Analysis of potentially suitable habitat within migration connections of an intra-African migrant-the Blue Swallow (Hirundo atrocaerulea)

Mudereri, Bester Tawona; Mukanga, Concilia; Mupfiga, Elvis Tawanda; Gwatirisa, Calisto; Kimathi, Emily; Chitata, Tavengwa

doi:10.1016/j.ecoinf.2020.101082

Cited by 16 publications

(9 citation statements)

References 42 publications

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“…A previous study showed that using biased background data have increased the performance of the model and should be applicable for cases with small numbers of occurrence points ( Kramer-Schadt et al, 2013 ). A bias file was created as a two-dimensional kernel density estimate, based on the coordinates of the occurrence points, using the kde2d function from the MASS package ( Ripley et al, 2020 ) in R. This approach was applied in previous works (e.g., Filazzola, Sotomayor & Lortie, 2018 ; Mudereri et al, 2020 ). Bias files were converted to the raster ASCII format and have been implemented into the biasfile option in Maxent.…”

Section: Methodsmentioning

confidence: 99%

Climatic niche comparison between closely related trans-Palearctic species of the genusOrthocephalus(Insecta: Heteroptera: Miridae: Orthotylinae)

Namyatova

2020

PeerJ

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Previously climatic niche modelling had been studied for only a few trans-Palearctic species. It is unclear whether and to what extent those niches are different, and which climatic variables influence such a wide distribution. Here, environmental niche modelling is performed based on the Worldclim variables using Maxent for eight species of the genus Orthocephalus (Insecta: Heteroptera: Miridae: Orthotylinae). This group belongs to one of the largest insect families and it is distributed across Palearctic. Orthocephalus bivittatus, O. brevis, O. saltator and O. vittipennis are distributed across Europe and Asia; O. coriaceus, O. fulvipes, O. funestus, O. proserpinae have more limited distribution. Niche comparison using ENMTools was also undertaken to compare the niches of these species, and to test whether the niches of closely related species with trans-Palearctic distributions are more similar to each other, than to other congeners. It has been found that climatic niche models of all trans-Palearctic species under study are similar but are not identical to each other. This has been supported by niche geographic projections, climatic variables contributing to the models and variable ranges. Climatic niche models of all the trans-Palearctic Orthocephalus species are also very similar to two species having more restricted distribution (O. coriaceus, O. funestus). Results of this study suggest that trans-Palearctic distributions can have different geographic ranges and be shaped by different climatic factors.

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Section: Methodsmentioning

confidence: 99%

Climatic niche comparison between closely related trans-Palearctic species of the genusOrthocephalus(Insecta: Heteroptera: Miridae: Orthotylinae)

Namyatova

2020

PeerJ

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“…The MaxEnt is a machine learning method that estimates the suitability of an area by calculating the probability distribution of maximum entropy. It has been extensively used in a wide range of ecological applications (e.g., [34,114,115]) because it is one of the bestperforming algorithms in species distribution modelling [116][117][118]. In particular, it has been proven useful for predicting the habitat suitability of tree species under current and future climate conditions (for example, [37,119]).…”

Section: Species Distribution Modellingmentioning

confidence: 99%

“…We, therefore, increased the presence points of the study species in Greece, with our own observations and data from forest stewardship plans, from a few tens to a few thousand. Subsequently, we used Maxent, a widely used, highly performant SDM algorithm [33,34], to simulate the current habitat suitability of the study species in Greece, using a suite of climate and edaphic variables. We then combined the SDM models with projections from general circulation models for two contrasting climate change scenarios and time periods (2041-2070 and 2071-2100) to predict the range of change in (i) the surface of suitable habitat for each species, and (ii) the elevational shift in habitat suitability.…”

Section: Introductionmentioning

confidence: 99%

Potential Impacts of Climate Change on the Habitat Suitability of the Dominant Tree Species in Greece

Fyllas

Koufaki

Sazeides

et al. 2022

Plants

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Climate change is affecting species distribution and ecosystem form and function. Forests provide a range of ecosystem services, and understanding their vulnerability to climate change is important for designing effective adaptation strategies. Species Distribution Modelling (SDM) has been extensively used to derive habitat suitability maps under current conditions and project species distribution shifts under climate change. In this study, we model the current and future habitat suitability of the dominant tree species in Greece (Abies cephalonica, Abies borisii-regis, Pinus brutia, Pinus halepensis, Pinus nigra, Quercus ilex, Quercus pubescens, Quercus frainetto and Fagus sylvatica), based on species-specific presence data from the EU-Forest database, enhanced with data from Greece that is currently under-represented in terms of tree species occurrence points. By including these additional presence data, areas with relatively drier conditions for some of the study species were included in the SDM development, yielding a potentially lower vulnerability under climate change conditions. SDMs were developed for each taxon using climate and soil data at a resolution of ~1 km2. Model performance was assessed under current conditions and was found to adequately simulate potential distributions. Subsequently, the models were used to project the potential distribution of each species under the SSP1-2.6 and SSP5-8.5 scenarios for the 2041–2070 and 2071–2100 time periods. Under climate change scenarios, a reduction in habitat-suitable areas was predicted for most study species, with higher elevation taxa experiencing more pronounced potential habitat shrinkages. An exception was the endemic A. cephalonica and its sister species A. borisii-regis, which, although currently found at mid and high elevations, seem able to maintain their potential distribution under most climate change scenarios. Our findings suggest that climate change could significantly affect the distribution and dynamics of forest ecosystems in Greece, with important ecological, economic and social implications, and thus adequate mitigation measures should be implemented.

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“…Several studies showed that there is no convincing evidence to suggest that there is an overall model that is better than all (Guo et al 2019;Hao et al 2019;Mudereri et al 2020b). Therefore, the use of the ensemble analysis becomes paramount in all predictive modeling, especially for producing a realistic and encompassing prediction (Araújo et al).…”

Section: Evaluation Of the Model Performancesmentioning

confidence: 99%

Modeling the geographic spread and proliferation of invasive alien plants (IAPs) into new ecosystems using multi-source data and multiple predictive models in the Heuningnes catchment, South Africa

Mtengwana

Dube

Mudereri

et al. 2021

GIScience & Remote Sensing

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The geographic spread and proliferation of Invasive Alien Plants (IAPs) into new ecosystems requires accurate, constant, and frequent monitoring particularly under the changing climate to ensure the integrity and resilience of affected as well as vulnerable ecosystems. This study thus aimed to understand the distribution and shifts of IAPs and the factors influencing such distribution at the catchment scale to minimize their risks and impacts through effective management. Three machine learning Species Distribution Modeling (SDM) techniques, namely, Random Forest (RF), Maximum Entropy (MaxEnt), Boosted Regression Trees (BRT) and their respective ensemble model were used to predict the potential distribution of IAPs within the catchment. The current and future bioclimatic variables, environmental and Sentinel-2 Multispectral Instrument satellite data were used to fit the models to predict areas at risk of IAPs invasions in the Heuningnes catchment, South Africa. The present and two future climatic scenarios from the Community Climate System Model (CCSM4) were considered in modeling the potential distribution of these species. The two future scenarios represented the minimum and maximum atmospheric carbon Representative Concentration Pathways (RCP) 2.6 and 8.5 for 2050 (average for 2041-2060). The results show that IAPs are predicted to expand under the influence of climate change in the catchment. Concurrently, riparian zones, bare areas, and the native vegetation which is rich in biodiversity will greatly be affected. The mean diurnal range (Bio2), warmest quarter maximum temperature (Bio5), and the warmest quarter precipitation (Bio18) were the most important bioclimatic variables in modeling the spatial distribution of IAPs in the catchment. Comparatively, all the models were successful in predicting the potential distribution of IAPs for all the scenarios. The BRT, MaxEnt, and RF predicted the spatial distribution of IAPs with an Area Under Curve (AUC) of 0.89, 0.92, and 0.94, respectively. The study highlighted the importance of multi-source data and multiple predictive models in predicting the current and potential future IAP distribution. The results from this study provide baseline information for effective land management, planning, and continuous monitoring of the further spread of IAPs within the Heuningnes catchment.

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Analysis of potentially suitable habitat within migration connections of an intra-African migrant-the Blue Swallow (Hirundo atrocaerulea)

Cited by 16 publications

References 42 publications

Climatic niche comparison between closely related trans-Palearctic species of the genusOrthocephalus(Insecta: Heteroptera: Miridae: Orthotylinae)

Climatic niche comparison between closely related trans-Palearctic species of the genusOrthocephalus(Insecta: Heteroptera: Miridae: Orthotylinae)

Potential Impacts of Climate Change on the Habitat Suitability of the Dominant Tree Species in Greece

Modeling the geographic spread and proliferation of invasive alien plants (IAPs) into new ecosystems using multi-source data and multiple predictive models in the Heuningnes catchment, South Africa

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