Small-scale patterns of species richness in Swedish semi-natural grasslands: the effects of community species pools

Franzén, Daniel; Eriksson, Ove

doi:10.1034/j.1600-0587.2001.d01-206.x

Cited by 17 publications

(13 citation statements)

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“…Recruitment in this system is probably explained by stochasticity in recruitment success, as suggested for other grassland ecosystems (van der Maarel & Sykes 1993; Franzen & Eriksson 2001), where an occasional recruitment event can sustain population size over long periods (Warner & Chesson 1985). Accordingly, in the longleaf pine‐wiregrass ecosystem, site moisture conditions suitable for establishment (as opposed to space limitations) and the available seed pools are feasible factors limiting recruitment (Zobel 1992, 1997; Franzen & Eriksson 2001). Seed pool composition, in turn, is controlled by dispersal distances, seed production rates, fragmentation of the surrounding landscape, and seed longevity in the soil (Gross 1987; Eriksson & Ehrlen 1992).…”

Section: Discussionmentioning

confidence: 65%

“…In relatively undisturbed ground‐cover sites subjected to frequent fire, soil moisture appears to be an important factor regulating the number of species present across the xeric‐mesic landscape. In contrast to many temperate grasslands (Abrams & Hulbert 1987; Gibson & Hulbert 1987; Franzen & Eriksson 2001), there is little/no evidence for competitive exclusion as a factor regulating species richness in the ground cover of longleaf pine‐wiregrass forests (Kirkman et al . 2001).…”

Section: Discussionmentioning

confidence: 99%

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Ground cover recovery patterns and life‐history traits: implications for restoration obstacles and opportunities in a species‐rich savanna

et al. 2004

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Summary 1We identified species with low re-colonization potential, which could be used as indicators of recovery of species-rich pine savannas, by comparing the ground-cover flora of a 64-year-old slash pine plantation (recovery site) with that of a nearby natural longleaf pine savanna (reference site). We also determined life-history traits that were useful predictors of recolonization potential. 2 The high floristic overlap in species between reference and recovery sites and similar species richness at scales ≥ 10 m 2 suggests that substantial vegetation recovery occurred over the 65-year period. However, for areas < 10 m 2 the lower species packing in the recovery sites indicates that coexistence of a high number of species at small scales is dependent on local dispersal and establishment, and may take much longer to achieve. 3 The absence, or near absence, of some species from the recovery site, even after 65 years, suggests that some species may be particularly vulnerable to disturbance and may re-establish infrequently, if ever. Several dispersal distance-restricted species were identified that require active reintroduction. While no particular guild of species was a strong indicator of recovery in this study, we identified a group of species that assess the absence of or the degree of recovery from, prior soil disturbance. 4 Local dispersal appears to be an important factor structuring species richness patterns in pine savannas. Limitations of dispersal distance in some species, particularly those with gravity and ant-dispersal mechanisms, represent an obstacle to passive restoration that can only be overcome either by introduction of propagules in the restoration process or by allowing for longer periods of recruitment. 5 This study demonstrates a method for identifying a suite of species that may be unsuccessful at recolonization. The method would be applicable to numerous degraded ecosystems, particularly similar species-rich savannas, grasslands and forests.

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Section: Discussionmentioning

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Ground cover recovery patterns and life‐history traits: implications for restoration obstacles and opportunities in a species‐rich savanna

et al. 2004

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“…Our protocol was different, since the botanical survey was conducted at the grassland scale by a random walk strategy, and only one biodiversity index was computed from it. Yet, grasslands are characterized by patterns of small scale species composition and spatial distribution [47][48][49]. Hence, this estimation of the biodiversity at the grassland level may be difficult to relate to remote sensing data and might have limited our analysis.…”

Section: Limitationsmentioning

confidence: 99%

Spectro-Temporal Heterogeneity Measures from Dense High Spatial Resolution Satellite Image Time Series: Application to Grassland Species Diversity Estimation

et al. 2017

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Grasslands represent a significant source of biodiversity that is important to monitor over large extents. The Spectral Variation Hypothesis (SVH) assumes that the Spectral Heterogeneity (SH) measured from remote sensing data can be used as a proxy for species diversity. Here, we argue the hypothesis that the grassland's species differ in their phenology and, hence, that the temporal variations can be used in addition to the spectral variations. The purpose of this study is to attempt verifying the SVH in grasslands using the temporal information provided by dense Satellite Image Time Series (SITS) with a high spatial resolution. Our method to assess the spectro-temporal heterogeneity is based on a clustering of grasslands using a robust technique for high dimensional data. We propose new SH measures derived from this clustering and computed at the grassland level. We compare them to the Mean Distance to Centroid (MDC). The method is experimented on 192 grasslands from southwest France using an intra-annual multispectral SPOT5 SITS comprising 18 images and using single images from this SITS. The combination of two of the proposed SH measures-the within-class variability and the entropy-in a multivariate linear model explained the variance of the grasslands' Shannon index more than the MDC. However, there were no significant differences between the predicted values issued from the best models using multitemporal and monotemporal imagery. We conclude that multitemporal data at a spatial resolution of 10 m do not contribute to estimating the species diversity. The temporal variations may be more related to the effect of management practices.

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“…Although the paired spectral and vegetation plots belong to the same grassland age categories, and there is no variation in grazing intensity between the spectral plot and its corresponding vegetation plot, we cannot exclude the possibility that the relationship may have been influenced by environmental conditions in the 2 m zone surrounding the vegetation plots. However, species diversity levels at different spatial scales often show a positive relationship within semi-natural grasslands (e.g., [66,67]). For example, within Swedish semi-natural grassland the species diversity at the 1 dmˆ1 dm scale was explained by the size of the species pool at the 2 mˆ2 m scale [66].…”

Section: Limitationsmentioning

confidence: 99%

“…However, species diversity levels at different spatial scales often show a positive relationship within semi-natural grasslands (e.g., [66,67]). For example, within Swedish semi-natural grassland the species diversity at the 1 dmˆ1 dm scale was explained by the size of the species pool at the 2 mˆ2 m scale [66].…”

Section: Limitationsmentioning

confidence: 99%

Airborne Hyperspectral Data Predict Fine-Scale Plant Species Diversity in Grazed Dry Grasslands

et al. 2016

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Semi-natural grasslands with grazing management are characterized by high fine-scale species richness and have a high conservation value. The fact that fine-scale surveys of grassland plant communities are time-consuming may limit the spatial extent of ground-based diversity surveys. Remote sensing tools have the potential to support field-based sampling and, if remote sensing data are able to identify grassland sites that are likely to support relatively higher or lower levels of species diversity, then field sampling efforts could be directed towards sites that are of potential conservation interest. In the present study, we examined whether aerial hyperspectral (414-2501 nm) remote sensing can be used to predict fine-scale plant species diversity (characterized as species richness and Simpson's diversity) in dry grazed grasslands. Vascular plant species were recorded within 104 (4 mˆ4 m) plots on the island of Öland (Sweden) and each plot was characterized by a 245-waveband hyperspectral data set. We used two different modeling approaches to evaluate the ability of the airborne spectral measurements to predict within-plot species diversity: (1) a spectral response approach, based on reflectance information from (i) all wavebands, and (ii) a subset of wavebands, analyzed with a partial least squares regression model, and (2) a spectral heterogeneity approach, based on the mean distance to the spectral centroid in an ordinary least squares regression model. Species diversity was successfully predicted by the spectral response approach (with an error of ca. 20%) but not by the spectral heterogeneity approach. When using the spectral response approach, iterative selection of important wavebands for the prediction of the diversity measures simplified the model but did not improve its predictive quality (prediction error). Wavebands sensitive to plant pigment content (400-700 nm) and to vegetation structural properties, such as above-ground biomass (700-1300 nm), were identified as being the most important predictors of plant species diversity. We conclude that hyperspectral remote sensing technology is able to identify fine-scale variation in grassland diversity and has a potential use as a tool in surveys of grassland plant diversity.

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Small-scale patterns of species richness in Swedish semi-natural grasslands: the effects of community species pools

Cited by 17 publications

References 0 publications

Ground cover recovery patterns and life‐history traits: implications for restoration obstacles and opportunities in a species‐rich savanna

Ground cover recovery patterns and life‐history traits: implications for restoration obstacles and opportunities in a species‐rich savanna

Spectro-Temporal Heterogeneity Measures from Dense High Spatial Resolution Satellite Image Time Series: Application to Grassland Species Diversity Estimation

Airborne Hyperspectral Data Predict Fine-Scale Plant Species Diversity in Grazed Dry Grasslands

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