Niche expansion after competitor extinction? A comparative assessment of habitat generalists and specialists in the tree floras of south‐eastern North America and south‐eastern Europe

Aim The aim of this study was to test R.H. MacArthur’s hypothesis that realized niche breadth is constrained by species pool size – the greater the number of species in a region, the more competition restricts the distribution of each species with respect to environmental tolerances and habitat characteristics. Location The northern Balkan region in south‐eastern Europe (Illyrian Floristic Province) and the southern Appalachian region of the USA. Methods We compared co‐occurrence‐based distributions of habitat specialization of tree species in two geographic regions that are ecologically similar but differ in species pool size. We applied two methods. First, we used a rank‐ordering of species along a gradient of estimated niche breadth that is based solely on species co‐occurrence information derived from vegetation databases from each region. To compare niche‐breadth distributions of different datasets we developed a procedure that standardizes expected values of species co‐occurrences independently of the size of the species pool. Second, we calculated species turnover along an elevational gradient for both regions, estimated as the rate of decay of compositional similarity with elevation distance. Results Despite a twofold larger species pool, and in contrast to our hypothesis, there was no greater specialization trend in the tree species of the southern Appalachian region, regardless of phylogenetic subgroupings or whether rare species were included. After correcting for differences in species pools, the similarity decay with elevation distance was marginally stronger in the southern Appalachian region. Main conclusions MacArthur’s hypothesis was not supported by our analysis. While the compositional distance decay with elevation revealed only a slight trend towards narrower realized niches in the tree flora of the southern Appalachian region, the co‐occurrence approach suggested the opposite. Our results indicate that species distributions are largely constrained by environmental tolerances, and that biotic pressure in the form of competition from ecologically similar species plays a relatively minor role in the ability of species to establish mature individuals in different habitat types.     

Does the disturbance hypothesis explain the biomass increase in basin‐wide Amazon forest plot data?

Positive aboveground biomass trends have been reported from old-growth forests across the Amazon basin and hypothesized to reflect a large-scale response to exterior forcing. The result could, however, be an artefact due to a sampling bias induced by the nature of forest growth dynamics. Here, we characterize statistically the disturbance process in Amazon old-growth forests as recorded in 135 forest plots of the RAINFOR network up to 2006, and other independent research programmes, and explore the consequences of sampling artefacts using a data-based stochastic simulator. Over the observed range of annual aboveground biomass losses, standard statistical tests show that the distribution of biomass losses through mortality follow an exponential or near-identical Weibull probability distribution and not a power law as assumed by others. The simulator was parameterized using both an exponential disturbance probability distribution as well as a mixed exponential–power law distribution to account for potential large-scale blowdown events. In both cases, sampling biases turn out to be too small to explain the gains detected by the extended RAINFOR plot network. This result lends further support to the notion that currently observed biomass gains for intact forests across the Amazon are actually occurring over large scales at the current time, presumably as a response to climate change.     

Dominant climate influences on North American bird distributions

Aim Geographic distributions of species are constrained by several factors acting at different scales, with climate assumed to be a major determinant at broad extents. Recent studies, however, have challenged this statement and indicated that climate may not dominate among the factors governing geographic distributions of species. Here, we argue that these results are misleading due to the lack of consideration of the geographic area that has been accessible to the species. Location North America. Methods We generated null distributions for 75 North American endemic and 19 non‐endemic bird species. For each species, climatic envelopes of observed and null distributions were modelled using neural networks and generalized linear models, and seven climatic predictors. Values of the area under the receiver–operating characteristic curve (AUC) based on models of observed distributions were compared with corresponding AUC values for the null distributions. Results More than 82% of the endemic species showed AUC higher for the observed than for the null distributions, while 63% of the non‐endemic species showed such a pattern. Main conclusions We demonstrate a dominant climatic signal in shaping North American bird distributions. Our results attest to the importance of climate in determining species distributions and support the use of climate‐envelope models for estimating potential distributional areas at the appropriate spatial scales.     

Current measures for distance decay in similarity of species composition are influenced by study extent and grain size

Aim The relationship between geographic distance and similarity in species composition is regularly used as a measure of species turnover and beta diversity. Distance–decay analyses are applied, cited and compared despite the variable extent, and different grain sizes of records (e.g. plots, islands, states) are regularly used within such analyses. Currently, differences among distance–decay relationships that cover different grain sizes and extents are attributed to ecological processes that are suspected to operate differently over varying extents and grain sizes. We assess whether the implicit assumption that the distance–decay relation is independent of grain size and study extent is valid, or whether sampling design could be the underlying cause for observed differences. Location An artificial one‐dimensional ‘landscape’. Methods The distance–decay relationship was quantified in simulated communities. Grain and study extent were varied systematically. In each sampled data set the linear relation of Simpson and Sørensen similarity to geographic distance (on both log‐transformed and original scales) between 100 even‐sized equidistant plots was assessed using linear regression and generalized linear regression with a log‐link function. Regressions were applied either including or removing zero similarities from the data. Results Both the slope (measuring turnover) and the goodness of fit measure r² (quantifying the influence of space on species composition) of the distance–decay relationship were strongly influenced by grain and study extent. Approaches that are able to cope with zero similarity values of large distance comparisons were less dependent on grain and extent. Main conclusions Reported differences between landscapes detected by current distance–decay measures cannot be explicitly traced back to ecological scale‐specific processes. Instead, they can largely be attributed to sampling design and are highly sensitive to grain size and study extent. More appropriate approaches for the study of distance–decay and the understanding of scale‐specific processes are required.     

Adding energy gradients and long‐distance dispersal to a neutral model improves predictions of Madagascan bird diversity

Macroecological patterns are likely the result of both stochastically neutral mechanisms and deterministic differences between species. In Madagascar, the simplest stochastically neutral hypothesis – the mid‐domain effects (MDE) hypothesis – has already been rejected. However, rejecting the MDE hypothesis does not necessarily refute the existence of all other neutral mechanisms. Here, we test whether adding complexity to a basic neutral model improves predictions of biodiversity patterns. The simplest MDE model assumes that: (1) species' ranges are continuous and unfragmented, (2) are randomly located throughout the landscape, and (3) can be stacked independently and indefinitely. We designed a simulation based on neutral theory that allowed us to weaken each of these assumptions incrementally by adjusting the habitat capacity as well as the likelihood of short‐ and long‐distance dispersal. Simulated outputs were compared to four empirical patterns of bird diversity: the frequency distributions of species richness and range size, the within‐island latitudinal diversity gradient, and the distance‐decay of species compositional similarity. Neutral models emulated empirical diversity patterns for Madagascan birds accurately. The frequency distribution of range size, latitudinal diversity gradient, and the distance‐decay of species compositional similarity could be attributed to stochastic long‐distance migration events and zero‐sum population dynamics. However, heterogenous environmental gradients improved predictions of the frequency distribution of species richness. Patterns of bird diversity in Madagascar can broadly be attributed to stochastic long‐distance migration events and zero‐sum population dynamics. This implies that rejecting simple hypotheses, such as MDE, does not serve as evidence against stochastic processes in general. However, environmental gradients were necessary to explain patterns of species richness and deterministic differences between species are probably important for explaining the distributions of narrow‐range and endemic species.     

Population fluctuations,power laws and mixtures of lognormal distributions

A number of investigators have invoked a cascading local interaction model to account for power‐law‐distributed fluctuations in ecological variables. Invoking such a model requires that species be tightly coupled, and that local interactions among species influence ecosystem dynamics over a broad range of scales. Here we reanalyse bird population data used by Keitt & Stanley (1998, Dynamics of North American breeding bird populations. Nature, 393, 257–260) to support a cascading local interaction model. We find that the power law they report can be attributed to mixing of lognormal distributions. More tentatively, we propose that mixing of distributions accounts for other empirical power laws reported in the ecological literature.     

Identifying type I excitability using dynamics of stochastic neural firing patterns

The stochastic firing patterns are simulated near saddle-node bifurcation on an invariant cycle corresponding to type I excitability in stochastic Morris–Lecar model. In absence of external periodic signal, the stochastic firing manifests continuous distribution in ISI histogram (ISIH), whose amplitude at first increases sharply and then decreases exponentially. In presence of the external periodic signal, stochastic firing patterns appear as two cases of integer multiple firing with multiple discrete peaks in ISIH. One manifests perfect exponential decay in all peaks and the other imperfect exponential decay except a lower first peak. These stochastic firing patterns simulated with or without external periodic signal can be demonstrated in the experiments on rat hippocampal CA1 pyramidal neurons. The exponential decay laws in the multiple peaks are also acquired using probability analysis method. The perfect decay law is determined by the independent characteristic within the firing while the imperfect decay law is from the inhibitory effect. In addition, the stochastic firing patterns corresponding to type I excitability are compared to those of type II excitability. The results not only reveal the dynamics of stochastic firing patterns with or without external signal corresponding to type I excitability, but also provide practical indicators to availably identify type I excitability.     

Species–area and species–sampling effort relationships: disentangling the effects

Species numbers tend to increase with both the area surveyed (species–area relationship, SAR) and the number of samples taken (species–sampling effort relationship, SSER). These two relationships differ in their nature and underlying mechanisms but are not clearly distinguished in field studies. To discriminate the effects of area (spatial extent) and sampling effort (SE) on species richness, several models explicitly involving both variables were proposed and tested against 13 datasets from marine micro‐, meio‐ and macrobenthos. A combination of power SSER and piecewise power SAR terms was found to have the best fit. The effects of area and SE were both significant, but the former one was noticeably weaker. The SSERs were roughly linear in log‐log space, whereas the SARs demonstrated scale‐dependent behavior with a noticeable threshold (slope breakpoint). Species richness was almost area‐independent below this threshold (the “small area effect”, SAE) but followed typical power‐law SAR beyond the threshold. This effect was similar to the “small island effect” but occurred for arbitrarily delineated areas within continuous habitats. Parameters of the SAR curves depended on organism size. The upper limit of the SAE increased from microorganisms to meiofauna to macrofauna. Also, SAR curves for unicellular groups had significantly lower slopes. SAE is supposed to indicate a spatial range of statistical homogeneity in species composition. Its upper limit corresponds to the characteristic size of a local community (a single habitat occupied by a common species pool). Interpretations of SAR and SSER parameters in terms of α‐ and β‐diversity are proposed. Both SAR and SSER slopes obtained from univariate regressions are overestimated. This upward bias depends on sampling design, decreasing for SAR but increasing for SSER with more unequally spaced samples. Both spatial extent and sampling effort should be taken into account to disentangle properly their effects on diversity.     

Non-random patterns in the Yellowstone ecosystem: inferences from mammalian body size, order and biogeographical affinity

Aim Our aim was to investigate how the environment, species characteristics and historical factors at the subcontinental scale affect patterns of diversity. We used the assembly of the Yellowstone biota over the past 10,000 years as a natural experiment for investigating the processes that generate a modern non‐volant mammal species pool. Location The data represent species from throughout North America with special attention to the non‐volant mammals of Yellowstone National Park, USA. Methods We used digitized range maps to determine biogeographical affinity for all non‐volant mammals in the Rocky Mountains, Deserts and Great Plains biogeographical regions of North America. This biogeographical affinity, along with taxonomic order and body size class, was used to test whether non‐random patterns exist in the assemblage of Yellowstone non‐volant mammals. These characteristics were also used to investigate the strength of non‐random processes, such as habitat or taxon filtering, on particular groups of species or individual species. Results Our results indicated that the Yellowstone fauna is composed of a non‐random subset of mammals from specific body size classes and with particular biogeographical affinities. Analyses by taxonomic order found significantly more Carnivora from the Rocky Mountains region and significantly fewer Rodentia from the Deserts region than expected from random assembly. Analyses using body size classes revealed deviations from expectations, including several significant differences between the frequency distribution of regional body sizes and the distribution of those species found within Yellowstone. Main conclusions Our novel approach explores processes affecting species pool assembly in the Yellowstone region and elsewhere, and particularly identifies unique properties of species that may contribute to non‐random assembly. Focusing on the mechanisms generating diversity, not just current diversity patterns, will assist the design of conservation strategies given future environmental change scenarios.     

Distance decay in an old‐growth neotropical forest

Abstract. Questions: Does distance decay exist in an old‐growth neotropical forest? Is this distance decay stronger than expected due to environmental heterogeneity alone? At what spatial scales are distance decay manifested? Location: La Selva Biological Station, Costa Rica, Central America. Methods: An index of distance decay is applied appropriate for small quadrats (the probability of encountering a conspecific tree) to a grid of 1170 0.01‐ha plots. A null model is provided that accounts for environmental heterogeneity. Results: Significant, but weak, distance decay is found. After correcting for known patterns of environmental heterogeneity, the distance decay almost disappears, except for fine spatial scales. Conclusions: These results are inconsistent with models that predict distance decay at all spatial scales. However, biological processes leading to distance decay may be more relevant and detectable at scales broader than this study. Research utilizing objectively‐located samples over much broader scales is necessary to evaluate the generality and magnitude of distance decay.     

Linking biodiversity patterns by autocorrelated random sampling

Biodiversity macroecology deals with the commonly measured variables of abundance, distribution, occupancy, and range size across two scales: the local (or α) and regional (γ). There are ca. 15 patterns consisting of the frequency distributions of the variables, variables as a function of area or sample size, and interrelationships between variables that appear to be very general if not close to universal. A number of links can be drawn between these patterns. In particular, I show that local communities can be seen as random samples of the regional pool, but only as a special form of sampling that is autocorrelated due to the spatial clumping of individuals within a species. I describe two distinct sets of mathematical machinery that can start with the regional species abundance distribution and then predict local species richness, local species abundance distributions, and β-diversity (in the form of species area relationships or decay of similarity with distance). I conclude by examining some of the implications of the fact that biodiversity patterns are linked by autocorrelated sampling.     

Power-law species–area relationships and self-similar species distributions within finite areas

The species–area relationship (SAR) is often expressed as a power law, which indicates scale invariance. It has been claimed that the scale invariance – or self‐similarity at the community level – is not compatible with the self‐similarity at the level of spatial distribution of individual species, because the power law would only emerge if distributions for all species had identical fractal dimensions (FD). Here we show that even if species differ in their FD, the resulting SAR is approximately linear on a log–log scale because observed spatial distributions are inevitably spatially restricted – a phenomenon we term the ‘finite‐area effect’. Using distribution atlases, we demonstrate that the apparent power law of SARs for central European birds is attributable to this finite‐area effect affecting species that indeed reveal self‐similar distributions. We discuss implications of this mechanism producing the SAR.     

Two dominant forms of multisite similarity decline – Their origins and interpretation

The number of species shared by two or more sites is a fundamental measure of spatial variation in species composition. As more sites are included in the comparison of species composition, the average number of species shared across them declines, with a rate increasingly dependent on only the most widespread species. In over 80% of empirical communities, models of decline in shared species across multiple sites (multisite similarity decline) follow one of two distinct forms. An exponential form is assumed to reflect stochastic assembly and a power law form niche‐based sorting, yet these explanations are largely untested, and little is known of how the two forms arise in nature. Using simulations, we first show that the distribution of the most widespread species largely differentiates the two forms, with the power law increasingly favored where such species occupy more than ~75% of sites. We reasoned the less cosmopolitan distribution of widespread species within exponential communities would manifest as differences in community biodiversity properties, specifically more aggregated within‐species distributions, less even relative abundance distributions, and weaker between‐species spatial associations. We tested and largely confirmed these relationships using 80 empirical datasets, suggesting that the form of multisite similarity decline offers a basis to predict how landscape‐scale loss or gain of widespread species is reflected in different local‐scale community structures. Such understanding could, for example, be used to predict changes in local‐scale competitive interactions following shifts in widespread species'' distributions. We propose multiple explanations for the origin of exponential decline, including high among‐site abiotic variation, sampling of highly specialized (narrow niche width) taxa, and strong dispersal limitation. We recommend these are evaluated as alternative hypotheses to stochastic assembly.     

The spatial scaling of saprotrophic fungal beta diversity in decomposing leaves

Assembly of fungal communities remains poorly understood in part because of the daunting range of spatial scales that may be involved in this process. Here, we use individual leaves as a natural sampling unit, comprising spatially distinct habitat and/or resource patches with unique histories and suites of resources. Spatial patterns in fungal beta diversity were tested for consistency with the metacommunity paradigms of species sorting and neutral dynamics. Thirty senesced leaves were collected from the forest floor (O horizon) in replicate upland forest, riparian forest and vernal pool habitats. We quantified spatial distance between leaves, and fungal community composition was assayed by terminal restriction fragment length polymorphism. Significant distance‐decay relationships were detected at all but one upland site. This is the first study where changes in fungal community composition were quantified across discrete adjacent habitat patches, providing evidence that fungal distance decay is operational at a scale of centimetres. Although leaves of differing lignin contents were sampled from each site, leaf type was not consistently important in explaining variation in fungal community composition. However, depth of a leaf within the forest floor significantly influenced community composition at five of six sites. Environmental heterogeneity associated with depth could include moisture gradients, relative influence of soil or spore colonization, and impact of forest floor biotic community (i.e. collembola and earthworms). Because the influence of spatial distance and depth on fungal community composition could not be disentangled, both species‐sorting and neutral processes may be embedded within the distance‐decay relationships that we found.     

Local-regional relationships and the geographical distribution of species

Aim Local‐regional (LR) species diversity plots were conceived to assess the contribution of regional and local processes in shaping the patterns of biological diversity, but have been used also to explore the scaling of diversity in terms of its alpha, beta, and gamma components. Here we explore the idea that patterns in the geographical ranges of species over a continent can determine the shape of small region to large region (SRLR) plots, which are equivalent to LR plots when comparing the diversity of sites at two regional scales. Location To test that idea, we analysed the diversity patterns at two regional scales for the mammals of North America, defined as the mainland from Alaska and Canada to Panama. Method We developed a theoretical model relating average range size of species over a large‐scale region with its average regional point species diversity (RPD). Then, we generated a null model of expected SRLR plots based on theoretical predictions. Species diversities at two scales were modelled using linear and saturation functions for Type I and Type II SRLR relationships, respectively. We applied the models to the case of North American mammals by examining the regional diversity and the RPD for 21 large‐scale quadrats (with area equal to 160,000 km²), arranged along a latitudinal gradient. Results Our model showed that continental and large‐scale regional patterns of distribution of species can generate both types of SRLR relationship, and that these patterns can be reflected in LR plots without invoking any kind of local processes. We found that North American nonvolant mammals follow a Type I SRLR relationship, whereas bats follow a Type II pattern. This difference was linked to patterns in which species of the two mammalian groups distribute in geographical space. Conclusion Traditional LR plots and the new SRLR plots are useful tools in exploring the scaling of species diversity and in showing the relationship between distribution and diversity. Their usefulness in comparing the relative role of local and regional processes is, however, very limited.     

Modeling bond correlations in denatured proteins and polypeptides

Bond‐orientational correlations for finite‐length homopolypeptides and a selected group of denatured proteins are obtained by numerical simulations using a polypeptide model with a potential of mean force. These correlations characterize the stiffness of the polypeptide backbone and are generally described by either an exponential or a power‐law decay in the asymptotic limit. However, for finite length polypeptides and unfolded proteins the correlations significantly deviate from either single exponential or power‐law behavior. A heuristic model is developed to analyze the correlations of homopolypeptides, which depends on the chain length and the side‐chain properties. The model contains power‐law and multi‐exponential terms, the latter which could be interpreted as local persistence lengths. In the asymptotic limit, the model reduces to the expected power‐law behavior. Simulations of denatured proteins show that the power‐law behavior of the correlations is significantly suppressed and only the multi‐exponential term is needed to model the correlations. In addition, average persistence lengths (ranging from 2.0 to 2.5 nm) are obtained from the correlations by fitting single exponentials and shown to be in general agreement with experiments, which also assume single exponential decay. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 312–323, 2016.     

Process‐based functions for seed retention on animals: a test of improved descriptions of dispersal using multiple data sets

Studies of external seed transport on animals usually assume that the probability of detachment is constant, so that seed retention should show a simple exponential relationship with time. This assumption has not been tested explicitly, and may lead to inaccurate representation of long distance seed dispersal by animals. We test the assumption by comparing the fit to empirical data of simple, two‐parameter functions. Fifty‐two data sets were obtained from five published studies, describing seed retention of 32 plant species on sheep, cattle, deer, goats and mice. Model selection suggested a simple exponential function was adequate for data sets in which seed retention was followed for short periods ( <48 h). The data gathered over longer periods (49–219 days) were best described by the power exponential function, a form of the stretched exponential which allows a changing dropping rate. In these cases the power exponential showed that seed dropping rate decreased with time, suggesting that seeds vary in attachment, with some seeds becoming deeply buried or wound up in the animal's coat. Comparison of fitted parameters across all the data sets also confirmed that seeds with adhesive structures have lower dropping rates than those without. We conclude that the seed dropping rate often changes with time during external transport on animals and that the power exponential is an effective function to describe this change. We advise that, to analyse seed dropping rates adequately, retention should be measured over reasonable time periods – until most seeds are dropped – and both the simple and power exponential functions should be fitted to the resulting data. To increase its utility, we provide functions describing the seed dropping rate and the dispersal kernel resulting from the power exponential relationship.     

The effects of forest conversion to oil palm on ground‐foraging ant communities depend on beta diversity and sampling grain

Beta diversity – the variation in species composition among spatially discrete communities – and sampling grain – the size of samples being compared – may alter our perspectives of diversity within and between landscapes before and after agricultural conversion. Such assumptions are usually based on point comparisons, which do not accurately capture actual differences in total diversity. Beta diversity is often not rigorously examined. We investigated the beta diversity of ground‐foraging ant communities in fragmented oil palm and forest landscapes in Sabah, Malaysia, using diversity metrics transformed from Hill number equivalents to remove dependences on alpha diversity. We compared the beta diversities of oil palm and forest, across three hierarchically nested sampling grains. We found that oil palm and forest communities had a greater percentage of total shared species when larger samples were compared. Across all grains and disregarding relative abundances, there was higher beta diversity of all species among forest communities. However, there were higher beta diversities of common and very abundant (dominant) species in oil palm as compared to forests. Differences in beta diversities between oil palm and forest were greatest at the largest sampling grain. Larger sampling grains in oil palm may generate bigger species pools, increasing the probability of shared species with forest samples. Greater beta diversity of all species in forest may be attributed to rare species. Oil palm communities may be more heterogeneous in common and dominant species because of variable community assembly events. Rare and also common species are better captured at larger grains, boosting differences in beta diversity between larger samples of forest and oil palm communities. Although agricultural landscapes support a lower total diversity than natural forests, diversity especially of abundant species is still important for maintaining ecosystem stability. Diversity in agricultural landscapes may be greater than expected when beta diversity is accounted for at large spatial scales.     

Spatial autocorrelation analysis allows disentangling the balance between neutral and niche processes in metacommunities

One of the most popular approaches for investigating the roles of niche and neutral processes driving metacommunity patterns consists of partitioning variation in species data into environmental and spatial components. The logic is that the distance decay of similarity in communities is expected under neutral models. However, because environmental variation is often spatially structured, the decay could also be attributed to environmental factors that are missing from the analysis. Here, we use a spatial autocorrelation analysis protocol, previously developed to detect isolation‐by‐distance in allele frequencies, to evaluate patterns of species abundances under neutral dynamics. We show that this protocol can be linked with variation partitioning analyses. Moreover, in an attempt to test the neutral model, we derive three predictions to be applied both to original species abundances and to abundances predicted by a pure spatial model species abundances will be uncorrelated; Moran's I correlograms will reveal similar short‐distance autocorrelation patterns; an increasing degree of non‐neutrality will tend to generate patterns of correlation among abundances within groups of species with similar correlograms (i.e. within species with neutral and non‐neutral dynamics). We illustrate our protocol by analyzing spatial patterns in abundance of 28 terrestrially breeding anuran species from Central Amazonia. We recommend that researchers should investigate spatial autocorrelation patterns of abundances predicted by pure spatial models to identify similar patterns of spatial autocorrelation at short distances and lack of correlation between species abundances. Therefore, the hypothesis that spatial patterns in abundances are primarily due to pure neutral dynamics (rather than to missing spatiallystructured environmental factors) can be confirmed after taking environmental variables into account.     

Detection probability of Golden-winged Warblers during point counts with and without playback recordings

ABSTRACT Use of point‐count data to estimate population sizes of North American landbirds may be challenged by limitations on detection probability of particular species, thereby requiring correction factors to ensure accurate estimates. We estimated detection probability of Golden‐winged Warblers (Vermivora chrysoptera) during 3‐min point‐count surveys conducted both with and without use of playback recordings in a mixed shrubland‐forest habitat (clearcut area) and a 60‐m wide electric transmission line right‐of‐way (ROW) in central Pennsylvania from 20 May to 17 June 2002–2003. In addition, we assessed the value of playback with respect to response rates of warblers and distance within which warblers approached the observer. Without playback, detection probability was approximately 23% in the clearcut area and 61% in the ROW. Use of playback resulted in 7% and 19% net increases in probability at the clearcut area and the ROW, respectively; proportional increase was approximately 30% for both habitats. Warblers responded to playback 68% of the time, but response rate was greater within 100 m (72%) than beyond (53%). Most responses (85%) included approach of the warbler toward the observer, and most individuals approached within 10 m. We conclude that 3‐min point counts with playback do not yield detection probabilities sufficient to estimate population size of Golden‐winged Warblers without use of correction factors. Furthermore, detection probability in mixed shrubland‐forest habitats can be much lower than in linear habitats such as utility ROWs. Efforts to estimate population size of Golden‐winged Warblers from data of the North American Breeding Bird Survey should recognize that habitat structure has much influence on detection probability as it relates to distance at which an observer can hear (or see) warblers. Accordingly, we recommend that such efforts incorporate a maximum detection distance of 100–150 m in mixed shrubland‐forest habitats.