Modelling the ecosystem indicators of British Columbia using Earth observation data and terrain indices

Fitterer, Jessica L.; Nelson, Trisalyn A.; Coops, Nicholas C.; Wulder, Michael A.

doi:10.1016/j.ecolind.2012.02.024

Cited by 29 publications

(23 citation statements)

References 51 publications

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“…This is the reason why the TWI derived from DEMs is commonly used and regarded as one of the most important secondary topographic attributes [28,47,48]. In the present paper, we have confirmed that the TWI, particularly the sum values, is significantly positively correlated with the proportion of species that require higher light, humidity, and humus content.…”

Section: Discussionsupporting

confidence: 77%

“…In general the correlation coefficients obtained were much higher for the left than the right river bank. Solar radiation (SRAD), which affects the microclimatic conditions and influences the growth activity of plants in the study river valley, was also recognized as a very important secondary topographic attribute [48,49]. In our study, we have confirmed that the mean and sum SRAD values are significantly correlated with the share of plant species with higher light, humidity, and organic matter content requirements, particularly on the left bank of the river.…”

Section: Discussionsupporting

confidence: 74%

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Assessment of flora diversity in a minor river valley using ecological indicator values, Geographical Information Systems and Digital Elevation Models

Czarnecka

Chabudziński

2013

Open Life Sciences

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Abstract:Ellenberg indicator values (EIV) have been widely used to estimate habitat variables from floristic data and to predict vegetation compositionbasedonhabitatproperties.GeographicalInformationSystems(GIS)andDigitalElevationModels(DEM)arevaluable toolsforstudyingtherelationshipsbetweentopographicandecologicalcharactersofriversystems.A3-meterresolutionDEMwas derived for a.3-km-longbreaksectionoftheSzumRiver(SEPoland)froma1:10,000topographicmap.Dataonthediversityand ecological requirements of the local vascular flora were obtained while making floristic charts for 32 sections of the river valley (each200 mlong)andphysicalandchemicalsoilmeasurements;next,thedataweretranslatedintoEIV.Thecorrelationsofthe primaryandsecondarytopographicattributesofthevalley,speciesrichness,andEIV(adaptedforthePolishvascularflora)were assessedforallspeciesrecognizedineachvalleysection.Thetotalareaandproportionofaflatarea,meanslope,slopecurvature, solar radiation (SRAD), and topographic wetness index (TWI) are the most important factors influencing local flora richness and diversity.Thehighestcorrelationswerefoundforthreeecologicalindicators,namelylight,soilmoisture,andsoilorganiccontent. TheDEMseemstobeusefulindeterminationofcorrelationsbetweentopographicandecologicalattributesalongaminorrivervalley.©VersitaSp.zo.o.

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Section: Discussionsupporting

confidence: 77%

Section: Discussionsupporting

confidence: 74%

Assessment of flora diversity in a minor river valley using ecological indicator values, Geographical Information Systems and Digital Elevation Models

Czarnecka

Chabudziński

2013

Open Life Sciences

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“…This secondary topographic attribute is highly variable from place to place due to changing slope and aspect [17,18,44]. In the present study, the decisive condition shaping the energy amounts delivered for both riverbanks was the almost parallel course of the valley in a greater part of the analyzed fragment.…”

Section: Discussionmentioning

confidence: 57%

“…Elevation gradients (denivelations) determine soil variables, species distribution, vegetation production levels, and patterns of disturbance [3,17,18,42,43]. Surprisingly, the denivelation of the Sopot river valley (incision into the substratum: mean = 20 m, max = 27 m) does not alone influence significantly the species richness but shapes the values of all ecological indicators for ground-floor vegetation: L, W, Tr, R, D and H, particularly for the more "sunny" right bank.…”

Section: Discussionmentioning

confidence: 99%

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How a river course influences the species richness and ecological requirements on two opposite riverbanks in a forest area

2015

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The goal of the present research was to find correlations between the topographic attributes of a river valley and local ground-floor vegetation and its habitat requirements expressed by ecological indicator values (EIV), using the geographical information systems (GIS), digital elevation model (DEM), and multivariate statistical analysis. We paid special attention to the river course, which determines the differentiation in slope aspects and the amount of solar radiation reaching the ground surface. The model object was an almost latitudinal, ca. 4-km-long break section of the Sopot river, crossing the escarpment zone of the Central Roztocze Highlands, southeastern Poland. The main material comprised species lists (with estimated abundance) for each ca. 200-m-long section, according to the river valley course, separately for the left and right riverbanks, 40 sections altogether, ca. 15 000 vegetation records, and physical and chemical soil measurements. A 3-meter resolution DEM was derived from a 1:10 000 topographic map. We calculated the correlations between the topographic attributes of the valley, species richness, and the EIVs for all the species recognized in each section of the valley. We found 241 herb plant species in the ground-floor vegetation of the study area. We did not find significant differences between the two riversides (61 ±13 species per one section for the left and 63 ±17 for the right side). Thus, the parallel course of the river valley does not change the species richness on a more "sunny" and more "shiny" riverbank. However, this factor "cooperating" with other topographic attributes of the valley significantly differentiates the shape of species showing various requirements for basic habitat resources: light, moisture, soil trophy, reaction, dispersion, and organic-matter content.

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Will remote sensing shape the next generation of species distribution models?

Bradley

Cord

et al. 2015

Remote Sens Ecol Conserv

288

239

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Two prominent limitations of species distribution models (SDMs) are spatial biases in existing occurrence data and a lack of spatially explicit predictor variables to fully capture habitat characteristics of species. Can existing and emerging remote sensing technologies meet these challenges and improve future SDMs? We believe so. Novel products derived from multispectral and hyperspectral sensors, as well as future Light Detection and Ranging (LiDAR) and RADAR missions, may play a key role in improving model performance. In this perspective piece, we demonstrate how modern sensors onboard satellites, planes and unmanned aerial vehicles are revolutionizing the way we can detect and monitor both plant and animal species in terrestrial and aquatic ecosystems as well as allowing the emergence of novel predictor variables appropriate for species distribution modeling. We hope this interdisciplinary perspective will motivate ecologists, remote sensing experts and modelers to work together for developing a more refined SDM framework in the near future.

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Modelling the ecosystem indicators of British Columbia using Earth observation data and terrain indices

Cited by 29 publications

References 51 publications

Assessment of flora diversity in a minor river valley using ecological indicator values, Geographical Information Systems and Digital Elevation Models

Assessment of flora diversity in a minor river valley using ecological indicator values, Geographical Information Systems and Digital Elevation Models

How a river course influences the species richness and ecological requirements on two opposite riverbanks in a forest area

Will remote sensing shape the next generation of species distribution models?

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