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Modelling invasive plant alien species richness in Tenerife (Canary Islands) using Bayesian Generalised Linear Spatial Models
Island and Ocean Ecosystems, BRB
Available Online

Arévalo, J. R.

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Bacaro, G.

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Da Re, D.

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Fernàndez-Palacios, J. M.

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Negrín-Pérez, Z.

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Otto, R.

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Rocchini, D.

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Tordoni, E.

2019
Biological invasions are one of the major threats to biodiversity, especially on islands where the number of endemic species is the highest despite their small area. In the Canary Islands, the relationships among invasive alien species (hereafter IAS) and their environmental and anthropogenic determinants have been thoroughly described but robust provisional models integrating species spatial autocorrelation and patterns of IAS communities are still lacking. In this study, we developed a Generalised Linear Spatial Model for Invasive Alien Species Richness (IASR) under a Bayesian framework, using a methodological approach that encompass GIS and geostatistical analysis. In this study, we hypothesised that the inclusion of spatial autocorrelation can improve model performance thus obtaining more IASR-reliable predictions. In addition, this method provides uncertainty maps that prioritize areas where further sampling e?orts are needed. Our model showed that IASR in Tenerife is mainly driven by a combination of anthropogenic and natural processes, highlighting favourable conditions for IAS from the coastline to about 800 m a.s.l., especially on the windward humid aspect. Among anthropogenic factors, a clear positive relationship between road kernel density estimation and IASR was found. Indeed, road density has recently increased especially in low to mid altitudinal zones on the Canary Islands, strictly associated with urban expansion and it has been widely demonstrated to be one of the main IAS pathways. Hence, higher road density can be related to increased ‘propagule pressure’ which is, together with source of disturbance, one of the most important factors explaining richness in alien species invasion success. Our main conclusions highlight the importance of considering spatial autocorrelation and researchers’ prior knowledge to increase the predictive power of statistical models. From a practical perspective, these models and their related uncertainty, will serve as important management tools highlighting those portions of territories that will be more prone to biological invasions and where monitoring e? orts should be directed.
Analysis of the secondary nest of the yellow-legged hornet found in the Balearic Islands reveals its high adaptability to Mediterranean isolated ecosystems
Island and Ocean Ecosystems, BRB
Available Online

Colomar, V.

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Herrera, C.

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Leza, M.M.

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Marqués, A.

2019
The yellow-legged hornet (Vespa velutina) was detected for the ?rst time in the north of Spain in 2010, but was not detected in Majorca, Balearic Islands until 2015 and only one secondary nest, with 10 combs, was found in the northwest of the island. During 2016, nine more nests were found in the same region. To better understand the biology of V. velutina in isolated conditions, the following objectives were proposed: (I) describe the architecture and structure of nests; (II) analyse the shape of combs and develop a new method to con?rm the circular pattern of breeding; (III) determine the colony size and (IV) determine the succession of workers and sexual individuals throughout the season. For these reasons, nests that were removed were frozen for at least 48 days until analysis. Our results show that this species has a high reproductive potential under isolated conditions. Results reveal that parameters such as weight, height, diameter, number of cells and total individual production are directly related. Moreover, each mature nest can produce up to 9,000 individuals and several hundred potential founder queens. All results inform formulation of an e?cient control or eradication programme in the Balearic Islands, as we are in the early stages of invasion and intervention is essential to eradicate V. velutina on Majorca Island.