Biology subjects

Partel, M.

Publications and source records attributed to Partel, M..

4 recordsLinked to original sources

bioRxiv2022

The characteristics of high-dark-diversity habitats derived from lidar

A key aspect of nature conservation is knowledge of which aspects of nature to conserve or restore to favor the characteristic diversity of plants in a given area. Here, we used a large plant dataset with > 40.000 plots combined with airborne laser scanning (lidar) data to reveal the local characteristics of habitats having a high plant dark diversity - i.e., absence of suitable species - at national extent (> 43.000 km2). Such habitats have potential for reaching high realized diversity levels and hence are important in a conservation context. We calculated 10 different lidar based metrics (both terrain and vegetation structure) and combined these with 7 different field-based measures (soil chemistry and species indicators). We then used Integrated Nested Laplace Approximation for modelling plant dark diversity across 33 North European habitat types (open landscapes and forests) selected by the European communities to be important. In open habitat types high-dark-diversity habitats had relatively low pH, high nitrogen content, tall homogenous vegetation and overall relatively homogenous terrains (high terrain openness) although with a rather high degree of local microtopographical variations. High-dark-diversity habitats in forests had relatively tall vegetation, few natural-forest indicators, low potential solar radiation input and a low cover of small woody plants. Our results highlight important vegetation, terrain and soil related factors that managers and policymakers should be aware of in conservation and restoration projects to ensure a natural plant diversity, for example low nutrient loads, natural microtopography and open forests with old-growth elements such as dead wood and rot attacks.

ecology↗

bioRxiv2020

Mapping extinction risk in the global functional spectra across the tree of life

Although one quarter of the species of plants and vertebrates are threatened with extinction, little is known about how the potential effect of extinctions on the global diversity of ecological strategies. Using trait and phylogenetic information for more than 75,000 species of plants, mammals, birds, reptiles, amphibians and freshwater fishes, we characterized the global functional spectra of each of these groups. Mapping of extinction risk within these spectra revealed that larger species with slower pace of life are universally threatened. Simulated potential extinctions revealed extensive internal reorganizations in the global functional spectra, which are particularly severe for mammals and amphibians. Considering the disproportionate importance of the largest species for ecological processes, our results emphasize the importance of actions to prevent the extinction of the megabiota.Competing Interest StatementThe authors have declared no competing interest.View Full Text

ecology↗

bioRxiv2019

Dark diversity reveals importance of biotic resources and competition for plant diversity across broad environmental gradients

Species richness is the most commonly used metric to quantify biodiversity. However, examining dark diversity, the group of missing species which can potentially inhabit a site, can provide a more thorough understanding of the processes influencing observed biodiversity and help evaluate the restoration potential of local habitats. So far, dark diversity has mainly been studied for specific habitats or largescale landscapes while less attention has been given to variation across broad environmental gradients or as a result of local conditions and biotic interactions. In this study, we investigate the importance of local environmental conditions in determining dark diversity and observed richness in plant communities across broad environmental gradients. We use the ecospace concept to investigate how abiotic gradients (defined as position), availability of biotic resources (defined as expansion), spatiotemporal extent of habitats (defined as continuity), as well as species interactions through competition, relate to these biodiversity measures. Position variables were important for both plant richness and dark diversity, some with quadratic relationships, e.g., plant richness showing a unimodal response to soil fertility corresponding to the intermediate productivity hypothesis. Competition represented by community mean Grime C showed a negative correlation with plant richness. Besides position, organic carbon was the most important variable for dark diversity, indicating that in late succession habitats such as forests and shrubs, dark diversity is generally low. The importance of Grime C indicate that intermediate disturbance, such as grazing, may facilitate higher species richness and lower dark diversity. Comparing various biodiversity metrics and their influencing factors might reveal important drivers of biodiversity changes and result in better conservation decision-making.

ecology↗

bioRxiv2019

Estimating probabilistic dark diversity based on the hypergeometric distribution

O_LIThe biodiversity of a site includes the absent species from the region that are theoretically able to live in the sites particular ecological conditions. These species constitute the dark diversity of the site. Unlike present species, dark diversity is unobservable and can only be estimated. Most existing methods to designate dark diversity act in a binary fashion. However, dark diversity is more suitably defined as a fuzzy set--in which the degree of certainty about species membership is expressed as a probability.\nC_LIO_LIWe present a new method to estimate probabilistic dark diversity based on the hypergeometric distribution. The method relies on co-occurrences to infer the strength of the association between pairs of species and assign probabilistic adscription to dark diversity to absent species. We compare it with two established methods to estimate dark diversity (Beals index and favorability correction). To test the methods, we created simulations based on individual agents in which the suitability of each species in each site is known. We compared the ability of the methods to accurately predict suitability and the size of dark diversity, and compared their sensitivity to data availability. Further, we assessed the methods in two real datasets with nested sampling designs.\nC_LIO_LIOur simulations revealed that predictions of the Beals method were extremely sensitive to species frequency, and predicted suitability poorly. The Favorability transformation corrected this relationship, but did still predicted extremely low probabilities for species with very little information. The Hypergeometric method outperformed the Beals and Favorability methods in all considered aspects in the simulations and displayed better characteristics in the real datasets.\nC_LIO_LIProbabilistic consideratiosn of biodiversity will help to acknowledge the uncertainty associated with ecological information. Although the Beals method has been described as the best estimator of dark diversity, it should be preferred only when the goal is to predict future apperances of species. However, studies on dark diversity should focus on the ecological affinities of species. The Hypergeometric method is the most promising method to estimate probabilistic dark diversity and species pool composition based on co-occurrences.\nC_LI

ecology↗