Recreation Effects on Wildlife: A Review of Potential Quantitative Thresholds
Jeremy S. Dertien1*, Courtney L. Larson2, Sarah E. Reed1, 2
1Americas Program, Wildlife Conservation Society, 1474 Campus Delivery, Fort Collins,
Colorado, 80523-1474, United States of America
2Department of Fish, Wildlife, and Conservation Biology, Colorado State University, 1474
Campus Delivery, Fort Collins, Colorado, 80523-1474, United States of America
261 Lehotsky Hall
Clemson, SC 29634-0317
Outdoor recreation is increasingly recognized for its deleterious effects on wildlife individuals
and populations. However, planners and natural resource managers lack robust scientific
recommendations for the design of recreation infrastructure and management of recreation
activities. We reviewed 38 years of research on the effect of non-consumptive recreation on
wildlife to attempt to identify effect thresholds or the point at which recreation begins to exhibit
behavioral or physiological change to wildlife. We found that 53 of 330 articles identified a
quantitative threshold. The majority of threshold articles focused on bird or mammal species and
measured the distance to people or to a trail. Threshold distances varied substantially within and
among taxonomic groups. Threshold distances for wading and passerine birds were generally
less than 100 m, whereas they were greater than 400 m for hawks and eagles. Mammal threshold
distances varied widely from 50 m for small rodents to 1,000 m for large ungulates. We did not
find a significant difference between threshold distances of different recreation activity groups.
There were large gaps in the scientific literature regarding several recreation variables and
taxonomic groups including amphibians, invertebrates, and reptiles. Our findings exhibit the
need for studies to measure continuous variables of recreation extent and magnitude, not only to
detect effects of recreation on wildlife, but also to identify effect thresholds when and where
recreation begins or ceases to affect wildlife. These changes to studies of recreation ecology will
provide better recommendations to natural resource managers tasked with conserving
biodiversity while providing human access to protected lands.
Keywords: recreation impacts; protected areas; human disturbance; distance to people; wildlife
conservation; park management
Human disturbance is widely recognized for its deleterious effects on the physiology,
behavior, and demographics of individuals and populations of wild animals (Steven and Castley
2013, Coetzee and Chown 2016). Sources of disturbance are extremely diverse and include
mortality from hunting and roadkill (Scillitani et al. 2010) to non-consumptive sources such as
hiking, boating, and wildlife watching (Cowling et al. 2015, Tarjuelo et al. 2015). Whereas the
population- or community-level effects of human disturbance via take are more apparent, effects
of non-consumptive human disturbance on wildlife physiology and behavior are less easily
identified or separated from other confounding environmental factors. A growing body of
research has focused on the effects of non-consumptive human disturbance with a specific focus
on outdoor recreation (Larson et al. 2016).
Outdoor recreation is growing rapidly around the world and has been identified as one of
the biggest threats to protected areas (Balmford et al. 2015, Schulze et al. 2018). In the United
States visitation to developed recreation sites is projected to increase by 23% by 2030 (White et
al. 2014). Human disturbance on wildlife from non-consumptive recreation can result in altered
spatiotemporal habitat use (Kangas et al. 2010, Rösner et al. 2014), decreased survival and
reproduction (Iverson et al. 2006, Baudains and Lloyd 2007), and ultimately decreased
population abundance (Miller et al. 1998, Bejder et al. 2006) or extirpation from otherwise
suitable habitat (Steven and Castley 2013). To reduce or eliminate negative effects of recreation
on wildlife, land managers require explicit recommendations for how to design trails, manage
visitors and otherwise balance the multi-use objectives of many protected areas.
Identifying the effect threshold or the point at which wildlife begin to be disturbed by
such recreation activities is key to providing informed recommendations to land managers and
planners attempting to make decisions regarding infrastructure construction and visitor
management (Braunisch et al. 2011, Rösner et al. 2014, Monz et al. 2016). Data on effect
thresholds give protected area planners and managers a better understanding, for example, of the
overall effect area for each trail (Lenth et al. 2008), buffer zones around birds of prey nests
(Swarthout and Steidl 2001, Keeley and Bechard 2011), and evidence to defend limits on
visitation numbers or seasonal closures (Schummer and Eddleman 2003, Malo et al. 2011).
Researchers that study the effects of recreational activities on wildlife often attempt to estimate
quantitative effects thresholds as effect distances from people or infrastructure (Pittfield and
Burger 2017, Bötsch et al. 2018), density of trails and other infrastructure (Braunisch et al. 2011,
Harris et al. 2014), or visitation rates (Kerbiriou et al. 2009, Malo et al. 2011).
Elucidating an effect threshold can be difficult because a threshold doesn’t exist, the
study sample wasn’t large enough, or inferring an effect threshold wasn’t of interest during study
design. Therefore, often the mean distance , mean disturbance intensity, or an index of
disturbance is reported rather than an effect threshold. The mean effect level is important and
valuable information in regard to conservation, but likely does not capture the point at which all
or at least the vast majority of wildlife individuals are affected. Estimating the complete extent of
potential recreation impacts provides a more complete assessment for conservation planning.
Our objective was to identify quantitative thresholds of non-consumptive recreation in
order to provide clearer data to nature professionals about the potential extents and limits of
recreation impacts on wildlife. We conducted a systematic review of the published scientific
literature of non-consumptive human recreation effects on wildlife in terrestrial environments.
We analyzed articles to determine if the authors detected a quantitative threshold where
recreation began to impact a wildlife individual, population, or community or cause habitat
degradation. .We summarize the findings descriptively, reviewing the species and ecosystems
that have been studied, and identifying gaps in the available literature. We identify quantitative
thresholds across a wide array of recreation activity types, wildlife species, and response
measurements which only allows summation of our findings across broad categories . Finally,
we discuss the limitations of these findings and how future research should consider study
designs that explore the quantitative thresholds of systems as a means of providing the best
recommendations for natural resource professionals.
We used a database of primary literature compiled for a systematic review of the effects of
recreation on wildlife (Larson et al. 2016), supplemented with additional articles published
through December 2018 that matched the criteria of Larson et al. (2016). Their criteria was
limited to journals (n = 166) in the Web of Science database (Thompson Reuters, New York,
NY, USA) in the categories: biodiversity conservation, ecology, zoology, and behavioral
sciences. The criteria included articles that focused on non-consumptive human recreation
activities (i.e., did not include hunting or fishing), studied one or more animal species, assessed
recreation effects using statistical tests, and were published in English. For the purpose of our
review of quantitative thresholds, we included only studies of terrestrial species or interactions
with aquatic animals while they were on land. This resulted in 330 articles remaining in our
We sought to determine which papers identified a minimum effect threshold, which we
defined as the point at which ≥ 90% of sampled wildlife individuals already showed a behavioral
or physiological response (e.g., flushing, increased heart rate) to a recreation disturbance or the
point at which recreation disturbance begins to reduce the presence, abundance or survival
probability of a population or degrade the habitat ). For example, Thomas et al. (2003) found that
96% of sanderlings (Calidris alba Pallas, 1764) were disturbed at a distance of ≤ 30 meters and
Malo et al. (2011) found that detections of guanaco (Lama guanicoe, Müller 1776) began to
reduce at > 250 visitors/day. We chose this definition because of the preponderance of studies
that identified the 90th or 95th percentile of threshold distance rather than the furthest sample
outlier. We did not include papers that reported only the mean level of disturbance (e.g., mean
flush distance, mean recreation group size), as this value does not represent the full distribution
of disrupted animals . We did include papers that presented graphical representations that
allowed for estimation of a threshold effect, even if that threshold was not explicitly stated in the
We recorded the details of each quantitative threshold including the measure of wildlife
or indirect response (behavioral, occurrence, physiological, relative abundance, reproduction,
and habitat degradation), the measure of recreation disturbance (e.g., number of visitors, distance
to people) and the value at which the disturbance threshold was observed (e.g., > 14 visitors/day,
<100 meter from people). Some articles recorded multiple threshold effects per species that
varied by season or recreation type; therefore, several articles had multiple database inputs. To
avoid pseudoreplication we took the largest threshold response if there were multiple values for
one species across seasons or for the same recreation activity. We did record all values across
different recreation types for the same species since recreation types can be viewed as different
treatments. We classified each article into nine different ecosystem classifications alpine/tundra,
coast/shoreline, desert, forest, grassland, polar, savanna, scrub/shrub, and wetland. Studies were
classified into all the ecosystems that the authors identify in the paper. In addition, we extracted
details on study type (e.g., observational or experimental), species of interest, and publication
We further binned each paper based on recreation activities into either hiking-only, multi-
use nonmotorized, or motorized categories. This was done in order to compare threshold effects
across general recreation types. The multi-use nonmotorized included papers that had hiking as
one of multiple activities and the motorized category included papers that were motorized-only
and which had multiple motorized and non-motorized recreation activities. We used a single-
factor analysis of variance to test if there was a significant difference among these recreation
Finally, we researched body masses for all bird and mammal species (Dunning 2007,
Williamson et al. 2013) and used linear regression to analyze the relationship between mass and
effect distance for birds and mammals separately, with body mass as an explanatory variable. We
excluded two studies on flightless birds given the mass disparity to flighted birds and two studies
on mammal populations that were habituated to close human presence. We log transformed bird
(n = 50) and mammal (n = 21) body mass and effect distance to conform to assumptions of
normality. Significance of all tests was set at 0.05 and analyses were performed in program R (R
Core Development Team 2020). We predicted that bird and mammal body size would be
positively correlated with threshold distances (Blumstein et al. 2005, Piratelli et al. 2015, Battisti
et al. 2019) (i.e., larger birds and mammals would respond to disturbance at further distances).
We reviewed 330 journal articles, of which 53 articles identified one or more quantitative
threshold effects. The vast majority of the 53 articles focused on bird or mammal species, with
little representation of invertebrates, amphibians or reptiles. Studies of birds focused primarily on
species in the orders Charadriiformes (e.g., wading birds and gulls), Accipitriformes (e.g.,
hawks, eagles, and vultures) and Passeriformes (i.e., perching birds) (Fig. 1A). Mammal studies
primarily focused on species in the orders Artiodactyla (i.e., even-toed ungulates) and Carnivora
(i.e., bears and cats) (Fig. 1B).
Studies that identified threshold effects were conducted predominately in forest, or
coastal/shoreline ecosystems with limited representation in the other ecosystems (Fig. 2A).
Hiking was by far the most studied recreational activity, followed by wildlife viewing on land,
beach use, and dog-walking (Fig. 2B). Most studies examined only non-motorized activities
(71.7%) while fewer studies examined only motorized activities (15.1%) or both (13.2%). Nearly
half (39.6%) of the articles examined two or more recreation activities, two-thirds of which
included hiking as one of the activities.
Quantitative thresholds were identified for a variety of recreation disturbance variables,
but can be generally grouped into distance effects, visitation rates, and infrastructure effects (Fig.
2C). Distance effects included distance to people, trails, and vehicles. Studies that focused on the
distance effects to people included observational studies in coastal ecosystems where trails are
less well defined and quasi-experimental studies in which researchers approached individual
animals to measure alert and flight initiation distances. Quantitative thresholds for distance to
trail were identified in studies of birds, mammals, and invertebrates. Several studies were
precluded from the possibility of finding a threshold effect because the researchers only focused
on categorical differences between trail type.
Articles examining thresholds of visitation rates, or the number of people or vehicles per
unit time, were comparatively less well represented (Fig. 2C). Those measuring threshold
numbers of people focused on human visitation effects on primate group behavior, decreasing
detections correlated with increasing magnitude of visitation, and behavioral disturbance to
animals from tourist group visits to wildlife concentrations. Visitor numbers as low as one
person or off-road vehicle per day were shown to negatively affect the habitat use of studied
species in some cases. Very few articles focused on or found threshold effects of recreation
infrastructure (Fig. 2C).The vast majority of threshold studies focused on the behavioral
response of wildlife to a human disturbance, followed by measurements of occurrence and
relative abundance (Table 1). Of the behavioral response measurements over half were measured
as a flight initiation distance (i.e., the distance at which wildlife began to move due to a human
disturbance). Other behavior measurements included the number of wildlife individuals feeding
or standing, vigilance behavior, and changes in activity budget; however, each of these were
measured in less than 4% of papers. Occurrence measurements were a derivation of presence or
detection and abundance measurements included counts of individuals or fecal pellet densities.
Physiological, reproductive, or habitat degradation threshold responses were represented in less
than 2% of papers (Table 1).
Given the relatively low sample size of articles that identified thresholds we were only
able to make meaningful conclusions about distance thresholds for birds and mammals (Fig. 3).
Distance thresholds from people and trails varied among orders and species. For example,
wading birds and passerines were generally affected at distances less than 100 m, whereas larger-
bodied species such as hawks and eagles had threshold effect distances greater than 400 m (Fig.
4). Smaller rodent species avoided areas within 50-100 m of trails or people, whereas some
carnivores and ungulates had minimum effect distances anywhere from 40 to 1000 m from trails
and people. The median effect threshold distance was 80.0 m for birds and 77.5 m for mammals
and mean thresholds were 112.1 m and 151.1 m for birds and mammals, respectively (Fig. 4).
We found evidence of a positive correlation between increasing body mass of flighted birds (
0.233 SE 0.052; p < 0.001) and effect distance threshold (Fig. 6). We did not find the same
relationship between mammal body mass (
̂ = 0.138 SE 0.102; p = 0.192) and effect distance
threshold (Fig. 5).
Motorized recreation had the highest median threshold distance for birds (111.5 m)
whereas multi-use nonmotorized had the highest median value for mammals (100 m) (Fig. 6).
Hiking-only recreation had the lowest median threshold distance for both birds (45 m) and
mammals (40 m). However, there was substantial overlap of the distribution of values amongst
all recreation types and single-factor ANOVA found no significant difference among recreation
types for birds (F = 0.066, p < 0.936) or mammals (F = 0.760, p < 0.480).
There are numerous gaps in the scientific literature regarding quantitative thresholds of
recreation effects on wildlife. While the publication rate on the recreation effects on wildlife has
been increasing (Larson et al., 2016), there is still a need for science-based recommendations for
management of recreation that present thresholds of disturbance. Further, certain taxonomic
groups, including amphibian, reptile, and invertebrate communities, are substantially
underrepresented in this body of research. In this review, invertebrates were included in two
articles, and amphibians and reptiles were included in only one article each. While there are a
handful of papers that have focused on reptile and amphibian behavior (Moore and Seigel 2006,
Bowen and Janzen 2008, Selman et al. 2013) we only found one paper each that presented
evidence for a threshold to human disturbance on these taxa (Rodríguez-Prieto and Fernández-
Juricic 2005, Pittfield and Burger 2017). Thus, our review was not able to create species or
recreation specific recommendations given in part to the enormous number of species versus
recreation type and response measurements combinations.
Research that identified effect thresholds were heavily skewed towards studies that
measured the distance from which there was a behavioral response from wildlife. Few studies in
recreation ecology were able to identify a physiological or reproductive response threshold or
identify a threshold of visitation numbers or density of human infrastructure. Previous work has
shown that even low human presence can impact wildlife habitat use (Cornelius et al. 2001,
Spaul and Heath 2016, Patten and Burger 2018); however, isolating and interpreting the impacts
of visitor numbers or infrastructure density is arguably more difficult than the physical distance
to humans or trails, which could explain the sparse examples of density impacts in our findings.
Further, short-term behavioral responses to human disturbance can be difficult to link directly to
population consequences (Gill et al. 2001). With the increasing visitation pressure on the world’s
protected areas (Schulze et al 2018), there is a great opportunity and need to focus on identifying
physiological or reproductive effect thresholds of recreation and to measure when visitor
numbers begin to deleteriously impact wildlife.
We found that the median threshold distance for birds and mammals across different
recreation activities ranged from 40 to 111.5 meters, but that the values were not significantly
different among groups of recreation activities (Fig. 5). Though not statistically significant, the
hiking-only recreation group for both mammals and birds had median threshold distance
approximately half the magnitude of the nonmotorized multiple-use or motorized recreation.
This points to the magnitude of influence even nonmotorized recreation can have on the
disturbance of wildlife. Large buffer zones around human activities should always be considered
during the planning and maintenance of parks and protected areas. Efficient trail systems with
significant gaps of at minimum 250 meters between any two trails provide some undisturbed
areas for most wildlife species. The suppression and restoration of social trails maintains these
buffer zones between trails, one of several conservation benefits of reducing these unplanned
features. However, even intact buffers between trails do not ensure all species will have areas
free of human disturbance.
We found a positive correlation between flighted bird body mass and effect distance
threshold but no relationship between mammal body mass and effect distance threshold. Flight
initiation distance, the predominate response measure in our review (Table 1), is shown to be
significantly correlated with bird body mass (Piratelli et al. 2015). Similarly, Blumstein et al.
(2005) found a significant relationship between body mass and alert distance from a sample of
150 species, suggesting that bird body mass could be a good predictor for conservation decision-
making. However, this suggestion could be tempered by Larson et al. (2019) who found that
small bird abundance more so than large bird abundance was negatively affected by high
recreation levels. This indicates the importance of taking multiple response measures into
account when making conservation policy and guidelines.
The relationship between mammal body mass and human disturbance distance appears
less clear than for birds. While there is evidence that smaller sized mammals are more tolerant of
human disturbance and the proximity to human settlements (Battisti et al. 2019, Lhoest et al.
2020), these studies incorporate human disturbances beyond non-consumptive recreation. Larson
et al. (2019) did find a similar lack of relationship between mammal body size and recreation
effects on abundance, rather than effect distance. Also, what influence human habituation may
play in altering this relationship could not be quantified, though some studies in our analysis did
state the likelihood of wildlife individuals habituated to human presence (Lott and McCoy 1995,
Klailova et al. 2010). Ultimately, threshold data was much sparser for mammals than birds
making it difficult to draw any strong inferences from these results. .
There were few examples of recreation infrastructure thresholds, beyond those describing
distance to trail. Despite the small sample size, the findings were consistent: infrastructure even
at low levels can be a contributing factor to altering the habitat use of birds and mammals
(Braunisch et al. 2011, Harris et al. 2014, Richard and Côté 2016). At a regional scale, recreation
infrastructure can also further exacerbate underlying human-wildlife conflicts (Ménard et al.
2014) and fragment habitats (Whittington et al. 2005). Better understanding of how the density
and effect distance of buildings and trails influences the behavior and survival of wildlife species
is paramount for the creation of informed regulatory guidelines.
The detection of threshold effects, if present, can be constrained by the spatiotemporal
extent and overall design of a study. In addition, the effect threshold of human presence or
infrastructure may be outside the boundaries of the study area or may be difficult to disentangle
from correlated effects of other variables. Future researchers should consider how their
experimental design could isolate recreation activities and species to support the detection of
specific quantitative thresholds. Rodríguez-Prieto and Fernández-Juricic (2005) provide a
valuable example demonstrating the quantitative threshold of the effect of recreation activity on
the Iberian frog (Rana iberica Boulenger, 1879). Their study design incorporated systematic
exposure of the species of interest to human disturbance, which provided direct and measurable
flight initiation distances of individual animals from humans. Although this study system is
likely easier to control and observe than studies of larger bodied species, it is an important
example of implementing a study design to quantify a threshold effect of recreation disturbance
and how to effectively represent these results.
There remains a need to understand when and where recreation activities are affecting
species negatively or positively (Larson et al. 2016). However, to inform future designation and
management of recreation use, researchers must go beyond simple hypothesis testing. Studies
that focused on categorical variables (e.g., low versus high visitation rates, hikers versus
mountain bikers) to examine the potential effects of a recreation treatment rarely identified the
threshold at which the recreation activity may begin to cease to affect an animal species. Asking
when and to what extent a species is being disturbed and measuring beyond the spatial or
temporal magnitude where the disturbance is expected to begin or end allows researchers to
identify important thresholds of recreation disturbance. Researchers should not provide a
quantitative recommendation that is not justified by their results, but where possible researchers
should provide resource managers with clear guidance and conservative estimates to support
science-based management decisions. Ultimately, these thresholds allow for more informed and
effective management decisions and a higher probability of successful conservation of species.
We would like to thank Tony Nelson, the Sonoma Land Trust, and the Gordon and Betty Moore
Foundation for their support of this project. We would also like to thank Jessica Sushinsky
Stacey Lischka, Sasha Keyel and Miguel Jimenez for discussion and support. Two anonymous
reviewers provided very useful feedback and greatly improved the article.
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List of Figures
Figure 1. Recreation effect threshold articles by bird and mammal orders. (a) Bird and (b)
mammal orders studied in papers that identified an effect threshold. Several articles contained
more than one order thus the total number of articles sums to more than all the threshold effects
Figure 2. Descriptive statistics of recreation threshold articles. Summary of (a) ecosystem
types, (b) recreation activities, and (c) disturbance variables of articles that identified an effect
threshold. Several papers studied more than one ecosystem, recreation activity, or disturbance
variable, therefore, percentages in one plot sum to greater than 100%. Aquatic recreation only
included those water-based activities that effected wildlife on land. Disturbance variable distance
to trail included all forms of recreation (e.g., motorized, non-motorized, and dogs allowed and
not allowed) and infrastructure referred to distance or density of human built strucutres.
Table 1. Wildlife response measurements across threshold articles. Measurement variables
varied among the articles that identified an effect threshold. The majority of articles focused on
the behvioral response of wildlife disturbed by recreation. Cumulatively, less than 6% of articles
found an effect threshold of either a physiological, reproductive or habitat measurement.
% of Articles
Density per site
Number of birds observed
Number of herds sighted daily
Changes in activity budget of group
Distance at which animal changed direction
Flight initiation distance
Max alert distance
Number feeding or standing
Number of moves
Probability of active response
Probability of disturbance
Probability of flight
Proportion of birds disturbed
Time spent alert
Time spent feeding/day
Avoidance of human areas
Monthly juvenile survival
Figure 3. Distance of effect thresholds of birds and mammals. Minimum effect distance
thresholds across all mammal (n=24) and bird (n=53) species studied for the impacts of
recreation on wildlife. Thresholds included observed distances of direct human disturbance to
wildlife and disturbance from recreation infrastructure. Outliers for mammals are effect distances
for larger ungulates. Outliers for birds are effect distances for raptors, including hawks and
eagles. Boxplots indicate median and 25th and 75th percentiles. Whiskers extend to data 1.5
times the interquartile range.
Figure 4. Distance of effect thresholds across bird orders. Minimum threshold distances of
birds by taxonomic group. Black dots indicate individual data points. Shorebird studies
represented the majority of threshold data points. Owls, penguins, and upland birds were
especially underrepresented. The only owl threshold distance (x = 55 m) is not presented in this
figure. Boxplots indicate median and 25th and 75th percentiles. Whiskers extend to data 1.5
times the interquartile range.
Figure 5. Wildlife body mass as a predictor of effect threshold distance. Regression analysis
of body mass as a predictor for a taxa’s threshold of effect distance for (a) birds and (b)
mammals. Bird body mass was a significantly positive predictor of the species threshold of effect
distance. We did not find a relationship between mammal body mass and effect threshold,
however, the sample size is low making any inference cautionary.
Figure 6. Effect thresholds across groups of recreation activities and taxa. Hiking-only
recreation had the lowest median effect threshold distance for birds and mammals. Motorized
and multi-use nonmotorized had substantial overlap in their distribution of values, though we did
not find a significant different between within taxa groups. One outlier of 1000 m is not shown
for mammal motorized. Black dots indicate individual data points. Boxplots indicate median and
25th and 75th percentiles. Whiskers extend to data 1.5 times the interquartile range.
List of supplementary files
Table S1. Articles of recreation effect thresholds results and metadata. All articles within
our database that identified a quantitative threshold of where human disturbance on wildlife via
non-consumptive recreation began or ended. Articles are listed species specifically or by the
lowest taxonomic group where the threshold was identified.