*
 

iForest - Biogeosciences and Forestry

*

The missing part of the past, current, and future distribution model of Quercus ilex L.: the eastern edge

Osman Yalçin Yilmaz (1)   , Ünal Akkemik (2), Özgür Hüseyin Dogan (1), Hatice Yilmaz (3), Orhan Sevgi (4), Ece Sevgi (5)

iForest - Biogeosciences and Forestry, Volume 17, Issue 2, Pages 90-99 (2024)
doi: https://doi.org/10.3832/ifor4350-016
Published: Mar 22, 2024 - Copyright © 2024 SISEF

Research Articles


Ongoing climate change is anticipated to shift the geographical distribution range and impact local abundance of tree species by altering their ecological conditions. Given the lower resilience of populations at the species’ range edges, locally adapted range-edge populations are critical to the species’ survival under climate change. In this context, the distribution of holm oak (Quercus ilex L.) at the eastern border of its distribution range was assessed under current, past, and foreseeable future climate change scenarios, using species distribution models (SDMs). Current SDMs were developed using WorldClim 1.4 climate data as baseline at 30-second spatial resolution by using Generalized Boosted Regression Models (GBM) and showed moderate model performance. To compare temporal transferability and account for climate uncertainties of two versions of future climate data (CMIP5 and CMIP6), we used 4 Global Circulation Models (GCMs), 2 emission scenarios (moderate RCP45/SSP245 and pessimistic - RCP85/SSP585) for 2 different periods in the future (2040-2060 and 2060-2080). We also made predictions about the past (Mid-Holocene, about 6.000 years ago) using 4 CMIP5 GCMs. Most important variables of SDMs were distance to the sea, isothermality (BIO3), annual precipitation (BIO12), the mean temperature of driest quarter (BIO9), and the precipitation of driest month (BIO14). Our findings showed that the species’ potential distribution range probably used to be much wider in the mid-Holocene, which implies that the holm oak had a broader climatic niche during this period. The future projections indicate that its distribution area in the eastern border might increase particularly in the Black Sea region, while decreasing in the Aegean region resulting in a likely northward range shift in Turkey. However, other variables not included in our models such as land use changes might drive future shifts. Due to its high resistance to dry conditions and resilience, this species might continue to spread in southwestern Turkey in 2050s and 2070s. Finally, our study fills the gap in potential distribution predictions in context of climate change for the eastern boundary of the holm oak.

  Keywords


Species Distribution Model, Global Circulation Models, Holm Oak, Turkey, Range Edge, Generalized Boosted Regression Models, Climate Change

Authors’ address

(1)
Osman Yalçin Yilmaz 0000-0003-4711-8543
Özgür Hüseyin Dogan 0000-0002-3645-0586
Istanbul University-Cerrahpasa, Faculty of Forestry, Department of Surveying and Cadastre, Bahçeköy - Sariyer, Istanbul (Turkey)
(2)
Ünal Akkemik 0000-0003-2099-5589
Istanbul University-Cerrahpasa, Faculty of Forestry, Department of Forest Botany, Bahçeköy - Sariyer, Istanbul (Turkey)
(3)
Hatice Yilmaz 0000-0002-4614-9447
Istanbul University-Cerrahpasa, Vocational School of Forestry, Department of Landscape Design and Cultivation of Ornamental Plants, Bahçeköy - Sariyer, Istanbul (Turkey)
(4)
Orhan Sevgi 0000-0002-9706-9973
Istanbul University-Cerrahpasa, Faculty of Forestry, Department of Soil Science and Ecology, Bahçeköy - Sariyer, Istanbul (Turkey)
(5)
Ece Sevgi 0000-0002-8247-5178
Bezmialem Vakif University, Faculty of Pharmacy, Pharmaceutical Botany Department, Fatih, Istanbul (Turkey)

Corresponding author

 
Osman Yalçin Yilmaz
yilmazy@iuc.edu.tr

Citation

Yilmaz OY, Akkemik Ü, Dogan ÖH, Yilmaz H, Sevgi O, Sevgi E (2024). The missing part of the past, current, and future distribution model of Quercus ilex L.: the eastern edge. iForest 17: 90-99. - doi: 10.3832/ifor4350-016

Academic Editor

Maurizio Marchi

Paper history

Received: Mar 19, 2023
Accepted: Dec 06, 2023

First online: Mar 22, 2024
Publication Date: Apr 30, 2024
Publication Time: 3.57 months

Breakdown by View Type

(Waiting for server response...)

Article Usage

Total Article Views: 109
(from publication date up to now)

Breakdown by View Type
HTML Page Views: 0
Abstract Page Views: 0
PDF Downloads: 88
Citation/Reference Downloads: 0
XML Downloads: 21

Web Metrics
Days since publication: 69
Overall contacts: 109
Avg. contacts per week: 11.06

Article Citations

Article citations are based on data periodically collected from the Clarivate Web of Science web site
(last update: Nov 2020)

(No citations were found up to date. Please come back later)


 

Publication Metrics

by Dimensions ©

Articles citing this article

List of the papers citing this article based on CrossRef Cited-by.

 
(1)
Acácio V, Dias FS, Catry FX, Rocha M, Moreira F (2017)
Landscape dynamics in Mediterranean oak forests under global change: understanding the role of anthropogenic and environmental drivers across forest types. Global Change Biology 23: 1199-1217.
CrossRef | Gscholar
(2)
Akkemik U, Yilmaz OY, Yilmaz H, Sevgi O, Sevgi E, Akarsu F, Dogan H (2020)
Detection and evaluation of current and new distribution areas of Quercus ilex in Turkey. Eurasian Journal of Forest Science 8: 195-220. [in Turkish with English Summary]
CrossRef | Gscholar
(3)
Akkemik U, Genç S, Yilmaz OY, Selvi E, Yilmaz H, Sevgi E, Sevgi O, Akarsu F (2021)
Effects of growing site parameters on vessel elements of Quercus Ilex through Turkey and evaluating in respect of forestry. Turkish Journal of Agriculture and Forestry 45: 599-616.
CrossRef | Gscholar
(4)
Anderson RP, Raza A (2010)
The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela. Journal of Biogeography 37: 1378-1393.
CrossRef | Gscholar
(5)
Attorre F, Francesconi F, Scarnati L, De Sanctis M, Alfò M, Bruno F (2008)
Predicting the effect of climate change on tree species abundance and distribution at a regional scale. iForest 1: 132-139.
CrossRef | Gscholar
(6)
Banks-Leite C, Betts MG, Ewers RM, David C, Orme L, Pigot AL (2022)
The macroecology of landscape ecology. Trends in Ecology and Evolution 37: (6) 480-487.
CrossRef | Gscholar
(7)
Barbero M, Loisel R, Quézel P (1992)
Biogeography, ecology and history of Mediterranean Quercus ilex ecosystems. In: “Quercus ilex L. Ecosystems: Function, Dynamics and Management” (Romane F, Terradas J Eds.). Springer, Dordrecht, Netherlands, pp. 19-34.
CrossRef | Gscholar
(8)
Barbeta A, Peñuelas J (2016)
Sequence of plant responses to droughts of different timescales: lessons from holm oak (Quercus ilex) forests. Plant Ecology and Diversity 9 (4): 321-338.
CrossRef | Gscholar
(9)
Beaumont LJ, Graham E, Duursma DE, Wilson PD, Cabrelli A, Baumgartner JB, Hallgren W, Esperón-Rodríguez M, Nipperess DA, Warren DL, Laffan SW, VanDerWaal J (2016)
Which species distribution models are more (or less) likely to project broad€Âscale, climate€Â induced shifts in species ranges? Ecological Modelling 342: 135-146.
CrossRef | Gscholar
(10)
Booth TH (2018)
Species distribution modelling tools and databases to assist managing forests under climate change. Forest Ecology and Management 430: 196-203.
CrossRef | Gscholar
(11)
Cerasoli F, D’Alessandro P, Biondi M (2022)
Worldclim 2.1 versus Worldclim 1.4: climatic niche and grid resolution affect between-version mismatches in Habitat Suitability Models predictions across Europe. Ecology and Evolution 12: e8430.
CrossRef | Gscholar
(12)
Cheaib A, Badeau V, Boe J, Chuine I, Delire C, Dufrêne E, François C, Gritti ES, Legay M, Pagé C, Thuiller W, Viovy N, Leadley P (2012)
Climate change impacts on tree ranges: model intercomparison facilitates understanding and quantification of uncertainty. Ecology Letters 15: 533-544.
CrossRef | Gscholar
(13)
De Medeiros CM, Hernández-Lambraño RE, Ribeiro KAF, Agudo JAS (2018)
Living on the edge: do central and marginal populations of plants differ in habitat suitability? Plant Ecology 219: 1029-1043.
CrossRef | Gscholar
(14)
De Rigo D, Caudullo G (2016)
Quercus ilex in Europe: distribution, habitat, usage and threats. In: “European Atlas of Forest Tree Species” (San-Miguel-Ayanz J, de Rigo D, Caudullo G, Houston Durrant T, Mauri A eds). Office of the European Union, Luxembourg, pp. 152-153.
Gscholar
(15)
Delzon S, Urli M, Samalens JC, Lamy JB, Lischke H, Sin F, Zimmermann NE, Porté AJ (2013)
Field evidence of colonisation by Holm oak, at the northern margin of its distribution range, during the Anthropocene period. PLoS One 8: e80443.
CrossRef | Gscholar
(16)
Dormann CF, Elith J, Bacher S, Buchmann C, Carl G, Carré G, Marquéz JRG, Gruber B, Lafourcade B, Leitão PJ, Münkemüller T, McClean C, Osborne PE, Reineking B, SchröDer B, Skidmore AK, Zurell D, Dubrovsky M, Hayes M, Duce P, Trnka M, Svoboda M, Zara P (2014)
Multi-GCM projections of future drought and climate variability indicators for the Mediterranean region. Regional Environmental Change 14: 1907-1919.
CrossRef | Gscholar
(17)
Dyderski MK, Paz S, Frelich LE, Jagodzinski AM (2018)
How much does climate change threaten European forest tree species distributions? Global Change Biology 24: 1150-1163.
CrossRef | Gscholar
(18)
Elith J, Leathwick JR, Hastie T (2008)
A working guide to boosted regression trees. Journal of Animal Ecology 77: 802-813.
CrossRef | Gscholar
(19)
Fick SE, Hijmans RJ (2017)
WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37: 4302-4315.
CrossRef | Gscholar
(20)
Franklin J (2010)
Mapping species distributions: spatial inference and prediction, ecology, biodiversity and conservation. Cambridge University Press, Cambridge, UK, pp. 320.
CrossRef | Gscholar
(21)
Fyllas NM, Koufaki T, Sazeides CI, Spyroglou G, Theodorou K (2022)
Potential impacts of climate change on the habitat suitability of the dominant tree species in Greece. Plants 11: 1616.
CrossRef | Gscholar
(22)
Giorgi F (2006)
Climate change hot-spots. Geophysical Research Letters 33 (8): L08707.
CrossRef | Gscholar
(23)
Gómez JM (2003)
Spatial patterns in long-distance dispersal of Quercus ilex acorns by jays in a heterogeneous landscape. Ecography 26: 573-584.
CrossRef | Gscholar
(24)
Greenwell B, Boehmke B, Cunningham J, Developers G (2022)
gbm: generalized boosted regression models. R package version 2.1.8.1.
Online | Gscholar
(25)
Guisan A, Tingley R, Baumgartner JB, Naujokaitis-Lewis I, Sutcliffe PR, Tulloch AIT, Regan TJ, Brotons L, Mcdonald-Madden E, Mantyka-Pringle C, Martin TG, Rhodes JR, Maggini R, Setterfield SA, Elith J, Schwartz MW, Wintle BA, Broennimann O, Austin M, Ferrier S, Kearney MR, Possingham HP, Buckley YM (2013)
Predicting species distributions for conservation decisions. Ecology Letters 16: 1424-1435.
CrossRef | Gscholar
(26)
Guisan A, Thuiller W, Zimmermann NE (2017)
Habitat suitability and distribution models: with applications in R. Cambridge University Press, Cambridge, UK, pp. 462.
CrossRef | Gscholar
(27)
Gunal N (2011)
Geographical distribution, ecological and floristic characteristics of the holm oak (Quercus ilex) in Turkey. In: “Physical Geography Studies: Systematic and Regional” (Ekinci D ed). Turkish Geographic Institute Publication 6: 267-278. [in Turkish]
Gscholar
(28)
Hampe A, Petit RJ (2005)
Conserving biodiversity under climate change: the rear edge matters. Ecology Letters 8: 461-467.
CrossRef | Gscholar
(29)
Hao T, Elith J, Guillera-Arroita G, Lahoz-Monfort JJ (2019)
A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD. Diversity and Distribution 25: 839-852.
CrossRef | Gscholar
(30)
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005)
Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.
CrossRef | Gscholar
(31)
Hijmans R (2023)
terra: spatial data analysis. R package version 1.7-18.
Online | Gscholar
(32)
Iverson LR, McKenzie D (2013)
Tree-species range shifts in a changing climate: detecting, modeling, assisting. Landscape Ecology 28: 879-889.
CrossRef | Gscholar
(33)
Jiménez-Valverde A, Lobo JM, Hortal J (2008)
Not as good as they seem: the importance of concepts in species distribution modelling. Diversity and Distribution 14: 885-890.
CrossRef | Gscholar
(34)
Keenan RJ (2015)
Climate change impacts and adaptation in forest management: a review. Annals of Forest Science 72: 145-167.
CrossRef | Gscholar
(35)
López-Tirado J, Hidalgo PJ (2016)
Predictive modelling of climax oak trees in southern Spain: insights in a scenario of global change. Plant Ecology 217: 451-463.
CrossRef | Gscholar
(36)
López-Tirado J, Hidalgo PJ (2018)
Predicting suitability of forest dynamics to future climatic conditions: the likely dominance of Holm oak (Quercus ilex subsp. ballota (Desf.) Samp.) and Aleppo pine (Pinus halepensis Mill.). Annals of Forest Science 75: 1-11.
CrossRef | Gscholar
(37)
López-Tirado J, Vessella F, Schirone B, Hidalgo PJ (2018)
Trends in evergreen oak suitability from assembled species distribution models: assessing climate change in south-western Europe. New Forests 49: 471-487.
CrossRef | Gscholar
(38)
Mauri A, Girardello M, Strona G, Beck PSA, Forzieri G, Caudullo G, Manca F, Cescatti A (2022)
EU-Trees4F, a dataset on the future distribution of European tree species. Scientific Data 9: 37.
CrossRef | Gscholar
(39)
Naimi B, Hamm NAS, Groen TA, Skidmore AK, Toxopeus AG (2014)
Where is positional uncertainty a problem for species distribution modelling? Ecography 37 (2): 191-203.
CrossRef | Gscholar
(40)
Newbold T, Oppenheimer P, Etard A, Williams JJ (2020)
Tropical and Mediterranean biodiversity is disproportionately sensitive to land-use and climate change. Nature Ecology and Evolution 4: 1630-1638.
CrossRef | Gscholar
(41)
Norberg A, Abrego N, Blanchet FG, Adler FR, Anderson BJ, Anttila J, Araújo MB, Dallas T, Dunson D, Elith J, Foster SD, Fox R, Franklin J, Godsoe W, Guisan A, Hara B, Hill NA, Holt RD, Hui FKC, Husby M, Kalas JA, Lehikoinen A, Luoto M, Mod HK, Newell G, Renner I, Roslin T, Soininen J, Thuiller W, Vanhatalo J, Warton D, White M, Zimmermann NE, Gravel D, Ovaskainen O (2019)
A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels. Ecological Monographs 89: e01370.
CrossRef | Gscholar
(42)
Parmesan C, Hanley ME (2015)
Plants and climate change: complexities and surprises. Annals of Botany 116 (6): 849-864.
CrossRef | Gscholar
(43)
Pebesma E, Bivand R (2023)
Spatial data science: with applications in R (1st edn). Chapman & Hall/CRC, Boca Raton, FL, USA, pp. 314.
CrossRef | Gscholar
(44)
Petroselli A, Vessella F, Cavagnuolo L, Piovesan G, Schirone B (2013)
Ecological behavior of Quercus suber and Quercus ilex inferred by topographic wetness index (TWI). Trees - Structure and Function 27: 1201-1215.
CrossRef | Gscholar
(45)
Picard N, Marchi M, Serra-Varela MJ, Westergren M, Cavers S, Notivol E, Piotti A, Alizoti P, Bozzano M, González-Martínez SC, Grivet D, Aravanopoulos FA, Vendramin GG, Ducci F, Fady B, Alía R (2022)
Marginality indices for biodiversity conservation in forest trees. Ecological Indicators 143: 109367.
CrossRef | Gscholar
(46)
Phillips SJ, Elith J (2013)
On estimating probability of presence from use availability or presence background data. Ecology 94: 1409-1419.
CrossRef | Gscholar
(47)
Príncipe A, Nunes A, Pinho P, Aleixo C, Neves N, Branquinho C (2022)
Local-scale factors matter for tree cover modelling in Mediterranean drylands. Science of The Total Environment 831 (2): 154877.
CrossRef | Gscholar
(48)
QGIS.org (2022)
QGIS geographic information system. QGIS Association, web site.
Online | Gscholar
(49)
R Core Team (2020)
R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Online | Gscholar
(50)
Rehm EM, Olivas P, Stroud J, Feeley KJ (2015)
Losing your edge: climate change and the conservation value of range-edge populations. Ecology and Evolution 5 (19): 4315-26.
CrossRef | Gscholar
(51)
Roberts N, Brayshaw D, Kuzucuoglu C, Perez R, Sadori L (2011)
The mid-Holocene climatic transition in the Mediterranean: causes and consequences. The Holocene 21: 3-13.
CrossRef | Gscholar
(52)
Ruiz-Labourdette D, Nogués-Bravo D, Ollero HS, Schmitz MF, Pineda FD (2012)
Forest composition in Mediterranean mountains is projected to shift along the entire elevational gradient under climate change. Journal of Biogeography 39: 162-176.
CrossRef | Gscholar
(53)
Sadori L, Bertini A, Combourieu-Nebout N, Kouli K, Lippi M, Roberts N, Mercuri AM (2013)
Palynology and Mediterranean vegetation history. Flora Mediterranea 23: 141-156.
CrossRef | Gscholar
(54)
Schirone B, Vessella F, Varela MC (2019)
EUFORGEN technical guidelines for genetic conservation and use for Holm oak (Quercus ilex). European Forest Genetic Resources Programme -EUFORGEN, European Forest Institute, Barcelona, Spain, pp. 6.
Gscholar
(55)
Smith AB, Santos MJ (2020)
Testing the ability of species distribution models to infer variable importance. Ecography 43: 1801-1813.
CrossRef | Gscholar
(56)
Tabet S, Belhemra M, Francois L, Arar A (2018)
Evaluation by prediction of the natural range shrinkage of Quercus ilex L. in eastern Algeria. Forestist 68: 7-15.
CrossRef | Gscholar
(57)
Thuiller W, Georges D, Gueguen M, Engler R, Breiner F, Lafourcade B, Patin R (2023)
biomod2: ensemble platform for species distribution modeling. R package version 4.2-2.
Online | Gscholar
(58)
Villar-Salvador P, Castro-Díez P, Pérez-Rontomé C, Montserrat-Martí G (1997)
Stem xylem features in three Quercus (Fagaceae) species along a climatic gradient in NE Spain. Trees 12 (2): 90-96.
CrossRef | Gscholar
(59)
Wickham H (2016)
ggplot2: elegant graphics for data analysis (2nd edn). Springer-Verlag, New York, USA, pp. 260.
Gscholar
 

This website uses cookies to ensure you get the best experience on our website. More info