Combining Remote Sensing and Species Distribution Modelling to Assess Pinus hartwegii Response to Climate Change and Land Use from Izta-Popo National Park, Mexico

A detailed analysis of distribution shifts in Pinus hartwegii Lindl. is provided across time for Izta-Popo National Park (México). Combining satellite images, species distribution models, and connectivity analysis we disentangled the effect of climate change and anthropogenic land use on the habitat availability. Twenty-four Maxent habitat suitability models with varying complexity were combined with insights on vegetation and land cover change derived from two Landsat satellite images at 30-m resolution from 1993 and 2013. To evaluate effects of climate change on Izta-Popo’s P. hartwegii forest, projections for future climatic conditions (averaged for 2050 and 2070) were derived using two General Circulation Models under three Representative CO2 concentration pathways (RCPs). Calculated fragmentation and connectivity indexes (Equivalent Connected Area and Probability of Connectivity metrics) showed significant habitat loss and habitat fragmentation that weakens P. hartwegii dispersion flux and the strength of connections. Projections of future climate conditions showed a reduction of P. hartwegii habitat suitability as populations would have to migrate to higher altitudes. However, the impact of anthropogenic land use change documented over the 20 years masks the predicted impact of climate change in Izta-Popo National Park.

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Predicting the impact of climate change on the distribution pattern of Agamura persica (Dumeril, 1856) (Squamata: Gekkonidae) in Iran

Belgian Journal of Zoology ◽

10.26496/bjz.2017.11 ◽

2017 ◽

Vol 147 (2) ◽

Cited By ~ 3

Author(s):

Sayyed Saeed Hosseinian Yousefkhani ◽

Mansour Aliabadian ◽

Eskandar Rastegar-Pouyani ◽

Jamshid Darvish

Keyword(s):

Climate Change ◽

Species Distribution ◽

Habitat Suitability ◽

Vegetation Type ◽

Area Under The Curve ◽

Suitable Habitat ◽

Ecological Data ◽

Central Plateau ◽

Impact Of Climate Change ◽

The Impact

Species distribution modeling is an important tool that uses ecological data to aid in biological conservation. In the present study we used prediction methods, including maximum entropy (Maxent), to project the distribution of the Persian Spider gecko and the impact of climate change on its distribution in Iran. The results were consistent between models and indicated that two of the most important variables in determining distribution of Agamura persica are mean temperature of the wettest quarter and temperature seasonality. All of the models used in this study obtained high area-under-the-curve (AUC) values. Because of the nocturnal behavior of the species, these variables can directly affect species’ activity by determining the vegetation type in habitat. Suitable habitats of Agamura persica were in two locations in eastern Iran and a third location in the central plateau. Habitat suitability for this species was increased in the last glacial maximum (LGM), at which time most parts of the Iranian Plateau were suitable (even southwest Iran). However, the suitable habitat area is restricted to the central part of the plateau in the current period. Predictions from four scenarios indicate that future habitat suitability will be patchy and that the central part of the plateau will remain the most important part of the species distribution.

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Prediction of habitat suitability for Patrinia sibirica Juss. in the Southern Urals

Scientific Reports ◽

10.1038/s41598-021-99018-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Nikolai Fedorov ◽

Aliya Kutueva ◽

Albert Muldashev ◽

Oksana Mikhaylenko ◽

Vasiliy Martynenko ◽

...

Keyword(s):

Climate Change ◽

Habitat Suitability ◽

General Circulation ◽

Southern Urals ◽

Mountain Forest ◽

Forest Steppe ◽

Climate Change Scenarios ◽

The Southern Urals ◽

Habitat Persistence ◽

The Impact

AbstractThe paper presents the results of predictions of the habitat persistence for rare relict of the Pleistocene floristic complex Patrinia sibirica (L.) Juss. in the Southern Urals under various forecasted climate change scenarios. Climate variables from CHELSA BIOCLIM, elevation data (GMTED2010) and coarse fragment content in the top level of soil were used as predictors for modeling in the MaxEnt software. The impact of climate change on P. sibirica habitats under the RCP4.5 and RCP8.5 scenarios calculated from an ensemble of four general circulation models has been analyzed. The modeling has shown that the changes in the habitat suitability depend on the altitude. Deterioration of the habitats could be attributed to a temperature increase in mountain forest locations, and to a precipitation of driest quarter increase in mountain forest-steppe locations. In both cases, this leads to the expansion of forest and shrub vegetation. Monitoring of the habitat persistence of P. sibirica and other relict species of the Pleistocene floristic complex can play a major role in predictions, as their massive decline would constitute that climatic changes exceed the ranges of their fluctuations in the Holocene.

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Implications of Climate Change to Niche Patterns of Rothschild’s Giraffe in Africa

Biodiversity Information Science and Standards ◽

10.3897/biss.3.38426 ◽

2019 ◽

Vol 3 ◽

Author(s):

George Njagi ◽

David Chiawo

Keyword(s):

Climate Change ◽

Land Use ◽

Land Use Change ◽

Species Distribution ◽

Habitat Suitability ◽

Climatic Data ◽

Global Biodiversity Information Facility ◽

Species Response ◽

Occurrence Data ◽

Over Time

The distribution of species is strongly influenced by habitat quality and its changes over time. Climate change has been identified as one of the major drivers of habitat loss, threatening the survival of many range-restricted animal species. Identification of spatiotemporal hotspots of species occurrence is important for understanding basic ecological processes particularly for the conservation of species at risk. This study models the spatiotemporal distribution of Rothschild’s giraffe (Giraffa camelopardalis rothschildi) with the view of explaining the possible effects of changing habitat suitability in Kenya and across Africa. The study analyzes the relative importance of different climatic variables and establishes the variables that are the strongest predictors of the species’ geographic range. We apply species distribution modelling to predict the species' response to future climate and land use change scenarios. Our model is based on occurrence data from the Global Biodiversity Information Facility (GBIF) for the period 1923-2019 and climatic data from the WorldClim. We fit the model using the Maximum Entropy (Maxent) algorithm to identify the combination of environmental responses, which best predicts evolving hotspots of occurrence for this species and future habitat suitability in face of climate change. The study demonstrates the usability of occurrence data over time on Rothschild’s giraffe and gives insights on the integration of land use variables to be able to link species distribution patterns, land use change and climate change to effectively inform conservation management.

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The application of Species Distribution Modeling for wetland restoration: A case study in the Songnen Plain, Northeast China

10.5194/egusphere-egu2020-4344 ◽

2020 ◽

Author(s):

Yehui Zhong ◽

Ming Jiang ◽

Zhenshan Xue ◽

Bo Liu ◽

Guodong Wang

Keyword(s):

Climate Change ◽

Land Use ◽

Wetland Restoration ◽

Species Distribution ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Songnen Plain ◽

Priority Areas ◽

Wetland Species ◽

The Impact

Species distribution models (SDMs) are an effective tool for measuring and predicting plant response to climate change, but their application to wetland species has been relatively limited. Here, we investigate the application of SDMs to study the current and future delimitation of wetlands in the Songnen Plain, one of the densest areas of natural wetlands in China. Specifically, we focus on the iconic wetland species Phragmites australis, one of the dominant species in the Songnen plain, which has been widely used for wetland restoration efforts.Our study has four main goals: (i) to test and improve the applicability of SDM in our study; (ii) to delimit wetland areas for prioritization; (iii) to investigate the projected change in wetland distributions under future climate change scenarios; and (iv) to identify regions that appear more (or less) stable in the face of change, and to propose areas for suitable restoration efforts with land-use.To achieve our goals, we apply a broad variety of environmental variables using MaxEnt, to project present and future (2050s) suitable areas under two representative concentration pathways (RCP4.5 and RCP8.5). AUC (area under the curve) is used as the test measure for model evaluation. To obtain a rich representative sampling of this species&#8217; distribution, we use field-observational records from the National Science and Technology Fundamental Research Project &#8220;Investigation on Wetland Resource of China and Its Ecological and Environmental Benefits&#8221; (2013FY111800). In addition to exploring key abiotic parameters that influence P. australis distribution, we also explore the impact of different spatial resolutions (1 km2, 250 m2, 90 m2, 30 m2) of topographic information to assess model performance.Our results demonstrated that the performance of the MaxEnt projection of P. australis was excellent (AUC=0.922), and improved with the addition of soil, topographic and hydrological variables, but did not improve significantly with increased resolutions of topographic variables. Using the optimized model, we delimited 28,644 km2 of suitable areas and 7,959 km2 of highly suitable areas under current scenarios. The future model under RCP4.5 scenario predicted a 9.5% and 3.1% increase in the suitable and highly suitable areas, respectively. The model under RCP8.5 predicted a much smaller increase in suitable areas, and a slight reduction in highly suitable habitat compared with the current scenario. Under both future scenarios, the geographic centers of potential habitat moved toward the southeast, with the mean latitude slightly rising. Finally, we delimited 2,364 km2 of priority restoration areas under RCP4.5, including 152 km2 of paddy field, 950 km2 of dry field and 1,262 km2 of saline-alkali land. The priority areas under RCP8.5 were smaller in all three land-use types.Our study illuminates potential priority areas of the Songnen Plain for consideration in future wetland restoration efforts. For future research, we recommend more applications of SDMs with multiple species in wetland restoration, especially over larger scales and higher resolutions.

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Progress in modeling the impact of land cover change on the global climate

Progress in Physical Geography Earth and Environment ◽

10.1177/0309133306071956 ◽

2006 ◽

Vol 30 (6) ◽

pp. 737-749 ◽

Cited By ~ 11

Author(s):

Haydee Salmun ◽

Andrea Molod

Keyword(s):

Land Use ◽

Land Use Change ◽

Land Cover ◽

Land Cover Change ◽

General Circulation ◽

Global Climate ◽

New Technique ◽

Anthropogenic Land Use Change ◽

The Impact ◽

Anthropogenic Land Use

The prediction of the impact of anthropogenic land use change on the climate system hinges on the ability to properly model the interaction between the heterogeneous land surface and the atmosphere in global climate models. This paper contains a review of techniques in general use for modeling this interaction in general circulation models (GCMs) that have been used to assess the impact of land use change on climate. The review includes a summary of GCM simulations of land cover change using these techniques, along with a description of the simulated physical mechanisms by which land cover change affects the climate. The vertical extent to which surface heterogeneities retain their individual character is an important consideration for the land-atmosphere coupling, and the description of a recently developed technique that improves this aspect of the coupling is presented. The differences in the simulated climate between this new technique and a technique in general use include the presence of a boundary layer feedback mechanism that is not present in simulations with the standard technique. We postulate that the new technique when implemented in a GCM has the potential to guide an improved understanding of the mechanisms by which anthropogenic land use change affects climate.

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Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

Regional Environmental Change ◽

10.1007/s10113-021-01799-7 ◽

2021 ◽

Vol 21 (3) ◽

Author(s):

Susanne Rolinski ◽

Alexander V. Prishchepov ◽

Georg Guggenberger ◽

Norbert Bischoff ◽

Irina Kurganova ◽

...

Keyword(s):

Climate Change ◽

Land Use ◽

Organic Carbon ◽

Land Use Change ◽

Soil Organic Carbon ◽

Arable Land ◽

Future Climate ◽

Future Climate Change ◽

Climate Scenarios ◽

The Impact

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.

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Simulating the Impact of Future Land Use and Climate Change on Soil Erosion and Deposition in the Mae Nam Nan Sub-Catchment, Thailand

Sustainability ◽

10.3390/su5083244 ◽

2013 ◽

Vol 5 (8) ◽

pp. 3244-3274 ◽

Cited By ~ 32

Author(s):

Pheerawat Plangoen ◽

Mukand Babel ◽

Roberto Clemente ◽

Sangam Shrestha ◽

Nitin Tripathi

Keyword(s):

Climate Change ◽

Land Use ◽

Soil Erosion ◽

Erosion And Deposition ◽

The Impact

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Impact of climate change on sediment yield in the Mekong River basin: a case study of the Nam Ou basin, Lao PDR

Hydrology and Earth System Sciences ◽

10.5194/hess-17-1-2013 ◽

2013 ◽

Vol 17 (1) ◽

pp. 1-20 ◽

Cited By ~ 88

Author(s):

B. Shrestha ◽

M. S. Babel ◽

S. Maskey ◽

A. van Griensven ◽

S. Uhlenbrook ◽

...

Keyword(s):

Climate Change ◽

Sediment Yield ◽

General Circulation ◽

Climate Models ◽

Greenhouse Gas Emission ◽

Circulation Model ◽

Sediment Flux ◽

Seasonal Temperature ◽

Impact Of Climate Change ◽

The Impact

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

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Investigation of Climate and Land Use Change Impacts on Stream Flow of Guder Catchment, Ethiopia

10.21203/rs.3.rs-976225/v1 ◽

2021 ◽

Author(s):

Bekam Bekele Gulti ◽

Boja Mokonnen Manyazew ◽

Abdulkerim Bedewi Serur

Keyword(s):

Climate Change ◽

Land Use ◽

Stream Flow ◽

Open Space ◽

Smart Growth ◽

Assessment Model ◽

Study Region ◽

Climate Conditions ◽

Change Impact ◽

The Impact

Abstract Climate change (CC) and land use/cover change (LUCC) are the main drivers of streamflow change. In this paper, we investigate the impact of climate and LULC change impact on stream flow of Guder catchment by using Soil and Water Assessment model (SWAT). The scenarios were designed in a way that LULC was changed while climate conditions remain constant; LULC was then held constant under a changing climate and combined effect of both. The result shows that, the combined impacts of climate change and LULC dynamics can be rather different from the effects that follow-on from LULC or climate change alone. Streamflow would be more sensitive to climate change than to the LULC changes scenario, even though changes in LULC have far-reaching influences on streamflow in the study region. A comprehensive strategy of low impact developments, smart growth, and open space is critical to handle future changes to streamflow systems.

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Impacts of Urbanization on Land Use Pattern and Environment: A Case Study of Ajmer City, Rajasthan

Asian Review of Social Sciences ◽

10.51983/arss-2019.8.1.1514 ◽

2019 ◽

Vol 8 (1) ◽

pp. 87-91

Author(s):

Bhanu Priya Chouhan ◽

Monika Kannan

Keyword(s):

Land Use ◽

Urban Growth ◽

Land Degradation ◽

Satellite Images ◽

Agricultural Land ◽

Population Pressure ◽

Geographical Information ◽

Land Use Patterns ◽

Use Patterns ◽

The Impact

The world is undergoing the largest wave of urban growth in history. More than half of the world’s population now lives in towns and cities, and by 2030 this number will swell to about 5 billion. ‘Urbanization has the potential to usher in a new era of wellbeing, resource efficiency and economic growth. But due to increased population the pressure of demand also increases in urban areas’ (Drakakis-Smith, David, 1996). The loss of agricultural land to other land uses occasioned by urban growth is an issue of growing concern worldwide, particularly in the developing countries like India. This paper is an attempt to assess the impact of urbanization on land use and land cover patterns in Ajmer city. Recent trends indicate that the rural urban migration and religious significance of the place attracting thousands of tourists every year, have immensely contributed in the increasing population of city and is causing change in land use patterns. This accelerating urban sprawl has led to shrinking of the agricultural land and land holdings. Due to increased rate of urbanization, the agricultural areas have been transformed into residential and industrial areas (Retnaraj D,1994). There are several key factors which cause increase in population here such as Smart City Projects, potential for employment, higher education, more comfortable and quality housing, better health facilities, high living standard etc. Population pressure not only directly increases the demand for food, but also indirectly reduces its supply through building development, environmental degradation and marginalization of food production (Aldington T, 1997). Also, there are several issues which are associated with continuous increase in population i.e. land degradation, pollution, poverty, slums, unaffordable housing etc. Pollution, formulation of slums, transportation congestion, environmental hazards, land degradation and crime are some of the major impacts of urbanization on Ajmer city. This study involves mapping of land use patterns by analyzing data and satellite imagery taken at different time periods. The satellite images of year 2000 and 2017 are used. The change detection techniques are used with the help of Geographical Information System software like ERDAS and ArcGIS. The supervised classification of all the three satellite images is done by ERDAS software to demarcate and analyze land use change.

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