Research Article
BibTex RIS Cite

Evaluation by prediction of the natural range shrinkage of Quercus ilex L. in Eastern Algeria

Year 2018, Volume: 68 Issue: 1, 7 - 15, 01.01.2018

Abstract

Abstract: This study focuses on the evaluation by prediction of the spatial distribution of Quercus ilex. L in its natural range in Eastern Algeria. The maximum entropy method has allowed the modelling of the species potentially favourable areas under environmental conditions linking the spatial occurrence and the environmental conditions. Three explanatory parameter groups were used for modelling: i) Edaphic variables, ii) Variables related to topography, iii) Climatic variables. The established predictions demonstrate that over the horizons 2050 and 2070, we will lose 125000 and 147000 hectares respectively. It would seem that the most favourable areas for Quercus ilex would extend between elevations of 1430 meters for 2050 and reach by 2070, 1650 meters. The performance of the used model has been confirmed by the value of AUC which is 0,929. The high elevations especially those of the Saharian Atlas will offer the climatic refuges. These results represent a decision support tool for the best strategy of sensibilization and planning for the holm oak conservation.

Keywords: Climatic forcing, ecological niche, species distribution model, kolm oak, maximum entropy


Received (Geliş): 04.08.2017 - Revised (Düzeltme): 26.10.2017 -   Accepted (Kabul): 08.11.2017

References

  • Aguirre-Gutiérrez, J., Carvalheiro, L. G., Polce, C., van Loon, E. E., Raes, N., Reemer, M., Biesmeijer, J. C., 2013. Fit-for-purpose: species distribution model performance depends on evaluation criteria–Dutch hoverflies as a case study. PloS one, 8(5), e63708, doi:10.1371/journal.pone.0063708.
  • Ahmed, L., Djamel, A., Amina, A., 2016. Apport Des Images Satellites MODIS Dans L'étude De L'évolution De La Végétation Forestière De l'Est Algérien. European Scientific Journal, 12(20) ,195-213.
  • Ahmed, S. E., McInerny, G., O'Hara, K., Harper, R., Salido, L., Emmott, S., Joppa, L. N., 2015. Scientists and software–surveying the species distribution modelling community. Diversity and Distributions, 21(3), 258-267, doi: 10.1111/ddi.12305.
  • Al Hamndou, D., Requier-Desjardins, M., 2008. Variabilité climatique, désertification et biodiversité en Afrique: s’ adapter, une approche intégrée. VertigO-la revue électronique en sciences de l'environnement, 8(1), doi: 10.4000/vertigo.5356.
  • Araujo, M. B., Pearson, R. G., Thuiller, W., Erhard, M., 2005. Validation of species–climate impact models under climate change. Global Change Biology, 11(9), 1504-1513, doi: 10.1111/j.1365-2486.2005.01000.x.
  • Austin, M. P., 2002. Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological modelling, 157(2), 101-118, doi: 10.1016/S0304-3800(02)00205-3.
  • Bennadji MH., 2005. Algérie environnement et développement durable, rapport. institut national d'études des stratégies globale. pp 32.
  • Bertrand, R., Perez, V., Gégout, J. C., 2012. Disregarding the edaphic dimension in species distribution models leads to the omission of crucial spatial information under climate change: the case of Quercus pubescens in France. Global Change Biology, 18(8), 2648-2660, doi: 10.1111/j.1365-2486.2012.02679.x.
  • Boudy, P., 1955. Economie forestière nord-africaine. vol.1 : Description forestière de l’Algérie et de la Tunisie. La rose, Paris, 370 p. Cartes.
  • Daget, P., (1977). Le bioclimat méditerranéen: caractères généraux, modes de caractérisation. Plant Ecology, 34(1), 1-20.
  • De'Ath, G., 2007. Boosted trees fore cological modeling and prediction. Ecology, 88(1),243-251,doi:10.1890/0012-9658(2007)88[243:BTFEMA]2.0.CO;2.
  • DGF., 2007. Rapport sur la politique forestière et stratégique d’aménagement et de développement durable des ressources forestières et alfatières. pp 81.
  • Donadieu P., 1977. Contribution à une synthèse bioclimatique et phytogéographique au Maroc. Trav. Inst. Agron. Vét. Hassan II, Rabat, 1-155.
  • Fielding, A.H., Bell, J.F., 1997. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental conservation, 24(1), 38-49.
  • Ghazi, A., Lahouati, R., 1997. Algérie 2010. Sols et ressources biologiques. Alger: Institut national des études de stratégie globale (INESG).
  • Gaussen, H., Vernet, A,. 1958. Carte internationale du tapis végétal. Feuilles NJ-32 et NI-32, Tunis - Sfax. Bulletin du Service de la carte phytogéographique. Série A, Carte de la végétation. Centre national de la recherche sciéntifique.
  • Guisan, A., Hofer, U., 2003. Predicting reptile distributions at the mesoscale: relation to climate and topography. Journal of Biogeography, 30(8), 1233-1243.
  • Guisan, A., Thuiller, W., 2005. Predicting species distribution: offering more than simple habitat models. Ecology letters, 8(9),doi: 993-1009,10.1111/j.1461-0248.2005.00792.x.
  • Hengl, T., de Jesus, J. M,. MacMillan, R..A., Batjes, N.H., Heuvelink, G.B., Ribeiro, E., Samuel-Rosa, A., Kempen, B., Leenaars, J. G.B., Walsh, M. G., et al., 2014. SoilGrids1km- global soil information based on automated mapping. PLoS One, 9(8), e105992, doi: 10.1371/journal.pone.011478.8.
  • Hijmans,R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978, doi: 10.1002/joc.1276.
  • Hirzel, A.H., Hausser, J., Chessel, D., Perrin, N., 2002. Ecological-niche factor analysis: how to compute habitat‐suitability maps without absence data?. Ecology, 83(7), 2027-2036.
  • Stocker, T. F., Qin, D., Plattner, G. K., Alexander, L. V., Allen, S. K., Bindoff, N. L., Forster, P., 2013. Technical summary. In Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 33-115). Cambridge University Press.
  • Keya, Z. Y., Faryadi, S., Yavari, A., Kamali, Y., Shabani, A. A., 2016. Habitat Suitability & Connectivity of Alborz Wild Sheep in the East of Tehran, Iran. Open Journal of Ecology, 6(06), 325,doi: 10.4236/oje.2016.66032.
  • Kumar, S., Graham, J., West, A.M., Evangelista, P.H., 2014. Using district-level occurrences in MaxEnt for predicting the invasion potential of an exotic insect pest in India. Computers and Electronics in Agriculture, 103, 55-62, doi: 10.1016/j.compag.2014.02.007.
  • Laala, A., Alatou, D., 2016. Analyse de la dynamique des massifs forestiers de l'Est algérien par la télédétection satellitaire/[Dynamics Analysis of the forests of eastern Algeria by satellite remote sensing]. International Journal of Innovation and Applied Studies, 17(3), 954-964.
  • Lenoir, J., Gégout, J. C., Marquet, P. A., De Ruffray, P., Brisse, H., 2008. A significant upward shift in plant species optimum elevation during the 20th century. science, 320(5884), 1768-1771, doi: 10.1126/science.1156831.
  • Lobo, J. M., Jiménez,-Valverde, A., Real, R., 2008. AUC : A misleading measure of the performance of predictive distribution models. Global ecology and Biogeography, 17(2), 145-151, doi: 10.1111/j.1466-8238.2007.00358.x.
  • Lobry, C., Sari, T., 2007. La mod´elisation de la persistance en ´ecologie. Colloque `a la m´emoire d’Emmanuel Isambert, Universit´e de Paris 7, Dec 2007, Paris, France. Publications de l’Universit´e de Paris 13, 163 - 184.
  • Maire, R.,1926. Principaux groupement de végétaux d’Algérie. Station centrale de recherche en écologie forestière. CNREF Inst. NRA d'Algérie.7p.
  • Matawa, F., Murwira, A., Zengeya, F. M., Atkinson, P. M., 2016. Modelling the spatial-temporal distribution of tsetse (Glossina pallidipes) as a function of topography and vegetation greenness in the Zambezi Valley of Zimbabwe. Applied Geography, 76, 198-206, 10.1016/j.apgeog.2016.09.008.
  • Mendoza-Fernández, A., Pérez-García, F. J., Medina-Cazorla, J. M., Martínez-Hernández, F., Garrido-Becerra, J. A., Sánchez, E. S., Mota, J. F., 2010. Gap Analysis and selection of reserves for the threatened flora of eastern Andalusia, a hot spot in the eastern Mediterranean region. Acta Botanica Gallica, 157(4), 749-767, doi: 10.1080/12538078.2010.10516245.
  • Merdas S, Mostephaoui T, Belhamra M., 2017. Reforestation in Algeria: History, current practice and future perspectives. REFORESTA. Vol 0, No 3.116-125, doi: 10.21750/R EFOR.3.10.34.
  • M'Hirit, O., 1999. La forêt méditerranéenne: espace écologique, richesse économique et bien social. Unasylva (FAO).197 (50).
  • Norby, R. J., Cotrufo, M. F., 1998. Global change: a question of litter quality. Nature, 396(6706), 17-18, doi: 10.1038/23812
  • Önder, D., Aydin, M., BERBEROĞLU, S., Önder, S., Yano, T., 2009. The use of aridity index to assess implications of climatic change for land cover in Turkey. Turkish Journal of Agriculture and Forestry, 33(3), 305-314, doi:10.3906/tar-0810-21.
  • Parmesan, C., 2006. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Evol. Syst., 37, 637-669, doi: 10.1146/annurev.ecolsys.37.091305.110100.
  • Parmesan, C., Yohe, G., 2003. A globally coherent fingerprint of climate change impacts across natural systems, Nature 421: 37–42,doi: 10.1038/nature01286.
  • Parry M.L., O.F. Canziani, J.P. Palutikof, P.J. van der Linden., C.E. Hanson, Eds., 2007. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, 982pp.
  • Peterson, A. T., Nakazawa, Y., 2008. Environmental data sets matter in ecological niche modelling: an example with Solenopsis invicta and Solenopsis richteri. Global ecology and Biogeography, 17(1), 135-144, doi: 10.1111/j.1466-8238.2007.00347.x.
  • Phillips, S. J., Dudík, M., Elith, J., Graham, C. H., Lehmann, A., Leathwick, J., Ferrier, S., 2009. Sample selection bias and presence‐only distribution models: implications for background and pseudo‐absence data. Ecological applications, 19(1), 181-197, doi: 10.1890/07-2153.1.
  • Phillips, S. J., Dudík, M., 2008. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography, 31(2), 161-175, doi: 10.1111/j.2007.0906-7590.05203.x.
  • Phillips, S. J., Dudík, M., Schapire, R. E., 2004. A maximum entropy approach to species distribution modeling. In Proceedings of the twenty-first international conference on Machine learning (p. 83). ACM ,doi: 10.1145/1015330.1015412.
  • Pouteau, R., Meyer, J. Y., Taputuarai, R., Stoll, B., 2010. La fonte de la biodiversité dans les îles: modélisation de l’impact du réchauffement global sur la végétation orophile de Tahiti (Polynésie française). [VertigO] La revue électronique en sciences de l’environnement, 10(3), 0-0.
  • Qin, A., Liu, B., Guo, Q., Bussmann, R. W., Ma, F., Jian, Z., Pei, S., 2017. Maxent modeling for predicting impacts of climate change on the potential distribution of Thuja sutchuenensis Franch., an extremely endangered conifer from southwestern China. Global Ecology and Conservation, 10, 139-146, doi: 10.1016/j.gecco.2017.02.004.
  • Quezel, P., 1979. La région méditerranéenne française et ses essences forestières, signification écologique dans le contexte circum-méditerranéen. Forêt méditerranéenne, 1(1), 7-18.
  • Quezel, P., 1999. Biodiversité végétale des forêts méditerranéennes: son évolution éventuelle d'ici trente ans. Forêt méditerranéenne t. XX, n° 1.pp 3-8. Quezel, P., Barbero, M., Bonnin, G., Loisel, R., 1980. Essai de corrélations phyto-sociologiques et bioclimatiques entre quelques structures actuelles et passées de la végétation méditerranéenne. Rev. Nat. Montpellier, Nhors série, 89, 1000.
  • Quézel, P., Médail, F., 2003. Ecologie et biogéographie des forêts du bassin méditerranéen, Editions scientifiques Elsevier, Collection environnement,2-84299-451-5, 574 p.
  • Ray, D, Behera, M.D., Jacob, J., 2017. Evaluating Ecological Niche Models: A Comparison Between Maxent and GARP for Predicting Distribution of Hevea brasiliensis in India. Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, 1-7.
  • Reddy, M. T., Begum, H., Sunil, N., Pandravada, S. R., Sivaraj, N., Kumar, S., 2015. Mapping the Climate Suitability Using MaxEnt Modeling Approach for Ceylon Spinach (Basella alba L.) Cultivation in India. Journal of Agricultural Sciences, 10(2).
  • Rivas-Martínez, S., 1980. Les étages bioclimatiques de la végétation de la Péninsule Ibérique. In Anales del Jardín Botánico de Madrid (Vol. 37, No. 2, 251-268.
  • Saifi, M., Nouar, B., Fattoum, L., 2015. The Green Dam in Algeria as a tool to combat desertification. Planet@ Risk, 3(1).pp 68-71, Davos: Global Risk Forum GRF Davos.
  • Seigue, A., 1985. forêt circumméditerranéenne et ses problèmes. Maisonneuve et Larose, 502p.
  • Slimani, S., Derridj, A., Gutierrez, E., 2014. Ecological response of Cedrus atlantica to climate variability in the Massif of Guetiane (Algeria). Forest Systems, 23(3), 448-460, doi: 10.5424/fs/2014233-05175.
  • Swets, J. A., 1988. Measuring the accuracy of diagnostic systems. Science, 240(4857), 1285-1293.
  • Thuiller, W., 2003. BIOMOD–optimizing predictions of species distributions and projecting potential future shifts under global change. Global change biology, 9(10), 1353-1362.
  • Vessella, F., López-Tirado, J., Simeone, M.C., Schirone, B., Hidalgo, P.J., 2017. A tree species range in the face of climate change: cork oak as a study case for the Mediterranean biome. European Journal of Forest Research, 1-15,doi: 10.1007/s10342-017-1055-2.
  • Vitousek, P. M., Mooney, H. A., Lubchenco, J., Melillo, J. M., 1997. Human domination of Earth's ecosystems. Science, 277(5325),494-499 ,doi: 10.1126/science.277.5325.494.
  • Warren, D. L., Glor, R. E., Turelli, M., 2010. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography, 33(3), 607-611.doi:0.1111/j.1600-0587.2009.06142.x.
  • Warren, D. L., eifert, S. N., 2011. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecological Applications, 21(2), 335-342.
  • Williams, J. W., Jackson, S. T., 2007. Novel climates, no‐analog communities, and ecological surprises. Frontiers in Ecology and the Environment, 5(9), 475-482,doi: 10.1890/070037.
  • Zaidi, F., Fatima, S. H., Khisroon, M., Gul, A., 2016. Distribution modeling of three screwworm species in the ecologically diverse landscape of North West Pakistan. Acta tropica, 162, 56-65,doi: 10.1016/j.actatropica.2016.06.015.
  • Zuur, A.F., Ieno, E.N., Walker, N.J0, Saveliev, A.A., Smith, G.M., 2009. Things are not always linear; additive modelling. Mixed effects models and extensions in ecology with R, 35-69.

Doğu Cezayir’de Quercus ilex L.’nin doğal yayılış alanında azalmanın öngörülmesinin değerlendirilmesi

Year 2018, Volume: 68 Issue: 1, 7 - 15, 01.01.2018

Abstract

Bu çalışma
Quercus ilex. L
nin Doğu Cezayirde doğal yayılışının mekansal dağılımının öngörülmesinin
değerlendirilmesine odaklanmaktadır. Maksimum entropi yöntemi, mekansal oluşum
ve çevre koşullarını ilişkilendiren çevresel şartlar altında potansiyel olarak
uygun türleri modellemeye olanak sağlamıştır. Modelleme için üç açıklayıcı
parametre grubu kullanıldı: i) edafik değişkenler, ii) topografya ile ilgili değişkenler
ve iii) iklimsel değişkenler. Öngörülere göre, 2050 ve 2070 yıllarında sırasıyla
125000 ve 147000 hektar alan kaybolacaktır. Quercus ilex için en uygun alanlar
2050 yılında 1430 metre rakıma ve 2070
de
1650 metre rakıma çıkacaktır. Çalışmada kullanılan modelin performansı 0,929
olan AUC değeri ile doğrulandı. Yüksek rakımlar, özellikle Sahra Atlaslarının
rakımları, iklime bağlı olarak sığınaklar sunacaktır. Bu sonuçlar en iyi
sensibilizasyon stratejisi ve çalı meşesinin korunmasının planlaması için
verilecek kararları destekleyecek bir araç niteliğindedir.

References

  • Aguirre-Gutiérrez, J., Carvalheiro, L. G., Polce, C., van Loon, E. E., Raes, N., Reemer, M., Biesmeijer, J. C., 2013. Fit-for-purpose: species distribution model performance depends on evaluation criteria–Dutch hoverflies as a case study. PloS one, 8(5), e63708, doi:10.1371/journal.pone.0063708.
  • Ahmed, L., Djamel, A., Amina, A., 2016. Apport Des Images Satellites MODIS Dans L'étude De L'évolution De La Végétation Forestière De l'Est Algérien. European Scientific Journal, 12(20) ,195-213.
  • Ahmed, S. E., McInerny, G., O'Hara, K., Harper, R., Salido, L., Emmott, S., Joppa, L. N., 2015. Scientists and software–surveying the species distribution modelling community. Diversity and Distributions, 21(3), 258-267, doi: 10.1111/ddi.12305.
  • Al Hamndou, D., Requier-Desjardins, M., 2008. Variabilité climatique, désertification et biodiversité en Afrique: s’ adapter, une approche intégrée. VertigO-la revue électronique en sciences de l'environnement, 8(1), doi: 10.4000/vertigo.5356.
  • Araujo, M. B., Pearson, R. G., Thuiller, W., Erhard, M., 2005. Validation of species–climate impact models under climate change. Global Change Biology, 11(9), 1504-1513, doi: 10.1111/j.1365-2486.2005.01000.x.
  • Austin, M. P., 2002. Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological modelling, 157(2), 101-118, doi: 10.1016/S0304-3800(02)00205-3.
  • Bennadji MH., 2005. Algérie environnement et développement durable, rapport. institut national d'études des stratégies globale. pp 32.
  • Bertrand, R., Perez, V., Gégout, J. C., 2012. Disregarding the edaphic dimension in species distribution models leads to the omission of crucial spatial information under climate change: the case of Quercus pubescens in France. Global Change Biology, 18(8), 2648-2660, doi: 10.1111/j.1365-2486.2012.02679.x.
  • Boudy, P., 1955. Economie forestière nord-africaine. vol.1 : Description forestière de l’Algérie et de la Tunisie. La rose, Paris, 370 p. Cartes.
  • Daget, P., (1977). Le bioclimat méditerranéen: caractères généraux, modes de caractérisation. Plant Ecology, 34(1), 1-20.
  • De'Ath, G., 2007. Boosted trees fore cological modeling and prediction. Ecology, 88(1),243-251,doi:10.1890/0012-9658(2007)88[243:BTFEMA]2.0.CO;2.
  • DGF., 2007. Rapport sur la politique forestière et stratégique d’aménagement et de développement durable des ressources forestières et alfatières. pp 81.
  • Donadieu P., 1977. Contribution à une synthèse bioclimatique et phytogéographique au Maroc. Trav. Inst. Agron. Vét. Hassan II, Rabat, 1-155.
  • Fielding, A.H., Bell, J.F., 1997. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental conservation, 24(1), 38-49.
  • Ghazi, A., Lahouati, R., 1997. Algérie 2010. Sols et ressources biologiques. Alger: Institut national des études de stratégie globale (INESG).
  • Gaussen, H., Vernet, A,. 1958. Carte internationale du tapis végétal. Feuilles NJ-32 et NI-32, Tunis - Sfax. Bulletin du Service de la carte phytogéographique. Série A, Carte de la végétation. Centre national de la recherche sciéntifique.
  • Guisan, A., Hofer, U., 2003. Predicting reptile distributions at the mesoscale: relation to climate and topography. Journal of Biogeography, 30(8), 1233-1243.
  • Guisan, A., Thuiller, W., 2005. Predicting species distribution: offering more than simple habitat models. Ecology letters, 8(9),doi: 993-1009,10.1111/j.1461-0248.2005.00792.x.
  • Hengl, T., de Jesus, J. M,. MacMillan, R..A., Batjes, N.H., Heuvelink, G.B., Ribeiro, E., Samuel-Rosa, A., Kempen, B., Leenaars, J. G.B., Walsh, M. G., et al., 2014. SoilGrids1km- global soil information based on automated mapping. PLoS One, 9(8), e105992, doi: 10.1371/journal.pone.011478.8.
  • Hijmans,R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978, doi: 10.1002/joc.1276.
  • Hirzel, A.H., Hausser, J., Chessel, D., Perrin, N., 2002. Ecological-niche factor analysis: how to compute habitat‐suitability maps without absence data?. Ecology, 83(7), 2027-2036.
  • Stocker, T. F., Qin, D., Plattner, G. K., Alexander, L. V., Allen, S. K., Bindoff, N. L., Forster, P., 2013. Technical summary. In Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 33-115). Cambridge University Press.
  • Keya, Z. Y., Faryadi, S., Yavari, A., Kamali, Y., Shabani, A. A., 2016. Habitat Suitability & Connectivity of Alborz Wild Sheep in the East of Tehran, Iran. Open Journal of Ecology, 6(06), 325,doi: 10.4236/oje.2016.66032.
  • Kumar, S., Graham, J., West, A.M., Evangelista, P.H., 2014. Using district-level occurrences in MaxEnt for predicting the invasion potential of an exotic insect pest in India. Computers and Electronics in Agriculture, 103, 55-62, doi: 10.1016/j.compag.2014.02.007.
  • Laala, A., Alatou, D., 2016. Analyse de la dynamique des massifs forestiers de l'Est algérien par la télédétection satellitaire/[Dynamics Analysis of the forests of eastern Algeria by satellite remote sensing]. International Journal of Innovation and Applied Studies, 17(3), 954-964.
  • Lenoir, J., Gégout, J. C., Marquet, P. A., De Ruffray, P., Brisse, H., 2008. A significant upward shift in plant species optimum elevation during the 20th century. science, 320(5884), 1768-1771, doi: 10.1126/science.1156831.
  • Lobo, J. M., Jiménez,-Valverde, A., Real, R., 2008. AUC : A misleading measure of the performance of predictive distribution models. Global ecology and Biogeography, 17(2), 145-151, doi: 10.1111/j.1466-8238.2007.00358.x.
  • Lobry, C., Sari, T., 2007. La mod´elisation de la persistance en ´ecologie. Colloque `a la m´emoire d’Emmanuel Isambert, Universit´e de Paris 7, Dec 2007, Paris, France. Publications de l’Universit´e de Paris 13, 163 - 184.
  • Maire, R.,1926. Principaux groupement de végétaux d’Algérie. Station centrale de recherche en écologie forestière. CNREF Inst. NRA d'Algérie.7p.
  • Matawa, F., Murwira, A., Zengeya, F. M., Atkinson, P. M., 2016. Modelling the spatial-temporal distribution of tsetse (Glossina pallidipes) as a function of topography and vegetation greenness in the Zambezi Valley of Zimbabwe. Applied Geography, 76, 198-206, 10.1016/j.apgeog.2016.09.008.
  • Mendoza-Fernández, A., Pérez-García, F. J., Medina-Cazorla, J. M., Martínez-Hernández, F., Garrido-Becerra, J. A., Sánchez, E. S., Mota, J. F., 2010. Gap Analysis and selection of reserves for the threatened flora of eastern Andalusia, a hot spot in the eastern Mediterranean region. Acta Botanica Gallica, 157(4), 749-767, doi: 10.1080/12538078.2010.10516245.
  • Merdas S, Mostephaoui T, Belhamra M., 2017. Reforestation in Algeria: History, current practice and future perspectives. REFORESTA. Vol 0, No 3.116-125, doi: 10.21750/R EFOR.3.10.34.
  • M'Hirit, O., 1999. La forêt méditerranéenne: espace écologique, richesse économique et bien social. Unasylva (FAO).197 (50).
  • Norby, R. J., Cotrufo, M. F., 1998. Global change: a question of litter quality. Nature, 396(6706), 17-18, doi: 10.1038/23812
  • Önder, D., Aydin, M., BERBEROĞLU, S., Önder, S., Yano, T., 2009. The use of aridity index to assess implications of climatic change for land cover in Turkey. Turkish Journal of Agriculture and Forestry, 33(3), 305-314, doi:10.3906/tar-0810-21.
  • Parmesan, C., 2006. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Evol. Syst., 37, 637-669, doi: 10.1146/annurev.ecolsys.37.091305.110100.
  • Parmesan, C., Yohe, G., 2003. A globally coherent fingerprint of climate change impacts across natural systems, Nature 421: 37–42,doi: 10.1038/nature01286.
  • Parry M.L., O.F. Canziani, J.P. Palutikof, P.J. van der Linden., C.E. Hanson, Eds., 2007. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, 982pp.
  • Peterson, A. T., Nakazawa, Y., 2008. Environmental data sets matter in ecological niche modelling: an example with Solenopsis invicta and Solenopsis richteri. Global ecology and Biogeography, 17(1), 135-144, doi: 10.1111/j.1466-8238.2007.00347.x.
  • Phillips, S. J., Dudík, M., Elith, J., Graham, C. H., Lehmann, A., Leathwick, J., Ferrier, S., 2009. Sample selection bias and presence‐only distribution models: implications for background and pseudo‐absence data. Ecological applications, 19(1), 181-197, doi: 10.1890/07-2153.1.
  • Phillips, S. J., Dudík, M., 2008. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography, 31(2), 161-175, doi: 10.1111/j.2007.0906-7590.05203.x.
  • Phillips, S. J., Dudík, M., Schapire, R. E., 2004. A maximum entropy approach to species distribution modeling. In Proceedings of the twenty-first international conference on Machine learning (p. 83). ACM ,doi: 10.1145/1015330.1015412.
  • Pouteau, R., Meyer, J. Y., Taputuarai, R., Stoll, B., 2010. La fonte de la biodiversité dans les îles: modélisation de l’impact du réchauffement global sur la végétation orophile de Tahiti (Polynésie française). [VertigO] La revue électronique en sciences de l’environnement, 10(3), 0-0.
  • Qin, A., Liu, B., Guo, Q., Bussmann, R. W., Ma, F., Jian, Z., Pei, S., 2017. Maxent modeling for predicting impacts of climate change on the potential distribution of Thuja sutchuenensis Franch., an extremely endangered conifer from southwestern China. Global Ecology and Conservation, 10, 139-146, doi: 10.1016/j.gecco.2017.02.004.
  • Quezel, P., 1979. La région méditerranéenne française et ses essences forestières, signification écologique dans le contexte circum-méditerranéen. Forêt méditerranéenne, 1(1), 7-18.
  • Quezel, P., 1999. Biodiversité végétale des forêts méditerranéennes: son évolution éventuelle d'ici trente ans. Forêt méditerranéenne t. XX, n° 1.pp 3-8. Quezel, P., Barbero, M., Bonnin, G., Loisel, R., 1980. Essai de corrélations phyto-sociologiques et bioclimatiques entre quelques structures actuelles et passées de la végétation méditerranéenne. Rev. Nat. Montpellier, Nhors série, 89, 1000.
  • Quézel, P., Médail, F., 2003. Ecologie et biogéographie des forêts du bassin méditerranéen, Editions scientifiques Elsevier, Collection environnement,2-84299-451-5, 574 p.
  • Ray, D, Behera, M.D., Jacob, J., 2017. Evaluating Ecological Niche Models: A Comparison Between Maxent and GARP for Predicting Distribution of Hevea brasiliensis in India. Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, 1-7.
  • Reddy, M. T., Begum, H., Sunil, N., Pandravada, S. R., Sivaraj, N., Kumar, S., 2015. Mapping the Climate Suitability Using MaxEnt Modeling Approach for Ceylon Spinach (Basella alba L.) Cultivation in India. Journal of Agricultural Sciences, 10(2).
  • Rivas-Martínez, S., 1980. Les étages bioclimatiques de la végétation de la Péninsule Ibérique. In Anales del Jardín Botánico de Madrid (Vol. 37, No. 2, 251-268.
  • Saifi, M., Nouar, B., Fattoum, L., 2015. The Green Dam in Algeria as a tool to combat desertification. Planet@ Risk, 3(1).pp 68-71, Davos: Global Risk Forum GRF Davos.
  • Seigue, A., 1985. forêt circumméditerranéenne et ses problèmes. Maisonneuve et Larose, 502p.
  • Slimani, S., Derridj, A., Gutierrez, E., 2014. Ecological response of Cedrus atlantica to climate variability in the Massif of Guetiane (Algeria). Forest Systems, 23(3), 448-460, doi: 10.5424/fs/2014233-05175.
  • Swets, J. A., 1988. Measuring the accuracy of diagnostic systems. Science, 240(4857), 1285-1293.
  • Thuiller, W., 2003. BIOMOD–optimizing predictions of species distributions and projecting potential future shifts under global change. Global change biology, 9(10), 1353-1362.
  • Vessella, F., López-Tirado, J., Simeone, M.C., Schirone, B., Hidalgo, P.J., 2017. A tree species range in the face of climate change: cork oak as a study case for the Mediterranean biome. European Journal of Forest Research, 1-15,doi: 10.1007/s10342-017-1055-2.
  • Vitousek, P. M., Mooney, H. A., Lubchenco, J., Melillo, J. M., 1997. Human domination of Earth's ecosystems. Science, 277(5325),494-499 ,doi: 10.1126/science.277.5325.494.
  • Warren, D. L., Glor, R. E., Turelli, M., 2010. ENMTools: a toolbox for comparative studies of environmental niche models. Ecography, 33(3), 607-611.doi:0.1111/j.1600-0587.2009.06142.x.
  • Warren, D. L., eifert, S. N., 2011. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecological Applications, 21(2), 335-342.
  • Williams, J. W., Jackson, S. T., 2007. Novel climates, no‐analog communities, and ecological surprises. Frontiers in Ecology and the Environment, 5(9), 475-482,doi: 10.1890/070037.
  • Zaidi, F., Fatima, S. H., Khisroon, M., Gul, A., 2016. Distribution modeling of three screwworm species in the ecologically diverse landscape of North West Pakistan. Acta tropica, 162, 56-65,doi: 10.1016/j.actatropica.2016.06.015.
  • Zuur, A.F., Ieno, E.N., Walker, N.J0, Saveliev, A.A., Smith, G.M., 2009. Things are not always linear; additive modelling. Mixed effects models and extensions in ecology with R, 35-69.
There are 62 citations in total.

Details

Primary Language English
Journal Section Research Articles (Araştırma Makalesi)
Authors

Slimane Tabet

Mohammed Belhemra This is me

Louis Francois This is me

Abdlekrim Arar This is me

Publication Date January 1, 2018
Published in Issue Year 2018 Volume: 68 Issue: 1

Cite

APA Tabet, S., Belhemra, M., Francois, L., Arar, A. (2018). Evaluation by prediction of the natural range shrinkage of Quercus ilex L. in Eastern Algeria. Journal of the Faculty of Forestry Istanbul University, 68(1), 7-15.
AMA Tabet S, Belhemra M, Francois L, Arar A. Evaluation by prediction of the natural range shrinkage of Quercus ilex L. in Eastern Algeria. J FAC FOR ISTANBUL U. January 2018;68(1):7-15.
Chicago Tabet, Slimane, Mohammed Belhemra, Louis Francois, and Abdlekrim Arar. “Evaluation by Prediction of the Natural Range Shrinkage of Quercus Ilex L. In Eastern Algeria”. Journal of the Faculty of Forestry Istanbul University 68, no. 1 (January 2018): 7-15.
EndNote Tabet S, Belhemra M, Francois L, Arar A (January 1, 2018) Evaluation by prediction of the natural range shrinkage of Quercus ilex L. in Eastern Algeria. Journal of the Faculty of Forestry Istanbul University 68 1 7–15.
IEEE S. Tabet, M. Belhemra, L. Francois, and A. Arar, “Evaluation by prediction of the natural range shrinkage of Quercus ilex L. in Eastern Algeria”, J FAC FOR ISTANBUL U, vol. 68, no. 1, pp. 7–15, 2018.
ISNAD Tabet, Slimane et al. “Evaluation by Prediction of the Natural Range Shrinkage of Quercus Ilex L. In Eastern Algeria”. Journal of the Faculty of Forestry Istanbul University 68/1 (January 2018), 7-15.
JAMA Tabet S, Belhemra M, Francois L, Arar A. Evaluation by prediction of the natural range shrinkage of Quercus ilex L. in Eastern Algeria. J FAC FOR ISTANBUL U. 2018;68:7–15.
MLA Tabet, Slimane et al. “Evaluation by Prediction of the Natural Range Shrinkage of Quercus Ilex L. In Eastern Algeria”. Journal of the Faculty of Forestry Istanbul University, vol. 68, no. 1, 2018, pp. 7-15.
Vancouver Tabet S, Belhemra M, Francois L, Arar A. Evaluation by prediction of the natural range shrinkage of Quercus ilex L. in Eastern Algeria. J FAC FOR ISTANBUL U. 2018;68(1):7-15.