in rural Nepal; b) which crops provide their nutrients and how these crops are grown; c) which insects pollinate these crops, and; d) how climate change is likely to impact the system. Full details about this dataset can be found at https://doi.org/10.5285/d7434d83-c30d-4186-aab0-9764821cd807