The Influence of Tilia tomentosa Moench on Plant Species Diversity and Composition in Mesophilic Forests of Western Romania–A Potential Tree Species for Warming Forests in Central Europe?

Climate change challenges important native timber species in Central Europe. The introduction of non-native tree species originating from warmer climates is one option to make Central European forests compatible to global warming. This, however, requires an assessment of the species’ growth requirements, and of its impact on biodiversity in its native ranges. Silver lime (Tilia tomentosa), a moderately drought-tolerant, thermophilous tree species of South-eastern Europe is considered suitable for the future. Along three elevational transects in western Romania, we assessed the impact of changing climate and local site conditions on the abundance of this tree species and contrasted plant species diversity and composition of lime-dominated forests with mesophytic oak and beech forests. Local site conditions and disturbance histories shaped the distribution pattern of silver lime. When dominant, it reduced plant species diversity within stands due to its dense canopy. For shade-tolerant, mesophytic species, though, lime forests provided an additional habitat and extended their range into warmer environments. Thus, silver lime may have the potential as an admixed tree species forming a transitory meso-thermophilous habitat in the future. At the same time, silver lime may be limited under increasing drought frequency.

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Investigating the Relationship between Tree Species Diversity and Landsat-8 Spectral Heterogeneity across Multiple Phenological Stages

Remote Sensing ◽

10.3390/rs13132467 ◽

2021 ◽

Vol 13 (13) ◽

pp. 2467

Author(s):

Sabelo Madonsela ◽

Moses A. Cho ◽

Abel Ramoelo ◽

Onisimo Mutanga

Keyword(s):

Species Diversity ◽

Plant Species ◽

Tree Species ◽

Diversity Indices ◽

Plant Species Diversity ◽

Landsat 8 ◽

Tree Species Diversity ◽

Phenological Stages ◽

Species Diversity Indices ◽

The Relationship

The emergence of the spectral variation hypothesis (SVH) has gained widespread attention in the remote sensing community as a method for deriving biodiversity information from remotely sensed data. SVH states that spectral heterogeneity on remotely sensed imagery reflects environmental heterogeneity, which in turn is associated with high species diversity and, therefore, could be useful for characterizing landscape biodiversity. However, the effect of phenology has received relatively less attention despite being an important variable influencing plant species spectral responses. The study investigated (i) the effect of phenology on the relationship between spectral heterogeneity and plant species diversity and (ii) explored spectral angle mapper (SAM), the coefficient of variation (CV) and their interaction effect in estimating species diversity. Stratified random sampling was adopted to survey all tree species with a diameter at breast height of > 10 cm in 90 × 90 m plots distributed throughout the study site. Tree species diversity was quantified by the Shannon diversity index (H′), Simpson index of diversity (D2) and species richness (S). SAM and CV were employed on Landsat-8 data to compute spectral heterogeneity. The study applied linear regression models to investigate the relationship between spectral heterogeneity metrics and species diversity indices across four phenological stages. The results showed that the end of the growing season was the most ideal phenological stage for estimating species diversity, following the SVH concept. During this period, SAM and species diversity indices (S, H′, D2) had an r2 of 0.14, 0.24, and 0.20, respectively, while CV had an r2 of 0.22, 0.22, and 0.25, respectively. The interaction of SAM and CV improved the relationship between the spectral data and H′ and D2 (from r2 of 0.24 and 0.25 to r2 of 0.32 and 0.28, respectively) at the end of the growing season. The two spectral heterogeneity metrics showed differential sensitivity to components of plant diversity. SAM had a high relationship with H′ followed by D2 and then a lower relationship with S throughout the different phenological stages. Meanwhile, CV had a higher relationship with D2 than other plant diversity indices and its relationship with S and H′ remained similar. Although the coefficient of determination was comparatively low, the relationship between spectral heterogeneity metrics and species diversity indices was statistically significant (p < 0.05) and this supports the assertion that SVH could be implemented to characterize plant species diversity. Importantly, the application of SVH should consider (i) the choice of spectral heterogeneity metric in line with the purpose of the SVH application since these metrics relate to components of species diversity differently and (ii) vegetation phenology, which affects the relationship that spectral heterogeneity has with plant species diversity.

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