Maxent Modelling for Distribution of Plant Species Habitats of Rangelands (Iran)

• Autorzy: Chahouki M. A. Z. , Sahragard H. P.

Identyfikatory

DOI

10.3161/15052249PJE2016.64.4.002

• Języki publikacji: EN

Abstrakty

EN

Quantifying the pattern of habitat distribution for range plant species can assist sustainable planning of rangeland use and management. However, data of plant species distribution are often scarce and modeling of habitat distribution using commonly used models is difficult. In this study, the Maximum Entropy Method (MaxEnt) was used to model the distribution of plant habitat to find the effective variables in plant species occurrence in the Poshtkouh rangelands on Yazd province, central Iran. Maps of the environmental variables were generated using GIS and Geostatistics facilities. Accuracy of model output was assessed using area under the curve (AUC) of the receiver operating characteristic and keeping 30 percent of the data. Evaluation of model accuracy by AUC indicated good and acceptable predictive accuracy for all plant species habitats, except Artemisia sieberi which had high frequency. The predictive maps of Artemisia aucheri, Scariola orientalis — Astragalus albispinus, A. sieberi₂ and A. sieberi — Zygophyllum eurypterum had fair agreement with their corresponding observed maps. In addition, the accuracy of S. orientalis — A. sieberi and Tamarix ramosissima predictive maps was low and the estimated conformity rate of prediction and observed maps was poor. In fact, due to differences in the optimal ecological range, level of agreement of predictive and observed maps at each site was different. MaxEnt was substantially excellent to predict distributions of plant species habitat with narrow ecological niches e.g. Rheum ribes — A. sieberi, Seidlitzia rosmarinus and Cornulaca monacantha. It can also perform well with fairly few samples due to employing regularization.

Słowa kluczowe

EN

quantifying habitat distribution; maximum entropy; model accuracy; regularization; Poshtkouh rangelands; Iran

PL

ustalanie wysokości siedlisk dystrybucji; maksymalna wartość; dokładność modelu; uregulowania; pastwiska Poshtkouh; Iran

• Wydawca: Museum and Institute of Zoology, Polish Academy of Sciences
• Czasopismo: Polish Journal of Ecology
• Rocznik: 2016
• Tom: Vol. 64, nr 4
• Strony: 453--467
• Opis fizyczny: Bibliogr. 52 poz., mapa, tab., wykr.

Twórcy

autor

Chahouki M. A. Z.

• Department of Rehabilitation of Arid and Mountainous Regions, University of Tehran, Iran, P.O. Box: 31585-4314

autor

Sahragard H. P.

• Department of Range and Watershed, University of Zabol, Zabol, Iran

Bibliografia

• [1] Allen M. M., Stainer S. T. 1974 — Chemical Analysis of Ecological Materials — Blackwell Scientific Publications, Oxford, London, 565 pp.
• [2] Abdel El-Ghani M., Amer W. M. 2003 — Soil vegetation relationships in a coastal desert plain of southern Sina, Egypt — J. Arid Environ. 55: 607–628.
• [3] Anderson R. P., Lew D., Peterson A. T. 2003 — Evaluating predictive models of species' distributions: criteria for selecting optimal models — Ecol. Model. 162: 211–232.
• [4] Ardestani E. G., Tarkesh M., Bassiri M., Vahabi M. R. 2015 — Potential habitat modeling for reintroduction of three native plant species in central Iran — J. Arid Land.7: 381–390.
• [5] Arekhi S., Heydari M., Pourbabaei H. 2010 — Vegetation-environmental relationships and ecological species groups of the Ilam oak forest landscape, Iran — Caspian J. Environ. Sci. 8: 115–125.
• [6] Austin M. P. 2002 — Spatial prediction of species distribution: an interface between ecological theory and statistical modelling — Ecol. Model. 157: 101–118.
• [7] Benito B. M., Martinez-Ortega M. M., Munoz L. M., Lorite J., Penas J. 2009 — Assessing extinction-risk of endangered plants using species distribution models: a case study of habitat depletion caused by the spread of greenhouses — Biodiv. Conserv. doi: 10.1007/s10531-009-9604-8.
• [8] Black C. A. 1979 — Methods of Soil Analysis — American Society of Agronomy, 2: 771–1572.
• [9] Biglouei M. H., Akbarzadeh A., Yousefi K. 2008 — Effect of composted wood barks (CWBs) on some soil physical and hydraulic properties — Int. J. App. Agr. Res. 4: 1–14.
• [10] Bouyoucos G. J. 1962 — Hydrometer method improved for making particle size analysis of soil — J. Agronomy. 54: 464–465.
• [11] Brotons L., Thuiller W., Araujo M. B., Hirzel A. H. 2004 — Presence-absence versus presence-only modelling methods for predicting bird habitat suitability — Ecography, 27: 437–448.
• [12] Death G., Fabricius K. E. 2000 — Classification and regression trees: a powerful yet simple technique for the analysis of complex ecological data — Ecology, 81: 3178–3192.
• [13] Elith J., Graham C. H., Anderson R. P. 2006 — Novel methods improve prediction of species distributions from occurrence data — Ecography, 29: 129–151.
• [14] Evangelista P. H., Kumar S., Stohlgren T. J. 2008 — Modelling invasion for a habitat generalist and a specialist plant species — Divers Distrib. 14: 808–817.
• [15] Fielding A. H., Bell J. F. 1997 — A Review of Methods for the Assessment of Prediction Errors in Conservation Presence/Absence Methods — Environ. Conserv. 24: 38–49.
• [16] Gaston A., Garcia-Vinas J.I. 2011 — Modelling species distributions with penalized logistic regressions: A comparison with maximum entropy models — Ecol. Model. 222: 2037–2041.
• [17] Graham C. H., Ferrier S., Huettman F., Moritz C., Peterson A. T. 2004 — New developments in museum-based informatics and applications in biodiversity analysis — Trends Ecol. Evol. 199: 497–503.
• [18] Graham C. H., Hijmans R. J. 2006 — A comparison of methods for mapping species ranges and species richness — Glob. Ecol. Biogeogr. 15: 578–587.
• [19] Guisan A., Zimmermann N. E. 2000 — Predictive habitat distribution models in ecology — Ecol. Modell. 135: 147–186.
• [20] Hernandez P. A., Graham C. H., Master L. L., Albert D. L. 2006 — The effect of sample size and species characteristics on performance of different species distribution modeling method — Ecography, 29: 773–785.
• [21] Hosseini S. Z., Kappas M., Zare Chahouki M. A., Gerold G., Erasmi S., Rafiei Emam A. 2013 — Modelling potential habitats for Artemisia sieberi and Artemisia aucheri in Poshtkouh area, central Iran using the maximum entropy model and geostatistics — Ecol. Inform. 18: 61–68.
• [22] Hutchinson G. E. 1957 — Concluding remarks — Cold Spring Harbor Symposia on Quantitative Biology, 22 :415– 427.
• [23] Jackson M. L. 1967 — Soil Chemical Analysis: Advanced Course — Washington, DC, Department of Soil Sciences.
• [24] Khalasi Ahvazi L., Zare Chahouki M. A., Ghorbannezhad F. 2012 — Comparing Discriminant Analysis, Ecological Niche Factor Analysis and Logistic Regression Methods for Geographic Distribution Modelling of Eurotia ceratoides (L.) C. A. Mey — J. Rangeland Sci. 3: 45–57.
• [25] Kumar S., Stohlgren T. J. 2009 — Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia — J. Ecol. Nat. Environ. 1: 94–98.
• [26] Liu C., Berry P. M., Dawson T. P., Pearson R. G. 2005 — Selecting Thresholds of Occurrence in the Prediction of Species Distributions — J. Ecog. 28: 385–393.
• [27] Luoto M., Hjort J. 2005 — Downscaling of coarse-grained geomorphological data — Earth Surf. Process Landf. 33: 75–89.
• [28] Mcpherson J. M., Jetz W. 2007 — Effects of species ecology on the accuracy of distribution models — Ecography, 30: 135–151.
• [29] Monserud R. A., Leemans R. 1992 — Comparing global vegetation maps with the Kappa statistic — J. Ecol. Model. 62: 275–293.
• [30] Ortega-Huerta M. A., Peterson A. T. 2008 — Modeling ecological niches and predicting geographic distributions: a test of six presence-only methods — Revista Mexicana de Biodiversidad. 79: 205–216.
• [31] Pearson R. G., Raxworthy C. J., Nakamura M., Peterson A. T. 2007 — Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar — J. Biogeo. 34: 102–117.
• [32] Phillips S. J., Anderson R. P., Schapire R. E. 2006 — Maximum entropy modeling of species geographic distributions — Ecol. Modell. 190: 231–259.
• [33] Phillips S. J., Dudik M. 2008 — Modeling of species distributions with Maxent. New extensions & a comprehensive evaluation — Ecography, 31: 161–175.
• [34] Phillips S. J., Dudik M., Schapire R. E. 2004 — A maximum entropy approach to species distribution modeling — Proceedings of the 21st International Conference on Machine Learning, ACM Press, New York, pp. 655–662.
• [35] Piri Sahragard H., Azarnivand H., Zare Chahouki M. A., Arzani H., Qumi S. 2011 — Study of effective environmental factors on distribution of plant communities in middle Taleghan basin — J. Range Water Manag. 64: 1–12.
• [36] Piri Sahragard H., Zare Chahouki M. A. 2015 — An evaluation of predictive habitat models performance of plant species in Hoze soltan rangelands of Qom province — Ecol. Modell. 309–310: 64–71.
• [37] Piri Sahragard H., Zare Chahouki M. A., 2016 — Comparison of logistic regression and machine learning techniques in prediction of habitat distribution of plant species — Range Mgmt. & Agroforestry, 37: 21–26.
• [38] Piri Sahragard H., Zare Chahouki M. A., Azarnivand H. 2014 — Modelling of plant species distribution in the Hoze sultan west rangelands of by Logistic regression analysis — J. Range Manage. 1: 15–25.
• [39] Root T. 1988 — Environmental factors associated with avian distributional boundaries — J. Biogeogr. 15: 489–505.
• [40] Sérgio C., Figueira R., Draper D., Menezes R., Sousa A. J. 2007 — Modelling bryophyte distribution based on ecological information for extent of occurrence assessment - Biological distributions: criteria for selecting optimal models — Ecol. Modell. 162: 211–232.
• [41] Steyerberg E. W., Eijkemans M. J., Harrell F. E., Habbema J. D. 2000 — Prognostic modelling with logistic regression analysis: a comparison of selection and estimation methods in small data sets — Stat. Med. 19: 1059–1079.
• [42] Sweet J. A. 1988 — Measuring the accuracy of a diagnostic system — Science, 240: 1285–1293.
• [43] Tarkesh M., Jetschke G. 2012 — Comparison of six correlative models in predictive vegetation mapping on a local scale — Environ. Ecol. Stat. 19: 437–457.
• [44] Thomas C. D., Cameron A., Green R. E., Bakkenes M., Beaumont L. J., Collingham Y. C., Erasmus B. F. N., De Siqueira M. F., Grainger A., Hannah L., Hughes L., Huntley B., van Jaarsveld A. S., Midgley G. F., Miles L., Ortega-Huerta M. A., Peterson A. T., Phillips O. L., Williams S. E. 2004 — Extinction risk from climate change — Nature, 427: 145–148.
• [45] Thuiller W., Richardson D. M., Pyek P., Midgley G. F., Hughes G. O., Rouget M. 2005 — Niche based modelling as a tool for predicting the risk of alien plant invasions at a global scale — Glob. Chang. Biol. 11: 2234–2250.
• [46] Wilson D. J., Western A. W., Grayson R. B. 2004 — Identifying and quantifying sources of variability in temporal and spatial soil moisture observations — Water Resour. Res. 40: 147–186.
• [47] Wisz M. S., Hijmans R. J., Li J., Peterson A. T., Graham C. H., Guisan A. 2008 — Effects of sample size on the performance of species distribution models — Divers. Distrib. 14: 763–773.
• [48] Yang X. Q., Kushwaha S. P. S., Saran S. 2013 — Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills — Ecol. Eng. 51: 83–87.
• [49] Zare Chahouki M. A., Khalasi Ahvazi L., Azarnivand H. 2012 — Comparison of three modelling approaches for predicting plant species distribution in mountaneous scrub vegetation (Semnan rangelands, Iran) — Pol. J. Ecol. 60: 277–289.
• [50] Zare Chahouki M. A., Khojasteh F., Tavili A. 2010 — Distribution of vegetation type according to edaphic properties and topography in Iran — Pol. J. Environ. Stud. 21: 1071–1077.
• [51] Zare Chahouki M. A., Piri Sahragard H., Azarnivand H. 2014 — Habitat distribution modeling of plant species in the Hoze Sultan rangelands of Qom with Maximum Entropy method — J. Range Manage. 7: 212–221.
• [52] Zare Chahouki M. A., Zare Chahouki A. 2010 — Predicting the distribution of plant species using logistic regression (Case study: Garizat rangelands of Yazd province) — Desert Journal, 15: 151—158.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.