2014, Shabani, Farzin, Kumar, Lalit, Taylor, Subhashni

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 dactylifera' L.) 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 non-climatic 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), were employed with the A2 emission scenario to model the potential date 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 palm cultivation: the rest of the area comprises soil types that are not favourable for date palm cultivation. Moreover, the refined outputs indicate that the total area suitable for date palm cultivation will increase to 31.3 million ha by 2100, compared with 4.8 million ha for current date palm cultivation. The present results also indicate that only heat stress will have an impact on date palm distribution in Iran by 2100, with the areas currently impacted by cold stress diminishing by 2100.

2016, Shabani, Farzin, Kumar, Lalit, Ahmadi, Mohsen

To investigate the comparative abilities of six different bioclimatic models in an independent area, utilizing the distribution of eight different species available at a global scale and in Australia. Global scale and Australia. We tested a variety of bioclimatic models for eight different plant species employing five discriminatory correlative species distribution models (SDMs) including Generalized Linear Model (GLM), MaxEnt, Random Forest (RF), Boosted Regression Tree (BRT), Bioclim, together with CLIMEX (CL) as a mechanistic niche model. These models were fitted using a training dataset of available global data, but with the exclusion of Australian locations. The capabilities of these techniques in projecting suitable climate, based on independent records for these species in Australia, were compared. Thus, Australia is not used to calibrate the models and therefore it is as an independent area regarding geographic locations. To assess and compare performance, we utilized the area under the receiver operating characteristic (ROC) curves (AUC), true skill statistic (TSS), and fractional predicted areas for all SDMs. In addition, we assessed satisfactory agreements between the outputs of the six different bioclimatic models, for all eight species in Australia. The modeling method impacted on potential distribution predictions under current climate. However, the utilization of sensitivity and the fractional predicted areas showed that GLM, MaxEnt, Bioclim, and CL had the highest sensitivity for Australian climate conditions. Bioclim calculated the highest fractional predicted area of an independent area, while RF and BRT were poor. For many applications, it is difficult to decide which bioclimatic model to use. This research shows that variable results are obtained using different SDMs in an independent area. This research also shows that the SDMs produce different results for different species; for example, Bioclim may not be good for one species but works better for other species. Also, when projecting a "large" number of species into novel environments or in an independent area, the selection of the "best" model/technique is often less reliable than an ensemble modeling approach. In addition, it is vital to understand the accuracy of SDMs' predictions. Further, while TSS, together with fractional predicted areas, are appropriate tools for the measurement of accuracy between model results, particularly when undertaking projections on an independent area, AUC has been proved not to be. Our study highlights that each one of these models (CL, Bioclim, GLM, MaxEnt, BRT, and RF) provides slightly different results on projections and that it may be safer to use an ensemble of models.

2017, Shabani, Farzin, Kumar, Lalit, Ahmadi, Mohsen, Esmaeili, Atefeh

Analyses of knowledge gaps can highlight imbalances in research, encouraging greater proportionality in the distribution of research efforts. In this research we used generalized linear mixed models (GLMM) with the aim to determine if research efforts for the period 2005–2015 for terrestrial vertebrates of Amphibia, Aves, Mammalia and Reptilia in the South Pacific region were correlated with conservation status (critically endangered (CR), endangered (EN), vulnerable (VU), least concern (LC) and near threatened (NT)) or population trends (increasing, stable, decreasing and unknown) through the International Union for Conservation of Nature (IUCN) database. Our results showed that research distribution was uneven across different classes. Out of 633623 investigated papers, the average number of publications per species was 43.7, 306.7, 717.6 and 115.3 for Amphibia (284 species), Aves (1306 species), Mammalia (243 species) and Reptilia (400 species), respectively. Consistently, the lower publication effort on Amphibia compared to other taxonomic classes was revealed as significant by GLMM analysis. There was no significant differences in research effort among levels of conservation status. However, we found significantly different publication efforts among population trends of all examined species in that species with "unknown" population trends gained significantly lower researchers' attention compared to species with "decreasing" trend. Results also indicated that, although it was not significant, the highest attention is given to species with "increasing" population trend over all taxonomic classes. Using the Information Theoretic approach we also generated a set of competing models to identify most important factors influencing research efforts, revealing that the highest ranked model included taxonomic class and population.

2017, Silva, R S, Kumar, Lalit, Shabani, Farzin, Picanco, M C

Tomato ('Solanum lycopersicum' L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

2017, Tehrany, Mahyat, Shabani, Farzin, Javier, Dymphna, Kumar, Lalit

Soil erosion is a global geological hazard which can be mitigated through better future land-use planning. In the current research, a Dempster-Shafer-based evidential belief function (EBF) and frequency ratio (FR) were used to map the soil erosion susceptible areas and their outcomes were compared subsequently. These methods were selected due to their efficiency and popularity in natural hazard studies. Moreover, the application of EBF is poorly examined in this area of research. Nine conditioning factors belonging to the current time, and rainfall intensity for the two time periods of current time and 2100 based on the A2 scenario CSIRO global climate model, were utilized in this research. The main aim was to estimate and compare the soil erosion hazards at Southern Luzon in the Philippines under two time periods, current time and 2100. This region has been highly affected by erosion and has not received much attention in the past. The area under the curve outcomes indicated that the FR model produced 70.6% prediction rate, while EBF showed superior prediction accuracy with a rate of 83.1%. The results also project that soil erosion hazards in the Philippines will increase due to changes in rainfall patterns by 2100.

2015, Shabani, Farzin, Kumar, Lalit, Esmaeili, Atefeh

'Aim': To model the areas becoming and remaining highly suitable for 'Aspergillus niger' growth over the next ninety years by future climate alteration, in relation to the species' potential enhancement of Low Density Polyethylene (LDPE) biodegradation in soil. 'Location': Global scale 'Methods': Projections of 'A. niger' growth suitability for 2030, 2050, 2070 and 2100 were made using the A2 emissions scenario together with two Global Climate Models (GCMs): the CSIRO-Mk3.0 (CS) model and the MIROC-H (MR) model through CLIMEX software. Subsequently the outputs of the two GCMs were overlaid to extract common areas in each period of time, providing higher certainty concerning areas which will become highly suitable to 'A. niger' in the future. Afterwards, GIS software was employed to extract sustainable regions for this species growth from present time up to 2100. 'Results': Central and eastern Argentina, Uruguay, southern Brazil, eastern United States, southern France, northern Spain, central and southern Italy, southern Hungary, eastern Albania, south western Russia, central and eastern China, eastern Australia, south east of South Africa, central Zambia, Rwanda, Burundi, central Kenya, central Ethiopia and north eastern Oman will be highly suitable for 'A. niger' growth from present time up to 2100. 'Main conclusions': Accurately evaluating the impact of landfilling on land use and predicting future climate are vital components for effective long-term planning of waste management. From a social and economic perspective, utilization of our mapped projections to detect suitable regions for establishing landfills in areas highly sustainable for microorganisms like 'A. niger' growth will allow a significant cost reduction and improve the performance of biodegradation of LDPE over a long period of time, through making use of natural climatic and environmental factors.

2016, Shabani, Farzin, Cacho, Oscar J, Kumar, Lalit

This study set out to build a model identifying areas where a positive Net Present Value (NPV) could be obtained from date palm ('Phoenix dactylifera') using CLIMEX and six parameters including (a) suitable soil taxonomy and physicochemical soil properties, (b) slopes of less than 10°, (c) land uses suitable for date palm cultivation, (d) availability of roads, (e) availability of water, and (f) low risk of the lethal disease caused by 'Fusarium oxysporum' f. spp. in the years 2030, 2050, 2070, and 2100 in Iran. Here, we utilized the A2 scenario and two global climate models (GCMs): CSIRO-Mk3.0 (CS) and MIROC-H (MR). Economic feasibility was estimated based on the assumption that the decision to plant date palms by landholders is motivated by a desire to maximize their return to land. Our results indicate that only 5450 km² of southern Iran will be highly profitable for cultivation of date palm, with NPV > 10,000, while profitable (with NPV between 4200 and 10,000) and moderately profitable (with NPV between 0 and 4200) areas would cover only 500 and 50 km², respectively, in future. A comparison of mean outputs from the two chosen GCMs and those of the economic and CLIMEX output combination indicates that only about 0.01% of areas from both GCMs will be highly economically viable for cultivation of date palm. In this study we ensure that the predictions become robust, rather than producing hypothetical findings, limited purely to publication.