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A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 2

This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPPluc), the harvested NPP (including losses, HANPPharv), and the NPP remaining in ecosystems after harvest (NPPeco) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication. The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPPharv to NPPeco results in the actual NPP available before harvest (NPPact=NPPeco+HANPPharv), and adding HANPPluc to NPPact results in the potential NPP available in the hypothetical absence of land use (NPPpot=NPPact+HANPPluc) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPPpot can be calculated by summing up HANPPharv and HANPPluc and dividing it by NPPpot. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP.  This Zenodo repository provides data on following land-use classes: grazing land characterized by open wooded lands (GL-owl)

opencc-by-4.0Dec 2021View details →

Land use fractions and human impact index in 101 Canadian lake watersheds

Land use fractions (urban, mines, agriculture, pasture, forestry, managed grassland, water and natural landscape) and associated human impact index in 101 lake watersheds sampled as part the NSERC Canadian Lake Pulse Network project. Land use and human impact index were calculated as described in Huot et al. (2019). Lakes IDs with respective locations (longitude and latitude coordinates) and Continental Basin allocations can be found here: <a href="https://doi.org/10.5281/zenodo.4701262">https://doi.org/10.5281/zenodo.4701262</a> Reference Huot, Y., C. A. Brown, G. Potvin, and others. 2019. The NSERC Canadian Lake Pulse Network: A national assessment of lake health providing science for water management in a changing climate. Sci. Total Environ. 695: 133668. doi:10.1016/j.scitotenv.2019.133668

A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 1

This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPPluc), the harvested NPP (including losses, HANPPharv), and the NPP remaining in ecosystems after harvest (NPPeco) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication. The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPPharv to NPPeco results in the actual NPP available before harvest (NPPact=NPPeco+HANPPharv), and adding HANPPluc to NPPact results in the potential NPP available in the hypothetical absence of land use (NPPpot=NPPact+HANPPluc) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPPpot can be calculated by summing up HANPPharv and HANPPluc and dividing it by NPPpot. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP. This Zenodo repository provides data on following land-use classes: unused productive wilderness areas (WILD-core); productive wilderness areas that are sporadically used at very low intensity (WILD-periphery); unused unproductive wilderness areas (WILD-nps); forestry areas, mainly coniferous (FO-con); forestry areas, mainly non-coniferous (FO-ncon); settlements, urban areas and infrastructure (BU-builtup)

A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 6

This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPPluc), the harvested NPP (including losses, HANPPharv), and the NPP remaining in ecosystems after harvest (NPPeco) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication. The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPPharv to NPPeco results in the actual NPP available before harvest (NPPact=NPPeco+HANPPharv), and adding HANPPluc to NPPact results in the potential NPP available in the hypothetical absence of land use (NPPpot=NPPact+HANPPluc) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPPpot can be calculated by summing up HANPPharv and HANPPluc and dividing it by NPPpot. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP. This Zenodo repository provides data on following land-use classes: cropland used for production of potatoes (CL-POTA); sweet potatoes and yams (CL-SWPY); and rest of crops (CL-REST)

A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 4

This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPPluc), the harvested NPP (including losses, HANPPharv), and the NPP remaining in ecosystems after harvest (NPPeco) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication. The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPPharv to NPPeco results in the actual NPP available before harvest (NPPact=NPPeco+HANPPharv), and adding HANPPluc to NPPact results in the potential NPP available in the hypothetical absence of land use (NPPpot=NPPact+HANPPluc) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPPpot can be calculated by summing up HANPPharv and HANPPluc and dividing it by NPPpot. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP.  This Zenodo repository provides data on following land-use classes: cropland used for production of wheat (CL-WHEA); maize (CL-MAIZ); soybean (CL-SOYB)

A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 5

This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPPluc), the harvested NPP (including losses, HANPPharv), and the NPP remaining in ecosystems after harvest (NPPeco) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication. The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPPharv to NPPeco results in the actual NPP available before harvest (NPPact=NPPeco+HANPPharv), and adding HANPPluc to NPPact results in the potential NPP available in the hypothetical absence of land use (NPPpot=NPPact+HANPPluc) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPPpot can be calculated by summing up HANPPharv and HANPPluc and dividing it by NPPpot. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP. This Zenodo repository provides data on following land-use classes: cropland used for production of millet (CL-MILL); barley (CL-BARL); sorghum (CL-SORG); rice (CL-RICE)

A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 7

This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPPluc), the harvested NPP (including losses, HANPPharv), and the NPP remaining in ecosystems after harvest (NPPeco) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication. The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPPharv to NPPeco results in the actual NPP available before harvest (NPPact=NPPeco+HANPPharv), and adding HANPPluc to NPPact results in the potential NPP available in the hypothetical absence of land use (NPPpot=NPPact+HANPPluc) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPPpot can be calculated by summing up HANPPharv and HANPPluc and dividing it by NPPpot. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP. This Zenodo repository provides data on following land-use classes:  cropland used for production of cassava (CL-CASS); sugarcane (CL-SUGC); sugarbeet (CL-SUGB); cotton (CL-COTT); fruits and vegetables (CL-VEFR)

A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 8

This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPPluc), the harvested NPP (including losses, HANPPharv), and the NPP remaining in ecosystems after harvest (NPPeco) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication. The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPPharv to NPPeco results in the actual NPP available before harvest (NPPact=NPPeco+HANPPharv), and adding HANPPluc to NPPact results in the potential NPP available in the hypothetical absence of land use (NPPpot=NPPact+HANPPluc) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPPpot can be calculated by summing up HANPPharv and HANPPluc and dividing it by NPPpot. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP. This Zenodo repository provides data on following land-use classes:  cropland used for production of beans (CL-BEAN); other pulses (CL-OPUL); groundnuts (CL-GROU); bananas and plantains (CL-BANP)

A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 9

This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPPluc), the harvested NPP (including losses, HANPPharv), and the NPP remaining in ecosystems after harvest (NPPeco) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication. The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPPharv to NPPeco results in the actual NPP available before harvest (NPPact=NPPeco+HANPPharv), and adding HANPPluc to NPPact results in the potential NPP available in the hypothetical absence of land use (NPPpot=NPPact+HANPPluc) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPPpot can be calculated by summing up HANPPharv and HANPPluc and dividing it by NPPpot. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP. This Zenodo repository provides data on following land-use classes: cropland used for production of other oilcrops (CL-OOIL); coffee (CL-COFF); fodder crops (CL-FODD)

publicFeb 2025View details →

dryad40/100

Differences in mammal community response to highway construction across different levels of human land use

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opencc-zeroFeb 2024View details →

Data from: Northern pikas experience reduced occupancy due to surrounding human land use despite the occurrence of suitable microclimates

Aim: Despite warming temperatures, some species are found persisting at the trailing edge of their distribution. Microclimates provided by complex topography are considered a key factor in these cases of range stationarity, buffering stress from exposure to warming and enabling persistence. However, for species with trailing-edges located in human-modified landscapes, refugial conditions provided by microclimates could be disrupted by human activities. Here, we aimed to understand the determinants of trailing-edge occupancy for a small lagomorph found in rocky patches harboring cool microclimates. Location: Hokkaido Island, Japan Taxon: Northern pika (Ochotona hyperborea) Methods: We surveyed the occupancy of northern pikas across a wide elevational gradient (350–2200 m) for two consecutive summers. Ambient air and microhabitat (i.e., rock interstices) thermal conditions were measured to assess their relationship. We then analyzed their effects on occupancy at two nested spatial scales: (1) whole-distribution, and (2) at identified trailing-edge sites where we explored the effects of microclimates and surrounding human activities (i,e., distance to nearest road and area of human land use such as plantation forests or agricultural fields). Results: Overall, rock interstices exhibited cooler conditions than ambient air with temperature differences of 1–2 ºC. The overall distribution of northern pikas was affected by both mean ambient temperature and microhabitat availability, with warmer (lower elevation) sites with less microhabitats corresponding to the trailing edge of its distribution. Interestingly, trailing edge occupancy patterns were best explained by the negative effect of surrounding human land despite the existence of suitable microclimates in the rocky patches. Main conclusions: Our findings suggest that the local refugial conditions supported by cool microclimates are likely to be disrupted by the effects of human land at the larger landscape scale. This result highlights the importance of considering the effects of human activities and landscape alteration for effective microrefugia conservation. --

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Data Shared: Human land-uses homogenize stream assemblages and reduce animal biomass production

This is a dataset compiled from 117 sampling stream sites distributed across two neotropical biomes (rainforest and grassland). Dataset included single scaled vales of human land-use (agriculture, pasture, urbanization, and afforestation), scaled values of multifaceted biodiversity of fish, arthropods, and macrophytes (taxonomic richness, functional diversity[FDis], CWV and CWM of trait categories [recruitment and life-history, resource and habitat-use, and body size]), scaled values of local environmental predictors (stream site depth, water quality deterioration index, and sediment heterogeneity index), scaled values of climate predictors (temperature and precipitation), and log of animal biomass (fish and arthropod).

opencc-by-4.0May 2022View details →

opencc-zeroMay 2022View details →

Human land-use effects on mammalian mesopredator occupancy of a northeastern Connecticut landscape

Mammalian mesopredators—mid-sized carnivores—are ecologically, economically and socially important. With their adaptability to a variety of habitats and diets, loss of apex predators and forest regrowth, many of these species are increasing in number throughout the northeastern USA. However, currently the region is seeing extensive landscape alterations, with an increase in residential and industrial development especially at the expense of existing forest and small-scale farmland. We sought to understand how important an existing mosaic of working lands (timberland and farmland) in a forested landscape is to mesopredator species. We did this through studying mesopredator occupancy across three land uses (or habitat types): forest reserve (protected), timber harvest (shelterwood cuts) and field (both crop yielding and fallow) in and around a 3200-ha forest in northeastern Connecticut. We examined coyote (Canis latrans), bobcat (Lynx rufus), fisher (Pekania pennanti), and raccoon (Procyon lotor) occupancy using paired camera traps across juxtaposed reserve, shelterwood and field units from April 2018 to March 2019. We created a priori habitat variable models for each species and season, as well as analyzed the impact of habitat types on each species. Throughout the year bobcats positively associated with foliage height diversity, and had the highest use of shelterwoods and lowest of fields. Land use utilization varied seasonally for coyotes and raccoons, with higher use of fields than reserves and shelterwoods for half the year and no difference between land uses the other half. Both species were not strongly associated with any particular habitat variables. Reserve forest was moderately to highly used by all species for at least half the year, and highly use year-round by fisher. Our findings reveal that a mosaic of intact forest and working lands, timber harvest and agriculture can support mesopredator diversity.

opencc-zeroSep 2022View details →

High resolution ancient sedimentary DNA shows that alpine plant diversity is associated with human land use and climate change

The European Alps are highly rich in species, but their future may be threatened by ongoing changes in human land use and climate. Here, we reconstructed vegetation, temperature, human impact and livestock over the past ~12,000 years from Lake Sulsseewli, based on sedimentary ancient plant and mammal DNA, pollen, spores, chironomids, and microcharcoal. We assembled a highly-complete local DNA reference library (PhyloAlps, 3,923 plant taxa), and used this to obtain an exceptionally rich sedaDNA record of 366 plant taxa. Vegetation mainly responded to climate during the early Holocene, while human activity had an additional influence on vegetation from 6 ka onwards. Land-use shifted from episodic grazing during the Neolithic and Bronze Age to agropastoralism in the Middle Ages. Associated human deforestation allowed the coexistence of plant species typically found at different elevational belts, leading to levels of plant richness that characterise the current high diversity of this region. Our findings indicate a positive association between low-intensity agropastoral activities and precipitation with the maintenance of the unique subalpine and alpine plant diversity of the European Alps.

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Supplementary File 8; The full data set derived from formal quantitative surveys of land cover types and activities of humans, livestock and wildlife (Section 2.3) that were used for the analyses described in sections 2.4, 2.5 and 2.7

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opencc-by-4.0Apr 2024View details →

zenodo36/100

Habitat differences influence genetic impacts of human land use on the American beech (Fagus grandifolia)

Natural reforestation after regional forest clearance is a globally common land-use sequence. The genetic recovery of tree populations in these recolonized forests may depend on the biogeographic setting of the landscape, for instance whether they are in the core or in the marginal part of the species' range. Using data from 501 individuals genotyped across 7 microsatellites, we investigated whether regional differences in habitat quality affected the recovery of genetic variation in a wind-pollinated tree species, American beech (Fagus grandifolia) in Massachusetts. We compared populations in forests that were recolonized following agricultural abandonment to those in remnant forests that have only been logged in both central inland and marginal coastal regions. Across all populations in our entire study region, recolonized forests showed limited reduction of genetic diversity as only observed heterozygosity was significantly reduced in these forests (H O = 0.520 and 0.590, respectively). Within inland region, this pattern was observed, whereas in the coast, recolonized populations exhibited no reduction in all genetic diversity estimates. However, genetic differentiation among recolonized populations in marginal coastal habitat increased (F st logged = 0.072; F st secondary = 0.249), with populations showing strong genetic structure, in contrast to inland region. These results indicate that the magnitude of recovery of genetic variation in recolonized populations can vary at different habitats.

opencc-zeroMay 2023View details →

opencc-zeroJul 2023View details →

A secure future? Human urban and agricultural land use benefits a flightless island-endemic rail despite climate change

Identifying environmental characteristics that limit species' distributions is important for contemporary conservation and inferring responses to future environmental change. The Tasmanian native hen is an island-endemic flightless rail and a survivor of a prehistoric extirpation event. Little is known about the regional-scale environmental characteristics influencing the distribution of native hens, or how their future distribution might be impacted by environmental shifts (e.g., climate change). Using a combination of local fieldwork and species distribution modelling, we assess environmental factors shaping the contemporary distribution of the native hen, and project future distribution changes under predicted climate change. We find 37.2% of Tasmania is currently suitable for the native hens, owing to low summer precipitation, low elevation, human-modified vegetation, and urban areas. Moreover, in unsuitable regions, urban areas can create 'oases' of habitat, able to support populations with high breeding activity by providing resources and buffering against environmental constraints. Under climate change predictions, native hens were predicted to lose only 5% of their occupied range by 2055. We conclude that the species is resilient to climate change and benefits overall from anthropogenic landscape modifications. As such, this constitutes a rare example of a flightless rail to have adapted to human activity.

opencc-zeroSep 2023View details →

Spatial separation of prey from livestock facilitates coexistence of a specialized large carnivore with human land use

There is an increasing emphasis in conservation strategies for large carnivores on facilitating their coexistence with humans. Justification for coexistence strategies should be based on a quantitative assessment of currently remaining large carnivores in human-dominated landscapes. An essential part of a carnivore's coexistence strategy has to rely on its prey. In this research, we studied snow leopards Panthera uncia whose habitat mainly comprises human-dominated, unprotected areas, to understand how a large carnivore and its primary prey, the bharal Pseudois nayaur, could coexist with human land use activities in a large proportion of its range. Using a combination of livestock census, camera trapping and wildlife surveys, across a broad gradient of livestock grazing intensity in a 363,000 km2 landscape on the Tibetan Plateau, we found no evidence of livestock grazing impacts on snow leopard habitat use, bharal density and spatial distribution, even though livestock density was 13 times higher than bharal density. Bharal were found to prefer utilizing more rugged habitats at higher elevations with lower grass forage conditions, whereas livestock dominated in flat valleys at lower elevations with higher productivity, especially during the resource-scarce season. These findings suggest that the spatial niche separation between bharal and livestock, together with snow leopards' specialized bharal diet, minimized conflicts and allowed snow leopards and bharal to coexist in landscapes dominated by livestock grazing. In recent years, reduced hunting and nomadic herder's lifestyle changes towards permanent residence may have further reinforced this spatial separation. Our results indicated that, for developing conservation strategies for large carnivores, the niche of their prey in relation to human land-use is a key variable that needs to be evaluated.