scholarly journals Role of Maximum Entropy and Citizen Science to Study Habitat Suitability of Jacobin Cuckoo in Different Climate Change Scenarios

2021 ◽  
Vol 10 (7) ◽  
pp. 463
Author(s):  
Priyanka Singh ◽  
Sameer Saran ◽  
Sultan Kocaman
Keyword(s):  
Climate Change ◽  
Maximum Entropy ◽  
Citizen Science ◽  
Habitat Suitability ◽  
Environmental Variables ◽  
Monsoon Season ◽  
Bird Species ◽  
Machine Learning Algorithms ◽  
Maximum Temperature ◽  
Climate Change Scenarios

Recent advancements in spatial modelling and mapping methods have opened up new horizons for monitoring the migration of bird species, which have been altered due to the climate change. The rise of citizen science has also aided the spatiotemporal data collection with associated attributes. The biodiversity data from citizen observatories can be employed in machine learning algorithms for predicting suitable environmental conditions for species’ survival and their future migration behaviours. In this study, different environmental variables effective in birds’ migrations were analysed, and their habitat suitability was assessed for future understanding of their responses in different climate change scenarios. The Jacobin cuckoo (Clamator jacobinus) was selected as the subject species, since their arrival to India has been traditionally considered as a sign for the start of the Indian monsoon season. For suitability predictions in current and future scenarios, maximum entropy (Maxent) modelling was carried out with environmental variables and species occurrences observed in India and Africa. For modelling, the correlation test was performed on the environmental variables (bioclimatic, precipitation, minimum temperature, maximum temperature, precipitation, wind and elevation). The results showed that precipitation-related variables played a significant role in suitability, and through reclassified habitat suitability maps, it was observed that the suitable areas of India and Africa might decrease in future climatic scenarios (SSPs 2.6, 4.5, 7.0 and 8.5) of 2030 and 2050. In addition, the suitability and unsuitability areas were calculated (in km2) to observe the subtle changes in the ecosystem. Such climate change studies can support biodiversity research and improve the agricultural economy.

scholarly journals Mapping current and potential future distributions of the oak tree (Quercus aegilops) in the Kurdistan Region, Iraq

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Nabaz R. Khwarahm
Keyword(s):  
Climate Change ◽  
Habitat Suitability ◽  
Environmental Variables ◽  
Climate Changes ◽  
Future Climate ◽  
Annual Precipitation ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Kurdistan Region ◽  
Oak Tree

Abstract Background The oak tree (Quercus aegilops) comprises ~ 70% of the oak forests in the Kurdistan Region of Iraq (KRI). Besides its ecological importance as the residence for various endemic and migratory species, Q. aegilops forest also has socio-economic values—for example, as fodder for livestock, building material, medicine, charcoal, and firewood. In the KRI, Q. aegilops has been degrading due to anthropogenic threats (e.g., shifting cultivation, land use/land cover changes, civil war, and inadequate forest management policy) and these threats could increase as climate changes. In the KRI and Iraq as a whole, information on current and potential future geographical distributions of Q. aegilops is minimal or not existent. The objectives of this study were to (i) predict the current and future habitat suitability distributions of the species in relation to environmental variables and future climate change scenarios (Representative Concentration Pathway (RCP) 2.6 2070 and RCP8.5 2070); and (ii) determine the most important environmental variables controlling the distribution of the species in the KRI. The objectives were achieved by using the MaxEnt (maximum entropy) algorithm, available records of Q. aegilops, and environmental variables. Results The model demonstrated that, under the RCP2.6 2070 and RCP8.5 2070 climate change scenarios, the distribution ranges of Q. aegilops would be reduced by 3.6% (1849.7 km2) and 3.16% (1627.1 km2), respectively. By contrast, the species ranges would expand by 1.5% (777.0 km2) and 1.7% (848.0 km2), respectively. The distribution of the species was mainly controlled by annual precipitation. Under future climate change scenarios, the centroid of the distribution would shift toward higher altitudes. Conclusions The results suggest (i) a significant suitable habitat range of the species will be lost in the KRI due to climate change by 2070 and (ii) the preference of the species for cooler areas (high altitude) with high annual precipitation. Conservation actions should focus on the mountainous areas (e.g., by establishment of national parks and protected areas) of the KRI as climate changes. These findings provide useful benchmarking guidance for the future investigation of the ecology of the oak forest, and the categorical current and potential habitat suitability maps can effectively be used to improve biodiversity conservation plans and management actions in the KRI and Iraq as a whole.

scholarly journals Potential distribution and habitat suitability of Picea crassifolia with climate change scenarios

2021 ◽  
Author(s):  
Yuan Gao ◽  
Zhibin He ◽  
Xi Zhu ◽  
Longfei Chen ◽  
Jun Du ◽  
...  
Keyword(s):  
Climate Change ◽  
Habitat Suitability ◽  
Environmental Variables ◽  
Potential Distribution ◽  
Yellow River ◽  
Tibet Plateau ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Helan Mountains ◽  
Qinghai Tibet Plateau

The Qinghai-Tibet Plateau in China is a region strongly impacted by climate change, yet its effects are unknown on the keystone endemic forest species, P. crassifolia. Understanding changes in potential distribution and habitat suitability of P. crassifolia forest with the climate change will contribute to water conservation, forest management, and ecological protection in the upper reaches of the Yellow River. A total of 129 records of species distribution data and 19 environmental variables were chosen for modeling. The MaxEnt model was used to analyze the main environmental factors affecting the potential distribution of P. crassifolia in two periods (2050s and 2070s) and four representative emission pathways (RCP2.6, RCP4.5, RCP6.0 and RCP 8.5). The main results are follows: (1) the most important environmental variables affecting distribution of P. crassifolia and percentage variance explained were: altitude (41.85%), precipitation of driest month (19.76%), slope (12.35%), annual precipitation (6.56%), precipitation of wettest month (5.73%), and precipitation of warmest quarter (5.12%), (2) habitat suitability of P. crassifolia shifted to the northwest and into high-altitude areas under climate change scenarios, but its core distribution areas were concentrated in northeastern Qinghai-Tibet Plateau, Qilian Mountains, southern Ningxia, and Helan Mountains, (3) total area of potential suitable habitat of P. crassifolia will change significantly in the future, and change of habitat area of not suitable, low, moderate, and high suitability exceed 60%.

scholarly journals Northward expansion trends and future potential distribution of a dragonfly Ischnura senegalensis Rambur under climate change using citizen science data in South Korea

2021 ◽  
Vol 45 (1) ◽  
Author(s):  
Sookyung Shin ◽  
Kwang Soo Jung ◽  
Hong Gu Kang ◽  
Ji-Hee Dang ◽  
Doohee Kang ◽  
...  
Keyword(s):  
Climate Change ◽  
South Korea ◽  
Citizen Science ◽  
Baseline Data ◽  
Distribution Range ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Science Data ◽  
Northward Expansion

Abstract Background Citizen science is becoming a mainstream approach of baseline data collection to monitor biodiversity and climate change. Dragonflies (Odonata) have been ranked as the highest priority group in biodiversity monitoring for global warming. Ischnura senegalensis Rambur has been designated a biological indicator of climate change and is being monitored by the citizen science project “Korean Biodiversity Observation Network.” This study has been performed to understand changes in the distribution range of I. senegalensis in response to climate change using citizen science data in South Korea. Results We constructed a dataset of 397 distribution records for I. senegalensis, ranging from 1980 to 2020. The number of records sharply increased over time and space, and in particular, citizen science monitoring data accounted for the greatest proportion (58.7%) and covered the widest geographical range. This species was only distributed in the southern provinces until 2010 but was recorded in the higher latitudes such as Gangwon-do, Incheon, Seoul, and Gyeonggi-do (max. Paju-si, 37.70° latitude) by 2020. A species distribution model showed that the annual mean temperature (Bio1; 63.2%) and the maximum temperature of the warmest month (Bio5; 16.7%) were the most critical factors influencing its distribution. Future climate change scenarios have predicted an increase in suitable habitats for this species. Conclusions This study is the first to show the northward expansion in the distribution range of I. senegalensis in response to climate warming in South Korea over the past 40 years. In particular, citizen science was crucial in supplying critical baseline data to detect the distribution change toward higher latitudes. Our results provide new insights on the value of citizen science as a tool for detecting the impact of climate change on ecosystems in South Korea.

scholarly journals MAXIMUM ENTROPY MODELING USING CITIZEN SCIENCE: USE CASE ON JACOBIN CUCKOO AS AN INDICATOR OF INDIAN MONSOON

2020 ◽  
Vol V-5-2020 ◽  
pp. 23-30
Author(s):  
P. Singh ◽  
S. Saran
Keyword(s):  
Maximum Entropy ◽  
Citizen Science ◽  
Indian Monsoon ◽  
Monsoon Season ◽  
Cold Climate ◽  
Distribution Data ◽  
Climate Change Scenarios ◽  
Science Data ◽  
Maximum Entropy Modeling ◽  
Bioclimatic Variables

Abstract. Due to a growing revolution of the citizen science era with the involvement of non-professionals in scientific tasks such as species observation, yields an opportunistic data for modeling and planning purposes. Such citizen science based scientific observations can be a sustainable option to answer many research questions. Here, citizen science data of the Clamator jacobinus bird is taken from Global Biodiversity Information facility to predict its habitat suitability through maximum entropy approach. The distribution data is divided into two monthly sets – June to October and November to May for critically analysing the probable climatic reasons for its migration and understanding the influence of climatic variables in its suitability during the Indian monsoon season and Southern Africa rainy season. Also, the influential role of different bioclimatic variables in determining the bird’s suitability is described in this paper and to predict how this bird will react to different climate change scenarios in 2050 year. The maximum entropy modeling is performed on both sets of data and results are surprisingly interesting, which verifies an Indian myth that this bird is harbinger of the monsoon in India. This study concluded that the precipitation during warmest and wettest quarter, and isothermality are the major factors in determining the migration of Clamator jacobinus, but, hot, dry and cold climate is not suitable for this bird suitability. Such study using the citizen science data can be used in biodiversity planning as well as in improving the agricultural economy because monsoon is considered as an auspicious season for functioning of biodiversity and agricultural tasks.

scholarly journals Impact of Climate Change on Water Availability and Food Security of Nepal

2012 ◽  
pp. 59-63
Author(s):  
Roshan Kumar Mehta ◽  
Shree Chandra Shah
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Climatic Factors ◽  
Monsoon Season ◽  
Groundwater Table ◽  
Maximum Temperature ◽  
Aquatic Life ◽  
Temperature And Precipitation ◽  
Average Maximum ◽  
Water Scarce

The increase in the concentration of greenhouse gases (GHGs) in the atmosphere is widely believed to be causing climate change. It affects agriculture, forestry, human health, biodiversity, and snow cover and aquatic life. Changes in climatic factors like temperature, solar radiation and precipitation have potential to influence agrobiodiversity and its production. An average of 0.04°C/ year and 0.82 mm/year rise in annual average maximum temperature and precipitation respectively from 1975 to 2006 has been recorded in Nepal. Frequent droughts, rise in temperature, shortening of the monsoon season with high intensity rainfall, severe floods, landslides and mixed effects on agricultural biodiversity have been experienced in Nepal due to climatic changes. A survey done in the Chitwan District reveals that lowering of the groundwater table decreases production and that farmers are attracted to grow less water consuming crops during water scarce season. The groundwater table in the study area has lowered nearly one meter from that of 15 years ago as experienced by the farmers. Traditional varieties of rice have been replaced in the last 10 years by modern varieties, and by agricultural crops which demand more water for cultivation. The application of groundwater for irrigation has increased the cost of production and caused severe negative impacts on marginal crop production and agro-biodiversity. It is timely that suitable adaptive measures are identified in order to make Nepalese agriculture more resistant to the adverse impacts of climate change, especially those caused by erratic weather patterns such as the ones experienced recently.DOI: http://dx.doi.org/10.3126/hn.v11i1.7206 Hydro Nepal Special Issue: Conference Proceedings 2012 pp.59-63

scholarly journals Assessing runoff sensitivities to precipitation and temperature changes under global climate-change scenarios

2018 ◽  
Vol 50 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Lei Chen ◽  
Jianxia Chang ◽  
Yimin Wang ◽  
Yuelu Zhu
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Yellow River ◽  
Control Variable ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Temperature Changes ◽  
Runoff Change ◽  
Precipitation And Temperature

Abstract An accurate grasp of the influence of precipitation and temperature changes on the variation in both the magnitude and temporal patterns of runoff is crucial to the prevention of floods and droughts. However, there is a general lack of understanding of the ways in which runoff sensitivities to precipitation and temperature changes are associated with the CMIP5 scenarios. This paper investigates the hydrological response to future climate change under CMIP5 RCP scenarios by using the Variable Infiltration Capacity (VIC) model and then quantitatively assesses runoff sensitivities to precipitation and temperature changes under different scenarios by using a set of simulations with the control variable method. The source region of the Yellow River (SRYR) is an ideal area to study this problem. The results demonstrated that the precipitation effect was the dominant element influencing runoff change (the degree of influence approaching 23%), followed by maximum temperature (approaching 12%). The weakest element was minimum temperature (approaching 3%), despite the fact that the increases in minimum temperature were higher than the increases in maximum temperature. The results also indicated that the degree of runoff sensitivity to precipitation and temperature changes was subject to changing external climatic conditions.

scholarly journals Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

2011 ◽  
Vol 11 (12) ◽  
pp. 3275-3291 ◽  
Author(s):  
M. Ruiz-Ramos ◽  
E. Sánchez ◽  
C. Gallardo ◽  
M. I. Mínguez
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
High Temperatures ◽  
Climate Models ◽  
Cropping Systems ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Grain Filling ◽  
Maximum Temperature ◽  
Climate Change Scenarios

Abstract. Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.

scholarly journals Current and Future Potential Distribution of the Xerophytic Shrub Candelilla (Euphorbia antisyphilitica) under Two Climate Change Scenarios

Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 530 ◽  
Author(s):  
Gonzalo Vargas-Piedra ◽  
Ricardo David Valdez-Cepeda ◽  
Armando López-Santos ◽  
Arnoldo Flores-Hernández ◽  
Nathalie S. Hernández-Quiroz ◽  
...  
Keyword(s):  
Climate Change ◽  
North America ◽  
Habitat Suitability ◽  
Potential Distribution ◽  
The United States ◽  
Economic Importance ◽  
Distribution Area ◽  
Climate Projections ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Climate Change Scenarios

Candelilla (Euphorbia antisyphilitica Zucc.) is a shrub species distributed throughout the Chihuahuan Desert in northern Mexico and southern of the United States of America. Candelilla has an economic importance due to natural wax it produces. The economic importance and the intense harvest of the wax from candelilla seems to gradually reduce the natural populations of this species. The essence of this research was to project the potential distribution of candelilla populations under different climate change scenarios in its natural distribution area in North America. We created a spatial database with points of candelilla presence, according to the Global Biodiversity Information Facility (GBIF). A spatial analysis to predict the potential distribution of the species using Maxent software was performed. Thirteen of 19 variables from the WorldClim database were used for two scenarios of representative concentration pathways (RCPs) (4.5 as a conservative and 8.5 as extreme). We used climate projections from three global climate models (GCMs) (Max Planck institute, the Geophysical Fluid Dynamics Laboratory and the Met Office Hadley), each simulating the two scenarios. The final predicted distribution areas were classified in five on-site possible candelilla habitat suitability categories: none (< 19%), low (20–38%), medium (39–57%), high (58–76%) and very high (> 77%). According to the area under the curve (0.970), the models and scenarios used showed an adequate fit to project the current and future distribution of candelilla. The variable that contributed the most in the three GCMs and the two RCPs was the mean temperature of the coldest quarter with an influence of 45.7% (Jackknife test). The candelilla’s distribution area for North America was predicted as approximately 19.1 million hectares under the current conditions for the high habitat suitability; however, the projection for the next fifty years is not promising because the GCMs projected a reduction of more than 6.9 million hectares using either the conservative or extreme scenarios. The results are useful for conservation of the species in the area with vulnerable wild populations, as well as for the selection of new sites suitable for the species growth and cultivation while facing climate change.

scholarly journals Predicting the Bioclimatic Habitat Suitability of Ginkgo biloba L. in China with Field-Test Validations

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 705 ◽  
Author(s):  
Ying Guo ◽  
Jing Guo ◽  
Xin Shen ◽  
Guibin Wang ◽  
Tongli Wang
Keyword(s):  
Climate Change ◽  
Field Test ◽  
Ginkgo Biloba ◽  
Habitat Suitability ◽  
Leaf Traits ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Living Fossil ◽  
Model Predictions ◽  
The Impact

Ginkgo (Ginkgo biloba L.) is not only considered a ‘living fossil’, but also has important ecological, economic, and medicinal values. However, the impact of climate change on the performance and distribution of this plant is an increasing concern. In this study, we developed a bioclimatic model based on data about the occurrence of ginkgo from 277 locations, and validated model predictions using a wide-ranging field test (12 test sites, located at the areas from 22.49° N to 39.32° N, and 81.11° E to 123.53° E). We found that the degree-days below zero were the most important climate variable determining ginkgo distribution. Based on the model predictions, we classified the habitat suitability for ginkgo into four categories (high, medium, low, and unsuitable), accounting for 9.29%, 6.09%, 8.46%, and 76.16% of China’s land area, respectively. The ANOVA results of the validation test showed significant differences in observed leaf-traits among the four habitat types (p < 0.05), and importantly the rankings of the leaf traits were consistent with our classification of the habitat suitability, suggesting the effectiveness of our classification in terms of biological and economic significance. In addition, we projected that suitable (high and medium) habitats for ginkgo would shrink and shift northward under both the RCP4.5 and RCP8.5 climate change scenarios for three future periods (the 2020s, 2050s, and 2080s). However, the area of low-suitable habitat would increase, resulting in a slight decrease in unsuitable habitats. Our findings contribute to a better understanding of climate change impact on this plant and provide a scientific basis for developing adaptive strategies for future climate.

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