Fecal DNA metabarcoding reveals seasonal and annual variation in willow ptarmigan diet.

Understanding spatio-temporal variation in the diet of alpine herbivores is important to predict how a changing climate will affect these species in the future. We examined the spatio-temporal variation in willow ptarmigan (Lagopus l. lagopus) diet using DNA metabarcoding of fecal pellets sampled from winter to early summer over three consecutive years. Furthermore, we assessed how snow cover and vegetation phenology affected diet variation. We also investigated sex differences in diet composition. We identified 18 important diet taxa and the genera Betula, Vaccinium and Empetrum occurred most frequently. Diet composition and richness varied within and between years. Seasonally, there was a shift from a narrow winter diet dominated by trees and dwarf shrubs to a broader spring diet with more nutritious field vegetation. This seasonal progression differed among years. The temporal variation in diet was better explained by day of year than by snow cover and vegetation phenology. Females had a more diverse diet than males, but there were no sex differences in diet composition. Our results demonstrate that metabarcoding of fecal samples provides the opportunity to assess factors affecting diet composition of species in alpine ecosystems in the context of a changing climate.

Climatic forcing and individual heterogeneity in a resident mountain bird: legacy data reveal effects on reproductive strategies.

Optimization of clutch size and timing of reproduction have substantial effects on lifetime reproductive success in vertebrates, and both individual quality and environmental variation may impact life history strategies. We tested hypotheses related to maternal investment and timing of reproduction, using 17 years (1978-1994) of individual-based life history data on willow ptarmigan (Lagopus l. lagopus, n = 290 breeding females with n = 319 breeding attempts) in central Norway. We analysed whether climatic variation and individual state variables (age and body mass) affected the number of offspring and timing of reproduction, and individual repeatability in strategies. The results suggest that willow ptarmigan share a common optimal clutch size that is largely independent of measured individual states. While we found no clear direct weather effects on clutch size, higher spring temperatures advanced onset of breeding, and early breeding was followed by an increased number of offspring. Warmer springs were positively related to maternal mass, and mass interacted with clutch size in production of hatchlings. Finally, clutch size and timing of reproduction were highly repeatable within individuals, indicating that individual quality guided trade-offs in reproductive effort. Our results demonstrate how climatic forcing and individual heterogeneity in combination influenced life history traits in a resident montane keystone species.

Recognizability bias in citizen science photographs.

Citizen science and automated collection methods increasingly depend on image recognition to provide the amounts of observational data research and management needs. Recognition models, meanwhile, also require large amounts of data from these sources, creating a feedback loop between the methods and tools. Species that are harder to recognize, both for humans and machine learning algorithms, are likely to be under-reported, and thus be less prevalent in the training data. As a result, the feedback loop may hamper training mostly for species that already pose the greatest challenge. In this study, we trained recognition models for various taxa, and found evidence for a 'recognizability bias', where species that are more readily identified by humans and recognition models alike are more prevalent in the available image data. This pattern is present across multiple taxa, and does not appear to relate to differences in picture quality, biological traits or data collection metrics other than recognizability. This has implications for the expected performance of future models trained with more data, including such challenging species.

Close to open-Factors that hinder and promote open science in ecology research and education.

The Open Science (OS) movement is rapidly gaining traction among policy-makers, research funders, scientific journals and individual scientists. Despite these tendencies, the pace of implementing OS throughout the scientific process and across the scientific community remains slow. Thus, a better understanding of the conditions that affect OS engagement, and in particular, of how practitioners learn, use, conduct and share research openly can guide those seeking to implement OS more broadly. We surveyed participants at an OS workshop hosted by the Living Norway Ecological Data Network in 2020 to learn how they perceived OS and its importance in their research, supervision and teaching. Further, we wanted to know what OS practices they had encountered in their education and what they saw as hindering or helping their engagement with OS. The survey contained scaled-response and open-ended questions, allowing for a mixed-methods approach. We obtained survey responses from 60 out of 128 workshop participants (47%). Responses indicated that usage and sharing of open data and code, as well as open access publication, were the most frequent OS practices. Only a minority of respondents reported having encountered OS in their formal education. A majority also viewed OS as less important in their teaching than in their research and supervisory roles. The respondents' suggestions for what would facilitate greater OS engagement in the future included knowledge, guidelines, and resources, but also social and structural support. These are aspects that could be strengthened by promoting explicit implementation of OS practices in higher education and by nurturing a more inclusive and equitable OS culture. We argue that incorporating OS in teaching and learning of science can yield substantial benefits to the research community, student learning, and ultimately, to the wider societal objectives of science and higher education.

Land cover type modulates the distribution of litter in a Nordic cultural landscape.

Litter pollution is a global environmental problem that occurs in virtually all ecosystems. Scientific research on anthropogenic litter and its environmental impacts focusses predominantly on plastics and the marine environment. Little empirical knowledge exists about the distribution and ecological impacts of litter in terrestrial environments, where most litter is produced. To start closing that knowledge gap, we investigated the distribution of litter in a cultural landscape in central Norway and in relation to land cover types. We registered and collected litter in 110 survey plots that were randomly stratified across various land cover types. Our results show that land cover type modulates the occurrence, abundance, fragments size, and that litter is most present and abundant in or near land cover types associated with high human activities. Plastic was by far the most common litter material type, although the litter community (in terms of materials type) was not independent from land cover type. This knowledge can help to inform and optimize litter management and clean-up activities in terrestrial landscapes. How and to what extent the spatial structure of the litter community mediates ecological effects across various land cover types remains unknown to a large extent and warrants further study.

ROBITT: A tool for assessing the risk-of-bias in studies of temporal trends in ecology.

Aggregated species occurrence and abundance data from disparate sources are increasingly accessible to ecologists for the analysis of temporal trends in biodiversity. However, sampling biases relevant to any given research question are often poorly explored and infrequently reported; this can undermine statistical inference. In other disciplines, it is common for researchers to complete 'risk-of-bias' assessments to expose and document the potential for biases to undermine conclusions. The huge growth in available data, and recent controversies surrounding their use to infer temporal trends, indicate that similar assessments are urgently needed in ecology.We introduce ROBITT, a structured tool for assessing the 'Risk-Of-Bias In studies of Temporal Trends in ecology'. ROBITT has a similar format to its counterparts in other disciplines: it comprises signalling questions designed to elicit information on the potential for bias in key study domains. In answering these, users will define study inferential goal(s) and relevant statistical target populations. This information is used to assess potential sampling biases across domains relevant to the research question (e.g. geography, taxonomy, environment), and how these vary through time. If assessments indicate biases, then users must clearly describe them and/or explain what mitigating action will be taken.Everything that users need to complete a ROBITT assessment is provided: the tool, a guidance document and a worked example. Following other disciplines, the tool and guidance document were developed through a consensus-forming process across experts working in relevant areas of ecology and evidence synthesis.We propose that researchers should be strongly encouraged to include a ROBITT assessment when publishing studies of biodiversity trends, especially when using aggregated data. This will help researchers to structure their thinking, clearly acknowledge potential sampling issues, highlight where expert consultation is required and provide an opportunity to describe data checks that might go unreported. ROBITT will also enable reviewers, editors and readers to establish how well research conclusions are supported given a dataset combined with some analytical approach. In turn, it should strengthen evidence-based policy and practice, reduce differing interpretations of data and provide a clearer picture of the uncertainties associated with our understanding of reality.

Quantifying the checks and balances of collaborative governance systems for adaptive carnivore management.

Recovering or threatened carnivore populations are often harvested to minimise their impact on human activities, such as livestock farming or game hunting. Increasingly, harvest quota decisions involve a set of scientific, administrative and political institutions operating at national and sub-national levels whose interactions and collective decision-making aim to increase the legitimacy of management and ensure population targets are met. In practice, however, assessments of how quota decisions change between these different actors and what consequences these changes have on population trends are rare.We combine a state-space population modelling approach with an analysis of quota decisions taken at both regional and national levels between 2007 and 2018 to build a set of decision-making models that together predict annual harvest quota values for Eurasian lynx (Lynx lynx) in Norway.We reveal a tendency for administrative decision-makers to compensate for consistent quota increases by political actors, particularly when the lynx population size estimate is above the regional target. Using population forecasts based on the ensemble of decision-making models, we show that such buffering of political biases ensures lynx population size remains close to regional and national targets in the long term.Our results go beyond the usual qualitative assessment of collaborative governance systems for carnivore management, revealing a system of checks and balances that, in the case of lynx in Norway, ensures both multi-stakeholder participation and sustainable harvest quotas. Nevertheless, we highlight important inter-regional differences in decision-making and population forecasts, the socio-ecological drivers of which need to be better understood to prevent future population declines. Synthesis and applications. Our work analyses the sequence of decisions leading to yearly quotas for lynx harvest in Norway, highlighting the collaborative and structural processes that together shape harvest sustainability. In doing so, we provide a predictive framework to evaluate participatory decision-making processes in wildlife management, paving the way for scientists and decision-makers to collaborate more widely in identifying where decision biases might lie and how institutional arrangements can be optimised to minimise them. We emphasise, however, that this is only possible if wildlife management decisions are documented and transparent.

Maximizing citizen scientists' contribution to automated species recognition.

Technological advances and data availability have enabled artificial intelligence-driven tools that can increasingly successfully assist in identifying species from images. Especially within citizen science, an emerging source of information filling the knowledge gaps needed to solve the biodiversity crisis, such tools can allow participants to recognize and report more poorly known species. This can be an important tool in addressing the substantial taxonomic bias in biodiversity data, where broadly recognized, charismatic species are highly over-represented. Meanwhile, the recognition models are trained using the same biased data, so it is important to consider what additional images are needed to improve recognition models. In this study, we investigated how the amount of training data influenced the performance of species recognition models for various taxa. We utilized a large citizen science dataset collected in Norway, where images are added independently from identification. We demonstrate that while adding images of currently under-represented taxa will generally improve recognition models more, there are important deviations from this general pattern. Thus, a more focused prioritization of data collection beyond the basic paradigm that "more is better" is likely to significantly improve species recognition models and advance the representativeness of biodiversity data.

Drivers and consequences of partial migration in an alpine bird species.

Partial migration, where a portion of the population migrates between winter and summer (breeding) areas and the rest remain year-round resident, is a common phenomenon across several taxonomic groups. Several hypotheses have been put forward to explain why some individuals migrate while others stay resident, as well as the fitness consequences of the different strategies. Yet, the drivers and consequences of the decision to migrate or not are poorly understood.We used data from radio-tagged female (n = 73) willow ptarmigan Lagopus lagopus in an alpine study area in Central Norway to test if (i) the decision to migrate was dependent on individual state variables (age and body weight), (ii) individuals repeated migratory decisions between seasons, and (iii) the choice of migratory strategy was related to reproductive success.Partially supporting our prediction that migratory strategy depends on individual state, we found that juvenile birds with small body sizes were more likely to migrate, whereas large juveniles remained resident. For adult females, we found no relationship between the decision to migrate or stay resident and body weight. We found evidence for high individual repeatability of migratory decision between seasons. Migratory strategy did not explain variation in clutch size or nest fate among individuals, suggesting no direct influence of the chosen strategy on reproductive success.Our results indicate that partial migration in willow ptarmigan is related to juvenile body weight, and that migratory behavior becomes a part of the individual life history as a fixed strategy. Nesting success was not affected by migratory strategy in our study population, but future studies should assess other traits to further test potential fitness consequences.

Rewriting results sections in the language of evidence.

Despite much criticism, black-or-white null-hypothesis significance testing with an arbitrary P-value cutoff still is the standard way to report scientific findings. One obstacle to progress is likely a lack of knowledge about suitable alternatives. Here, we suggest language of evidence that allows for a more nuanced approach to communicate scientific findings as a simple and intuitive alternative to statistical significance testing. We provide examples for rewriting results sections in research papers accordingly. Language of evidence has previously been suggested in medical statistics, and it is consistent with reporting approaches of international research networks, like the Intergovernmental Panel on Climate Change, for example. Instead of re-inventing the wheel, ecology and evolution might benefit from adopting some of the 'good practices' that exist in other fields.

Heuristics for the sustainable harvest of wildlife in stochastic social-ecological systems.

Sustainable wildlife harvest is challenging due to the complexity of uncertain social-ecological systems, and diverse stakeholder perspectives of sustainability. In these systems, semi-complex stochastic simulation models can provide heuristics that bridge the gap between highly simplified theoretical models and highly context-specific case-studies. Such heuristics allow for more nuanced recommendations in low-knowledge contexts, and an improved understanding of model sensitivity and transferability to novel contexts. We develop semi-complex Management Strategy Evaluation (MSE) models capturing dynamics and variability in ecological processes, monitoring, decision-making, and harvest implementation, under a diverse range of contexts. Results reveal the fundamental challenges of achieving sustainability in wildlife harvest. Environmental contexts were important in determining optimal harvest parameters, but overall, evaluation contexts more strongly influenced perceived outcomes, optimal harvest parameters and optimal harvest strategies. Importantly, simple composite metrics popular in the theoretical literature (e.g. focusing on maximizing yield and population persistence only) often diverged from more holistic composite metrics that include a wider range of population and harvest objectives, and better reflect the trade-offs in real world applied contexts. While adaptive harvest strategies were most frequently preferred, particularly for more complex environmental contexts (e.g. high uncertainty or variability), our simulations map out cases where these heuristics may not hold. Despite not always being the optimal solution, overall adaptive harvest strategies resulted in the least value forgone, and are likely to give the best outcomes under future climatic variability and uncertainty. This demonstrates the potential value of heuristics for guiding applied management.

Open Data Practices among Users of Primary Biodiversity Data.

Presence-only biodiversity data are increasingly relied on in biodiversity, ecology, and conservation research, driven by growing digital infrastructures that support open data sharing and reuse. Recent reviews of open biodiversity data have clearly documented the value of data sharing, but the extent to which the biodiversity research community has adopted open data practices remains unclear. We address this question by reviewing applications of presence-only primary biodiversity data, drawn from a variety of sources beyond open databases, in the indexed literature. We characterize how frequently researchers access open data relative to data from other sources, how often they share newly generated or collated data, and trends in metadata documentation and data citation. Our results indicate that biodiversity research commonly relies on presence-only data that are not openly available and neglects to make such data available. Improved data sharing and documentation will increase the value, reusability, and reproducibility of biodiversity research.

Coexistence of large mammals and humans is possible in Europe's anthropogenic landscapes.

A critical question in the conservation of large mammals in the Anthropocene is to know the extent to which they can tolerate human disturbance. Surprisingly, little quantitative data is available about large-scale effects of human activity and land use on their broad scale distribution in Europe. In this study, we quantify the relative importance of human land use and protected areas as opposed to biophysical constraints on large mammal distribution. We analyze data on large mammal distribution to quantify the relative effect of anthropogenic variables on species' distribution as opposed to biophysical constraints. We finally assess the effect of anthropogenic variables on the size of the species' niche by simulating a scenario where we assumed no anthropogenic pressure on the landscape. Results show that large mammal distribution is primarily constrained by biophysical constraints rather than anthropogenic variables. This finding offers grounds for cautious optimism concerning wildlife conservation in the Anthropocene.

LOUPING-ILL VIRUS SEROSURVEY OF WILLOW PTARMIGAN (LAGOPUS LAGOPUS LAGOPUS) IN NORWAY.

In Norway, the Willow Ptarmigan (Lagopus lagopus lagopus) is experiencing population declines and is nationally Red Listed as Near Threatened. Although disease has not generally been regarded as an important factor behind population fluctuations for Willow Ptarmigan in Norway, disease occurrence has been poorly investigated. Both louping-ill virus (LIV) and the closely related tick-borne encephalitis virus are found along the southern part of the Norwegian coast. We assessed whether and where Norwegian Willow Ptarmigan populations have been infected with LIV. We expected to find infected individuals in populations in the southernmost part of the country. We did not expect to find infected individuals in populations further north and at higher altitudes because of the absence of the main vector, the sheep tick (Ixodes ricinus). We collected serum samples on Nobuto filter paper and used a hemagglutination inhibition assay for antibodies against LIV. We collected data at both local and country-wide levels. For local sampling, we collected and analyzed 87 hunter-collected samples from one of the southernmost Willow Ptarmigan populations in Norway. Of these birds, only three positives (3.4%) were found. For the country-wide sampling, we collected serum samples from 163 Willow Ptarmigan carcasses submitted from selected locations all over the country. Of these birds, 32% (53) were seropositive for LIV or a cross-reacting virus. Surprisingly, we found seropositive individuals from locations across the whole country, including outside the known distribution of the sheep tick. These results suggest that either LIV or a cross-reacting virus infects ptarmigan in large parts of Norway, including at high altitudes and latitudes.

Impacts of predator-mediated interactions along a climatic gradient on the population dynamics of an alpine bird.

According to classic theory, species' population dynamics and distributions are less influenced by species interactions under harsh climatic conditions compared to under more benign climatic conditions. In alpine and boreal ecosystems in Fennoscandia, the cyclic dynamics of rodents strongly affect many other species, including ground-nesting birds such as ptarmigan. According to the 'alternative prey hypothesis' (APH), the densities of ground-nesting birds and rodents are positively associated due to predator-prey dynamics and prey-switching. However, it remains unclear how the strength of these predator-mediated interactions change along a climatic harshness gradient in comparison with the effects of climatic variation. We built a hierarchical Bayesian model to estimate the sensitivity of ptarmigan populations to interannual variation in climate and rodent occurrence across Norway during 2007-2017. Ptarmigan abundance was positively linked with rodent occurrence, consistent with the APH. Moreover, we found that the link between ptarmigan abundance and rodent dynamics was strongest in colder regions. Our study highlights how species interactions play an important role in population dynamics of species at high latitudes and suggests that they can become even more important in the most climatically harsh regions.

Survival and cause-specific mortality of harvested willow ptarmigan (Lagopus lagopus) in central Norway.

Survival is a key demographic component that often varies as a result of human activities such as recreational harvest. Detailed understanding of seasonal variation in mortality patterns and the role of various risk factors is thus crucial for understanding the link between environmental variation and wildlife population dynamics and to design sustainable harvest management systems. Here, we report from a detailed seasonal and cause-specific decomposition of mortality risks in willow ptarmigan (Lagopus lagopus) in central Norway. The analyses are based on radio-collared (n = 188) birds that were monitored across all seasons, and we used time-to-event models for competing risks to estimate mortality patterns. Overall, annual survival was estimated at 0.43 (SE: 0.04), with no distinct difference among years (2015/16 to 2018/19) or between sexes. Analysis of mortality risk factors revealed that on the annual basis, the risk of harvest mortality was lower than the risk of dying from natural causes. However, during the autumn harvest season (September-November), survival was low and the dominating cause of mortality was harvest. During winter (December-March) and spring seasons (April-May), survival was in general high and did not vary between males and females. However, during the spring season, juveniles (i.e., birds born last year) of both sexes had lower survival than adults, potentially because they are more prone to predation. During the summer season (June-August), females experienced a higher hazard than males, underlining the greater parental investment of females during egg production, incubation, and chick rearing compared to males. Our analyses provide unique insight into demographic and seasonal patterns in willow ptarmigan mortality risks in a harvested population and revealed a complex interplay across seasons, risk factors, and demographic classes. Such insight is valuable when designing sustainable management plans in a world undergoing massive environmental perturbations.

Hunting strategies to increase detection of chronic wasting disease in cervids.

The successful mitigation of emerging wildlife diseases may involve controversial host culling. For livestock, 'preemptive host culling' is an accepted practice involving the removal of herds with known contact to infected populations. When applied to wildlife, this proactive approach comes in conflict with biodiversity conservation goals. Here, we present an alternative approach of 'proactive hunting surveillance' with the aim of early disease detection that simultaneously avoids undesirable population decline by targeting demographic groups with (1) a higher likelihood of being infected and (2) a lower reproductive value. We applied this harvesting principle to populations of reindeer to substantiate freedom of chronic wasting disease (CWD) infection. Proactive hunting surveillance reached 99% probability of freedom from infection (<4 reindeer infected) within 3-5 years, in comparison to ~10 years using ordinary harvest surveillance. However, implementation uncertainties linked to social issues appear challenging also with this kind of host culling.