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Home > VOLUME 30 > ISSUE 3 > Article 9 Research

A need for assessing the resiliency of conservation funding

Lant, M. J., C. R. Bendel, C. J. Parent, and M. A. Kaemingk. 2025. A need for assessing the resiliency of conservation funding. Ecology and Society 30(3):9. https://doi.org/10.5751/ES-16322-300309
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  • Michael J. LantORCIDcontact author, Michael J. Lant
    Department of Biology, University of North Dakota, Grand Forks, North Dakota, USA
  • Cayla R. Bendel, Cayla R. Bendel
    North Dakota Game and Fish Department, Bismarck, North Dakota, USA
  • Chad J. Parent, Chad J. Parent
    North Dakota Game and Fish Department, Bismarck, North Dakota, USA
  • Mark A. KaemingkORCIDMark A. Kaemingk
    Department of Biology, University of North Dakota, Grand Forks, North Dakota, USA

The following is the established format for referencing this article:

Lant, M. J., C. R. Bendel, C. J. Parent, and M. A. Kaemingk. 2025. A need for assessing the resiliency of conservation funding. Ecology and Society 30(3):9.

https://doi.org/10.5751/ES-16322-300309

  • Introduction
  • Methods
  • Results
  • Discussion
  • Conclusions
  • Epilogue
  • Author Contributions
  • Acknowledgments
  • Data Availability
  • Literature Cited
  • conservation; conservation funding sources; funding resiliency; recreational fishing
    A need for assessing the resiliency of conservation funding
    Copyright © by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution 4.0 International License. You may share and adapt the work provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license. ES-2025-16322.pdf
    Research

    ABSTRACT

    The ability to address conservation challenges hinges, in part, on a robust understanding of complex social-ecological systems. Conservation funding is a critical component that can impede or facilitate our ability to understand issues and overcome conservation challenges. Conservation funding is dynamic and is often dependent on organizations sustained by individual contributions (e.g., memberships, donations). A shift in funding sources, away from federal government support, could lead to greater uncertainty and instability in conservation funding. Herein, we use an individual-based conservation organization database to demonstrate how to assess funding resiliency by identifying subpopulation typologies (subgroups of individuals) that reflect similar patterns in conservation contributions. We identified three typologies that provide North Dakota Game and Fish Department support for managing and protecting natural resources. Most (~68%) individuals (typology I) infrequently contributed to recreational fishing conservation; few (~9%) individuals (typology III) provided frequent contributions to recreational fishing conservation over the 11-year study period. While conservation funding has been relatively consistent for North Dakota Game and Fish Department, it may be subject to rapid change. Identifying the number of conservation typologies (e.g., diversity) and associated characteristics (e.g., frequency and amount of funding contributions, socio-demographic characteristics) could provide conservation-oriented organizations the ability to quantify, track, and predict underlying contribution trends that are masked by overall (i.e., population-level) funding patterns. Ultimately, identifying subpopulations and associated contribution patterns could aid in avoiding potential losses in conservation funding.

    INTRODUCTION

    We lack a firm understanding of conservation organization constituency and associated monetary contributions. Many authors have called for different allocation of conservation funding (James et al. 1999, Wu and Boggess 1999, Kareiva and Marvier 2003, Waldron et al. 2013, Larson et al. 2021), yet great uncertainty remains regarding the conservation contributions of individuals. At one time, U.S. federal government organizations (e.g., National Science Foundation) dominated the sources of conservation funding; however, changes in economic conditions and the political landscape have shifted conservation funding toward large non-governmental organizations (NGOs) and state natural resource agencies (Bakker et al. 2010). These emerging sources of conservation funding are often dependent on voluntary contributions of individuals (e.g., donations, memberships, license sales), which can fluctuate dramatically depending on socio-economic values (Bakker et al. 2010, Larson et al. 2021). Inadequate funding, repeatedly cited as a major barrier (among others) to meeting conservation challenges (Evans et al. 2012, Waldron et al. 2013, Echols et al. 2019), hinges on a concrete understanding of who is contributing and how they are contributing to conservation. Shifts in conservation contributions have already been identified in Asian country NGOs (Parks 2008), and Bakker et al. (2010) acknowledged the changing landscape of conservation funding in the United States. Without this knowledge and understanding, we have no way of assessing the short- and long-term resiliency of conservation funding.

    Several studies have investigated conservation funding sources (James et al. 1999, Bakker et al. 2010, Gallo‐Cajiao et al. 2018, Larson et al. 2021) and identified large NGOs (e.g., World Wildlife Fund) as emerging sources of funds for conservation. However, the sustainability of NGOs depends on voluntary contributions of individuals through memberships. Therefore, it is not the organization itself but the constituents that facilitate conservation efforts. Yet, very little is understood about who is, and how individuals are, contributing to conservation funding due to the lack of peer-reviewed literature on the topic. Parks (2008) identified extreme fluctuations in Asian country NGO funding as a result of international donor priority shifts, suggesting heterogeneity among constituency contributions. Identifying conservation typologies, defined as individuals who share conservation contribution histories (e.g., donation, membership, license purchasing histories) could be critical for understanding and predicting fluctuations in conservation funding worldwide (Parks 2008). We assume that shared contribution histories reflect similar motivations and values of conservation (Ijabadeniyi and Govender 2019).

    We contend that existing user-pay conservation model databases (e.g., donations, membership, license sale) could provide important information for understanding current contributions, identifying conservation typologies, and predicting future changes in conservation funding. We assume that most organizations track their funding at the population (i.e., not subpopulation or individual) level, and consider their membership populations to be functionally homogenous. However, should variation in conservation contribution in subpopulations (i.e., typologies) exist, it poses a potential challenge for organization sustainability. An understanding of current and future changes in contributions of a conservation organization’s constituency is essential for its relevancy, viability, and impact on conservation. In other words, a resilient organization will have the greatest impact on conservation by maintaining a diverse constituency.

    Our goal is to demonstrate the utility of user-pay conservation model databases in making subpopulation-level inferences and assessing organization funding resiliency to guide decision-making for conservation organizations. We used a large (n > 285,000) recreational fishing license online database from the state of North Dakota, USA to determine if we could detect subpopulations (hereafter angler typologies) that differ in their frequency, timing, and duration of contributions to conservation. Recreational fishing license sales are the primary funding source for many natural resource conservation agencies that aim to “protect, conserve and enhance fish and wildlife populations and their habitat for sustained public consumptive and nonconsumptive use” (North Dakota Game and Fish n.d.). We then explored differences in socio-demographic characteristics among identified angler typologies. We hypothesize that the decision to participate via a membership purchase (e.g., license) has immense meaning associated with an individual’s psychology (Lichev 2017), social behavior (Yang 2022), and loyalty (Jacoby and Kyner 1973). Identifying shifts in subpopulation participation could be used to detect early warning signs of changes in conservation funding and resiliency. We acknowledge that angler licenses may represent a unique type of conservation contribution (i.e., provides access to resources), but believe the concept and methodology has broad application to other types of conservation funding.

    METHODS

    Angler license sale database

    Annually, individuals in the state of North Dakota, USA contribute to recreational fishing conservation in the state by purchasing a recreational fishing license. The North Dakota Game and Fish Department’s (NDGF) online angler license sale database contains information on long-term angler participation in the state. The database is a record of an individual’s interannual license purchasing history. From 2009 to 2015, licenses could be purchased through an in-person vendor or by using the NDGF website; starting in 2016, licenses could be purchased only online. Prices of angler licenses increased marginally (effective in 2014) during our study period (2009–2019) (costs are reported in Table 1). We assumed this change had minimal influence on license purchases because there was no obvious changes in license sales from 2013 to 2014. We evaluated online license sales (~64% of angler license purchases) of resident anglers throughout our study period. NDGF uses license sale revenue for conservation efforts such as aquatic habitat rehabilitation, development of user access areas, and protection of sportfish species. The database includes the year and type of license purchased, which is linked to a unique customer identification number. Individuals who are 16 years of age and older are required by law to purchase a recreational fishing license in order to fish in North Dakota. Residents of North Dakota can purchase different types of licenses within a given year, which putatively reflect the experiences sought and the intended conservation contribution (Table 1).

    The NDGF angler license sale database also includes socio-demographic information, such as the individual’s ZIP code (U.S. Zone Improvement Plan), age, and sex. Rurality was determined using an angler’s ZIP code and 2021 population and spatial data (ESRI 2021). We followed U.S. Census Bureau definitions for urban areas (urban ≥ 2590 people per square kilometer [ppskm]) and rural areas (rural < 2590 ppskm) (DaRugna et al. 2022). Generational regimes (e.g., Millennial) have also been linked to behavior, attitudes, and values associated with conservation (Manfredo et al. 2003, Tomasello 2016). Generation of individuals was calculated using Brunjes’ (2023) definitions, based on both the Pew Research Center’s Gen Z analysis and U.S. Census Bureau’s Baby Boomer definitions. We combined the “Boomer” generations I and II into a single Boomer generation, as suggested by Hogan et al. (2008).

    Sequence analysis

    We used sequence analysis to identify angler typologies, which are groups of anglers exhibiting similar conservation contributions that are reflected in their interannual license purchasing patterns. Sequence analysis provides a robust way of analyzing conservation contribution histories with respect to the sequencing, timing, and duration that individuals purchase specific license types and contribute to fisheries conservation. We present an application of this methodology that weighs multiple aspects of individuals’ contribution history (sequencing, timing, and duration), as well as the “type” of contribution (i.e., license) an individual provides to robustly classify conservation efforts throughout time.

    Sequence analysis, originally used for DNA sequencing, has been adopted by social sciences to predict trajectories for subpopulations or typologies that exhibit similar sequences (Abbott 1995). A sequence analysis is a nonparametric statistical analysis that is sensitive to the sequencing, timing, and duration of states (e.g., license types) an individual exhibits throughout their sequence (e.g., conservation contribution history). The use of sequence analysis is advantageous because it has the ability to describe trajectories of individuals, how that process changes over a study period, and the time at which transitions occur at a population or subpopulation level (Cezard et al. 2022). Sequencing is defined as the order of distinct state occurrences throughout the entire sequence (Cezard et al. 2022). Timing is defined as when the transition between states occurs (e.g., not purchasing a license for the first 3 years and then purchasing a regular fishing license in the fourth year) (Cezard et al. 2022). Duration is defined as the length an individual exhibits the same state chronologically without interruption of entering another state (Cezard et al. 2022).

    Sequence analysis first uses a dissimilarity measure to calculate the differences in sequence frequencies, timings, and durations of states, and then a cluster analysis is performed on the cost matrix to group individuals that exhibit statistically similar sequences, with the end result being typologies of individuals that exhibit similar sequences. We used the R package TraMineR (Gabadinho et al. 2011) for sequencing angler license purchasing histories, and the R package WeightedCluster (Studer 2013) for cluster analysis of angler license purchasing histories in R version 4.3.0 (R Core Team 2023). Due to our large sample size (n = 285,074), we randomly subsampled seven groups because TraMineR (Gabadinho et al. 2011) limits sample size (n ≤ 46,431). Subsampled groups were subsequently combined only for socio-demographic characteristic tests.

    We used optimal matching to calculate dissimilarities (Studer and Ritschard 2016). Optimal matching attempts to turn sequence x into sequence y, and calculates the cost for substituting, inserting, or deleting states within sequences. Costs associated with the substitution operation are set by a substitution matrix; costs associated with insertion or deletion operations are set by an indel value (Studer and Ritschard 2016, Cezard et al. 2022). Indel values that are set high enable dissimilarity to be particularly sensitive to timing. Additionally, indel costs unequal to 1 assume states are not equally different. For our study, we kept the substitution matrix and indel cost equal to 1 because all license types equally qualify an individual to participate in, and contribute to, recreational fishing. Succeeding the cost matrix calculation, we used Ward’s (1963) method to identify the number of unique angler typologies (Gauthier et al. 2010).

    Socio-demographic characteristics of typologies

    Once we identified angler typologies using sequence analysis, we then compared socio-demographic characteristics, which have been linked to recreational fishing attitudes (Karanth et al. 2008). We used a Chi-square test to determine differences among angler typology sex, rurality, and generation types. Statistical significance was determined using α = 0.05 (R version 4.3.0, R Core Team 2023).

    RESULTS

    Angler typologies

    We identified three distinct angler typologies based on sequencing, timing, and duration of license types purchased throughout 2009–2019 (Fig. 1 and 2). Angler typology I and III exhibited the greatest differences among license purchasing and demographic characteristics. Typology II exhibited intermediate characteristics, and shared license purchasing and demographic characteristics that were unique to typologies I and III. Angler typology I infrequently contributed to recreational fishing conservation (i.e., lack of license purchase), and contributed primarily a comparatively small contribution, given the cost of license type purchased (Fig. 1 and 2; Table 1). Most individuals in typology I purchased an annual resident fishing license only one or two times during the 11-year study period (Fig. 3) and chose the license type that both limited experiences (only fishing resources) and was the least expensive (Table 1). Thus, typology I, at an individual level, contributed to recreational fishing conservation the least but represented most of the recreational fishing conservation constituency (~68%). Angler typology III frequently contributed to recreational fishing conservation and purchased primarily a combination fishing and hunting license (Fig. 1 and 2). In stark contrast to angler typology I, most typology III individuals purchased a license more than seven times during the study period (Fig. 3) and chose the most expensive license type (Table 1), which provided access to the greatest quantity of resources (fishing resources, hunting resources). Thus, typology III, at an individual level, contributed to recreational fishing conservation the most but represented the minority of the recreational fishing conservation constituency (~9%).

    We found significant differences in socio-demographic characteristics (sex, p < 0.0005; rurality, p < 0.0005; generation, p < 0.0005) among all typologies (Fig. 4). Typology I had the highest number of females, exhibited the strongest urban residency, was primarily younger, and included mostly Millennial generation individuals (Fig. 4). Typology III had the lowest number of females and significantly fewer individuals residing in urban areas, and exhibited a diversity of generational representation among Generation X, Millennial, and Boomer (Fig. 4).

    DISCUSSION

    Funding is one aspect that is essential for effective conservation. Conservation funding supports and facilitates efforts to meet conservation challenges such as preserving biodiversity (Bell 1993, Kareiva and Marvier 2003, Ellis 2013), preventing habitat fragmentation (Saunders et al. 1991, Margules and Pressey 2000, Rayfield et al. 2023), and slowing urban expansion (Chen et al. 2020). Yet, we know very little about the resiliency of conservation funding supported through individual contributions. Future conservation efforts will likely depend on the sustainability of conservation-oriented organizations to combat environmental challenges (Waldron et al. 2013). We have demonstrated the utility of using a conservation contribution database to reveal patterns and identify heterogeneous contribution typologies. Understanding heterogeneity among constituency contributions could be leveraged with additional information when readily available (e.g., socio-demographic characteristics) to identify individual and subpopulation-level patterns (i.e., who is contributing and not contributing). Typology differences in conservation contributions such as those identified in our study could be used to inform conservation decisions and determine organization sustainability and relevance. Furthermore, heterogeneity among constituency contributions may be tied to motivations or experiences received from previous contributions and could be used for forecasting conservation funding resiliency (i.e., future changes in organization funding) (Johnson et al. 2017, Echols et al. 2019) or leveraged with behavioral information to identify strategies for recruiting new members, sustaining current members, or engaging lapsed members.

    Conservation funding is undoubtedly subject to change in the future (Bakker et al. 2010, Johnson et al. 2017), which will challenge our ability to address global threats to natural resources. We may have already observed the initial impact of limitations in conservation effort due to a lack of funding, such as the global extinction crisis (Knapp et al. 2021). Global changes such as the projected 30–180% urban expansion in the next 100 years (Chen et al. 2020) could cause higher variability in conservation funding. We observed that typology I individuals (majority of fishing conservation constituency, infrequent contributors) exhibited a significantly higher residency in urban areas and were represented primarily by Millennial generation individuals. At the individual level, typology I contributed the least by purchasing primarily the annual resident fishing license, whereas typology III contributed the most by purchasing primarily the combination fishing and hunting license. When compared with frequency of contributions (i.e., typology I infrequent, typology III frequent), we infer that typology I individuals may exhibit minimal commitment and typology III maximum commitment to recreational fishing conservation. However, given this commitment, typology III may have the greatest impact on the resource by exerting more fishing effort. We speculate that fishing conservation funding may become increasingly variable if typology I becomes even more prominent in the future. Funding that is dependent on constituency contributions and is influenced by internal (e.g., aging) and external (e.g., urbanization) characteristics could shift to being highly variable and could become unreliable. In an extreme case, the potential loss of an entire typology (e.g., an aging typology III) could dramatically impact the resiliency and sustainability of an organization.

    We observed a significant difference in generational representation among angler typologies. Individual values and attitudes, such as intrinsic and extrinsic values of wildlife, have been suspected to be heterogeneous across generations (Tomasello 2016, Manfredo et al. 2017). Furthermore, Manfredo et al. (2017) observed differences among individual values between industrialized areas and non-industrialized areas, and hypothesized that as countries industrialize (i.e., urbanization, population growth), societal values of conservation and wildlife move from utilitarian (pre-industrialization) toward protection-orientation (post-industrialization). Thus, we predict that differences in contributions for recreational fishing conservation among angler typologies may be influenced by differences in generational representation stemming from conservation and wildlife value heterogeneity. For instance, fishing has traditionally been motivated primarily by harvest. However, new primary motivations, such as catch and release, tranquility, or scenic beauty, have been identified and attributed to new “social norms” (Gilbert and Sass 2016, Sass and Shaw 2020). Sherif (1936) identified a correlation between social norms and individual values. Further industrialization, such as increased urbanization in the United States, may direct wildlife values toward protection-orientation, and threaten the funding resiliency of some conservation organizations.

    Recognition that some individuals, or entire typologies, could be contributing across multiple organizations (e.g., World Wildlife Fund, Audubon Society) presents possible opportunities to understand the resiliency of the entire conservation funding landscape. Examination of cross-organization patterns and the ability to track individual contributions across multiple organizations could provide broad tracking of user-pay conservation funding. Multiple organization contributions may also be tied to individual values or attitudes toward conservation. For instance, if we examine the success of a business, we can conclude it is dependent on meeting the needs of customers (Gladson Nwokah 2009). In the context of conservation organizations, this could be efforts taken to achieve an organization mission, such as habitat restoration projects to meet the World Wildlife Fund’s mission “to conserve nature and reduce the most pressing threats to the diversity of life” (World Wildlife Fund n.d.). If customer expectations are not met (i.e., alignment of conservation values between organization and contributors), loss of entire segments (i.e., typologies) may result (Böttcher et al. 2009). Therefore, identifying and tracking cross-organization contribution among typologies could be used to forecast societal-level changes in values and attitudes about natural resources and conservation (Böttcher et al. 2009, Nayyar 2019). However, the ability to observe an individual’s conservation contributions across multiple organizations does not currently exist.

    Conservation-oriented organizations may not suspect the need to evaluate their own funding resiliency because population-level funding may appear stable and resilient (Fig. 5).

    The conservation funding landscape is dynamic (Bakker et al. 2010), and underlying subpopulation-level characteristics (e.g., values, attitudes) could impact overall conservation-organization funding resiliency. Sequence analysis provides a robust and objective approach to identifying heterogeneity of subpopulation-level conservation contribution. Furthermore, sequence analysis can be followed by survey approaches to characterize a variety of attributes, such as values and motivations, and capture information not traditionally collected (e.g., age, sex, ZIP code) within and among identified typologies. Evaluating funding resiliency can be challenging due to its novelty as an emerging topic in the field of business (Eriksson et al. 2022). Resiliency, in an ecosystem context, is the ability of a system (i.e., organization) to return to a stable state when subject to disturbances. Carpenter et al.’s (2011) seminal paper on early warning signs of regime shifts identified high variation in system characteristics (i.e., population abundance variation) to be positively correlated with predicting system regime shifts. If we use Carpenter et al. (2011) to contextualize a conservation organization’s funding, high variability in conservation contributions at any level (i.e., population, subpopulation, individual) may indicate a vulnerability in a conservation funding source. However, these patterns in conservation contributions are still unclear, and it remains a ripe area for future research. We advocate for further investigation using sequence analysis as a preliminary method for identifying heterogeneity in constituency contribution to prepare for the imminent changes to conservation funding (Bakker et al. 2010).

    Limitations

    We investigated constituency dynamics of only a single source of conservation funding, which could have limited application to the broader types of conservation funding worldwide. License sales have one primary distinction among voluntary conservation contributions (e.g., donations, memberships) in that constituents receive something for their contribution. Hunters, anglers, and trappers are allowed to recreationally extract natural resources (e.g., harvesting wild game) in exchange for their monetary contribution to the conservation-oriented organization. Other contribution types such as donations or memberships do not explicitly provide constituents a return. Due to a lack of literature on this topic, it is unclear how this distinction may influence the resiliency of an organization’s funding. Disparities in typology richness and characteristics among these distinct funding sources (i.e., license sales, donations, memberships) may reveal opportunities to strengthen funding by adopting practices employed by more resilient organizations. Despite different conservation contribution types, we assume that all voluntary contributions aim to support an organization’s mission.

    CONCLUSIONS

    The future of conservation is uncertain. We are faced with a suite of conservation challenges (e.g., climate crisis, biodiversity loss, habitat fragmentation) that can be addressed, in part, through consistent and resilient funding sources. However, we lack information on subpopulation characteristics and patterns in contributions that will likely underpin these conservation efforts in the future (i.e., a shift away from federal funding). Our work attempts to begin filling this knowledge gap and is a starting point that is intended to provide conservation organizations with objective methods such as the use of sequence analysis to investigate their own constituencies. Much work is still needed to contextualize the funding resiliency of an organization based on constituency characteristics (e.g., diversity of typologies). However, we postulate that relationships observed in ecological systems (e.g., Carpenter et al. 2011) could be used to begin understanding a conservation organization’s funding resiliency.

    Funding will continue to be a topic in conservation biology because it is an essential component in meeting conservation and management challenges. We expect that shifts in funding will continue and could require even greater contributions from NGOs in the future (Bakker et al. 2010). If so, more emphasis should be placed on understanding individual contributions and linking them to organization-level resiliency. This has already occurred within state fish and wildlife management agencies that recognize the importance of individual contributions, and has prompted large-scale efforts to address issues related to recruitment, retention, and reactivation of sportspersons (Rubino and Serenari 2022, Granneman et al. 2024). We are unaware of any similar efforts related to NGOs. Perhaps by assessing both government entities and NGOs we can identify which organizations will be the most resilient, and the mechanisms responsible for sustaining resiliency within and among conservation funding sources.

    EPILOGUE

    Many of the traditional forms of conservation funding in the United States appear to be threatened, shifting, or have perhaps outlived their original intention. Many federal agencies are expecting a substantial reduction in funding given recent socio-political events. Furthermore, reliance on a user-pay, user-benefit funding model that provides the backbone of funding for most state natural resource agencies may no longer be sufficient in ensuring the sustainability of conservation funding. Until contemporary times, the user-pay, user-benefit funding model reliably funded conservation and was considered resilient. However, declines in fishing and hunting participation and license sales throughout the United States threaten the viability of this user-pay and user-benefit funding model. These examples and recent events suggest that the exploration of alternative funding models may be necessary to ensure stable and resilient conservation funding in the future.

    RESPONSES TO THIS ARTICLE

    Responses to this article are invited. If accepted for publication, your response will be hyperlinked to the article. To submit a response, follow this link. To read responses already accepted, follow this link.

    AUTHOR CONTRIBUTIONS

    Michael J. Lant – conceptualization; formal analysis; writing original draft; writing review and editing. Cayla R. Bendel – conceptualization; writing review and editing. Chad J. Parent – data curation; writing review and editing. Mark A. Kaemingk – funding acquisition; project administration; conceptualization; formal analysis; writing review and editing.

    ACKNOWLEDGMENTS

    We thank all the past and current employees of the North Dakota Game and Fish Department for collection of the data used in this study. We also thank the North Dakota Game and Fish Department for providing the funding for this research. The research was approved by University of North Dakota’s IRB (#0003412).

    Use of Artificial Intelligence (AI) and AI-assisted Tools

    No Artificial Intelligence was used in this work.

    DATA AVAILABILITY

    Data curated, generated, analyzed, or used in any manner during this study are not available due to maintaining the privacy of anglers, and to legal restrictions of the North Dakota Game and Fish Department and the University of North Dakota.

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    Corresponding author:
    Michael Lant
    michael.lant@montana.edu
    Fig. 1
    Fig. 1. Conservation contribution history index plot for each angler typology generated from the North Dakota Game and Fish Department’s resident angler license database, 2009–2019. Plots depict all individual conservation contribution histories for a single (<em>n</em> = 45,000) random sample. Rows represent complete contribution history for individuals. Colors denote contribution type (i.e., license type purchased).

    Fig. 1. Conservation contribution history index plot for each angler typology generated from the North Dakota Game and Fish Department’s resident angler license database, 2009–2019. Plots depict all individual conservation contribution histories for a single (n = 45,000) random sample. Rows represent complete contribution history for individuals. Colors denote contribution type (i.e., license type purchased).

    Fig. 1
    Fig. 2
    Fig. 2. Conservation contribution history distribution plot for each angler typology generated from the North Dakota Game and Fish Department’s resident angler license database, 2009–2019. Plots depict the proportion of contribution type among angler typologies of a single (<em>n</em> = 45,000) random sample. Colors denote contribution type (i.e., license type purchased).

    Fig. 2. Conservation contribution history distribution plot for each angler typology generated from the North Dakota Game and Fish Department’s resident angler license database, 2009–2019. Plots depict the proportion of contribution type among angler typologies of a single (n = 45,000) random sample. Colors denote contribution type (i.e., license type purchased).

    Fig. 2
    Fig. 3
    Fig. 3. Contribution-frequency plots for all individuals (<em>n</em> = 285,074) among the three angler typologies generated from the North Dakota Game and Fish Department’s resident angler license database, 2009–2019. Note different y-axis scales.

    Fig. 3. Contribution-frequency plots for all individuals (n = 285,074) among the three angler typologies generated from the North Dakota Game and Fish Department’s resident angler license database, 2009–2019. Note different y-axis scales.

    Fig. 3
    Fig. 4
    Fig. 4. Socio-demographic characteristic frequency plots for all individuals (<em>n</em> = 285,074) among the three angler typologies generated from the North Dakota Game and Fish Department’s resident angler license database, 2009–2019.

    Fig. 4. Socio-demographic characteristic frequency plots for all individuals (n = 285,074) among the three angler typologies generated from the North Dakota Game and Fish Department’s resident angler license database, 2009–2019.

    Fig. 4
    Fig. 5
    Fig. 5. Conceptual figure demonstrating interannual variation in conservation funding (panel A), subpopulation diversity of constituency (panels B), and cross-organization contributions (panels C) of a resilient versus non-resilient conservation-oriented organization constituency. Roman numerals (panels B) denote the number of subpopulations with associated histograms of frequency of contributions in years 1–9 for number of individuals. Arrows (panels C) denote contributions to associated additional conservation-oriented organizations. The top histograms (panels B) represent total conservation funds throughout years for resilient and non-resilient organizations.

    Fig. 5. Conceptual figure demonstrating interannual variation in conservation funding (panel A), subpopulation diversity of constituency (panels B), and cross-organization contributions (panels C) of a resilient versus non-resilient conservation-oriented organization constituency. Roman numerals (panels B) denote the number of subpopulations with associated histograms of frequency of contributions in years 1–9 for number of individuals. Arrows (panels C) denote contributions to associated additional conservation-oriented organizations. The top histograms (panels B) represent total conservation funds throughout years for resilient and non-resilient organizations.

    Fig. 5
    Table 1
    Table 1. North Dakota resident fishing conservation contribution types and associated contributions (2014–2019). Residents are individuals who have claimed occupancy within the state of North Dakota for more than 6 months.

    Table 1. North Dakota resident fishing conservation contribution types and associated contributions (2014–2019). Residents are individuals who have claimed occupancy within the state of North Dakota for more than 6 months.

    Fishing license type Annual cost
    Fishing prerequisite (required) $1
    Annual resident fishing $18
    Married couple $24
    Combination hunting/fishing $52
    Veteran combination $3
    Senior citizen $5
    Totally permanently disabled $5
    Veteran 50% related disability $5
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