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.

A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using open-field Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed “sensitive”. Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive.

Background: 'Neoleucinodes elegantalis' is one of the major insect pests of 'Solanum lycopersicum'. Currently, 'N. elegantalis' is present only in America and the Caribbean, and is a threat in the world's largest 'S. lycopersicum'-producing countries. In terms of potential impact on agriculture, the impact of climate change on insect invasions must be a concern. At present, no research exists regarding the effects of climatic change on the risk level of 'N. elegantalis'. The purpose of this study was to develop a model for 'S. lycopersicum' and 'N. elegantalis', utilizing CLIMEX to determine risk levels of 'N. elegantalis' in open-field 'S. lycopersicum' cultivation in the present and under projected climate change, using the global climate model CSIRO-Mk3.0. Results: Large areas are projected to be suitable for 'N. elegantalis' and optimal for open-field 'S. lycopersicum' cultivation at the present time. However, in the future these areas will become unsuitable for both species. Conversely, other regions in the future may become optimal for open-field 'S. lycopersicum' cultivation, with a varying risk level for 'N. elegantalis'. Conclusion: The risk level results presented here provide a useful tool to design strategies to prevent the introduction and establishment of 'N. elegantalis' in open-field 'S. lycopersicum' cultivation.

Seasonal variations are important components in understanding the ecology of insect population of crops. Ecological studies through modeling may be a useful tool for enhancing knowledge of seasonal patterns of insects on field crops as well as seasonal patterns of favorable climatic conditions for species. Recently CLIMEX, a semi-mechanistic niche model, was upgraded and enhanced to consider spatio-temporal dynamics of climate suitability through time. In this study, attempts were made to determine monthly variations of climate suitability for 'Neoleucinodes elegantalis' (Guenée) (Lepidoptera: Crambidae) in five commercial tomato crop localities through the latest version of CLIMEX. We observed that N. elegantalis displays seasonality with increased abundance in tomato crops during summer and autumn, corresponding to the first 6 months of the year in monitored areas in this study. Our model demonstrated a strong accord between the CLIMEX weekly growth index (GIw) and the density of 'N. elegantalis' for this period, thus indicating a greater confidence in our model results. Our model shows a seasonal variability of climatic suitability for 'N. elegantalis' and provides useful information for initiating methods for timely management, such as sampling strategies and control, during periods of high degree of suitability for 'N. elegantalis'. In this study, we ensure that the simulation results are valid through our verification using field data.

Palm oil (PO) is a very important commodity used as food, in pharmaceuticals, for cooking and as biodiesel: PO is a major contributor to the economies of many countries, especially Indonesia and Malaysia. Novel tropical regions are being explored increasingly to grow oil palm as current land decreases, whilst recent published modelling studies by the current authors for Malaysia and Indonesia indicate that the climate will become less suitable. Countries that grow the crop commercially include those in Latin America, Africa and Asia. How will climate change (CC) affect the ability to grow oil palm in these countries? Worldwide projections for apt climate were made using Climex software in the present paper and the global area with unsuitable climate was assessed to increase by 6%, whilst highly suitable climate (HSC) decreased by 22% by 2050. The suitability decreases are dramatic by 2100 suggesting regions totally unsuitable for growing OP, which are currently appropriate: the global area with unsuitable climate increased from 154 to 169 million km² and HSC decreased from 17 to 4 million km². This second assessment of Indonesia and Malaysia confirmed the original findings by the current authors of large decreases in suitability. Many parts of Latin America and Africa were dramatically decreased: reductions in HSC for Brazil, Columbia and Nigeria are projected to be 119 000, 35 and 1 from 5 000 000, 219 and 69 km², respectively. However, increases in aptness were observed in 2050 for Paraguay and Madagascar (HSC increases were 90 and 41%, respectively), which were maintained until 2100 (95 and 45%, respectively). Lesser or transient increases were seen for a few other countries. Hot, dry and cold climate stresses upon oil palm for all regions are also provided. These results have negative implications for growing oil palm in countries as: (a) alternatives to Malaysia and Indonesia or (b) economic resources per se. The inability to grow oil palm may assist in amelioration of CC, although the situation is complex. Data suggest a moderate movement of apposite climate towards the poles as previously predicted.

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.

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 biodegradation were 29.5% and 15.8% for the UV-irradiated and non-UV-irradiated films, respectively. The percentage decrease in the carbonyl index was higher for the UV-irradiated LDPE when the biodegradation was performed in soil inoculated with the selected microorganisms. The percentage elongation of the films decreased during the biodegradation process. The Fourier transform infra-red (FT-IR), x-ray diffraction (XRD) and scanning electron microscopy (SEM) were used to determine structural, morphological and surface changes on polyethylene. These analyses showed that the selected microorganisms could modify and colonise both types of polyethylene. This study also confirmed the ability of these isolates to utilise virgin polyethylene without pro-oxidant additives and oxidation pretreatment, as the carbon source.

Date palm (Phoenix dactylifera L.) is an important cash crop in many countries, including Saudi Arabia. Understanding the likely potential distribution of this crop under current and future climate scenarios will enable environmental managers to prepare appropriate strategies to manage the changes. In the current study, the simulation model CLIMEX was used to develop a niche model to estimate the impacts of climate change on the current and future potential distribution of date palm. Two global climate models (GCMs), CSIRO-Mk3.0 and MIROC-H under the A2 emission scenario for 2050 and 2100, were used to assess the impacts of climate change. A sensitivity analysis was conducted to identify which model parameters had the most effect on date palm distribution. Further refinements of the potential distributions were performed through the integration of six non-climatic parameters in a geographic information system. Areas containing suitable soil taxonomy, soil texture, soil salinity, land use, landform and slopes of <7° for date palm were selected as suitable refining variables in order to achieve more realistic models. The results from both GCMs exhibited a significant reduction in climatic suitability for date palm cultivation in Saudi Arabia by 2100. Climate sensitivity analysis indicates that the lower optimal soil moisture, cold stress temperature threshold and wet stress threshold parameters had the most effect on sensitivity, while other parameters were moderately sensitive or insensitive to change. The study also demonstrated that the inclusion of non-climatic parameters with CLIMEX outputs increased the explanatory power of the models. Such models can provide early warning scenarios for how environmental managers should respond to changes in the distribution of the date palm in Saudi Arabia.

The aim of this study was to have a comparative investigation and evaluation of the capabilities of correlative and mechanistic modeling processes, applied to the projection of future distributions of date palm in novel environments and to establish a method of minimizing uncertainty in the projections of differing techniques. The location of this study on a global scale is in Middle Eastern Countries. We compared the mechanistic model CLIMEX (CL) with the correlative models MaxEnt (MX), Boosted Regression Trees (BRT), and Random Forests (RF) to project current and future distributions of date palm ('Phoenix dactylifera' L.). The Global Climate Model (GCM), the CSIRO-Mk3.0 (CS) using the A2 emissions scenario, was selected for making projections. Both indigenous and alien distribution data of the species were utilized in the modeling process. The common areas predicted by MX, BRT, RF, and CL from the CS GCM were extracted and compared to ascertain projection uncertainty levels of each individual technique. The common areas identified by all four modeling techniques were used to produce a map indicating suitable and unsuitable areas for date palm cultivation for Middle Eastern countries, for the present and the year 2100. The four different modeling approaches predict fairly different distributions. Projections from CL were more conservative than from MX. The BRT and RF were the most conservative methods in terms of projections for the current time. The combination of the final CL and MX projections for the present and 2100 provide higher certainty concerning those areas that will become highly suitable for future date palm cultivation. According to the four models, cold, hot, and wet stress, with differences on a regional basis, appears to be the major restrictions on future date palm distribution. The results demonstrate variances in the projections, resulting from different techniques. The assessment and interpretation of model projections requires reservations, especially in correlative models such as MX, BRT, and RF. Intersections between different techniques may decrease uncertainty in future distribution projections. However, readers should not miss the fact that the uncertainties are mostly because the future GHG emission scenarios are unknowable with sufficient precision. Suggestions towards methodology and processing for improving projections are included.