Environmental impact assessment of development projects improved by merging species distribution and habitat connectivity modelling

Tarabon, Simon; Bergès, Laurent; Dutoit, Thierry; Isselin-Nondedeu, Françis

doi:10.1016/j.jenvman.2019.02.031

Cited by 53 publications

(26 citation statements)

References 85 publications

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“…This method has recently been applied in land-use planning for habitat prioritization and connectivity improvement (Clauzel et al, 2018;Foltête, 2018). In addition, a recentlydeveloped methodological framework combining SDM and spatial graphs has improved assessment of the environmental impacts of development projects, valuable input to decision-making (Duflot et al, 2018;Tarabon et al, 2019). However, although the latter study strongly recommended that the framework be applied to implement appropriate avoidance and reduction measures, this has not yet followed.…”

Section: Introductionmentioning

confidence: 99%

Maximizing habitat connectivity in the mitigation hierarchy. A case study on three terrestrial mammals in an urban environment

Tarabon

Bergès

Dutoit

et al. 2019

Journal of Environmental Management

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Environmental policies and the objective of no net loss highlight the importance of preserving ecological networks to limit the fragmentation of natural habitats and biodiversity loss, especially due to urbanization. In the environmental impact assessment context, habitat connectivity and the spatio-temporal dynamics of biodiversity are crucial to obtaining reliable predictions that can support decision-making. We propose a methodological framework 1) to quantify the overall impact of a development project on the functioning of an ecological network, and 2) to select the best locations for implanting new habitat patches intended to enhance landscape connectivity. The amount of reachable habitat concept was applied to three representative terrestrial mammal species: the red squirrel, the Eurasian badger and the European hedgehog. All three species are recognized as vulnerable to human pressures and potentially affected by the construction of a new stadium in our study site, Lyon (Southern France). The method combines the species distribution model Maxent with the landscape functional connectivity model Graphab. The results showed that using any one of the avoidance and reduction measures on its own was unsuccessful in achieving the objective of no net loss when habitat connectivity is considered. However, the combination of new habitat patches and corridors offered a higher gain than distinct measures. This is especially important in the short term, when new hedgerow plantations have not yet developed enough to be used by the target species. Our findings indicate, first, the need to take the temporal scale into account in environmental impact assessment. We also show that applying the optimal scenario, constructed using a cumulative patch addition followed by a similar process testing a set of potential land-use changes, maximizes habitat connectivity. Our methodology provides a useful tool to increase target species' habitat connectivity within the mitigation hierarchy and to enhance development project design for increased environmental efficiency.

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Section: Introductionmentioning

confidence: 99%

Maximizing habitat connectivity in the mitigation hierarchy. A case study on three terrestrial mammals in an urban environment

Tarabon

Bergès

Dutoit

et al. 2019

Journal of Environmental Management

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“…Akaike information criterion (AIC) quantity reflects the fitting and complexity of the model, which is an excellent standard to measure the performance of the model. A model with a minimum AICc value (i.e., delta AICc = 0) is considered the best model [14]. The area under the ROC curve (AUC), true skill statistic (TSS) and Cohen's Kappa (Kappa) were used to evaluate model accuracy [15].…”

Section: Model Optimization and Validationmentioning

confidence: 99%

“…The value of area (0-1) under the ROC curve (AUC) can well reflect the accuracy of model prediction. Thus, the model was optimized according to the AIC values (delta AIC) and the difference between the training AUC value and the test AUC value (AUC DIFF ) [14,36].…”

Section: Establishment Optimization and Evaluation Of Modelmentioning

confidence: 99%

Predicting distribution of Zanthoxylum bungeanum Maxim. in China

Zhuo

Biao

et al. 2020

BMC Ecol

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Background: With the growth of economic benefits brought by Zanthoxylum bungeanum Maxim. and the increasing market demand, this species has been widely introduced and cultivated in China. It is important to scientifically select suitable areas for artificial planting and promotion, and to understand the status and potential of Z. bungeanum resources. Results: The maximum entropy (MaxEnt) model and ArcGIS technologies were used to analyze the climatic suitability of Z. bungeanum based on known distribution data, combined with environmental data in China. Z. bungeanum was mainly distributed in subtropical and mid-eastern warm temperate regions. The total suitable area (high and medium suitability) accounted for 32% of China's total land area, with high suitability areas composing larger percentage, reaching 1.93 × 10 6 km 2. The suitable range (and optimum value) of the key environmental variables affecting the distribution of Z. bungeanum were the maximum temperature in February of 2.8-17.7 °C (10.4 °C), the maximum temperature in March of 8.6-21.4 °C (16.3 °C), the maximum temperature in December of 2.5-17.1 °C (9.9 °C), the maximum temperature in November of 7.7-22.2 °C (14.5 °C) and the mean temperature in March of 3.2-16.2 °C (12.0 °C). Conclusions: The model developed by MaxEnt was applicable to explore the environmental suitability of Z. bungeanum.

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“…They have recently grown in popularity as a way to easily identify ecological networks (see for instance Clauzel & Bonnevalle, 2019;Mechai et al, 2018;Niculae, Nita, Vanau, & Patroescu, 2016), to assess the effects of fragmentation and loss of landscape connectivity (Clauzel, 2017;Liu, Peng, Zhang, & Zhao, 2016;Tournant, Afonso, Roué, Giraudoux, & Foltête, 2013), and to wholly or partially implement the mitigation hierarchy (for instance Bergès et al, 2020;Clauzel, Bannwarth, & Foltête, 2015;Tarabon, Bergès, Dutoit, & Isselin-Nondedeu, 2019a, b). Moreover, graph-theory-based models can be combined with species distribution models (SDMs) to identify habitat patches (see Tarabon et al, 2019a). SDMs relate species distribution records to environmental data and can be used to produce maps of habitat suitability (Elith et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Integrating a landscape connectivity approach into mitigation hierarchy planning by anticipating urban dynamics

Tarabon

Calvet

Delbar

et al. 2020

Landscape and Urban Planning

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Urbanization leads to land-use changes and landscape fragmentation, impacting natural habitats and their connectivity. In principle, many local decision-makers are obliged to adopt a mitigation hierarchy whereby development projects must be designed to avoid impacts on biodiversity, reduce, and ultimately compensate for the remaining impacts to reach the goal of no net loss (NNL) of biodiversity. In practice, however, both developers and regulators lack relevant practical tools to support their strategies to better anticipate and plan this mitigation hierarchy. More importantly, the available tools generally ignore connectivity issues and ecological constraints. Here, we propose an original methodology that anticipates future urban needs under different development scenarios and selects the most relevant strategies for biodiversity offsets (BO). We used a spatialized digital simulator (called SimUrba) to model fine-scale urban dynamics, combining it with ecological networks modelling based on graph theory to assess the environmental impacts of urbanization on a habitat connectivity index for focal species. We test the different outcomes produced by adopting two offset ratios (1:1 and 2:1) using this approach. The methodology is applied to empirical data on the future urban sprawl of a large French city up to 2040 under two realistic development scenarios currently discussed by policy-makers, and on 20 species that we grouped by type of habitat. Our results reveal that that the most highly impacted species are those associated with open and semi-open areas, and cultivated plots. Then, we identify the most promising cells for BO implementation to compensate for negative effects on habitat area, according to gains in habitat connectivity. We further show that using both private and public land can maximize habitat connectivity by including larger plots and reducing the number of plots needing long-term monitoring. Finally, we demonstrate that using standard offset ratios that ignore connectivity issues is very risky and can compromise any BO objective. Overall, we show that this framework provides decision-makers with a valuable and precise strategic tool that articulates land-use planning with ecological constraints to identify whether, how and where NNL objectives can be achieved.

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Environmental impact assessment of development projects improved by merging species distribution and habitat connectivity modelling

Cited by 53 publications

References 85 publications

Maximizing habitat connectivity in the mitigation hierarchy. A case study on three terrestrial mammals in an urban environment

Maximizing habitat connectivity in the mitigation hierarchy. A case study on three terrestrial mammals in an urban environment

Predicting distribution of Zanthoxylum bungeanum Maxim. in China

Integrating a landscape connectivity approach into mitigation hierarchy planning by anticipating urban dynamics

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