Capacity building as a pathway to indigenous participation in tropical birding and citizen science

Introduction

Citizen science has emerged as a vital mechanism for enhancing public participation in biodiversity monitoring, advancing ecological understanding, and supporting conservation objectives. By engaging non-professionals in systematic data collection and interpretation, citizen science programs can produce extensive ecological datasets while promoting environmental awareness, stewardship, and advocacy (Bonney et al., 2014; Chandler et al., 2017a). However, participation is unevenly distributed across regions, reflecting differences in institutional capacity, access to training, and opportunities for engagement. Participation-based frameworks including social learning theory, communities of practice, and diffusion of innovations suggest that sustained involvement in citizen science depends not only on individual motivation, but also on access to skills, mentorship, and social networks that enable learning and integration into scientific practice (Chandler et al., 2017b). These advantages are particularly pertinent in populous developing nations such as Nigeria, where rapid demographic expansion, poverty reduction efforts, and dependence on natural resources exert considerable pressure on biodiversity. In such contexts, broadening public involvement in biodiversity monitoring could provide a pragmatic avenue for aligning conservation goals with community engagement and local ownership (Jordan et al., 2016). Yet participation is often hindered by barriers such as limited expertise, low awareness, and weak social infrastructure for knowledge exchange. From a social learning perspective, these barriers restrict opportunities for experiential learning and limit entry into communities of practice that sustain long-term participation.

The evolution of citizen-driven bird monitoring clearly illustrates these disparities (Danielsen et al., 2009; Parker, 2019). In Europe and North America, established birdwatching societies and volunteer-based monitoring schemes have operated for more than a century, bolstered by robust institutions and a longstanding tradition of recreational natural history (Greenwood, 2007; Lindström et al., 2025). Comparable success in parts of the global South, such as the Southern African Bird Atlas Project (SABAP2) has been achieved through sustained investment in volunteer training and community development. Initiated in 2007, (SABAP2) has cultivated a substantial citizen science community contributing fine-scale distribution data across a diverse landscape (Lee et al., 2022; Brooks et al., 2022). On the contrary, other African nations have lacked both the historical and institutional foundations necessary to support widespread participation. In Nigeria for example, the science of ornithology evolved during the colonial era but continued to be dominated by expatriate researchers several decades post colonization. The Nigerian Ornithological Society (NOS), founded in February 1964, initially comprised mainly European ornithologists working in British West Africa (Elgood, 1964). In 1977, the society expanded to form the West African Ornithological Society (WAOS) following a council meeting in Liverpool, United Kingdom, to include francophone ornithologists from former French colonies (Morel et al., 2004). Despite this expansion, African representation in governance remained limited for decades, with the first indigenous (African) West African council member joining only in 2000 (Morel et al., 2004). This framework naturally created limited indigenous representation and few formal training pathways necessary to support widespread participation. Currently, the WAOS council comprises six Africans and four Europeans, indicating increased local participation.

Professional ornithological capacity within Nigeria developed gradually, with one of the earliest influential indigenous-led contributions being a comprehensive assessment of Nigeria’s Important Bird and Biodiversity Areas in 1996 (Ezealor, 2001). Next, the establishment of the A. P. Leventis Ornithological Research Institute (APLORI) in 2001 marked a significant milestone in building local ornithological capacity (Vickery and Jones, 2002; Mwansat et al., 2011), as no formal training programs or institutions existed previously. At this point, the number of PhD trained indigenous (Nigerian) ornithologists were fewer than five, reflecting the limited technical foundation from which local ornithological and citizen science efforts have developed. Consequently, the broader academic and social infrastructure necessary for widespread public participation such as accessible training pathways and peer learning networks remained largely underdeveloped. Hence, prior to 2015, birdwatching in Nigeria was confined to a small and largely expatriate community, with fewer than 200 active participants under the auspices of the Lekki and Ibadan Bird Clubs, both established by the Nigerian Conservation Foundation in 2009 and 2014, respectively (Awoyemi and Bown, 2019; NCF, 2026).

The establishment of the Nigerian Bird Atlas Project (NiBAP) in 2015 marked a pivotal shift toward addressing these constraints. With initial funding and technical support from Swedish and South African partners, NiBAP set out to establish the first coordinated national citizen science framework for bird monitoring in Nigeria (NiBAP, 2026b; Tende et al., 2024). From its outset, NiBAP integrated data collection with deliberate capacity development, recognizing that participation would require targeted training and outreach in a society where volunteer birdwatching and citizen science were novel concepts (Danielsen et al., 2009). NiBAP’s strategy for capacity building incorporated two complementary approaches: formal ornithology training of volunteers through workshops and field courses, and informal training via the strategic establishment of bird clubs that paired trained ornithologists with amateur birdwatchers and nature enthusiasts, enabling skill and knowledge transfer through social learning and fostering communities of practice.

Here, we evaluated the role of these capacity- and community-building strategies in lowering barriers to entry, enhancing technical capacity, and fostering indigenous engagement in birdwatching in Nigeria. Specifically, we (i) examine the impact of capacity building efforts by comparing before and after training checklist submission rates of a cohort of participants in our Introductory Ornithology Field Course (IOFC), (ii) analyze and assess trends and differences in eBird checklist submission rates and birding experience among Indigenous and Non-native/Expatriate contributors to eBird in Nigeria from 2000 to 2024. Finally, we (iii) review questionnaire responses from a cross-section of NiBAP volunteers to elucidate motivations for participation and identify persistent barriers.

Methods

Study area and data sources

Nigeria is located in West Africa, extending from approximately 4° to 14°N and 3° to 15°E, with a land area of approximately 923,769 km² and a population exceeding 230 million (World Bank Group, 2026, Worldometer, 2026). The country encompasses diverse ecological zones, including coastal, savanna, and arid regions, and is recognized for its rich avifauna, with about 975 documented bird species (Lepage, 2026). Authoritative checklists such as the African Bird Club identify 921 species (Dowsett et al., 2016), while citizen science platforms including eBird and the Nigerian Bird Atlas Project (NiBAP) report between 760 and 880 species, respectively (eBird, 2026c; NiBAP, 2026b).

The eBird project, established in 2002 by the Cornell Lab of Ornithology and the National Audubon Society, collects bird observations globally through standardized checklists to support research and conservation (Sullivan et al., 2009). The platform expanded worldwide in 2010 (eBird, 2010) and now hosts over 120 million checklists submitted by more than 1.2 million contributors, documenting over 10,980 species (eBird, 2026b). Data collection protocols require users to record all observed species per birding event, specifying whether observations were made at a single location or along a travel route, also allowing the submission/digitization of historical bird records not obtained via the eBird app, or before the app was developed, or from regions not previously covered prior to 2010 (Sullivan et al., 2009; eBird, 2026d). In Nigeria, 444 eBird participants have submitted 5,874 checklists, recording 762 species from 1968 to the present (eBird, 2026a).

The Nigerian Bird Atlas Project (NiBAP), initiated in late 2015, represents the first coordinated citizen science bird monitoring initiative in Nigeria (NiBAP, 2026b). NiBAP adopts the BirdMap protocol, modeled after the Southern African Bird Atlas Project (SABAP2), and collects bird lists within spatial units known as pentads (5 x 5 minutes of latitude and longitude). A full protocol card requires active bird recording over a minimum of 2 hours, up to a maximum of five consecutive days, across multiple habitats within a pentad (Brooks et al., 2022). As of the most recent reporting, over 320 NiBAP observers have contributed 13,226 full protocol cards from 6,026 pentads, covering approximately 54% of the country’s grid (Figure 1), documenting 880 species (Tende et al., 2024; NiBAP, 2026b), with over 570,000 observation records published to GBIF (Chaskda et al., 2022; Danmallam et al., 2025). NiBAP’s data management includes rigorous protocols for data collection, vetting, and verification, detailed in Tende et al. (2024).

Building local capacity for birding in Nigeria

NiBAP’s capacity building approach comprised ongoing, casual social learning facilitated through the establishment and support of bird clubs, and semi-formal, intensive field training courses for selected participants. Both components were supplemented by technical guidance, provision of field equipment, and travel grants to lower barriers to entry and sustain engagement.

Between 2015 and 2019, NiBAP conducted outreach on university campuses, introducing the BirdMap protocol and recruiting APLORI-trained ornithologists, students, and nature enthusiasts into newly formed bird clubs. In total, about 30 new clubs have been established (NiBAP, 2026a), in addition to the two pre-existing NCF clubs. Each club was coordinated by at least one APLORI-trained ornithologist responsible for leading monthly bird identification sessions, while workshop participants (mostly students) were recruited as founding members of bird clubs. All members were encouraged to bring at least one new family member or friend regardless of (prior birding experience or professional background) to regular club meetings as a strategy for inclusive growth and expansion of the clubs. Clubs received technical and equipment support from the NiBAP management team including training visits to club meetings and donation of used binoculars which were distributed for use during training events and retrieved afterwards for safekeeping. Monthly sessions emphasized basic-level, inclusive instruction, fostering social learning and environmental awareness among participants with varied experience levels. This informal, peer-supported model aligns with evidence that social learning and community engagement are effective for building capacity in biodiversity monitoring (Randler et al., 2007; Danielsen et al., 2009; Newman et al., 2012).

In response to increased demand for advanced training, NiBAP secured funding from the National Geographic Society in 2019 to train 30 citizen scientists selected from a competitive pool of over 200 applicants drawn from university workshops and bird clubs. Training was delivered through intensive field courses held at two regional conservation sites in northern and southern Nigeria. The curriculum included lectures, workshops, practical fieldwork, and research presentations, covering bird identification, avian ecology, survey design, population and habitat monitoring, application of the BirdMap protocol, and use of citizen science platforms (BirdLasser, eBird, iNaturalist). Course participants were assigned to a field training course in their region of residence, enabling more relevant bird identification training focused on regional birds.

Institutional capacity for the management and use of generated data was further developed through a collaborative GBIF Biodiversity Information Development regional grant involving the Kenya BirdMap, Nigeria Bird Atlas Project and the sub-regional second Southern Africa Bird Atlas Project (SABAP2) represented by Namibia and South Africa (GBIF.org, 2021b). Through this grant five data managers (two in Kenya and three in Nigeria) were trained through monthly virtual workshops by experienced data managers from SABAP2 between 2021-2022.

To assess changes in participation and effort following training, we constructed a longitudinal panel dataset comprising annual records of each field course participant. Variables included participant ID, year, period (pre-training [2016-2018], 1–3 years post-training [2019-2021], 4–6 years post-training [2022-2024), number of full protocol checklist submissions, and number of pentads surveyed. Full protocol checklist submissions and number of pentads surveyed were used as a proxy for bird monitoring activity and as the response variables. Given the count nature and skewed distribution of the response variables, we applied a negative binomial generalized linear mixed model (NB-GLMM) with period as a fixed effect and participant as a random intercept. The model was fitted using the glmmTMB package (McGillycuddy et al., 2025). Pairwise comparisons among periods were conducted using estimated marginal means (emmeans) (Lenth and Piaskowski, 2017) and reported as ratio contrasts, with Holm correction for multiple comparisons. Model-estimated marginal means and 95% confidence intervals were visualized using ggplot2.

Trends in indigenous participation and birding experience in Nigeria’s ebird data (2000–2024)

Participation Trends: Proportion of indigenous vs. expatriate participants.

To analyze engagement trends, we used publicly available data from the eBird platform - a longstanding globally established citizen science repository for bird occurrence records (eBird, 2026a). We identified all contributors to Nigeria’s bird checklists for each year from 2000 to 2024 via the eBird “Top 100” leaderboard, selecting “Nigeria” as the focal region and iterating across each year of the study period. Contributors were ranked by the number of submitted checklists. The annual contributor pool averaged 30 individuals per year, ranging from 3 contributors in 2000 to 75 in 2023, reflecting the broader growth of the eBird platform over this period.

We classified each contributor as either indigenous Nigerian or expatriate using a hierarchical approach that prioritized the most direct and verifiable sources of information. Classification drew on three information types in order of reliability: publicly available profile information including self-reported location and affiliation (n = 128); identification of recognizably Nigerian names in cases where regional profile details were absent (n = 18); and authors’ direct personal knowledge of contributors with private profiles based on sustained engagement with the Nigerian birding community (n = 84). We recognize that name-origin inference and personal knowledge, while informed, are imperfect proxies for indigenous status and could introduce potential misclassification error. To the extent possible, we applied classifications conservatively and discuss the implications of this approach below.

To examine temporal trends in the composition of eBirders in Nigeria, we modeled the probability of an observer being classified as an indigenous birder as a function of year (2000–2024). We acknowledge that misclassification error is an inherent limitation of the classification approach described above; however, we expect any such errors to be non-differential with respect to the temporal trend being modeled i.e. misclassifications are unlikely to be systematically concentrated in particular years in ways that would bias the direction of observed trends. Importantly also, the 109 observers with private profiles and no identifiable information were conservatively imputed as non-indigenous (coded 0), meaning our estimates of indigenous participation likely represent a lower bound. Any bias introduced by this imputation would therefore render our findings conservative rather than inflated, strengthening confidence in the directionality of results even if absolute magnitudes are underestimated.

The response variable was coded as a binary indicator of indigenous status (1 = indigenous Nigerian eBirder and 0 = non-native/expatriate eBirder or unclassifiable). We fitted a logistic regression model using the glm() function in R with a binomial error distribution. Model coefficients were interpreted on the log-odds scale, and odds ratios were calculated by exponentiating the estimated coefficients. Model fit was assessed using deviance statistics and the Akaike Information Criterion (AIC).

Differences in birding experience between indigenous and non-native/expatriate eBirders in Nigeria

To assess differences in birding experience between indigenous and expatriate eBird contributors in Nigeria, we utilized the “oldest checklist” feature available on public eBird profiles. This feature records the year of a user’s earliest submitted bird observation checklist, including associated date and location information. For each contributor to Nigeria’s bird checklist, we extracted the year of their oldest checklist and calculated birding experience as the difference between this year and the year of each subsequent checklist submission in Nigeria. This approach provided a consistent and uniformly accessible proxy for individual birding experience across all contributors and allowed for temporal comparison across the study period (2000-2024).

We acknowledge an important limitation of this proxy: although eBird permits the retrospective submission of historical checklists including observations predating the platform’s existence, not all users choose to submit such records. The year of a contributor’s oldest checklist therefore reflects the earliest observation they elected to submit to the platform rather than necessarily the true onset of their birding activity. This limitation applies to both indigenous and expatriate contributors, though the degree to which individuals have backdated their historical records likely varies across users in ways that we could not systematically assess. As a result, experience comparisons based on this metric should be interpreted with caution, and we treat them as indicative of relative engagement patterns rather than as definitive measures of ornithological experience.

Contributors were classified as indigenous or expatriate based on profile information, name origin, and personal knowledge as outlined in the preceding section. The distribution of birding experience was evaluated for normality using the Shapiro–Wilk test, which indicated a non-normal distribution. Accordingly, the Wilcoxon rank-sum test was applied to compare birding experience between the two groups, providing a robust nonparametric assessment of group differences. Group-specific means and median values were also calculated to facilitate interpretation of central tendency and dispersion. Given the limitations of the experience proxy described above, these comparisons are presented descriptively to contextualize participation patterns rather than to make inferences about differential birding competence between groups.

Participant characteristics, motivations and barriers to participation in citizen science bird monitoring in Nigeria

We administered a structured online questionnaire using Google Forms and distributed the survey link across all WhatsApp groups established by NiBAP-supported bird clubs in Nigeria. The questionnaire, which was adapted from (Squires et al., 2021), invited participants to voluntarily provide demographic information, including age, education level, and employment status, as well as details regarding their birdwatching experience, motivations, and perceived barriers to participation. The form began with a brief introduction outlining the survey’s background and objectives, followed by an informed consent item that allowed respondents to either continue with or withdraw from the survey based on their preference.

All statistical analyses assessing the impact of capacity building and participation trends of both NiBAP and eBird data were conducted using R version 4.5.2 (R Core Team, 2025). Established protocols for parametric and nonparametric testing in ecological research were followed as appropriate. Data preparation and visualization were performed using the tidyverse suite (Wickham et al., 2019), with ggplot2 employed to generate all graphical representations of the results (Wickham, 2016). Questionnaire survey data were compiled and descriptive statistics calculated using Microsoft Excel.

Results

Local capacity building outcomes

Pre- and post-training variation in full protocol checklist submissions

Full protocol checklist submissions varied significantly across periods (negative binomial GLMM with participant as a random intercept; n = 252 submissions from 28 participants). The model showed strong evidence of non-linear temporal change, with both linear (z = 3.70, p < 0.001) and quadratic (z = −5.79, p < 0.001) period effects, indicating a pronounced increase followed by partial attenuation. Model diagnostics indicated adequate fit, with no evidence of overdispersion (dispersion ratio = 0.62) and no clear patterns in Pearson residuals when plotted against fitted values. A relatively low dispersion parameter (θ = 0.338) further supported the suitability of the negative binomial error structure for these data.

Pairwise contrasts of model-estimated marginal means (EMMs), expressed as rate ratios on the response scale, revealed that full protocol checklist submissions were substantially higher during both post-intervention periods compared to the baseline. Submission rates in the short-term period were ~24-fold higher than before (rate ratio = 0.04 for before vs. short-term; 95% CI: 0.01–0.14; Holm-adjusted p < 0.0001), and ~6-fold higher in the long-term period relative to baseline (rate ratio = 0.17; 95% CI: 0.06–0.54; p = 0.0004). Short-term submission rates also significantly exceeded long-term rates (rate ratio = 4.05; 95% CI: 1.49–11.02; p = 0.0008), indicating a peak in activity shortly after intervention (Figure 2). In absolute terms however, mean full protocol checklist submissions increased from 1.5 in the baseline pre-training period to 9.3 in the short-term and further to 17 in the long-term post-training period suggesting continued increases in full protocol checklist submissions post-training.

Pre- and post-training variation in pentad-level contributions

Pentad-level spatial contributions exhibited a closely parallel temporal structure. Pentad counts differed significantly across periods (negative binomial GLMM; n = 252 observations, 28 participants), with significant linear (z = 2.80, p = 0.005) and quadratic (z = −5.95, p < 0.001) effects of period. Residual diagnostics again suggested no overdispersion (dispersion ratio = 0.65) and no systematic deviations in residual patterns.

EMM contrasts showed that pentad contributions increased markedly following the intervention. Compared to the baseline, pentad submissions were ~17-fold higher in the short-term period (rate ratio = 0.06; 95% CI: 0.02–0.18; p < 0.0001) and ~3.5-fold higher in the long-term period (rate ratio = 0.28; 95% CI: 0.10–0.83; p = 0.005). As with full protocol checklist submissions, pentad contributions were significantly higher in the short term than in the long-term period (short-term vs. long-term rate ratio = 4.72; 95% CI: 1.77–12.59; p = 0.0003) (Figure 2), indicating a peak in spatial coverage shortly after training, whereas mean pentad contributions increased from 1.6 in the baseline period to 9.7 in the short-term period and further to 15.8 in the long-term post-training period.

It is noteworthy that while the absolute raw mean values suggest continued increases in both full protocol checklist submissions and pentad contributions into the long-term period, model-based estimates indicated relatively highest activity in the short-term post-training period. This discrepancy reflects the influence of a small number of highly active participants disproportionately contributing to long-term counts, whereas the mixed-effects model accounts for participant-level variation and therefore better represents typical engagement patterns across the cohort. Taken together, these results suggest that the training program produced a broad-based short-term increase in engagement across participants, followed by sustained contributions in the long-term that are partly driven by a smaller subset of highly active individuals.

Following the training program supported through the GBIF grant, NiBAP’s data managers were able to support the development of a centralized database for the African Bird Atlas Project as well as an indigenous mobile app BirdPlus that has contributed to expanding the coverage of underrepresented bird species in Nigeria through its multilingual, user-friendly and offline-capable platform (GBIF.org, 2021b; GBIF.org, 2025). Trained data managers also facilitated APLORI’s registration as a local GBIF data publisher, making APLORI one of only 10 Nigeria-based institutions in the GBIF community (GBIF.org, 2023). They also led the publication of over 578,000 geo-referenced bird observations on GBIF (GBIF.org, 2021a) representing over three quarters of all Nigeria’s records, making NiBAP and APLORI the largest source of data about biodiversity in Nigeria (GBIF.org, 2023).

Participation trends: indigenous and expatriate participation over time

Between 2000 and 2024, 339 birders contributed to Nigeria’s eBird checklist (mean = 30, median = 14 per year). Of 231 contributors with determined status, 110 were classified as indigenous and 121 as non-native/expatriate contributors. Logistic regression analysis identified a significant positive trend in the proportion of indigenous participants over time, with a positive and highly significant year coefficient (β = 0.28, SE = 0.03, z = 9.25, p < 0.001). This result indicates that the odds of an observer being indigenous increased by approximately 33% per year (odds ratio = 1.33) (Figure 3). The model deviance decreased from 763.19 (null) to 593.44 (residual), with a deviance reduction of 169.75, demonstrating that year accounted for a substantial portion of the variation in birder origin. The results indicate a consistent increase in indigenous birder participation over the period under consideration.

Differences in birding experience between indigenous and non-native/expatriate eBirders in Nigeria

A marked disparity in our proxy for birding experience was observed between Indigenous and Expatriate participants. Indigenous birders reported significantly fewer years of experience compared to Expatriates, as indicated by lower group means and medians. The Wilcoxon rank-sum test demonstrated a highly significant difference in experience distributions between the groups (W = 13,513, p < 0.001), suggesting that indigenous participants consistently had less experience than their Expatriate counterparts throughout the dataset. Visual inspection of the distributions reinforced this finding, with Indigenous birders displaying a more recent and compressed range of experience relative to the broader and higher-centered distribution seen among Expatriates (Figure 4).

Participant characteristics, birding experience, motivation and barriers to participation

Participant characteristics: Thirty-two respondents, all Nigerians, and all members of at least one birding group, completed the survey. Of these, 28% were female and approximately 63% were under 40 years old (mean age = 36 years). Employment status varied: 37.5% worked in the nature and environmental science or management sector, 15.6% in public or civil service, 12.5% were self-employed, 9.4% were unemployed, and 25% were students.

Birdwatching experience and expertise: All participants were affiliated with at least one bird club and reported an average of about eight years of birding experience (range: less than one year to 42 years). Nearly half (47%) had participated in a BirdMap protocol training workshop and only one had also attended the intensive field course in 2019. Birding frequency varied, with 16% birding at least weekly, 66% at least monthly, 6% at least every three months, 3% at least annually, and 9% birding only occasionally. Most respondents (84%) rated their bird identification skills as above average (score of 4 or higher on a 7-point scale, where 1 indicates a beginner and 7 indicates expert-level identification by sight and call). Regarding species observed, 37% reported a lifelist exceeding 200 species, 22% had seen 100–200 species, and 41% had recorded fewer than 100 species.

Motivations: The primary motivations for participation included “contributing to conservation” at local and international levels, and “raising awareness about bird population declines”. Additional motivations were “supporting Nigeria’s first indigenous-led bird atlas” and “traveling to new locations” (Figure 5).

Barriers and limitations: The most frequently reported barriers to participation were time constraints and lack of equipment, each cited by 56% of respondents. Notably, 41% did not own binoculars and 38% lacked a field guide. Work commitments were cited by 41% as a limiting factor, while study and family responsibilities were reported by 9% each.

Discussion

Capacity building impacts temporal patterns of engagement and contribution

Analysis of temporal engagement among field training course participants revealed a marked increase in activity across multiple effort-based metrics, including full protocol checklist submission and pentad survey coverage, that coincided with participation in the intensive four weeks field training course. Raw summary statistics indicate that this increase was broad-based, reflecting elevated engagement across participants, and continued as a steady upward trend over the long term. Model-based estimates, however, reveal a more nuanced pattern: participation peaked in the short-term period following training before declining modestly in the 4–6 year window post-completion, yet remained consistently above pre-intervention baseline levels thereafter. Together, these complementary results suggest that training produced an initial surge in engagement across a wide cross-section of participants, followed by a transition to sustained long-term contribution driven in part by a smaller subset of highly active individuals.

This pattern aligns with established dynamics observed in capacity-building initiatives, where intensive hands-on training catalyzes broad immediate increases in participant contribution that subsequently stabilize as novelty effects attenuate and engagement consolidates among the most committed participants (Şekercioğlu, 2012; Von Gönner et al., 2024). The persistence of contributions above baseline levels over the long term is nonetheless meaningful, indicating that program impact extends well beyond the short-term window and that training effects are not simply an artifact of initial enthusiasm. These findings underscore the value of distinguishing between short-term activation and long-term retention when evaluating the efficacy of citizen science capacity-building programs and suggest that complementary strategies targeting sustained engagement — such as ongoing mentorship, community reinforcement, and periodic retraining opportunities — may help consolidate and extend initial training gains.

The observed temporal dynamics are attributable, in part, to a combination of targeted capacity-building and systematic barrier-removal strategies implemented across training and post-training phases. Training delivered by professional ornithologists from APLORI emphasized practical skill development in bird identification and the BirdMap protocol, while provision of essential equipment — including binoculars and field guides — directly addressed resource access barriers widely recognized as persistent obstacles to citizen science participation in under-resourced contexts (Bonney et al., 2014; Chandler et al., 2017a; Greenwood, 2007). These interventions likely contributed to the broad-based short-term surge in engagement documented across participants.

The transition toward sustained but more concentrated long-term contribution also seems consistent with the integration of participants into regional bird atlas teams, supported by travel grants and ongoing mentorship. These community-building mechanisms fostered collective purpose and reduced attrition among committed contributors, consistent with findings from analogous ornithological capacity-building programs in the region (Cresswell, 2018; Chandler et al., 2017b). The gradual moderation of engagement over the 4–6 year post-training period likely reflects competing life demands — including career and family responsibilities — rather than program failure, as contribution rates nonetheless remained above pre-intervention baselines throughout. Together, these patterns suggest that the combination of technical training, resource provision, and sustained social support structures operated across different timescales: broadly activating participation in the short term while selectively reinforcing long-term engagement among the most dedicated contributors.

Training indigenous data managers through the NiBAP initiative also directly enabled the establishment of a new local GBIF data publisher in Nigeria, specifically through APLORI’s registration as a recognized contributor within the GBIF community. This development is significant, as the increase in local data publishers has also facilitated a dramatic increase in the volume of biodiversity records submitted from Nigeria. Notably, the output from APLORI and NiBAP-trained managers now accounts for over 578,000 geo-referenced bird observations, representing more than three-quarters of all Nigeria’s records on GBIF and a fourfold increase compared to the cumulative submissions by foreign institutions previously responsible for Nigeria’s biodiversity data (GBIF.org, 2023). This surge underscores the scientific value of empowering indigenous experts, who are uniquely positioned to generate, curate, and share high-quality data that is locally relevant and contextually accurate. The enhanced participation of local data managers not only improves data quantity and accessibility but also strengthens the sustainability and ownership of biodiversity knowledge within Nigeria, thereby advancing both national and global conservation efforts (GBIF.org 2021b; GBIF.org, 2023).

Positive engagement trends observed in indigenous eBirder contributions in Nigeria

The analysis of eBird checklist submissions in Nigeria revealed a pronounced shift in participation dynamics between indigenous and expatriate contributors over the study period. In the earlier years of the eBird platform’s global expansion, eBird activity in Nigeria was dominated by expatriate and non-native birders, a pattern consistent with the platform’s North American origins and its initial uptake among Global North user communities (Greenwood, 2007; Bonney et al., 2014). By 2010, only 10 contributors had submitted 29 checklists, reporting 174 species from Nigeria (eBird, 2026d).

Identifiable indigenous contribution to eBird does not appear until 2015, a timing that coincides with the launch of the Nigerian Bird Atlas Project (NiBAP). This temporal association suggests that NiBAP’s targeted capacity-building and community development strategies may have been associated with early indigenous uptake and engagement with the platform. We note, however, that NiBAP and eBird participation records have not been cross-referenced at the individual contributor level; the relationship between the two platforms is therefore inferred from parallel temporal trends rather than documented at the participant level. The observed increase in indigenous eBird engagement is consistent with the broader proliferation of bird clubs and the strengthening of local ornithological networks during this period (Chandler et al., 2017a; Harebottle, 2020; Tende et al., 2024), though we cannot isolate the contribution of any single initiative from these data.

These patterns align with findings from analogous capacity-building programs in the region. Formal training initiatives such as the MSc in Conservation Biology and Ornithology at the A.P. Leventis Ornithological Research Institute (APLORI), have been associated with increased indigenous representation in ornithological research output (Cresswell, 2018) — a documented cross-program effect that provides independent support for the broader argument that structured and sustained investment in both academic and field-based training can meaningfully expand indigenous participation in citizen science and biodiversity monitoring (Bonney et al., 2014; Chandler et al., 2017a; Greenwood, 2007).

Disparities in birding experience remain, despite progress to address them.

The marked differences in our birding experience proxy between the indigenous and expatriate birders may be rooted in their distinct natural history traditions. Many expatriate birders were from the Global North countries with established cultures of natural history observation and organized birding, often dating back to the nineteenth century (Birkhead and Gallivan, 2012; Dunn, 2017). In these settings, birdwatching is typically introduced early through family and community activities, fostering intergenerational engagement and skill development (Saha, 2015; Koszycki, 2017; Cannariato, 2023). Expatriate birders contributing to eBird in Nigeria generally bring substantial prior experience which appear to have been shaped by these cultural and educational backgrounds.

In contrast, formally organized birding has only recently emerged in many Global South countries, including Nigeria, despite their considerable biodiversity (Chandler et al., 2017a; Pototsky and Cresswell, 2021). Historically, national priorities have focused less on natural history and environmental studies and more on developmental challenges (Elgood et al., 1994; Ezealor, 2001; Thompson and Ivande, 2025). Anecdotal accounts, including from indigenous authors involved in this research, as well as insights from interactions with other both expatriate and indigenous birders in Nigeria, provide further perspective on these disparities. Many indigenous Nigerian birders report that engagement with birding and natural history observation often begins as an academic or professional endeavor, typically after years of higher education (Thompson and Ivande, 2025). By comparison, expatriate contributors tend to possess decades of experience acquired in regions where birding is a mainstream recreational activity (Cordell and Herbert, 2002; Che, 2004; Ocampo‐Peñuela et al., 2025). Our analysis of eBird data from Nigeria supports this distinction: initial contributions have been predominantly led by expatriates, with increasing participation from indigenous individuals following targeted capacity-building initiatives such as the Nigerian Bird Atlas Project (NiBAP) and the MSc in Conservation Biology and Ornithology at APLORI (Chandler et al., 2017a; Cresswell, 2018).

Demographic diversity and capacity-building drive inclusive growth in Nigerian bird clubs

Analysis of Nigerian bird club participants reveals a fairly diverse group, with reasonably balanced gender participation and a largely youthful membership, most of whom are under 40 years of age. These findings are drawn from a self-selected sample of 32 respondents, all of whom were active bird club members, and should be interpreted accordingly. The sample likely over-represents engaged, motivated participants and may not capture the full range of experiences and barriers among the broader Nigerian birding community. Motivational findings should therefore be treated as illustrative of patterns within this group rather than generalizable to indigenous Nigerian citizen science participants more broadly.

The high representation of individuals employed in environmental sectors or enrolled as students also reflects the initial capacity-building focus on academic and research institutions, targeting professional ornithologists and students from natural sciences as founding club members. This recruitment strategy aligns with established citizen science best practices, where academic networks facilitate the development of technical capacity and leadership (Sullivan et al., 2009; Bonney et al., 2009; Loss et al., 2015; Randler, 2021; Tiago et al., 2024). Respondents reported an average of eight years of birdwatching experience, frequent birding activity, and generally strong species identification skills, though experience levels varied widely. Among this group, conservation and awareness motives predominated, consistent with findings from similar participatory biodiversity monitoring programs (Randler and Großmann, 2022; Lowe et al., 2025). Persistent barriers included limited access to equipment and time constraints due to work, study, or family responsibilities, mirroring challenges identified in the broader citizen science literature (Merenlender et al., 2016; Benyei et al., 2023). The subsequent strategy of encouraging students to invite family and friends to club outings regardless of their prior experience with birding or scientific background was a deliberate inclusion strategy that broadened participation and supported sustained engagement, as documented in similar community-based monitoring programs (Şekercioğlu, 2012; Chandler et al., 2017a). Within this sample, the success of some bird clubs in drawing members from diverse backgrounds, promoting gender balance, and involving younger people illustrates how academic and professional networks can positively influence community composition. While persistent barriers such as equipment access and time constraints remain, strategies that foster community participation—such as encouraging members to involve family and friends—appear effective in expanding and sustaining engagement. These observations highlight promising directions for intentional capacity-building and barrier reduction in Nigerian citizen science, though broader evaluation across larger and more representative samples would strengthen the generalizability of these conclusions.

Conclusion

Our study provides strong evidence that targeted capacity-building and community inclusion strategies are associated with increased citizen science engagement in Nigeria. Our observations indicate that training initiatives were associated with a marked increase in participation, which remained elevated compared to pre-intervention levels. However, due to the absence of a control group and the potential influence of other contextual factors such as expanding peer networks and increased visibility of citizen science platforms, we interpret these findings as associative rather than strictly causal. While barriers for indigenous participants, including limited technical skills and resource access initially limited engagement and data quality; our results suggest that strategic investments in training, resource provision, and community development are likely contributing to enhanced indigenous participation and expertise, and contributing to reducing experience disparities over time. Differences in birding experience between indigenous and expatriate contributors reflect longstanding historical and cultural factors, but these gaps appear to be narrowing in the context of focused capacity-building and broader community building efforts. Inclusive recruitment and academic-oriented approaches continue to support and strengthen a local, demographically diverse, and youthful citizen science community in Nigeria. Together, these findings underscore the critical importance of intentional capacity-building and barrier reduction in fostering a vibrant, inclusive citizen science community and offer insights that may be valuable for other under-resourced biodiversity-rich countries seeking to enhance local engagement in citizen science.

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Footnotes

Edited by: Ana Isabel Catarino, Flanders Marine Institute, Belgium

Reviewed by: Martie Van Deventer, University of Pretoria, South Africa

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