Modeling Alternative Approaches to the Biodiversity Offsetting of Urban Expansion in the Grenoble Area (France): What Is the Role of Spatial Scales in ‘No Net Loss’ of Wetland Area and Function?

Abstract

It is increasingly common for developers to be asked to manage the impacts of their projects on biodiversity by restoring other degraded habitats that are ecologically equivalent to those that are impacted. These measures, called biodiversity offsets, generally aim to achieve ‘no net loss’ (NNL) of biodiversity. Using spatially-explicit modeling, different options were compared in terms of their performance in offsetting the impacts on wetlands of the planned urban expansion around Grenoble (France). Two implementation models for offsetting were tested: (a) the widespread bespoke permittee-led restoration project model, resulting in a patchwork of restored wetlands, and (b) recently-established aggregated and anticipated “banking” approaches whereby larger sets of adjacent parcels offset the impacts of several projects. Two ecological equivalence methods for sizing offsets were simulated: (a) the historically-prevalent area-based approach and (b) recently introduced approaches whereby offsets are sized to ensure NNL of wetland functions. Simulations showed that a mix of functional methods with minimum area requirements was more likely to achieve NNL of wetland area and function across the study area and within each subwatershed. Our methodology can be used to test the carrying capacity of a landscape to support urban expansion and its associated offsetting in order to formulate more sustainable development plans.

Mitigation bank applications for freshwater systems: Control mechanisms, project complexity, and caveats

“…HEA is most often used to evaluate the gain of ecological function for stream habitats like estuaries or floodplains and their use for anadromous species and to identify biodiversity hotspots [ 76 , 77 ]. Habitat-focused approaches taking species life history, temporal aspects, community goals, and the role of specific habitat types into account are highly recommended to be used when establishing a debiting and crediting system that aims to value fish habitat holistically and comprehensively (Condition and Function method, Table 1 ; [ 13 , 72 – 74 , 76 , 77 ]). Habitat, Community, and Species can be applied to larger urban areas and large-scale impacts like mining, leading to long-term habitat degradation or offset requirements that often cannot be tackled through mitigation steps or a single offset [ 13 , 16 , 74 , 76 , 78 ].…”

“…Long-term monitoring and staggered credit release over a long time aim to address increasing complexity and ensure long-term benefits [ 19 , 42 ]. Consequently, Habitat, Community, and Species approaches may not be feasible for small-scale projects or projects not part of a larger planning or management framework or service area [ 74 , 80 ].…”

“…Bank establishment targeting whole aquatic ecosystems (Habitat, Community, and Species) aims to restore essential habitat features like hydrology or connectivity while simultaneously creating new aquatic habitat areas, increasing habitat function and complexity, and benefiting aquatic-dependent wildlife or specific target species. Habitat-focused banks often take other landuse aspects into account, actively aiming to restore sites to pre-impact conditions on a landscape level, exceeding individual impacts (Function and Condition method, Table 1; [72][73][74][75]).…”

Landscape Naturalness Scenarios Modeling for the Juréia-Itatins Protected Areas Mosaic, State of São Paulo, Brazil

“…In this context, using landscape indicators can be useful for understanding the dynamics of land use and occupation over time, because they demonstrate, even if indirectly, the anthropic impacts exerted on the environment, providing support for decision making in the construction of public policies and governmental actions for environmental protection (Wu and Hobbs 2002;Turner and Gardner 2015).…”

“…This index combines two indicators, the Degree of naturalness (Nd), that based on hemeroby scale to classify land use and land cover information, and the Distance from natural habitat (Dn), which considers, for each pixel, the Euclidean distance to the next habitat patch within the data set classified as one of the two most natural hemeroby levels: "natural" or "near natural" (Rüdisser et al 2012). Turner and Gardner (2015) evaluate D2N as a "simple but smart" index among the promising indicators and indices for assessing landscape structure. However, there are still few works that have been dedicated to evaluate the landscape from the perspective of this index.…”