Maximizing citizen scientists’ contribution to automated species recognition

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Spatial distribution of biodiversity citizen science in a natural area depends on area accessibility and differs from other recreational area use

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Recognizability bias in citizen science photographs

Citizen science and automated collection methods increasinglydepend on image recognition to provide the amountsof observational data research and management needs.Recognition models, meanwhile, also require large amounts ofdata from these sources, creating a feedback loop between themethods and tools. Species that are harder to recognize, bothfor humans and machine learning algorithms, are likely to beunder-reported, and thus be less prevalent in the trainingdata. As a result, the feedback loop may hamper trainingmostly for species that already pose the greatest challenge. Inthis study, we trained recognition models for various taxa, andfound evidence for a‘recognizability bias’, where species thatare more readily identified by humans and recognitionmodels alike are more prevalent in the available image data.This pattern is present across multiple taxa, and does notappear to relate to differences in picture quality, biologicaltraits or data collection metrics other than recognizability. Thishas implications for the expected performance of futuremodels trained with more data, including such challenging species. citizen science, image recognition, machinelearning, recognizability, artificial intelligence/environmental science/ecology, Ecology, conservation and global change biologypublishedVersio

A regionally coherent ecological fingerprint of climate change, evidenced from natural history collections

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Salmonid fishes in a changing climate : the winter challenge

In the present thesis, winter mortality was linked to levels of stored energy by a field study from a northern Atlantic salmon population where population frequency distributions for specific somatic energy were compared among sampling periods. Interspecific differences in seasonal acclimatization were studied by performing common environment experiments on Atlantic salmon and establish models for thermal performance of winter acclimatized fish. These models were then compared to previously published thermal performance models for summer acclimatized salmon. Furthermore, the effect of changes in ice-cover conditions on the energy budget of the individual fish was studied using a series of common environment experiments in both laboratory and semi-natural environment. The latter experiments aimed at testing both interspecific and intraspecific variation in the effect of ice-cover. The results from these experiments were linked to winter mortality using bioenergetic modelling, where the input parameters originated from both field studies and experiments. The purpose of this conceptual modelling was not to provide quantitative predictions, but to demonstrate how environmental induced changes in the energy budget of individual fish may affect populations through the energy dependence of winter survival

Spatial diffusion modelling of juvenile Atlantic salmon (Salmo salar) shows ontogenetic increase in movement rates

For organisms with extensive ontogenetic changes in phenotypes, knowledge of how movement of individuals changes throughout life is pivotal to understanding ecological processes. Here, we study the spatial distribution of a cohort of Atlantic salmon (Salmo salar) from hatching to their third summer of juvenile life, during which they go through a fourfold change in body size. The fish originated from three distinct breeding sites and their distribution was mapped using electrofishing throughout the river at 10 sampling periods. The spatial distribution throughout ontogeny was analysed using diffusion models. The distribution changed from three distinct non-overlapping distributions centred on the individual breeding sites at the early first summer stage, to a single continuous distribution at the end of the study. The diffusion coeficient increased throughout ontogeny, and that spatial distribution was well-described using diffusion models, explaining 46-89 % of the variation. This highlights the utility of diffusion models when considering spatial habitat structure both in conservation and research.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Freswhater fish survey data resurrection

Archive for data and procedures for retrieving legacy freshwater fish survey data from published sources where raw data are lost. Data are either scrapped from grey literature (technical reports etc.) or available only in raw analog or other non-machine readable digital form. Current geographical range of interest covers Norway and Swede

Amphibian recovery after a decrease in acidic precipitation

We here report the first sign of amphibian recovery after a strong decline due to acidic precipitation over many decades and peaking around 1980–90. In 2010, the pH level of ponds and small lakes in two heavily acidified areas in southwestern Scandinavia (Aust-Agder and Østfold in Norway) had risen significantly at an (arithmetic) average of 0.14 since 1988–89. Parallel with the general rise in pH, amphibians (Rana temporaria, R. arvalis, Bufo bufo, Lissotriton vulgaris, and Triturus cristatus) had become significantly more common: the frequency of amphibian localities rose from 33% to 49% (n = 115), and the average number of amphibian species per locality had risen from 0.51 to 0.88. In two other (reference) areas, one with better buffering capacity (Telemark, n = 21) and the other with much less input of acidic precipitation (Nord-Trøndelag, n = 106), there were no significant changes in pH or amphibians

Participatory monitoring drives biodiversity knowledge in global protected areas

Protected areas are central in strategies to conserve biodiversity. Effective area-based conservation relies on biodiversity data, but the current biodiversity knowledge base is insufficient and limited by geographic and taxonomic biases. Public participation in biodiversity monitoring such as via community-based monitoring or citizen science increases data collection but also contributes to replicating these biases or introducing new ones. Here we examine how participatory monitoring has changed the landscape of open biodiversity knowledge in protected areas using biodiversity data shared on the Global Biodiversity Information Facility. We highlight a growing dominance of participatory monitoring within protected areas. We find that patterns in geographic, taxonomic, and threatened species coverage differ from non-participatory monitoring, suggesting complementarity between the two approaches. The relative contribution of participatory monitoring varies with characteristics of both protected areas and monitoring programs. We synthesize these results to derive context-specific strategies for extending the conservation impact of participatory biodiversity monitoring.publishedVersio

Historical abundance and spatial distributions of spawners determine juvenile habitat accessibility in salmon: implications for population dynamics and management targets

Spatial distribution of spawning may have important ramifications for population dynamics in species where early life stages suffer from low mobility and high density-dependent mortality. Here, we use time series of spatial spawning distribution in Atlantic salmon (Salmo salar) to test for density-dependent behavioural effects on the spatial utilization of spawning sites and resulting juvenile habitat availability. The probability of utilizing spawning sites in a given year increased both with increasing spawner abundance and proximity to sites used the previous year. The accessible area for juveniles increased asymptotically with both current and time-lagged spawner abundance. Several nonexclusive mechanisms may be responsible for the observed direct and lagged density dependence of spawner distributions, including social aggregation, asymmetric competition for space, local homing, and habitat modification by the previous year’s spawners. Time-lagged density-dependent spawner distributions can be predicted to reduce the realized population growth rate. If such effects are not accounted for, this may lead to a downward bias in estimates of spawning targets or other associated conservation or management measures derived from population abundance time series