Dataset Information

Modeling current and future global distribution of Chrysomya bezziana under changing climate.

ABSTRACT: In the last few years, significant changes in climate have had a disparate effect on biodiversity. The influences of these changes are random and unpredictable. The resurgence of insect pests, especially of medical and veterinary importance, often corresponds with climate changes. The Old World screwworm, Chrysomya bezziana, is one of the most important myiasis-causing flies that parasitize warm-blooded animals in the Eastern Hemisphere. We used a spatial distribution modeling approach to estimate the consequences of climatic changes on the potential geographic distribution of this insect throughout the world currently and in the future. A Maxent model used occurrence data from 104 localities and 19 climatic factors to predict the suitable habitat regions throughout the world. Two representative concentration pathways 2.6 and 8.5, were used to forecast the future distribution of C. bezziana in 2050 and 2070. The Maxent model for C. bezziana provided a satisfactory result, with a high value of the Area Under Curve equal to 0.855 (±0.001). Furthermore, the True Skilled Statistics value is equal to 0.67. These values indicate the significant influence on the model of the ecology of this fly species. Jackknife test indicated that temperature variables play a significant role in C. bezziana dynamics. The resultant models indicated the areas at risk of invasion by potential serious medical/veterinary issues, especially in countries with a large livestock production.

SUBMITTER: Hosni EM

PROVIDER: S-EPMC7080715 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Modeling current and future global distribution of Chrysomya bezziana under changing climate.

Hosni Eslam M EM Nasser Mohamed G MG Al-Ashaal Sara A SA Rady Magda H MH Kenawy Mohamed A MA

Scientific reports 20200318 1

In the last few years, significant changes in climate have had a disparate effect on biodiversity. The influences of these changes are random and unpredictable. The resurgence of insect pests, especially of medical and veterinary importance, often corresponds with climate changes. The Old World screwworm, Chrysomya bezziana, is one of the most important myiasis-causing flies that parasitize warm-blooded animals in the Eastern Hemisphere. We used a spatial distribution modeling approach to estima ...[more]

PMID: 32188920

Similar Datasets

Project description:AimInvasive alien species (IAS) threaten ecosystems and humans worldwide, and future climate change may accelerate the expansion of IAS. Predicting the suitable areas of IAS can prevent their further expansion. Ageratina adenophora is an invasive weed over 30 countries in tropical and subtropical regions. However, the potential suitable areas of A. adenophora remain unclear along with its response to climate change. This study explored and mapped the current and future potential suitable areas of Ageratina adenophora.LocationGlobal.TaxaAsteraceae A. adenophora (Spreng.) R.M.King & H.Rob. Commonly known as Crofton weed.MethodsBased on A. adenophora occurrence data and climate data, we predicted its suitable areas of this weed under current and future (four RCPs in 2050 and 2070) by MaxEnt model. We used ArcGIS 10.4 to explore the potential suitable area distribution characteristics of this weed and the "ecospat" package in R to analyze its altitudinal distribution changes.ResultsThe area under the curve (AUC) value (>0.9) and true skill statistics (TSS) value (>0.8) indicated excelled model performance. Among environment factors, mean temperature of coldest quarter contributed most to the model. Globally, the suitable areas for A. adenophora invasion decreased under climate change scenarios, although regional increases were observed, including in six biodiversity hotspot regions. The potential suitable areas of A. adenophora under climate change would expand in regions with higher elevation (3,000-3,500 m).Main conclusionsMean temperature of coldest quarter was the most important variable influencing the potential suitable area of A. Adenophora. Under the background of a warming climate, the potential suitable area of A. adenophora will shrink globally but increase in six biodiversity hotspot regions. The potential suitable area of A. adenophora would expand at higher elevation (3,000-3,500 m) under climate change. Mountain ecosystems are of special concern as they are rich in biodiversity and sensitive to climate change, and increasing human activities provide more opportunities for IAS invasion.

Project description:Simple Summary Climate change has always been a noticeable factor in the research of species distribution. In recent decades, the habitats of species have been gradually destroyed due to the changing climate. Thus, in order to predict how climate change will influence the survival and suitable habitats of wild Morchella Dill. ex Pers. species in China, we used a maximum entropy model to simulate the changes in its distribution area from historical periods to future periods. Our results illustrate that precipitation, elevation and temperature are indispensable factors affecting the presence and suitable habitats of wild Morchella species. Furthermore, this research showed us a promising trend that, regardless of which scenario, the suitable area of the species will increase to a certain scale in the near future. Based on these findings, we could explore and design an optimal scheme for the conservation of wild Morchella resources. Abstract Morchella is a kind of precious edible, medicinal fungi with a series of important effects, including anti-tumor and anti-oxidation effects. Based on the data of 18 environmental variables and the distribution sites of wild Morchella species, this study used a maximum entropy (MaxEnt) model to predict the changes in the geographic distribution of Morchella species in different historical periods (the Last Glacial Maximum (LGM), Mid Holocene (MH), current, 2050s and 2070s). The results revealed that the area under the curve (AUC) values of the receiver operating characteristic curves of different periods were all relatively high (>0.83), indicating that the results of the maximum entropy model are good. Species distribution modeling showed that the major factors influencing the geographical distribution of Morchella species were the precipitation of the driest quarter (Bio17), elevation, the mean temperature of the coldest quarter (Bio11) and the annual mean temperature (Bio1). The simulation of geographic distribution suggested that the current suitable habitat of Morchella was mainly located in Yunnan, Sichuan, Gansu, Shaanxi, Xinjiang Uygur Autonomous Region (XUAR) and other provinces in China. Compared with current times, the suitable area in Northwest and Northeast China decreased in the LGM and MH periods. As for the future periods, the suitable habitats all increased under the different scenarios compared with those in contemporary times, showing a trend of expansion to Northeast and Northwest China. These results could provide a theoretical basis for the protection, rational exploitation and utilization of wild Morchella resources under scenarios of climate change.

Project description:Climate change is expected to alter the geographic distribution of wildfire, a complex abiotic process that responds to a variety of spatial and environmental gradients. How future climate change may alter global wildfire activity, however, is still largely unknown. As a first step to quantifying potential change in global wildfire, we present a multivariate quantification of environmental drivers for the observed, current distribution of vegetation fires using statistical models of the relationship between fire activity and resources to burn, climate conditions, human influence, and lightning flash rates at a coarse spatiotemporal resolution (100 km, over one decade). We then demonstrate how these statistical models can be used to project future changes in global fire patterns, highlighting regional hotspots of change in fire probabilities under future climate conditions as simulated by a global climate model. Based on current conditions, our results illustrate how the availability of resources to burn and climate conditions conducive to combustion jointly determine why some parts of the world are fire-prone and others are fire-free. In contrast to any expectation that global warming should necessarily result in more fire, we find that regional increases in fire probabilities may be counter-balanced by decreases at other locations, due to the interplay of temperature and precipitation variables. Despite this net balance, our models predict substantial invasion and retreat of fire across large portions of the globe. These changes could have important effects on terrestrial ecosystems since alteration in fire activity may occur quite rapidly, generating ever more complex environmental challenges for species dispersing and adjusting to new climate conditions. Our findings highlight the potential for widespread impacts of climate change on wildfire, suggesting severely altered fire regimes and the need for more explicit inclusion of fire in research on global vegetation-climate change dynamics and conservation planning.

Project description:Most of the non-point source nitrogen (N) load in rural areas is attributed to onsite wastewater treatment systems (OWTS). Nitrogen compounds cause eutrophication, depleting the oxygen in marine ecosystems. OWTS rely on physical, chemical and biological soil processes to treat wastewater and these processes may be affected by climate change. We simulated the fate and transport of N in different types of OWTS drainfields, or soil treatment areas (STA) under current and changing climate scenarios, using 2D/3D HYDRUS software. Experimental data from a mesocosm-scale study, including soil moisture content, and total N, ammonium (NH4+) and nitrate (NO3-) concentrations, were used to calibrate the model. A water content-dependent function was used to compute the nitrification and denitrification rates. Three types of drainfields were simulated: (1) a pipe-and-stone (P&S), (2) advanced soil drainfields, pressurized shallow narrow drainfield (PSND) and (3) Geomat (GEO), a variation of SND. The model was calibrated with acceptable goodness-of-fit between the observed and measured values. Average root mean square error (RSME) ranged from 0.18 and 2.88 mg L-1 for NH4+ and 4.45 mg L-1 to 9.65 mg L-1 for NO3- in all drainfield types. The calibrated model was used to estimate N fluxes for both conventional and advanced STAs under current and changing climate conditions, i.e. increased soil temperature and higher water table. The model computed N losses from nitrification and denitrification differed little from measured losses in all STAs. The modeled N losses occurred mostly as NO3- in water outputs, accounting for more than 82% of N inputs in all drainfields. Losses as N2 were estimated to be 10.4% and 9.7% of total N input concentration for SND and Geo, respectively. The highest N2 losses, 17.6%, were estimated for P&S. Losses as N2 increased to 22%, 37% and 21% under changing climate conditions for Geo, PSND and P&S, respectively. These findings can provide practitioners with guidelines to estimate N removal efficiencies for traditional and advanced OWTS, and predict N loads and spatial distribution for identifying non-point sources. Our results show that N losses on OWTS can be modeled successfully using HYDRUS. Furthermore, the results suggest that climate change may increase the removal of N as N2 in the drainfield, with the magnitude of the effect depending on a drainfield type.

Dataset Information

Modeling current and future global distribution of Chrysomya bezziana under changing climate.

Publications

Modeling current and future global distribution of Chrysomya bezziana under changing climate.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure