Global identification and mapping of socio-ecological production landscapes with the Satoyama Index

Production landscapes play an important role in conserving biodiversity outside protected areas. Socio-ecological production landscapes (SEPL) are places where people use for primary production that conserve biodiversity. Such places can be found around the world, but a lack of geographic information on SEPL has resulted in their potential for conservation being neglected in policies and programs. We tested the global applicability of the Satoyama Index for identifying SEPL in multi-use cultural landscapes using global land use/cover data and two datasets of known SEPL. We found that the Satoyama Index, which was developed with a focus on biodiversity and tested in Japan, could be used globally to identify landscapes resulting from complex interactions between people and nature with statistical significance. This makes SEPL more relevant in the global conservation discourse. As the Satoyama Index mapping revealed that approximately 80% of SEPL occur outside recognized conservation priorities, such as protected areas and key biodiversity areas, identifying SEPL under the scheme of other area-based conservation measures (OECM) may bring more conservation attention to SEPL. Based on the issues identified in the SEPL mapping, we discuss ways that could improve the Satoyama Index mapping at global scale with the longitudinal temporal dimension and at more local scale with spatial and thematic resolution.

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

Human activities have modified the landscape composition. The changes in the landscape structure can be evaluated by metrics, which are influenced, among other factors, by the number of cover classes used for the landscape classification (thematic resolution). In high thematic resolutions, landscape covers that can influence biological responses are identified and detailed. In low thematic resolutions, this detail level is lower because it aggregates different landscape covers in a few classes. However, how the thematic resolution influences our ability to understand landscape structure on biodiversity is poorly explored, particularly for pollinators. Here we asked how thematic resolution affects the explanatory power of landscape composition on explaining Euglossini bees (richness and abundance) within 15 landscapes composed mainly of coffee and pasture. To address this issue, we quantified the association between five attributes of the euglossine bee community and landscape composition: landscape cover classes (%) and landscape heterogeneity. Moreover, we also evaluated how the thematic resolution influences bee responses to landscape structure. We found a strong and positive influence of landscape heterogeneity in low thematic resolutions (i.e., few cover classes on maps) over the richness and rare species abundance. We also observed that- in addition to the forest cover in the landscape- the pasture cover (%) quantified in high thematic resolution positively influenced the total abundance and abundance of common and intermediate species. Our study highlights the importance of maintaining compositional heterogeneity for the orchid bee community in agroecosystems, and forest cover for the biological requirements and conservation of these pollinators. Moreover, the use of different thematic resolutions showed how specific types of landscape covers influence the euglossine community attributes. This can highlight the species preferences for habitats and landscape covers. Thus, we call the attention of landscape ecologists to the importance of the definition of thematic resolution, as our ability to quantify the association between biological responses and landscape structure may be influenced by the number of classes used when building thematic maps.

Effects of Land Use-Land Cover Thematic Resolution on Environmental Evaluations

Land use/land cover (LULC) maps are a key input in environmental evaluations for the sustainable planning and management of socio-ecological systems. While the impact of map spatial resolution on environmental assessments has been evaluated by several studies, the effect of thematic resolution (the level of detail of LU/LC typologies) is discordant and still poorly investigated. In this paper, four scenarios of thematic resolutions, corresponding to the four levels of the CORINE classification scheme, have been compared in a real case study of landscape connectivity assessment, a major aspect for the biodiversity conservation and ecosystem service provision. The PANDORA model has been employed to investigate the effects of LULC thematic resolution on Bio-Energy Landscape Connectivity (BELC) at the scale of the whole system, landscape units, and single land cover patches, also in terms of ecosystem services. The results show different types of impacts on landscape connectivity due to the changed spatial pattern of the LULC classes across the four thematic resolution scenarios. Moreover, the main priority areas for conservation objectives and future sustainable urban expansion have been identified. Finally, several indications are given for supporting practitioners and researchers faced with thematic resolution issues in environmental assessment and land use planning.

Monitoring and Recording Changes in Natural Landscapes: A Case Study from Two Coastal Wetlands in SE Italy

This study analyzed and evaluated the changes that occurred in two coastal wetlands, characterized by complex and fragmented landscape patterns, in Southern Italy, which were monitored over a period of seven years from 2007 to 2014. Furthermore, the performances of two Land Cover (LC) and habitat taxonomies, compared for their suitability in mapping the identified changes, were assessed. A post-mapping method was adopted to detect the habitat/LC changes that occurred in the study period. Various changes were identified, both inter-class changes (class conversions) and intra-class changes (class modifications), and quantified by means of transition matrices. Conversions were easily mapped, while the modification mapping depended on the taxonomy adopted: the Land Cover Classification System (LCCS) allowed the detection of morpho-structural changes in woody vegetation, but the European Nature Information System (EUNIS) showed a higher thematic resolution for the salt marsh types. The detected changes were related to specific impacts, pressures and underlying factors. Landscape indices highlighted different trends in landscape richness and complexity in the two sites. Changes are occurring very quickly in the observed coastal sites and the ongoing dynamics are strictly related to their small size and complexity. For effective monitoring and detection of change in these environments, the coupling of EUNIS and LCCS is suggested.

Mapping Forest Composition with Landsat Time Series: An Evaluation of Seasonal Composites and Harmonic Regression

The Landsat program has long supported pioneering research on the recovery of forest information by remote sensing technologies for several decades, and efforts to improve the thematic resolution and accuracy of forest compositional products remains an area of continued innovation. Recent development and application of Landsat time series analysis offers unique opportunities for quantifying seasonality and trend components among different forest types for developing alternative feature sets for forest vegetation mapping. Within a large forested landscape in Southeastern Ohio, USA, we examined the use of harmonic metrics developed from time series of all available Landsat-8 observations (2013–2019) relative to seasonal image composites, including accompanying spectral components and vegetation indices. A reference dataset among three sources was integrated and used to categorize forest inventory data into seven forest type classes and gradient compositional response. Results showed that the combination of harmonic metrics and topographic variables achieved an accuracy agreement with the reference data of 74.9% relative to seasonal composites (71.6%) and spectral indices (70.3%). Differences in agreement were attributed to improved discrimination of three heterogeneous upland hardwood classes and an early-successional, young forest class, all forest types of primary interest among managers across the region. Variable importance metrics often identified the cosine and sine terms that quantify the seasonality in spectral values in the harmonic feature space, suggesting these aspects best support the characterization of forest types at greater thematic detail than seasonal compositing procedures. This study demonstrates how advanced time series metrics can improve forest type modeling and forest gradient quantifications, thus showcasing a need for continued exploration of such approaches across different forest types.