scholarly journals Maintaining tiger connectivity and minimizing extinction into the next century: Insights from landscape genetics and spatially-explicit simulations

2016 ◽  
Author(s):  
Prachi Thatte ◽  
Aditya Joshi ◽  
Srinivas Vaidyanathan ◽  
Erin Landguth ◽  
Uma Ramakrishnan
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Protected Areas ◽  
Landscape Genetics ◽  
Extinction Risk ◽  
Population Connectivity ◽  
Extinction Probability ◽  
Spatially Explicit ◽  
Infrastructure Development ◽  
Human Settlements

AbstractHabitat loss is the greatest threat to large carnivores around the world. Maintenance of functional connectivity in fragmented landscapes will be important for long-term species persistence. Here, we merge landscape genetics analyses and spatially-explicit simulations to understand future persistence and extinction of tigers (Panthera tigris) in Central India. Tigers in this landscape are restricted to Protected Areas (PAs) and forest fragments embedded within a mosaic of agricultural fields and human settlements. We examined current population connectivity of tigers across nine reserves (using 116 non-invasively sampled individuals and 12 microsatellites). Genetic data was used to infer resistance-to-movement. Our results suggest that dense human settlements and roads with high traffic are detrimental to tiger movement. We used landscape genetic simulations to model 86 different scenarios that incorporated impacts of future land-use change on inferred population connectivity and extinction. Our results confirm that genetic variability (heterozygosity) will decrease in the future and small and/or isolated PAs will have a high risk of local extinction. The average extinction risk of small PAs reduced by 23-70% on adding a 5 km buffer around exiting boundaries. Unplanned development results in 35% lower heterozygosity and 56% higher average extinction probability for tigers even within protected areas. Increasing tiger numbers in such a scenario decreases extinction probability just by 12 % (from 56% to 44%). Scenarios where habitat connectivity was enhanced and maintained, stepping-stone populations were introduced/maintained, and tiger numbers were increased, led to low overall extinction probability (between 3-21%). Our simulations provide a means to quantitatively evaluate the effects of different land-use change scenarios on connectivity and extinction, linking basic science to land-use change policy and planned infrastructure development.

scholarly journals Assessment on the rates and potentials of soil organic carbon sequestration in agricultural lands in Japan using a process-based model and spatially explicit land-use change inventories – Part 1: Historical trend and validation based on nation-wide soil monitoring

2014 ◽  
Vol 11 (16) ◽  
pp. 4429-4442 ◽  
Author(s):  
Y. Yagasaki ◽  
Y. Shirato
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Paddy Fields ◽  
Spatially Explicit ◽  
Crop Fields ◽  
Upland Crop ◽  
Soc Stock ◽  
Stock Change ◽  
Soc Stocks

Abstract. In order to estimate a country-scale soil organic carbon (SOC) stock change in agricultural lands in Japan, while taking into account the effect of land-use changes, climate, different agricultural activities and the nature of soils, a spatially explicit model simulation system was developed using Rothamsted Carbon Model (RothC) with an integration of spatial and temporal inventories. Simulation was run from 1970 to 2008 with historical inventories. Simulated SOC stock was compared with observations in a nation-wide stationary monitoring program conducted during 1979–1998. Historical land-use change, characterized by a large decline in the area of paddy fields as well as a small but continuous decline in the area of orchards, occurred along with a relatively large increase in upland crop fields, unmanaged grasslands, and settlements (i.e. conversion of agricultural fields due to urbanization or abandoning). Results of the simulation on SOC stock change under varying land-use change indicated that land-use conversion from agricultural fields to settlements or other lands, as well as that from paddy fields to croplands have likely been an increasing source of CO2 emission, due to the reduction of organic carbon input to soils and the enhancement of SOC decomposition through transition of soil environment from anaerobic to aerobic conditions. The area-weighted mean concentrations of the simulated SOC stocks calculated for major soil groups under paddy fields and upland crop fields were comparable to those observed in the monitoring. Whereas in orchards, the simulated SOC stocks were underestimated. As the results of simulation indicated that SOC stock change under managed grasslands and settlements has been likely a major sink and source of CO2 emission at country-scale, respectively, validation of SOC stock change under these land-use types, which could not have been accomplished due to limited availability or a lack of measurement, remains a forthcoming challenge.

scholarly journals Future climate and land use instability can negate the benefits of protected areas

2021 ◽  
Author(s):  
Ernest Asamoah ◽  
Linda Beaumont ◽  
Joesph M Maina
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Protected Areas ◽  
Multiple Scales ◽  
Future Climate ◽  
Spatially Adaptive ◽  
Climate Stress ◽  
Potential Benefits ◽  
High Conservation ◽  
Climate Velocity

Abstract Expanding protected area networks and enhancing their capacities is currently one avenue at the forefront of efforts to conserve and restore global biodiversity. Climate and habitat loss resulting from land use interact synergistically to undermine the potential benefits of protected areas (PAs). Targeting conservation, adaptation and mitigation efforts requires an understanding of patterns of climate and land-use change within the current arrangement of PAs, and how these might change in the future. In this paper, we provide this understanding using predicted rates of temporal and spatial displacement of future climate and land use globally and within PAs. We show that ~ 47% of the world’s PAs—10.6% of which are under restrictive management—are located in regions that will likely experience both climate stress and land-use instability by 2050. The vast majority of these PAs are also distributed across moist biomes and in high conservation value regions, and fall into less-restrictive management categories. The differential impacts of combined land use and climate velocity across protected biomes indicate that climate and land-use change may have fundamentally different ecological and management consequences at multiple scales. Taken together, our findings can inform spatially adaptive natural resource management and actions to achieve sustainable development and biodiversity goals.

scholarly journals Estimating Changes in Habitat Quality through Land-Use Predictions: Case Study of Roe Deer (Capreolus pygargus tianschanicus) in Jeju Island

2020 ◽  
Vol 12 (23) ◽  
pp. 10123
Author(s):  
Dong-jin Lee ◽  
Seong Woo Jeon
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Protected Areas ◽  
Habitat Quality ◽  
Green Infrastructure ◽  
Roe Deer ◽  
Land Use Changes ◽  
Jeju Island ◽  
Invest Model ◽  
Integrated Valuation

This study predicts future land-use changes and the resulting changes in habitat quality, suggesting a method for establishing land-use management to ensure sustainable wildlife habitats. The conservation effects were verified in terms of wild animal habitat quality according to the designation of protected areas. Land-use change until 2050 was predicted using the Dyna-Conversion of Land Use Change and its effects (Dyna-CLUE) model for Jeju Island, Korea, and the change in the quality of roe deer habitats was predicted using the Integrated Valuation and Environmental Services and Tradeoffs (InVEST) model. Results indicate that, compared to 2030, urbanized area increased by 42.55 km2, farmland decreased by 81.36 km2, and natural area increased by 38.82 km2 by 2050. The average habitat quality on Jeju Island was predicted to decrease from 0.306 in 2030 to 0.303 in 2050. The average habitat quality ranged from 0.477 in 2030 to 0.476 in 2050 in protected areas and 0.281 in 2030 to 0.278 in 2050 outside protected areas. Habitat quality in protected areas was relatively high, and its reduction was limited. Areas with lower habitat quality need approaches such as expanding greenery and improving its quality. By establishing appropriate land-use plans by predicting habitat quality, wildlife habitats can be better maintained and protected, which is a primary goal of green infrastructure.

scholarly journals Deriving spatially explicit water uses from land use change modelling results in four river basins across Europe

2018 ◽  
Vol 628-629 ◽  
pp. 1079-1097 ◽  
Author(s):  
Verena Huber García ◽  
Swen Meyer ◽  
Kasper Kok ◽  
Peter Verweij ◽  
Ralf Ludwig
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
River Basins ◽  
Spatially Explicit ◽  
Explicit Water ◽  
Water Uses

scholarly journals Size-dependent resistance of protected areas to land-use change

2008 ◽  
Vol 275 (1640) ◽  
pp. 1297-1304 ◽  
Author(s):  
Luigi Maiorano ◽  
Alessandra Falcucci ◽  
Luigi Boitani
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Protected Areas ◽  
Size Dependent

scholarly journals Land Use Change from Biofuels Derived from Forest Residue: A Case of Washington State

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Daniel Brent ◽  
Sergey Rabotyagov
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
The United States ◽  
Washington State ◽  
Spatially Explicit ◽  
Biofuel Policy ◽  
Indirect Land Use Change ◽  
Forest Residue ◽  
Net Returns ◽  
Processing Plants

Biofuel policy in the United States is transitioning away from corn towards second-generation biofuels in part because of the debate over environmental damages from indirect land use change. We combine a spatially explicit parcel level model for land use change in Washington State with simulations for biofuel policy aimed at utilizing forest residue as feedstock. Using a spatially explicit model provides greater precision in measuring net returns to forestland and development and indicates which areas will be most impacted by biofuel policy. The effect of policy is simulated via scenarios of increasing net returns to forestry and of siting feedstock-processing plants. Our results suggest that forestland will increase from such a policy, leading to a net reduction in atmospheric carbon from indirect land use change. This is in contrast to the experience of corn ethanol where the change in carbon emissions is potentially positive and large in magnitude.

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