European primary forest database v2.0.

Primary forests, defined here as forests where the signs of human impacts, if any, are strongly blurred due to decades without forest management, are scarce in Europe and continue to disappear. Despite these losses, we know little about where these forests occur. Here, we present a comprehensive geodatabase and map of Europe's known primary forests. Our geodatabase harmonizes 48 different, mostly field-based datasets of primary forests, and contains 18,411 individual patches (41.1 Mha) spread across 33 countries. When available, we provide information on each patch (name, location, naturalness, extent and dominant tree species) and the surrounding landscape (biogeographical regions, protection status, potential natural vegetation, current forest extent). Using Landsat satellite-image time series (1985-2018) we checked each patch for possible disturbance events since primary forests were identified, resulting in 94% of patches free of significant disturbances in the last 30 years. Although knowledge gaps remain, ours is the most comprehensive dataset on primary forests in Europe, and will be useful for ecological studies, and conservation planning to safeguard these unique forests.

Cannot see the diversity for all the species: Evaluating inclusion criteria for local species lists when using abundant citizen science data.

Abundant citizen science data on species occurrences are becoming increasingly available and enable identifying composition of communities occurring at multiple sites with high temporal resolution. However, for species displaying temporary patterns of local occurrences that are transient to some sites, biodiversity measures are clearly dependent on the criteria used to include species into local species lists. Using abundant opportunistic citizen science data from frequently visited wetlands, we investigated the sensitivity of α- and ß-diversity estimates to the use raw versus detection-corrected data and to the use of inclusion criteria for species presence reflecting alternative site use. We tested seven inclusion criteria (with varying number of days required to be present) on time series of daily occurrence status during a breeding season of 90 days for 77 wetland bird species. We show that even when opportunistic presence-only observation data are abundant, raw data may not produce reliable local species richness estimates and rank sites very differently in terms of species richness. Furthermore, occupancy model based α- and ß-diversity estimates were sensitive to the inclusion criteria used. Total species lists (all species observed at least once during a season) may therefore mask diversity differences among sites in local communities of species, by including vagrant species on potentially breeding communities and change the relative rank order of sites in terms of species richness. Very high sampling effort does not necessarily free opportunistic data from its inherent bias and can produce a pattern in which many species are observed at least once almost everywhere, thus leading to a possible paradox: The large amount of biological information may hinder its usefulness. Therefore, when prioritizing among sites to manage or preserve species diversity estimates need to be carefully related to relevant inclusion criteria depending on the diversity estimate in focus.

Exploiting opportunistic observations to estimate changes in seasonal site use: An example with wetland birds.

Nonsystematically collected, a.k.a. opportunistic, species observations are accumulating at a high rate in biodiversity databases. Occupancy models have arisen as the main tool to reduce effects of limited knowledge about effort in analyses of opportunistic data. These models are generally using long closure periods (e.g., breeding season) for the estimation of probability of detection and occurrence. Here, we use the fact that multiple opportunistic observations in biodiversity databases may be available even within days (e.g., at popular birding localities) to reduce the closure period to 1 day in order to estimate daily occupancies within the breeding season. We use a hierarchical dynamic occupancy model for daily visits to analyze opportunistic observations of 71 species from nine wetlands during 10 years. Our model derives measures of seasonal site use within seasons from estimates of daily occupancy. Comparing results from our "seasonal site use model" to results from a traditional annual occupancy model (using a closure criterion of 2 months or more) showed that our model provides more detailed biologically relevant information. For example, when the aim is to analyze occurrences of breeding species, an annual occupancy model will over-estimate site use of species with temporary occurrences (e.g., migrants passing by, single itinerary prospecting individuals) as even a single observation during the closure period will be viewed as an occupancy. Alternatively, our model produces estimates of the extent to which sites are actually used. Model validation based on simulated data confirmed that our model is robust to changes and variability in sampling effort and species detectability. We conclude that more information can be gained from opportunistic data with multiple replicates (e.g., several reports per day almost every day) by reducing the time window of the closure criterion to acquire estimates of occupancies within seasons.

Dynamic anthropogenic edge effects on the distribution and diversity of fungi in fragmented old-growth forests.

Diversity patterns and dynamics at forest edges are not well understood. We disentangle the relative importance of edge-effect variables on spatio-temporal patterns in species richness and occupancy of deadwood-dwelling fungi in fragmented old-growth forests. We related richness and log occupancy by 10 old-growth forest indicator fungi and by two common fungi to log conditions in natural and anthropogenic edge habitats of 31 old-growth Picea abies forest stands in central Sweden. We compared edge-to-interior gradients (100 m) to the forest interior (beyond 100 m), and we analyzed stand-level changes after 10 yr. Both richness and occupancy of logs by indicator species was negatively related to adjacent young clear-cut edges, but this effect decreased with increasing clear-cut age. The occupancy of logs by indicator species also increased with increasing distance to the natural edges. In contrast, the occupancy of logs by common species was positively related or unrelated to distance to clear-cut edges regardless of the edge age, and this was partly explained by fungal specificity to substrate quality. Stand-level mean richness and mean occupancy of logs did not change for indicator or common species over a decade. By illustrating the importance of spatial and temporal dimensions of edge effects, we extend the general understanding of the distribution and diversity of substrate-confined fungi in fragmented old-growth forests. Our results highlight the importance of longer forest rotation times adjacent to small protected areas and forest set-asides, where it may take more than 50 yr for indicator species richness levels to recover to occupancy levels observed in the forest interior. Also, non-simultaneous clear-cutting of surrounding productive forests in a way that reduces the edge effect over time (i.e., dynamic buffers) may increase the effective core area of small forest set-asides and improve their performance on protecting species of special concern for conservation.

Challenges and priorities for modelling livestock health and pathogens in the context of climate change.

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire based exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change.

Testicular length as an indicator of the onset of sperm production in alpacas under Swedish conditions.

BACKGROUND: The popularity of alpacas (Vicugna pacos) is increasing in Sweden as well as in other countries; however, knowledge about optimal management practices under Swedish conditions is still limited. The wide age range reported when the onset of puberty can occur, between 1 and 3 years of age, makes management decisions difficult and may be influenced by the conditions under which the alpacas are kept. The aim of this study was to find out when Swedish alpacas can be expected to start producing sperm, by using testicular length and body condition score as a more precise indirect indicator than age. RESULTS: This study suggests that animals with a testicular length ≥3.8 cm would be producing sperm; however, if it is crucial to know that there is no sperm production for management purposes, the threshold level for testicular length used to differentiate between sperm-producing and non-sperm producing animals should be ≤1.6 cm instead. If only one variable is considered, testicular length appears to better than age alone to predict sperm production. Body condition score together with testicular length explains the individual onset of puberty and better guide management recommendations. CONCLUSIONS: Using a combination of these parameters (testicular length, body condition score and age) as a tool for decision making for alpaca husbandry under Swedish conditions is suggested.

Explaining Spatial Variation in the Recording Effort of Citizen Science Data across Multiple Taxa.

The collation of citizen science data in open-access biodiversity databases makes temporally and spatially extensive species' observation data available to a wide range of users. Such data are an invaluable resource but contain inherent limitations, such as sampling bias in favour of recorder distribution, lack of survey effort assessment, and lack of coverage of the distribution of all organisms. Any technical assessment, monitoring program or scientific research applying citizen science data should therefore include an evaluation of the uncertainty of its results. We use 'ignorance' scores, i.e. spatially explicit indices of sampling bias across a study region, to further understand spatial patterns of observation behaviour for 13 reference taxonomic groups. The data is based on voluntary observations made in Sweden between 2000 and 2014. We compared the effect of six geographical variables (elevation, steepness, population density, log population density, road density and footpath density) on the ignorance scores of each group. We found substantial variation among taxonomic groups in the relative importance of different geographic variables for explaining ignorance scores. In general, road access and logged population density were consistently important variables explaining bias in sampling effort, indicating that access at a landscape-scale facilitates voluntary reporting by citizen scientists. Also, small increases in population density can produce a substantial reduction in ignorance score. However the between-taxa variation in the importance of geographic variables for explaining ignorance scores demonstrated that different taxa suffer from different spatial biases. We suggest that conservationists and researchers should use ignorance scores to acknowledge uncertainty in their analyses and conclusions, because they may simultaneously include many correlated variables that are difficult to disentangle.

Identification of limiting climatic and geographical variables for the distribution of the tortoise Chelonoidis chilensis (Testudinidae): a baseline for conservation actions.

Background. Just as for most other tortoise species, the once common Chaco tortoise, Chelonoidis chilensis (Testudinidae), is under constant threat across it distribution in Argentina, Bolivia and Paraguay. Despite initial qualitative description of the species distribution and further individual reports of new locations for the species, there is no description of the species distribution in probabilistic terms. With this work we aim to produce an updated predictive distribution map for C. chilensis to serve as a baseline management tool for directed strategic conservation planning. Methods. We fitted a spatially expanded logistic regression model within the Bayesian framework that accounts for uncertainty on presence-only and generated pseudo-absence data into the parameter estimates. We contrast the results with reported data for the national networks of protected areas to assess the inclusion of the species in area-based conservation strategies. Results. We obtained maps with predictions of the occurrence of the species and reported the model's uncertainty spatially. The model suggests that potential suitable habitats for the species are continuous across Argentina, West Paraguay and South Bolivia, considering the variables, the scale and the resolution used. The main limiting variables were temperature-related variables, and precipitation in the reproductive period. Discussion. Given the alarming low density and coverage of protected areas over the distribution area of C. chilensis, the map produced provides a baseline to identify areas where directed strategic conservation management actions would be more efficient for this and other associated species.

Displaying bias in sampling effort of data accessed from biodiversity databases using ignorance maps.

BACKGROUND: Open-access biodiversity databases including mainly citizen science data make temporally and spatially extensive species' observation data available to a wide range of users. Such data have limitations however, which include: sampling bias in favour of recorder distribution, lack of survey effort assessment, and lack of coverage of the distribution of all organisms. These limitations are not always recorded, while any technical assessment or scientific research based on such data should include an evaluation of the uncertainty of its source data and researchers should acknowledge this information in their analysis. The here proposed maps of ignorance are a critical and easy way to implement a tool to not only visually explore the quality of the data, but also to filter out unreliable results. NEW INFORMATION: I present simple algorithms to display ignorance maps as a tool to report the spatial distribution of the bias and lack of sampling effort across a study region. Ignorance scores are expressed solely based on raw data in order to rely on the fewest assumptions possible. Therefore there is no prediction or estimation involved. The rationale is based on the assumption that it is appropriate to use species groups as a surrogate for sampling effort because it is likely that an entire group of species observed by similar methods will share similar bias. Simple algorithms are then used to transform raw data into ignorance scores scaled 0-1 that are easily comparable and scalable. Because of the need to perform calculations over big datasets, simplicity is crucial for web-based implementations on infrastructures for biodiversity information. With these algorithms, any infrastructure for biodiversity information can offer a quality report of the observations accessed through them. Users can specify a reference taxonomic group and a time frame according to the research question. The potential of this tool lies in the simplicity of its algorithms and in the lack of assumptions made about the bias distribution, giving the user the freedom to tailor analyses to their specific needs.

Breed influences on in vitro development of abattoir-derived bovine oocytes.

BACKGROUND: There is a discrepancy in the reproductive performance between different cattle breeds. Using abattoir-derived ovaries and data base information we studied the effects of breed on in vitro fertilization and early embryo development. METHODS: The in vitro developmental competence of oocytes from cattle (n = 202) of Swedish Red (SR), Swedish Holstein (SH) and mixed beef breeds was compared, retrospectively tracing donors of abattoir-derived ovaries using a combination of the national animal databases and abattoir information. Age was significantly lower and carcass conformation score was higher in the beef breeds than in the dairy breeds.Cumulus oocyte complexes (n = 1351) were aspirated from abattoir-derived ovaries from animals of known breed (visual inspection confirmed through databases), age (databases), and abattoir information. Oocytes were matured, fertilized (frozen semen from two dairy bulls) and cultured according to conventional protocols. On day 8, blastocysts were graded and the number of nuclei determined. RESULTS: Cleavage rate was not different between the breeds but was significantly different between bulls. The percentage of blastocysts on day 8 was significantly higher when the oocyte donor's breed was beef or SR than SH. There was no significant difference in blastocyst grades or stages between the breeds, but the number of nuclei in day 8 blastocysts was significantly lower in SH compared to the beef. CONCLUSIONS: The use of abattoir-derived ovaries from animals whose background is traceable can be a valuable tool for research. Using this approach in the present study, oocyte donor breed was seen to affect early embryo development during in vitro embryo production, which may be a contributing factor to the declining fertility in some dairy breeds seen today.

Disentangling effects of uncertainties on population projections: climate change impact on an epixylic bryophyte.

Assessment of future ecosystem risks should account for the relevant uncertainty sources. This means accounting for the joint effects of climate variables and using modelling techniques that allow proper treatment of uncertainties. We investigate the influence of three of the IPCC's scenarios of greenhouse gas emissions (special report on emission scenarios (SRES)) on projections of the future abundance of a bryophyte model species. We also compare the relative importance of uncertainty sources on the population projections. The whole chain global climate model (GCM)-regional climate model-population dynamics model is addressed. The uncertainty depends on both natural- and model-related sources, in particular on GCM uncertainty. Ignoring the uncertainties gives an unwarranted impression of confidence in the results. The most likely population development of the bryophyte Buxbaumia viridis towards the end of this century is negative: even with a low-emission scenario, there is more than a 65 per cent risk for the population to be halved. The conclusion of a population decline is valid for all SRES scenarios investigated. Uncertainties are no longer an obstacle, but a mandatory aspect to include in the viability analysis of populations.