Identifying Spatial Patterns and Ecosystem Service Delivery of Nature-Based Solutions

Abstract

Compared to technical infrastructure, nature-based solutions, NBS, strive to work with nature and to move beyond business-as-usual practices in order to address societal challenges such as flood risks. This research aims to spatially identify possible NBS areas and evaluate the areas capacity to provide selected ecosystem services, ES, for the Lahn river landscape in Germany. The research follows the functional landscape approach using hydromorphological landscape units, HLU, based on specific biophysical spatial criteria, such as slope, to then identify locations which may be considered suitable for NBS. The current ES delivery of these possible NBS areas is then evaluated. The three ES assessed are carbon storage, nutrient retention and recreation. We then undertake a geospatial comparison analysis to show the spatial relationships and patterns that emerge in regards to the ES configuration of the distinct NBS apt areas. Results show the HLU method serves to delineate and identify areas where NBS may exist or be implemented. The data depicts a distinct spatial pattern for each possible NBS space and complementary ES delivery. This explorative method is a useful spatial approach that can support NBS implementation and serve to investigate the multiple benefits NBS provide. The use of ecosystem services to compare and understand NBS is a viable prospect that must, however, be cautiously, locally and scientifically approached. Noticeable limitations regarding ES assessment remain, as available methods are often insufficiently inclusive of natural ecosystem processes and functions. Further research should assess a broader spectrum of NBS and their delivery of ES.

Nature-based solutions to enhance urban flood resiliency: case study of a Thailand Smart District

“…While NbS has the potential to deliver multiple ecosystem services, in choosing between different NbS designs, it would be helpful to better define a theoretical framework for assessment (Caneva et al 2020 ; Castellar et al 2021 ; Almenar et al 2021 ). A starting point for such evaluations, at least at the large scale, could be Stanford’s InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) suite of models ( https://naturalcapitalproject.stanford.edu/software/invest , accessed 14 Apr 2022) (e.g., Guerrero et al 2022 ), while at a neighborhood scale Irvine et al ( 2023 ) included dynamic, hydrologic modeling to quantify water quantity and quality ecosystem services, as well as considering carbon sequestering, food provisioning, temperature mitigation, biodiversity, and aesthetics. This ecosystem service approach to evaluating NbS design performance is promising.…”

Biological mechanisms matter in contemporary wildlife conservation

“…Physiological and behavioral knowledge can provide a first-principles understanding of how animals respond to landscape characteristics that contain much greater predictive power than descriptions of presence and absence. Physiology and behavior therefore must become an integral part in landscape assessment for conservation and integrated landscape use, 145 in conjunction with evaluation of physical characteristics (e.g., hydromorphological and biophysical 146 ) and species distribution modeling. 70 Although much progress has been made in all of these domains in the last few decades, there remains need for long-term studies/monitoring to generate robust empirical data that fully reflect spatiotemporal dynamics and relationships that presumably govern animal-environment interactions.…”

A Review of Ecosystem Services Based on Bibliometric Analysis: Progress, Challenges, and Future Directions

“…Keywords are the extraction and summary of an article [48]. Keyword co-occurrence maps can intuitively reveal hot spots in the research field of ES assessment through keyword occurrence frequency [49], and correlations in the field of ES assessment research can be intuitively seen through the relationships between keywords [50]. A co-occurrence map of keywords in the field of ES assessment is shown in Figure 5.…”