Climate change may threaten the southernmost Pinus nigra subsp. salzmannii (Dunal) Franco populations: an ensemble niche-based approach

doi:10.3832/ifor2588-011

Climate change may threaten the southernmost Pinus nigra subsp. salzmannii (Dunal) Franco populations: an ensemble niche-based approach

Rafael M Navarro-Cerrillo⁽¹⁾ , Joaquín Duque-Lazo⁽¹⁾, Rubén D Manzanedo⁽²⁾, Raúl Sánchez-Salguero⁽³⁾, Guillermo Palacios-Rodriguez⁽¹⁾

iForest - Biogeosciences and Forestry, Volume 11, Issue 3, Pages 396-405 (2018)
doi: https://doi.org/10.3832/ifor2588-011
Published: May 15, 2018 - Copyright © 2018 SISEF

Research Articles

PDF Version

Full Text

Citation

We used Species Distribution Modeling to predict the probability of Iberian pine (Pinus nigra subsp. salzmannii [Dunal] Franco) occurrences in southern Spain in response to environmental variables and to forecast the effects of climate change on their predicted geographical distribution. The ensemble modeling approach “biomod2” was used, together with present Iberian pine data, to predict the current potential distribution based on bioclimatic explanatory variables (200 m resolution) and to forecast future suitability by studying three periods (2040, 2070, and 2100), considering the Global Circulation Models BCM2, CNCM3, and ECHAM5, and the regional model EGMAM, for different scenarios (SRAB1, SRA2, SRB1). Model evaluation was performed using Kappa, True Skills Statistic (TSS), and Area Under the Curve (AUC) values. The biomod2 approach highlighted the average number of days with a minimum temperature equal to or below 0°C, annual precipitation, and aridity index as the most important variables to describe the P. nigra occurrence probability. Model performances were generally satisfactory and the highest AUC values and high stability of the results were given by GAM and GLM, but MaxEnt and the SRE model were scarcely accurate according to all our statistics. The ensemble Species Distribution Modeling of P. nigra in Andalusia predicted the highest probability of species occurrence in the eastern areas, Sierra de Cazorla being the area with the highest occurrence of P. nigra in Andalusia. In the future habitat, the general probability of P. nigra occurrence in Andalusia will decrease widely; the species is expected to lose habitat suitability at moderate altitudes and its occurrence probability will have decreased by nearly 70% on average by 2100, affected by the selected scenario. Populations in Sierra de Cazorla are those most suitable for P. nigra growth, even under the most pessimistic scenarios. It is likely that the natural southern populations of P. nigra will be very sensitive to changes in climate.

Keywords

Species Distribution Modeling, Climate Change, Ensemble Modeling, Iberian Pine, Mediterranean Relict Forests

Authors’ address

(1)

Department of Forestry, School of Agriculture and Forestry, University of Córdoba, Edf. Leonardo da Vinci, Campus de Rabanales s/n, Mail Box 3048, E-14071 Córdoba (Spain)

(2)

Institute of Plant Sciences, University of Bern, Altenbergrain 21, CH-3013 Bern (Switzerland)

(3)

Area de Ecología, Dpto. Sistemas Físicos, Químicos y Naturales, Universidad Pablo de Olavide, Ctra. Utrera km. 1, E-41013 Sevilla (Spain)

Corresponding author

Rafael M Navarro-Cerrillo
rmnavarro@uco.es

Citation

Navarro-Cerrillo RM, Duque-Lazo J, Manzanedo RD, Sánchez-Salguero R, Palacios-Rodriguez G (2018). Climate change may threaten the southernmost Pinus nigra subsp. salzmannii (Dunal) Franco populations: an ensemble niche-based approach. iForest 11: 396-405. - doi: 10.3832/ifor2588-011

Academic Editor

Francesco Ripullone

Paper history

Received: Aug 07, 2017
Accepted: Mar 10, 2018

First online: May 15, 2018
Publication Date: Jun 30, 2018
Publication Time: 2.20 months

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Breakdown by View Type

(Waiting for server response...)

Article Usage

Total Article Views: 44729
(from publication date up to now)

Breakdown by View Type
HTML Page Views: 37816
Abstract Page Views: 2942
PDF Downloads: 3116
Citation/Reference Downloads: 14
XML Downloads: 841

Web Metrics
Days since publication: 2382
Overall contacts: 44729
Avg. contacts per week: 131.45

Article Citations

Article citations are based on data periodically collected from the Clarivate Web of Science web site
(last update: Feb 2023)

Total number of cites (since 2018): 8
Average cites per year: 1.33

(no Plumx Metrics available for this paper)

Publication Metrics

by Dimensions ^©

Articles citing this article

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

(1)

Allouche O, Tsoar A, Kadmon R (2006)
Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology 43: 1223-1232.
CrossRef | Gscholar

(2)

Araújo MB, New M (2007)
Ensemble forecasting of species distributions. Trends in Ecology and Evolution 22: 42-47.
CrossRef | Gscholar

(3)

Attorre F, Alfò M, De Sanctis M, Francesconi F, Valenti R, Vitale M, Bruno F (2011)
Evaluating the effects of climate change on tree species abundance and distribution in the Italian peninsula. Applied Vegetation Science 14 (2): 242-255.
CrossRef | Gscholar

(4)

Badeau V, Dupouey JL, Cluzeau C, Drapier JS, Le Bas C (2010)
Climate change and the biogeography of French tree species: first results and perspectives. In: “Forests, Carbon Cycle and Climate Change” (Loustau D ed). Edition Quae, Collection Update Sciences and Technology, Paris, France, pp. 231-252.
Online | Gscholar

(5)

Barbet-Massin M, Jiguet F, Albert CH, Thuiller W (2012)
Selecting pseudoâ€ absences for species distribution models: how, where and how many? Methods in ecology and evolution 3 (2): 327-338.
CrossRef | Gscholar

(6)

Bede-Fazekas A, Horvath L, Kocsis M (2014)
Impact of climate change on the potential distribution of Mediterranean pines. Idojaras 118: 41-52.
Online | Gscholar

(7)

Benito Garzón M, Sánchez De Dios R, Sainz Ollero H (2008)
Effects of climate change on the distribution of Iberian tree species. Applied Vegetation Science 11: 169-178.
CrossRef | Gscholar

(8)

Camarero JJ, Manzanedo R, Sanchez-Salguero R, Navarro-Cerrillo R (2013)
Growth response to climate and drought change along an aridity gradient in the southernmost Pinus nigra relict forests. Annals of Forest Science 70: 769-780.
CrossRef | Gscholar

(9)

Candel-Pérez D, Linares JC, Viñegla B, Lucas-Borja ME (2012)
Assessing climate-growth relationships under contrasting stands of co-occurring Iberian pines along an altitudinal gradient. Forest Ecology and Management 274: 48-57.
CrossRef | Gscholar

(10)

Cohen J (1960)
A coefficient of agreement for nominal scales. Educational and Psychological Measurement 20: 37-46.
CrossRef | Gscholar

(11)

Collins Johnson N, Wilson GW, Bowker MA, Wilson JA, Miller R (2010)
Resource limitation is a driver of local adaptation in mycorrhizal symbioses. Proceedings of the National Academy of Sciences USA 107: 2093-2098.
CrossRef | Gscholar

(12)

Duque-Lazo J, Van Gils H, Groen TA, Navarro-Cerrillo RM (2016)
Transferability of species distribution models: the case of Phytophthora cinnamomi in Southwest Spain and Southwest Australia. Ecological Modelling 320: 62-70.
CrossRef | Gscholar

(13)

Elena-Rosselló R, Sánchez-Palomares O (1991)
Los pinares españoles de Pinus nigra: síntesis ecológica [The Spanish pine forests of Pinus nigra: ecological synthesis]. INIA, Madrid, Spain, pp. 110. [in Spanish]
Gscholar

(14)

Elith J, Franklin J (2013)
Species distribution modeling. In: “Encyclopedia of Biodiversity (2nd edn)” (Simon AL eds). Academic Press, Waltham, MS, USA, pp. 692-705.
Gscholar

(15)

Felicísimo AM, Muñoz J, Villalba CJ, Mateo RG (2011)
Impactos, vulnerabilidad y adaptación al cambio climático de la biodiversidad española: proyecciones de las áreas de distribución potencial de la flora amenazada y las especies forestales de la España peninsular con efecto del cambio climático [Impacts, vulnerability and adaptation to climate change of Spanish biodiversity: projections of the areas of potential distribution of threatened flora and forest species in peninsular Spain with the effect of climate change]. Oficina Española de Cambio Climático, Ministerio de Medio Ambiente y Medio Rural y Marino, Madrid, Spain, pp. 552. [in Spanish]
Gscholar

(16)

Franklin J (2010)
Mapping species distributions: spatial inference and prediction. Cambridge University Press, New York, USA, pp. 319.
Online | Gscholar

(17)

Gandullo JM, Palomares OS (1994)
Estaciones ecológicas de los pinares españoles [Ecological sites of the Spanish pine forests]. ICONA, Madrid, Spain, pp. 188. [in Spanish].
Gscholar

(18)

García-Valdés R, Zavala MA, Araújo MB, Purves DW (2013)
Chasing a moving target: projecting climate change-induced shifts in non-equilibrial tree species distributions. Journal of Ecology 101: 441-453.
CrossRef | Gscholar

(19)

Giorgi F (2006)
Climate change hot-spots. Geophysical Research Letters 33 (8): 89.
CrossRef | Gscholar

(20)

Hampe A, Petit RJ (2005)
Conserving biodiversity under climate change: the rear edge matters. Ecology Letters 8: 461-467.
CrossRef | Gscholar

(21)

Herrero A, Rigling A, Zamora R (2013)
Varying climate sensitivity at the dry distribution edge of Pinus sylvestris and P. nigra. Forest Ecology and Management 308: 50-61.
CrossRef | Gscholar

(22)

IPCC (2014)
Climate change (2014): impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL eds). Cambridge University Press, Cambridge, UK and New York, NY, USA, pp. 1132.
Gscholar

(23)

Kautz M, Meddens AJ, Hall RJ, Arneth A (2017)
Biotic disturbances in Northern Hemisphere forests-a synthesis of recent data, uncertainties and implications for forest monitoring and modelling. Global Ecology and Biogeography 26 (5): 533-552.
CrossRef | Gscholar

(24)

Lenoir J, Gégout JC, Marquet PA, De Ruffray P, Brisse H (2008)
A significant upward shift in plant species optimum elevation during the 20th century. Science 320: 1768-1771.
CrossRef | Gscholar

(25)

Linares JC, Tíscar PA (2010)
Climate change im pacts and vulnerability of the southern populations of Pinus nigra subsp. salzmannii. Tree Physiology 30: 795-806.
CrossRef | Gscholar

(26)

López-Tirado J, Hidalgo PJ (2014)
A high resolution predictive model for relict trees in the Mediterranean-mountain forests (Pinus sylvestris L., P. nigra Arnold and Abies pinsapo Boiss.) from the south of Spain: a reliable management tool for reforestation. Forest Ecology and Management 330: 105-114.
CrossRef | Gscholar

(27)

Madrigal-González J, Zavala MA (2014)
Competition and tree age modulated last century pine growth responses to high frequency of dry years in a water limited forest ecosystem. Agricultural and Forest Meteorology 192-193: 18-26.
CrossRef | Gscholar

(28)

Marchi M, Nocentini S, Ducci F (2016)
Future scenarios and conservation strategies for a rear-edge marginal population of Pinus nigra Arnold in Italian central Apennines. Forest Systems 25 (3): e072.
CrossRef | Gscholar

(29)

Merow C, Smith MJ, Edwards TC, Guisan A, McMahon SM, Normand S, Thuiller W, Wüest RO, Zimmermann NE, Elith J (2014)
What do we gain from simplicity versus complexity in species distribution models? Ecography 37: 1267-1281.
CrossRef | Gscholar

(30)

Mod HK, Scherrer D, Luoto M, Guisan A (2016)
What we use is not what we know: environmental predictors in plant distribution models. Journal of Vegetation Science 27 (6): 1308-1322.
CrossRef | Gscholar

(31)

Navarro-Cerrillo RM, Hernandez-Bermejo JE, Hernandez-Clemente R (2011)
Evaluating models to assess the distribution of Buxus balearica in southern Spain. Applied Vegetation Science 14: 256-267.
CrossRef | Gscholar

(32)

Navarro-Cerrillo RM, Sánchez-Salguero R, Manzanedo RD, Camarero JJ, Fernández-Cancio A (2014)
Site and age condition the growth responses to climate and drought of relict Pinus nigra subsp. salzmannii populations in Southern Spain. Tree-Ring Research 70: 145-155.
CrossRef | Gscholar

(33)

Petit RJ, Hampe A (2006)
Some evolutionary consequences of being a tree. Annual Review of Ecology Evolution and Systematics 37: 187-214.
CrossRef | Gscholar

(34)

Piermattei A, Renzaglia F, Urbinati C (2012)
Recent expansion of Pinus nigra Arn. above the timberline in the central Apennines, Italy. Annals of Forest Science 69: 509-517.
CrossRef | Gscholar

(35)

Porfirio LL, Harris RM, Lefroy E, Hugh S, Gould SF, Lee G, Bindoff NL, Mackey B (2014)
Improving the use of species distribution models in conservation planning and management under climate change. PLoS ONE 9 (11): e113749.
CrossRef | Gscholar

(36)

Pyšek P, Manceur AM, Alba C, McGregor KF, Pergl J, Chytry M, Danihelka J, Kartesz J, Klimešová J, Lučanová M, Moravcová L, Nishino M, Sádlo J, Suda J, Tichy L, Kühn I (2014)
Naturalization of central Iberian plants in North America: species traits, habitats, propagule pressure, residence time. Ecology 96 (3): 762-774.
Gscholar

(37)

Quinn GG, Keough MJ (2002)
Experimental design and data analysis for biologists. Cambridge University Press, Cambridge, UK, pp. 553.
CrossRef | Gscholar

(38)

R Core Development Team (2014)
R: a language and environment for statistical computing. R Foundation for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
Online | Gscholar

(39)

REDIAM (2010)
Andalusian Regional Government database. Web site.
Online | Gscholar

(40)

Sanchez-Salguero R, Navarro-Cerrillo RM, Swetnam TW, Zavala MA (2012)
Is drought the main decline factor at the rear edge of Europe? The case of southern Iberian pine plantations. Forest Ecology and Management 271: 158-169.
CrossRef | Gscholar

(41)

Sanchez-Salguero R, Camarero JJ, Dobbertin M, Fernández-Cancio A, Vilà-Cabrera A, Manzanedo RD, Zavala MA, Navarro-Cerrillo RM (2013)
Contrasting vulnerability and resilience to drought-induced decline of densely planted vs. natural rear-edge Pinus nigra forests. Forest Ecology and Management 310: 956-967.
CrossRef | Gscholar

(42)

Soto A, Robledo-Arnuncio JJ, González-Martínez SC, Smouse PE, Alía R (2010)
Climatic niche and neutral genetic diversity of the six Iberian pine species: a retrospective and prospective view. Molecular Ecology 19: 1396-1409.
CrossRef | Gscholar

(43)

Svenning JC, Skov F (2007)
Could the tree diversity pattern in Europe be generated by postglacial dispersal limitation? Ecology Letters 10: 453-460.
CrossRef | Gscholar

(44)

Syphard AD, Franklin J (2009)
Differences in spatial predictions among species distribution modeling methods vary with species traits and environmental predictors. Ecography 32: 907-918.
CrossRef | Gscholar

(45)

Thuiller W (2014)
Editorial commentary on “Patterns and uncertainties of species’ range shifts under climate change”. Global Ecology and Biogeography 20: 3593-3594.
CrossRef | Gscholar

(46)

Thuiller W, Georges D, Engler R (2013)
biomod2: ensemble platform for species distribution modeling. R package version 2.0.3/r539.
Online | Gscholar

(47)

Tíscar PA, Lucas-Borja ME (2016)
Structure of old-growth and managed stands and growth of old trees in a Mediterranean Pinus nigra forest in southern Spain. Forestry 89 (2): 201-207.
CrossRef | Gscholar

(48)

Vale CG, Tarroso P, Brito JC (2014)
Predicting species distribution at range margins: testing the effects of study area extent, resolution and threshold selection in the Sahara-Sahel transition zone. Diversity and Distributions 20: 20-33.
CrossRef | Gscholar

(49)

Van Gils H, Conti F, Ciaschetti G, Westinga E (2012)
Fine resolution distribution modelling of endemics in Majella National Park, Central Italy. Plant Biosystems 146: 276-287.
CrossRef | Gscholar

(50)

Villanueva JA (2005)
Tercer inventario forestal nacional (1997-2007) [Third national forest inventory (1997-2007)]. Ministerio de Medio Ambiente y Medio Rural y Marino. Madrid, Spain, pp. 305. [in Spanish]
Gscholar

(51)

Zhang L, Liu S, Sun P, Wang T, Wang G, Zhang X, Wang L (2015)
Consensus forecasting of species distributions: the effects of niche model performance and niche properties. PLoS ONE 10 (3): e0120056.
CrossRef | Gscholar

iForest - Biogeosciences and Forestry

Contents

Search

Journal Info

Journal Subjects and Fields

For Authors

For Reviewers

For Readers

SISEF Publishing

Search iForest Contents