How climate change is likely to impact the future distribution of Date Palms and whether we can use simulation software to model this? Address: Australia
Striga asiatica (dicot), an obligate hemiparasitic of monocots, is a potential threat to South Am... more Striga asiatica (dicot), an obligate hemiparasitic of monocots, is a potential threat to South America. Determining the ecological factors that explain the occurrence and predicting suitable areas for S. asiatica are fundamental for designing prevention strategies. We developed a Spatio-temporal dynamics model and evaluated Brazil's Weekly Growth Index (GIW) for S. asiatica. We analyzed four Brazilian regions (Central-West, South, Southeast, and Northeast) to verify the local seasonal variation of the species in climatic data. Our results indicated areas with favorable climatic suitability for the species in part of South America. Seasonal assessment models showed that high rainfall and the dry and cold periods common in tropical regions affect the GIW for S. asiatica. When we associate periods with maximum rainfall of 53 mm per week and temperature above 20 • C, the GIW approaches the optimal index for the regions evaluated, indicating the influence of soil moisture and air temperature. Our risk assessment indicated that the Southeast and Northeast are at the most significant risk of S. asiatica invasion. Projections for climate change between 2040-2059 showed expansions in areas suitable for S. asiatica compared to the current climate of South America.
This study aimed to identify the global risk of invasion and establishment of Bedellia somnulente... more This study aimed to identify the global risk of invasion and establishment of Bedellia somnulentella, a pest of the sweet potato crop, for the present and future time, to develop policies and prevent future outbreaks. Current climate projections and future (2030, 2050, 2070, and 2100) of the insect B. somnulentella were carried out using CLIMEX. The projections showed that climate change could reduce areas of high aptitude for B. somnulentella in the parallel range of latitude 0°, the equator. On the other hand, temperate regions in the parallels with latitudes above 30°S and 30°N can increase hot and humid stress and become more suitable for the pest. This survey is based on weather data only. Data on land use and types, biotic interactions, diseases, natural enemies, alternative hosts, and competition were not considered for this model. Another uncertainty is associated with future levels of greenhouse gas emissions. The data presented here are helpful for the development of policies, studies, and strategies for the management of the B. somnulentella pest in the field. We encourage agricultural organizations in various countries to make strategic and long-term plans to avoid losses of millions of dollars through B. somnulentella.
climatic_past, climatic_present, continental areas data, nonclimatic_clay data. We also provided ... more climatic_past, climatic_present, continental areas data, nonclimatic_clay data. We also provided four README files for each data
The koala's (Phascolarctos cinereus) distribution is currently restricted to eastern and sout... more The koala's (Phascolarctos cinereus) distribution is currently restricted to eastern and south‐eastern Australia. However, fossil records dating from 70 ± 4 ka (ka = 103 years) from south‐western Australia and the Nullarbor Plain are evidence of subpopulation extinctions in the southwest at least after the Last Interglacial (128‐116 ka). We hypothesize that koala sub‐population extinctions resulted from the eastward retraction of the koala's main browse species in response to unsuitable climatic conditions. We further posit a general reduction in the distribution of main koala‐browse trees in the near future in response climate change. We modelled 60 koala‐browse species and constructed a set of correlative species distribution models for five time periods: Last Interglacial (128‐116 ka), Last Glacial Maximum (~ 23‐19 ka), Mid‐Holocene (~ 7‐5 ka), present (interpolations of observed data, representative of 1960‐1990), and 2070. We based our projections on five hindcasts and one forecast of climatic variables extracted from WorldClim based on two general circulation models (considering the most pessimistic scenario of high greenhouse‐gas emissions) and topsoil clay fraction. We used 17 dates of koala fossil specimens identified as reliable from 70 (± 4) to 535 (± 49) ka, with the last appearance of koalas at 151 ka in the southwest. The main simulated koala‐browse species were at their greatest modelled extent of suitability during the Last Glacial Maximum, with the greatest loss of koala habitat occurring between the Mid‐Holocene and the present. We predict a similar habitat loss between the present and 2070. The spatial patterns of habitat change support our hypothesis that koala extinctions in the southwest, Nullarbor Plain, and central South Australia resulted from the eastward retraction of the dominant koala‐browse species in response to long‐term climate changes. Future climate patterns will likely increase the extinction risk of koalas in their remaining eastern ranges
In this study, CLIMEX modeling software was used to develop a model of the potential distribution... more In this study, CLIMEX modeling software was used to develop a model of the potential distribution of P. dactylifera under current and various future climate scenarios for Spain. CLIMEX parameters were adjusted depending on satisfactory agreement between the potential and known distribution of P. dactylifera in northern African countries, Iraq, Saudi Arabia, Oman and Iran. The potential date palm distribution was modeled under current and future climate scenarios using one emission scenario (A2) with two different Global Climate Models (GCMs): CSIRO-Mk3.0 (CS) and MIROC-H (MR). The CLIMEX outputs were then refined by land use types and areas less than 10̊ slope, since sloping areas impose problems in hydraulic conductivity and root development. The refined results indicated that large areas in Spain are projected to become climatically more suitable for date palm growth by 2100. However, the results from the CS and MR GCMs show some disagreements. The refined MR GCM projected that ap...
Climate is changing and, as a consequence, some areas that are climatically suitable for date pal... more Climate is changing and, as a consequence, some areas that are climatically suitable for date palm (Phoenix dactylifera L.) cultivation at the present time will become unsuitable in the future. In contrast, some areas that are unsuitable under the current climate will become suitable in the future. Consequently, countries that are dependent on date fruit export will experience economic decline, while other countries ’ economies could improve. Knowledge of the likely potential distribution of this economically important crop under current and future climate scenarios will be useful in planning better strategies to manage such issues. This study used CLIMEX to estimate potential date palm distribution under current and future climate models by using one emission scenario (A2) with two different global climate models (GCMs), CSIRO-Mk3.0 (CS) and MIROC-H (MR). The results indicate that in North Africa, many areas with a suitable climate for this species are projected to become climatica...
SUMMARY The objective of the present paper is to use CLIMEX software to project how climate chang... more SUMMARY The objective of the present paper is to use CLIMEX software to project how climate change might impact the future distribution of date palm (Phoenix dactyliferaL.) in Iran.Although the outputs of this software are only based on the response of a species to climate, the CLIMEX results were refined in the present study using two nonclimatic parameters: (a) the location of soils containing suitable physicochemical properties and (b) the spatial distribution of soil types having suitable soil taxonomy for dates, as unsuitable soil types impose problems in air permeability, hydraulic conductivity and root development. Here, two different Global climate models (GCMs), CSIRO-Mk3.0 (CS) and MIROC-H(MR), wereemployedwiththe A2 emission scenario tomodelthe potentialdate palm distribution under current and future climates in Iran for the years 2030, 2050, 2070 and 2100. The results showed that only c. 0·30 of the area identified as suitable by CLIMEX will actually be suitable for date...
The level of destruction caused by an earthquake depends on a variety of factors, such as magnitu... more The level of destruction caused by an earthquake depends on a variety of factors, such as magnitude, duration, intensity, time of occurrence, and underlying geological features, which may be mitigated and reduced by the level of preparedness of risk management measures. Geospatial technologies offer a means by which earthquake occurrence can be predicted or foreshadowed; managed in terms of levels of preparation related to land use planning; availability of emergency shelters, medical resources, and food supplies; and assessment of damage and remedial priorities. This literature review paper surveys the geospatial technologies employed in earthquake research and disaster management. The objectives of this review paper are to assess: (1) the role of the range of geospatial data types; (2) the application of geospatial technologies to the stages of an earthquake; (3) the geospatial techniques used in earthquake hazard, vulnerability, and risk analysis; and (4) to discuss the role of g...
The level of destruction caused by an earthquake depends on a variety of factors, such as magnitu... more The level of destruction caused by an earthquake depends on a variety of factors, such as magnitude, duration, intensity, time of occurrence, and underlying geological features, which may be mitigated and reduced by the level of preparedness of risk management measures. Geospatial technologies offer a means by which earthquake occurrence can be predicted or foreshadowed; managed in terms of levels of preparation related to land use planning; availability of emergency shelters, medical resources, and food supplies; and assessment of damage and remedial priorities. This literature review paper surveys the geospatial technologies employed in earthquake research and disaster management. The objectives of this review paper are to assess: (1) the role of the range of geospatial data types; (2) the application of geospatial technologies to the stages of an earthquake; (3) the geospatial techniques used in earthquake hazard, vulnerability, and risk analysis; and (4) to discuss the role of geospatial techniques in earthquakes and related disasters. The review covers past, current, and potential earthquake-related applications of geospatial technology, together with the challenges that limit the extent of usefulness and effectiveness. While the focus is mainly on geospatial technology applied to earthquake research and management in practice, it also has validity as a framework for natural disaster risk assessments, emergency management, mitigation, and remediation, in general.
Striga asiatica (dicot), an obligate hemiparasitic of monocots, is a potential threat to South Am... more Striga asiatica (dicot), an obligate hemiparasitic of monocots, is a potential threat to South America. Determining the ecological factors that explain the occurrence and predicting suitable areas for S. asiatica are fundamental for designing prevention strategies. We developed a Spatio-temporal dynamics model and evaluated Brazil's Weekly Growth Index (GIW) for S. asiatica. We analyzed four Brazilian regions (Central-West, South, Southeast, and Northeast) to verify the local seasonal variation of the species in climatic data. Our results indicated areas with favorable climatic suitability for the species in part of South America. Seasonal assessment models showed that high rainfall and the dry and cold periods common in tropical regions affect the GIW for S. asiatica. When we associate periods with maximum rainfall of 53 mm per week and temperature above 20 • C, the GIW approaches the optimal index for the regions evaluated, indicating the influence of soil moisture and air temperature. Our risk assessment indicated that the Southeast and Northeast are at the most significant risk of S. asiatica invasion. Projections for climate change between 2040-2059 showed expansions in areas suitable for S. asiatica compared to the current climate of South America.
ABSTRACT One consequence of climate change is the change in the phenology and distribution of pla... more ABSTRACT One consequence of climate change is the change in the phenology and distribution of plants. The unique and distinctive date palm (Phoenix dactylifera L.) in Spain may be negatively or positively affected by climate change; particularly if favourable climate conditions shift to other areas. Effective management of such an economically important crop necessitates knowledge of their potential distribution under current and future climate. This study utilised CLIMEX to model the potential date palm distribution under current and future climate scenarios using one emission scenario (A2) with two different Global Climate Models (GCMs): CSIRO-Mk3.0 (CS) and MIROC-H (MR). In Spain, large areas are projected to become more climatically suitable for date palm growth by 2100. However, the results from the CS and MR GCMs show disagreements, especially from 2070 to 2100. The MR GCM projected that approximately 33.8 million hectares in Spain may become suitable for date palm growth, while the CS GCM showed approximately 28.12 million hectares by 2100. In other words, the MR model projected more areas may become climatically suitable for date palm cultivation compared with the CS model. Our results indicate that cold and wet stresses will play a significant role in date palm distribution in some Central and Northern regions of Spain by 2100. These results can inform strategic planning by government and agricultural organisations to identify areas for cultivation of this profitable crop in the future and to address those areas that will need greater attention, because they are becoming marginal regions for date palm cultivation. Introduction Agricultural productivity is sensitive to global climate change resulting from changes in air and sea surface temperatures
In this study, two strains of Aspergillus sp. and Lysinibacillus sp. with remarkable abilities to... more In this study, two strains of Aspergillus sp. and Lysinibacillus sp. with remarkable abilities to degrade low-density polyethylene (LDPE) were isolated from landfill soils in Tehran using enrichment culture and screening procedures. The biodegradation process was performed for 126 days in soil using UV- and non-UV-irradiated pure LDPE films without pro-oxidant additives in the presence and absence of mixed cultures of selected microorganisms. The process was monitored by measuring the microbial population, the biomass carbon, pH and respiration in the soil, and the mechanical properties of the films. The carbon dioxide measurements in the soil showed that the biodegradation in the un-inoculated treatments were slow and were about 7.6 % and 8.6 % of the mineralisation measured for the non-UV-irradiated and UV-irradiated LDPE, respectively, after 126 days. In contrast, in the presence of the selected microorganisms, biodegradation was much more efficient and the percentages of biodegr...
Large damages and losses resulting from floods are widely reported across the globe. Thus, the id... more Large damages and losses resulting from floods are widely reported across the globe. Thus, the identification of the flood-prone zones on a flood susceptibility map is very essential. To do so, 13 conditioning factors influencing the flood occurrence in Brisbane river catchment in Australia (i.e., topographic, water-related, geological, and land use factors) were acquired for further processing and modeling. In this study, artificial neural networks (ANN), deep learning neural networks (DLNN), and optimized DLNN using particle swarm optimization (PSO) were exploited to predict and estimate the susceptible areas to the future floods. The significance of the conditioning factors analysis for the region highlighted that altitude, distance from river, sediment transport index (STI), and slope played the most important roles, whereas stream power index (SPI) did not contribute to the hazardous situation. The performance of the models was evaluated against the statistical tests such as se...
The survival of humanity is dependent on the survival of forests and the ecosystems they support,... more The survival of humanity is dependent on the survival of forests and the ecosystems they support, yet annually wildfires destroy millions of hectares of global forestry. Wildfires take place under specific conditions and in certain regions, which can be studied through appropriate techniques. A variety of statistical modeling methods have been assessed by researchers; however, ensemble modeling of wildfire susceptibility has not been undertaken. We hypothesize that ensemble modeling of wildfire susceptibility is better than a single modeling technique. This study models the occurrence of wildfire in the Brisbane Catchment of Australia, which is an annual event, using the index of entropy (IoE), evidential belief function (EBF), and logistic regression (LR) ensemble techniques. As a secondary goal of this research, the spatial distribution of the wildfire risk from different aspects such as urbanization and ecosystem was evaluated. The highest accuracy (88.51%) was achieved using the...
This study predicts forest fire susceptibility in Chaloos Rood watershed in Iran using three mach... more This study predicts forest fire susceptibility in Chaloos Rood watershed in Iran using three machine learning (ML) models—multivariate adaptive regression splines (MARS), support vector machine (SVM), and boosted regression tree (BRT). The study utilizes 14 set of fire predictors derived from vegetation indices, climatic variables, environmental factors, and topographical features. To assess the suitability of the models and estimating the variance and bias of estimation, the training dataset obtained from the Natural Resources Directorate of Mazandaran province was subjected to resampling using cross validation (CV), bootstrap, and optimism bootstrap techniques. Using variance inflation factor (VIF), weight indicating the strength of the spatial relationship of the predictors to fire occurrence was assigned to each contributing variable. Subsequently, the models were trained and validated using the receiver operating characteristics (ROC) area under the curve (AUC) curve. Results o...
Predicting landslide occurrences can be difficult. However, failure to do so can be catastrophic,... more Predicting landslide occurrences can be difficult. However, failure to do so can be catastrophic, causing unwanted tragedies such as property damage, community displacement, and human casualties. Research into landslide susceptibility mapping (LSM) attempts to alleviate such catastrophes through the identification of landslide prone areas. Computational modelling techniques have been successful in related disaster scenarios, which motivate this work to explore such modelling for LSM. In this research, the potential of supervised machine learning and ensemble learning is investigated. Firstly, the Flexible Discriminant Analysis (FDA) supervised learning algorithm is trained for LSM and compared against other algorithms that have been widely used for the same purpose, namely Generalized Logistic Models (GLM), Boosted Regression Trees (BRT or GBM), and Random Forest (RF). Next, an ensemble model consisting of all four algorithms is implemented to examine possible performance improvemen...
Striga asiatica (dicot), an obligate hemiparasitic of monocots, is a potential threat to South Am... more Striga asiatica (dicot), an obligate hemiparasitic of monocots, is a potential threat to South America. Determining the ecological factors that explain the occurrence and predicting suitable areas for S. asiatica are fundamental for designing prevention strategies. We developed a Spatio-temporal dynamics model and evaluated Brazil's Weekly Growth Index (GIW) for S. asiatica. We analyzed four Brazilian regions (Central-West, South, Southeast, and Northeast) to verify the local seasonal variation of the species in climatic data. Our results indicated areas with favorable climatic suitability for the species in part of South America. Seasonal assessment models showed that high rainfall and the dry and cold periods common in tropical regions affect the GIW for S. asiatica. When we associate periods with maximum rainfall of 53 mm per week and temperature above 20 • C, the GIW approaches the optimal index for the regions evaluated, indicating the influence of soil moisture and air temperature. Our risk assessment indicated that the Southeast and Northeast are at the most significant risk of S. asiatica invasion. Projections for climate change between 2040-2059 showed expansions in areas suitable for S. asiatica compared to the current climate of South America.
This study aimed to identify the global risk of invasion and establishment of Bedellia somnulente... more This study aimed to identify the global risk of invasion and establishment of Bedellia somnulentella, a pest of the sweet potato crop, for the present and future time, to develop policies and prevent future outbreaks. Current climate projections and future (2030, 2050, 2070, and 2100) of the insect B. somnulentella were carried out using CLIMEX. The projections showed that climate change could reduce areas of high aptitude for B. somnulentella in the parallel range of latitude 0°, the equator. On the other hand, temperate regions in the parallels with latitudes above 30°S and 30°N can increase hot and humid stress and become more suitable for the pest. This survey is based on weather data only. Data on land use and types, biotic interactions, diseases, natural enemies, alternative hosts, and competition were not considered for this model. Another uncertainty is associated with future levels of greenhouse gas emissions. The data presented here are helpful for the development of policies, studies, and strategies for the management of the B. somnulentella pest in the field. We encourage agricultural organizations in various countries to make strategic and long-term plans to avoid losses of millions of dollars through B. somnulentella.
climatic_past, climatic_present, continental areas data, nonclimatic_clay data. We also provided ... more climatic_past, climatic_present, continental areas data, nonclimatic_clay data. We also provided four README files for each data
The koala's (Phascolarctos cinereus) distribution is currently restricted to eastern and sout... more The koala's (Phascolarctos cinereus) distribution is currently restricted to eastern and south‐eastern Australia. However, fossil records dating from 70 ± 4 ka (ka = 103 years) from south‐western Australia and the Nullarbor Plain are evidence of subpopulation extinctions in the southwest at least after the Last Interglacial (128‐116 ka). We hypothesize that koala sub‐population extinctions resulted from the eastward retraction of the koala's main browse species in response to unsuitable climatic conditions. We further posit a general reduction in the distribution of main koala‐browse trees in the near future in response climate change. We modelled 60 koala‐browse species and constructed a set of correlative species distribution models for five time periods: Last Interglacial (128‐116 ka), Last Glacial Maximum (~ 23‐19 ka), Mid‐Holocene (~ 7‐5 ka), present (interpolations of observed data, representative of 1960‐1990), and 2070. We based our projections on five hindcasts and one forecast of climatic variables extracted from WorldClim based on two general circulation models (considering the most pessimistic scenario of high greenhouse‐gas emissions) and topsoil clay fraction. We used 17 dates of koala fossil specimens identified as reliable from 70 (± 4) to 535 (± 49) ka, with the last appearance of koalas at 151 ka in the southwest. The main simulated koala‐browse species were at their greatest modelled extent of suitability during the Last Glacial Maximum, with the greatest loss of koala habitat occurring between the Mid‐Holocene and the present. We predict a similar habitat loss between the present and 2070. The spatial patterns of habitat change support our hypothesis that koala extinctions in the southwest, Nullarbor Plain, and central South Australia resulted from the eastward retraction of the dominant koala‐browse species in response to long‐term climate changes. Future climate patterns will likely increase the extinction risk of koalas in their remaining eastern ranges
In this study, CLIMEX modeling software was used to develop a model of the potential distribution... more In this study, CLIMEX modeling software was used to develop a model of the potential distribution of P. dactylifera under current and various future climate scenarios for Spain. CLIMEX parameters were adjusted depending on satisfactory agreement between the potential and known distribution of P. dactylifera in northern African countries, Iraq, Saudi Arabia, Oman and Iran. The potential date palm distribution was modeled under current and future climate scenarios using one emission scenario (A2) with two different Global Climate Models (GCMs): CSIRO-Mk3.0 (CS) and MIROC-H (MR). The CLIMEX outputs were then refined by land use types and areas less than 10̊ slope, since sloping areas impose problems in hydraulic conductivity and root development. The refined results indicated that large areas in Spain are projected to become climatically more suitable for date palm growth by 2100. However, the results from the CS and MR GCMs show some disagreements. The refined MR GCM projected that ap...
Climate is changing and, as a consequence, some areas that are climatically suitable for date pal... more Climate is changing and, as a consequence, some areas that are climatically suitable for date palm (Phoenix dactylifera L.) cultivation at the present time will become unsuitable in the future. In contrast, some areas that are unsuitable under the current climate will become suitable in the future. Consequently, countries that are dependent on date fruit export will experience economic decline, while other countries ’ economies could improve. Knowledge of the likely potential distribution of this economically important crop under current and future climate scenarios will be useful in planning better strategies to manage such issues. This study used CLIMEX to estimate potential date palm distribution under current and future climate models by using one emission scenario (A2) with two different global climate models (GCMs), CSIRO-Mk3.0 (CS) and MIROC-H (MR). The results indicate that in North Africa, many areas with a suitable climate for this species are projected to become climatica...
SUMMARY The objective of the present paper is to use CLIMEX software to project how climate chang... more SUMMARY The objective of the present paper is to use CLIMEX software to project how climate change might impact the future distribution of date palm (Phoenix dactyliferaL.) in Iran.Although the outputs of this software are only based on the response of a species to climate, the CLIMEX results were refined in the present study using two nonclimatic parameters: (a) the location of soils containing suitable physicochemical properties and (b) the spatial distribution of soil types having suitable soil taxonomy for dates, as unsuitable soil types impose problems in air permeability, hydraulic conductivity and root development. Here, two different Global climate models (GCMs), CSIRO-Mk3.0 (CS) and MIROC-H(MR), wereemployedwiththe A2 emission scenario tomodelthe potentialdate palm distribution under current and future climates in Iran for the years 2030, 2050, 2070 and 2100. The results showed that only c. 0·30 of the area identified as suitable by CLIMEX will actually be suitable for date...
The level of destruction caused by an earthquake depends on a variety of factors, such as magnitu... more The level of destruction caused by an earthquake depends on a variety of factors, such as magnitude, duration, intensity, time of occurrence, and underlying geological features, which may be mitigated and reduced by the level of preparedness of risk management measures. Geospatial technologies offer a means by which earthquake occurrence can be predicted or foreshadowed; managed in terms of levels of preparation related to land use planning; availability of emergency shelters, medical resources, and food supplies; and assessment of damage and remedial priorities. This literature review paper surveys the geospatial technologies employed in earthquake research and disaster management. The objectives of this review paper are to assess: (1) the role of the range of geospatial data types; (2) the application of geospatial technologies to the stages of an earthquake; (3) the geospatial techniques used in earthquake hazard, vulnerability, and risk analysis; and (4) to discuss the role of g...
The level of destruction caused by an earthquake depends on a variety of factors, such as magnitu... more The level of destruction caused by an earthquake depends on a variety of factors, such as magnitude, duration, intensity, time of occurrence, and underlying geological features, which may be mitigated and reduced by the level of preparedness of risk management measures. Geospatial technologies offer a means by which earthquake occurrence can be predicted or foreshadowed; managed in terms of levels of preparation related to land use planning; availability of emergency shelters, medical resources, and food supplies; and assessment of damage and remedial priorities. This literature review paper surveys the geospatial technologies employed in earthquake research and disaster management. The objectives of this review paper are to assess: (1) the role of the range of geospatial data types; (2) the application of geospatial technologies to the stages of an earthquake; (3) the geospatial techniques used in earthquake hazard, vulnerability, and risk analysis; and (4) to discuss the role of geospatial techniques in earthquakes and related disasters. The review covers past, current, and potential earthquake-related applications of geospatial technology, together with the challenges that limit the extent of usefulness and effectiveness. While the focus is mainly on geospatial technology applied to earthquake research and management in practice, it also has validity as a framework for natural disaster risk assessments, emergency management, mitigation, and remediation, in general.
Striga asiatica (dicot), an obligate hemiparasitic of monocots, is a potential threat to South Am... more Striga asiatica (dicot), an obligate hemiparasitic of monocots, is a potential threat to South America. Determining the ecological factors that explain the occurrence and predicting suitable areas for S. asiatica are fundamental for designing prevention strategies. We developed a Spatio-temporal dynamics model and evaluated Brazil's Weekly Growth Index (GIW) for S. asiatica. We analyzed four Brazilian regions (Central-West, South, Southeast, and Northeast) to verify the local seasonal variation of the species in climatic data. Our results indicated areas with favorable climatic suitability for the species in part of South America. Seasonal assessment models showed that high rainfall and the dry and cold periods common in tropical regions affect the GIW for S. asiatica. When we associate periods with maximum rainfall of 53 mm per week and temperature above 20 • C, the GIW approaches the optimal index for the regions evaluated, indicating the influence of soil moisture and air temperature. Our risk assessment indicated that the Southeast and Northeast are at the most significant risk of S. asiatica invasion. Projections for climate change between 2040-2059 showed expansions in areas suitable for S. asiatica compared to the current climate of South America.
ABSTRACT One consequence of climate change is the change in the phenology and distribution of pla... more ABSTRACT One consequence of climate change is the change in the phenology and distribution of plants. The unique and distinctive date palm (Phoenix dactylifera L.) in Spain may be negatively or positively affected by climate change; particularly if favourable climate conditions shift to other areas. Effective management of such an economically important crop necessitates knowledge of their potential distribution under current and future climate. This study utilised CLIMEX to model the potential date palm distribution under current and future climate scenarios using one emission scenario (A2) with two different Global Climate Models (GCMs): CSIRO-Mk3.0 (CS) and MIROC-H (MR). In Spain, large areas are projected to become more climatically suitable for date palm growth by 2100. However, the results from the CS and MR GCMs show disagreements, especially from 2070 to 2100. The MR GCM projected that approximately 33.8 million hectares in Spain may become suitable for date palm growth, while the CS GCM showed approximately 28.12 million hectares by 2100. In other words, the MR model projected more areas may become climatically suitable for date palm cultivation compared with the CS model. Our results indicate that cold and wet stresses will play a significant role in date palm distribution in some Central and Northern regions of Spain by 2100. These results can inform strategic planning by government and agricultural organisations to identify areas for cultivation of this profitable crop in the future and to address those areas that will need greater attention, because they are becoming marginal regions for date palm cultivation. Introduction Agricultural productivity is sensitive to global climate change resulting from changes in air and sea surface temperatures
In this study, two strains of Aspergillus sp. and Lysinibacillus sp. with remarkable abilities to... more In this study, two strains of Aspergillus sp. and Lysinibacillus sp. with remarkable abilities to degrade low-density polyethylene (LDPE) were isolated from landfill soils in Tehran using enrichment culture and screening procedures. The biodegradation process was performed for 126 days in soil using UV- and non-UV-irradiated pure LDPE films without pro-oxidant additives in the presence and absence of mixed cultures of selected microorganisms. The process was monitored by measuring the microbial population, the biomass carbon, pH and respiration in the soil, and the mechanical properties of the films. The carbon dioxide measurements in the soil showed that the biodegradation in the un-inoculated treatments were slow and were about 7.6 % and 8.6 % of the mineralisation measured for the non-UV-irradiated and UV-irradiated LDPE, respectively, after 126 days. In contrast, in the presence of the selected microorganisms, biodegradation was much more efficient and the percentages of biodegr...
Large damages and losses resulting from floods are widely reported across the globe. Thus, the id... more Large damages and losses resulting from floods are widely reported across the globe. Thus, the identification of the flood-prone zones on a flood susceptibility map is very essential. To do so, 13 conditioning factors influencing the flood occurrence in Brisbane river catchment in Australia (i.e., topographic, water-related, geological, and land use factors) were acquired for further processing and modeling. In this study, artificial neural networks (ANN), deep learning neural networks (DLNN), and optimized DLNN using particle swarm optimization (PSO) were exploited to predict and estimate the susceptible areas to the future floods. The significance of the conditioning factors analysis for the region highlighted that altitude, distance from river, sediment transport index (STI), and slope played the most important roles, whereas stream power index (SPI) did not contribute to the hazardous situation. The performance of the models was evaluated against the statistical tests such as se...
The survival of humanity is dependent on the survival of forests and the ecosystems they support,... more The survival of humanity is dependent on the survival of forests and the ecosystems they support, yet annually wildfires destroy millions of hectares of global forestry. Wildfires take place under specific conditions and in certain regions, which can be studied through appropriate techniques. A variety of statistical modeling methods have been assessed by researchers; however, ensemble modeling of wildfire susceptibility has not been undertaken. We hypothesize that ensemble modeling of wildfire susceptibility is better than a single modeling technique. This study models the occurrence of wildfire in the Brisbane Catchment of Australia, which is an annual event, using the index of entropy (IoE), evidential belief function (EBF), and logistic regression (LR) ensemble techniques. As a secondary goal of this research, the spatial distribution of the wildfire risk from different aspects such as urbanization and ecosystem was evaluated. The highest accuracy (88.51%) was achieved using the...
This study predicts forest fire susceptibility in Chaloos Rood watershed in Iran using three mach... more This study predicts forest fire susceptibility in Chaloos Rood watershed in Iran using three machine learning (ML) models—multivariate adaptive regression splines (MARS), support vector machine (SVM), and boosted regression tree (BRT). The study utilizes 14 set of fire predictors derived from vegetation indices, climatic variables, environmental factors, and topographical features. To assess the suitability of the models and estimating the variance and bias of estimation, the training dataset obtained from the Natural Resources Directorate of Mazandaran province was subjected to resampling using cross validation (CV), bootstrap, and optimism bootstrap techniques. Using variance inflation factor (VIF), weight indicating the strength of the spatial relationship of the predictors to fire occurrence was assigned to each contributing variable. Subsequently, the models were trained and validated using the receiver operating characteristics (ROC) area under the curve (AUC) curve. Results o...
Predicting landslide occurrences can be difficult. However, failure to do so can be catastrophic,... more Predicting landslide occurrences can be difficult. However, failure to do so can be catastrophic, causing unwanted tragedies such as property damage, community displacement, and human casualties. Research into landslide susceptibility mapping (LSM) attempts to alleviate such catastrophes through the identification of landslide prone areas. Computational modelling techniques have been successful in related disaster scenarios, which motivate this work to explore such modelling for LSM. In this research, the potential of supervised machine learning and ensemble learning is investigated. Firstly, the Flexible Discriminant Analysis (FDA) supervised learning algorithm is trained for LSM and compared against other algorithms that have been widely used for the same purpose, namely Generalized Logistic Models (GLM), Boosted Regression Trees (BRT or GBM), and Random Forest (RF). Next, an ensemble model consisting of all four algorithms is implemented to examine possible performance improvemen...
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