Alejandro Ruete

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.

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

Abstract 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.

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 IPCCs 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.

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

BackgroundThere 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.MethodsThe 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.ResultsCleavage 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.ConclusionsThe 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.

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.

Conservation benefits of international Aichi protection and restoration targets for future epiphyte metapopulations

1.More than half way towards the deadline for 2020 Aichi targets, a key question is whether the metapopulation dynamics of dispersal-restricted habitat specialists can be sustained under current international targets of protection and restoration. 2.We present the first metapopulation projections under scenarios of multiple Aichi biodiversity targets of protecting high quality habitats and restoring suboptimal quality habitats under management. We simulate 200 years of metapopulation dynamics of nine old-growth beech (Fagus sylvatica) associated epiphytic lichens, under a range of protection and restoration scenarios in a realistic landscape realm. 3.Protection was generally more efficient than restoration, where protection resulted in a constant increase in occupancy over time. However, projections showed that substantial increments in the number of occupied protected beech stands will most likely occur within the next 100-200 years. The time frame was dependent on species-specific dispersal restriction, occupancy levels at onset and forest-age requirements. Suboptimally restored beech stands increased lichen metapopulation sizes over a transient period and shortened the time for dispersal-restricted species to reach higher occupancy levels inside protected areas of the landscape (~85-125 years). 4.Synthesis and applications. Based on projections of metapopulation dynamics of species associated with old-growth forest we argue that a combination of protection and restoration with the shortest possible time frame for increasing occupancy is the safest strategy. This is especially important under climatic and socio-political changes that are unforeseeable over centuries. If choosing between conservation strategies, highest priority should be given to increased protection because it means larger metapopulation sizes of these species on the long-term. This article is protected by copyright. All rights reserved.

Goodness of fit checks for binomial N-mixture models

Binomial N-mixture models are commonly applied to analyze population survey data. By estimating detection probabilities, N-mixture models aim at extracting information about abundances in terms of actual 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 have hindered evaluations of their performances. We develop computationally efficient graphical goodness of fit checks and measures of overdispersion for binomial N-mixture models. These checks are illustrated in a case study, and evaluated in simulations under two scenarios. The two scenarios assume overdispersion in the abundance distribution via a negative binomial distribution or in the detection probability via a beta-binomial distribution. We evaluate the ability of the checks to detect lack of fit, and how lack of fit affects estimates of abundances. The simulations show that if the parametric assumptions are incorrect there can be severe biases in estimated abundances: negatively if there is overdispersion in abundance relative to the fitted model and positively if there is overdispersion in detection. Our goodness of fit checks performed well in detecting lack of fit when the abundance distribution is 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 in estimated abundances 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 in ecological studies that use these methods. 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 unless additional information about detection is collected.

Contrasting long‐term effects of transient anthropogenic edges and forest fragment size on generalist and specialist deadwood‐dwelling fungi

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. We used Bayesian models fitted to empirical data to predict 40years 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 (1-20ha). Small fragment size (1-314ha) 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. 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.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.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.

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

Abstract 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.

Asynchronous changes in abundance over large scales are explained by demographic variation rather than environmental stochasticity in an invasive flagellate

1.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. 2.Using a hierarchical mixed modeling approach we analyzed 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 14 years. 3.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. 4.G. semen previous years 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. 5.Synthesis: A full understanding of the mechanisms driving abundance changes across large scales can only be gained if endogenous and environmental factors are analyzed 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. This article is protected by copyright. All rights reserved.