Inequality persists in a large citizen science programme despite increased participation through ICT innovations

Biological recording is a prominent and widely practised form of citizen science, but few studies explore long-term demographic trends in participation and knowledge production. We studied long-term demographic trends of age and gender of participants reporting to a large online citizen science multi-taxon biodiversity platform ( www.artportalen.se ). Adoption by user communities and continually developing Information and Communications Technologies (ICTs) greatly increased the number of participants reporting data, but profound long-term imbalances in gender contribution across species groups persisted over time. Reporters identifying as male dominated in numbers, spent more days in the field reporting and reported more species on each field day. Moreover, an age imbalance towards older participants amplified over time. As the first long-term study of citizen participation by age and gender, our results show that it is important for citizen science project developers to account for cultural and social developments that might exclude participants, and to engage with underrepresented and younger participants. This could facilitate the breadth of engagement and learning across a larger societal landscape, ensure project longevity and biodiversity data representation (e.g. mitigate gender bias influence on the number of reports of different species groups).

Knowledge gaps hamper understanding the relationship between fragmentation and biodiversity loss: the case of Atlantic Forest fruit-feeding butterflies

Background

A key challenge for conservation biology in the Neotropics is to understand how deforestation affects biodiversity at various levels of landscape fragmentation. Addressing this challenge requires expanding the coverage of known biodiversity data, which remain to date restricted to a few well-surveyed regions. Here, we assess the sampling coverage and biases in biodiversity data on fruit-feeding butterflies at the Brazilian Atlantic Forest, discussing their effect on our understanding of the relationship between forest fragmentation and biodiversity at a large-scale. We hypothesize that sampling effort is biased towards large and connected fragments, which occur jointly in space at the Atlantic forest.

Methods

We used a comprehensive dataset of Atlantic Forest fruit-feeding butterfly communities to test for sampling biases towards specific geographical areas, climate conditions and landscape configurations.

Results

We found a pattern of geographical aggregation of sampling sites, independently of scale, and a strong sampling bias towards large and connected forest fragments, located near cities and roads. Sampling gaps are particularly acute in small and disconnected forest fragments and rare climate conditions. In contrast, currently available data can provide a fair picture of fruit-feeding butterfly communities in large and connected Atlantic Forest remnants.

Discussion

Biased data hamper the inference of the functional relationship between deforestation and biodiversity at a large-scale, since they are geographically clustered and have sampling gaps in small and disconnected fragments. These data are useful to inform decision-makers regarding conservation efforts to curb biodiversity loss in the Atlantic Forest. Thus, we suggest to expand sampling effort to small and disconnected forest fragments, which would allow more accurate evaluations of the effects of landscape modification.

Assessing spatial and temporal biases and gaps in the publicly available distributional information of Iberian mosses

One of the most valuable initiatives on massive availability of biodiversity data is the Global Biodiversity Information Facility, which is creating new opportunities to develop and test macroecological knowledge. However, the potential uses of these data are limited by the gaps and biases associated to large-scale distributional databases (the so-called Wallacean shortfall). Describing and quantifying these limitations are essential to improve knowledge on biodiversity, especially in poorly-studied groups, such as mosses. Here we assess the coverage of the publicly-available distributional information on Iberian mosses, defining its eventual biases and gaps. For this purpose, we compiled IberBryo v1.0, a database that comprises 82,582 records after processing and checking the geospatial and taxonomical information. Our results show the limitations of data and metadata of the publicly-available information. Particularly, ca. 42% of the records lacked collecting date information, which limits data usefulness for time coverage analyses and enlarges the existing knowledge gaps. Then we evaluated the overall coverage of several aspects of the spatial, temporal and environmental variability of the Iberian Peninsula. Through this assessment, we demonstrate that the publicly-available information on Iberian mosses presents significant biases. Inventory completeness is strongly conditioned by the recorders' survey bias, particularly in northern Portugal and eastern Spain and the spatial pattern of surveys is also biased towards mountains. Besides, the temporal pattern of survey effort intensifies from 1970 onwards, encompassing a progressive increase in the geographic coverage of the Iberian Peninsula. Although we just found 5% of well-surveyed cells of 30' of resolution over the 1970-2018 period, they cover about a fifth of the main climatic gradients of the Iberian Peninsula, which provides a fair - though limited - coverage. Yet, the well-surveyed cells are biased towards anthropised areas and some of them are located in areas under intense land-use changes, mainly due to the wood-fires of the last decade. Despite the overall increase, we found a noticeable gap of information in the south-west of Iberia, the Ebro river basin and the inner plateaus. All these gaps and biases call for a careful use of the available distributional data of Iberian mosses for biogeographical and ecological modelling analysis. Further, our results highlight the necessity of incorporating several good practices to increase the coverage of high-quality information. These good practices include digitalisation of specimens and metadata information, improvement on the protocols to get accurate data and metadata or revisions of the vouchers and recorders' field notebooks. These procedures are essential to improve the quality and coverage of the data. Finally, we also encourage Iberian bryologists to establish a series of re-surveys of classical localities that would allow updating the information on the group, as well as to design their future surveys considering the most important information gaps on IberBryo.

India Biodiversity Portal: An integrated, interactive and participatory biodiversity informatics platform

Background

This paper describes a growing biodiversity platform, launched in 2008, which organizes knowledge on the biodiversity of India. The main objective and originality of the India Biodiversity Portal (IBP) is to aggregate curated biodiversity data of different kinds (e.g. distribution maps, temporal distribution or life history) in an integrated platform where amateurs and experts can easily interact.

New information

Since its launch, the platform has seen an exceptional increase in both user activity and biodiversity data. Currently the portal has descriptions of over 20,400 species, and has aggregated approximately 1,280,000 observations covering more than 30,000 species, which already constitutes a unique source of information for scientists and stakeholders in conservation. Over 8500 users have registered on the portal. The amount of data generated and to be generated in the next few years by this portal will certainly help the effective implementation of biodiversity conservation and management in one of the most ecologically diverse countries in the world.

Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method

We propose a novel multivariate method to analyse biodiversity data based on the Latent Dirichlet Allocation (LDA) model. LDA, a probabilistic model, reduces assemblages to sets of distinct component communities. It produces easily interpretable results, can represent abrupt and gradual changes in composition, accommodates missing data and allows for coherent estimates of uncertainty. We illustrate our method using tree data for the eastern United States and from a tropical successional chronosequence. The model is able to detect pervasive declines in the oak community in Minnesota and Indiana, potentially due to fire suppression, increased growing season precipitation and herbivory. The chronosequence analysis is able to delineate clear successional trends in species composition, while also revealing that site-specific factors significantly impact these successional trajectories. The proposed method provides a means to decompose and track the dynamics of species assemblages along temporal and spatial gradients, including effects of global change and forest disturbances.