An artificial bird nest experiment in urban environments: Lessons from a school‐based citizen science programme

Maintaining suitable vegetation within urban environments is crucial for wildlife conservation in the face of anthropogenic habitat change. Here, we report on a citizen science project, involving students from seven schools across south‐eastern Australia, that investigated the effectiveness of urban vegetation as habitat for bird nests. The ‘nest concealment hypothesis’ posits that vegetation should obscure the nest from predator detection, thus reducing the likelihood of predation. To test this, participating school‐aged citizen scientists constructed artificial nests, which were placed in garden trees within school grounds and monitored for signs of predation. We found no evidence to support the nest concealment hypothesis, with no relationship between the density of vegetation immediately surrounding a nest and its likelihood of predation (binomial model:  = 1.714, P = 0.190). It was observed that 80% of the nests experienced predation. This aligns with mounting evidence suggesting that other factors, such as olfaction and adult defence, may be more important factors in the protection of bird nests. It is important to note that artificial nests are unreliable, and therefore, the veracity of the overall conclusions is limited. However, in conducting this experiment, we demonstrate the suitability of this method as a school‐based citizen science activity. This study exemplifies that field‐based experiments can used to engage future generations with conservation science.     

COVID‐19 lockdown measures impacted citizen science hedgehog observation numbers in Bavaria,Germany

The COVID‐19 pandemic has led to temporary changes in human–animal interactions due to changes in human activities. Here, we report on a surge in hedgehog observations during the first COVID‐19 lockdown in Germany in 2020, on the citizen science Web portal “Igel in Bayern” (Hedgehogs in Bavaria) in Germany. This increase in comparison with previous years was attributed to an increase in the number of people reporting hedgehog observations, rather than an increase in the number of hedgehog observations made by each observer. Additionally, in contrast to other studies on the effects of a COVID‐19 lockdown on observations recorded by citizen science projects, the share of observations made in more urbanized areas during the lockdown time was not higher than the change observed in less urbanized areas. This is possibly a result of the differences in COVID‐19 measures between Germany and other countries where preceding studies were carried out, in particular the lack of measures limiting traveling outdoor activities for citizens.     

Equivalence of citizen science and scientific data for modelling species distribution of birds from a tropical savanna

The Wallacean deficit continues to be a challenge to species distribution modelling. Although some authors have suggested that data collected by citizen scientists can be relevant for a better understanding of biodiversity, to our knowledge, no work has quantitatively tested the equivalence between scientific and citizen science data. Here, we investigate the hypothesis that data collected by citizen scientists can be equivalent to data collected by professional scientists when generating species spatial distribution models. For 42 bird species in the Cerrado region we generated and compared species distribution models based on three data sources: (1) scientific data, (2) citizen science data and (3) sample size corrected citizen science data. To test our hypothesis, we compared the equivalence of these datasets. We rejected the hypothesis of equivalence for about one-third (38%) of the evaluated species, revealing that, for most of the species considered, the models generated were equivalent irrespective of the data set used. The distances between centroids of the models that were equivalent were on average smaller than the distances between non-equivalent models. Also, the direction of change in the models showed no pattern, with no trend towards more populated regions. Our results show that the use of data collected by citizen scientists can be an ally in filling the Wallacean deficit gap. In fact, the lack of use of this wide range of data collected by citizen scientists seems to be an unjustified caution. We indicate the potential of using citizen science data for modelling the distribution of species, mainly due to the large set of data collected, which is impracticable for scientists alone to collect. Conservation measures will be favoured by the union of professional and amateur data, aiming for a better understanding of species distribution and, consequently, biodiversity conservation.     

Grass Gazers: Using citizen science as a tool to facilitate practical and online science learning for secondary school students during the COVID‐19 lockdown

The coronavirus disease of 2019 (COVID‐19) pandemic has impacted educational systems worldwide during 2020, including primary and secondary schooling. To enable students of a local secondary school in Brisbane, Queensland, to continue with their practical agricultural science learning and facilitate online learning, a “Grass Gazers” citizen science scoping project was designed and rapidly implemented as a collaboration between the school and a multidisciplinary university research group focused on pollen allergy. Here, we reflect on the process of developing and implementing this project from the perspective of the school and the university. A learning package including modules on pollen identification, tracking grass species, measuring field greenness, using a citizen science data entry platform, forensic palynology, as well as video guides, risk assessment and feedback forms were generated. Junior agriculture science students participated in the learning via online lessons and independent data collection in their own local neighborhood and/or school grounds situated within urban environments. The university research group and school coordinator, operating in their own distributed work environments, had to develop, source, adopt, and/or adapt material rapidly to meet the unique requirements of the project. The experience allowed two‐way knowledge exchange between the secondary and tertiary education sectors. Participating students were introduced to real‐world research and were able to engage in outdoor learning during a time when online, indoor, desk‐based learning dominated their studies. The unique context of restrictions imposed by the social isolation policies, as well as government Public Health and Department of Education directives, allowed the team to respond by adapting teaching and research activity to develop and trial learning modules and citizen science tools. The project provided a focus to motivate and connect teachers, academic staff, and school students during a difficult circumstance. Extension of this citizen project for the purposes of research and secondary school learning has the potential to offer ongoing benefits for grassland ecology data acquisition and student exposure to real‐world science.     

Birds rarely hybridize: A citizen science approach to estimating rates of hybridization in the wild*

The rate of hybridization among taxa is a central consideration in any discussion of speciation, but rates of hybridization are difficult to estimate in most wild populations of animals. We used a successful citizen science dataset, eBird, to estimate the rates of hybridization for wild birds in the United States. We calculated the frequency at which hybrid individuals belonging to different species, families, and orders of birds were observed. Between 1 January 2010 and 31 December 2018, a total of 334,770,194 species records were reported to eBird within the United States. Of this total, 212,875 or 0.064% were reported as hybrids. This estimate is higher than the rate of hybridization (0.00167%) reported by Mayr based on impressions from a career studying museum specimens. However, if the 10 most influential hybrid species are removed from the eBird dataset, the rate of hybridization decreases substantially to about 0.009%. We conclude that the rate of hybridization for individuals in most bird species is extremely low, even though the potential for birds to produce fertile offspring through hybrid crosses is high. These findings indicate that there is strong prezygotic selection working in most avian species.     

Identifying and correcting spatial bias in opportunistic citizen science data for wild ungulates in Norway

Many publications make use of opportunistic data, such as citizen science observation data, to infer large‐scale properties of species’ distributions. However, the few publications that use opportunistic citizen science data to study animal ecology at a habitat level do so without accounting for spatial biases in opportunistic records or using methods that are difficult to generalize. In this study, we explore the biases that exist in opportunistic observations and suggest an approach to correct for them. We first examined the extent of the biases in opportunistic citizen science observations of three wild ungulate species in Norway by comparing them to data from GPS telemetry. We then quantified the extent of the biases by specifying a model of the biases. From the bias model, we sampled available locations within the species’ home range. Along with opportunistic observations, we used the corrected availability locations to estimate a resource selection function (RSF). We tested this method with simulations and empirical datasets for the three species. We compared the results of our correction method to RSFs obtained using opportunistic observations without correction and to RSFs using GPS‐telemetry data. Finally, we compared habitat suitability maps obtained using each of these models. Opportunistic observations are more affected by human access and visibility than locations derived from GPS telemetry. This has consequences for drawing inferences about species’ ecology. Models naïvely using opportunistic observations in habitat‐use studies can result in spurious inferences. However, sampling availability locations based on the spatial biases in opportunistic data improves the estimation of the species’ RSFs and predicted habitat suitability maps in some cases. This study highlights the challenges and opportunities of using opportunistic observations in habitat‐use studies. While our method is not foolproof it is a first step toward unlocking the potential of opportunistic citizen science data for habitat‐use studies.     

Correcting for bias in distribution modelling for rare species using citizen science data

Aim

To improve the accuracy of inferences on habitat associations and distribution patterns of rare species by combining machine‐learning, spatial filtering and resampling to address class imbalance and spatial bias of large volumes of citizen science data.

Innovation

Modelling rare species’ distributions is a pressing challenge for conservation and applied research. Often, a large number of surveys are required before enough detections occur to model distributions of rare species accurately, resulting in a data set with a high proportion of non‐detections (i.e. class imbalance). Citizen science data can provide a cost‐effective source of surveys but likely suffer from class imbalance. Citizen science data also suffer from spatial bias, likely from preferential sampling. To correct for class imbalance and spatial bias, we used spatial filtering to under‐sample the majority class (non‐detection) while maintaining all of the limited information from the minority class (detection). We investigated the use of spatial under‐sampling with randomForest models and compared it to common approaches used for imbalanced data, the synthetic minority oversampling technique (SMOTE), weighted random forest and balanced random forest models. Model accuracy was assessed using kappa, Brier score and AUC. We demonstrate the method by evaluating habitat associations and seasonal distribution patterns using citizen science data for a rare species, the tricoloured blackbird (Agelaius tricolor).

Main Conclusions

Spatial under‐sampling increased the accuracy of each model and outperformed the approach typically used to direct under‐sampling in the SMOTE algorithm. Our approach is the first to characterize winter distribution and movement of tricoloured blackbirds. Our results show that tricoloured blackbirds are positively associated with grassland, pasture and wetland habitats, and negatively associated with high elevations or evergreen forests during both winter and breeding seasons. The seasonal differences in distribution indicate that individuals move to the coast during the winter, as suggested by historical accounts.

     

Dispatches from the neighborhood watch: Using citizen science and field survey data to document color morph frequency in space and time

Heritable color polymorphisms have a long history of study in evolutionary biology, though they are less frequently examined today than in the past. These systems, where multiple discrete, visually identifiable color phenotypes co‐occur in the same population, are valuable for tracking evolutionary change and ascertaining the relative importance of different evolutionary mechanisms. Here, we use a combination of citizen science data and field surveys in the Great Lakes region of North America to identify patterns of color morph frequencies in the eastern gray squirrel (Sciurus carolinensis). Using over 68,000 individual squirrel records from both large and small spatial scales, we identify the following patterns: (a) the melanistic (black) phenotype is often localized but nonetheless widespread throughout the Great Lakes region, occurring in all states and provinces sampled. (b) In Ohio, where intensive surveys were performed, there is a weak but significantly positive association between color morph frequency and geographic proximity of populations. Nonetheless, even nearby populations often had radically different frequencies of the melanistic morph, which ranged from 0% to 96%. These patterns were mosaic rather than clinal. (c) In the Wooster, Ohio population, which had over eight years of continuous data on color morph frequency representing nearly 40,000 records, we found that the frequency of the melanistic morph increased gradually over time on some survey routes but decreased or did not change over time on others. These differences were statistically significant and occurred at very small spatial scales (on the order of hundreds of meters). Together, these patterns are suggestive of genetic drift as an important mechanism of evolutionary change in this system. We argue that studies of color polymorphism are still quite valuable in advancing our understanding of fundamental evolutionary processes, especially when coupled with the growing availability of data from citizen science efforts.     

Counting Cats: The integration of expert and citizen science data for unbiased inference of population abundance

Free‐roaming animal populations are hard to count, and professional experts are a limited resource. There is vast untapped potential in the data collected by nonprofessional scientists who volunteer their time to population monitoring, but citizen science (CS) raises concerns around data quality and biases. A particular concern in abundance modeling is the presence of false positives that can occur due to misidentification of nontarget species. Here, we introduce Integrated Abundance Models (IAMs) that integrate citizen and expert data to allow robust inference of population abundance meanwhile accounting for biases caused by misidentification. We used simulation experiments to confirm that IAMs successfully remove the inflation of abundance estimates caused by false‐positive detections and can provide accurate estimates of both bias and abundance. We illustrate the approach with a case study on unowned domestic cats, which are commonly confused with owned, and infer their abundance by analyzing a combination of CS data and expert data. Our case study finds that relying on CS data alone, either through simple summation or via traditional modeling approaches, can vastly inflate abundance estimates. IAMs provide an adaptable framework, increasing the opportunity for further development of the approach, tailoring to specific systems and robust use of CS data.     

Acoustic facilitation of object movement detection during self-motion

In humans, as well as most animal species, perception of object motion is critical to successful interaction with the surrounding environment. Yet, as the observer also moves, the retinal projections of the various motion components add to each other and extracting accurate object motion becomes computationally challenging. Recent psychophysical studies have demonstrated that observers use a flow-parsing mechanism to estimate and subtract self-motion from the optic flow field. We investigated whether concurrent acoustic cues for motion can facilitate visual flow parsing, thereby enhancing the detection of moving objects during simulated self-motion. Participants identified an object (the target) that moved either forward or backward within a visual scene containing nine identical textured objects simulating forward observer translation. We found that spatially co-localized, directionally congruent, moving auditory stimuli enhanced object motion detection. Interestingly, subjects who performed poorly on the visual-only task benefited more from the addition of moving auditory stimuli. When auditory stimuli were not co-localized to the visual target, improvements in detection rates were weak. Taken together, these results suggest that parsing object motion from self-motion-induced optic flow can operate on multisensory object representations.     

How to work with children and animals: A guide for school‐based citizen science in wildlife research

Engaging school students in wildlife research through citizen science projects can be a win–win for scientists and educators. Not only does it provide a way for scientists to gather new data, but it can also contribute to science education and help younger generations become more environmentally aware. However, wildlife research can be challenging in the best of circumstances, and there are few guidelines available to help scientists create successful citizen science projects for school students. This paper explores the opportunities and challenges faced when developing school‐based citizen science projects in wildlife research by synthesising two sources of information. First, we conducted a small, school‐based citizen science project that investigated the effects of supplementary feeding on urban birds as a case study. Second, we reviewed the literature to develop a database of school‐based citizen science projects that address questions in wildlife ecology and conservation. Based on these activities, we present five lessons for scientists considering a school‐based citizen science project. Overall, we found that school‐based citizen science projects must be carefully designed to ensure reliable data are collected, students remain engaged, and the project is achievable under the logistical constraints presented by conducting wildlife research in a school environment. Ultimately, we conclude that school‐based citizen science projects can be a powerful way of collecting wildlife data while also contributing to the education and development of environmentally aware students.     

基于不同网格尺度福州主城区鸟类多样性与景观特征的关系研究

理解城市鸟类多样性与景观特征的关系对城市生物多样性保护和可持续发展具有重要意义。通过爬取中国观鸟记录中心网站2020年福州主城区436份观鸟报告数据计算鸟类丰富度指数(S)、Shannon-Wiener多样性指数(H)和Simpson多样性指数(D);基于谷歌地球引擎和高分辨率Worldview影像量化景观特征因子;在此基础上,采用Mann-Whitney U检验了两个网格尺度(300 m和1000 m)下S、H和D指数的差异性;运用广义线性模型探究了两个尺度下影响鸟类多样性指数的关键景观因子及其重要性。结果表明：(1)2020年研究区内共观测到242种鸟类,隶属19目59科,雀形目鸟类为优势种;数量占比从高到低依次为留鸟、冬候鸟、旅鸟和夏候鸟,分别为63.53%、25.83%、6.71%和3.93%;(2)两个尺度下鸟类多样性指数差异明显,1000 m尺度下S和H指数均显著高于300 m尺度(0.05相似文献   

The evolution of embryonic patterning mechanisms in animals

Animals exhibit an enormous diversity of life cycles and larval morphologies. The developmental basis for this diversity is not well understood. It is clear, however, that mechanisms of pattern formation in early embryos differ significantly among and within groups of animals. These differences show surprisingly little correlation with phylogenetic relationships; instead, many are correlated with ecological factors, such as changes in life histories.     

A unique role for citizen science in ecological restoration: a case study in streams

Citizen science has the potential to generate valuable biologic data for use in restoration monitoring, while also providing a unique opportunity for public participation in local restoration projects. In this article, we describe and evaluate a citizen science program designed to monitor the effect of stream restoration construction disturbance on the macroinvertebrate community. We present the results of a 7‐year stream restoration study conducted by citizen scientists utilizing a Before‐After‐Control‐Impact (BACI) design. Trait‐based macroinvertebrate data showed a strong response to restoration construction disturbance and return to pre‐restoration conditions within 2 years. The findings of this study suggest that citizen science can generate meaningful BACI‐oriented data about ecological restoration; however, until more research is conducted, citizen data should only be used to augment professional data intended to demonstrate restoration success.     

A citizen science approach to long-term monitoring of humpback whales (Megaptera novaeangliae) off Sydney,Australia

The Cape Solander Whale Migration Study is a citizen science project that annually counts northward migrating humpback whales (Megaptera novaeangliae) off Cape Solander, Sydney, Australia. Dedicated observers have compiled a 20-year data set (1997–2017) of shore-based observations from Cape Solander's high vantage point. Using this long-term data set collected by citizen scientists, we sought to estimate the humpback whale population trend as it continues to recover postexploitation. We estimated an exponential growth rate of 0.099 (95% CI = 0.079–0.119) using a generalized linear model, based on observer effort (number of observation days) and number of whales observed, equating to 10% per annum growth in sightings since 1997. We found that favorable weather conditions for spotting whales off Cape Solander consisted of winds <30 km/hr from a southerly through a north westerly direction. Incidental observations of other cetacean species included the endangered blue whale (Balaenoptera musculus) and data deficient species such as killer whales (Orcinus orca) and false killer whales (Pseudorca crassidens). Citizen science-based studies can provide a cost-effective approach to monitoring wildlife over the time necessary to detect change in a population. Information obtained from citizen science projects like this may help inform policy makers responsible for State and Federal protection of cetaceans in Australian waters and beyond.     

Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers

Citizen science initiatives have been increasingly used by researchers as a source of occurrence data to model the distribution of alien species. Since citizen science presence-only data suffer from some fundamental issues, efforts have been made to combine these data with those provided by scientifically structured surveys. Surprisingly, only a few studies proposing data integration evaluated the contribution of this process to the effective sampling of species' environmental niches and, consequently, its effect on model predictions on new time intervals. We relied on niche overlap analyses, machine learning classification algorithms and ecological niche models to compare the ability of data from citizen science and scientific surveys, along with their integration, in capturing the realized niche of 13 invasive alien species in Italy. Moreover, we assessed differences in current and future invasion risk predicted by each data set under multiple global change scenarios. We showed that data from citizen science and scientific surveys captured similar species niches though highlighting exclusive portions associated with clearly identifiable environmental conditions. In terrestrial species, citizen science data granted the highest gain in environmental space to the pooled niches, determining an increased future biological invasion risk. A few aquatic species modelled at the regional scale reported a net loss in the pooled niches compared to their scientific survey niches, suggesting that citizen science data may also lead to contraction in pooled niches. For these species, models predicted a lower future biological invasion risk. These findings indicate that citizen science data may represent a valuable contribution to predicting future spread of invasive alien species, especially within national-scale programmes. At the same time, citizen science data collected on species poorly known to citizen scientists, or in strictly local contexts, may strongly affect the niche quantification of these taxa and the prediction of their future biological invasion risk.