Skip to main content

Advertisement

SpringerLink
Log in

Mapping species density of trees, shrubs and vines in a tropical forest, using field measurements, satellite multiespectral imagery and spatial interpolation

  • Original Paper
  • Published:
Biodiversity and Conservation Aims and scope Submit manuscript

Abstract

We estimated the number of species in a tropical forest landscape in Quintana Roo, Mexico, based on the relationship between reflectance values of satellite imagery and field measurements of plant species density (mean number of species per plot). Total species density as well as that of tree, shrub and vine species were identified from 141 sampling quadrats (16543 individuals sampled). Spatial prediction of plant diversity was performed using universal kriging. This approach considered the linear relationship between plant species density and reflectance values of Thematic Mapper™, as well as the spatial dependence of the observations. We explored the linear relationships between spectral properties of TM bands and the species density of trees, shrubs and vines, using regression analysis. We employed Akaike Information Criterion (AIC) to select a set of candidate models. Based on Akaike weights, we calculated model-averaged parameters. Linear regression between number of species and reflectance values of TM bands yielded regression residuals. We used variogram analysis to analyze the spatial structure of these residuals. Results show that accounting for spatial autocorrelation in the residual variation improved model R2 from 0.57 to 0.66 for number of all species, from 0.58 to 0.65 for number of tree species, from 0.26 to 0.41 for number of shrub species and from 0.13 to 0.17 for species density of vines. The empirical models we developed can be used to predict landscape-level species density in the Yucatan Peninsula, helping to guide and evaluate management and conservation strategies.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Anderson DR, Burnham KP, Thompson WL (2000) Null hypothesis testing: problems, prevalence, and an alternative. J Wildlife Manage 64(4):912–923

    Article  Google Scholar 

  • Anderson DR, Burnham KP (2002) Avoiding pitfalls when using information-theoretic methods. J Wildlife Manage 66(3):912–918

    Article  Google Scholar 

  • Austin MP (2002) Spatial prediction of species distribution: an interface between ecological theory and statistical modeling. Ecol Model 157:101–118

    Article  Google Scholar 

  • Borrough PA, McDonnell RA (1998) Principles of geographical information systems. Spatial information systems and geostatistics. Oxford University Press

  • Burnham KP, Anderson DR (1998) Model selection and inference: a practical information-theoretic approach. Springer-Verlag, New York

    Google Scholar 

  • Cabrera CE, Souza SM, Tellez VO (1982) Imagenes de la flora Quintanaroense. Centro de Investigaciones de Quintana Roo, Mexico

    Google Scholar 

  • Campbell JB (1987) Introduction to remote sensing. The Guilford Press, New York

    Google Scholar 

  • Carroll SS (1998) Modeling abiotic indicators when obtaining spatial predictions of species richness. Environ Ecol Stat 5:257–276

    Article  Google Scholar 

  • Clark DB, Palmer MW, Clark DA (1999) Edaphic factors and the landscape-scale distributions of tropical rain forest trees. Ecology 80(8):2662–2675

    Google Scholar 

  • Earth Resource Mapping Ltd (1998) ER mapper 6.1. User guide, San Diego CA

    Google Scholar 

  • Fairbanks HK, McGwire KC (2004) Patterns of floristic richness in vegetation communities of California: regional scale analysis with multi-temporal NDVI. Global Ecol Biogeogr 13:221–235

    Article  Google Scholar 

  • FAO (2001) Global Forest Resource Assessment 2000–Main Report. FAO Forestry Paper 140. FAO. Rome, Italy

  • French K (1999) Spatial variability in species composition in birds and insects. J Insect Conserv 3:183–189

    Article  Google Scholar 

  • Fuller RM, Groom GB, Mugisha S, Ipulet P, Pomeroy D, Katende A, Bailey R, Ogutu-Ohwayo R (1997) The integration of field survey and remote sensing for biodiversity assessment: a case study in the tropical forest and wetlands of Sango Bay, Uganda. Biol Conserv 86:379–391

    Article  Google Scholar 

  • Gaston KJ (2000) Global patterns in biodiversity. Nature 405:220–227

    Article  PubMed  CAS  Google Scholar 

  • Guariguata MR (1990) Landslide disturbances and forest regeneration in upper Luquillo Mountains of Puerto Rico. J Ecol 78:814–832

    Article  Google Scholar 

  • Gould W (2000) Remote sensing of vegetation, plant species richness, and regional biodiversity hotspots. Ecol Appl 10:1861–1870

    Article  Google Scholar 

  • Hernández-Stefanoni JL, Ponce-Hernandez R (2004) Mapping the spatial distribution of plant diversity indices using multi-spectral satellite image classification and field measurements. Biodivers Conserv 13:2599–2621

    Article  Google Scholar 

  • Hernandez-Stefanoni JL (2005) Relationships between landscape patterns and species richness of trees, shrubs and vines in a tropical forest. Plant Ecol 179:53–55

    Article  Google Scholar 

  • Hernández-Stefanoni JL, Ponce-Hernandez R (2006) Mapping the spatial variability of plant diversity in a tropical forest: comparison of spatial interpolation methods. Environ Monit Assess 117:307–334

    Article  PubMed  Google Scholar 

  • Hernández-Stefanoni JL, Bello-Pineda J, Valdes-Valadez G (2006) Comparing the use of indigenous knowledge with classification and ordination techniques for assessing the species composition and structure of vegetation in a tropical forest. Environ Manage 37(5):686–702

    Article  PubMed  Google Scholar 

  • Isaaks EH, Srivastava RM (1989) An introduction to applied geostatistics. Oxford University press, New York

    Google Scholar 

  • Isik K, Yaltikik F, Akesen A (1997) The interrelationship of forests, biological diversity and the maintenance of natural resources. Unasylva FAO 48:190–191

    Google Scholar 

  • Johnson JB, Omland KS (2004) Model selection in ecology and evolution. Trends Ecol Evol 19(2):101–108

    Article  PubMed  Google Scholar 

  • Jensen JR (2000) Remote sensing of environment: an earth resource perspective. Prentice Hall, New Jersey, 544 pp

    Google Scholar 

  • Kerr JT, Southowood TRE, Chilar J (2001) Remotely sensing habitat diversity predicts butterfly species richness and community similarity in Canada. Proc Nat Acad Sci USA 98:11365–11370

    Article  PubMed  CAS  Google Scholar 

  • Kitanidis PK (2000) Introduction to Geoestatistics. Applications in hydrogeology. Cambrige University Press

  • Moreno CE, Halffter G (2001) Spatial and temporal analysis of a, b, and g diversities of bats in a fragmented landscape. Biodivers Conserv 10:367–382

    Article  Google Scholar 

  • Muldavin EH, Neville P, Harpper G (2001) Indices of grassland biodiversity in the Chihuahuan desert ecoregion derived from remote sensing. Conserv Biol 15:844–855

    Article  Google Scholar 

  • Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 43(24):853–858

    Article  CAS  Google Scholar 

  • Nagendra H, Gadgil M (1999) Satellite imagery as a tool for monitoring species diversity: an assessment. J Appl Ecol 36:388–397

    Google Scholar 

  • National Aeronautics and Space Administration (1998) Landsat 7 science data users handbook Greenbelt, Maryland, Goddard Space Flight Center, electronic version http://ltpwww.gsfc.nasa.gov/IAS/handbook/handbook_toc.html

  • Oindo BO, Skidmore AK (2002) Interannual variability of NDVI and species richness in Kenya. Int J Remote Sens 23:1195–1198

    Article  Google Scholar 

  • O’Neill RJ, Krummel JR, Gardner RH, Sugihara G, Jackson B, Deangelis DL, Milne BT, Turner MG, Zygmunt B, Christensen SW, Dale VH, Graham RL (1988) Indices of landscape pattern. Landscape Ecol 1:153–162

    Article  Google Scholar 

  • Palmer MW, Clark DB, Clark DA (2000) Is the number of tree species en small tropical forest plots nonramdom? Community Ecol 1(1):95–101

    Article  Google Scholar 

  • Pfeffer K, Pebesma EJ, Burrough PA (2003) Mapping alpine Vegetation using vegetation observations and topographic attributes. Landscape Ecol 18:759–776

    Google Scholar 

  • Pitkanen S (1998) The use of diversity indices to assess the diversity of vegetation in managed boreal forest. Forest Ecol Manage 112:121–137

    Article  Google Scholar 

  • Plotkin JB, Potts MD, Yu DW, Bunyavejchewin S, Condit R, Foster R, Hubbell S, LaFrankie J, Manokaran N, Lee HS, Sukumar R, Nowak MA, Ashton PS (2000) Predicting species diversity in tropical forests. Proc Nat Acad Sci 97(20):10850–10854

    Article  PubMed  CAS  Google Scholar 

  • Putz FE (1984) The natural history of lianas on Barro Colorado Island, Panama. Ecology 65:1713:1724

    Article  Google Scholar 

  • Robertson GP (2000) GS+: geostatistics for environmental science. Gamma Design Software. Plainwell, Michigan

    Google Scholar 

  • Rocchini D, Chiarucci A, Loiselle SA (2004) Testing the spectral variation hypothesis by uing satellite multispectral images. Acta Oecologica 26:117–120

    Article  Google Scholar 

  • Schnitzer SA, Bongers F (2002) The ecology of lianas and their role in forests. Trends Ecol Evol 17:223–230

    Article  Google Scholar 

  • Silbaugh JM, Betters DR (1995) Quantitative biodiversity measures applied to forest management. Environ Rev 3:277–285

    Google Scholar 

  • Tabachnick BG, Fidell LS (1996) Using multivariate statistics. Harper Collins College Publishers, New York

    Google Scholar 

  • Thenkabail PS, Enclona EA, Ashton MS, Legg C, De Dieu MJ (2004) Hyperion, IKONOS, ALI and ETM+ sensors in the study of African rainforest. Remote Sens Environ 90:23–43

    Article  Google Scholar 

  • Tuomisto H, Ruokolainen K, Aguilar M, Sarmiento A (2003) Floristic patterns along 43 km long in an Amazonian rain forest. J Ecol 91:743–756

    Article  Google Scholar 

  • Pitkanen S (1998) The use of diversity indices to assess the diversity of vegetation in managed boreal forest. Forest Ecol Manage 112:121–137

    Article  Google Scholar 

  • Turner W, Spector S, Gadirner N, Fladeland M, Sterinling E, Steiniger M (2003) Remote sensing for biodiversity science and conservation. Trends Ecol Evol 18:306–314

    Article  Google Scholar 

  • Vieira IMG, De Almeida AS, Davidson EA, Stone TA, Carvalh CJR, Guerrero JB (2003) Classifying successional forest using Landsat spectral properties and ecological characteristics in eastern Amazonia. Remote Sens Environ 87:470–481

    Article  Google Scholar 

  • Voltz M, Webster R (1990) A comparison of kriging, cubic splines and classification for predicting soil properties from sample information. J Soil Sci 41:473–490

    Article  Google Scholar 

  • Waide RB, Willig MR, Steiner CF Mittelbach G, Gough L, Dodson SI, Juday GP, Parmenter R (1999) The relationship between productivity and species richness. Ann Rev Ecol Sistematics 30:257–300

    Article  Google Scholar 

  • Wagner HH, Wildi O, Ewald KC (2000) Additive partitioning of plant species diversity in an agricultural mosaic landscape. Landscape Ecol 15:219–227

    Article  Google Scholar 

  • Waring R, Coops NC, Ohmann JL, Sarr DA (2002) Interpreting woody plant richness from seasonal ratios of photosynthesis. Ecology 83(11):2964–2970

    Article  Google Scholar 

  • Webster R, Oliver MA (2001) Geostatistics for environmental science. John Wiley and Sons, LTD, Toronto, Canada

    Google Scholar 

  • Whitmore TC (1997) Tropical forest disturbance, disappearance, and species loss. In: Laurance WF, Bierregaard ROJ (eds) Tropical forest remnants. The University of Chicago Press, Chicago, USA, pp 3–12

    Google Scholar 

  • Wilcox BA (1995) Tropical forest resources and biodiversity the risk of forest loss and degradation. Unasylva FAO. 46(181)

  • Witting L, Loeschcke V (1995) The optimization of biodiversity conservation. Biol Conserv 71:205–207

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centro de Investigación Científica de Yucatán A.C., Unidad de Recursos Naturales, Calle 43 # 130. Colonia Chuburná de Hidalgo, Mérida, Yucatán, C.P. 97200, México

    J. Luis Hernández-Stefanoni & Juan Manuel Dupuy

Authors
  1. J. Luis Hernández-Stefanoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juan Manuel Dupuy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. Luis Hernández-Stefanoni.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hernández-Stefanoni, J.L., Dupuy, J.M. Mapping species density of trees, shrubs and vines in a tropical forest, using field measurements, satellite multiespectral imagery and spatial interpolation. Biodivers Conserv 16, 3817–3833 (2007). https://doi.org/10.1007/s10531-007-9182-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10531-007-9182-6

Keywords

Search

Navigation