EcoLand: A multiscale niche modelling framework to improve predictions on biodiversity and conservation

Sobral‐Souza, Thadeu; Santos, Jessie Pereira dos; Maldaner, Maria E.; Lima‐Ribeiro, Matheus S.; Ribeiro, Milton Cézar

doi:10.1016/j.pecon.2021.03.008

Cited by 14 publications

(13 citation statements)

References 63 publications

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“…Mapping land-use land-cover (LULC) changes through time is, therefore, important and desirable to predict these threats and propose effective conservation policies (Jetz et al 2007). LULC is also an important predictor of species' occurrence and, thus extensively used in ecological and conservation studies (Eyringet al 2016;Ruiz-Benito et al 2020;Sobral-Souza et al 2021). There are several LULC datasets available at a global scale under cur-rent conditions, such as the Copernicus (Buchhorn et al 2020), Global Land Survey, the 30 Meter Global Land Cover, and the GlobeLand30 (Gutman et al 2013;Pengra et al 2015;Brovelli et al 2015), as well as the near historical period, such as the ESA Climate Change Initiative (1992 to 2015), the Finer Resolution Observation, Monitoring of Global Land Cover (1984 (Hollmann et al 2013;Gong et al 2013) and GCAM (2015-2100) (Chen et al 2020).…”

Section: Introductionmentioning

confidence: 99%

“…These datasets are usually available in standard Geographic Information System (GIS) formats (e.g. TIF or KMZ), routinely used by landscape ecologists, macroecologists, biogeographers, and others (Eyringet al 2016;Ruiz-Benito et al 2020;Sobral-Souza et al 2021). However, there is an important gap of historical LULC data covering pre-industrial periods (i.e.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Global land-use and land-cover data for ecologists: Historical, current, and future scenarios

Rocha

Vale²,

Lima‐Ribeiro³

2021

Biodiv. Inf.

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Land-use land-cover (LULC) data are important predictors of species occurrence and biodiversity threat. Although there are LULC datasets available for ecologists under current conditions, there is a lack of such data under historical and future climatic conditions. This hinders, for example, projecting niche and distribution models under global change scenarios at different times. The Land Use Harmonization Project (LUH2) is a global terrestrial dataset at 0.25o spatial resolution that provides LULC data from 850 to 2300 for 12 LULC state classes. The dataset, however, is compressed in a file format (NetCDF) that is incompatible with most ecological analysis and intractable for most ecologists. Here we selected and transformed the LUH2 data in order to make it more useful for ecological studies. We provide LULC for every year from 850 to 2100, with data from 2015 on provided under two Shared Socioeconomic Pathways (SSP2 and SSP5). We provide two types of file for each year: separate files with continuous values for each of the 12 LULC state classes, and a single categorical file with all state classes combined. To create the categorical layer, we assigned the state with the highest value in a given pixel among the 12 continuous data. The final dataset provides LULC data for 1251 years that will be of interest for macroecology, ecological niche modeling, global change analysis, and other applications in ecology and conservation. We also provide a description of LUH2 prediction of future LULC change through time.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Global land-use and land-cover data for ecologists: Historical, current, and future scenarios

Rocha

Vale²,

Lima‐Ribeiro³

2021

Biodiv. Inf.

View full text Add to dashboard Cite

show abstract

“…For example, Williams et al (2020) showed 58.4% of terrestrial land under the influence of moderate to severe human pressure using human footprint maps; Bellard et al (2014) predicted average 31% loss of the area under biodiversity hotspots based on climate change and land-cover data sets; Verma et al (2020) found 70% human modified land in the Sundaland biodiversity hotspot using dataset generated by Venter et al (2016). However, the human impacts on the biodiversity are not uniform globally and are influenced by many factors (Sobral-Souza et al 2021). This is what prompted the present study with the aim of helping better prioritising species for conservation following an approach that is complemented by earlier works demonstrating the improvements in conservation models by factoring in the information on climate change, land-use change and HPI (Bellard et al 2014;Helmus et al 2014;Venter et al 2016;Williams et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Predicting distribution and range dynamics of Trillium govanianum under climate change and growing human footprint for targeted conservation

Sofi

Verma

Charles³

et al. 2021

Plant Ecol

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Climate change, land-use changes and other anthropogenic pressures are globally the major drivers of biodiversity decline with profound implications, especially for the fragile Himalayan ecosystems. These drivers, if factored into the biodiversity conservation models, significantly improve their reliability and help a great deal prioritise habitats for better management. Here we focussed on an important medicinal plant species (Trillium govanianum), endemic to Himalayan region that is beset with the twin challenge of climate change and growing human footprint. We predicted the current and future projection of the distribution range of this species using SDM tool 'MaxEnt' supplemented with 'Zonation' software and 'human pressure index'. Decrease in the potential geographic range of T. govanianum, with a narrow room for conservation due to anthropogenic pressures in the predicted suitable habitats, was clearly revealed from our results. We identified the precise zones within the predicted suitable habitats under the future climatic scenarios (2050 and 2070) for priority conservation to endure the impact of climate change and growing human pressures. These results hold considerable promise in designing the effective conservation strategies for the target species. In the context of post 2020 biodiversity outlook, we advocate augmenting the species distribution models with human footprint index, zonation analysis and the climate change scenarios, to realistically meet the desired conservation targets.

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“…Mapping land-use land-cover (LULC) changes through time is, therefore, important and desirable to predict these threats and propose effective conservation policies (Jetz et al 2007). LULC is also an important predictor of species’ occurrence and, thus extensively used in ecological studies (Eyringet al 2016; Ruiz-Benito et al 2020; Sobral-Souza et al 2021). There are several LULC datasets available for ecological studies at a global scale under current conditions, such as the Global Land Survey, the 30 Meter Global Land Cover, and the GlobeLand30 (Gutman et al 2013; Pengra et al 2015; Brovelli et al 2015), as well as the near historical period, such as the ESA Climate Change Initiative (1992 to 2015), the Finer Resolution Observation, Monitoring of Global Land Cover (1984 to 2011) (Hollmann et al 2013; Gong et al 2013) and GCAM (2015-2100) (Chen et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Global Land-Use and Land-Cover Data: Historical, Current and Future Scenarios

Vale

Lima‐Ribeiro

Rocha

2021

Preprint

Self Cite

View full text Add to dashboard Cite

Land-use land-cover (LULC) data are important predictors of species occurrence and biodiversity threat. Although there are LULC datasets available for ecologists under current conditions, there is a lack of such data under historical and future climatic conditions. This hinders, for example, projecting niche and distribution models under global change scenarios at different times. The Land Use Harmonization Project (LUH2) is a global terrestrial dataset at 0.25° spatial resolution that provides LULC data from 850 to 2300 for 12 LULC state classes. The dataset, however, is compressed in a file format (NetCDF) that is incompatible with most ecological analysis and intractable for most ecologists. Here we selected and transformed the LUH2 data in order to make it more useful for ecological studies. We provide LULC for every year from 850 to 2100, with data from 2015 on provided under two Shared Socioeconomic Pathways (SSP2 and SSP5). We provide two types of file for each year: separate files with continuous values for each of the 12 LULC state classes, and a single categorical file with all state classes combined. To create the categorical layer, we assigned the state with the highest value in a given pixel among the 12 continuous data. The final dataset provides LULC data for 1251 years that will be of interest for macroecology, ecological niche modeling, global change analysis, and other applications in ecology and conservation. We also provide a description of LUH2 prediction of future LULC change through time.

show abstract

EcoLand: A multiscale niche modelling framework to improve predictions on biodiversity and conservation

Cited by 14 publications

References 63 publications

Global land-use and land-cover data for ecologists: Historical, current, and future scenarios

Global land-use and land-cover data for ecologists: Historical, current, and future scenarios

Predicting distribution and range dynamics of Trillium govanianum under climate change and growing human footprint for targeted conservation

Global Land-Use and Land-Cover Data: Historical, Current and Future Scenarios

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