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Predictive mapping of two endemic oak tree species under climate change scenarios in a semiarid region: Range overlap and implications for conservation

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Abstract

Quercus infectoria and Quercus libani are two important species distributed across most of the Kurdistan Region of Iraq's mountain ranges (KRI). They have significant ecological, medicinal, and socioeconomic values. Recent studies have documented how plant distributions have been impacted by climate change. This study's goal is to establish the existing distributions of both species, measure the consequences of prospective environmental conditions on their distributions, predict possible habitat distributions, map the overlapped habitat ranges for the species in the KRI, and identify the key factors influencing their distributions. For these aims, distribution data points of the species, different environmental factors, including the existing climate, three emission predictions for the 2050s, 2070s, and 2090s of two general circulation models (GCMs), a machine learning approach, and geospatial techniques were used. Modeling revealed that the total magnitude of the habitat increase for the species would be less than the overall magnitude of the habitat contraction. The yearly mean temperature, yearly precipitation, and minimum temperature during the coldest period mostly alter the target species' geographic dispersion. Across the three emission scenarios of the both models, Q. infectoria habitat would contract by 2760.9–2856.9 km² (5.36–5.55%), 2856.9–3357.2 km² (5.55–6.52%) and 2822.1–3400.2 km² (5.48–6.60%), whereas it would expand by 1153.3–1638.9 km² (2.24–3.18%), 761.0–1556.8 km² (1.48–3.02%), and 721.5–1547.1 km² (1.40–3.00%) for the 2050s, 2070s, and 2090s, respectively. A similar pattern was also noted for Q. libani. The two species' habitat ranges in KRI would be considerably reduced due to climate change. The species' estimated area would extend mostly to the east and southeast of the KRI at high altitudes. The mountain areas, notably those where the species overlap by 1767.2–1807.5 km² (3.43–3.51%) for the two GCMs, must be the primary objective of conservation efforts. This research presents new baseline data for future research on mountain forest ecosystems and the techniques of biodiversity conservation to reduce climate change's effects in Iraq.

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Understanding land use land cover change (LULCC) dynamics is crucial for sustaining the integrity of structure and function of ecosystems. As such, frequent measuring and monitoring of LULCC are necessary. Over the last four decades, Duhok governorate in the north of Iraq has undergone sweeping changes caused mainly by anthropogenic factors (e.g. population growth). This study used geospatial techniques and the synergy Cellular Automata (CA)–Markov approach to quantify past, current and model the future changes of LULC. The maximum likelihood classifier (MLC) was employed to conduct classification for three consecutive-year Landsat imagery (i.e. 1988, 2008 and 2017). From the classified imageries, three LULC maps with several classes were created and then, change detection analysis was implied. The classified (1988–2008) and (2008–2017) LULC maps were incorporated into the hybrid model to predict LULC maps for 2017 and 2060, respectively. The classified 2017 LULC maps were used as a reference to validate the model output for 2017.Relatively high accuracy agreements were achieved between the classified and the modelled maps (Kno= 0.8315, Klocation= 0.8267, Kstandard = 0.7978). The model classes estimated for 2060 compared to the classified 2017 LULC classes revealed that dense forest, sparse forest, agricultural land and barren area would decrease by −26.26% (from 327.08 to 241.08 km2), −0.76% (from 2372.29 to 2355.82 km2), −5.86% (from 973.21 to 916.27 km2) and −10.03% (from 2918.9–2626.19 km2), respectively. In contrast, the urban area would significantly increase by 271.19%, (from 161.99 to 602.19.8 km2).Dense forest in Duhok governorate has seen remarkable decline from 1988 to 2017, and future predictions demonstrated that the declining trend would continue. Dense forest would predominantly convert to sparse forest and barren areas, suggesting forest thinning and clearing. Urban areas were the most dynamic cover types that increased significantly between 1998 and 2017. This trend would continue to increase from 2.36% (2017) to 8.76% (2060). Urbanization would be predominantly at the cost of agricultural land and barren area. Information on spatiotemporal dynamics of LULCC has been proved as an effective measure for maintaining the integrity of the ecosystem components through sustainable planning and management actions.
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p>Among the amphibians, the most sensitive group to climate change are salamanders (e.g., Salamandra infraimmaculata and Neurergus derjugini). In Iraq, these species are considered threatened by the International Union for Conservation of Nature (IUCN) RED List (2020). Apart from their important role in forest ecosystems stability and integrity, they are useful indicators for ecosystems functions. These species occur only in the mountain forests of the northeast, the Kurdistan region of Iraq (KRI), and information on their distributions is limited and poorly understood. Using the maximum entropy modeling and geospatial techniques, we aimed to: (i) map current distributions of the two species, and predict potential habitat distributions; (ii) model impact of the future climate change on their distributions; (iii) map overlapping habitat range for the species; and (iv) determine the main environmental variables shaping their distributions. Under the Representative Concentration Pathway (RCP) 2.62070 and RCP8.5 2070 climate change scenarios, the overall expansion magnitude of the habitat for the species would be smaller than the contraction magnitude. For S. infraimmaculata and N. derjugini, the habitat would contract by 1751.58 km<sup>2</sup> (3.42%) and 2127.22 km<sup>2</sup> (4.16%), whereas expand only 226.77 km<sup>2</sup> (0.44%) and 1877.49 km<sup>2</sup> (3.67%), respectively. Climate change would significantly reduce the habitat ranges of the two species in Iraq. Habitat reduction for S. infraimmaculata would be more than N. derjugini. The potential distribution of the species would be toward the mountain forests of the east mainly and southeast of the KRI. Conservation actions should concentrate on the mountain forests (mixed oak) by establishing national parks, protected areas, and developing forest management policy. Current emphasis for conservation priority should focus specifically on areas where the species overlap by 1583.71 km<sup>2</sup> (3.09%). Our study provides baseline information for further investigation of the mountain forest ecosystems, and biodiversity conservation actions in Iraq.</p
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Among the amphibians, the most sensitive group to climate change are salamanders (e.g., Salamandra infraimmaculata and Neurergus derjugini). In Iraq, these species are considered threatened by the International Union for Conservation of Nature (IUCN) RED List (2020). Apart from their important role in forest ecosystems stability and integrity, they are useful indicators for ecosystems functions. These species occur only in the mountain forests of the northeast, the Kurdistan region of Iraq (KRI), and information on their distributions is limited and poorly understood. Using the maximum entropy modeling and geospatial techniques, we aimed to: (i) map current distributions of the two species, and predict potential habitat distributions; (ii) model impact of the future climate change on their distributions; (iii) map overlapping habitat range for the species; and (iv) determine the main environmental variables shaping their distributions. Under the Representative Concentration Pathway (RCP) 2.62070 and RCP8.5 2070 climate change scenarios, the overall expansion magnitude of the habitat for the species would be smaller than the contraction magnitude. For S. infraimmaculata and N. derjugini, the habitat would contract by 1751.58 km2 (3.42%) and 2127.22 km2 (4.16%), whereas expand only 226.77 km2 (0.44%) and 1877.49 km2 (3.67%), respectively. Climate change would significantly reduce the habitat ranges of the two species in Iraq. Habitat reduction for S. infraimmaculata would be more than N. derjugini. The potential distribution of the species would be toward the mountain forests of the east mainly and southeast of the KRI. Conservation actions should concentrate on the mountain forests (mixed oak) by establishing national parks, protected areas, and developing forest management policy. Current emphasis for conservation priority should focus specifically on areas where the species overlap by 1583.71 km2 (3.09%). Our study provides baseline information for further investigation of the mountain forest ecosystems, and biodiversity conservation actions in Iraq.
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As a well-known Chinese important medicine, Dendrobium resources are increasingly scarce. In order to avoid the quality problems caused by blind cultivation, we predicted the ecologically suitable areas for three species of important Dendrobium species. In this paper, using the maximum entropy model and ArcGIS, we used a database and literature search to collect the known distribution information of Dendrobium, combined with the relevant ecological factors such as climate, elevation and soil, to divide the geographical distribution of Dendrobium into categories, and find out the main ecological factors that affect the distribution of Dendrobium and thus the most suitable regions in China. The results showed that Dendrobium is mainly distributed south of the Yangtze River And the distribution of the most suitable regions was different for each of these three species of Dendrobium species. The potential suitable areas of Dendrobium nobile Lindl, Dendrobium officinale Kimura et Migo, Dendrobium moniliforme (L.) Sw. were approximately 134.19 × 10⁴ km² (accounting for 13.98 %), 229.08 × 10⁴ km² (accounting for 23.86 %) and 188.33 × 10⁴ km² (accounting for 19.62 %) of China’s land area, respectively. Based on our model, annual temperature annual range and annual precipitation are the main ecological variables controlling the distribution of the three species of Dendrobium species, but these three species also have slightly different characteristics. All in all, these species prefer a warm, stable and humid climate and loose soil that is sufficiently aerated and with appropriate moisture properties in order to grow. This will provide a reference for the subsequent introduction, cultivation and local adaptation.
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Understanding the relationship between the geographical distribution of taxa and their environmental conditions is a key concept in ecology and conservation. The use of ensemble modelling methods for species distribution modelling (SDM) have been promoted over single algorithms such as Maximum Entropy (MaxEnt). Nevertheless, we suggest that in cases where data, technical support or computational power are limited, for example in developing countries, single algorithm methods produce robust and accurate distribution maps. We fit SDMs for 114 Egyptian medicinal plant species (nearly all native) with a total of 14,396 occurrence points. The predictive performances of eight single-algorithm methods (maxent, random forest (rf), support-vector machine (svm), maxlike, boosted regression trees (brt), classification and regression trees (cart), flexible dis-criminant analysis (fda) and generalised linear models (glm)) were compared to an ensemble modelling approach combining all eight algorithms. Predictions were based originally on the current climate, and then projected into the future time slice of 2050 based on four alternate climate change scenarios (A2a and B2a for CMIP3 and RCP 2.6 and RCP 8.5 for CMIP5). Ensemble modelling, MaxEnt and rf achieved the highest predictive performances based on AUC and TSS, while svm and cart had the poorest performance. There is high similarity in habitat suitability between MaxEnt and ensemble predictive maps for both current and future emission scenarios, but lower similarity between rf and ensemble, or rf and MaxEnt. We conclude that single-algorithm modelling methods, particularly MaxEnt, are capable of producing distribution maps of comparable accuracy to ensemble methods. Furthermore, the ease of use, reduced computational time and simplicity of methods like MaxEnt provides support for their use in scenarios when the choice of modelling methods, knowledge or computational power is limited but the need for robust and accurate conservation predictions is urgent.
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Vitellaria paradoxa, the shea tree, an economically important fruit-tree species native to savanna regions is threatened in Burkina Faso due to overexploitation and changing land-use. Furthermore, it remains unclear how climate change will influence its frequency and distribution. We investigated the impact of climate change on the projected spatial distribution of favorable habitats for V. paradoxa. Species distribution modeling techniques implemented in MaxEnt combined with GIS were used to forecast the current and future distribution of V. paradoxa. We selected two climatic scenarios (RCP4.5 and RCP8.5) and two global climate models (MPI-ESM-MR and HadGEM2-ES) to encompass the full range of variation in the models. Presence records of the species were collected and linked to bioclimatic and edaphic variables. The most characteristic and least correlated variables were selected for modeling after a collinearity test. Under current climatic conditions, ~51% of the national area was found to be favorable for cultivation and conservation of the species. Under future climate projections, our models predict that favorable habitats of this species will decline by 12% (RCP4.5) and 13% (RCP8.5) by 2070. The predictive modeling approach presented here may be applied to other economically important tree species.
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Although climate change influences the distribution of invasive plant species, there is limited knowledge regarding its potential effects on Lantana camara distributions, especially in southern African savanna ecosystems. In this study, we predict the potential effects of climate change on the future distribution of Lantana camara as well as determine the ecosystems at risk from Lantana camara invasion in Matabeleland South Province of Zimbabwe. To do this, ensemble modelling consisting of three Species Distribution Models (SDMs) was coupled with three Global Circulation Models (GCMs) and two climate scenarios (Representative Concentration Pathways) for the 2070s. Results show that, on average, the bioclimatically suitable habitat of Lantana camara is projected to increase in the province by between ~3 and 33% and 32 and 82% under RCP 2.6 and RCP8.5, respectively. On average, the habitat suitability of Lantana camara is projected to increase by 5892 km 2 , which is about 65% of the total area of southern Zimbabwe. The northern parts of the province are more likely to be invaded by the focal species than any other part of the province. Overall, the results of the study underscore the importance of species distribution modelling under a changing climate.
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Climate change has a great impact on the species distribution range and many endangered plant species. Fritillaria imperialis as a species that is native to Central Zagros, Iran is a medicinal plant with great ecological and commercial profits. Its population has decreased considerably and the species would be endangered in later decades. Understanding the habitat needs of this species, evaluating habitat conditions, and forecasting its potential habitat are important for protecting F. imperialis. The presence of F. imperialis points recorded from our field surveys in Chaharmahal-va-Bakhtiari province as a part of Central Zagros, Iran in spring 2017. In order to model its distribution based on correlation analysis, two topographic variables and eight bioclimatic ones as the input of Maximum Entropy model (MaxEnt) were used. The results showed that temperature seasonality (55.1%) and precipitation of driest quarter (22.9%) were important factor drivers of F. imperialis suitable habitat. The accuracy of the maximum entropy model in predicting the distribution of the studied species was high (AUC=0.91) as 2.33% (37986 ha) in Chaharmahal-va-Bakhtiari Province for the F. imperialis, which has had suitability. About 18% and 16.5% of F. imperialis habitats in the area may be lost due to climate change by 2070 under two climate warming scenarios (RCP4.5 and RCP8.5, given by the IPCC). As shown by the model, under the current climatic conditions, the suitable habitat would be rendered to an unsuitable one in the future resulting in local extinction. The results of this study can be used to identify sites with high extinction probability of F. imperialis and protect susceptible habitats against the effects of climate change.
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In recent years, many cryptic species of bats have been discovered thanks to the application of molecular techniques. The several long-eared bat species (genus Plecotus) occurring in Europe show a marked morphological similarity and occur in sympatry, so that when confusion may arise, molecular approaches have prime importance to establish the actual specific identity. Italy represents a diversity hotspot for bats in Europe, hosting 35 species among which four Plecotus species. In this study we report on the first confirmed record of the Balkan’s long-eared bat Plecotus kolombatovici for peninsular Italy, review previous unconfirmed records and analyse the species’ potential distribution in the country using a modelling approach. The species’ potential distribution is strongly associated with warm summer temperatures and relatively high winter precipitations, typical of Mediterranean climate. The modelling exercise we did highlights that P. kolombatovici may occur in much of the Italian territory, including the Tyrrhenian coast and on many islands that border it. We therefore argue that P. kolombatovici presence has been so far overlooked due to the morphological resemblance of this species with the grey long-eared bat P. austriacus. Comprehensive surveys are needed to ascertain the actual distribution and establish the conservation status in Italy of this poorly known species to adopt effective legal and practical conservation measures.
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Although numerous species distribution models have been developed, most were based on insufficient distribution data or used older climate change scenarios. We aimed to quantify changes in projected ranges and threat level by the years 2061-2080, for 12 European forest tree species under three climate change scenarios. We combined tree distribution data from the Global Biodiversity Information Facility, EUFORGEN and forest inventories, and we developed species distribution models using MaxEnt and 19 bioclimatic variables. Models were developed for three climate change scenarios – optimistic (RCP2.6), moderate (RCP4.5) and pessimistic (RPC8.5) – using three General Circulation Models, for the period 2061-2080. Our study revealed different responses of tree species to projected climate change. The species may be divided into three groups: “winners” – mostly late-successional species: Abies alba, Fagus sylvatica, Fraxinus excelsior, Quercus robur and Q. petraea; “losers” – mostly pioneer species: Betula pendula, Larix decidua, Picea abies and Pinus sylvestris and alien species – Pseudotsuga menziesii, Q. rubra and Robinia pseudoacacia, which may be also considered as “winners”. Assuming limited migration, most of the species studied would face significant decrease of suitable habitat area. The threat level was highest for species that currently have the northernmost distribution centers. Ecological consequences of the projected range contractions would be serious for both forest management and nature conservation. This article is protected by copyright. All rights reserved.