The resolution‐dependent role of landscape attributes in shaping macro‐scale biodiversity patterns

Abstract

Aim The aim was to assess whether and to what extent the role of local landscape attributes in shaping macroscopic biodiversity patterns is sensitive to spatial and thematic resolutions of land cover data. Location Sub‐Saharan Africa and continental China. Time period Early 21st century. Taxa studied Terrestrial mammals. Methods We conducted spatial and thematic scaling analyses to generate land cover datasets of different spatial (0.3, 0.5, 1.0 and 9.0 km) and thematic (two, three and five classes) resolutions. We calculated landscape metrics based on the resulting land cover maps and examined the power of landscape metrics for explaining species richness patterns, using non‐spatial (OLS) and spatial (SAR) linear models and random forest (RF) models. We systematically assessed the resolution dependence of explanatory power for different geographical regions, different scaling approaches and different model types. We also compared the explanatory power of landscape attributes with that of macroclimate. Results Collectively, local landscape attributes generally had strong explanatory power for species richness. For the African system, the largest explanatory power was c. 60% based on the OLS models and random forest models and c. 30% based on the non‐spatial components of the SAR models. For the Chinese system, the largest explanatory power was c. 35% based on the OLS models and c. 40% based on the SAR and random forest models. We observed a linear scaling relationship, which is robust to studied systems, scaling approaches and model types. In contrast, the scaling relationship varies substantially among single landscape metrics. At coarse resolutions, the addition of landscape attributes collectively would not improve climate‐envelope models significantly, whereas at finer resolutions, landscape attributes collectively have explanatory power that is close to or even exceeds climate. Main conclusions Local landscape attributes play an important role in shaping macroscopic biodiversity patterns. However, their strength is highly sensitive to both spatial and thematic resolutions of land cover data, with stronger explanatory power detected at finer resolutions. Strong sensitivity to spatial and thematic resolutions makes landscape attributes highly plastic determinants, leading to contrasting conclusions if based on greatly different resolutions of land cover data. Scaling analyses are needed to examine such cross‐scale effects of macroecological determinants systematically.

The Interplay Between Thematic Resolution, Forest Cover, and Heterogeneity for Explaining Euglossini Bees Community in an Agricultural Landscape

“…The positive relationship between the richness of different bee groups and landscape heterogeneity has been reported (Boscolo et al, 2017;Moreira et al, 2017;Coutinho et al, 2020;Opedal et al, 2020), indicating the importance of landscape diversity for the biological requirements of these pollinators. It is expected that the landscape structure in fine thematic resolutions better explains species richness (Lawler et al, 2004;Qiu et al, 2019).…”

“…Lower thematic resolutions with a small number of cover classes have a more straightforward classification and may aggregate different functional covers, suppressing the necessary level of details to explain biological variables from landscape attributes (Lawler et al, 2004;Marshall et al, 2020). Higher thematic resolutions, on the other hand, result in more detailed mapping of landscape composition and functional covers (e.g., habitat specialists) (Kendall et al, 2011;Liang et al, 2013), increasing the probability to detect associations between biological attributes (e.g., species richness) and landscape structure (Qiu et al, 2019;Marshall et al, 2020).…”

“…For these reasons, increasing or decreasing the number of cover classes can modify landscapes' functional heterogeneity quantification (Li and Wu, 2004;Lechner and Rhodes, 2016). Thus, our ability of understanding spatio-temporal effects of landscape structure on biodiversity depends on the choice of a thematic resolution that represents the landscape elements that have the most significant explanatory power for ecological responses (Buyantuyev and Wu, 2007;Kendall et al, 2011;Qiu et al, 2019).…”

Neighbourhood landscape context shapes local species richness patterns across continents

“…Such a cross‐scale link, however, has long been overlooked in macroecology, as seen in a majority of existing studies where landscape attributes (defined as the quantities and configurations of spatially intertwined ecosystems across a landscape) have normally not been taken into account (e.g., Thuiller et al, 2004). This might be attributable, at least in part, to the limitation that global landscape datasets have had too coarse spatial resolutions (Qiu et al, 2019). Indeed, recent analyses based on fine‐resolution global land cover datasets have demonstrated that landscape attributes can provide a substantial fraction of power (in addition to bioclimatic variables) for explaining terrestrial species richness patterns at regional and continental scales (Martins et al, 2014; Qiu et al, 2019; Xu et al, 2014), and therefore landscape factors should not be excluded a priori for a complete understanding of macroecological determinants.…”

“…This might be attributable, at least in part, to the limitation that global landscape datasets have had too coarse spatial resolutions (Qiu et al, 2019). Indeed, recent analyses based on fine‐resolution global land cover datasets have demonstrated that landscape attributes can provide a substantial fraction of power (in addition to bioclimatic variables) for explaining terrestrial species richness patterns at regional and continental scales (Martins et al, 2014; Qiu et al, 2019; Xu et al, 2014), and therefore landscape factors should not be excluded a priori for a complete understanding of macroecological determinants. Beyond the complementary benefits, these findings help to bridge landscape ecology and macroecology, which are two important, but largely unconnected fields.…”