Sie können Operatoren mit Ihrer Suchanfrage kombinieren, um diese noch präziser einzugrenzen. Klicken Sie auf den Suchoperator, um eine Erklärung seiner Funktionsweise anzuzeigen.
Findet Dokumente, in denen beide Begriffe in beliebiger Reihenfolge innerhalb von maximal n Worten zueinander stehen. Empfehlung: Wählen Sie zwischen 15 und 30 als maximale Wortanzahl (z.B. NEAR(hybrid, antrieb, 20)).
Findet Dokumente, in denen der Begriff in Wortvarianten vorkommt, wobei diese VOR, HINTER oder VOR und HINTER dem Suchbegriff anschließen können (z.B., leichtbau*, *leichtbau, *leichtbau*).
Habitat ownership in the U.S. is primarily private, complicating management of public trust wildlife. Under this configuration, the rights and interests of private landowners can be at odds with those of trust beneficiaries. Recent wildlife scholarship has incorporated private landownership into analyses, but limited data accessibility and analysis tools have precluded landscape-wide assessments of landownership patterns and trends. Here, we present novel methods for analyzing cadastral data and the resulting assessment of private landownership characteristics in the large U.S. state of Montana from 2004 to 2023. Results showed 63% of private land/habitat in the state is owned by 3500 landowners who each control at least 3600 acres; a growing majority of landowners are legal entities (e.g., LLCs), rather than individuals or families; and substantial parcelization has occurred. We discuss implications of these trends, including advantages for wildlife, benefits to landowners, and complications for public trust wildlife management.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Introduction
Wildlife in the United States (U.S.) are ostensibly managed under the public trust doctrine that asserts wildlife cannot be privately owned but instead belong to the citizens of the country (The Wildlife Society 2010). This foundational principle of wildlife management has ancient origins, dating back to at least sixth-century Rome, and has been of profound importance to free societies throughout history (Nie et al. 2020). The oft-cited North American Model of Wildlife Conservation lists the public trust doctrine as one of its seven pillars (Organ et al. 2014), and courts, including the U.S. Supreme Court, have affirmed the doctrine and the requirement of its application to wildlife management (Bruskotter et al. 2011). Federal and State governments are obligated as trustees of the public trust to preserve wildlife and, “secure its beneficial use in the future to the people…” (Geer v. Connecticut, 161 U.S. 519, 1896). The wildlife public trust doctrine is in many ways a repudiation of the British rule that coupled ownership of land to that of wildlife, and offers protection against the monopolization of natural resources (Nie 2024).
In practice, state sovereign ownership of wildlife is complicated by the fact that wildlife habitat1 is disproportionately held in private ownership. Land in the U.S. is approximately 60% private, with most states (39) having higher proportions, and only six Western states and Alaska having majority public (USGS 2022). Even in places with smaller proportions of private land, quality wildlife habitat is often found on private parcels due to settlement patterns that favored privatization of lands suitable for agriculture and industry, leaving public those rugged lands with less water and poorer soils (Jenkins et al. 2015; Robinson et al. 2019). One estimate suggests 80% of wildlife habitat in the U.S. is privately owned (Benson, 2001). For some wildlife species, hunting pressure can exacerbate this imbalance, causing game species to seek refuge on private lands (Sergeyev et al. 2022). This configuration of public wildlife on private lands can pit the rights and interests of private landowners against those of public beneficiaries (Watson 2012).
Anzeige
The importance of private lands to wildlife has gained attention among natural resource scholars, although most wildlife habitat studies do not consider variation in ownership type. Some recent publications have investigated the role of private lands in species migration (Gigliotti et al. 2022); analyzed states’ investments in private land conservation (Morgan et al. 2019); and incorporated ownership characteristics into habitat selection models (Oakleaf et al. 2006). Most habitat assessments and prioritizations, however, do not explicitly consider private landownership (Cullen, 2012), with a couple notable exceptions, especially recently (Smith et al. 2025; Martinez et al. 2024; Jenkins et al. 2015).
A few authors have acknowledged the potential conflict between private lands and public trust wildlife (Sagarin and Turnipseed 2012; Slagle et al. 2023), and although the issue has been the topic of some public discourse and policy debate (e.g., Montana Private Land/Public Wildlife Advisory Committee, Wyoming Private Lands Public Wildlife Access Program), there is a dearth of landscape-scale assessments of private ownership patterns or discussions of how such patterns might affect public trust wildlife outcomes. For example, landowners’ decisions about habitat management or land conversion may have direct effects on public trust wildlife; their choices to allow or disallow public access determine whether and how benefits of public wildlife flow to beneficiaries; and the proportion of land owned by individuals versus legal entities such as Limited Liability Companies (LLCs) likely influences the transparency of management decisions and accessibility of owners. Although legal accountability does not vary across ownership type, owners whose names are publicly known are more accessible to beneficiaries and accountable for their wildlife management actions via informal governance mechanisms, like social norms. Landowners’ accessibility and accountability to beneficiaries are fundamental to fulfilling wildlife public trust since their decisions directly shape the habitats on which public trust wildlife depend and it is difficult to discern what truly constitutes a public benefit without beneficiary input or feedback (Freyfogle 2007). The true owners of legal entities are often shielded from public view (outside of lawsuits), and new financial policies adopted over the past 25 years have led to an increase in land held under these legal structures (Ashwood et al. 2022).
The spatial extent and pattern of private landownership can affect the wildlife held in public trust in several important ways. Although the number of private landowners in a state is generally quite large (i.e., usually hundreds of thousands of owners), the distribution of land among those owners is often skewed, with many owners of small parcels and relatively few owners of large parcels (Ver Planck et al. 2016). Decisions by these large parcel owners disproportionately affect wildlife habitat and dependent species. From this arrangement, a few natural questions arise: How concentrated is ownership of public trust wildlife habitat? Can the public (i.e., beneficiaries) identify and interact with these outsized stewards of the public trust? Is habitat being distributed among more owners over time, or is it concentrating in fewer hands? How much land is controlled by individuals versus legal entities, the former of whom are identifiable and accessible to the public whereas the latter may not be due to legal firewalls, and are these proportions shifting over time? In some instances, parcels could be large enough that many, most, or all wildlife species found there may never leave the property—what are the implications for the public trust when access to wildlife is so singularly controlled? Parcelization occurs when land is subdivided and distributed among several owners—is parcelization occurring and if so, what are the implications for wildlife habitat fragmentation? Conversely, if owners are consolidating landownership, what are the implications for public access? Missing from the literature and many wildlife policy discussions are answers to these foundational questions about how lands and habitats are distributed among private owners, who these owners are, how accessible they might be to beneficiaries of the public trust, and how this landscape of private land habitat is changing over time.
Spatially-explicit landownership data has long been compiled and used by government agencies, yet public access to it has generally been restricted or costly (Rissman et al. 2017). Availability is increasing, however, with some local and state governments providing free, online access and private vendors offering datasets at county-, state-, or country-wide extents, sometimes at reduced costs for research purposes (e.g., Regrid). Here, we use spatial landownership data to examine the patterns of private landownership across an entire U.S. state, investigating the characteristics of private landowners and the changes in these attributes over time. We focus our inquiry on the large, western state of Montana because landownership data is freely available for public access, including annually archived datasets for the past 20 years, and private land in the state supports myriad wildlife species. Our specific research questions included: (i) how are private lands divided among landowners?; (ii) in what types of ownerships are private lands held?; (iii) how have these characteristics of landownership changed over time; and (iv) how might these characteristics of landownership complicate public trust wildlife considerations? By advancing methods to answer these questions and providing longitudinal trend data for Montana’s landownership patterns, we seek to inspire and empower similar inquiry in other jurisdictions.
Anzeige
Methods
We used a multi-step approach to classify and analyze landownership patterns in Montana using spatial landownership data across nearly 20 years at roughly five-year intervals: 2004, 2008, 2013, 2018, and 2023 (Fig. 1). Unlike most US states, these data are publicly and freely available in Montana via the MT State Library (2024); see Supplemental Information for full description of data and attributes. We processed these data by dissolving parcels into ownerships (regardless of contiguity of parcels) and calculating total acreages owned by unique entities, including addressing unattributed data, primarily large public rights of way2. To classify landowners by ownership type, we used OpenAI’s large language models in a multi-step process resulting in a fine-tuned model that classified landowners into eight ownership types based on recorded owner’s name (GitHub repository of code available in Supplemental Information). For property attribute categorization, we normalized total annual acreage data to 2023 totals to account for minor variation in private land coverage of each year’s dataset, categorized properties into the top 10%, 1%, and 0.1% of all private ownerships based on size, and assigned property ownership as in-state or out-of-state based on mailing addresses. We present our findings using acres because it is the familiar unit to parties most directly interested in Montana landownership, management, and wildlife implications. We provide details on each of these methods below.
Fig. 1
Flowchart of cadastral data processing and analysis
To examine the patterns of private landownership in Montana, we accessed cadastral datasets for the years 2004, 2008, 2013, 2018, and 2023 (Montana State Library, 2024). These datasets provided detailed information on land parcels and their ownership. We processed these datasets using the ArcGIS Pro ‘dissolve’ command to combine individual parcels into larger ownership units, ensuring that distinct parcels under the same ownership (i.e., identical tax mailing addresses) were treated as a single entity, regardless of geographic continuity. This step allowed us to accurately calculate the total acreage controlled by each owner across all parcels at each point in time. Additionally, we addressed unattributed data, which primarily consisted of large areas of public road rights-of-way and federal land, by categorizing them as public. The processed data served as the foundation for subsequent analyses, including landowner classification and categorization based on ownership characteristics.
Landowner Classification
To classify landowners into different ownership types (e.g., individuals, LLCs, public), we used an iterative approach leveraging two OpenAI LLMs (Gilardi et al. 2023; Kuzman et al. 2023). We began with the dissolved list of landowners which contained 370,114 landowners. To classify the landowners, we used the OpenAI API (OpenAI, 2023) with the most advanced model available at the time, davinci-text-003. Using the ‘owner name’ attribute field, we classified groups of 10-20 owners 12 times to refine our prompt. We adjusted our prompt to use “few-shot learning” (Wang et al. 2020) and then classified a subset of 1000 landowners into the following categories: individual, joint-family, trust-estate, partnership, LLC, other-corporation, public, and uncertain. Owners were classified as follows:
“individuals” if there was only one set of first and last names (with or without a middle initial or suffix) listed in the ownership records;
“joint/family” if there were more than one set of first/last names listed, typically joined by an “and” or ampersand. Trailing conjunctions (e.g., “Jane Doe &”) also indicated additional owners;
“trust-estate” if the ownership records listed a trust, estate, or beneficiaries of such an entity;
“partnership” if the ownership records listed any type of legal partnership besides an LLC;
“LLC” if the abbreviation ‘LLC’ was listed in the ownership record;
“other-corporation” if the ownership record listed ‘INC,’ corporation, company, a company name that was distinguishable from a first/last name combination, churches, or other associations/groups such as non-governmental organizations or sportsman’s groups; and
“public” if the ownership record listed any public entity such as city, state, federal agency, tribal sovereign, or public utility, etc.
We manually assessed the initial classification to identify and correct errors. Based on this assessment, we updated the prompt for the davinci-text-003 model and then used the model to classify an additional 5554 landowners and manually assessed for errors (of which there were less than 1%). The most common errors were ambiguities between individual and joint ownership. Some examples included “John Doe &”, “John Doe AND”, and “Jane Doe 80%” all of which we re-classified as joint/family ownership. We used this data set to fine-tune a final custom classification model. To prepare the data to fine-tune the classification model, we used the OpenAI fine-tune API tool and reformatted the data to use all lowercase letters, following the recommendations provided by the tool developers. An ‘ada’ model was chosen for the fine-tuning, based on recommendations from OpenAI that a fine-tuned ada model would give acceptable accuracy and be orders of magnitude cheaper than the fine-tuned davinci model. This proved to be the case, as the training loss of the ada model was 1.4% and the validation loss was 1.6%, indicating performance that matched our manual classification. The fine-tuned model took approximately 15 minutes to train. We deployed this model against the full list of 370,114 landowners. We tested different batch sizes and determined that a batch size of 100 fit within the token limits for efficient processing. The full classification took approximately 90 minutes. After this classification, we manually inspected approximately ten thousand classifications and found no meaningful errors. Following the classification process we conducted a case-by-case review of the largest 1000 properties classified as “other-corporation” in 2023 to understand the nature of these businesses. We discuss this review below, however the owner names alone did not provide sufficient information to reliably infer more detailed information about property owner type or land use or to allow more granular classification.
Landownership Characteristics
To categorize properties by size and determine ownership characteristics, we normalized acreage of public and private land, respectively, in each year’s dataset to totals from 2023. This normalization was necessary because the total acreages of land included by the Montana State Library datasets fluctuated over the years, primarily due to the inclusion/exclusion of large public or tribal parcels. For each year we calculated the ratio of total public and private acreage by category type. We multiplied every parcel size by the ratio for its year within category type to ensure the total acreage in that year matched the 2023 total and the category type subtotal. We used normalized data for all comparative analyses.
We categorized properties into size-based groups, defining the top 10%, 1%, and 0.1% of all private ownerships based on the 2023 distribution of landownerships. For this categorization, we used rounded numbers, putting the 500 largest ownerships in the top tier (approximately the top 0.14% of owners), the next largest 3000 owners in the 1% tier (representing the top 0.95%), the next largest 26,500 ownerships (representing the top 8.1%), and then all remaining smaller ownerships in the final tier. In 2023, the acreage cutoffs that defined these tiers were 13,633 acres, 3620 acres, and 80 acres, respectively. The remaining 337,925 private owners had ownerships smaller than 80 acres. We used these equal-sized groups across years to compare the same number of largest ownerships, rather than using percentage tiers from each year which would have changed the number of ownerships, potentially suggesting a false concentration of land among the largest parcels. We assigned properties as either in- or out-of-state based on the mailing addresses of the landowners. Properties with missing addresses were classified as out-of-state, since a main purpose of the designation was to understand the ease with which owners of habitat on which public wildlife depend are knowable and accessible to public beneficiaries. The number of private owners with missing mailing state ranged from 1264 in 2004 to a high of 2573 in 2018. The total acreage of these parcels was negligible, ranging from 43,016 acres in 2004 to 59,009 in 2008, or between 0.08% and 0.1% of all MT private land.
Results
The 2023, full cadastral database showed 93.9 million acres in Montana (Table 1). Almost 60% of this land, and the wildlife habitat it provides, was privately controlled and divided among just over 370,000 parcels (Table 1), which were owned by about 368,000 different owners (Table 1). The total number of private landowners had increased 22% over the previous 20 years, from about 293,000 in 2004, reflecting sustained parcelization of private land/habitat. As such, mean acreage of private properties dropped from 187 to 149 acres between 2004 to 2023, while median acreage dropped from 0.80 to 0.78 acres over the same period. In 2023, about 17% of the private land/habitat in Montana was controlled by owners with out-of-state mailing addresses (Table 1). This proportion had risen over the previous 20 years (from 13% in 2004) at a rate of about +1% every 4–5 years (Table 1).
Table 1 –
Total land area, parcels, owners, property size attributes, and out-of-state ownership summary statistics for Montana, USA (2004–2023)
Year
Acres (MM)
Adj. Factor
Parcels
Owners
Mean Acres
Median Acres
Private Acres (MM)
Out-of-State Acreage (MM)
Percent Change in Out-of-State Acreage since 2004
Percent Change in Total Owners since 2004
2004
89.17
0.98
295,459
293,293
187.4
0.80
56.21
7.3
–
–
2008
92.32
0.96
326,304
323,971
169.6
0.80
56.97
7.4
1.7%
10.5%
2013
92.40
1.00
334,839
332,608
165.2
0.84
54.69
8.2
12.0%
13.4%
2018
93.77
1.01
345,969
343,682
159.9
0.83
54.50
8.4
14.2%
17.2%
2023
93.87
1.00
370,115
367,925
149.4
0.78
54.95
9.3
26.7%
25.4%
MM Millions of Acres
In Montana, private land and its habitat crucial to the wildlife public trust are predominantly managed by a limited group of owners (Fig. 2). About 3500 owners of the largest properties (the top 1% of owners by size, with properties at least 3600 acres in size) own nearly two-thirds (63%) of the private land in the state, or over one-third of the total land in Montana (37%; Fig. 1, Table 2). Within this top size tier, about 500 owners of the very largest properties (i.e., with properties at least 13,600 acres or larger) comprise the top 0.1% of owners by size and control 27% of the private land in the state or 16% of the total land in Montana (Fig. 2; Table 2). At the other end of the ownership size spectrum, approximately 3% of private land in Montana (2% of total land) is divvied among 337,925 owners, each with properties smaller than 80 acres. The proportion of private land controlled by the top 1% of owners by size has increased slightly (+1% of Montana private land) over the past 20 years (Table 2).
Fig. 2
Land/habitat ownership in Montana, USA graphically depicted as proportions of the state by ownership type and property size tier (top = 2004, bottom = 2023)
Area (in millions of acre) of land owned by ownership type and ownership tier by owners (2004, 2023) including percent of total land and of private land in Montana, USA
Ownership Type
Ownership Tier by Owners
Total Acres 2004 (MM)
Percent of Total Land 2004
Percent of Private Land 2004
Total Acres 2023 (MM)
Percent of Total Land 2023
Percent of Private Land 2023
Change in Proportion of Total Land 2004–2023
Change in Proportion of Private Land 2004–2023
Legal Entity
Top 0.1%
11.03
11.8%
20.1%
12.66
13.5%
23.0%
1.7%
3.0%
Top 1%
8.17
8.7%
14.9%
11.02
11.7%
20.0%
3.0%
5.2%
Top 10%
4.96
5.3%
9.0%
7.02
7.5%
12.8%
2.2%
3.7%
Bottom 90%
.18
0.2%
0.3%
.33
0.4%
0.6%
0.2%
0.3%
Subtotal
24.34
26.0%
44%
31.03
33.1%
56%
7%
12%
Person(s)
Top 0.1%
4.37
4.7%
8.0%
2.34
2.5%
4.3%
–2.2%
–3.7%
Top 1%
9.85
10.5%
17.9%
8.52
9.1%
15.5%
–1.4%
–2.4%
Top 10%
15.03
16.0%
27.4%
11.63
12.4%
21.2%
–3.6%
–6.2%
Bottom 90%
1.36
1.4%
2.5%
1.42
1.5%
2.6%
0.1%
0.1%
Subtotal
30.61
32.6%
56%
23.92
25.5%
44%
–7%
–12%
Combined
Top 0.1%
15.4
16.5%
28.1%
15
16.0%
27.3%
–0.5%
–0.7%
Top 1%
18.02
19.2%
32.8%
19.54
20.8%
35.5%
1.6%
2.8%
Top 10%
19.99
21.3%
36.4%
18.65
19.9%
34.0%
–1.4%
–2.5%
Bottom 90%
1.54
1.6%
2.8%
1.75
1.9%
3.2%
0.3%
0.4%
Total
54.95
58.6%
100.0%
54.95
58.6%
100.0%
–
–
Labels for “ownership tier by owners” are rounded for interpretation across years; the top 0.1% (combined) includes 500 owners, the top 1% includes 3000 owners, and the top 10% includes 26,500 owners. “Person(s)” include individual and joint-family owners; “Legal Entity” includes LLCs, corporations, partnerships, and other organizations
The private land in Montana is split between “legal entities” and “person(s)”, where the latter category comprises the categories of “Individual” and “Joint/Family” as described above. A majority of private land, and its habitat on which public wildlife rely, is owned by “legal entities” (56% in 2023). These owners own 33% of all land in Montana (Table 2; Fig. 3). Identifiable “person(s)” control 44% of the private land/habitat in Montana or about 26% of total land in the state (in 2023; Table 2; Fig. 3). In 2004, these proportions were the exact reverse what they were in 2023: 20 years ago, 56% of private land/habitat in the state was owned by person(s) and 44% controlled by legal entities (Table 2; Fig. 3). This shift is largely explained by a decrease in private land owned “jointly” by multiple owners and a corresponding increase in private land owned by LLCs (Figs. 2, 4; Supplemental Information Table S1).
Fig. 3
Private land/habitat ownership in Montana, USA by ownership type (2004–2023). Please see Supplemental Information for numbers of acres and owners in each ownership type and percent change thereof between 2004 and 2023
The shift in ownership type from person(s) to legal entities has occurred alongside increased private land parcelization in Montana. Legal entities like estates/trusts, LLCs, and other corporations tend to own larger properties and thus control substantial acres of private land, despite there being relatively few owners of this type (Fig. 4). In contrast, people who own land either individually or jointly are numerous, but tend to own smaller properties (Fig. 4). Between 2004 and 2023, property has shifted hands between ownership types such that: (i) although the private land/habitat collectively controlled by individual owners has not changed, the number of individual owners among whom those lands are divided has increased over 50% from just over 100,000 individual owners in 2004 to over 160,000 in 2023, reflecting high levels of parcelization within this ownership type; (ii) the number of joint/family owners has decreased by about 15,000 owners and the acres of private land/habitat controlled by this type of owner decreased by about 6 million acres, indicating a conversion of large ownership from this ownership type to some legal entity, most likely an LLC and less likely an estate/trust; (iii) the group “other corporation” controls about 2 million fewer acres of private land in 2023 than they did in 2004, while only slightly decreasing in number of owners, indicating a pattern of land divestment among owners of this type3; (iv) the number of estates/trusts was quite low in 2004 (about 10,000) as was the number of acres they controlled (about 2 million acres), but the population has more than doubled in the past 20 years, as has the number of acres they now control; and (v) LLCs, which were almost non-existent in 2004 (i.e., few in number, controlling very few private acres), have increased in number to about 20,000 in 2023 and dramatically increased the acres of private land/habitat they control—today, LLCs control about 9 million acres or about 16% of private land/habitat in Montana, up from 3% in 2004 (Figs. 3, 4).
Overall, the number of private landowners in Montana has increased 22% over the past 20 years whereas the acres of land they collectively control has remained virtually constant, demonstrating parcelization of private land/habitat (Table 1). Parcelization has occurred at varying intensity depending on property size (Fig. 5). The amount of land controlled on the very largest properties (i.e., 3600 acres and larger) changed only slightly in the last 20 years (Table 2). However, less private land/habitat is found today on properties with acreages between 100 and 3600 acres than in 2004 (Table 2; Fig. 5, where the top three size classes all show negative change in acreage). The private land/habitat from these medium-large properties is now controlled by owners in smaller size classes. For example, each of the smallest-size class ownerships control more acres today than they did in 2004 (Fig. 5 where the bottom five size classes all show positive change in acreage); the greatest growth in private land/habitat control has been in the 1–50 acres size classes, the result of parcelization of properties formerly in large size classes (Fig. 5). In all size classes less than 100 acres, the number of owners has increased substantially over the past 20 years, an outcome we again interpret as reflective of widespread parcelization that is not limited to urban areas (Fig. 5 where the number of acres and owners have increased within size classes 0–100 acres).
Fig. 5
Percent change in number of owners and acres of private land/habitat by property size class from 2004 to 2023. These metrics are used to evaluate parcelization trends across time among privately owned properties
Private lands provide important wildlife habitat in the United States, including in the state of Montana (Jenkins et al. 2015). Our analysis documents and expands understanding of how habitat ownership in Montana is concentrated among few owners of large properties who are more often legal entities rather than identifiable people (Epstein et al. 2022). Results show that this governance arrangement has intensified over the past 20 years. The specific ownership distribution of private land has several implications for the management of public trust wildlife on behalf of public beneficiaries.
For many if not most wildlife species in Montana, the public trust is effectively held in a few private hands who are often unidentifiable by trust beneficiaries. In Montana, a few mega-properties (e.g., greater than 13,600 acres in size) account for 16% of all land in the state, 27% of the private land, and likely an even greater proportion of the quality wildlife habitat that is disproportionately concentrated on private lands (Benson, 2001). If only as a function of geometry, many populations of wildlife species surely rely on land controlled by single private owners, especially those smaller-bodied and less transient species. The choices of these few private landowners can have profound implications for the wildlife public trust, yet the identities of these owners are increasingly unavailable to beneficiaries, hidden behind legal and corporate structures, limiting informal mechanisms of accountability. The concentration of wildlife habitat on large, private properties also raises questions about physical access by trust beneficiaries, directly and by limiting access to islands of public land surrounded by private (Frazier, 2023). Although access questions were beyond the scope of our analysis, participation in public access programs is declining among Montana private landowners (Eggert and Olness 2024).
In some cases, decisions of private landowners may undermine or supersede efforts by wildlife agencies to manage the wildlife public trust. For example, if hunting access is severely constrained on a substantial portion of private habitat in a wildlife management area, managers’ efforts to reduce wildlife population sizes, shift sex ratios, modify season dates to achieve management objectives, or limit disease spread are all less likely to succeed (Gruntorad and Chizinski 2020; Metcalf et al. 2017; Sergeyev et al. 2022). In other instances, landowners may choose to divide ownership or develop their properties, leading to fragmentation and parcelization of public trust wildlife habitat over which the public has limited oversight, nor do their fiduciaries in public wildlife agencies (Alig et al. 2010; Freyfogle, 2002). These few landowners will also determine whether or not efforts to enhance the wildlife public trust are implemented on large portions of the habitat in most regions of Montana, constituting effective veto authority over efforts like fence removal or fladry marking, wildlife overpass construction (i.e., when private owners control lands where transportation and wildlife corridors intersect), and the securing of wildlife attractants (Carlisle et al. 2022; Gigliotti et al. 2022; Nesbitt et al. 2021). Although private ownership does not pose a barrier to legal accountability, law enforcement efforts can sometimes be stymied by inaccessibly large properties (Freyfogle et al. 2019). In all but a few instances, these private decisions are not subject to public input and increasingly disconnected from informal social pressures that might hold landowners accountable for the implications of their decisions on public trust wildlife.
On the other hand, private ownership of public trust wildlife habitat likely provides benefits to wildlife, even if the benefits flow most directly to private landowners and create tension between public trust objectives. For example, some landowners with large properties operate with a land stewardship ethic, generating outsized and positive benefits for wildlife. With most habitat concentrated on few large properties, development and fragmentation become less likely than they would be under already parcelized landscapes (Mundell et al. 2010)—very large properties tend to stay intact and parcelization is more likely on medium-sized parcels. With public access more constrained under this private control than it would be under public, disturbance to wildlife is likely less than it would be if access was increased for consumptive and nonconsumptive recreation (Dertien et al. 2021). Wildlife often use private land as refugia (Sergeyev et al. 2022) and habitat improvement by private landowners can have benefits to public trust wildlife (Yeiser et al. 2018). For example, Bison (Bison bison) restoration on private lands in central Montana, among many others (Hage and Marcotty, 2025).
However, no matter how much wildlife benefit from this private ownership arrangement, the benefits of those wildlife often flow to private landowners and parties of their choosing, primarily because landowners control access to their land and the wildlife residing there. For example, benefits from viewing and interacting with wildlife (Keniger et al. 2013) flow directly to landowners and those to whom they provide access; other members of the public are excluded from these benefits, especially for wildlife that rarely or never leave single, large properties. Hunting can provide sustenance, self-actualization, and other health benefits (Guynn, 2015); these benefits from wildlife on private lands are similarly limited to landowners and individuals whom they select (or charge for the benefit), rather than public beneficiaries. For landowners who lease their properties for hunting or other uses of wildlife, the financial benefits of public trust wildlife flow most directly to those owners rather than the public. These private benefits from the public trust create a paradoxical situation where private landowners’ interests can sometimes serve to protect and enhance public trust wildlife, but benefits from the public trust flow most directly (if not solely) to the relatively few owners of large properties. Recent research has demonstrated that some landowners avoid participating in wildlife monitoring programs for fear of attracting attention and oversight from public trust beneficiaries (Kauffman et al. 2024).
Private landownership of public wildlife trust habitat is a collective action problem that challenges the achievement of positive outcomes for public trust wildlife, but the concentration of habitat ownership may promote cooperation among owners. Collective action problems require contributions from many actors to either prevent unsustainable consumption of resources or provide a public good (Ostrom 2010). Inspiring, let alone coordinating contributions from all these actors is challenging and group size is an oft-cited factor inversely related to success (Pecorino 2015). Although the landowner population in Montana (and the US) is indeed very large, the majority of wildlife habitat is controlled by relatively few owners. While still a collective action problem requiring cooperation among these entities, success is more likely in smaller groups. Tools like Section 10 of the Endangered Species Act allow for the development of Habitat Conservation Plans encouraging contributions from these private actors toward the public good. Other US Federal Agencies offer various private lands conservation/management programs as well. Cooperative efforts among large landowners might be more likely to achieve wildlife objectives, at least for objectives shared by these owners.
Although there are opportunities to bolster the wildlife public trust when private landowner and public interests align, accountability of private landowners to public beneficiaries is low and seems to be decreasing in Montana. Our analysis shows a significant portion of habitat in Montana is increasingly owned by legal entities rather than identifiable people (Fig. 3). Unlike owners whose names are available in cadastral datasets, legal entities are often unknowable and unreachable by the public. For example, LLCs provide a mailing address for contact, but other owner information is often inaccessible behind legal firewalls. Owners who are unknown to their neighbors and to trust beneficiaries are less accountable to informal social pressures and institutions. This depersonalization and anonymization of landownership may not simply constitute nostalgia for a bygone era but represent diminishment of the already limited accountability private landowners have for the decisions they make that affect the wildlife public trust. Even when landowners are accessible, the mechanisms through which beneficiaries can provide feedback may be informal and subtle; but when landowners are not accessible, opportunities for such feedback are greatly diminished if not eliminated altogether. That more land is owned by corporate entities like LLCs as opposed to trusts suggests that these owners’ goals are more focused on protecting financial assets, rather than securing conservation-related or even legacy values (Roth et al. 2024). Even when landowners donate or sell conservation easements to non-public entities, the terms of those agreements are not subject to input or oversight by wildlife public trust beneficiaries (Brown et al. 2023; Chapman et al. 2023); in contrast, easements held by state or federal entities are subject to public review and monitoring. Out-of-state ownership is also on a rise, albeit at a slower rate, further reducing accountability of private landowners to wildlife public trust beneficiaries for many of these same reasons.
Our trend analysis from 2004 to 2023 suggests that habitat ownership in Montana is becoming increasingly uneven and owners are becoming less identifiable by wildlife public trust beneficiaries. The landowners with properties of at least 3600 acres, who control a majority of public trust wildlife habitat, have increased their holdings slightly over the past 20 years (60% of private land in 2004 to 63% in 2023; Fig. 2). At the same time, smaller properties in the state have been increasingly parcelized, where mean and median ownership size is decreasing and the number of owners increasing over the same period. Thus, while the majority of habitat in the state remains and is slightly more concentrated among a few owners of vast properties, the minority of habitat controlled by owners of small parcels is being divided among an increasing number of owners, diluting the influence and control of these “small” owners. Simultaneously, ownership of public trust wildlife habitat is shifting from individuals and joint owners to legal and out-of-state entities, decreasing the availability of these owners to wildlife public trust beneficiaries (Gosnell and Abrams 2011; Knight and Landres 2013).
A few limitations and opportunities for future research should be considered when interpreting these results. The process for identifying unique owners of multiple parcels is imperfect, especially if the same owner uses different tax mailing addresses for separate properties or if different owners share an identical tax address. We suspect this is a minor problem (i.e., the dissolve only affected ~2000 properties total), but one that could be exacerbated by potential misspellings in mailing addresses in the cadastral attribute files that our process would have not recognized. Future work may seek to resolve this issue or explore methods to prevent the dissolve from collapsing owners of unique types into just one if identical tax addresses are used by multiple owners (e.g., an LLC and individual sharing a mailing address). Corporate ownership complicated our ability to understand out-of-state control; unlike individuals, business entities can be incorporated in any state regardless of the owner or owners’ residency. Thus, corporations with in-state mailing addresses may in fact be controlled by out-of-state owners; and vice versa. Future work should explore ways to disentangle this problem or estimate the unaccounted-for proportions of out-of-state ownership it may mask. Additionally, there may be ways to work with Secretary of State’s offices to identify single-member owners of LLCs to increase availability and accountability of these owners; legal experts indicated to us that this is likely a futile endeavor for multi-member LLCs due to legal firewalls that protect members’ names from disclosure outside of lawsuits.
The methods described here could empower future research seeking to understand private land ownership patterns effects on parcelization and fragmentation of wildlife habitat, land values and the implications on owners’ wildlife management decisions, habitat specific to focal species or pathways of connectivity required for other species (e.g., grizzly bears, migratory ungulates), the relationship between private landowners and recreational use (e.g., using cell-phone location data), optimal locations for wildlife reintroductions (Martinez et al. 2024), among many others (Carter et al. 2020). Cadastral data enabling these analyses are increasingly available through public agencies as well as private vendors.
Conclusion
Understanding the private ownership of public trust wildlife habitat challenges us to more deeply examine what public trust wildlife management means in a system where private interests so thoroughly dominate landownership. Our analysis shows that the majority of public trust wildlife habitat in Montana is owned by relatively few owners and concentrated on very large properties. Additionally, a large and increasing fraction of public trust wildlife habitat in Montana is controlled by legal entities, constraining accessibility and accountability of these owners to wildlife public trust beneficiaries. These descriptive statistics and trends raise questions about how public trust wildlife are affected by private landownership and whether additional measures are needed to protect the interests of beneficiaries. Is this level of control acceptable, or does the public trust doctrine demand more access and accountability? Do beneficiaries find acceptable the current flow of benefits from public trust wildlife to landowners versus beneficiaries? Would challenging the current governance arrangement undermine the benefits to wildlife offered by large, mostly undeveloped parcels? Should beneficiaries be allowed to demand other limitations, restriction, or requirements on landowners’ decisions that impact public trust wildlife? Contrary to popular interpretation, private landownership exists to protect public interests (Freyfogle, 2007). Our analysis of the large, western U.S. state of Montana helps us understand how this governance system has evolved there over recent years, and where it’s likely headed. It is our hope this information will inspire and empower similar analyses in other jurisdictions and allow public beneficiaries and policy makers a more rigorous dialog over whether the system is achieving desired outcomes and, if not, how it might need to change.
We sincerely thank wildlife policy expert M.N. for reviewing earlier drafts of this manuscript, ensuring our accurate presentation of the public trust doctrine.
Compliance with Ethical Standards
Conflict of Interest
The authors declare no competing interests.
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We allowed multipart features in our dissolve process, generating a dataset with single rows for each owner’s unique tax mailing address regardless of the spatial configuration of their parcels. Although only a few properties were dissolved (~2000) a separate spatial analysis might distinguish between contiguous parcels owned by the same owner vs. non-contiguous. Contiguous parcels may be managed more consistently than non-contiguous, with implications for wildlife, but even contiguous parcels can have highly variable management across their acres. These variables were outside the scope of our inquiry.
Note: our manual review of owners in the “other corporation” category revealed the vast majority of land in this category is owned by ranch-related businesses. NGOs only accounted for approximately 3.6% of the land in this category; churches for approximately 0.6%; other possible sub-categories owned even smaller proportions. However, the naming conventions among ranch-related businesses made a full analysis too complicated for our analysis. That is, many ranches do not have words in their owner names to indicate ranching, whereas others with the word ranch in their name do not actually own ranches or engage in ranching. More work is needed to fully describe the variety, however small, within the “other corporation” category.
Alig RJ, Plantinga AJ, Haim D, Todd M (Eds.) (2010) Area Changes in U.S. Forests and Other Major Land Uses, 1982 to 2002, With Projections to 2062.
Ashwood L, Canfield J, Fairbairn M, De Master K (2022) What owns the land: The corporate organization of farmland investment. J Peasant Stud 49(2):233–262.CrossRef
Benson DE (2001) Wildlife and Recreation Management on Private Lands in the United States. Wildl Soc Bull (1973-2006) 29(1):359–371.
Brown SA, Rotman RM, Powell MA, Wilhelm Stanis SA (2023) Conservation easements: A tool for preserving wildlife habitat on private lands. Wildl Soc Bull 47(2):e1415.CrossRef
Bruskotter JT, Enzler SA, Treves A (2011) Rescuing wolves from politics: Wildlife as a public trust resource. Science 333(6051):1828–1829.CrossRef
Carlisle KM, Ellis HE, Jaebker LM, Bright AD (2022) Producers’ perceptions of large carnivores and nonlethal methods to protect livestock from depredation: Findings from a multistate federal initiative. Hum Dimens Wildl 0(0):1–4.
Carter N, Williamson MA, Gilbert S, Lischka SA, Prugh LR, Lawler JJ, Metcalf AL, Jacob AL, Beltran BJ, Castro AJ (2020) Integrated spatial analysis for human-wildlife coexistence in the American West. Environ Res Lett 15(2):021001.CrossRef
Chapman M, Boettiger C, Brashares JS (2023) Leveraging private lands to meet 2030 biodiversity targets in the United States. Conserv Sci Pr 5(4):e12897.CrossRef
Cullen Ross (2012) Biodiversity protection prioritization: a 25-year review. Wildl Res 40(2):108–116.CrossRef
Dertien JS, Larson CL, Reed SE (2021) Recreation effects on wildlife: A review of potential quantitative thresholds. Nat Conserv 44:51–68.CrossRef
Epstein K, Haggerty JH, Gosnell H (2022) With, not for, money: Ranch management trajectories of the super-rich in greater yellowstone. Ann Am Assoc Geographers 112(2):432–448.
Frazier K (2023) Corner crossing: Unlocking public lands or invading the airspace of landowners?. Public Land Resour Law Rev 46:91–112.
Freyfogle ET (2002) The Tragedy of Fragmentation Dialogues. Environmental Law Reporter News &. Analysis 32(11):11321–11332.
Freyfogle ET (2007) On Private Property: Finding Common Ground on the Ownership of Land. Beacon Press.
Freyfogle ET, Goble DD, Wildermuth TA (2019) Wildlife Law, Second Edition: A Primer. Island Press.
Gigliotti LC, Xu W, Zuckerman GR, Atwood MP, Cole EK, Courtemanch A, Dewey S, Middleton AD (2022) Wildlife migrations highlight importance of both private lands and protected areas in the Greater Yellowstone Ecosystem. Biol Conserv 275:109752.CrossRef
Gilardi F, Alizadeh M, Kubli M (2023) ChatGPT outperforms crowd workers for text-annotation tasks. Proc Natl Acad Sci 120(30):e2305016120.CrossRef
Gosnell H, Abrams J (2011) Amenity migration: Diverse conceptualizations of drivers, socioeconomic dimensions, and emerging challenges. GeoJournal 76(4):303–322.CrossRef
Gruntorad MP, Chizinski CJ (2020) Constraints to hunting and harvesting elk in a landscape dominated by private land. Wildl Biol 2020(1):wlb.00596.CrossRef
Guynn ST (2015) Exploring and measuring the benefits of hunting [Ph.D., Clemson University].
Hage Dave, Josephine Marcotty Sea (2025) of Grass: The Conquest. Ruin, and Redemption of Nature on the American Prarie. Random House, ISBN: 9780593447406.
Jenkins CN, Van Houtan KS, Pimm SL, Sexton JO (2015) US protected lands mismatch biodiversity priorities. Proc Natl Acad Sci 112(16):5081–5086.CrossRef
Kauffman M, Lowrey B, Beaupre C, Bergen S, Bergh S, Blecha K, Bundick S, Burkett H, … Wood E (2024) Ungulate migrations of the Western United States, 4. In Scientific Investigations Report (Nos. 2024–5006). U.S. Geological Survey.
Keniger LE, Gaston KJ, Irvine KN, Fuller RA (2013) What are the Benefits of Interacting with Nature?. Int J Environ Res Public Health 10(3):Article 3.CrossRef
Knight RL, Landres P (2013) Stewardship Across Boundaries. Island Press.
Kuzman T, Mozetič I, Ljubešić N (2023) ChatGPT: Beginning of an End of Manual Linguistic Data Annotation? Use Case of Automatic Genre Identification (No. arXiv:2303.03953).
Martinez LA, Lombardi JV, Powers G, Anderson AD, Campbell T, Lopez RR (2024) Assessing ecological and socio-political factors in site selection for ocelot reintroductions in Texas. Conserv Sci Pr 6:e13113.CrossRef
Metcalf AL, Metcalf EC, Khumalo K, Gude J, Kujala Q, Lewis MS (2017) Public Wildlife Management on Private Lands: Reciprocity, Population Status, and Stakeholders’ Normative Beliefs. Hum Dimens Wildl 22(6):564–582.CrossRef
Morgan JJ, Rhoden CM, White B, Riley SP (2019) A state assessment of private lands wildlife conservation in the United States. Wildl Soc Bull 43(3):328–337.CrossRef
Mundell J, Taff SJ, Kilgore MA, Snyder SA (2010) Using real estate records to assess forest land parcelization and development: A Minnesota case study. Landsc Urban Plan 94(2):71–76.CrossRef
Nie M (2024) The public trust doctrine and wildlife management in. Mont: A Prim Pub Land Resour L Rev 47:35.
Nie M, Landres N, Bryan M (2020) The Public Trust in Wildlife: Closing the Implementation Gap in 13 Western States. Environ Law Rep 50:10909.
Oakleaf JK, Murray DL, Oakleaf JR, Bangs EE, Mack CM, Smith DW, Fontaine JA, Jimenez MD, Meier TJ, Niemeyer CC (2006) Habitat Selection by Recolonizing Wolves in the Northern Rocky Mountains of the United States. J Wildl Manag 70(2):554–563.CrossRef
Organ JF, Decker DJ, Stevens SS, Lama TM, Doyle-Capitman C (2014) Public Trust Principles and Trust Administration Functions in the North American Model of Wildlife Conservation: Contributions of Human Dimensions Research. Human Dimensions of Wildlife, 19(5), 407–416.
Ostrom E (2010) Analyzing collective action. Agric Econ 41(s1):155–166.CrossRef
Pecorino P (2015) Olson’s Logic of Collective Action at fifty. Public Choice 162(3):243–262.CrossRef
Rissman AR, Owley J, L’Roe AW, Morris AW, Wardropper CB (2017) Public access to spatial data on private-land conservation. Ecol Soc 22(2):24. https://doi.org/10.5751/ES-09330-220224.
Robinson NP, Allred BW, Naugle DE, Jones MO (2019) Patterns of rangeland productivity and land ownership: Implications for conservation and management. Ecol Appl 29(3):e01862.CrossRef
Sagarin RD, Turnipseed M (2012) The public trust doctrine: where ecology meets natural resources management. Annu Rev Environ Resour 37(1):473–496.CrossRef
Sergeyev M, McMillan BR, Hall LK, Hersey KR, Jones CD, Larsen RT (2022) Reducing the refuge effect: Using private-land hunting to mitigate issues with hunter access. J Wildl Manag 86(1):e22148.CrossRef
Slagle KM, Karns G, Bruskotter JT (2023) Private lands, public benefits: The potential for wildlife habitat and public recreation on private lands in Ohio. Hum Dimens Wildl 29:535–539
Smith LA, Lopez RR, Lund AA, Anderson RE (2025) Status Update and Trends of Texas Working Lands. Texas A&M Natural Resources Institute: College Station, TX, USA.
The Wildlife Society (2010) The Public Trust Doctrine: Implications for Wildlife Management and Conservation in the United States and Canada. Technical Reivew 01-10. Bethesda, MD: The Wildlife Society.
Ver Planck NR, Metcalf AL, Finley AO, Finley JC (2016) Evaluation of the USDA forest service national woodland owner survey estimators for private forest area and landowners: A case study of Montana. For Sci 62(5):525–534.
Wang Y, Yao Q, Kwok JT, Ni LM (2020) Generalizing from a few examples: A survey on few-shot learning. ACM Comput Surv 53(3):63:1–63:34.
Watson R (2012) Public wildlife on private land: Unifying the split estate to enhance trust resources conservative visions of our environmental. Future Duke Environ Law Policy Forum 23(2):291–322.
Yeiser JM, Morgan JJ, Baxley DL, Chandler RB, Martin JA (2018) Private land conservation has landscape-scale benefits for wildlife in agroecosystems. J Appl Ecol 55(4):1930–1939.CrossRef
