SpringerLink
Log in

Ecosystem restoration and degradation monitoring using ecological indices

  • Original Paper
  • Published:
International Journal of Environmental Science and Technology Aims and scope Submit manuscript

Abstract

Ecosystem monitoring provides us with valuable information for modeling the future response to global changes and designing management plans. This paper clarifies the ability of ecosystem indices to monitor ecosystem degradation and restoration. The indices include the changes in landscape metrics, water birds’ habitat, changes in the extent of the affected areas by sand and dust storms, and availability of water. The land-use/land-cover maps of 1977, 2000, 2015, and 2020 were created using the support vector machine classification method and were utilized as inputs to calculate ecological indices. The results of this study revealed advantages of landscape indices to monitor the ecosystem. Landscape metrics are measurable units allowing the quantification of spatial pattern change. The land-use/land-cover maps of 1977, 2000, 2015, and 2020 were created using the support vector machine classification method and were utilized as inputs to calculate ecological indices. The results show that in 2000 the ecosystem was in worse condition. In this year, the bare land area increased by 496% rather than in 1977. But, in 2020 the water body and flooded vegetation increased by 100% and vegetation raised up by 67%; also, the bare land decreased by 47%. Therefore, the ecosystem restored in 2020 in comparison with 2000, while in comparison with 1977 the ecosystem is degraded in 2020 because the water body and flooded vegetation declined by 40 and 67%. Also, the bare land area in 2020 is 215% higher than in 1977. Habitat suitability maps are valuable for designing conservation action plans for critical species. Sand and dust storms are a particular index for monitoring the ecosystem condition in an arid area. The change in water availability is a valuable index for monitoring ecosystem degradation and restoration. Based on these results, a combination of these indices provides a comprehensive tool for monitoring the ecosystem because each index quantifies the change in a particular criterion of the ecosystem.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Canada)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Availability of data and material

Not applicable.

Code availability

Not applicable.

References

  • Balist J, Malekmohammadi B, Jafari HR, Nohegar A, Geneletti D (2022) Detecting land use and climate impacts on water yield ecosystem service in arid and semi-arid areas A study in Sirvan River Basin-Iran. Appl Water Sci 12(1):1–14

    Article  Google Scholar 

  • Bigdeli B, Samadzadegan F, Reinartz PA (2013) Multiple SVM system for classification of hyperspectral remote sensing data. J Indian Soc Remote 41:763–776

    Article  Google Scholar 

  • Bocedi G, Palmer SC, Pe’er G, Heikkinen RK, Matsinos YG, Watts K, Travis JM (2014) Rangeshifter: a platform for modelling spatial eco-evolutionary dynamics and species’ responses to environmental changes. Methods Ecol Evol 5(4):388–396

    Article  Google Scholar 

  • Castañeda C, Herrero J, Auxiliadora Casterad M (2005) Landsat monitoring of playa-lakes in the Spanish monegros desert. J Arid Environ 63:497–516

    Article  Google Scholar 

  • Cherry JA (2011) Ecology of wetland ecosystems: water, substrate, and life. Nature Educ Knowl 3(10):16

    Google Scholar 

  • Cowling RM, Pressey RL, Sims-Castley R, le Roux A, Baard E, Burgers CJ, Palmer G (2003) The expert or the algorithm?ecomparison of priority conservation areas in the Cape Floristic region identified by park managers and reserve selection software. Biol Conserv 112:147–167

    Article  Google Scholar 

  • Csavina J, Field J, Félix O, Corral-Avitia AY, Sáez AE, Betterton EA (2014) Effect of wind speed and relative humidity on atmospheric dust concentrations in semi-arid climates. Sci Total Environ 487:82–90

    Article  CAS  Google Scholar 

  • Dong Z, Wang Z, Liu D, Li L, Ren C, Tang X, Jia M, Liu C (2013) Assessment of habitat suitability for waterbirds in the West Songnen Plain. Ecol Eng 55:94–100

    Article  Google Scholar 

  • Duflot R, Avon C, Roche P, Bergès L (2018) Combining habitat suitability models and spatial graphs for more effective landscape conservation planning: an applied methodological framework and a species case study. J Nat Conserv 46:38–47

    Article  Google Scholar 

  • Fennessy MS, Wardrop D (2016) Approaches to assessing the ecological condition of wetlands using soil indicators. In: Wetland soils: genesis, hydrology, landscapes, and classification, 2nd edn, pp 425–445. CRC Press‏

  • Frankenberg C, Berry J (2018) Reference module in earth systems and environmental sciences: comprehensive remote sensing‏

  • Ginoux P, Prospero JM, Gill TE, Hsu NC, Zhao P (2012) Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products. Rev Geophys 50:1–26

    Article  Google Scholar 

  • Hamidi M (2020) The key role of water resources management in the Middle East dust events. CATENA 187:104337

    Article  Google Scholar 

  • Holzmuell E, Gaskins M, Mangun J (2011) A GIS approach to prioritizing habitat for restoration using neotropical migrant songbird criteria. Environ Manage 48:150157

    Google Scholar 

  • Laukkonen J, Blanco PK, Lenhart J, Keiner M, Cavric B, Kinuthia-Njenga C (2009) Combining climate change adaptation and adaptation measures at the local level. Habitat Int 33(3):287–292

    Article  Google Scholar 

  • Li X, Li W, Zhao ZK, Luo JC (2005) Wetland restoration habitat rehabitartion and their ecological consquences on wetland habitats. Res Sci 27:112–117

    Google Scholar 

  • Li X, Li C, Zhang L (2010) Modeling the scenarios of wetland restoration in hengshui lake national nature reserve. Procedia Environ Sci 2:1279–1289

    Article  Google Scholar 

  • Lu K, Wu H, Guan Q, Lu X (2021) Aquatic invertebrate assemblages as potential indicators of restoration conditions in wetlands of Northeastern China. Restor Ecol 29(1):e13283

    Article  Google Scholar 

  • Lustig A, Stouffer DB, Doscher C, Worner SP (2017) Landscape metrics as a framework to measure the effect of landscape structure on the spread of invasive insect species. Landsc Ecol 32(12):2311–2325

    Article  Google Scholar 

  • Ma Z, Cai Y, Li B, Chen J (2010) Managing wetland habitats for waterbirds: an international perspective. Wetlands 30(1):15–27

    Article  CAS  Google Scholar 

  • MacLean MG, Congalton RGA (2015) Comparison of landscape fragmentation analysis programs for identifying possible invasive plant species locations in forest edge. Landsc Ecol 30:1241–1256

    Article  Google Scholar 

  • Maleki S, Soffianian AR, Soltani-Koupaei S, Saatchi S, Pourmanafi S, Sheikholeslam F (2016) Habitat map** as a tool for water birds’ conservation planning in an arid zone wetland: the case study Hamoun wetland. Ecol Eng 95:594–603

    Article  Google Scholar 

  • Maleki S, Soffianian AR, Koupaei SS, Pourmanafi S, Saatchi S (2018) Wetland restoration prioritizing, a tool to reduce negative effects of drought; an application of multicriteria-spatial decision support system. Ecol Eng 112:132–139

    Article  Google Scholar 

  • Maleki S, Koupaei SS, Soffianian A, Saatchi S, Pourmanafi S, Rahdari V (2019) Human and climate effects on the Hamoun wetlands. Weather Climate, Soc 11(3):609–622

    Article  Google Scholar 

  • Maleki S, Baghdadi N, Rahdari V (2020) Which water bird groups need greater habitat conservation measures in a wetland ecosystem? Ecol Eng 143:105677

    Article  Google Scholar 

  • Marti-Cardona B, Lopez-Martinez C, Dolz-Ripolles J, Bladè-Castellet E (2010) ASAR polarimetric, multi-incidence angle and multitemporal characterization of Doñana wetlands for flood extent monitoring. Remote Sens Environ 114:2802–2815. https://doi.org/10.1016/j.rse.2010.06.015

    Article  Google Scholar 

  • Martin EA, Dainese M, Clough Y, Báldi A, Bommarco R, Gagic V et al (2019) The interplay of landscape composition and configuration: new pathways to manage functional biodiversity and agroecosystem services across Europe. Ecol Lett 22(7):1083–1094

    Article  Google Scholar 

  • McAllister L, Peniston B, Leibowitz S, Abbruzzese B, Hyman J (2013) A synoptic assessment for prioritizing wetland restoration efforts to optimize flood attenuation. Wetlands 20:70–83

    Article  Google Scholar 

  • McCauley S, Goetz SJ (2004) Map** residential density patterns using multi-temporal Landsat imagery and a decision-tree classifier. Int J Remote Sens 25(6):1077–1094

    Article  Google Scholar 

  • McGarigal K, Cushman SA, Ene E (2012) FRAGSTATS v42.1: Spatial pattern analysis program for categorical and continuous maps, Computer software program produced by the authors at the University of Massachusetts, Amherst. Retrieved from: http://www.umass.edu/landeco/research/fragstats/fragstats.html

  • Middleton N (2019) Variability and trends in dust storm frequency on decadal timescales: climatic drivers and human impacts. Geosciences 9(6):261

    Article  Google Scholar 

  • Minckley TA, Turner DS, Weinstein SR (2013) The relevance of wetland conservation in arid regions: a re-examination of vanishing communities in the American Southwest. J Arid Environ 88:213–221

    Article  Google Scholar 

  • Miri A, Hasan A, Ekhtesasi MR, Panjehkeh N, Ghanbari A (2009) Environmental and socio-economic impacts of dust storms in Sistan Region, Iran. Int J Environ Stud 66(3):343–355

    Article  Google Scholar 

  • Mitchell GEM, Bennett EM, Andrew G (2013) Linking landscape connectivity and ecosystem service provision: current knowledge and research gaps. Ecosystems 16:894–908

    Article  Google Scholar 

  • Morandeira N, Grings F, Facchinetti C, Kandus P (2016) Map** plant functional types in floodplain wetlands: an analysis of C-band Polarimetric SAR Data from RADARSAT-2. Remote Sens 8:2–17

    Article  Google Scholar 

  • Naghibi SA, Moghaddam DD, Kalantar B, Pradhan B, Kisi O (2017) A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential map**. J Hydrol 548:471–483

    Article  Google Scholar 

  • Niu L, Guo Y, Li Y, Wang C, Hu Q, Fan L et al (2021) Degradation of river ecological quality in Tibet plateau with overgrazing: a quantitative assessment using biotic integrity index improved by random forest. Ecol Indic 120:106948

    Article  Google Scholar 

  • Partow H (2003) Sistan Oasis parched by drought. Atlas of Global Change. Oxford University Press, Oxford, pp 144–145

    Google Scholar 

  • Phillips SJ, Dudik M (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31:161–175

    Article  Google Scholar 

  • Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Mod 190(3–4):231–259

    Article  Google Scholar 

  • Qiu M, Zuo Q, Wu Q, Yang Z, Zhang J (2022) Water ecological security assessment and spatial autocorrelation analysis of prefectural regions involved in the Yellow River Basin. Sci Rep 12:5105

    Article  CAS  Google Scholar 

  • Rahimian Boogar A, Salehi H, Pourghasemi HR, Blaschke T (2019) Predicting habitat suitability and conserving Juniperus spp. habitat using SVM and maximum entropy machine learning techniques. Water 11(10):2049

    Article  Google Scholar 

  • Ramsar (2016) The List of Wetlands of International Importance 54

  • Rashki A, Kaskaoutis DG, Goudie AS, Kahn RA (2013) Dryness of ephemeral lakes and consequences for dust activity: the case of the Hamoun drainage basin, southeastern Iran. Sci Total Environ 463:552–564

    Article  Google Scholar 

  • Sabo JL, Sponseller R, Dixon M, Gade K, Harms T, Heffernan J, Jani A, Katz G, Soykan C, Watts J, Welter J (2005) Riparian zones increase regional species richness by harboring different, not more, species. Ecology 86:56–62

    Article  Google Scholar 

  • Schrandt MN, MacDonald TC, Sherwood ET, Beck MW (2021) A multimetric nekton index for monitoring, managing and communicating ecosystem health status in an urbanized Gulf of Mexico estuary. Ecol Ind 123:107310

    Article  Google Scholar 

  • Shahraiyni HT, Karimi K, Nokhandan MH, Moghadas NH (2015) Monitoring of dust storm and estimation of aerosol concentration in the middle east using remotely sensed images. Arab J Geosci 8(4):2095–2110

    Article  Google Scholar 

  • Shahriar A, Mozaffari GA, Poudineh S (2018) The impact of drought periods and wind erosion on the physical development of desert cities (case study: Zabol-Iran). Desert 23(2):199–209

    Google Scholar 

  • Shamohammadi Z, Maleki S (2011) Iranian student book agency. Tehran, Iran, pp 52–83

  • Smiraglia D, Ceccarelli T, Bajocco S, Perini L, Salvati L (2015) Unraveling landscape complexity: land use/land cover changes and landscape pattern dynamics (1954–2008) in contrasting Peri- urban and agro- forest regions of Northern Italy. Environ Manage 56:916–932

    Article  CAS  Google Scholar 

  • Taft O, Colwell M, Isola C, Safran R (2002) Waterbird responses to experimental drawdown: implications for multispecies management of wetland mosaics. J Appl Ecol 39:987–1001

    Article  Google Scholar 

  • Tolessa T, Senbeta F, Kidane M (2016) Landscape composition and configuration in the central highlands of Ethiopia. Ecol Evol 6(20):7409–7421

    Article  Google Scholar 

  • Torshizi MR, Miri A, Davidson-Arnott R (2020) Sheltering effect of a multiple-row Tamarix windbreak–a field study in Niatak, Iran. Agric for Meteorol 287:107937

    Article  Google Scholar 

  • Turner MG, Simard M (2017) Using spatial statistics and landscape metrics to compare disturbance mosaics. In: Learning landscape ecology, pp 175–190. Springer, New York, NY.

  • UNEP (2014) Hamoun wetlands: current situation and the way forward. United Nations Environment Programme; Nairobi, Kenya. Information Sheet dated March 20, 2014; 5.

  • UNESCO (2016) http://www.unesco.org/new/en/natural-sciences/environment/ecological-sciences/biosphere-reserves/asia-and-the-pacific/islamic-republic-of-iran/hamoun/

  • Vale CG, Brito JC (2015) Desert-adapted species are vulnerable to climate change: insights from the warmest region on Earth. Global Ecol Conserv 4:369–379

    Article  Google Scholar 

  • Walters D, Kotze DC, Rebelo A, Pretorius L, Job N, Lagesse JV et al (2021) Validation of a rapid wetland ecosystem services assessment technique using the Delphi method. Ecol Ind 125:107511

    Article  Google Scholar 

  • Whyte A, Ferentinos KP, Petropoulos GP (2018) A new synergistic approach for monitoring wetlands using Sentinels-1 and 2 data with object-based machine learning algorithms. Environ Model Softw 104:40–54

    Article  Google Scholar 

  • Yang W, Li X, Sun T, Pei J, Li M (2017) Macrobenthos functional groups as indicators of ecological restoration in the northern part of China’s Yellow River Delta wetlands. Ecol Ind 82:381–391

    Article  Google Scholar 

  • Yun J, Liu H, Xu Z, Cao X, Ma L, Wen L et al (2022) Assessing changes in the landscape pattern of wetlands and its impact on the value of wetland ecosystem services in the Yellow River Basin, Inner Mongolia. Sustainability 14(10):6328

    Article  Google Scholar 

  • Zhu Q, Peng C, Liu J, Jiang H, Fang X, Chen H et al (2016) Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades. Sci Rep 6(1):1–7

    Google Scholar 

Download references

Acknowledgements

This research was supported by the University of Zabol, under Grant UOZ-GR-1348 and UOZ-GR-4211.

Funding

This research was supported by the University of Zabol, under Grant UOZ-GR-1348 and UOZ-GR-4211.

Author information

Authors and Affiliations

  1. Faculty of Agriculture, University of Zabol, Zabol, Iran

    M. Mir

  2. Department of Environment, Faculty of Natural Resources, University of Zabol, Zabol, Iran

    S. Maleki & V. Rahdari

Authors
  1. M. Mir
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Maleki
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V. Rahdari
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SM and VR performed the field study. MM and SM analyzed the data. MM, SM and VR contributed to interpretation of results and writing the manuscript.

Corresponding author

Correspondence to S. Maleki.

Ethics declarations

Conflict of interest

Authors confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. Authors further confirm that the order of authors listed in the manuscript has been approved by all of them and there is not conflict between authors.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Additional information

Editorial responsibility: Samareh Mirkia.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mir, M., Maleki, S. & Rahdari, V. Ecosystem restoration and degradation monitoring using ecological indices. Int. J. Environ. Sci. Technol. 20, 1713–1724 (2023). https://doi.org/10.1007/s13762-022-04694-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13762-022-04694-8

Keywords

Search

Navigation