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Anticipating species distributions in space and time is necessary for effective biodiversity conservation and for prioritising management interventions. This is especially true when considering invasive species. In such a case, anticipating their spread is important to effectively plan management actions. However, considering uncertainty in the output of species distribution models is critical for correctly interpreting results and avoiding inappropriate decision-making. In particular, when dealing with species inventories, the bias resulting from sampling effort may lead to an over- or under-estimation of the local density of occurrences of a species. In this paper we propose an innovative method to i) map sampling effort bias using cartogram models and ii) explicitly consider such uncertainty in the modeling procedure under a Bayesian framework, which allows the integration of multilevel input data with prior information to improve the anticipation species distributions.

A selective sweep is the result of strong positive selection driving newly occurring or standing genetic variants to fixation, and can dramatically alter the pattern and distribution of allelic diversity in a population. Population-level sequencing data have enabled discoveries of selective sweeps associated with genes involved in recent adaptations in many species. In contrast, much debate but little evidence addresses whether “selfish” genes are capable of fixation—thereby leaving signatures identical to classical selective sweeps—despite being neutral or deleterious to organismal fitness. We previously described R2d2, a large copy-number variant that causes nonrandom segregation of mouse Chromosome 2 in females due to meiotic drive. Here we show population-genetic data consistent with a selfish sweep driven by alleles of R2d2 with high copy number (R2d2HC) in natural populations. We replicate this finding in multiple closed breeding populations from six outbred backgrounds segregating for R2d2 alleles. We find that R2d2HC rapidly increases in frequency, and in most cases becomes fixed in significantly fewer generations than can be explained by genetic drift. R2d2HC is also associated with significantly reduced litter sizes in heterozygous mothers, making it a true selfish allele. Our data provide direct evidence of populations actively undergoing selfish sweeps, and demonstrate that meiotic drive can rapidly alter the genomic landscape in favor of mutations with neutral or even negative effects on overall Darwinian fitness. Further study will reveal the incidence of selfish sweeps, and will elucidate the relative contributions of selfish genes, adaptation and genetic drift to evolution.

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 α- (local relative abundance and richness of spectral species) and β-diversity (turnover of spectral species) maps over wide geographical areas.

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich., This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively., Understanding the causes and effects of species invasions is a priority in ecology and conservation biology. One of the crucial steps in evaluating the impact of invasive species is to map changes in their actual and potential distribution and relative abundance across a wide region over an appropriate time span. While direct and indirect remote sensing approaches have long been used to assess the invasion of plant species, the distribution of invasive animals is mainly based on indirect methods that rely on environmental proxies of conditions suitable for colonization by a particular species. The aim of this article is to review recent efforts in the predictive modelling of the spread of both plant and animal invasive species using remote sensing, and to stimulate debate on the potential use of remote sensing in biological invasion monitoring and forecasting. Specifically, the challenges and drawbacks of remote sensing techniques are discussed in relation to: i) developing species distribution models, and ii) studying life cycle changes and phenological variations. Finally, the paper addresses the open challenges and pitfalls of remote sensing for biological invasion studies including sensor characteristics, upscaling and downscaling in species distribution models, and uncertainty of results.

Among rodent-borne viruses, those belonging to the genera Mammarenavirus, Orthohantavirus and Orthopoxvirus are a particular focus of study both in humans and animals, since they represent some of the most widespread rodent-borne disease-causing pathogens. More recently, the interest in parechoviruses has been increasing because some are known to cause diseases in humans, while others are carried by rodents, although the zoonotic potential of rodent-borne parechoviruses has not been established. Ljungan virus (LV), which belongs to the species Parechovirus B, was first isolated from bank voles in Sweden in 1998. It belongs to the Picornaviridae family. Currently, there is little information about LV host range and epidemiology, but a few reports suggest an association between LV and human disease. The main aims of this doctoral thesis were to establish the symptoms associated with LV in humans, to investigate the association of LV with human central nervous system (CNS) disease, and to determine the prevalence and distribution of LV in human and other animal populations in Europe. LV-associated symptoms were investigated in two human cohorts. Serum samples from Finnish patients hospitalized for suspected nephropathia epidemica (NE) caused by the Orthohantavirus Puumala virus (PUUV) were screened for the presence of lymphocytic choriomeningitis virus (LCMV, Arenavirus), cowpox virus (CPXV, Orthopoxvirus) and LV, in order to compare the disease outcomes in these patients and to establish if the co-existence of viruses could lead to an increase in the severity of symptoms. However, no unusual or additional manifestations between PUUV cases and PUUV-LV/LCMV/CPXV cases were detected. To determine if LV (together with the rodent-borne virus LCMV) could be one of the causes of neurological symptoms in Finnish patients with suspected CNS disease, anti-LV and LCMV antibodies were analyzed from serum and cerebrospinal fluid samples. LV- and LCMV-specific nucleic acids were also analyzed from the patient samples. However, no association between LV or LCMV antibodies or nucleic acids and the neurological manifestations in the patient cohort was detected. In order to improve the knowledge of the host and geographical distribution of LV, tissues from multiple rodent and insectivore species from ten European countries were screened for LV nucleic acids. We confirmed that LV is widespread geographically, having been detected in at least one host species in nine out of ten countries involved in the study. Seventeen out of 21 species screened were LV PCR-positive. Results indicated that bank voles are the main rodent host for LV. Male and subadult bank voles are significantly more likely to be LV-positive, and the prevalence has a temporal pattern (higher in autumn compared to spring and summer), possibly due to adult bank voles clearing the infection. Sekä ihmis- että eläinperäisiä mammarena-, orthohanta- ja orthopoxviruksia on tutkittu laajimmin, koska niitä esiintyy maailmanlaajuisesti ja aiheuttavat lisäksi jyrsijävälitteisiä zoonooseja. Nykyään kiinnostuksen kohteina ovat lisäksi jyrsijöissä esiintyvät parechovirukset. Ihmisvälitteisten parechovirusten tiedetään olevan patogeenisia ja helposti leviäviä mutta vielä ei ole osoitettu jyrsijöiden parechovirusten aiheuttavan zoonooseja. Parechovirus B –lajiin kuuluva Ljungan virus (LV) löydettiin ensimmäisen kerran vuonna 1998 ruotsalaisesta metsämyyrästä. Ljungan virus kuuluu muiden parechovirusten kanssa suureen pikornavirusperheeseen. Ljungan virus on jyrsijävirus mutta muuten tästä viruksesta tiedetään vähän ja esimerkiksi sen isäntäjoukon laajuutta tai epidemiologiaa ei ole tarkkaan selvitetty. Löytyy vain harvoja tutkimuksia, joissa Ljungan viruksen seroprevalenssia ihmisillä on selvitetty tai ehdotettu yhteyttä ihmistauteihin. Tämän väitöskirjatyön päätavoitteina oli tutkia ja selvittää Ljungan viruksen assosiaatiota ihmistauteihin ja näistä varsinkin keskushermostoinfektioihin, sekä määrittää viruksen prevalenssia ja levinneisyyttä Euroopan laajuisesti ihmisissä ja jyrsijöissä. Ljungan viruksen assosiaatiota ihmistauteihin tutkittiin kahdessa eri potilaskohortissa. Toinen potilaskohortti koostui suomalaisista sairaalahoitoisista myyräkuumepotilaista. Myyräkuumeen aiheuttaa jyrsijävälitteinen orthohantaviruksiin kuuluva Puumala-virus (PUUV). Ljungan viruksen lisäksi tästä potilaskohortista tutkittiin myös lymfosyyttisen koriomeningiittiviruksen (LCMV) sekä lehmärokkoviruksen (CPXV, Orthopoxvirus) aiheuttamia serokonversioita. Tuloksia ja potilaiden oirekuvia verrattiin toisiinsa. Lopputuloksena voitiin todeta, että myyräkuumeen taudinkuvassa ei huomattu eroa riippumatta siitä oliko potilaalla vain PUUV-infektio vai mahdollinen LV/LCMV/CXPV-yhteisinfektio. Toinen potilaskohortti koostui potilaista, joilla epäiltiin keskushermostoinfektiota. Tässä kohortista tutkittiin potilasnaytteistä niin Ljungan viruksen kuin LCMV:n seerumivasta-aineita sekä etsittiin selkäydinnestenäytteistä näiden virusten nukleiinihappoa. Aineistosta ei löydetty yhtään LV- tai LCMV-nukleiinihappopositiivista selkäydinnäytettä. Ljungan viruksen jyrsijäisäntäkirjoa ja maantieteellistä levinneisyyttä tutkittiin eri jyrsijälajien kudosnäytteiden avulla. Näitä näytteitä kerättiin yhdeksästä eri Euroopan maasta ja näytteistä tutkittiin Ljungan viruksen nukleiinihappoja. Pystyimme osoittamaan että LV on maantieteellisesti erittäin laajalle levinnyt. Jokaisesta tutkitusta yhdeksästä Euroopan maasta pystyttiin osoittamaan Ljungan viruksen nukleiinihappoa ainakin yhdestä jyrsijälajista. Testatuista 21 jyrsijälajista 17 lajissa osoitettiin LV nukeliinihappoa. Tulosten perusteella metsämyyrä toimii kuitenkin Ljungan viruksen pääisäntänä. Urokset sekä nuoret aikuiset metsämyyrät olivat merkittävästi useammin Ljungan virus positiivisia ja temporaalisen prevalenssin mukaan syksyllä esiintyvyys oli korkeampi kuin keväällä tai kesällä. Temporaalinen vaihtelu viittaisi siihen, että aikuisilla metsämyyrillä infektio on mahdollisesti itsestäänrajoittuva.

Predicting the geographical distribution of a species is a central topic in ecology, conservation and management of natural resources especially for invasive organisms. Invasive species can modify the structure and function of invaded ecosystems, altering their biodiversity, and causing significant economic losses locally and globally. Therefore, measuring and visualizing the uncertainty inherent in species’ potential distributions is fundamental for effective biodiversity monitoring and planning conservation interventions. This paper discusses a new Bayesian approach to mapping this uncertainty using cartograms, previously published knowledge, and presence/absence data.

An indirect method for estimating biodiversity from Earth observations is the Spectral Variation Hypothesis (SVH). SVH states that the higher the spatial variability of the spectral response of an optical remotely sensed image, the higher the number of available ecological niches and hence, the higher the diversity of tree species in the considered area. Here for the first time we apply the concept of the SVH to Light Detection and Ranging (LiDAR) data to understand the relationship between the height heterogeneity (HH) of a forest and its tree species diversity, a concept we have named the ‘Height Variation Hypothesis’ (HVH). We tested HVH in two different European forest types: a coniferous mountain forest in the eastern Italian Alps and a mixed temperate forest in southern Germany. We used the heterogeneity index Rao’s Q to estimate HH using a Canopy Height Model (CHM) at different resolutions derived from LiDAR data, and linear regression models and relation analysis to assess the relationships between HH and three species diversity indices derived from in situ collected data: Shannon’s H, Simpson’s S and species richness. The relationships were calculated for all plots in both study areas, and separately for plots with a defined Canopy Closure (CC > 70%, CC > 80%, CC > 90%) to understand the effect of forest density on the relationship between HH and tree species diversity. Our results showed that HH is related to the tree species diversity of the forest ecosystems reaching (in the case of Shannon’s H) values of R 2 = 0.63 for the coniferous mountain forest and R 2 = 0.56 for the mixed temperate forest, particularly when calculated with a CHM resolution of 2.5 m. The associations also increased with increasing canopy closure suggesting that HVH is scale and forest density dependent. Our results also underlined that the abundance-based diversity measures are more highly correlated with HH than with species richness. Finally, our findings suggest that the HVH is a valuable tool for assessing tree species diversity in forest ecosystems, and could also be useful for overall biodiversity estimates.

Anticipating species distributions in space and time is necessary for effective biodiversity conservation and for prioritising management interventions. This is especially true when considering invasive species. In such a case, anticipating their spread is important to effectively plan management actions. However, considering uncertainty in the output of species distribution models is critical for correctly interpreting results and avoiding inappropriate decision-making. In particular, when dealing with species inventories, the bias resulting from sampling effort may lead to an over- or under-estimation of the local density of occurrences of a species. In this paper we propose an innovative method to i) map sampling effort bias using cartogram models and ii) explicitly consider such uncertainty in the modeling procedure under a Bayesian framework, which allows the integration of multilevel input data with prior information to improve the anticipation species distributions.