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.
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.
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.
We studied the effect of heat stress on milk quality in Spanish organic dairy farms using published milk productivity equations. We collected data from 23 weather stations and 14,424 milk test-days ...for milk yield and milk fat and protein content for the period July 2011 to June 2013. As an indicator of heat stress, we used the maximum daily temperature–humidity index (THI) from 2 days before the milk test date. We fitted the data using hierarchical regression models stratified by farm, cow parity and monthly test-day milk records. The effect of THI was deemed low on biological costs through milk yield. However, the known negative relationship between milk yield and milk quality (protein and fat content) became even steeper when the THI increased, suggesting a significant negative correlation between heat stress and milk quality. Therefore, although the milk yield of cows in the organic farming systems analyzed appeared resilient to heat stress conditions, milk quality, a major selling point for organic dairy products, was negatively affected. The model presented here could be used to predict the potential impacts of different climate change scenarios on dairy farming, and to delineate adaptation strategies within organic systems.
Environmental stochasticity is important in explaining the persistence and establishment of invasive species, but the simultaneous effects of environmental and demographic factors are difficult to ...separate. Understanding how demography and environmental factors affect invasive species abundance over large temporal and spatial scales is essential to anticipate populations at risk of becoming established and setting appropriate management measures. Using a hierarchical mixed modelling approach, we analysed the spatial and interannual dynamics of the invasive raphidophyte Gonyostomum semen, a noxious flagellate which is spreading in northern Europe, in response to demographic and environmental variation. We used data from 76 lakes distributed across two biogeographical regions in Sweden (Central Plains in the south and Fennoscandian region in the north) and sampled during 14Â years. We found a strong asynchrony in the density dynamics of G. semen populations between the two regions. G. semen showed positive trends (i.e. increasing frequency of high density peaks) in most southern lakes, forming established populations with recurrent blooms in successive years in some of them. In contrast, G. semen populations were smaller and more stochastic in the north. G. semen previous year's abundance, a proxy for cyst production and recruitment, had a strong control on the dynamics, likely contributing to the stability of high density populations in southern lakes. Conversely, the effects of climate and habitat were weaker and their influence varied across regions. Temperature was the limiting factor in the north whereas local habitat was more important in the south. Synthesis. A full understanding of the mechanisms driving abundance changes across large scales can only be gained if endogenous and environmental factors are analysed together. For phytoplankton species, and specially, noxious microalgae, this implies that proxies for cyst production and recruitment, which are the inoculum for next year population, should be included in e.g. distribution, bloom formation and climate models, as these may modify establishment and population response to environmental variation. Asynchronous changes in abundance across regions also indicate that management plans should be developed for small regions, as inference at a large scale may obscure the mechanisms driving local population changes.
Binomial N‐mixture models are commonly applied to analyse population survey data. By estimating detection probabilities, N‐mixture models aim at extracting information about abundances in terms of ...absolute and not just relative numbers. This separation of detection probability and abundance relies on parametric assumptions about the distribution of individuals among sites and of detections of individuals among repeat visits to sites. Current methods for checking assumptions are limited, and their computational complexity has hindered evaluations of their performance.
We use simulations and a case study to assess the sensitivity of binomial N‐mixture models to overdispersion in abundance and in detection, develop computationally efficient graphical goodness of fit checks to detect it, and evaluate the ability of the checks to identify overdispersion.
The simulations show that if the parametric assumptions are not exact the bias in estimated abundances can be severe: underestimation if there is overdispersion in abundance relative to the fitted model and overestimation if there is overdispersion in detection. Our goodness‐of‐fit checks performed well in detecting lack of fit when the abundance distribution was overdispersed, but struggled to detect lack of fit when detections were overdispersed. We show that the inability to detect lack of fit due to overdispersed detection is caused by a fundamental similarity between N‐mixture models with beta‐binomial detections and N‐mixture models with negative binomial abundances.
The strong biases that can occur in the binomial N‐mixture model when the distribution of individuals among sites, or the detection model, is mis‐specified implies that checking goodness of fit is essential for sound inference about abundance. To check the assumptions we provide computationally efficient goodness of fit checks that are available in an R‐package nmixgof. However, even when a binomial N‐mixture model appears to fit the data well, estimates are not robust in the presence of overdispersion. We show that problems can occur even when estimated detection probabilities are high, and that previously reported problems with negative binomial models cannot always be diagnosed by checking the sensitivity of abundance estimates to numerical cutoff values used in likelihood computations.
1. Forests are becoming increasingly fragmented world-wide, creating forest patches with reduced area and greater exposure to human land uses along fragment edges. In this study, we predict the ...future impacts of anthropogenic edges and fragment size on the future occupancy of deadwood-dwelling fungi in boreal old-growth forest fragments. 2. We used Bayesian models fitted to empirical data to predict 40 years of occupancy dynamics of logs by a group of old-growth forest indicator fungi and two common fungi under different scenarios of clear-cutting in adjacent forest (0%, 25%, 50% and 100%) and fragment sizes (1-20 ha). 3. Small fragment size (1-3·14 ha) and intensified forestry with 50-100% clear-cutting of forest around old-growth forest fragments lead to lower predicted occupancy of old-growth indicator fungi while common generalist species like Fomitopsis pinicola increased. 4. There was a trade-off between fragment size and management, where increasing fragment size buffered the negative long-term effects from increased adjacent clear-cutting. These changes in fungal occupancy at the edge should be accounted for when working towards conservation targets for protected areas, such as the Aichi target 11. 5. Synthesis and applications. Preserve what is left — but buffer for change. Small forest fragments often represent the last vestiges of high habitat quality (i.e. species, structures) in managed forest landscapes. As effective area-based conservation measures for the long-term occupancy of old-growth fungi, small fragments need to be managed to protect species from degrading transient edge effects. Management should focus on increasing the size of conservation areas with permanent buffer zones. Alternatively, non-simultaneous adjacent clear-cutting in a way that reduces the edge effect over time (i.e. dynamic buffers) may increase the effective area and improve performance of set-asides in protecting species of special concern for conservation.
Resident birds in boreal forests can serve as indicators of habitat quality and are often species of conservation interest, particularly in multifunctional forests also used for timber production. To ...make informed forest management decisions, we must first understand which structural features provide habitats useful for resident birds. This is particularly true in winter, an understudied and critical season for their survival. The objective of this study was to establish reliable methods for monitoring bird presence and activity during winter, and to use these methods to evaluate the relative importance of stand structural features to make inferences about which features support and increase winter survival potential. Using a hybrid bioacoustic and ecoacoustic approach, we tested the ability of acoustic recordings to identify links between bird diversity and components of structural complexity, and compared these results to those from the traditional point count method. We conducted a vegetation survey, point count surveys and collected acoustic recordings from December 2019–February 2020 in 19 sites in a Swedish boreal forest. First, we compared species richness values derived from point counts and bioacoustic monitoring methods. Bioacoustic species richness was significantly higher than point count richness, although only when the time spent identifying species from recordings exceeded the time spent conducting point counts in the field. Next, we demonstrated that bioacoustic species identification yields additional metrics of bird activity that point counts cannot. We tested the response of these metrics, and point count metrics, to variables of structural heterogeneity and complexity of our sites. Almost all bioacoustic metrics increased significantly with increasing structural complexity, while point count richness and abundance did not, indicating that automated recording is more effective in identifying forest patches of high quality in winter. Lastly, using an ecoacoustic approach, we calculated six of the most common acoustic indices and tested if any could effectively reflect the bird-structure relationships described above. Two indices showed significant positive relationships to bioacoustic metrics, demonstrating their potential as biodiversity assessment proxies that respond to differences in habitat quality. This is the first winter acoustic study to monitor bird assemblages in detail; it employed both bioacoustic and multi-index ecoacoustic approaches, which provided evidence that automated acoustic recording can be an effective and superior method for monitoring resident forest birds.
•Winter is a critical period for resident birds of high conservation interest.•We compared point count, bioacoustic and ecoacoustic monitoring methods in winter.•Bioacoustic identification yielded higher bird richness than point counts.•New bioacoustic bird metrics significantly respond to structural heterogeneity.•BIO and ACI acoustic indices reflected bird assemblage metrics.
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.
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.
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.
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.
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.
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.
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