Design principles for engaging and retaining virtual citizen scientists

Citizen science initiatives encourage volunteer participants to collect and interpret data and contribute to formal scientific projects. The growth of virtual citizen science (VCS), facilitated through websites and mobile applications since the mid‐2000s, has been driven by a combination of software innovations and mobile technologies, growing scientific data flows without commensurate increases in resources to handle them, and the desire of internet‐connected participants to contribute to collective outputs. However, the increasing availability of internet‐based activities requires individual VCS projects to compete for the attention of volunteers and promote their long‐term retention. We examined program and platform design principles that might allow VCS initiatives to compete more effectively for volunteers, increase productivity of project participants, and retain contributors over time. We surveyed key personnel engaged in managing a sample of VCS projects to identify the principles and practices they pursued for these purposes and led a team in a heuristic evaluation of volunteer engagement, website or application usability, and participant retention. We received 40 completed survey responses (33% response rate) and completed a heuristic evaluation of 20 VCS program sites. The majority of the VCS programs focused on scientific outcomes, whereas the educational and social benefits of program participation, variables that are consistently ranked as important for volunteer engagement and retention, were incidental. Evaluators indicated usability, across most of the VCS program sites, was higher and less variable than the ratings for participant engagement and retention. In the context of growing competition for the attention of internet volunteers, increased attention to the motivations of virtual citizen scientists may help VCS programs sustain the necessary engagement and retention of their volunteers.     

Population structure of humpback whales in the western and central South Pacific Ocean as determined by vocal exchange among populations

For cetaceans, population structure is traditionally determined by molecular genetics or photographically identified individuals. Acoustic data, however, has provided information on movement and population structure with less effort and cost than traditional methods in an array of taxa. Male humpback whales (Megaptera novaeangliae) produce a continually evolving vocal sexual display, or song, that is similar among all males in a population. The rapid cultural transmission (the transfer of information or behavior between conspecifics through social learning) of different versions of this display between distinct but interconnected populations in the western and central South Pacific region presents a unique way to investigate population structure based on the movement dynamics of a song (acoustic) display. Using 11 years of data, we investigated an acoustically based population structure for the region by comparing stereotyped song sequences among populations and years. We used the Levenshtein distance technique to group previously defined populations into (vocally based) clusters based on the overall similarity of their song display in space and time. We identified the following distinct vocal clusters: western cluster, 1 population off eastern Australia; central cluster, populations around New Caledonia, Tonga, and American Samoa; and eastern region, either a single cluster or 2 clusters, one around the Cook Islands and the other off French Polynesia. These results are consistent with the hypothesis that each breeding aggregation represents a distinct population (each occupied a single, terminal node) in a metapopulation, similar to the current understanding of population structure based on genetic and photo‐identification studies. However, the central vocal cluster had higher levels of song‐sharing among populations than the other clusters, indicating that levels of vocal connectivity varied within the region. Our results demonstrate the utility and value of using culturally transmitted vocal patterns as a way of defining connectivity to infer population structure. We suggest vocal patterns be incorporated by the International Whaling Commission in conjunction with traditional methods in the assessment of structure.     

Determining Decision Thresholds and Evaluating Indicators when Conservation Status is Measured as a Continuum

Categorization of the status of populations, species, and ecosystems underpins most conservation activities. Status is often based on how a system's current indicator value (e.g., change in abundance) relates to some threshold of conservation concern. Receiver operating characteristic (ROC) curves can be used to quantify the statistical reliability of indicators of conservation status and evaluate trade‐offs between correct (true positive) and incorrect (false positive) classifications across a range of decision thresholds. However, ROC curves assume a discrete, binary relationship between an indicator and the conservation status it is meant to track, which is a simplification of the more realistic continuum of conservation status, and may limit the applicability of ROC curves in conservation science. We describe a modified ROC curve that treats conservation status as a continuum rather than a discrete state. We explored the influence of this continuum and typical sources of variation in abundance that can lead to classification errors (i.e., random variation and measurement error) on the true and false positive rates corresponding to varying decision thresholds and the reliability of change in abundance as an indicator of conservation status, respectively. We applied our modified ROC approach to an indicator of endangerment in Pacific salmon (Oncorhynchus nerka) (i.e., percent decline in geometric mean abundance) and an indicator of marine ecosystem structure and function (i.e., detritivore biomass). Failure to treat conservation status as a continuum when choosing thresholds for indicators resulted in the misidentification of trade‐offs between true and false positive rates and the overestimation of an indicator's reliability. We argue for treating conservation status as a continuum when ROC curves are used to evaluate decision thresholds in indicators for the assessment of conservation status. Determinación de Umbrales de Decisiones y Evaluación delos Indicadores cuando se Mide el Estado de de Conservación como un Continuo     

Effects of Harvesting Flowers from Shrubs on the Persistence and Abundance of Wild Shrub Populations at Multiple Spatial Extents

Abstract: Wildflower harvesting is an economically important activity of which the ecological effects are poorly understood. We assessed how harvesting of flowers affects shrub persistence and abundance at multiple spatial extents. To this end, we built a process‐based model to examine the mean persistence and abundance of wild shrubs whose flowers are subject to harvest (serotinous Proteaceae in the South African Cape Floristic Region). First, we conducted a general sensitivity analysis of how harvesting affects persistence and abundance at nested spatial extents. For most spatial extents and combinations of demographic parameters, persistence and abundance of flowering shrubs decreased abruptly once harvesting rate exceeded a certain threshold. At larger extents, metapopulations supported higher harvesting rates before their persistence and abundance decreased, but persistence and abundance also decreased more abruptly due to harvesting than at smaller extents. This threshold rate of harvest varied with species’ dispersal ability, maximum reproductive rate, adult mortality, probability of extirpation or local extinction, strength of Allee effects, and carrying capacity. Moreover, spatial extent interacted with Allee effects and probability of extirpation because both these demographic properties affected the response of local populations to harvesting more strongly than they affected the response of metapopulations. Subsequently, we simulated the effects of harvesting on three Cape Floristic Region Proteaceae species and found that these species reacted differently to harvesting, but their persistence and abundance decreased at low rates of harvest. Our estimates of harvesting rates at maximum sustainable yield differed from those of previous investigations, perhaps because researchers used different estimates of demographic parameters, models of population dynamics, and spatial extent than we did. Good demographic knowledge and careful identification of the spatial extent of interest increases confidence in assessments and monitoring of the effects of harvesting. Our general sensitivity analysis improved understanding of harvesting effects on metapopulation dynamics and allowed qualitative assessment of the probability of extirpation of poorly studied species.     

A Bayesian-weighted approach to predicting the number of newly discovered rare species

In natural ecological communities, most species are rare and thus susceptible to extinction. Consequently, the prediction and identification of rare species are of enormous value for conservation purposes. How many newly found species will be rare in the next field survey? We took a Bayesian viewpoint and used observed species abundance information in an ecological sample to develop an accurate way to estimate the number of new rare species (e.g., singletons, doubletons, and tripletons) in an additional unknown sample. A similar method has been developed for incidence-based data sets. Five seminumerical tests (3 abundance cases and 2 incidence cases) showed that our proposed Bayesian-weight estimator accurately predicted the number of new rare species with low relative bias and low relative root mean squared error and, accordingly, high accuracy. Finally, we applied the proposed estimator to 6 conservation-directed empirical data sets (3 abundance cases and 3 incidence cases) and found the prediction of new rare species was quite accurate; the 95% CI covered the true observed value very well in most cases. Our estimator performed similarly to or better than an unweighted estimator derived from Chao et al. and performed consistently better than the naïve unweighted estimator. We recommend our Bayesian-weight estimator for conservation applications, although the unweighted estimator of Chao et al. may be better under some circumstances. We provide an R package RSE (r are s pecies e stimation) at https://github.com/ecomol/RSE for implementation of the estimators.     

How the diversity of human concepts of nature affects conservation of biodiversity

Protecting nature has become a global concern. However, the very idea of nature is problematic. We examined the etymological and semantic diversity of the word used to translate nature in a conservation context in 76 of the primary languages of the world to identify the different relationships between humankind and nature. Surprisingly, the number of morphemes (distinct etymological roots) used by 7 billion people was low. Different linguistic superfamilies shared the same etymon across large cultural areas that correlate with the distribution of major religions. However, we found large differences in etymological meanings among these words, echoing the semantic differences and historical ambiguity of the contemporary European concept of nature. The principal current Western meaning of nature in environmental public policy, conservation science, and environmental ethics–that which is not a human artifact–appears to be relatively rare and recent and to contradict the vision of nature in most other cultures, including those of pre-Christian Europe. To avoid implicit cultural bias and hegemony–and thus to be globally intelligible and effective–it behooves nature conservationists to take into account this semantic diversity when proposing conservation policies and implementing conservation practices.     

Modeling Effectiveness of Gradual Increases in Source Level to Mitigate Effects of Sonar on Marine Mammals

Ramp‐up or soft‐start procedures (i.e., gradual increase in the source level) are used to mitigate the effect of sonar sound on marine mammals, although no one to date has tested whether ramp‐up procedures are effective at reducing the effect of sound on marine mammals. We investigated the effectiveness of ramp‐up procedures in reducing the area within which changes in hearing thresholds can occur. We modeled the level of sound killer whales (Orcinus orca) were exposed to from a generic sonar operation preceded by different ramp‐up schemes. In our model, ramp‐up procedures reduced the risk of killer whales receiving sounds of sufficient intensity to affect their hearing. The effectiveness of the ramp‐up procedure depended strongly on the assumed response threshold and differed with ramp‐up duration, although extending the duration of the ramp up beyond 5 min did not add much to its predicted mitigating effect. The main factors that limited effectiveness of ramp up in a typical antisubmarine warfare scenario were high source level, rapid moving sonar source, and long silences between consecutive sonar transmissions. Our exposure modeling approach can be used to evaluate and optimize mitigation procedures. Modelado de la Efectividad de los Incrementos Graduales en el Nivel de la Fuente para Mitigar Efectos de Sonar sobre Mamíferos Marinos     

Interpreting beta‐diversity components over time to conserve metacommunities in highly dynamic ecosystems

The concept of metacommunity (i.e., a set of local communities linked by dispersal) has gained great popularity among community ecologists. However, metacommunity research mostly addresses questions on spatial patterns of biodiversity at the regional scale, whereas conservation planning requires quantifying temporal variation in those metacommunities and the contributions that individual (local) sites make to regional dynamics. We propose that recent advances in diversity‐partitioning methods may allow for a better understanding of metacommunity dynamics and the identification of keystone sites. We used time series of the 2 components of beta diversity (richness and replacement) and the contributions of local sites to these components to examine which sites controlled source‐sink dynamics in a highly dynamic model system (an intermittent river). The relative importance of the richness and replacement components of beta diversity fluctuated over time, and sample aggregation led to underestimation of beta diversity by up to 35%. Our literature review revealed that research on intermittent rivers would benefit greatly from examination of beta‐diversity components over time. Adequately appraising spatiotemporal variability in community composition and identifying sites that are pivotal for maintaining biodiversity at the landscape scale are key needs for conservation prioritization and planning. Thus, our framework may be used to guide conservation actions in highly dynamic ecosystems when time‐series data describing biodiversity across sites connected by dispersal are available.     

On Valuing Information in Adaptive‐Management Models

Abstract: Active adaptive management looks at the benefit of using strategies that may be suboptimal in the near term but may provide additional information that will facilitate better management in the future. In many adaptive‐management problems that have been studied, the optimal active and passive policies (accounting for learning when designing policies and designing policy on the basis of current best information, respectively) are very similar. This seems paradoxical; when faced with uncertainty about the best course of action, managers should spend very little effort on actively designing programs to learn about the system they are managing. We considered two possible reasons why active and passive adaptive solutions are often similar. First, the benefits of learning are often confined to the particular case study in the modeled scenario, whereas in reality information gained from local studies is often applied more broadly. Second, management objectives that incorporate the variance of an estimate may place greater emphasis on learning than more commonly used objectives that aim to maximize an expected value. We explored these issues in a case study of Merri Creek, Melbourne, Australia, in which the aim was to choose between two options for revegetation. We explicitly incorporated monitoring costs in the model. The value of the terminal rewards and the choice of objective both influenced the difference between active and passive adaptive solutions. Explicitly considering the cost of monitoring provided a different perspective on how the terminal reward and management objective affected learning. The states for which it was optimal to monitor did not always coincide with the states in which active and passive adaptive management differed. Our results emphasize that spending resources on monitoring is only optimal when the expected benefits of the options being considered are similar and when the pay‐off for learning about their benefits is large.     

Fundamental insights on when social network data are most critical for conservation planning

As declines in biodiversity accelerate, there is an urgent imperative to ensure that every dollar spent on conservation counts toward species protection. Systematic conservation planning is a widely used approach to achieve this, but there is growing concern that it must better integrate the human social dimensions of conservation to be effective. Yet, fundamental insights about when social data are most critical to inform conservation planning decisions are lacking. To address this problem, we derived novel principles to guide strategic investment in social network information for systematic conservation planning. We considered the common conservation problem of identifying which social actors, in a social network, to engage with to incentivize conservation behavior that maximizes the number of species protected. We used simulations of social networks and species distributed across network nodes to identify the optimal state-dependent strategies and the value of social network information. We did this for a range of motif network structures and species distributions and applied the approach to a small-scale fishery in Kenya. The value of social network information depended strongly on both the distribution of species and social network structure. When species distributions were highly nested (i.e., when species-poor sites are subsets of species-rich sites), the value of social network information was almost always low. This suggests that information on how species are distributed across a network is critical for determining whether to invest in collecting social network data. In contrast, the value of social network information was greatest when social networks were highly centralized. Results for the small-scale fishery were consistent with the simulations. Our results suggest that strategic collection of social network data should be prioritized when species distributions are un-nested and when social networks are likely to be centralized.