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Despite large numbers of reintroduction projects taking place and the high cost involved, there is a generally low success rate. Insects in particular are understudied within reintroduction ecology, with guidelines focusing on more iconic vertebrate taxa. Species distribution models (SDMs) examine the associations between species observations and environmental variables to find the conditions in which populations could survive. This study utilises two frequently used SDM approaches, a regression model (general linear model (GLM)) and a machine learning method (MaxEnt) to model habitat suitability for Chequered Skipper, Carterocephalus palaemon, butterflies, which are being reintroduced to Northamptonshire following extinction in England. We look at how SDMs using widespread remotely sensed variables could be used to inform the reintroduction process by finding areas of suitable habitat that were previously overlooked. These remotely sensed variables have the potential to inform reintroductions without extensive on the ground research as they cover huge areas and are widely available. We found that both models are successful in discriminating between presences and absences, using only a limited number of explanatory variables. We conclude that these wide-scale SDMs are useful as a first step in the decision-making process in determining appropriate sites for reintroductions, but that they are less accurate when establishing precisely where species should be placed.

Ongewervelden maken het grootste deel van onze biodiversiteit uit, maar helaas worden ze, op enkele populaire groepen zoals dagvlinders of libellen na, momenteel amper in rekening gebracht in het natuurbeleid. Dit is nog opvallender als we kijken naar bodemorganismen. Bodems herbergen een enorme soortenrijkdom aan ongewervelden die de bovengrondse sterk overstijgt. Net door deze enorme soortenrijkdom in combinatie met hun hoge aantallen, de slecht gekende taxonomie en het kleine formaat van de meeste soorten hinkt studie naar bodemorganismen achterop. Nochtans vervullen bodemorganismen een cruciale rol in het functioneren van ecosystemen, denk maar aan de afbraak van strooisel, waterhuishouding, koolstofopslag, nutriëntenkringlopen. Helaas is voor de meeste groepen onze kennis over hun verspreiding en ecologie dan ook zeer beperkt. Voor pissebedden kwam hier de afgelopen jaren verandering in met de uitgebreide inventaris door Spinicornis, de Belgische pissebeddenwerkgroep.

A new kinetic Monte Carlo simulation approach for crystal growth from solution is presented. The simulations include an explicit representation of an extended volume of solution above the crystal face and realistically treats voids within the forming crystal, step overhangs and concentration gradients in the mother solution. The effect of impurities on step growth is investigated and it is shown that the results depend on a complex interplay between concentration gradients in solution driven by the consumption of material during step growth, the lifetime of impurities on the crystal surface and the geometry of the steps., SCOPUS: ar.j, info:eu-repo/semantics/published

Impurities control the formation of bio-crystals and can fully paralyze crystal growth at low levels of supersaturation. Traditional impurity models predict that an escape from this so-called “dead zone” requires an increase in the driving force (i.e. supersaturation). In this work, using protein crystals as a model system, we uncover an alternative escape route from the dead zone that does not involve an increase in supersaturation. We demonstrate that the merger of a protein cluster with the crystal surface triggers the formation of an ordered multi-layered island. The newly created surface on top of the resulting 3D island is initially devoid of impurities and therefore characterized by near-pure step growth kinetics. The accelerated step advancement on this relatively uncontaminated surface limits the available time for impurities to adsorb on the emerging terraces and by extension their resulting surface density. Cluster-mediated crystal growth occurring in heterogeneous media can therefore lead to stop-and-go dynamics, which offers a new model to explain crystallization taking place under biological control (e.g. biomineralization).

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Butterfly monitoring enjoys a growing popularity in Europe, mainly supported by Butterfly Conservation Europe (BCE) and its partners. While Butterfly Monitoring Schemes are present in a growing number of countries and new ones are being initiated in many places, long time-series are currently only available for a limited number of countries. For the indicators in this report, we used data from 22 countries (Figure 1): Andorra, Austria, Belgium, Czech Republic, Estonia, Finland, France, Germany, Hungary, Ireland, Jersey, Latvia, Lithuania, Luxembourg, Norway, Romania, Slovenia, Spain, Sweden, Switzerland, The Netherlands and the United Kingdom.The indicators use field data up to and including the 2020 field season. The method for calculating indicators has been greatly improved and enhanced. During 2020, more than 2,500 standardised butterfly transects distributed across 22 monitoring schemes were used to inform the EU27 Grassland Butterfly Indicator and almost 5,000 from 25 schemes for the European Grassland Butterfly Indicator (Figure 2). Since 1990 over 6,350 and 11,500 separate transects have contributed to the EU27 and Europe indicators, respectively.

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