The consequences of land use changes on biodiversity have been addressed by studies at different levels of ecological organization and geographic scales. These studies range from metapopulation established in fragmented landscapes (Ovaskainen and Hanski, 2003; Burkey, 1997), to the investigation of landscape features that modulate the species-area relationship (Benchimol and Peres, 2013; Hanski et al., 2013; Rybicki and Hanski, 2013). Also, the consequences of land use changes have been addressed by studies focusing on the perceived effects of habitat loss on biodiversity at regional and broader geographic scales (Banks-Leite et al., 2014; Brooks et al., 2002; Gaston et al., 2003; Pfeifer et al., 2017).

Given the Wallacean shortfall, i.e. lack of information about species’ distribution, habitat suitability models have been suggested as a tool to refine information on species distribution and help guiding conservation assessment and decision more precisely (da Fonseca et al., 2000; Ottaviani et al., 2004; Rondinini et al., 2011). Habitat is defined as the set of resources and conditions present in an area that produce occupancy, including survival and reproduction by a given organism (Krausman, 1999). Habitat suitability models are important tools to evaluate species distribution based on their potential habitat remnants. They rely on the Hutchinson's concept of ecological niche (Hirzel and Arlettaz, 2003) and are designed to predict species’ occurrence based on environmental data and species habitat preferences. Among several possible applications, these models have been used (1) to assess species recovery (Cianfrani et al., 2013); (2) to estimate extinction debt when coupled with species-area relationships (Olivier et al., 2013); (3) to map the potential distribution of invasive species (Crall et al., 2013); (4) to evaluate global patterns of species richness (Rondinini et al., 2011); and (5) to propose global priority areas for conservation efforts (Brum et al., 2017).

However, habitat suitability models by itself lack information about the interaction between species features and spatial structure of habitat patches. Thus, a set of methods to assess the effects of landscape structure on species responses have been developed (McGarigal and Cushman, 2005). Nonetheless, those methods employed to study the effect of patch size and isolation on biodiversity usually 1) lack information on species’ ecological features and their ecological meaning (for instance, classic landscape metrics describing landscape structure by itself, like habitat amount, edge length, shape index, etc.); 2) do not consider species-specific responses to landscape change; 3) are not able to transpose the results obtained from one scale to another; or 4) require a large amount of data. Considering this, Vos et al. (2001) proposed two indices linking species to habitat, both called Ecologically Scaled Landscape Indices: ESLIc and ESLIk. ESLIc associates patch area, pairwise distance between patches, and species’ movement ability resulting in an index that reflects landscape functional connectivity. ESLIk associates patch area and individual area requirement, resulting in an index that describes the landscape carrying capacity for a given metapopulation.

We employed an approach that classifies species according to their response to environment, specifically to habitat fragmentation and habitat amount sensitivity: the ecological profile. Such approach incorporates different colonization responses to environment when empirical data is missing (Grimm et al., 1996). The strength of this approach is the employment of this concept in answering general questions about how a given group of organisms with some intrinsic features can respond to differences in the composition and configuration of natural environments. For instance, species with similar dispersal ability and similar total areas required to reproduce, belonging to different taxa, could be considered part of the same ecological profile.

Here, we propose a framework to evaluate connectivity and carrying capacity at species range scale, coupling deductive habitat suitability model and landscape connectivity and carrying capacity through ESLIs. Our framework includes an intuitive and realistic definition of habitat and it is a more factual way to know how much habitat is there based not only on remaining area, but also on species’ habitat preferences. Also, it quantifies how much habitat would be potentially occupied by a metapopulation, given patches’ carrying capacity that, even though isolated, would be connected by individual moving ability, and it allows one to perform a validation test for obtained models. Using this approach, we 1) modeled habitat suitability based on deductive habitat suitability modelling in order; 2) to evaluate habitat amount, fragmentation, functional connectivity and carrying capacity at nine different scale extents from local landscapes to species range; 3) to evaluate the scale sensitivity of each metric and 4) to assess if the scale sensitivity of each metric changed according to the species. To exemplify our approach, we applied it to five species that represent different ecological profiles distributed in different places around the world.

Our model showed good power in predicting species occurrence and consequently determine were and how the habitat is distributed across the species range scale, in a straight forward approach. Habitat spatial structure affects ecological processes like extinction, which involving the whole species population (Forney and Gilpin, 1989). That is why population persistence should be evaluated at the geographic range scale, the area where network populations of a particular species inhabit.

Assessing the amount of remaining habitat and fragmentation degree for a species at the local scale can represent the same pattern found in the entire range, if the metric account only for landscape structure. However, if the biological features are being considered, the local scale analysis can no longer represent the species conservation status of a species. This because the conservation status of a species depends not only on the remaining habitat and its distribution, but also how the species respond to this pattern. The understanding of effects of habitat changes on species-habitat relationship should involve the application of methods that consider 1) aspects of the life history of the species, 2) the patterns of size and isolation of habitat patches and 3) that are able to synthesize all this information. All that because we might evaluate the fine scale patterns to understand the broad scale phenomena (Gouveia et al., 2016). For example, consider patch size and the area required for reproduction to determine landscape carrying capacity at different scales, and dispersal dynamics and patch isolation affect functional connectivity.

Landscape carrying capacity is lower for all the species at the range scale. It means that the effect of habitat loss could be worse when we consider the total area where the species inhabit. However, the movement ability to reach different patches of remaining habitat could mitigate this effect on the range scale, since we can see a much higher connectivity at the range scale, for most species. We propose that landscape metrics employed to study size and isolation of habitat patches should consider not only landscape features, but also intrinsic biological features of species, given that some metrics fail to account for scale-dependent variation within species due to the lack of ecological significance. The metrics proposed by Vos et al. (2001) is an accordant initial step in that way since they are easy to interpret and have an understandable ecological meaning (Swihart and Verboom, 2004). In this study, we showed that habitat amount and fragmentation effects on landscape carrying capacity and functional connectivity can vary greatly. Even species occurring in landscapes with less than 20% of habitat amount and fragmentation degree above 50% can experience high functional connectivity at the range scale. These results highlight the importance of differences in sensitivity of ecological profiles, since they respond in a similar way to landscape patterns, irrespective to the ecological processes (fragmentation and habitat amount).

We need a realistic definition and applicable data about the habitat concept and landscape scale (Didham et al., 2012; Fahrig, 2013; Rueda et al., 2013). The scale in which conservation planning is usually done must consider the focal patch and its neighborhood as well other patches that act as sources of individuals (Lindenmayer et al., 2007; Visconti and Elkin, 2009). Since metapopulation is a complex network of habitat patches, landscape supplementation must be studied in a more broadly scale, under a holistic point of view. For conservation purposes, Dunning et al. (1992)’s definition of landscapes (“landscapes generally occupy some spatial scale intermediate between an organism's normal home range and its regional distribution”) do not comprise all the aspects that affect metapopulation persistence. A holistic analysis of the environment and local conservation initiatives need to rely on approaches that can deal with high amounts of data and that can be easily applied. Habitat suitability modeling is an approach increasingly used for different purposes, including in connectivity assessment (da Fonseca et al., 2000; Ottaviani et al., 2004; Rondinini et al., 2011; Cianfrani et al., 2013).

Here, we were able to diagnose the status of different species’ geographic distribution, getting closer to the actual area of occupancy (AOO) of species, and landscape supplementation. Habitat suitability models based on a free global land use map allowed us to assess the suitable areas within species’ range, being a starting point to analyze species-habitat relationship. It was a more factual way to know how much and where are the habitat based not only on the area, but also on species’ habitat preferences. By applying this method, one would incur in fewer errors arising from the underestimation of area of occupancy (Beresford et al., 2011; Rodrigues, 2011), because extent of occurrence data typically overestimate the area occupied by each species and delineate habitat patches in a more realistic way than simply relying on native vegetation remnants. This study helps in the recent discussion about the downscaling of biodiversity distribution data, based not only on GIS information, but also on intrinsic features of the species, which have more ecological meaning, confirming what was raised by Jenkins et al. (2013).

We also considered the scale dependency of landscape studies. Didham et al. (2012) argued that there are differences in responses to fragmentation due to differences between sets of species traits, indeed generating similar species responses in groups of related species. Here we show that species with different habitat preferences, dispersal abilities and sensitivity to habitat amount and fragmentation have differences in responses until a given point where these species could be grouped in ecological profiles. In the same way, Rueda et al. (2013) opened a venue for investigation about ‘what extent are species’ responses to fragmentation’.

We must highlight some possible caveats of our approach. First, species with dispersal ability under the spatial resolution of our analyses cannot have their functional connectivity assessed by the ratio between dispersal distance and distance between patches, but would be by the ESLIc. Still, species that have small home ranges, like some amphibians, are not sensible to ESLIk or any landscape metric because their home range does not go beyond the grid cell scale. Another limitation is to deal with more than one species in a given region. If the geographic range can be used as the landscape scale, how we can deal with more than one non-coincident geographic range? We suggest that the first step to deal with this kind of problem is to take into account (1) the proportion of geographic range of each species will be evaluated in the given region, (2) how much habitat is enough to maintain viable populations in patches with minimum carrying capacity and functionally connected, and (3) where is the area most vulnerable to habitat loss (Fahrig, 2003).

The novelty of this study is a framework using deductive habitat suitability modeling, plus ESLIs to understand the conservation status at the range scale. In other words, the novelty is the landscape-range scaled analyses. We are proposing this because the land use change is the major threat to species conservation. Since the basic action unit is the species (which is a meaningful evolutive unit) we are proposing that landscape analyses should also be addressed at the range scale, because it is the “reality” of the species. Analyses performed in any other smaller scale are just an estimative. This framework could be applied to understand the species conservation status and to understand landscape changes at a species level, especially when land use time-series and species occurrence data are available (as in Gouveia et al., 2016).

We are showing a well outcomed framework in predicting species occurrence and consequently determining were and how the habitat is distributed across the species range scale, in a straight forward approach. We also showed that when the biological features are being considered, the local scale analysis can no longer represent the species conservation status of a species, since it depends not only on the remaining habitat and its distribution, but also how the species respond to this pattern. The landscape carrying capacity is lower for all the species at the range scale. It means that the effect of habitat loss could be worse when we consider the total area where the species inhabit. However, the movement ability to reach different patches of remaining habitat could mitigate this effect on the range scale, since we can see a much higher connectivity at the range scale, for most species. Our approach can lead to lower risks of incurring in commission errors arising from landscape-scale underestimation of species’ occurrences and provide a new approach to assess species-habitat relationship. We highlight the importance of considering range-scaled landscape, landscape carrying capacity, and patch functional connectivity in a synthetic and integrated framework for conservation studies.