Global endemics-area relationships of vascular plants

Hobohm, Carsten; Janišová, Monika; Steinbauer, Manuel J.; Landi, Sara; Field, Richard; Vanderplank, Sula E.; Beierkuhnlein, Carl; Grytnes, John‐Arvid; Vetaas, Ole R.; Fidelis, Alessandra; Nascimento, Lea de; Clark, Vincent Ralph; Fernández‐Palacios, José María; Franklin, Scott B.; Guarino, Riccardo; Huang, Jihong; Krestov, Pavel V.; Ma, Keping; Онипченко, В. Г.; Palmer, Michael W.; Simon, Marcelo F.; Stolz, Christian; Chiarucci, Alessandro

doi:10.1016/j.pecon.2019.04.002

Cited by 23 publications

(16 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…With regards to a potential validation with in-situ data, the uncertainty of wide-scale datasets hampers a spatial overlap. In this case, in-situ datasets meet all five major concerns recently raised by Hobohm et al (2019), i.e. : i) there is insufficient data coverage across Europe to make an unbiased comparison between predicted and actual distributions, ii) taxonomic standards differ across sampled regions, iii) there are generally different shapes of areas being sampled, iv) political borders often define sampling areas and aggregated sampling areas, and v) data are not aggregated in the same way in all areas.…”

Section: Discussionmentioning

confidence: 79%

From local spectral species to global spectral communities: a benchmark for ecosystem diversity estimate by remote sensing

Rocchini

Salvatori

Beierkuhnlein

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

In the light of unprecedented change in global biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential. Nevertheless, estimation of biodiversity using ecological field data can be difficult for several reasons. For instance, for very large areas, it is challenging to collect data that provide reliable information. Some of these restrictions in Earth observation can be avoided through the use of remote sensing approaches. Various studies have estimated biodiversity on the basis of the Spectral Variation Hypothesis (SVH). According to this hypothesis, spectral heterogeneity over the different pixel units of a spatial grid reflects a higher niche heterogeneity, allowing more organisms to coexist. Recently, the spectral species concept has been derived, following the consideration that spectral heterogeneity at a landscape scale corresponds to a combination of subspaces sharing a similar spectral signature. With the use of high resolution remote sensing data, on a local scale, these subspaces can be identified as separate spectral entities, the so called "spectral species". Our approach extends this concept over wide spatial extents and to a higher level of biological organization. We applied this method to MODIS imagery data across Europe. Obviously, in this case, a spectral species identified by MODIS is not associated to a single plant species in the field but rather to a species assemblage, habitat, or ecosystem. Based on such spectral information, we propose a straightforward method to derive alpha- (local relative abundance and richness of spectral species) and beta-diversity (turnover of spectral species) maps over wide geographical areas.

show abstract

Section: Discussionmentioning

confidence: 79%

From local spectral species to global spectral communities: a benchmark for ecosystem diversity estimate by remote sensing

Rocchini

Salvatori

Beierkuhnlein

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…1) from a total of 331,718 species. Endemic plant species are unevenly distributed globally, as previously shown [13][14][15] . Five countries hold the majority of endemic species; Australia, Brazil, China, Mexico, South Africa each provide habitat for >10,000 endemic plant species, which in total represents 35% of all endemic species in our national scale analysis (n = 74,964 of 215,206 species).…”

mentioning

confidence: 93%

Global shortfalls in extinction risk assessments for endemic flora

Gallagher

Allen

Rivers

et al. 2020

Preprint

View full text Add to dashboard Cite

The Global Strategy for Plant Conservation (GSPC) ambitiously calls for an assessment of extinction risk for all recognised plant taxa by 2020 1 . It is now clear that this target will not be met in the short-term; only 21-26% of known plant species have been assessed 2 -a monumental shortfall in anticipated knowledge. Yet the need for risk assessments has never been more urgent. Plants are rapidly going extinct 3,4 and face threats such as climate change 5 and permanent deforestation 6 . Extinction risk assessments continue to provide the critical foundation to inform protection, management and recovery of plant species 7,8 , the loss of which will have clear consequences for maintaining planetary systems and human well-being 9 . Here, we rank countries of the world based on progress towards assessing the extinction risk to their endemic flora. Overall, 67% of countrybased endemic species do not have an extinction risk assessment completed (143,294 species). We show that some of the world's wealthiest nations, which also have relatively strong species protections, are failing to protect their unique flora by not systematically assessing risks to their endemic species.Target 2 of the GSPC seeks to provide 'An assessment of the conservation status of all known plant species, as far as possible, to guide conservation action' 1 . To meet this challenge, we argue that initially, the endemic flora of individual countries must be systemically assessed. This declaration requires an objective evaluation of the current performance of countries with regard to completing assessments. To achieve this, we have combined country-level information on five elements: (1) the proportion of endemic plant species with an extinction risk assessment according to the ThreatSearch 10 database, (2) economic wealth, (3) species protection, (4) population density, and (5) exposure to two key threats: climate warming and permanent deforestation. We use this data to objectively identify countries that may require significant assistance to assess their flora due to low economic status, a lack of species protection or urgent threats.

show abstract

“…Diversity varies with area, thus investigating multiple spatial grains, until wide extents, is important to effectively monitor spatial diversity change in space and time (MacArthur et al, 1966). This is especially true in macroecology, where the primary aim is to model large-scale spatial patterns to infer the ecological processes which generated them, particularly considering the recent effect of global changes worldwide (Hobohm et al, 2019). In order to determine the horizontal distribution of diversity within a satellite image (i.e.…”

Section: Introductionmentioning

confidence: 99%

From zero to infinity: minimum to maximum diversity of the planet by spatio-parametric Rao’s quadratic entropy

Rocchini

Marcantonio

et al. 2021

Preprint

View full text Add to dashboard Cite

AimThe majority of work done to gather information on Earth diversity has been carried out by in-situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannon’s Information Theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Rao’s quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, namely they can account only for a part of the whole diversity continuum. The aim of this paper is thus to generalize the Rao’s quadratic entropy by proposing its parameterization for the first time.InnovationThe parametric Rao’s quadratic entropy, coded in R, i) allows to represent the whole continuum of potential diversity indices in one formula, and ii) starting from the Rao’s quadratic entropy, allows to explicitly make use of distances among pixel reflectance values, together with relative abundances.Main conclusionsThe proposed unifying measure is an integration between abundance- and distance-based algorithms to map the continuum of diversity given a satellite image at any spatial scale.

show abstract

Global endemics-area relationships of vascular plants

Cited by 23 publications

References 44 publications

From local spectral species to global spectral communities: a benchmark for ecosystem diversity estimate by remote sensing

From local spectral species to global spectral communities: a benchmark for ecosystem diversity estimate by remote sensing

Global shortfalls in extinction risk assessments for endemic flora

From zero to infinity: minimum to maximum diversity of the planet by spatio-parametric Rao’s quadratic entropy

Contact Info

Product

Resources

About