Global literature review and survey of implementation constraints on natural climate solutions

Domain: biology
Published: 2026-03-14
Editorial outcome: minor_revision

Abstract
Natural Climate Solutions – protection, restoration, and improved management of lands and waters that
reduce greenhouse gasses – have large climate change mitigation potential. However, lack of
comprehensive information on implementation challenges hinders the adoption of Natural Climate
Solutions and the delivery of near-term mitigation. Using a global survey of Natural Climate Solutions
projects and a systematic review of recent studies, we map 46 constraints in eight categories, yielding
15,572 geo-referenced pathway-constraint observations from 501 studies and projects in 137 countries
covering 20 of 22 United Nations subregions. Social-behavioral, Knowledge, and Government-
Organizational are the most-reported constraint categories, and lack of policy coordination or
implementation capacity the most-observed constraint and most frequently top-ranking constraint for
pathways and subregions. Despite broad congruence, top constraint and category rankings vary among
subregions and pathways, respectively. We find that projects generally encounter diverse sets of
challenges. Without enabling efforts, near-term mitigation from Natural Climate Solutions may remain
well below its biophysical potential.

Introduction
Limiting global warming to less than 2°C above 1850-1900 temperatures will require rapid and large-
scale implementation of greenhouse gas (GHG) emission reductions and atmospheric carbon dioxide
removal (CDR)1–4. Natural climate solutions (NCS) – deliberate human actions that protect, restore, and
improve management of forests, wetlands, grasslands, oceans, and agricultural lands and that reduce
GHG emissions or increase carbon dioxide sequestration, with no net negative impact on food and fiber
supply or biodiversity and implemented in socially and culturally responsible ways5–7 – are the least-cost
mitigation option that could achieve large-scale, short-term CDR1,8.

NCS are broadly equivalent to the Intergovernmental Panel on Climate Change (IPCC) supply-
side measures related to agriculture, forestry, and other land uses (AFOLU)1. AFOLU mitigation measures
have an estimated 2020-2050 mean total technical mitigation potential of 28.4 GtCO e yr-1 (full range:
2
8.8-65.1;1). In part due to their technical readiness1,9 and cost-effectiveness, several NCS feature
prominently in national climate change mitigation and adaptation strategies10–13 and international
mitigation scenarios 14–16, and their large-scale implementation is promoted by high-profile international
initiatives17,18, national governments (including via Nationally Determined Contributions [NDCs] under
the Paris Agreement) and private actors.

Yet NCS implementation remains limited relative to its technical potential1. Given the need for
rapid and large-scale action during a climate-critical window1,6,19–21 and the time required to achieve
maximum NCS mitigation rates (e.g.,22), such limited implementation is problematic. NCS
implementation faces many challenges that vary in scale from the local (site or project) to the national
level23–26. High-profile, global or pan-tropical analyses of NCS mitigation potential (e.g.,27) often fail to
consider the effect of local constraints on that potential28,29. Country-level analyses that consider even a
select number of constraints find that the realistically feasible NCS implementation potential can be
substantially below the biophysical or technological potential30,31, supporting the IPCC’s assessment that
“[t]he economic and political feasibility of implementing AFOLU mitigation measures is hampered by
persistent barriers”1 (p.751).

Several recent global or pan-tropical analyses of NCS mitigation potential do consider
implementation feasibility23, constraints26,32,33 or enabling conditions24,33,34 of NCS. However, these
studies focus on a small set of high-level indicators of national-level feasibility or enabling conditions32,35;
report assessments of enabling conditions at the national level24; limit their analysis to a small, highly
aggregated set of broad types of constraints33; or do not assess constraints spatially26,33. Thus, there is an
urgent need for a geographically-comprehensive and more spatially-resolved mapping of constraints, at
the finer spatial scales at which many constraints operate, and including a broader, more finely
differentiated set of constraints that affect the feasibility of NCS implementation in different socio-
ecological contexts7,13,33. Without this information, it is impossible to know how much of the mitigation
potential estimated to be available at up to USD 100 tCO e-1 may be achievable in the near to medium
2
term.

Brumberg et al.’s36 systematic review of the recent literature on NCS constraints was an
important contribution to filling this critical knowledge gap. In this paper, we build on and advance that
effort by conducting a global survey of NCS projects that uses an expanded set of implementation
constraints, recoding Brumberg et al.’s36 literature dataset to this expanded constraints set,
georeferencing all survey and literature constraint observations to their corresponding administrative
levels, and integrating the survey and literature datasets into a spatial database that reflects the current
evidence base on NCS implementation constraints.

Our analysis advances and complements existing assessments in several ways. First, by focusing
on reported constraints on NCS rather than enabling conditions or feasibility indicators of NCS24,35, we
identify which critical enabling conditions are currently absent, and where. Second, rather than report
constraints, enabling factors or feasibility at the national level24,32,35,36 or non-spatially (e.g.,26,33), we
collect and report constraints at the study or project level. Third, we distinguish constraints and discrete
NCS mitigation options (hereafter, pathways6) in greater detail than previous studies26,33,36. Finally, our
survey expands the existing evidence base on NCS constraints by including NCS projects not currently
captured in the peer-reviewed literature. Our findings can help NCS planners anticipate challenges and
inform efforts to identify solutions that can overcome constraints on NCS, enabling broader NCS uptake
and effectiveness. A better, spatially-explicit understanding of the factors that constrain NCS adoption
also can inform more realistic assessments of the feasible (vs the technical) mitigation potential37,38.

Results
Sample frame
Our combined literature and survey dataset comprises 501 unique sources that provide spatially-explicit
information on constraints to specific NCS pathways. This evidence base consists of 347 peer-reviewed
studies from 133 countries (Fig. S2) and 154 surveyed projects in 46 countries (Fig. S3), with a combined
coverage of 137 countries in 20 of 22 United Nations (UN) subregions (Fig. 1). The five countries with
the highest number of papers or survey projects are Brazil (52), USA (49), Indonesia (32), China (28) and
Kenya (26).

The Americas are the single most-studied region in our combined dataset with a total of 26 countries in
the hemisphere covered a combined 243 times in papers and survey responses (Table S3). Africa and
Asia follow with 179 counts each, covering 44 and 37 countries, respectively. Europe and Australia-New
Zealand-Melanesia have 81 and 21 counts, respectively, covering 26 and four countries, respectively.
Our sample covers 81% of all countries in Africa, 79% in the Americas, 77% in Asia, 59% in Europe, and
57% in Australia-New Zealand-Melanesia.

Africa accounts for a relatively high share of survey projects, with 63 projects (41% of all survey projects)
in 22 countries (48% of all survey countries), followed by the Americas (59 projects [38%] in 15 countries
[33%]), and Asia (25 projects [16%] in five countries [11%]) (Fig. S3). In the literature sample, the
Americas are the most-studied region (184 country observations covering 25 countries), followed by
Asia (154 observations, 37 countries), Africa (116 observations, 41 countries) and Europe (79
observations, 26 countries). Fig. S4 shows the spatial coverage of our combined sample by
administrative level. Forty percent of our literature sample are country-level (ADM-0) studies, with the
remainder approximately evenly split between state-level (ADM-1) and county-level (ADM-2). By
contrast, 60% of the survey projects most closely represent ADM-1 level interventions in terms of their
implementation extent, followed by ADM-2 (27%) and ADM-0 level (13%).

In 29 cases, a group of individuals completed a survey for a project, resulting in a total of 215 survey
participants from 40 organizations representing environment (38%) and development (18%) NGOs,
research institutions (18%), governmental entities including utilities (10%), multi-sectoral entities (10%)
and for-profit enterprises (8%).

NCS pathway representation
The number of papers in our sample (347) exceeds that of surveyed projects (154), with papers
contributing the majority (60%) of the overall pathway observation count (i.e., the number of times a
pathway is reported in papers and survey responses) as well as the counts for most pathways (Fig. S5).
Yet, on average, surveyed projects implement more pathways (2.5) than are reported on in the
literature sample (1.5). In both the literature and survey samples, reforestation is the pathway with the
largest share of observations (27% and 25%, respectively), followed by agroforestry (25% and 14%,
respectively) and avoided forest conversion (20% and 14%, respectively). Reforestation is the most-
represented pathway in our data, with a combined 220 papers and survey projects (44% of all papers or
survey projects), followed by agroforestry (172; 35%) and avoided forest conversion (147; 30%) (Fig. S5).
Regenerative agriculture, which was not included in Brumberg et al.36, accounts for only five percent of
observations. Fewer than 20 papers or projects report on peatland restoration, avoided peatland
conversion, avoided grassland conversion, and reduced woodfuel harvests in forests, respectively. Given
the dominance of reforestation, agroforestry and avoided forest conversion, it is not surprising that
restoration is the most-represented NCS strategy (277 papers and survey projects; 56%), followed by
improved management (249; 50%) and protection (176; 36%).

Eastern Africa and South America contribute by far the largest numbers of papers and survey
responses at the pathway level (155 and 150, respectively), followed by South-Eastern Asia (86),
Northern America (83), Central America (73) and Western Africa (72) (Fig. S6). Central Asia (2), Southern
Africa (7), and Melanesia, Eastern Europe and Western Asia (8 each) have the lowest numbers of papers
and survey responses. In most of the 20 global subregions, reforestation or avoided forest conversion
are the single most-represented pathways in the combined literature and survey sample. The exceptions
are Western and Eastern Africa and Southern Asia, where agroforestry is the most-represented
pathway.

NCS implementation constraints
Our combined dataset contains 15,572 constraint observations, each of which identifies a specific
implementation constraint for a specific NCS pathway in a specific location. Approximately three
quarters (73.5%; n=11,448) of observations are from the survey, despite the survey accounting for only
one-third of the combined number of survey responses and papers. This inverse relationship is due to
surveyed projects reporting higher numbers of implemented pathways and constraints on average than
the average paper in the literature review. This evidence base is distributed highly unevenly across
pathways (Fig. S7) and UN subregions (Fig. S8), and pathway-subregion combinations (Fig. S9).

Most-reported constraint categories overall
There are no constraint categories whose observation counts dominate (Fig. 2). Even the sixth-most
reported category (Markets) still has two-thirds of the observation count of the most-reported (Social-
behavioral). Social-behavioral constraints (e.g., skepticism or disinterest in NCS or lack of trust in NCS
promotors, lack of social learning or exchange networks, preferences for non-NCS, lack of coordination
among interested parties, concerns about equity) was the most frequently reported constraint category
in the combined sample, accounting for nearly one-fifth (19%) of all constraint observations, followed by
Knowledge (17%), Government and Organizations (16%), Rules and Laws (14%), Finance (13%), Markets
(12%) and Material Inputs (8%), with Negative Side Effects by far the least-observed constraint category
(1%) (Fig. 2). In the literature sample, Government and Organizations was the most-observed constraint
category, followed closely by Social-behavioral, and then by Knowledge (Fig. S11). In the survey sample,
Knowledge is the most-reported category, followed closely by both Social-behavioral and Rules and
Laws, respectively. The survey data show a more even distribution of observations among constraint
categories than the literature (Fig. S11).

Most-reported individual constraints and high prevalence of many constraints
Our results show that many constraints identified by individual NCS papers or projects are encountered
frequently in NCS implementation. In fact, except for the most-reported constraint, there is no clear
break in the frequency count distribution of our 46 constraints (Fig. 3). Similarly, the well-mixed
constraint categories (indicated by the different bar colors in Fig. 3) show that constraints in all
categories except Negative Side Effects are encountered often, with the top five most-reported
constraints representing four different constraint categories. Both the generally smooth frequency
count distribution across individual constraints and the high degree of mixing of constraint categories in
Fig. 3 show that the overall frequency ranking of constraint categories (Fig. 2) is driven by a large
number of often-encountered constraints, not a small number of dominant constraints.

The most frequently reported constraint was lack of policy coordination or implementation capacity,
followed by uncertain, or lack of, enforcement of environmental laws (Fig. 3), both of which fall in the
Government and Organizations category. Lack of information about how to design the NCS, skepticism
or disinterest in NCS or lack of trust in NCS promoters, and project access to other funding for NCS
round out the top-five constraints, followed closely by lack of non-credit funding for land managers.

Lack of policy coordination or implementation capacity also was the most-frequently reported
constraint in the individual literature and survey samples. In the literature data, this was followed by
skepticism or disinterest in NCS or lack of trust in NCS promoters; uncertain, or lack of, enforcement of
environmental laws; greater profitability of alternative land uses; and information about how to design
or begin the NCS. In the survey data, the second-most-frequent constraint was land manager access to
other funding for NCS, followed by uncertain, or lack of, enforcement of environmental laws; unclear
laws and policies related to NCS outputs/markets; and financial or other incentives for non-NCS.

NCS projects face multiple, diverse constraints
Implementation generally encountered multiple constraints in multiple categories, with an overall
weighted average of 7.8 constraints in 3.2 categories per paper or project. This is true for both the
literature (average: 2.7 constraints in 2.2 categories per paper) and survey samples (average: 19.3
constraints in 5.6 categories per project), but especially the latter, which is not surprising since the
survey explicitly aimed to identify the full range of constraints, while papers frequently tested for or
analyzed specific constraints or did not have the identification of constraints as their main research
objective. These findings support the observation that NCS implementation commonly encounters
diverse challenges, facing a complex set of constraints that require integrated solutions39.

Relative prevalence of constraint category observations by pathway
Given the uneven distribution of the constraints evidence base across pathways (Fig. S12; Fig. S7), to
facilitate comparisons of the relative prevalence of constraint categories among pathways, Fig. 4 shows
a z-score heatmap of the number of observations in each constraint category normalized at the pathway
level. Social-behavioral and Knowledge are the top-ranking constraint categories for the highest number
of pathways (five each), followed by Government and Organizations (two) and Markets (one). Social-
behavioral also is the second-highest-ranking constraint category for five additional pathways, and the
category with the highest combined top-three rankings among pathways (Fig. S13).

Social-behavioral also is the most-reported constraint category for all three NCS strategies (Protection,
Restoration, Improved Management), with Knowledge and Government and Organizations the second
and third-most reported categories depending on strategy (Fig. S14).

Relative prevalence of constraint category observations by subregion
Social-behavioral is the most frequently number one-ranking constraint category at the subregion level
(8 of 20 subregions), followed by Markets (6 subregions) and Knowledge (5 subregions) (Fig. 5). Social-
behavioral, Knowledge, Markets, and Government and Organizations are the constraint categories with
the highest numbers of top-three rankings in subregions (17, 14, 8, and 8, respectively) (Fig. S15, right
panel). The approach used to aggregate constraint category observations across pathways in each
subregion (summing raw counts vs summing pathway-level z-scores) only marginally affects these
results: Social-behavioral is the most-frequently number one-ranking constraint category under both
approaches, and Social-behavioral, Knowledge, and Market constraints are the most-frequently top-
three-ranking categories, although Knowledge displaces Markets as the second-most frequently top-
ranking category under pathway-level z-score aggregation (Fig. S15). Material Inputs consistently is the
constraint category with the fewest top-three rankings overall at the subregion level (0 or 1), followed
by Negative Side Effects and Rules and Laws (3 times each). Dropping subregions with fewer than 30 or
50 observations does not affect these rankings.

Congruence of most-reported constraint categories among NCS pathways and UN subregions
A key finding is the broad consistency of the most prevalent constraint categories among pathways and
subregions, respectively.

While their specific rankings may vary among pathways and among subregions, Social-
behavioral, Knowledge, Markets, and Government and Organizations constraints are highly prevalent for
nearly all pathways and subregions, while Finance and Rules and Laws are important for large subsets of
pathways and subregions as well. Notably, Finance is a top-three-ranking constraint category in seven —
one-third of all— subregions (based on raw counts; five under pathway-level z-score aggregation [Fig.
S15]), including in all five African subregions. Finance also is the third-most frequently-reported
constraint category for three pathways, all of which are avoided conversion pathways (i.e., protection).
The latter is perhaps not surprising given that actual avoided conversion results in the foregoing of
prospective private benefits derived from the alternative land uses (e.g., 40), which, at least on private or
community-owned lands, but also on multi-use public lands or public lands lacking effective
enforcement of property rights, often requires financial incentives 41–46.

Most-reported individual constraints by pathway
Five (out of 46) constraints are the highest-ranking constraints for all 13 pathways (Fig. S18). If the
reduced woodfuel harvest in forests pathway, which has only five papers or survey responses, is
excluded, only three constraints are top-ranking for all pathways. Lack of policy coordination or
implementation capacity was the most-observed constraint for eight (62%) of the 13 pathways, and
ranking second or third, respectively, for two addition pathways. Information about how to design or
begin the NCS was the most-frequently reported constraint for four pathways (avoided coastal wetland
conversion, coastal wetland restoration, avoided peatland conversion, and peatland restoration, for
which it was tied with lack of policy coordination or implementation capacity), while greater profitability
of alternative land uses was the most frequently reported constraint for one pathway (avoided
grassland conversion). The constraint frequency distributions for all pathways are fairly smooth overall
(Fig. S19). However, eight pathways (62%) show a marked discontinuity, with the top one or two
constraints much more frequently reported than the next constraints. This is true for agroforestry (lack
of policy coordination or implementation capacity), avoided coastal wetland conversion (information
about how to design or begin the NCS), avoided forest conversion (lack of policy coordination or
implementation capacity and uncertain, or lack of, enforcement of environmental laws), climate-smart
forestry (lack of policy coordination or implementation capacity and information about how to manage
the NCS), coastal wetland restoration (information about how to design or begin the NCS), reforestation,
and savanna management (lack of policy coordination or implementation capacity).

Interestingly, lack of planting stock, while often mentioned as a key constraint in reforestation
analyses (e.g.,47,48), does not emerge as a dominant constraint in our data, accounting for only two
percent of all constraint observations in the literature and survey data, respectively. For reforestation,
lack of all material inputs (planting stock or other materials; labor [external or own]; land; or water for
the NCS) combined accounts for only eight percent of all constraint observations, close to the pathway
mean (7%) (Fig. S18), while lack of planting stock or other materials itself is reported only 114 times by
220 papers and projects that reported on this pathway, ranking it twelfth out of 46 reforestation
constraints in terms of frequency count. This does not mean that seedlings and other inputs are not an
important constraint on large-scale reforestation efforts or in specific geographies (e.g.,49), rather that
they are not an apparent dominant constraint across most reforestation projects, or across NCS
pathways generally. When other constraints are overcome, reforestation initiatives are able to organize
the seedling supply50.

Most-reported individual constraints by subregion
Twelve constraints are highest-ranking in at least one of the 20 subregions (Fig. S20), or ten if subregions
with <10 studies and survey responses are excluded. Lack of policy coordination or implementation
capacity is the top constraint in seven subregions (35% ) and the second or third-most-reported
constraint for a further five. Skepticism or disinterest in NCS or lack of trust in NCS promoters and
markets for ecosystem services and biodiversity provided by the NCS are the most-reported constraints
for the next-highest number of subregions (three each). Land manager access to other funding for NCS is
tied with skepticism or disinterest in NCS or lack of trust in NCS promoters and markets for ecosystem
services or biodiversity provided by the NCS for the second-highest number of combined first and
second-place rankings, and has the second-highest number of top-three rankings, after lack of policy
coordination or implementation capacity. Subregions where lack of policy coordination or
implementation capacity is not the most-frequently reported constraint are Central Africa, where
uncertain, or lack of, enforcement of environmental laws is the most-reported constraint, which is also
second-ranking in both South America and Central America; Australia and New Zealand and Eastern
Europe (small n), for which negative side effects of NCS is the top constraint; Southern Europe, Northern
Africa, and Western Asia (small n) (markets for ecosystem services or biodiversity provided by the NCS);
the Caribbean (information about how to design or begin the NCS, land manager access to other funding
for NCS); Northern Europe (greater profitability of alternative land uses); and Western Europe and
Eastern Asia (skepticism or disinterest in NCS or lack of trust in NCS promoters). As was true for some
pathways, several subregions show exponential or quasi-exponential frequency distributions with one or
a few constraints with much higher counts than the next most frequent constraints (Fig. S21). This is
true for Northern, Central, and South America and Southern Asia (lack of policy coordination or
implementation capacity; and in South America, also uncertain, or lack of, enforcement of
environmental laws); Eastern Asia (skepticism or disinterest in NCS or lack of trust in NCS promoters);
Australia and New Zealand (negative side effects of NCS); Northern Africa (markets for ecosystem
services or biodiversity provided by the NCS, markets for NCS outputs, and greater profitability of
alternative land uses); Northern Europe (greater profitability of alternative land uses); Southern Europe
(markets for ecosystem services or biodiversity provided by the NCS; skepticism or disinterest in NCS or
lack of trust in NCS promoters, and availability of technical advice for land managers); and Western
Europe (skepticism or disinterest in NCS or lack of trust in NCS promoters and availability of technical
advice for land managers).

Congruence of most-reported constraints among NCS pathways and, to a lesser extent, UN subregions
The top individual constraints highlight the diverse nature of the key implementation challenges faced
by many NCS projects. Lack of policy coordination or implementation capacity is the single most
frequently reported individual constraint in both the survey and literature samples, followed by lack of
enforcement of environmental laws, highlighting the importance of lack of institutional capacity as a key
barrier32,35. The next four constraints have nearly identical frequency counts, indicating a widespread
lack of NCS design information, skepticism or disinterest in NCS or lack of trust in NCS promoters, and
lack of funding for NCS on the part of both land managers and projects. Indeed, if the two funding
constraints (land manager; project-level) were combined, funding would be the most-reported
individual constraint overall, just edging out lack of policy coordination or implementation capacity —
not surprising given the current large funding gap for NCS and CDR more broadly51, and confirming the
general view of funding as a key constraint for NbS more broadly52,53. Together, these six constraints
account for one quarter of all observations for the 46 constraints.

The top-ranking overall constraints are not driven primarily by a small set of pathways or
subregions with high observation counts in our sample, but rather by high rankings of these constraints
for most pathways and subregions. Lack of policy coordination or implementation capacity, the top
overall constraint, also is the top-reported constraint for eight of 13 pathways (62 percent) and seven of
20 subregions (35 percent) and is a top-five constraint for ten pathways and 15 subregions. Information
about how to design or begin the NCS (third-ranking overall) is top-ranking and top-five-ranking for four
and six pathways, respectively, and one and seven subregions, respectively. Skepticism or disinterest in
NCS or lack of trust in NCS promoters, the fourth-ranking constraint overall, is second-ranking for two
and top-five-ranking for five pathways, and top-ranking in three and top-five-ranking in nine subregions,
respectively. Land manager access to other funding for NCS (sixth-ranking overall) is top-ranking in two,
and top-five-ranking in nine subregions, respectively; and top five-ranking for five pathways. There are
exceptions to this pattern of high overall rankings of individual constraints being driven by their high
rankings for many pathways and subregions. The second-place overall ranking of uncertain, or lack of,
enforcement of environmental laws results from its high observation counts in the large-sample South
and Central America and Western and Eastern Africa subregions and its high ranking (second or third
place) in the three pathways with the highest numbers of constraint observations (reforestation,
agroforestry, avoided forest conversion), despite being the top-ranking and top-five-ranking constraint
in only three and five subregions, respectively. Similarly, the fifth-place overall ranking of project access
to other funding for NCS —which is not top-ranking for any pathway or subregion— is driven
predominantly by its relatively high (fifth-place) ranking in the three subregions with the highest
observation counts (Western Africa, Eastern Africa, South America) and its sixth-place ranking in the
subregion with the fourth-highest observation count (Central America).

Despite broad congruence among subregions and pathways in terms of leading constraint categories
and constraints, some key differences emerge. At the broad regional to continental level, in Africa,
Knowledge, Social-behavioral and Finance constraints are most prevalent; in East and South Asia, Social-
behavioral constraints rank highest, followed by Knowledge and Markets constraints. In Central and
South America, Social-behavioral and Government and Organizations constraints are most prevalent,
followed by Knowledge constraints; while in Europe, Social-behavioral constraints are most prevalent,
followed by Markets and Knowledge constraints.

Uncertain, or lack of, enforcement of environmental laws is the top constraint in Central Africa,
and second-ranking in South and Central America. Lack of funding, while an important barrier in most
subregions, is particularly prevalent in Africa: in all African subregions except Northern Africa, either
land manager access to credit for NCS or land manager access to other funding for NCS is the most or
second-most reported constraint, with the respective other constraint also ranking high. Moreover,
project access to funding is the fifth-most frequently reported constraint in Eastern, Western, and
Central Africa. Limited social learning networks, land manager literacy, numeracy or technological
capabilities, concerns over negative equity impacts, and politically influential interests favoring non-NCS
all are barriers particularly prevalent in Africa, as evidenced by the relatively darker shading of these
constraints for these sub-regions in Fig. S20 (note that the figure is color-coded at the subregion level, so
the shading is comparable across subregions as an indicator of the relative prevalence of a constraint
across all subregions).

Greater profitability of alternative land uses is the most-reported market constraint overall, but
in some subregions, other market constraints rank higher: in Southern Asia and Eastern Africa, carbon
prices, markets for NCS outputs (i.e., food and fiber), and prices for ecosystem services or biodiversity all
rank higher; in Australia and New Zealand, carbon prices, and markets and prices for ecosystem services
or biodiversity rank higher. This points to the importance of missing or weak markets for NCS products,
ecosystem services or biodiversity provided in large portions of these subregions, caused in part by high
transaction costs54, the public good nature of some of these outputs55, or lack of accounting frameworks
that capture the full social value of natural assets and their services56,57.

These differences suggest that efforts to enable broader implementation of specific pathways
often may require tailored bundles of interventions in different subregions.

Among the large-sample subregions, Western and Eastern Africa stand out by their much thicker
(fat-tailed) frequency distributions and the absence of one or two dominant constraints (Fig. S21). These
two subregions thus are characterized by a comparatively larger number of highly prevalent constraints
on NCS implementation. In contrast, Northern America, Eastern and Southern Asia, and especially South
and Central America and South-Eastern Asia with their near-exponential frequency distributions are
characterized by a smaller number of much more prevalent constraints. All else equal, this suggests that
enabling broad NCS uptake may require addressing a larger number of barriers across larger
geographies in Western and Eastern Africa than in the other large-sample subregions.

Top-ranking constraints are more similar among pathways than among UN subregions. There are only
five top-ranking constraints across 13 pathways —three if the reduced woodfuel harvest in forests
pathway, which has only five papers or survey responses, is excluded. In contrast, there are 12 top-
ranking constraints across 20 subregions. For example, lack of policy coordination and implementation
capacity is the most-frequently top-ranking constraint for both pathways and subregions, but it is so for
only 35 percent of subregions versus for 62 percent of pathways. Even adjusted for the greater number
of subregions compared to pathways, diversity in top constraints is over 50 percent higher among
subregions than pathways. This is due to differences among regions in both the relative size of the
evidence base for different pathways, and the ranking of individual constraints (Fig. S21) and constraint
categories for given pathways (Fig. S17). As was true for subregions, the somewhat thicker constraint
frequency distributions exhibited by some large-sample pathways (regenerative agriculture, grassland
restoration, and climate-smart forestry) indicate that projects implementing these pathways on average
face more constraints.

Constraint composition in ten countries with highest NCS biophysical mitigation potential
The countries with the largest identified NCS biophysical mitigation potential show a surprising similarity
in the relative prevalence of constraint categories, represented by the colored bar segments in Fig. 6. As
in our overall sample (Fig. 2), in each of the top-five countries by biophysical mitigation potential, Social-
behavioral constraints account for the highest, and Knowledge generally the second-highest share of
constraint observations, though in China and India, the latter are tied with Rules and Laws. Government
and Organizations constraints account for a notably smaller share (9-11%) of total constraint
observations in each of the top five mitigation potential countries than they do in our full sample (16%),
while Rules and Laws and Markets account for slightly larger shares than in the full sample. Importantly,
despite the limited number of papers and surveyed projects in each country (N≤52), nearly all (41-44) of
the 46 tracked constraints are reported in each country with at least ten papers or survey projects.

Methods
The research presented here complies with all relevant ethical regulations. The survey was approved by
The Nature Conservancy’s (TNC) Chief Scientist under TNC’s Human Subject Research Review. Free, prior
and informed consent was obtained from all survey participants.

We combined a systematic literature review and a multilingual survey to identify implementation
constraints on NCS (e.g.,158). The rationale for this mixed-methods approach was threefold. First, the
survey allowed us to probe more comprehensively for the presence of potential constraints at a study
site, compared to published papers which often focus on one or a few specific constraints. The survey
also allowed us to enlarge the peer-reviewed English language literature evidence base on NCS
constraints, which shows uneven geographic and NCS pathway coverage36, and may help counter the
potential language and geographic biases in peer-review journals (e.g.,159).

Constraints typology
Following Brumberg et al.36, we defined constraints as factors that negatively affect the adoption,
viability, or effective implementation of NCS. We used mixed a priori and emergent coding to develop a
list of implementation constraints. We extracted an initial list of constraints from a set of recent papers
that identify constraints on specific NCS23,32 or nature-based solutions for climate change mitigation52,160.
We refined this initial list through a systematic review of recent peer-reviewed studies that document
NCS constraints, which yielded 39 discrete constraints36. These were further refined through pre-testing
of our NCS project survey instrument and analysis of survey responses. This further refinement resulted
in two changes: a decomposition of several of Brumberg et al.’s36 constraints into discrete component
constraints, changes in the wording of some constraints to better encompass the diversity of specific
permutations a constraint presented in the literature and survey, and the decomposition of Brumberg et
al.’s ‘economic’ constraints category into ‘finance’ and ‘markets’ categories. Our final list contained 46
discrete constraints that we grouped into eight categories (Table 1): Material Inputs, Finance, Markets,
Knowledge, Social-behavioral, Rules and Laws, Government and Organizations, and Negative Side Effects
(see Supplementary Materials Table S1 for descriptions). Despite differences in terminology and in some
cases categorization, our list captures the constraints identified in other recent classifications24–26,36 and
often presents a finer parsing or decomposition of constraints (Supplementary Materials, Constraint
terminology and categorization; Table S2). For example, Ref. 26 identifies high up-front costs as an
economic constraint. However, the latter are more likely to be a barrier if access to credit is lacking
(e.g.,161) or if this up-front cost is not at least offset by increased profitability of NCS during a decision-
relevant time period – two constraints that we capture separately. A crosswalk of our 46 constraints
with those identified in other recent studies can be found in the Supplementary Materials (Constraint
terminology and categorization; Table S2).

Survey instrument and implementation
The survey was targeted at projects that implement activities that qualify as NCS (Fig. S1), regardless of
whether a project self-identified primarily by that activity (e.g., agroforestry) or implemented it as part
of a broader portfolio of actions, and regardless of whether a project had stated climate mitigation
goals. For the purposes of this survey, a ‘project’ was defined as (1) the direct implementation of NCS by
an entity other than an individual landowner, or (2) the support of NCS implementation by others
through the provision of technical expertise, supply of inputs, or some other activity. The survey was
directed at project leads and their teams because a global survey of individual landowners was beyond
the scope of this study. However, respondents were asked to report constraints faced by their project
itself as well as by the land managers it engages. Project-level responses lead to the unavoidable
filtering of individual land manager perceptions of constraints, but likely also promote a synthesis of
constraints reported by individual land managers and thus facilitate the identification of the most
important project-level constraints. The survey was implemented through an online questionnaire
(Supplementary Materials, Survey questionnaire). Respondents were asked to provide information
about select project characteristics (Supplementary Materials, Questionnaire development and
distribution), identify the implemented NCS pathways and sub-pathways (Fig. S1), and select from our
list of 46 constraints all that made it challenging to achieve the full project objectives, with write-in
options for additional constraints. The questionnaire was piloted with NCS projects in Brazil and
Indonesia. To minimize the risk of misinterpretation, key terms in the questionnaire were identified
through different font color, underlined, and accompanied by pop-up explanations. The questionnaire
was originally developed in English and then professionally translated into French, Portuguese and
Spanish, with translations checked by NCS practitioners who are native speakers in each language. The
survey employed conditional (skip) logic and was implemented on the mobile-friendly Qualtrics
platform. The survey was open from December 2022 – December 2023, was distributed to prospective
projects by the authors and colleagues at 16 conservation, development and research institutions,
and was promoted in, and accessible via, the online newsletters of Restor (restor.eco) and
Nature4Climate (https://nature4climate.org) (Supplementary Materials, Questionnaire development
and distribution).

Georeferencing of literature study sites and survey projects
All literature and survey projects were geo-referenced to their corresponding administrative (ADM)
units at the ADM-0 (country), ADM-1 (state or equivalent), or ADM-2 (county or equivalent) level using
the geoBoundaries dataset162, based on the study area information provided in a paper and the
implementation area reported for each surveyed project, respectively. If a paper or survey covered
multiple ADM units and did not report to which ADM unit(s) an observed constraint applied, we
assigned the constraint to all ADM units covered by the paper or survey. All data analysis was performed
in R163. For additional information on geocoding and data analysis see Supplementary Materials.

Included NCS pathways
Our analysis includes 22 NCS pathways as shown in Fig. S1. These are commonly grouped into three NCS
strategies – protection, improved management, and restoration (Fig. S1;5). The survey questionnaire
referred to the increased soil carbon in grazing lands, reduced emissions in grazing lands, reduced
emissions in croplands, and increased soil carbon in croplands pathways jointly as regenerative
agriculture (other than agroforestry)164, and our analysis maintains this grouping. Similarly, we also
report the pooled results for the three agroforestry pathways (cropland-based agroforestry,
silvopasture, forest-based agroforestry) and the two reforestation pathways (natural forest restoration,
reforestation with plantations), respectively. The literature portion of our analysis is based on Brumberg
et al.36, which analyzed the constraints reported in recent (2020-2021) peer-reviewed papers that
identify barriers to 13 NCS. Brumberg et al.’s analysis excluded regenerative agriculture pathways (other
than agroforestry). We reviewed and recoded the studies included in Brumberg et al.36 to the
constraints used in this paper (Supplementary Materials, Recoding), and geo-referenced them to the
corresponding ADM units. We screened the literature and survey datasets for overlap to avoid double-
counting and found that no project was represented in both.

Because our analysis of constraints is implemented at the NCS pathway level, a survey project or paper
that reported the same constraint for multiple sub-pathways of the same pathway – say, tree-based
intercropping and silvopasture, two forms of agroforestry – generated a single constraint-pathway-
location observation (hereafter: constraint observation). Conversely, a paper or survey that recorded
the same constraint for two different pathways – say, agroforestry and reforestation – generated two
constraint observations.

We count each unique instance of a constraint reported in a paper or survey response. For
example, if a paper reported skepticism or disinterest in NCS among landowners, local government
representatives, and national policymakers, we counted this as three counts of skepticism or disinterest
because each instance independently affects NCS implementation feasibility. Consequently, the
constraint counts for a pathway or subregion generally exceed the number of papers and survey
responses for that pathway or subregion.

We present results primarily at the UN subregion level, which distinguishes 22 geographic
subregions165. Because neither the literature nor the survey sample included two subregions
(Micronesia, Polynesia), we present results only for the 20 subregions with data.

Data analysis
In addition to the overall frequency counts of observations of individual constraints and constraint
categories, we analyze observation counts by NCS pathway and UN subregion. We identify the most-
frequently number one-ranking constraints and constraint categories for pathways and subregions,
respectively, and the constraints and categories with the highest number of combined top-three
rankings for pathways and subregions, respectively.

We assess the impact of different aggregation approaches for pathway and subregion-level data
on these rankings. To illustrate how different aggregation approaches can impact constraint or
constraint category rankings for a pathway or subregion, consider the case of aggregating pathway-level
constraint observations in a subregion. The most straightforward way of doing so is to sum the
observations of a given constraint for all pathways in the subregion. Under this raw count aggregation
approach, the constraints that are most prevalent in better-studied pathways tend to emerge as the
prevalent constraints for the subregion as a whole. This may lead to a biased assessment of the
prevalent NCS constraints in the subregion if the relative prevalence of constraints differs among
pathways and the pathway composition of the evidence base does not reflect actual current or potential
future pathway implementation extent. An alternative aggregation approach that overcomes this
potential drawback assigns equal importance weights to all pathways, calculates for each pathway a
metric that indicates the relative prevalence of each constraint for the pathway, and then, for each
constraint, sums the values of this metric over all pathways, to arrive at a subregional measure of
relative prevalence that removes the impact of (i.e., normalizes for) differences in the pathway
observation counts in that subregion. This approach allows constraints that are more prevalent in larger
numbers of pathways in a subregion to emerge as the more prevalent constraints for the subregion as a
whole, rather than the constraints that are more prevalent in better-studied pathways in the subregion.

We implement this latter approach by calculating z-scores as a measure of relative prevalence of each
constraint and constraint category for each pathway in a subregion and compare the results to the first
approach that sums raw observation counts across pathways in each subregion. Because we found that
the impact of the choice of aggregation approach on the rankings of constraints and constraint
categories is marginal, we report the rankings based on pathway or subregion raw count aggregation
(over subregions and pathways, respectively). However, we show how little results differ under the z-
score aggregation approach, using the example of ranking the most-prevalent constraint categories in
subregions.

To identify which constraints may be most important to address to unlock the global NCS
mitigation potential, we also assess the constraint composition in each of the ten countries with the
largest identified NCS biophysical mitigation potential, which together account for over half of the total
identified global potential (3.24 of 5.85 Gt CO e-yr;166).
2

Data availability
The geo-referenced database generated in this study has been deposited in the Harvard Dataverse
Repository under accession code https://doi.org/10.7910/DVN/EDZHBF.

Code availability
The analysis code and the figure code generated in this study have been deposited in the Harvard
Dataverse Repository under accession code https://doi.org/10.7910/DVN/EDZHBF.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This is a thorough, detailed piece of work which contributes valuable insight into the failure of natural climate solutions to reach their full potential and identifies the principal constraints by region and pathway. Used well, this work could be highly impactful in allowing those concerned with NCS implementation the mitigate constraints and develop successful implementation strategies. The evidence presented supports the conclusions drawn; there is clear and honest enumeration of the limitations. There are no evident flaws in the data analysis. The methodology is clearly described, such that replicability is possible and meets a high standard.", "reviewer_2": "The manuscript presents a study that aims to identify, categorize, and map the barriers hindering the implementation of Natural Climate Solutions (NCS). The authors provide a comprehensive, spatially explicit assessment of NCS constraints worldwide by combining two complementary datasets: a systematic literature review and a global survey. Overall, I find the manuscript well written and methodologically sound, with only minor issues to address.\n• Line 58: Insert “(AFOLU)” after “other land uses” so that readers immediately understand the acronym for Agriculture, Forestry, and Other Land Uses.\n• Lines 849–850: The phrase “each were completed” is grammatically acceptable but stylistically awkward, as each is singular while were is plural. Consider revising to: “Each of the twenty-nine complete survey responses was completed by a group of respondents, representing a total of 215 individuals from 40 organizations, including environmental (38%) and development (18%) NGOs, research institutions (18%), governmental entities including utilities (10%), multi-sectoral entities (10%), and for-profit enterprises (8%).”\n• Figure 1: Include the percentage that each category accounts for next to its corresponding bar to help readers quickly interpret the data.\n• Figure S10: Adopt the same visual style as Figures S6 and S16 for consistency. Although the meaning can be inferred, please state in the caption what the red and green colors represent for clarity.", "reviewer_3": "The paper presents a valuable contribution to climate change mitigation and to the fields related to the protection, restoration, and sustainable management of nature through the implementation of appropriate solutions. The effort devoted to data collection, systematization, and synthesis, as well as to the interpretation of the results obtained from the analysis of the literature and survey outcomes, is clearly recognised and appreciated. The results are presented and discussed in a comprehensive way, both in the main text and in the supplementary materials. The paper also provides several insightful considerations on how to address and overcome the identified constraints, which adds significant value to the work.\nHowever, I believe that the MS should better clarify the links with Brumberg et al. 2025 (https://doi.org/10.1093/pnasnexus/pgaf173). The MS combines both a survey and a review. My understanding is that the review has been already (partially or entirely?) presented in Brumberg et al. 2025. If this is the case, the MS should be more explicit in describing what is really new (the survey + the integration between survey and review, I assume) from what was has been already published. The introduction contains a reference to the published paper, but the results and methods are more ambiguous in reporting the outcomes of this study vs the ones of the previous study (e.g., some of the figures of the MS builds on figures from the published paper). It is also quite surprising that the introduction (e.g., in lines 75-76) does not mention the previous study in the relevant literature, considering that it contributed substantially to address the need mentioned in lines from 80 on.\nSpecific comments\n1. Lines 112–119: I suggest moving this paragraph to the beginning of the “NCS pathway representation” section, so that a general overview of the results is provided before going into details about the most and least represented pathways.\n2. Figure 1: Consider adding the total numbers at the end of each bar to improve readability (for instance, it is not immediately clear that government and organizations is the most frequently observed, as it visually appears similar to social-behavioral). Alternatively, you could adjust the x-axis interval (e.g., using 500 instead of 1000) or switch to percentages to facilitate comparison between the text and the figure. The same comment applies to Figure 2.\n3. Line 157: As in Comment 1, a general overview of the results would be useful here before discussing the “most frequently reported” aspects.\n4. Figure 2 and lines 159–162: Although Table S1 in the Supplementary Materials provides the full names of the constraints, it remains difficult to match them between the text and the figure, since the abbreviations and full names differ slightly (e.g., “lack of non-credit funding for land managers” vs. “land manager access to other (non-credit) funding for NCS”). I suggest adding serial numbers (in both the figure and Table S1) to make the correspondence clearer.\n5. Line 210: The reference to figure S13 does not seem correct — please double-check it.\n6. Figure S19: The image appears blurred and is difficult to read. Since abbreviations were used in Figure 2, consider adopting the same approach here to enlarge the text.\n7. Lines 690–695: It seems that the third reason is missing in this list — please check.\n8. Lines 702–705: This passage is somewhat difficult to understand — could you please provide an example to clarify your point?\n9. Lines 733–734: Within brackets, you refer to “Supplementary Materials, Survey questionnaire and distribution,” but there is no section in the Supplementary Information with that exact title. I understand you may be referring to both the “Survey Questionnaire” and “Questionnaire development and distribution” sections. If so, please specify both names to make the reference clearer; otherwise, revise the reference according to your intended meaning.\n10. Line 748: From this point onward, the text appears somewhat disorganised. I suggest adding a subheading instead of relying on line breaks.\n11. Section starting at line 821 – “Sample frame”: This section already presents results — in fact, they seem to be the first results worth discussing to contextualise the others. I therefore recommend moving this section to the beginning of the Results, before “NCS pathway representation” (line 104).\n12. Minor typos and formatting issues:\na. Line 68: Capitalise “implementation.”\nb. Line 74: Missing spaces.\nc. Line 690: Missing closing parenthesis “)”.\nd. Line 716: There seems to be an extra or missing parenthesis.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "December 16, 2025\nDear referees,\nThank you for taking the time to review and provide thoughtful comments on our manuscript\n‘Implementation constraints on natural climate solutions: A global literature review and survey.’\nWe believe that we have addressed all comments and that the manuscript has gained in clarity\nas a result.\nPlease find below our responses to all referees’ commentson the manuscript NCOMMS-25-\n45305A. The referee comments are shown verbatim followed by our responses in boldface.\nPlease note: all line numbers shown in our responses to the referees’ comments refer to the\nrevised manuscript with tracked changes.\nReviewer #1 (Remarks to the Author):\nThis is a thorough, detailed piece of work which contributes valuable insight into the failure of\nnatural climate solutions to reach their full potential and identifies the principal constraints by\nregion and pathway. Used well, this work could be highly impactful in allowing those concerned\nwith NCS implementation the mitigate constraints and develop successful implementation\nstrategies. The evidence presented supports the conclusions drawn; there is clear and honest\nenumeration of the limitations. There are no evident flaws in the data analysis. The\nmethodology is clearly described, such that replicability is possible and meets a high standard.\nResponse: We appreciate your taking the time to review our manuscript. It is encouraging to\nhear that you think the work presented has the potential to be impactful.\nReviewer #2 (Remarks to the Author):\nThe manuscript presents a study that aims to identify, categorize, and map the barriers\nhindering the implementation of Natural Climate Solutions (NCS). The authors provide a\ncomprehensive, spatially explicit assessment of NCS constraints worldwide by combining two\ncomplementary datasets: a systematic literature review and a global survey. Overall, I find the\nmanuscript well written and methodologically sound, with only minor issues to address.\n• Line 58: Insert “(AFOLU)” after “other land uses” so that readers immediately understand the\nacronym for Agriculture, Forestry, and Other Land Uses.\nResponse: Thank you. We have made this change (58).\n• Lines 849–850: The phrase “each were completed” is grammatically acceptable but stylistically\nawkward, as each is singular while were is plural. Consider revising to: “Each of the twenty-nine\ncomplete survey responses was completed by a group of respondents, representing a total of\n1\n215 individuals from 40 organizations, including environmental (38%) and development (18%)\nNGOs, research institutions (18%), governmental entities including utilities (10%), multi-sectoral\nentities (10%), and for-profit enterprises (8%).”\nResponse: Thank you for this suggestion. However, the wording you suggest would change the\nmeaning as it would state that we received 29 complete survey responses, which is incorrect.\nRather, 29 of the complete survey responses we received were completed by groups of\nindividuals rather than by a single individual. We mentioned this fact of several responses\nbeing completed by groups to explain why the total number of respondents (215) exceeds the\ntotal number of projects represented in our survey data (154).\nTo avoid the awkward phrasing in the original manuscript, we reworded the sentence as\nfollows (139-142):\n“In 29 cases, a group of individuals completed a survey for a project, resulting in a total of 215\nsurvey participants from 40 organizations representing environment (38%) and development\n(18%) NGOs, research institutions (18%), governmental entities including utilities (10%), multi-\nsectoral entities (10%) and for-profit enterprises (8%).”\n• Figure 1: Include the percentage that each category accounts for next to its corresponding bar\nto help readers quickly interpret the data.\nResponse: Thank you for this suggestion. We agree that showing the percentage of each\ncategory is helpful and have added it to each bar.\n• Figure S10: Adopt the same visual style as Figures S6 and S16 for consistency. Although the\nmeaning can be inferred, please state in the caption what the red and green colors represent for\nclarity.\nResponse: Thank you. We have changed the color coding for subregions and regions to the\nsame applied in Figures S6 and S16. We also added the following text to the caption of Figure\nS10:\n“Shading intensity is proportional to a subregion-pathway combination’s share in all\nconstraint observations (red shading) or the subregional or regional shares in all constraints\nobservations (green shading).”\nFor consistency, we also added similar text explaining the color coding to the caption of Figure\nS6:\n“Shading intensity is proportional to a subregion-pathway combination’s share in all\npapers or\nsurvey projects (red shading) or the subregional or regional shares in all papers or projects\n(green shading).”\nThe paper presents a valuable contribution to climate change mitigation and to the fields\nrelated to the protection, restoration, and sustainable management of nature through the\nimplementation of appropriate solutions. The effort devoted to data collection, systematization,\nand synthesis, as well as to the interpretation of the results obtained from the analysis of the\nliterature and survey outcomes, is clearly recognised and appreciated. The results are presented\nand discussed in a comprehensive way, both in the main text and in the supplementary\nmaterials. The paper also provides several insightful considerations on how to address and\novercome the identified constraints, which adds significant value to the work.\nHowever, I believe that the MS should better clarify the links with Brumberg et al. 2025\n(https://doi.org/10.1093/pnasnexus/pgaf173). The MS combines both a survey and a review.\nMy understanding is that the review has been already (partially or entirely?) presented in\nBrumberg et al. 2025. If this is the case, the MS should be more explicit in describing what is\nreally new (the survey + the integration between survey and review, I assume) from what was\nhas been already published. The introduction contains a reference to the published paper, but\nthe results and methods are more ambiguous in reporting the outcomes of this study vs the\nones of the previous study (e.g., some of the figures of the MS builds on figures from the\npublished paper). It is also quite surprising that the introduction (e.g., in lines 75-76) does not\nmention the previous study in the relevant literature, considering that it contributed\nsubstantially to address the need mentioned in lines from 80 on.\nResponse: Thank you for reviewing our manuscript carefully and for the very helpful\nsuggestions. Thank you in particular for highlighting the need to better explain the specific\ncontributions this manuscript makes to the identification and mapping of NCS\nimplementation constraints, beyond Brumberg et al.’s (2025) work.\nIn addition to the global survey that expands the evidence base beyond the published\nliterature, these contributions are as follows:\n Disaggregation of several of the constraints used in Brumberg et al., which results in a\nlarger set of constraints (46 compared to 39);\n Recoding of Brumberg et al.’s (2025) evidence base to the new, larger constraints set;\n Splitting Brumberg et al.’s “economic” constraint category into two categories,\n“finance” and “markets”, to better reflect the distinct sets of challenges that finance\nand markets represent;\n Separating out NCS pathways that Brumberg et al. (2025) combined due to the small\nnumber of studies in the reviewed literature. Specifically, Brumberg et al. combined\navoided coastal wetland conversion and coastal wetland restoration; avoided\n3\ngrassland conversion and grassland restoration; and avoided peatland conversion and\npeatland restoration, respectively. We consider these six pathways separately;\n Mapping of the spatial extents of the study areas in the papers analyzed in Brumberg\net al. Brumberg et al. only recorded the country of a study (ADM0 level). In contrast,\nwe extracted location information from the studies and mapped study locations to the\nrelevant lower administrative levels (ADM1 or ADM2) that matched the study areas;\n Integration of the literature and survey datasets\nWe note that in the Supplementary Materials, our original submission already provided a\ndetailed description of how the literature review constraints observations were recoded to\nthe slightly larger set of constraints used in the present paper (see SM section ‘Recoding of\nBrumberg et al.’s constraints’).\nIn the main text methods section, we now more clearly describe the two-step process through\nwhich the list of constraints used in the present manuscript were derived. Specifically, we\nnow state that we further refined the 39 constraints identified in Brumberg et al. through pre-\ntesting of our survey and analysis of survey responses, resulting in the 46 constraints used in\nthe present manuscript. (763-784)\nWe also added Brumberg et al. (2025) to the cited studies in line 778.\nIn the introduction, we changed the paragraph starting on line 86, which now reads as\nfollows:\n“Brumberg et al.’s36 systematic review of the recent literature on NCS constraints was an\nimportant contribution to filling this critical knowledge gap. In this paper, we build on and\nadvance that effort by conducting a global survey of NCS projects that uses an expanded set\nof implementation constraints, recoding Brumberg et al.’s36 literature dataset to this\nexpanded constraints set, georeferencing all survey and literature constraint observations to\ntheir corresponding administrative levels, and integrating the survey and literature datasets\ninto a spatial database that reflects the current evidence base on NCS implementation\nconstraints.”\nWe also added Brumberg et al. (2025) in line 100 as an additional reference (after reference\n#35) for national-level assessments and in line 102 as an example of studies that employed a\ncoarser NCS pathway set (they combined coastal wetland restoration and avoided conversion\npathways, the peatland restoration and avoided conversion pathways, and the grassland\nrestoration and avoided conversion pathways, respectively).\nSpecific comments\n1. Lines 112–119: I suggest moving this paragraph to the beginning of the “NCS pathway\nrepresentation” section, so that a general overview of the results is provided before going into\ndetails about the most and least represented pathways. Response: Thank you. We\nimplemented this change.\n4\n2. Figure 1: Consider adding the total numbers at the end of each bar to improve readability (for\ninstance, it is not immediately clear that government and organizations is the most frequently\nobserved, as it visually appears similar to social-behavioral). Alternatively, you could adjust the\nx-axis interval (e.g., using 500 instead of 1000) or switch to percentages to facilitate comparison\nbetween the text and the figure. The same comment applies to Figure 2. Thank you. Reviewer\n#2 had a similar suggestion: to add to each bar the percentage each category accounts for in\nthe total number of observations. We implemented that change. We also added an\nexplanatory statement to the figure caption. We implemented the same changes to Figure 2.\n3. Line 157: As in Comment 1, a general overview of the results would be useful here before\ndiscussing the “most frequently reported” aspects.\nResponse: Thank you for this suggestion. We have moved the statements that present key\nhigh-level findings to the beginning of this section (206-216). These pertain to 1) the overall\nsmooth frequency distribution of observation counts across constraints, with the exception of\nthe most frequently reported constraint; and 2) constraints in all categories except Negative\nside effects are frequently encountered.\n4. Figure 2 and lines 159–162: Although Table S1 in the Supplementary Materials provides the\nfull names of the constraints, it remains difficult to match them between the text and the figure,\nsince the abbreviations and full names differ slightly (e.g., “lack of non-credit funding for land\nmanagers” vs. “land manager access to other (non-credit) funding for NCS”). I suggest adding\nserial numbers (in both the figure and Table S1) to make the correspondence clearer.\nResponse: Thank you for catching this inconsistency in the wording of the “land manager\naccess to other funding” constraint.We checked all instances of constraints in the manuscript\nand their wording now matches the full constraint names shown in Table S1. We believe this\neliminates the possibility of confusion regarding which constraint we are referring to in a\nspecific instance.\n5. Line 210: The reference to figure S13 does not seem correct — please double-check it.\nResponse: Thank you for catching this error. We appreciate your careful review! We removed\nthe reference to figure S13. This figure is correctly referenced elsewhere in the manuscript.\n6. Figure S19: The image appears blurred and is difficult to read. Since abbreviations were used\nin Figure 2, consider adopting the same approach here to enlarge the text. Response: Thank\nyou for noticing this. We now use the abbreviated constraint names in this figure and have\nincreased its resolution. We have implemented the same changes in Figure S21.\n7. Lines 690–695: It seems that the third reason is missing in this list — please check. Thank\nyou. The third reason is given in the last two lines in this paragraph (755-761): “...and may\nhelp counter the potential language and geographic biases in peer-review journals.”\n5\n8. Lines 702–705: This passage is somewhat difficult to understand — could you please provide\nan example to clarify your point? Thank you. An example of our decomposition of some\nconstraints used in other classifications is provided in lines 779-782: “For example, Ref. 26\nidentifies high up-front costs as an economic constraint. However, the latter are more likely to\nbe a barrier if access to credit is lacking (e.g.,162) or if this up-front cost is not at least offset by\nincreased profitability of NCS during a decision-relevant time period – two constraints that we\ncapture separately.”\n9. Lines 733–734: Within brackets, you refer to “Supplementary Materials, Survey questionnaire\nand distribution,” but there is no section in the Supplementary Information with that exact title.\nI understand you may be referring to both the “Survey Questionnaire” and “Questionnaire\ndevelopment and distribution” sections. If so, please specify both names to make the reference\nclearer; otherwise, revise the reference according to your intended meaning. Thank you for\nnoticing this error.We were referring to the Questionnaire development and distribution\nsection in the Supplementary Materials and now are referencing that section correctly (802).\n10. Line 748: From this point onward, the text appears somewhat disorganised. I suggest adding\na subheading instead of relying on line breaks. Thank you for this suggestion. We have added\ntwo new subheadings, Georeferencingof literature study sites (817) and survey projectsand\nIncluded NCS pathways (825).\n11. Section starting at line 821 – “Sample frame”: This section already presents results — in fact,\nthey seem to be the first results worth discussing to contextualise the others. I therefore\nrecommend moving this section to the beginning of the Results, before “NCS pathway\nrepresentation” (line 104). Thank you for this suggestion. We moved the Sample frame section\nto the beginning of the Results section (111-142).\n12. Minor typos and formatting issues:\na. Line 68: Capitalise “implementation.” Corrected, thank you (68).\nb. Line 74: Missing spaces. Space added, thank you (74).\nc. Line 690: Missing closing parenthesis “)”. Added, thank you (756).\nd. Line 716: There seems to be an extra or missing parenthesis. Thank you. We added the\nmissing opening parenthesis (783).\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nTimm Kroeger, Ph.D. (on behalf of all co-authors)\nSenior Environmental Economist\nGlobal Science\nThe Nature Conservancy\nBethesda, MD 20817, USA\nEmail: tkroeger@tnc.org\nPh: (301) 728-7776\n7"}, {"round": 2, "reviewer_comments": {"reviewer_3": "My previous remarks have been addressed in a satisfactory way and the MS has been improved and it is now ready for acceptance. No further comments.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": ""}]

Decision letter