Current Landscape Ecology Reports

, Volume 3, Issue 1, pp 12–22 | Cite as

The Scale-Dependent Role of Biological Traits in Landscape Ecology: A Review

  • Andrés Felipe Suárez-Castro
  • Jeremy S. Simmonds
  • Matthew G. E. Mitchell
  • Martine Maron
  • Jonathan R. Rhodes
Scale-Measurement, Influence, and Integration (A Martin and J Holland, Section Editors)
Part of the following topical collections:
  1. Topical Collection on Scale-Measurement, Influence, and Integration


Purpose of Review

We describe current approaches that evaluate how the influence of species traits on the relationship between environmental variables and ecological responses varies among scales (i.e. the scale-dependent role of traits). We quantify which traits and ecological responses have been assessed, and discuss the main challenges associated with quantifying the scale-dependent effect of traits.

Recent Findings

We identify three main approaches used to evaluate the scale-dependent role of traits, based on whether 1) traits are used as predictors or responses, 2) intraspecific variation in single traits is considered, or 3) trait diversity indices are used. Our review identifies several gaps that include the following: 1) evidence of the scale-dependent role of traits is biased towards studies of plants; 2) we lack evidence of whether the traits of interacting species groups are consistently related across spatial scales; and 3) interactions between species traits and landscape structure are usually ignored.


The explicit inclusion of landscape structure effects in trait-based approaches at multiple scales will benefit the integration of approaches from community ecology and landscape ecology. This is important for describing the mechanisms that operate simultaneously across scales and for predicting the impact of landscape change on a broad range of ecological responses, including species diversity and interspecific interactions.


Environmental change Functional diversity Landscape structure Multi-scale 


Conducting research across multiple spatial scales is important for evaluating community and species responses to landscape change [1, 2]. Species interact with the landscape at different scales; thus, understanding how the influence of environmental variables on ecological responses changes across scales remains a key challenge [1, 3, 4]. Importantly, we can use species’ traits to explain mechanistic links between environmental variables and ecological responses [5, 6, 7, 8], as patterns in trait variation within and among species can allow for inferences about how spatial processes affect biodiversity across scales [9, 10, 11, 12]. There is currently some understanding about how traits influence the scale at which species respond most strongly to particular environmental variables (i.e. the scale of effect) [1, 3]. Yet, a different, but equally important, perspective focuses on the need to understand how the effect of different traits varies with the scale at which environmental variables and/or species’ responses are measured (i.e. the scale-dependent effect of traits).

The effect of traits on ecological responses depends on the spatial scales of measurement [2, 11, 13]. This is because the way that biotic, abiotic and anthropogenic factors relate to species traits can be quite different when measured at continental, regional or landscape scales compared to small habitat patches or microhabitats [14, 15]. Therefore, identifying how the effects of traits vary with spatial scale should make it possible to better predict how species may respond to specific environmental variables at particular scales. This information is critical for moving towards more general scale-dependent models of species and community distributions and dynamics.

We consider two components of scale [16]: spatial resolution (i.e. grain size) and spatial extent (Fig. 1). Spatial resolution corresponds to the plot size at which ecological responses, species traits and/or environmental variables are measured, whereas spatial extent is the area defining the population or community under consideration. Increasing the resolution helps to detect fine-scale associations between species traits and local environmental heterogeneity, as well as biotic interactions. For example, at fine resolutions, traits related to competitive ability and reproduction can shape interactions among species sharing similar resources [15, 17]. On the other hand, at coarse resolutions, the impacts of spatial patterns such as landscape fragmentation become more evident, and thus the importance of traits associated with dispersal capacity increases [18, 19]. Large spatial extents tend to include a broad range of environmental conditions across gradients; therefore, communities exhibit a wide range of trait values [15, 20]. In contrast, at small spatial extents, groups of species or individuals are defined by a more restricted number of suitable traits that represent adaptations to local conditions [21].
Fig. 1

Spatial scale has two components: 1) extent, the total area that contains the population or assemblage under consideration, and 2) resolution (e.g. the plot area of the sampled community). Broad spatial extents tend to include a broad range of environmental variables (e.g. elevational and climatic gradients), whereas medium and small spatial extents reflect local habitat and landscape structure variables. Circles represent the plots used to measured ecological responses and/or environmental variables. All the plots (blue + yellow) could be used to discern the relationships between traits, environmental variables and ecological responses at large extents, whereas the yellow plots could help to analyse these relationships at smaller extents. Individual plots can be of different sizes; the size of a plot used in a specific study determines the spatial resolution of that study. Fine resolutions may be more appropriate for detecting the influence of traits related to biotic interactions and local environmental heterogeneity, whereas at coarse resolutions, ecological responses reflect the averaging effect of broad-scale environmental variables

To understand the extent to which previous research has evaluated the scale-dependent effect of species traits, we undertook a systematic review of the literature from the past 5 years. We 1) identified the main approaches that have been used to describe the influence of traits on ecological responses to environmental changes at multiple scales, 2) identified which traits have been assessed for scale-dependent effects, and 3) identified which major environmental variables and ecological responses have been measured and related to traits at the community and population levels. Based on our review, we note that a more refined understanding of how traits drive species responses to environmental variables at different scales, will be of great benefit for understanding the ecological requirements (including optimal landscape structure) of species and ecological communities. We then identify future research challenges to address this. Detailed methods and references for the literature review are provided in Appendix 1.


We were interested in and reviewed studies that 1) measured explanatory environmental variables and/or ecological responses at more than one spatial scale (e.g. resolution, extent or both), 2) quantified species traits as predictors or response variables, and 3) evaluated how the relationships between a particular set of traits, environmental variables and ecological responses change across scales. In this sense, our review does not focus on studies that only evaluate the scale at which environmental variables have their strongest effect on species with different traits (the scale of effect; Fig. 2a), as this approach has received considerable attention and its importance has been discussed in recent reviews [1, 3].
Fig. 2

Approaches where traits are used to explain ecological responses at multiple scales (n = 101). Different landscape sizes show the different scales at which environmental variables are measured. a) Scale of effect: studies aiming to identify which traits affect the scale at which environmental variables have their strongest effect. b) Traits as predictors: the effects of different traits on the relationship between environmental variables and ecological responses are measured at different scales. c) Studies that evaluate how the expression of single traits vary over different spatial scales and how environmental variables mediate such variation. d) The distribution of traits at particular scales is used to explain community assembly processes. In this case, researchers measure the abundance and frequency of trait values across species to infer how environmental variables shape community diversity patterns

We searched (27 March 2017) for all papers published in the last 5 years, using the following search term sequence in Web of Science: TI (Title) = (scale or scale* or multiscale or multi-scale or spatial) and TS (topic) = (trait or trait* or dispersal or size or size* or reproductive or foraging or behaviour) and TS = (scale or scale* or multiscale or multi-scale). To facilitate our search, we reviewed papers from 40 ecological journals most likely to publish papers on ecological responses to landscape change, and discarded all studies that did not include “scale” in the abstract. This produced a sample of 1540 papers (see Appendix 1 for details of search methodology). Most of the results were then eliminated based on the titles or the abstracts if they failed to meet one or more of the three criteria above. In cases where suitability could not be determined based on the abstract, an assessment was made after reading the methods and results sections. This process produced a set of 101 studies, which are listed in Table S2.

Approaches for Evaluating the Effect of Traits in Multi-scale Studies

The approaches that we focus on in this review explicitly account for how the relationship between particular traits, environmental variables and ecological responses changes across scales. This is important if we want to describe the key mechanisms that operate simultaneously at different scales and to predict the impact of environmental variables on a broader range of ecological responses, including species diversity patterns and interspecific interactions (Table 1). We identified three approaches: “species traits as predictors”, “single trait expression across scales” and “trait diversity”. In the “species traits as predictors” approach (Fig. 2b), different traits are used as predictors to identify how they moderate ecological responses to environmental change across scales. Here, the focus is in evaluating how interspecific variation in trait values affects ecological responses at different scales—for example, how the effects of dispersal capacity and competitive ability on species abundance differ among local, landscape and regional scales. In the “single trait expression across scales” and “trait diversity” approaches, traits are used mainly as response variables to identify how changes in intraspecific trait variation (Fig. 2c) or trait diversity (Fig. 2d) are related to particular environmental conditions at each spatial scale. In these cases, traits help to infer what set of environmental conditions has a stronger influence on species and communities at each scale.
Table 1

Main approaches used to evaluate the role of traits in multi-scale studies


Main research question

Examples of ecological responses of interest

Scale of effect

How do traits determine the scale at which environmental variables most strongly influence an ecological response?

Species presence and abundance patterns, physiological responses

Species traits as predictors

How does the effect of different traits vary with the scale of measurement of environmental variables and/or species’ responses?

Species presence and abundance patterns, biotic interactions (e.g. seed dispersal, pollination, parasitism), functional and species diversity patterns

Single trait expression across scales

How does the expression of a single trait for a particular species vary over different spatial scales, and how do environmental variables moderate this variation? This includes studies that measure phenotypic plasticity or intraspecific variation.

Intraspecific trait variability (variation in body size across scales, changes in home range and dispersal capacity related to changes in landscape structure at multiple scales)

Trait diversity

How do patterns of trait diversity (the variation or distribution of species traits in an assemblage) change across multiple scales?

Functional trait diversity, species diversity patterns

Species Traits as Predictors

We found 46 studies using the “species traits as predictors” approach. Studies of this type explicitly use traits as predictors to measure their moderating effect on the relationship between environmental variables and ecological responses at different spatial resolutions and/or extents (Fig. 2b). It has been hypothesised that at broad spatial extents (e.g. landscape, region), environmental variables such as climate and topography influence species and communities based on sets of traits related to tolerance to disturbance, dispersal capacity and habitat specialization [4, 22, 23], while at smaller spatial extents, other traits, including diet and nesting behaviour, operate through more localised environmental variables to influence species abundance [24, 25]. To test this, multivariate analyses may be used to measure how specific traits account for variation in ecological responses at each scale of interest [11, 17]. If variation in the effect of particular traits across scales is non-random, it can be hypothesized that this trait acts as a driving trait for a particular ecological response at some scales more than at other scales.

Studies that use this approach include those that identify species traits that explain variation in invasion area among species at different extents (e.g. [26, 27]), as well as those that predict how species with different traits respond to land-use change or biotic conditions at different resolutions (e.g. [15, 28, 23]). For instance, Akasaka et al. [26] found that, irrespective of the resolution analysed, non-native species with clonality had significantly larger invasion areas than species without that attribute. Clonal reproduction enhanced competitive ability and establishment, promoting rapid expansion and maintenance within suitable habitats at fine and coarse resolutions. In contrast, traits related to species’ colonization capacity, such as seed size, were only marginally related to invasion areas at coarser resolutions (i.e. 80 km2 grid). This suggests that invasive plants are dispersal-limited at large scales. In another example, Gilroy et al. [29] showed that habitat specialization was a good predictor of bird species abundances in cloud forest zones in the Colombian Chocó-Andes. However, this trait was strongly linked to amount of tree cover and the distance from forest only at within-farm spatial resolutions. Conversely, foraging plasticity was a strong predictor of species responses to distance from forest at coarser landscape resolutions, but not for responses to local habitat within each farm.

Single Trait Expression across Scales

This approach includes studies that measure how the effect of environmental variables on the expression of a particular trait within species varies over different spatial scales (Fig. 1c). At the population level, phenotypic plasticity can modify the expression of the same trait at different scales [9, 12, 30]. For example, there is evidence that the expression of morphological traits in response to variation in landscape structure may change at different spatial extents and resolutions [1, 31]. Kaiser et al. [32] showed that, by altering temperature, urbanization affected butterfly size at fine resolutions (200 × 200 m), but these effects were not evident at broad resolutions (3 X 3 km). We found that 18% of the reviewed studies analysed variation in trait expressions across different resolutions and/or extents. Most evidence on how environmental variables affect the expression of species traits and their effect on ecological responses comes from studies analysing trait variation across environmental gradients (e.g. levels of disturbance) rather than at multiple scales [9, 10, 33]. Some of these studies show that intraspecific variation in traits may lead to different ecological responses, such as changes in demographic attributes in terms of survival and reproduction [31, 32]. However, there is a lack of empirical evidence on this topic, and further research effort is needed to address this gap.

Trait Diversity

An approach that has become more popular in the last few years is to measure the frequency of trait values across species and relate this to community diversity patterns at different scales (54 studies, Fig. 1d). The main objective of this approach is to identify groups of species with similar morphological, physiological or behavioural traits that are affected in a similar fashion by biotic or abiotic conditions at different scales [11, 13, 34, 35]. Recent multi-scale studies show how sets of variables linked to fire regimes [36], grazing [35] and urbanization gradients [37, 38] explain variation in functional diversity indices at different scales that reflect the spatial scale at which environmental factors operate [11, 17, 39]. For some assemblages, coexisting species tend to express more divergence in trait values at fine resolutions (e.g. 10 × 10 cm subplots within larger plots), suggesting niche differentiation. Conversely, at broad resolutions and extents, environmental variables tend to filter species with similar traits, and these patterns become more evident when disturbance increases [4, 15]. Thus, in addition to their importance for analysing how landscape structure affects the distribution and abundance of individual species in habitat models, traits have become crucial to understanding how different sets of species maximize community-wide coexistence and hence measures of species diversity at different scales [5, 40, 41].

What Traits Have Been Used to Understand the Scale-Dependent Role of Traits?

Our review shows that traits related to size (e.g. body mass, plant height) and habitat specialization are most commonly used at both the species and the community level to explain the scale-dependent role of traits (Fig. 3a). For animals, the most common trait was body size (n = 27), followed by habitat specialization (primary habitat and/or breadth of habitats used; n = 21), dispersal (n = 14), diet (n = 12) and various morphological traits (n = 11). How the effect of species competitive abilities on ecological responses change across scales is a topic that has received less attention, while traits associated with nesting and social behaviour have been investigated mostly in single-scale studies [42]. Community-level approaches are most common in plants, and generally evaluate easily measurable morphological traits such as height, seed mass and specific leaf area. These traits are used to describe reproductive abilities and tolerance to disturbance (e.g. [43, 44]). Traits related to species interactions (e.g. morphological traits for pollination and reproduction, chemical defences for herbivory and social behaviour) are still mostly ignored in most multi-scale trait-based approaches. Although some studies included species or population attributes such as geographic range size, we did not take them into account in our analysis, since they are not a property of the organisms measured at the individual level [8].
Fig. 3

a) The main ecological responses and b) the main traits used in multi-scale studies for explaining the effects of traits on ecological responses at different scales. n = 101

Of the studies that included multiple traits to calculate trait diversity indices, only 31% aimed to disentangle which particular set of traits was driving diversity patterns at each scale [15, 17, 45]. Most community-level studies focused on evaluating how indices of functional diversity changed across spatial extents, without reporting the major combination of traits driving these differences. This information is fundamental to understanding how species traits affect population responses and community dynamics at each scale [12, 30, 46]. For example, there is evidence that traits such as body size, dispersal capacity, trophic level and matrix tolerance increase or decrease a species’ vulnerability to fragmentation and habitat loss [47, 48, 49]. However, multi-scale trait-based approaches still require information on how the interaction between these traits varies among microhabitats, patches and habitat types across landscapes. Using this information, it may be possible to explain, for example, whether edge sensitivity is primarily related to dispersal ability at the landscape scale [47], or whether a much wider range of traits is influential in explaining this effect [50]. Additional studies relating species traits and fragmentation patterns at multiple scales are needed to predict how changes to landscape structure affect biological communities.

What Predictors Have Been Measured to Understand the Scale-Dependent Role of Traits?

Most studies we found focused on habitat or landscape composition variables, but less than 35% of the studies considered landscape structure predictors associated with both habitat size and configuration. There are numerous examples of how changes in landscape structure variables can modify the effect of particular traits [10, 51]. For example, matrix quality and fragmentation modify species mobility and fecundity through changes in mobility traits [51, 52, 53, 54]. In addition, the effect of dispersal capacity on community composition patterns may be higher in areas with complex topography; conversely, flatter natural areas may increase connectivity. Thus, the spatial configuration of the landscape may have a greater effect on community composition than differences in dispersal capacities between species [55, 56]. Ignoring the role of landscape structure may have consequences for the interpretation of how landscape change affects community dynamics and ecosystem functioning.

The importance of species traits for explaining ecological responses is highly dependent on environmental gradients that may affect the expression of traits [57, 58, 59]. For example, differences in topography, disturbance level and elevation affect how traits such as plant height, nutrient concentration in leaves, and foraging behaviour influence population and community structure [51, 57, 58, 59, 60]. Most of the studies we reviewed measured environmental predictors at local habitat resolutions [39, 44] and/or at broad extents (across continents, nations or regions) [55, 61, 62]. However, we lack trait-based studies combining both different resolutions and spatial extents that aim to detect the effect of environmental gradients on trait effects at local habitat resolutions (e.g. [36, 37, 44, 63]). In addition, in most of the studies (n = 72), trait measurements were averaged at the species level, ignoring how environmental variables may affect the expression of traits within species at different extents. Understanding how environmental predictors interact with scale to affect the influence of traits on ecological responses is a critical gap to be filled.

What Ecological Responses Have Been Measured in Multi-scale Trait Approaches?

We found that the main ecological responses that have been measured to investigate the effects of species traits across scales include the analysis of multiple indices of diversity (e.g. beta diversity, functional and phylogenetic diversity; 48%) [29], taxonomic diversity (17% of studies) (Fig. 2a) [15, 27], interspecific interactions (8%) such as parasitism [27, 64] and predation [65], and patterns of single species occurrence and distribution (10%). Most work regarding community trait-based approaches comes from studies on plant assemblages (38%) [4, 22] and, to a lesser extent, on invertebrates (23%) [19, 66] and birds (14%) [29, 67].

With respect to the “single trait expression across scales” approach, we found that most studies did not link intraspecific trait variation and population ecological responses at multiple scales [32, 33]. This is despite the fact that the study of the impacts of landscape change on species traits, such as foraging behaviour and dispersal distance, is an active area of research [10, 13, 18]. Since most studies describing species–environment relationships are still not adopting multi-scale frameworks (reviewed by [1, 16]), we have little understanding of how different environmental variables, including landscape structure, affect intraspecific variation in many traits across scales and its effect on ecological responses. Ignoring intraspecific trait variation may mask the effect of environmental variables on ecological responses, especially in landscape-scale studies that encompass strong environmental gradients and locally adapted populations [45].

Evaluation of the scale-dependent role of traits on species interactions such as predation, seed dispersal and pollination has been poorly addressed, and we found that only 8% of studies examined these processes (Fig. 3b). Species interactions might be inferred from a small number of traits [68, 69]. However, additional evidence is needed to infer whether the traits of interacting species groups are consistently related across spatial scales [70]. Some examples of advances in this area come from studies on host–parasite relationships. A meta-analysis by Gunton and Poyry [64] tested the hypothesis that, within a landscape, the risk of an insect being attacked by a parasite is strongest at medium spatial resolutions with respect to parasite foraging range, whereas it is weak at fine resolutions. However, these authors also showed that there is a lack of evidence that this change in risk across scales depends on certain traits such as the level of specialization and whether the parasite is gregarious. In another example, Barnagaud et al. [27] found that the abundance patterns of the parasitic brown-headed cowbird (Molothrus ater) are influenced by specific hosts' ecological traits at fine resolutions within landscapes rather than at coarse (regional or continental) spatial extents. These authors found that the effects of nest parasitism depend more on landscape structure and other environmental factors operating at landscape and patch scales than on specific associations with particular groups of species at larger scales. Therefore, evidence provided by these studies shows that the importance of species traits in explaining species interactions is highly dependent on regional and landscape context.

Towards a Better Understanding of the Scale-Dependent Effect of Traits

Although traits can provide a mechanistic approach for evaluating the link between ecological responses and environmental variables, current understanding of the scale-dependent role of traits in shaping these relationships is still in its infancy. From our review, we identify three main gaps: 1) there is a lack of studies explicitly quantifying the relative effect of particular sets of traits on ecological responses across scales; 2) several ecological responses related to ecosystem functioning and species interactions, such as seed dispersal, predation and multi-trophic networks, have been widely overlooked; and 3) the effects of landscape structure are ignored in many studies. While recognizing the challenges associated with evaluating the scale-dependent effect of traits in real landscapes, we discuss these gaps and provide some general recommendations for future progress.

Most community-level studies do not explicitly quantify the relative effect of single traits on ecological responses across spatial scales. Instead, studies measuring trait diversity tend to condense multiple traits in a single metric, and many of them do not test for how sensitive these metrics are to including different traits. Since species traits may represent different niche axes, aggregated information of functional metrics can overlook specific associations between environmental variables and community patterns at different scales [15, 45, 71]. Therefore, in order to explain the scale-dependent role of traits in heterogeneous landscapes, ecologists must 1) test for different sets of traits to represent the main variations in trait effects across scales [12, 60, 72] and 2) evaluate the congruence between trait diversity metrics and single-trait models.

Current research shows the importance of evaluating the congruence of functional diversity patterns with single-trait models. For example, Chalmadrier et al. [15] classified traits as “driving traits” if they had a significant pattern going in the same direction as the multi-trait functional diversity pattern, and “countering traits” if they showed a significant pattern going into the opposite direction. In this way, the authors showed how leaf dry matter content is more important for explaining the distribution of species at fine resolutions, whereas specific leaf area and height play a more important role in structuring assemblages that respond in a similar way to environmental stressors at large extents (an entire landscape). More empirical evidence about how particular sets of traits drive trait diversity patterns across scales is needed, and the use of probability density function approaches to calculate functional diversity at multiple scales constitutes a promising area of research (see [13]).

Understanding the scale-dependent role of traits requires evaluating how local ecological responses are context-dependent across management practices or regions. Trait effects depend on multiple factors, including the ecological response and the taxonomic group of interest, as well as inter-regional variation in landscape attributes such as matrix quality, road density or topography. For example, although the effect of dispersal traits as determinants of beta diversity may be highest at landscape extents [11, 55], there is evidence that regional disturbances such as urbanization moderate the strength of the effect of dispersal capacity with increasing spatial extents [38]. Further studies disentangling the effects of environmental variables, community composition, traits and phylogeny are necessary in order to generalize findings of trait effects across regions. These studies may benefit from the current development of large databases (e.g. [73, 74, 75]) that allow the simultaneous extraction of trait values from a large number of species or populations rather than on measurement of traits in the field [44].

Our review found a paucity of research regarding the scale-dependent effect of species traits in processes such as competition, parasitism and trophic interactions. Some works have shown how fluxes in resources and individuals across habitats influence each other’s structure and dynamics [76, 77, 78]. Other models have explicitly evaluated how traits of resistance to herbivory influence spatial patterns in plants [79], and there is some empirical evidence showing that traits related to body size, body shape and behaviour help to predict predator–prey interactions across multiple extents, including individual prey foraging areas and entire landscapes [65]. However, the study of the effects of traits on ecosystem processes such as food web interactions is still very limited, and deriving generalities across scales is still a major challenge. In order to assess the impacts of human modification on ecosystem services, we need to understand how traits of interacting species groups and ecosystem functions are consistently related across spatial scales.

Although it is expected that the diversity of functional traits determines ecosystem functioning, we still lack information regarding how much trait diversity is needed to maintain multiple ecosystem functions within habitat types within landscapes, between landscapes and among regions [80, 81]. A key knowledge gap exists in our understanding of how species sharing similar functional traits respond to scale-specific disturbances. In addition, issues still remain in scaling up how local-scale diversity affects ecosystem processes at larger spatial scales (e.g. how functional diversity at the landscape scale influences the recovery of productivity after wildfires across landscapes [81]). To address this, tools used in large-scale studies of biodiversity (remote sensing and trait databases) can be combined with theoretical advances developed from small-scale experiments. This could help facilitate scaling up data on local trait variation to regional extents in order to understand species interactions and ecosystem service management [81, 82].

Finally, studies tend to ignore how landscape structure and landscape context influence the scale-dependent role of traits; only a few empirical studies have addressed the impact of regional landscape context on local trait divergence in natural populations [32, 56, 83]. Generally, landscape ecologists focus on measuring landscape structure at varying spatial extents around sites/patches from which a response variable is measured, and then infer how species traits influence the scale at which landscape structure has the strongest observed effect on the response [1, 3, 4]. In contrast, multi-scale studies that focus on the scale-dependent role of traits generally use a hierarchical approach to compare ecological responses at local (plot scale) and regional scales that captures heterogeneity in conditions related to variables such as climate and topography. Studies that seek to link traits to ecological responses at the landscape scale must consider a hierarchical design in which landscape structure is measured at multiple scales around plots distributed across an environmental gradient. This will allow for a more comprehensive understanding of how traits affect ecological responses in space, as well as guide management responses that explicitly account for trait effects across a wider range of spatial scales.


Over the past few decades, the dependence of ecological processes on drivers acting across a range of scales has been widely studied [1, 3, 84]. Theoretical and empirical evidence suggests that species responses to landscape change are determined partly by the spatial resolution and extent at which physical and biological attributes are measured, and partly by the ecological traits of species [1, 21, 47, 85]. However, the study of the scale-dependent role of traits that drive ecological responses is still in its infancy. Furthermore, methodological developments in trait approaches for animal ecology substantially lag those currently used for plant ecology.

Without a proper quantification of variation in abiotic and biotic conditions at multiple scales in trait-based approaches, it is still difficult to disentangle whether the responses of ecological systems are dependent on traits or on environmental variables acting across habitats, patches and landscapes. There is variation at every scale at which we measure traits, as well as context dependence in which traits have varying effects on ecological responses. Therefore, we advocate the use of models that evaluate how variation in environmental conditions across regions and habitat types influences trait effects on ecological responses, as well as the measurement of landscape structure at a wider range of spatial extents and resolutions. The explicit inclusion of landscape structure effects in trait-based approaches at multiple scales will benefit the integration of approaches from community ecology and landscape ecology. This is fundamental if we want to predict the impact of landscape change on a broad range of ecological responses, including species diversity patterns and interspecific interactions. In this way, we could avoid missing essential information about the mechanisms that operate simultaneously at multiple scales to shape biological communities in changing landscapes.



This work was supported by an Australian Research Council Discovery Project (DP130100218) and a Colombian Ministry of Education (COLCIENCIAS 529) scholarship to A.F.S.C. Martine Maron is supported by an Australian Research Council Future Fellowship (FT140100516).

Compliance with Ethical Standards

Conflict of Interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Supplementary material

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Andrés Felipe Suárez-Castro
    • 1
    • 2
  • Jeremy S. Simmonds
    • 1
    • 2
  • Matthew G. E. Mitchell
    • 1
    • 2
    • 3
  • Martine Maron
    • 1
    • 2
  • Jonathan R. Rhodes
    • 1
    • 2
  1. 1.Centre for Biodiversity and Conservation ScienceThe University of QueenslandBrisbaneAustralia
  2. 2.School of Earth and Environmental SciencesThe University of QueenslandBrisbaneAustralia
  3. 3.Institute for Resources, Environment & SustainabilityUniversity of British ColumbiaVancouverCanada

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