scholarly journals Spatiotemporal dynamics of habitat suitability for the Ethiopian staple crop, Eragrostis tef (teff), under changing climate

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10965
Author(s):  
Dinka Zewudie ◽  
Wenguang Ding ◽  
Zhanlei Rong ◽  
Chuanyan Zhao ◽  
Yapeng Chang
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Habitat Suitability ◽  
Climate Model ◽  
Land Suitability ◽  
Eragrostis Tef ◽  
Entropy Model ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables ◽  
Total Study Area

Teff (Eragrostis tef (Zucc.) Trotter) is a staple, ancient food crop in Ethiopia. Its growth is affected by climate change, so it is essential to understand climatic effects on its habitat suitability in order to design countermeasures to ensure food security. Based on the four Representative Concentration Pathway emission scenarios (i.e., RCP2.6, RCP4.5, RCP6.0 and RCP8.5) set by the Intergovernmental Panel on Climate Change (IPCC), we predicted the potential distribution of teff under current and future scenarios using a maximum entropy model (Maxent). Eleven variables were selected out of 19, according to correlation analysis combined with their contribution rates to the distribution. Simulated accuracy results validated by the area under the curve (AUC) had strong predictability with values of 0.83–0.85 for current and RCP scenarios. Our results demonstrated that mean temperature in the coldest season, precipitation seasonality, precipitation in the cold season and slope are the dominant factors driving potential teff distribution. Proportions of suitable teff area, relative to the total study area were 58% in current climate condition, 58.8% in RCP2.6, 57.6% in RCP4.5, 59.2% in RCP6.0, and 57.4% in RCP8.5, respectively. We found that warmer conditions are correlated with decreased land suitability. As expected, bioclimatic variables related to temperature and precipitation were the best predictors for teff suitability. Additionally, there were geographic shifts in land suitability, which need to be accounted for when assessing overall susceptibility to climate change. The ability to adapt to climate change will be critical for Ethiopia’s agricultural strategy and food security. A robust climate model is necessary for developing primary adaptive strategies and policy to minimize the harmful impact of climate change on teff.

scholarly journals A Bioclimate-Based Maximum Entropy Model for Comperiella calauanica Barrion, Almarinez and Amalin (Hymenoptera: Encyrtidae) in the Philippines

Insects ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 26
Author(s):  
Billy Joel M. Almarinez ◽  
Mary Jane A. Fadri ◽  
Richard Lasina ◽  
Mary Angelique A. Tavera ◽  
Thaddeus M. Carvajal ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Biological Control Agent ◽  
The Philippines ◽  
Distribution Model ◽  
Field Surveys ◽  
Probability Of Occurrence ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables

Comperiella calauanica is a host-specific endoparasitoid and effective biological control agent of the diaspidid Aspidiotus rigidus, whose outbreak from 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (Maxent) algorithm, we developed a species distribution model (SDM) for C. calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016. The calculated the area under the ROC curve (AUC) values for the model were very high (0.966, standard deviation = 0.005), indicating the model’s high predictive power. Precipitation seasonality was found to have the highest relative contribution to model development. Response curves produced by Maxent suggested the positive influence of mean temperature of the driest quarter, and negative influence of precipitation of the driest and coldest quarters on habitat suitability. Given that C. calauanica has been found to always occur with A. rigidus in Luzon Island due to high host-specificity, the SDM for the parasitoid may also be considered and used as a predictive model for its host. This was confirmed through field surveys conducted between late 2016 and early 2018, which found and confirmed the occurrence of A. rigidus in three areas predicted by the SDM to have moderate to high habitat suitability or probability of occurrence of C. calauanica: Zamboanga City in Mindanao; Isabela City in Basilan Island; and Tablas Island in Romblon. This validation in the field demonstrated the utility of the bioclimate-based SDM for C. calauanica in predicting habitat suitability or probability of occurrence of A. rigidus in the Philippines.

Hotspots of change in major tree species under climate warming

2020 ◽  
Author(s):  
Flurin Babst ◽  
Richard L. Peters ◽  
Rafel O. Wüest ◽  
Margaret E.K. Evans ◽  
Ulf Büntgen ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Sensitivity ◽  
Tree Growth ◽  
Species Distribution ◽  
Tree Species ◽  
Habitat Suitability ◽  
Species Distribution Models ◽  
Sensitivity Index ◽  
Distribution Models ◽  
Bioclimatic Variables

<p>Warming alters the variability and trajectories of tree growth around the world by intensifying or alleviating energy and water limitation. This insight from regional to global-scale research emphasizes the susceptibility of forest ecosystems and resources to climate change. However, globally-derived trends are not necessarily meaningful for local nature conservation or management considerations, if they lack specific information on present or prospective tree species. This is particularly the case towards the edge of their distribution, where shifts in growth trajectories may be imminent or already occurring.</p><p>Importantly, the geographic and bioclimatic space (or “niche”) occupied by a tree species is not only constrained by climate, but often reflects biotic pressure such as competition for resources with other species. This aspect is underrepresented in many species distribution models that define the niche as a climatic envelope, which is then allowed to shift in response to changes in ambient conditions. Hence, distinguishing climatic from competitive niche boundaries becomes a central challenge to identifying areas where tree species are most susceptible to climate change.</p><p>Here we employ a novel concept to characterize each position within a species’ bioclimatic niche based on two criteria: a climate sensitivity index (CSI) and a habitat suitability index (HSI). The CSI is derived from step-wise multiple linear regression models that explain variability in annual radial tree growth as a function of monthly climate anomalies. The HSI is based on an ensemble of five species distribution models calculated from a combination of observed species occurrences and twenty-five bioclimatic variables. We calculated these two indices for 11 major tree species across the Northern Hemisphere.</p><p>The combination of climate sensitivity and habitat suitability indicated hotspots of change, where tree growth is mainly limited by competition (low HSI and low CSI), as well as areas that are particularly sensitive to climate variability (low HSI and high CSI). In the former, we expect that forest management geared towards adjusting the competitive balance between several candidate species will be most effective under changing environmental conditions. In the latter areas, selecting particularly drought-tolerant accessions of a given species may reduce forest susceptibility to the predicted warming and drying.</p>

scholarly journals Present and future projections of habitat suitability of the Asian tiger mosquito, a vector of viral pathogens, from global climate simulation

2015 ◽  
Vol 370 (1665) ◽  
pp. 20130554 ◽  
Author(s):  
Y. Proestos ◽  
G. K. Christophides ◽  
K. Ergüler ◽  
M. Tanarhte ◽  
J. Waldock ◽  
...  
Keyword(s):  
Climate Change ◽  
Fuzzy Logic ◽  
Habitat Suitability ◽  
Climate Model ◽  
Global Climate ◽  
Asian Tiger Mosquito ◽  
Model Simulations ◽  
Asian Tiger ◽  
Tiger Mosquito ◽  
Climate Model Simulations

Climate change can influence the transmission of vector-borne diseases (VBDs) through altering the habitat suitability of insect vectors. Here we present global climate model simulations and evaluate the associated uncertainties in view of the main meteorological factors that may affect the distribution of the Asian tiger mosquito ( Aedes albopictus ), which can transmit pathogens that cause chikungunya, dengue fever, yellow fever and various encephalitides. Using a general circulation model at 50 km horizontal resolution to simulate mosquito survival variables including temperature, precipitation and relative humidity, we present both global and regional projections of the habitat suitability up to the middle of the twenty-first century. The model resolution of 50 km allows evaluation against previous projections for Europe and provides a basis for comparative analyses with other regions. Model uncertainties and performance are addressed in light of the recent CMIP5 ensemble climate model simulations for the RCP8.5 concentration pathway and using meteorological re-analysis data (ERA-Interim/ECMWF) for the recent past. Uncertainty ranges associated with the thresholds of meteorological variables that may affect the distribution of Ae. albopictus are diagnosed using fuzzy-logic methodology, notably to assess the influence of selected meteorological criteria and combinations of criteria that influence mosquito habitat suitability. From the climate projections for 2050, and adopting a habitat suitability index larger than 70%, we estimate that approximately 2.4 billion individuals in a land area of nearly 20 million km 2 will potentially be exposed to Ae. albopictus . The synthesis of fuzzy-logic based on mosquito biology and climate change analysis provides new insights into the regional and global spreading of VBDs to support disease control and policy making.

scholarly journals Genomic, Habitat, and Leaf Shape Analyses Reveal a Possible Cryptic Species and Vulnerability to Climate Change in a Threatened Daisy

Life ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 553
Author(s):  
Colette Blyth ◽  
Matthew J. Christmas ◽  
Douglas C. Bickerton ◽  
Martin F. Breed ◽  
Nicole R. Foster ◽  
...  
Keyword(s):  
Climate Change ◽  
Cryptic Species ◽  
Habitat Suitability ◽  
Conservation Management ◽  
Leaf Shape ◽  
Significant Proportion ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Precipitation Seasonality ◽  
Habitat Suitability Modelling

Olearia pannosa is a plant species listed as vulnerable in Australia. Two subspecies are currently recognised (O. pannosa subsp. pannosa (silver daisy) and O. pannosa subsp. cardiophylla (velvet daisy)), which have overlapping ranges but distinct leaf shape. Remnant populations face threats from habitat fragmentation and climate change. We analysed range-wide genomic data and leaf shape variation to assess population diversity and divergence and to inform conservation management strategies. We detected three distinct genetic groupings and a likely cryptic species. Samples identified as O. pannosa subsp. cardiophylla from the Flinders Ranges in South Australia were genetically distinct from all other samples and likely form a separate, range-restricted species. Remaining samples formed two genetic clusters, which aligned with leaf shape differences but not fully with current subspecies classifications. Levels of genetic diversity and inbreeding differed between the three genetic groups, suggesting each requires a separate management strategy. Additionally, we tested for associations between genetic and environmental variation and carried out habitat suitability modelling for O. pannosa subsp. pannosa populations. We found mean annual maximum temperature explained a significant proportion of genomic variance. Habitat suitability modelling identified mean summer maximum temperature, precipitation seasonality and mean annual rainfall as constraints on the distribution of O. pannosa subsp. pannosa, highlighting increasing aridity as a threat for populations located near suitability thresholds. Our results suggest maximum temperature is an important agent of selection on O. pannosa subsp. pannosa and should be considered in conservation strategies. We recommend taxonomic revision of O. pannosa and provide conservation management recommendations.

scholarly journals Climate Predictions for Ludhiana District of Indian Punjab under RCP 4.5 and RCP 8.5

2019 ◽  
pp. 128-141 ◽  
Author(s):  
Mehraj U. Din Dar ◽  
Rajan Aggarwal ◽  
Samanpreet Kaur
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Water Resources ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Climate Prediction ◽  
Global Food Security ◽  
Rcp 8.5 ◽  
Global Food

Climate change poses significant threats to global food security and water resources. In a present study, a Global Climate Model HAD GEM2-ES under RCPs 4.5 and 8.5 was used for climate prediction study. The study spanned 46 years of baseline (1970-2015) as well as two future periods’ mid-century (MC) (2020-2050) and end century EC (2060-2090). The results showed that the temperature would increase by 1.56°C and rainfall would decrease by 98 mm in MC (2020-2050); and 3.11°C and 90 mm in EC (2060-2090), respectively under RCP 4.5. In RCP 8.5 the increase in temperature and rainfall was 2.75°C and 153 mm, respectively in MC and the corresponding values in EC was 5.46°C and 251 mm, respectively.

scholarly journals Assessing the Impact of Climate Change on the Distribution of Lime (16srii-B) and Alfalfa (16srii-D) Phytoplasma Disease Using MaxEnt

Plants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 460
Author(s):  
Amna M. Al Ruheili ◽  
Alaba Boluwade ◽  
Ali M. Al Subhi
Keyword(s):  
Climate Change ◽  
Arable Land ◽  
Geographical Information ◽  
Climate Change Scenarios ◽  
Entropy Model ◽  
Bioclimatic Variables ◽  
Entire Country ◽  
Climatic Scenarios ◽  
Broom Disease ◽  
The Impact

Witches’ broom disease has led to major losses in lime and alfalfa production in Oman. This paper identifies bioclimatic variables that contribute to the prediction of distribution of witches’ broom disease in current and future climatic scenarios. It also explores the expansion, reduction, or shift in the climatic niche of the distribution of the disease across the different geographical areas of the entire country (309,501 km²). The maximum entropy model (MaxEnt) and geographical information system were used to investigate the potential suitability of habitats for the phytoplasma disease. This study used current (1970–2000) and future projected climatic scenarios (2021–2040, 2041–2060, 2061–2080, and 2081–2100) to model the distribution of phytoplasma for lime trees and alfalfa in Oman. Bioclimatic variables were downloaded from WorldClim with ± 60 occurrence points for lime trees and alfalfa. The area under the curve (AUC) was used to evaluate the model’s performance. Quantitatively, the results showed that the mean of the AUC values for lime (16SrII-B) and alfalfa (16SrII-D) future distribution for the periods of 2021–2040, 2041–2060, 2061–2080, and 2081–2100 were rated as “excellent”, with the values for the specified time periods being 0.859, 0.900, 0.931, and 0.913 for 16SrII-B; and 0.826, 0.837, 08.58, and 0.894 for 16SrII-D respectively. In addition, this study identified the hotspots and proportions of the areas that are vulnerable under the projected climate-change scenarios. The area of current (2021–2040) highly suitable distribution within the entire country for 16SrII-D was 19474.2 km2 (7.1%), while for 16SrII-B, an area of 8835 km2 (3.2%) was also highly suitable for the disease distribution. The proportions of these suitable areas are very significant from the available arable land standpoint. Therefore, the results from this study will be of immense benefit and will also bring significant contributions in mapping the areas of witches’ broom diseases in Oman. The results will equally aid the development of new strategies and the formulation of agricultural policies and practices in controlling the spread of the disease across Oman.

scholarly journals Predicting the Potential Geographic Distribution and Habitat Suitability of Two Economic Forest Trees on the Loess Plateau, China

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 747
Author(s):  
Wei Xu ◽  
Jingwei Jin ◽  
Jimin Cheng
Keyword(s):  
Loess Plateau ◽  
Geographic Distribution ◽  
Habitat Suitability ◽  
Prunus Armeniaca ◽  
Forest Trees ◽  
The Loess Plateau ◽  
Entropy Model ◽  
Bioclimatic Variables ◽  
Suitable Habitats ◽  
Potential Geographic Distribution

The Loess Plateau is one of the most fragile ecosystems in the world. In order to increase the biodiversity in the area, develop sustainable agriculture and increase the income of the local people, we simulated the potential geographic distribution of two economic forest trees (Malus pumila Mill and Prunus armeniaca L.) in the present and future under two climate scenarios, using the maximum entropy model. In this study, the importance and contributions of environmental variables, areas of suitable habitats, changes in habitat suitability, the direction and distance of habitat range shifts, the change ratios for habitat area and land use proportions, were measured. According to our results, bioclimatic variables, topographic variables and soil variables play a significant role in defining the distribution of M. pumila and P. armeniaca. The min temperature of coldest month (bio6) was the most important environmental variable for the distribution of the two economic forest trees. The second most important factors for M. pumila and P. armeniaca were, respectively, the elevation and precipitation of the driest quarter (bio17). At the time of the study, the area of above moderately suitable habitats (AMSH) was 8.7967 × 104 km2 and 11.4631 × 104 km2 for M. pumila and P. armeniaca. The effect of Shared Socioeconomic Pathway (SSP) 5-85 was more dramatic than that of SSP1-26. Between now and the 2090s (SSP 5-85), the AMSH area of M. pumila is expected to decrease to 7.5957 × 104 km2, while that of P. armeniaca will increase to 34.6465 × 104 km2. The suitability of M. pumila decreased dramatically in the south and southeast regions of the Loess Plateau, increased in the middle and west and resulted in a shift in distance in the range of 78.61~190.63 km to the northwest, while P. armeniaca shifted to the northwest by 64.77~139.85 km. This study provides information for future policymaking regarding economic forest trees in the Loess Plateau.

scholarly journals Projected Impact of Climate Change on Habitat Suitability of a Vulnerable Endemic Vachellia negrii (Pic.-Serm.) (Fabaceae) in Ethiopia

2021 ◽  
Vol 13 (20) ◽  
pp. 11275
Author(s):  
Arayaselassie Abebe Semu ◽  
Tamrat Bekele ◽  
Ermias Lulekal ◽  
Paloma Cariñanos ◽  
Sileshi Nemomissa
Keyword(s):  
Climate Change ◽  
Solar Radiation ◽  
Anthropogenic Impacts ◽  
Leading Edge ◽  
Range Shift ◽  
Suitable Habitat ◽  
Herbarium Specimens ◽  
Climate System Model ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables

Species tend to shift their suitable habitat both altitudinally and latitudinally under climate change. Range shift in plants brings about habitat contraction at rear edges, forcing leading edge populations to explore newly available suitable habitats. In order to detect these scenarios, modeling of the future geographical distribution of the species is widely used. Vachellia negrii (Pic.-Serm.) Kyal. & Boatwr. is endemic to Ethiopia and was assessed as vulnerable due to changes to its habitat by anthropogenic impacts. It occurs in upland wooded grassland from 2000–3100 m.a.s.l. The main objective of this study is to model the distribution of Vachellia negrii in Ethiopia by using Maxent under climate change. Nineteen bioclimatic variables were downloaded from an open source. Furthermore, topographic position index (tpi), solar radiation index (sri) and elevation were used. Two representative concentration pathways were selected (RCP 4.5 and RC P8.5) for the years 2050 and 2070 using the Community Climate System Model (CCSM 5). A correlation analysis of the bioclimatic variables has resulted in the retention of 10 bioclimatic variables for modeling. Forty-eight occurrence points were collected from herbarium specimens. The area under curve (AUC) is 0.94, indicating a high-performance level of the model. The distribution of the species is affected by elevation (26.4%), precipitation of the driest month (Bio 14, 21.7%), solar radiation (12.9%) and precipitation seasonality (Bio15, 12.2%). Whereas the RCP 8.5 has resulted in decrease of suitable areas of the species from the current 4,314,153.94 ha (3.80%) to 4,059,150.90 ha (3.58%) in 2050, this area will shrink to 3,555,828.71 ha in 2070 under the same scenario. As climate change severely affects the environment, highly suitable areas for the growth of the study subject will decrease by 758,325 ha. The study’s results shows that this vulnerable, endemic species is facing habitat contraction and requires interventions to ensure its long-term persistence.

scholarly journals Climate Change Increases the Expansion Risk of Helicoverpa zea in China According to Potential Geographical Distribution Estimation

Insects ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 79
Author(s):  
Haoxiang Zhao ◽  
Xiaoqing Xian ◽  
Zihua Zhao ◽  
Guifen Zhang ◽  
Wanxue Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Helicoverpa Zea ◽  
Host Plants ◽  
Plant Protection ◽  
Future Climate Change ◽  
General Tendency ◽  
Response Curves ◽  
Diurnal Range ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables

Helicoverpa zea, a well-documented and endemic pest throughout most of the Americas, affecting more than 100 species of host plants. It is a quarantine pest according to the Asia and Pacific Plant Protection Commission (APPPC) and the catalog of quarantine pests for plants imported to the People’s Republic of China. Based on 1781 global distribution records of H. zea and eight bioclimatic variables, the potential geographical distributions (PGDs) of H. zea were predicted by using a calibrated MaxEnt model. The contribution rate of bioclimatic variables and the jackknife method were integrated to assess the significant variables governing the PGDs. The response curves of bioclimatic variables were quantitatively determined to predict the PGDs of H. zea under climate change. The results showed that: (1) four out of the eight variables contributed the most to the model performance, namely, mean diurnal range (bio2), precipitation seasonality (bio15), precipitation of the driest quarter (bio17) and precipitation of the warmest quarter (bio18); (2) PGDs of H. zea under the current climate covered 418.15 × 104 km2, and were large in China; and (3) future climate change will facilitate the expansion of PGDs for H. zea under shared socioeconomic pathways (SSP) 1-2.6, SSP2-4.5, and SSP5-8.5 in both the 2030s and 2050s. The conversion of unsuitable to low suitability habitat and moderately to high suitability habitat increased by 8.43% and 2.35%, respectively. From the present day to the 2030s, under SSP1-2.6, SSP2-4.5 and SSP5-8.5, the centroid of the suitable habitats of H. zea showed a general tendency to move eastward; from 2030s to the 2050s, under SSP1-2.6 and SSP5-8.5, it moved southward, and it moved slightly northward under SSP2-4.5. According to bioclimatic conditions, H. zea has a high capacity for colonization by introduced individuals in China. Customs ports should pay attention to host plants and containers of H. zea and should exchange information to strengthen plant quarantine and pest monitoring, thus enhancing target management.

scholarly journals Potential Distribution of the Biocontrol Agent Toxorhynchites rutilus By 2070

2020 ◽  
Vol 36 (3) ◽  
pp. 131-138
Author(s):  
Daniel S. Marshall ◽  
Christopher J. Butler
Keyword(s):  
Climate Change ◽  
Biocontrol Agent ◽  
Mosquito Control ◽  
Disease Incidence ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Distribution Models ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables ◽  
Toxorhynchites Rutilus

ABSTRACT Climate change projections indicate that mosquito distributions will expand to include new areas of North America, increasing human exposure to mosquito-borne disease. Controlling these vectors is imperative, as mosquito-borne disease incidence will rise in response to expansion of mosquito range and increased seasonality. One means of mosquito control used in the USA is the biocontrol agent, Toxorhynchites rutilus. Climate change will open new habitats for its use by vector control organizations, but the extent of this change in habitat is currently unknown. We used a maximum entropy approach to create species distribution models for Tx. rutilus under 4 climate change scenarios by 2070. Mean temperature of warmest quarter (22.6°C to 29.1°C), annual precipitation (1,025.15 mm to 1,529.40 mm), and precipitation seasonality (≤17.86) are the most important bioclimatic variables for suitable habitat. The center of current possible habitat distribution of Tx. rutilus is in central Tennessee. Depending upon the scenario, we expect centroids to shift north-northeast by 97.68 km to 280.16 km by 2070. The extreme change in area of greater than 50% suitable habitat probability is 141.14% with 99.44% area retained. Our models indicate limited change in current habitat as well as creation of new habitat. These results are promising for North American mosquito control programs for the continued and potential combat of vector mosquitoes using Tx. rutilus.

Sign in / Sign up

Export Citation Format

Share Document