- OSUR: https://osur.univ-rennes1.fr
- Team leaders:
- Jacques Baudry: firstname.lastname@example.org
- Françoise Burel: email@example.com
- Team leaders:
- Universidad polytecnica de Madrid: http://www2.montes.upm.es/
- Team leader:
- Miguel Marchamalo: firstname.lastname@example.org
- Team leader:
- Université catholique de Louvain: https://www.uclouvain.be/239886.html
- Team leader:
- Thierry Hance: email@example.com
- Team leader:
- Université de Picardie Jules Verne: www.u-picardie.fr/edysan/
- Team leader:
- Annie Guiller: firstname.lastname@example.org
- Team leader:
Connectivity patterns and processes along a gradient of European landscapes with woody vegetation and spatial heterogeneity : Woodnet
A BIODIVERSA Project (accepted June 2016) http://www.biodiversa.org/.
Keywords: remote sensing, permeability maps, connectivity models, bears, carabids, Iberian lynx, plants, biocontrol, scientific uncertainties, policy design
WOODNET aims at providing innovative spatially-explicit tools for connectivity analysis along a range of landscapes from forest and shrubland to agricultural landscapes where woody vegetation elements play a key role for conservation or service delivery. Novel satellite images at different resolutions, permitting to describe the internal structure of landscape elements, will produce improved resistance maps, considering landscape characteristics at different scales, and supported by species empirical data and models of habitat suitability, resource selection and landscape genetics. New connectivity models based on a diversity of possible pathways for species movements through landscapes will be produced. WOODNET also considers the effect of landscape legacies (past connectivity) on current species distribution. The biological models are diverse, from bears and lynx for large landscapes dominated by forests or shrublands to beetles, plants, birds and damselflies for landscapes characterized by hedgerows. We will provide new tools for enhancing connectivity analysis of a diversity of functional networks, together with an evaluation of the synergies and antagonisms among them. We will, for arable crops, study how landscape connectivity drives the distribution of pest and beneficial arthropods and the associated (dis)services. The project also discusses science-policy interface and legal connectivity issues, focusing on how law may integrate both connectivity science, stakeholders knowledge and scientific uncertainty to inform green infrastructure (GI) policy and provide for adaptive management. This is an important point for discussion with stakeholders. We will decipher the different sources of scientific uncertainties, and their consequences on the design of the legal framework of GBIs. The involvement of stakeholders at different scales will permit to further discuss the links between research design and its outputs on GBIs implementation and management.
GREEN Infrastructures in our study sites: a diversity on site size related to the size of the wooded elements, from fine hedgerows to coarse forests.
Study areas/countries covered by the project
We will consider different types of landscapes characterized by a diversity of patterns of wooded vegetation.
In Spain, three landscapes characterized by the abundance of woodland patches. One in the Cantabrian Range (NW Spain) composed mainly by a mosaic of patches of deciduous forest, shrublands, pastures and croplands. This will be the study area where presence records and landscape genetic data for the brown bear (Ursus arctos) will be used to develop landscape permeability and connectivity models. The study area of the Cantabrian Range (NW Spain) has a total extension of about 3,000,000 ha and includes parts of the regions of Asturias, Cantabria, Galicia and Castilla and León (provinces of León, Palencia and Burgos). The study area covers the whole known range of the brown bear native populations in Spain, and its peripheral zones where future population expansion may be likely (buffer of ~ 25 km around current species range).
Two landscapes in Montes de Toledo and Sierra Morena (center and south Spain), where Mediterranean woodlands are mixed at fine spatial scales with agricultural lands and other human-made land covers. These will be the study areas where the telemetry data (GPS collars) for the Iberian lynx (Lynx pardinus) will be used to develop landscape permeability and connectivity models. Sierra Morena is located in the region of Andalucía and hosts the largest Iberian lynx populations in all the Iberian Peninsula. Montes de Toledo is located in the region of Castilla-La Mancha. The total extent of the areas covered by lynx populations is of about 85,000 ha in Sierra Morena and of about 40,000 ha in Montes de Toledo.
In France and Belgium, six agricultural landscapes: 1) a landscape characterized by a gradient of hedgerow network density and dairy farming based on grass, maize and wheat in Brittany (France), 2) Similar landscape in the Picardie plain where hedgerows have been planted 20 years ago; 3) Thierache … 4) Three sites along a gradient of agricultural landscape in Belgium presenting different levels of hedgerow and woody elements that will be quantify in the Hainaut and Walloon Brabant. The soil will be similar for all the conditions.
In Brittany, France, the study area is the “Zone Atelier Armorique” (https://osur.univ-rennes1.fr/za-armorique/), a member of the French network of Long Term Ecological Research sites. It has been established in 1993 and focuses, for the rural part, on the dynamics of hedgerow networks and the associated crop mosaics, their consequences on biodiversity and how the dynamics are driven by farming activities and policies. The research team of OSUR has a large experience of interdisciplinary research in this area. The landscapes present different types of structural connectedness and a large set of biodiversity data is already available. (web site of metadata soon available). Biodiversity questions are on conservation (plants, carabids) and ecosystem services, mainly biological control.
In Picardie, France, The Thiérache region is a rural area located in the NE of the Aisne department in northern France (centred at: 49°56′ N, 3°54′ E). The climate is humid Atlantic. The geological substrate consists of Cretaceous calcareous chalks, marls and clays, largely covered by Quarternary loess. A century ago most of the population worked in those sectors. The Thiérache landscape by the late 18th century was characterized by open field agriculture for grain cultivation. Grassland-dominated and arable field-dominated landscapes are located in the administrative subdivisions of the N and NE and of the S and SW, respectively.
For the purpose of Woodnet, a 5x5km landscape window will be selected within this area, dominated by grasslands enclosed by a dense hedgerow network (ca. 150 km cumulated length), also comprising small forest patches and arable lands. Most hedgerows were planted during the 19th century with pollarded hornbeam (Carpinus betulus) forming a tree line, and hawthorn (Crataegus monogyna) a sub row.
In Belgium,the study area is located in the province of Hainaut and Walloon Brabant, , which have varied kind landscapes from areas of intensive agriculture to more extensive areas with hedges, permanent grasslands and small wooded areas. The province of Hainaut is close to Picardy and offers the same type of landscape and socio-economic activities that Picardy and Brittany workshop area. In addition, we will especially follow a farm in reconversion to agro-ecology which has conducted numerous replanting of hedgerows and had divided plots using grassy strips. Preliminary data exists on ground beetles and parasitoids in that farm and adjacent intensive field.
Our main goal is to decipher the features of the GBIs that determine their support for biodiversity and ecosystem service delivery, sub-theme T2.1 of the call (links to the call in italic in parentheses).
Therefore, we will:
- analyze in a consistent framework the diversity of landscape structures characterized by woody vegetation elements, across Europe and several associated ecological networks. (influence of landscape structure and management)
- validate the newly launched satellites (Sentinel) to analyse vegetation and landscape structure
- improve connectivity models by a better integration of landscape structures and their dynamics at different scales using different biological models and a consideration of alternative routes for movement across landscapes. (influence of GBIs on a range of species and functional groups)
- utilize landscape genetics with plants, carabids, bears. (study of gene flow)
- develop of a methodology for linking connectivity and ecosystem services using standardized microcosms. (delivery of services)
- make the relationships between connectivity services in a conservation frame and biological control
- screen the scientific evidences supporting connectivity to make policy makers aware of uncertainties in the development of evidence based policies and legal frameworks. (involvement of stakeholders and end-users)
- establish a dialog between conservationist and plant protection specialist regarding woody element of the landscape
- enhance discussion and information sharing between disciplines and with stakeholders. (interdisciplinarity)
Hypotheses (H) and research questions (RQ):
H1) The incorporation of the internal structure of landscape elements will improve the prediction of connectivity models. The wide range of remotely sensed images in terms of spatial, spectral and time resolutions is underused or unexplored in landscape characterization, particularly those coming from recently launched sensors (Sentinel 1-2), as well as Lidar and radar (SAR) images.
H2) The consideration of the overall landscape structure (grain, heterogeneity) to produce landscape permeability maps improves the prediction of connectivity models, when compared to permeability maps based on one value per type of land cover.
H3) Landscape legacies must be considered in the relationships between species distribution and landscape structure.
H4) The incorporation of a biodiversity componentin resistance maps, as derived from suitability maps improve connectivity models (Zeller et al, 2012).
RQ1: These three hypotheses will be treated by an overarching research question 1:How can remote sensing data and connectivity models be optimized for Green Infrastructure conservation planning over a range of spatial resolutions, temporal scales, landscape patterns and species traits?
H5) The potential and delivery of ecosystem services depend on landscape heterogeneity at different spatial and temporal scales (Mac Fayden et al, 2015). Landscape heterogeneity is itself a consequence of connectivity elements present in a global landscape matrix, as measured in the previous question. For biological control, semi-natural habitats may act as refuges for useful natural enemies or for pests; connections among them insure the continuity of the presence of beneficial arthropods and pests, as well (Schellhorn et al, 2015).
RQ2: How does the provision of ecosystem services of conservation and regulation vary along a gradient of landscapes characterized by different connectivity between wooded elements (forest, hedgerows) and different spatial heterogeneity?
H6)The different conceptual approaches of protocols for sampling or data analysis are a major source of uncertainty in connectivity science; each has blind spot to be made explicit. A single observation of species distribution at a given time cannot incorporate fluctuations in species distribution and use of the landscape that occur seasonally or in different years.These blind spots must also be identified and treated as important elements when using scientific evidences to design public policy and legal frameworks.
RQ3: How to incorporate and manage the scientific uncertainties and their dynamics into policy models and legal frameworks for green infrastructure implementation, and how to interact with stakeholders about these uncertainties at different decision levels (European, national and local)?
1) in the design of the network of study sites and species models. We will do the research on deliberately different and contrasted landscapes and will use a diversity of species groups (from plants to bears) to cover a wide range of situations. Therefore, we will have a better test of our methods and results encompassing a wide range of situations.
2) From a methodological standpoint, four novelties:
- i) the use of remote sensing to describe the internal structure of landscape elements, including images from recently launched optical and radar satellites; novel types of landscape permeability maps including the structure of landscape elements and landscapes at different scales in space and time; Several authors make a plea to increase the use of remote sensing to better understand biodiversity dynamics (Rose et al, 2015), and the developments become urgent (Pettorelli et al, 2015).
- ii) The development of connectivity models based on resistance maps constructed from empirical data for on landscape factors driving species distribution, therefore allowing evaluating commonalities and differences across taxa. The models will be general enough to accommodate the difference in the scale behavior (extent and spatial and time resolution of species) (Coulon et al, 2015).
- iii) the combination of landscape genetics and novel connectivity models.
- iv) the use of microcosms experiments will be used to relate wooded structure connectivity and ecosystem services (pest control).
3) for policy making, law design and implementation, the analysis of uncertainty sources using the different remote sensing and ecology protocols and products will show the problems and will provide guidelines on how to reduce these problems. Looking closely at the process of building the legal standard for the protection of GBIs from the scientific evidences is a real challenge.
|Work packages (WP) – Title only, detailed descriptions should be included in the project description section|
|No. of WP||Responsible Partner||Title|
|0||Jacques Baudry (OSUR)||Project management|
|1||Laurence Hubert-Moy (OSUR)||Relationships between landscape characteristics derived from remote sensing images and species distribution|
|2||Annie Guiller (UP-JV)||Landscape legacies and species distribution|
|3||Thierry Hance (UCL)||The effect of wooded networks of biological control in crops: synergy or antagonism|
|4||Santiago Saura (UPM)||Modelling connectivity and landscape resistance to movement|
|5||Alexandra Langlais-Hesse (OSUR)||The science/policy interface: Incorporation of scientific uncertainties into policies|
(Use as many lines as needed)
Relationships between the work packages: arrows indicate the main flows of information between work packages and tasks
WP01: Relationships between landscape characteristics derived from remote sensing images and species distribution (responsible: L. Hubert-Moy)
This WP is the foundation of the project, the basis to characterize landscapes and landscape elements (structure of hedgerows and forest, growth of crops). Few ecological studies use remote sensing data to assess the biophysical or structural properties of vegetation to understand species distribution. To date, most studies use optical images, while synthetic aperture radar (SAR) and Lidar data are under-exploited for ecological applications. To demonstrate their complementarity, we will run joint and purposefully developed analysis of remote sensing images maps to find the landscape metrics and threshold values with a better match and predictive ability for the biodiversity data. We will take advantage of the new satellite imagery available over Europe (Sentinel 1 & 2) to have a consistent landscape analysis.
Task 1.1: analysis of the characteristics of remotely sensed images for production of land-cover maps from Sentinel 1 & 2 images (responsible: P. Defourny)
The objective is to study the synergy between high resolution optical and radar time-series to produce land cover maps. Land cover and crop type classification along the season will be performed on three sites(Belgium site, France PF, France Amiens)based on polarimetric parameters backscattering coefficients reflectances, and biophysical variables, retrieved from Sentinel 1 & 2 high-resolution time series, using data fusion methods.
Task 1.2: analysis of the characteristics of remotely sensed images for the study of intra and inter-annual dynamics of crop vegetation covers from Sentinel 1 & 2 images (responsible: L. Hubert-Moy)
We will focus on the monitoring of the intra and inter-annual dynamics of vegetation covers using information related to their biophysical properties (i.e. Leaf Area Index, crop phenology, yield, biomass…) or to their structural properties (i.e. vegetation density, architecture) using optical and radar time-series, respectively, and agro-meteorological modelling. These indicators will be calculated using in field collected information to calibrate and validate the model (SAFY-WB model). The yield model will on be run in Brittany, while the phenology model will be run on all agricultural sites.
Task 1.3: deriving metrics of vegetation and landscape structure from various images(responsible J. Baudry)
For the woody vegetation structure, at the core of the project, we will quantify woody vegetation structure heterogeneityusing very high spatial resolution radar images (TerraSAR-X) according to the method proposed by Betbeder et al (2014) combining field measurement of canopy structure with phemispherical photographs and image analysis (Shannon Entropy). Hedgerow structure in will measured in France and Belgium. This will help to test the generality of metrics extracted from radar images.
In Spain and Brittany, the sites where LIDAR images are available, we will derive evaluate the contribution of 3D information derived from Aerial LIDAR (Light detection and ranging) data images to characterize inner heterogeneity of woody vegetation of forest and hedgerows. For that purpose, we will compare LIDAR data with TerraSAR-X data for hedgerow characterization in the Brittany site, and LIDAR data with Sentinel 1 data for forest characterization in the Spain.
For landscape metrics, we will evaluate the quality and the complementarities of the indicators derived from Sentinel-1 and Sentinel-2 time-series on all study sites to develop new landscape metrics in order to characterize landscape intra-annual dynamics. The TerraSAR-X images can also be used to characterize hedgerow networks (Betbeder et al 2014).
Task 1.4: data collection and management for the Iberian lynx and brown bears (responsible: M.C. Mateo-Sánchez)
For the brown bear, we will use existing species presence records and landscape genetic data available since 2000. For the Iberian lynx, telemetry data acquired through GPS collars between 2008 and 2015
Task 1.5: data collection and management for plants, carabids, damselflies, birds in hedgerows (responsible S. Croci)
In Brittany and Picardy, several sets of data exist on plants and carabids with repeated sampling at several years interval since 1994. (https://osur.univ-rennes1.fr/za-armorique/news.php). The metadata of available data will be online starting in January (OSURIS.fr). They will be completed as to cover the diversity of situations revealed by the analysis of remote sensing images. Data on birds will be collected to compare their requirement in terms of hedgerow structure to plants and carabids. the permeability of hedgerows. Data on dragonflies will allow the analysis of the permeability of hedgerows along streams.
Task 1.6: data analysis of the relationships between maps of metrics and biodiversity data to produce habitat suitability maps (responsible L. Hubert-Moy, P. Defourny, C. Mateo-Sánchez,S. Croci, A. Alignier and J. Baudry,)
We will test the different metrics and their combination at patch (hedgerow, forest) and landscape scales derived from the remotely sensed data to explain the spatial distribution of plants and carabids for each type of remote sensing data (Sentinel 1 and 2, Radar and Lidar) (Betbeder et al, 2015). Then we will build habitat suitability maps (i.e. maps where potentially the various groups of species can live in hedgerows, forested areas, and crops). Those habitat suitability maps will then be used to model landscape permeability and connectivity in WP04.
We will ensure that the input data were quite balanced between presence and absence data. We will reduce the set of predictor variables by model selection (e.g. upon AIC criterion). The most relevant predictors will then be used to model habitat suitability maps over all studied sites where the taxa were censed. Then, we will assess the accuracy of our habitat suitability maps either by field censuses or bootstraps methods.
WP02: landscape legacies and species distribution (responsible A. Guiller)
Task 2.1.: Understanding the role of connectivity dynamics on the biodiversity: specific and functional approach(responsible A.Alignier, A.Ernoult and C.Mony)
We will investigate the effect of landscape connectivity changes on species (plants and carabids) assemblages i.e. time lag in biodiversity responses. Past landscapes (with a focus on wooded elements i.e. woodlots and hedgerow networks) will be mapped and characterized from aerial photographs, at 5 dates, since 1952 until today. We will investigate the contribution of past connectivity relatively to present connectivity measures and local hedgerow characteristics (both from WP1) in structuring plant and carabid assemblages (surveyed in WP1) by using multivariate trajectories for landscape dynamics. Using a functional approach through plant trait databases, we will test the hypothesis that plant extinction debt or immigration credit may depend on plant species reproductive strategies (i.e. investment in sexual reproduction, vector type, dispersal distance, seed bank duration,…). Results from this task, by showing how connectivity dynamics may affect species assemblages, will contribute in improving the performance of models by adding a temporal component (WP4).
Task 2.2Disentangling dispersal from recruitment limitation in hedgerow corridors (responsible Guillaume Decocq and Aude Ernoult)
The absence of forest species in recent hedgerows may be the consequence of intrinsic low dispersal capacities of species and/or lack of landscape connectivity (i.e. dispersal limitation) or the unsuitability of local environmental conditions for the establishment of forest species due to low habitat quality (i.e. recruitment limitation). Only dispersal limitation can be reduced over time by increasing connectivity. In this task, we aim at disentangling dispersal from recruitment limitation of forest species in recent hedgerows by conducting a controlled experiment. From WP1.4, we will select a range of 5 forest fragments and connected hedgerows in both study regions to implement plant transplantation experiments. We will select 10 vascular forest plant species, absent of these hedgerows (but present in surrounding forest fragments) and exhibiting contrasted life-history traits based on the floristic data acquired in WP 1.4. and the functional approach developed in WP 2.1. Adult plant and seeds will be collected from local populations in selected forest fragments or near the study sites. 100 seeds will be sown and 15 adult plants for each species will be transplanted in five hedgerows connected to each forest fragment. A monitoring will be implemented twice a year (Spring and late Summer) to record germination (seeds), survival (transplants), growth and fertility/fecundity (all plants), at different distances from the forest fragment. In parallel seed germination rate will be quantified in greenhouse conditions. Species that are dispersal-limited are expected to germinate, grow and reproduce well, while those that are recruitment-limited are not.
Task 2.3: Measuring landscape connectivity: a landscape genetic approach (responsible A. Guiller)
Objective of this task is to quantify landscape connectivity through indirect estimates of functional connectivity that takes account (i) past and present genetic variation, (ii) dispersal as trait co-variated with other traits such ecological specialization. We plan to explore the relationship between structural and functional connectivity using a set of species with contrasted ecology: two plants and two carabid species, one forest specialist (Primulaelatioras plant and Abax parallelepipedusas carabid (cf Marcus et al, 2014) and one generalist (Geum urbanumfo plants, one carabid not selected yet) and one snail Cepaea hortensiscommonly found in hedgerow (Le Mitouard, 2009). We will also use several markers: cytoplasmic, nuclear and SSR locus.
WP03: The effect of wooded networks of biological control in crops: synergy or antagonism? (responsible: T. Hance)
This WP will be done in wheat fields of the three agricultural zones in Brittany, Picardy and Wallonia
Task 3.1: Evaluation of the population assemblages of species of interest for biocontrol in relation with GBIs structure and Connectivity (Remote sensing and ecology) (responsible Vincent Le Roux and Th. Hance)
Using Landscape analysis from WP1, we will define landscapes with different structures, high, medium and low in wooded structures. Two biological models of natural enemies will be investigated: generalist predators with slow numerical response (Carabid beetles) and specialist aphid parasitoids with high numerical responses. Both are important component of biological control services. During two consecutive years, carabid beetles will be sampled using pitfall traps two weeks consecutively alongside a transect extending from the field margin (with or without a hedgerow) to the field interior (middle of the field, near the field margin and inside the field margin). This will be done at two different dates per season in relation with winter wheat phenology.. Two pitfall traps will be used per sampling point. At the same time, aphid parasitoids will be analysed by collecting mummies on 100 plants that present an aphid colony per field, in the centre and at the field border. We will analyse the species assemblages, diversity, equitability, and food web across the landscape heterogeneity gradient
Task 3.2. Ecosystem disservices delivered by GBIs structure and Connectivity (responsible Vincent Le Roux)
In the same fields, we will quantify three potential pests (weeds, slugs and pest aphids) associated to wooded networks. Sampling will be done along transects extending from the field margin (with or without a hedgerow) to the field interior: For each field sampled, data on agricultural practices will be also collected.
Task 3.3 Ecosystem services delivered by GBIs structure and Connectivity (responsible Joan van Baaren)
The quantification of ecosystem services linked to connectivity element is difficult to evaluate. Recently, using a similar protocol, Wilson et al. (2015) have shown that the level of parasitism on the leafhopper (E. elegantulaOsborn) in Vineyardsby the parasitoid Anagrus erythroneuraeincreased along a gradient of landscape heterogeneity. The originality of our approach will be the use of standardized microcosms to analyse the level of parasitism and the presence of other natural enemies. Microcosms will be constituted of wheat in pot containing the same kind of soil and infested with 50 Sitobion avenaeaphid of stage L2. They will be placed in the crop at three distances from crop edges in part of landscapes characterized by different levels of connectivity already characterized in Task 3.1 and at the same place than task 3.2 and 3.3. In order to evaluate the level of parasitism in relationship with the increase in connectivity elements, these microcosms will be set at two different dates during each season.
Task 3.4:Data collection for phenology and and yield modelling in WP1 (responsible F. Baup)
Cereal yields data(winter wheat) will be produced from the SAR images (Sentinel-1) andcompared between zones taking into account the level of connectivity. The SAPHY model will be used. This will be done in Brittany only due to the heavy requirement of field data to calibrate the model to be created. These agronomic metrics will serve as dependent variables in mixed models and can be also be evaluated using Sentinel images.
Phenology modeling only requires field observations of phenology and will be done on the three sites.
Task 3.5: Overall of connectivity on pest damage and crop production (T. Hance, J. van Baaren, V. Leroux)
This last task aimed at integrate the services and disservices of the increase in landscape heterogeneity to draw new directions of landscape management combining both ecosystems services of biodiversity conservation by implementing a hedged network and biological control. Opposite prediction may be made: 1) for slugs and weeds, an increase in heterogeneity and source habitat should increase their population while 2) Aphid abundance should decrease with and increasing presence of hedges because, hedges may hampered the fly of alate aphid and their landing. In that context, a relationship will be done between reflectance of fields and aphid presence.
WP04: Modelling connectivity and landscape resistance to movement (reponsible S. Saura)
Task 4.1. Estimating landscape resistance from empirical data. (responsible C. Ciudad)
A correct and empirically-informed parameterization of resistance surfaces is crucial to obtain solid ecological insights and efficiently guide conservation management measures. Landscape resistances will be estimated in all the study areas as an inverse of habitat suitability models (generated in WP1: task 1.5). In addition, this task will test the use of different subsets of location records based on space utilization distributions by the focal species, differentiating permanent habitat use by residents (home ranges) and locations corresponding to dispersal or exploration through unfamiliar landscapes.
In the study areas of the Cantabrian Range, Sierra Morena, Montes de Toledo, Brittany and Picardy, additional empirical data will be used to obtain resistance surfaces. These data will allow validating the results from the habitat suitability modelling approach, evaluating the differences in the resistance estimates and, later in task 4.2, exploring their differences in terms of the ecological and management implications of the connectivity models. Landscape genetics and causal modelling (Mateo-Sánchez et al. 2015) will be applied to brown bear genetic samples in the Cantabrian Range. Resource selection functions (Zeller et al. 2014) will be applied to Iberian lynx telemetry data in Sierra Morena and Montes de Toledo. Individual based models (Bergerot et al. 2013) will be applied to carabid data in Brittany and Picardy.
This combination of different remote sensors as inputs for landscape characterization, different empirical species data, and different methods for assessing movement and landscape use will allow determining the best approaches for estimating landscape resistance, as well as providing insight on the costs (e.g. data gathering, staff specialization requirements) and benefits (improved estimates of resistance and connectivity models) for stakeholders and applied management of the different possibilities considered. This will include evaluating the added value of each remote sensing product for improved estimates of landscape resistance.
Task 4.2: Connectivity modelling approaches. (responsible S. Saura)
While the available approaches to identify movement pathways through heterogeneous landscapes require a resistance surface as an input, they differ in their assumptions on species movements and in their practical outcomes. Least cost path modelling (Adriaensen et al. 2003) is one of the most widely used methods, but relies in the strong assumption of optimal, omniscient movement decisions by dispersing organisms. On the other hand, circuit theory (McRae et al. 2008) assumes that individuals move similarly to random walkers: movement decisions are taken locally and the probability of following a particular direction is proportional to the inverse of landscape resistance in that direction. This task will consider both least cost path and circuit-based modelling, as well as other recent approaches that provide a continuum of modelling options in between these two extremes movement modalities (optimal vs. ≈random), with intermediate degrees of exploration and optimization (Panzacchi et al. 2015).
These approaches will be used to (i) generate estimates of effective (resistance-weighted) distance among populations and habitat areas, and to (ii) predict movement pathways through the landscape, including a set of alternative plausible corridors beyond the least cost path. The difference in these results (i and ii) between remote sensing products, resistance surfaces, and modelling approaches will be explored, interpreted, and validated using independent empirical data. These independent data will correspond to species distribution or telemetry data not used in estimating the resistance surfaces, as well as road kill data for the Iberian lynx (> 100 available roadkill records for the species). We will also use additional species distribution data for carabids collected in Brittany since twenty years.
Finally, an evaluation of the practical feasibility and of the uncertainty of connectivity model predictions will be performed in coordination with WP5, considering the availability and cost of acquisition of the required input data and the results for each model.
Task 4.3.Spatiotemporal connectivity. (responsible S. Saura)
Connectivity models generally disregard changes over time and provided a static, single-solution answer for processes that actually change through time. We will (i) assess how seasonal or temporal changes in species distributions may affect the results and performance of resistance and connectivity models, and (ii) develop specific methods for spatiotemporal connectivity analysis based on directional (asymmetric) habitat network models.
Seasonal data and landscape use will be analysed for brown bears in the Cantabrian Range considering the distribution of foraging resources and for the Iberian lynx in Sierra Morena and Montes de Toledo. Different multi-annual periods corresponding to different bear population status and trends (e.g. constrained vs. growing population) will be also considered in the Cantabrian Range. Seasonal and temporal data on changes in crops and hedgerow patterns will be assessed in France and Belgium.
Spatiotemporal connectivity models will be developed based on graph theory and on the generalization of the probability of connectivity metric to directional networks suited to represent dynamic landscapes. The models will explicitly integrate spatial and temporal connections provided by shifting patterns of patches and links. The model will account for the effect of temporary stepping stones that may sustain connectivity to a higher level than what predicted from the typical purely spatial connectivity models that do not consider the temporal interactions and movement possibilities between the habitat patches existing in the different dates.
Workpackage 5 The science/policy interface: Incorporation of scientific uncertainties intopolicies (responsible A. Langlais-Hesse)
The objective is to address some of the legal challenges raised by connectivity conservation (Lausche et al., 2013) which is in the heart of the strategy for green & blue infrastructure (GBI) – defined by the EU Commission as “a strategically planned network of natural and semi-natural areas with other environmental features designed and managed to deliver a wide range of ecosystem services (…)” (EUC, COM(2013)249). We will first question science-law interface issues in the light of the multi-functionality of the GBI concept (task 1). The results of this first step will allow an interdisciplinary thinking on the opportunities and limitations of law for integrating adaptive management concept and tools into GBI strategy (Ruhl, 2006) (task 2).
Task 5.1: The legal challenges of building GBIs: coping with complexity and scientific uncertainty and ensuring public policies consistency (responsible A. Langlais-Hesse)
5.1-1 : Complexity and scientific uncertainties vs accessible law and legal certainty ?
We will first analyze theprocess of buildinglegal standards ofprotectionof ecological continuity on sound science, as it raises legal issuesabout the nature and the complexityof the data,their relevance tothepolicyaim(conservation objectives, restoration, …),the scientific methodology used for setting priorities(the choice of experts, selection of models, mapping methodology,…), the legal significance of scientific outputs (maps and inventories) and the way to address uncertainties in connectivity science, including precautionary approaches and adaptive management. We will start from the science-law interface theories (Naim-Gesbert, 1999; de Sadeleer, 2002; Truilhe-Marengo, 2015) and apply them to our case studies (infra).
5.1-2 : The hierarchy and the role of ecosystem services in the GBI strategy
We will analyze 1) how to deal, from a legal point of view, with the necessary trade-offs between connectivity conservation and the other objectives of GI, each of which may lead to different spatial configurations and conservation measures, and 2) how ecosystem services may play a role to deal with the antagonisms in the design of GBIs. At this end, we will compare French and US law on GBIs and ES, at the light of recent development in legal literature on ES and GBIs. Our hypothesis is that, under appropriate regulation and spatially-explicit priorities, GBI may bring coherent ‘nature-based’ responses to the expectations of potentially conflicting policies (social and economic cohesion, common agricultural policy, Natura 2000, flood control etc.).
Task 5.2: Legal tools and flexibilityfor the implementation of GBIs (responsible Charles-Hubert Born)
5.2-1 : The legal tools: we will investigate, in our case studies, the set of available legal toolsto design and implement GBIs and examine their potential to maintain or restore connectivity (Lausche et al., 2013; Verschuuren, 2015). This will help us to identify legal gaps and inconsistencies for building functionally connected landscapes. “Landscape” indeed holds a special place in all those designs, as it is both a spatial structure and a memory of past actions.
5.2.2 : A legal standpoint on adaptive management: limits and opportunities.
We will finally investigate in which extent law makes possibletheprocess of adaptingconservation policiesto new scientificdata and ecological dynamics through the conceptof adaptive management, as part of the ecosystem approach (COP CBD, Decisions V/6 and VI/12). However, it remains to be seen whether adaptive governance is compatible with legal principles like legal certainty. Research is also needed on how tobuild legal frameworks for effectivemonitoringand evaluation indicators, to define their placein the legalsystem, to investigate the legal consequences of adaptive managementin spatial planning (Ruhl, 2006; Biber, 2013).
The methodological foundations of WP5: our legal study will be mainly based on classical legal research methods (legislations/case-law/literature) together with specific comparative law methods; we will investigate the legal responses brought to connectivity conservation challenges in France, Belgium, USA and, if the budget allows for it, in Australia. Specific cases-studies will be carried out in part or all of these countries through interviews, legal analysis of GBI projects at local and regional scales (e.g., GBI in Rhône-Alpes region in France). Two workshops will be organized, one on science-law interface, the other on comparative law for connectivity conservation in France, Belgium and USA.
Relevance for the identified policy application, importance of the research for solving pressing concerns and/or issues related to biodiversity
This project totally fits the Green Infrastructure (COM(2013) 249 final) of the EU. Woodnet aims at both connecting semi-natural elements to foster species movement and evaluating the regulation services for crop protection. The later point support policies aiming at reducing the use of pesticides. For GBIs, the three major problems are 1) a poor description of landscapes, 2) a difficulty to use biodiversity observations into connectivity models and 3) the dominance of models offering no alternative choices. The dichotomy between “conservation” and “services to agriculture” is also a question to address. Woodnet will decipher some synergies and antagonisms.
The close cooperation between ecologists, geographers and law scientists enhance the chance to design tools, models usable in the making of policies.
Description of stakeholder engagement and identification of end users for project results
Stakeholders are at EU, national and regional levels. At the EU level a two days meeting will organized around month 32 in Brussels with representatives of the commission to discuss the results. At the national level (ministry of environment) they are policy makers. In France, the bureau in charge of the “Trame Verte et Bleue” agreed to organize meeting with us. At the regional levels, we work with the Brittany Region which finances projects with NGOs, consultants and local administration in charge of the plan for ecological networks. Our role is to help in the development of methods. The NGO Bretagne Vivante which federates naturalist associations is interested in developing procedure to make the best use of data collected. In Picardy and Brittany, strong relationships with the chamber of agriculture exist since previous projects.
In Spain, Brown Bear Foundation, WWF-Spain and the Regional Governments of Castilla y León and of Andalucía will be engaged as strakeholders, all of them with direct interest in the methodologies to be developed and results to be obtained in the study areas where they carry management, conservation and restoration actions aimed either to particular endangered species or to a broader landscape planning perspective. All of the Spanish stakeholders will provide expert-based feedback to the project. In addition, three of these stakeholders (Regional Governments of Castilla y León and of Andalucía and Brown Bear Foundation) will provide data of high importance for the development of the foreseen activities, such as telemetry and presence data for the Iberian lynx and brown bears respectively.
In Belgium, we will invite the NGOs of Nature protection and farmers associations. The team also work with the ministry of environment of Wallonia.
So, each team will work with its regional stakeholders and two meetings will be organized at the project level. The first to discuss the practical issues stakeholders meet when implementing GBIs. These issues will be taken into account in the development of methods and the analysis of legal issues. The second meeting, toward the end of the project will present the major outputs of the research as well as the products of the regional interactions. The later will include publications in magazines, and, in some instances co-production of operational methods (projects financed outside of Biodiversa).
Proposed exploitation of project results
The results will be 1) publish in scientific journals in various disciplines and interdisciplinary journals; 2) used in workshops with policy makers to publish reports on their potential use; 3) adapted to the general public on websites and 4) incorporated in academics courses at the university level and on line.
The protocols (including scripts of analysis) and models, an important part of the products, will be public, available on various websites the WOODNET site as well as OSUR, CONEFOR.
All teams are in universities, therefore teaching at graduate and undrgraduate levels, as well as in continuing education, will be straightforward.
Knowledge transfer, communication of results to practitioners, policy- and decision-makers: See communication plan
European added value of the proposed research (including overseas)
Compare to national approaches, WOODNET has a real European added value for three points: 1) it covers a broad climatic and landscape gradient; 2) it compasses a wide range of national and regional policies; and 3) it brings together leading teams from different countries. It is also a good opportunity to train students and post-doc in a EU network.
GBIs are also, very often termed as Ecological Focus Areas EFA) in the Common Agricultural Policy implementation. J. Baudry led the group of expert on EFA and the service they deliver to production within the European Innovative Program (EIP-Agri). It clearly appears a need to have a European view of the GBIs to understand their role for nature conservation and services to crop production. This project dealing with these two aspects is a step forward.
IV.B. Communication plan
- Who will receive results
The results will be of interest to different end-users.
First of all academia will benefit of the conceptual and methodological advances as well as novel empirical results. The models and protocols will be publically available.
Consultants, public bodies (ministries, regional and local administration), as well as NGOs will benefit from both the advance in modeling and the outputs of work with stakeholders.
Online courses on “planning for connectivity” can be proposed on various platforms, e.g. ENVAM, a french e-university in environment (envam.org). Its director is the leader of WP1. All teams being involved in teaching in universities, the results will be incorporated in curriculum.
The project will have a website to inform of the progress and news and post leaflets. We will also use the metadata website of the OSUR () to post the metadata of the project in real time. We will use a metadata form compatible with the INSPIRE directive.
- What, why, when and how
As is usually the case there will be a time lag between the onset of the work and the publication of results. However, we expect the first publications in remote sensing to be ready at the end of year one.
For the stakeholders, information can be disseminated through their magazines and websites, after each meeting. The stakeholders involved in the project use either French or Spanish at the national, regional levels, English being used for the EU level. Therefore the different teams will produce material related to the finding of the different countries in the adequate language.
- Planned publications (scientific and other) and expected impact
Scientific publications will target major remote sensing, ecology, landscape science, and environmental policy journals. Rapid results on novel source of satellite imagery (sentinel) or barely used in ecology (TerraSAR) will strengthen the emerging research community in remote sensing and conservation. In ecology, the results will be relevant to both the basic understanding of the role of landscape structure and heterogeneity on the composition, structure and function of living communities and the more applied aspects of ecosystem service management (nature conservation, pest regulation). In the policy domain, a better understanding of the construction of the scientific evidences will lead to better consideration of limits and potentialities of laws and policies to regulate biodiversity. Finally two papers on interdisciplinarity will be produced, one on the conceptual and theoretical constructs and one on the practical aspects in policy design and implementation.
- Timelines for open access to data and how
Foreseen timeline for open access is 5 years after project completion. The access will be provided on the metadata server.
V. Time schedule and working programme (use a Gantt chart or equivalent)
Gantt chart summarizing the chronology of the working program: in pink activities related to Work Package 1, in blue to Work Package 2, in light brown to Work Package 3, in green to Work Package 4 and in red to Work Package 5. In yellow coordination, management, analysis and write up tasks by the coordinator (orange squares primary meetings, light orange squares secondary meetings; squares with F refer to period of field work, without F refer to preparation of field work, analysis and write up of results. In WP5, M indicates the dates of the seminars between ecologists and law scientists.
VIII. Description of project management
The three major challenges of the project are to insure 1) the consistency of the conceptual framework with a diversity of types of ecological networks under study, 2) that the deliverables necessary to the connections among the work packages are delivered on time, and 3) that science/ policy / end user interactions are effective.
As for the first challenge, the project will be managed by a senior scientist (J. Baudry) who has a large experience in landscape ecology and the management of long term interdisciplinary projects, as the Zone Armorique (a member of the French LTER network) and programs (DIVA, Public Action, Agriculture, Biodiversity of the ministry of environment, currently dealing with ecological networks). He has published on every topic of the project. J. Baudry will manage the project with the group of WP leaders (all ofthem team leaders) plus F. Burel, a leading landscape ecologist with a large experience in interdisciplinary projects.
The project management necessitates two basic documents: 1) a memorandum of understanding (MoU) on data sharing and management as well as publication agreement strategy and 2) a work flow document presenting the linkages among deliverables to set the dates of delivery. In Woodnet, WPs are not independent clusters of tasks. What is expected from one WP from other WP to run the different tasks is crucial; therefore the variables to be used in each task must be described in detail. For instance, modeling crop phenology and yields in WP01 is based on field observations from WP03 for calibration. The workflow document is the basis for the Ghantt chart. It will be completed during the first general meeting planned within three months after the project start.
To insure the consistency of the analysis of remote sensing images, which is needed in all sites, the task is divided in two teams (Rennes and Louvain) each running the analysis for different types of remote sensors and images. Connectivity model development is under the responsibility of a single team (its leader, S. Saura, is also recognized worldwide for its models). That insures consistent outputs across sites. In Rennes and Louvain, two post-doc in remote sensing with basic knowledge in ecology will be hired as the success of these tasks is crucial. For connectivity modeling a post doc will be hired with specialization in modelling landscape resistance to movement and producing spatial products with putative movement pathways and their validation.
The diversity of “model species and landscapes” is a novelty compared to most project sharing biodiversity data collection protocols. The purpose of the project is to cover a large range landscapes and species. It also makes the management easier as the data gathering and some of the analyses on the different groups are independent and carried out by teams with extensive experience in each individual landscape or species. The use of satellite images and connectivity models are common to all sites.
Strength of the project is that several sets of biodiversity data are available. Therefore, by starting the project in October, we will do the first analysis of remote sensing images (sentinel 1 &2) to run the first habitat suitability models. From those some connectivity models could be start to be developed already at a relatively early stage of the project development. This will permit to prepare additional biodiversity sampling (plants, carabids, birds and dragonflies for WP01 and experiments for WP03) for spring 2017 and subsequent modeling and comparisons.
Field work in ecology will be under the responsibility of scientists’ specialist for each species group. Master students will be hired to complete the tasks.
Different loops will be organized between WPs. A core feature of Woodnet is the making of habitat suitability maps (HSM) in WP01 & 02 as a basis of resistance maps (RM) in WP4 (although other empirical data sources and methodological approaches different from suitability models will be also evaluated and compared in WP04). Each time a novel satellite image is produced and analyzed, a new HSM will be generated. Connectivity models will be run for each resistance map and tested. The result of the model will feedback WP01 & 02 each time a better model is yielded. Meanwhile, the assumptions, the blind spots and the uncertainties at each step will be recorded as an input to WP05. These analyses will enhance interdisciplinarity as everyone will have to question every other researcher on her/his choices.
WP5 will benefit from the input of two law PhD students starting in the fall 2015 and finishing in 2018 working on “environmental laws and ecological processes”. They are both under the co-supervision of the WP5 leader and one with the project coordinator, the other with the leader of the OSUR team.
The project coordinator will organize, in coordination with WP leaders the general annual meeting as well as specific meeting on topics as “habitat suitability analysis”, “connecting field observations and remote sensing observations”, “connectivity modeling”, “mapping of ecological networks” etc.
The project coordinator will also organize the interactions with the stakeholders at different scales. He has committed time for that in different projects (time not included in this proposal) at national and regional levels. A meeting at the EU level (month 32) to communicate with the commission is also planned.
The output of the interactions with stakeholders will be posted on their websites.
To maintain the communication among partners, a private storage place will use to store minutes of all meetings, protocols and data that can be shared.
III. Scientific publications
Top 5 recent scientific publications of the applicants relevant to the application
Please, consult your Funding organisation Contact Point to be sure about the eligibility of your publications
In the following table, please specify the names and countries of each Partner.
|1. Vannier, C., C. Vasseur, L. Hubert-Moy & J. Baudry (2011). “Multiscale ecological assessment of remote sensing images.” Landscape Ecology26: 1053-1069.
2. Betbeder, J., L. Hubert-Moy, F. Burel, S. Corgne & J. Baudry (2015). “Assessing ecological habitat structure from local to landscape scales using synthetic aperture radar.” Ecological Indicators 52(0): 545-557.
3. Andrade, T. O., Y. Outreman, L. Krespi, M. Plantegenest, A. Vialatte, B. Gauffre & J. Van Baaren (2015). “Spatiotemporal variations in aphid-parasitoid relative abundance patterns and food webs in agricultural ecosystems.” Ecosphere 6(7): art113.
4. Favre-Bac, L., Ernoult, A., Mony, C., Rantier, Y., Nabucet, J., Burel, F. (2014). “Connectivity and propagule sources composition drive ditch plant metacommunity structure.” Acta Oecologica 61(0): 57-64.
5 Langlais, A. 2012 Le droit de la biodiversité à l’aune du développement durable ou l’ouverture à de nouvelles formes d’équité environnementale ? L’exemple controversé de la compensation écologique », Agnès Michelot (dir.), Equité et environnement, Langlais, A. & Hervé-Fournereau, N. Quel(s) modèle(s) de justice environnementale ?», Bruxelles, éd. Larcier, pp. 231-258.
|1. Rubio, L., Bodin, Ö, Brotons, L. & Saura, S. 2015. Connectivity conservation priorities for individual patches evaluated in the present landscape: how durable and effective are they in the long term? Ecography 38: 782-791.
2. Mateo-Sánchez, M.C., Balkenhol, N., Cushman, S., Pérez, T., Domínguez, A. & Saura, S. 2015. A comparative framework to infer landscape effects on population genetic structure: are habitat suitability models effective in explaining gene flow? Landscape Ecology 30: 1405-1420.
3. Santini, L., Saura, S. & Rondinini, C. 2015. Connectivity of the global network of protected areas. Diversity and Distributions (in press). DOI 10.1111/ddi.12390.
4. Saura, S., Bodin, Ö. & Fortin, M.J. 2014. Stepping stones are crucial for species’ long-distance dispersal and range expansion through habitat networks. Journal of Applied Ecology 51: 171-182.
5. Gurrutxaga, M. & Saura, S. 2014. Prioritizing highway defragmentation locations for restoring landscape connectivity. Environmental Conservation 41: 157-164.
|1. Astudillo Fernandez, A., Hance, T., Deneubourg, J.L, 2012. Interplay between Allee effects and collective movement in metapopulations. Oikos, 121 (6) : 813-822.
2 Hance, T., Demeter, S., Le Roi, A., Walot, T., Rouxhet, S., Thirion, M., Mulders, Ch., 2010. Agriculture et Biodiversité. Collection Agrinature, Direction générale opérationnelle de l’agriculture, des resources naturelles et de l’environnement. SPW, Namur, 203 pp.
3 Matton N, GS Canto, F Waldner, S Valero, D Morin, J Inglada, M Arias, S Bontemps, B Koetz, P Defourny . (2015). An Automated Method for Annual Cropland Mapping along the Season for Various Globally-Distributed Agrosystems Using High Spatial and Temporal Resolution Time Series. Remote Sensing 7 (10), 13208-13232
4. Waldner F, MJ Lambert, W Li, M Weiss, V Demarez, D Morin, C. Marais-Sicre, O Hagolle, F Baret, P Defourny, 2015.
5 Lausche B., D. Farrier, J. Verschuuren, A.G.M. La Vina, A. Trouwborst, Ch.-H. Born & L. Aug, 2013. The legal Aspects of Connectivity Conservation. A Concept Paper, IUCN Environmental Policy and Law. Paper n° 85, vol. 1, Gland, Switzerland, 2013, xxiv + 190 pp.
|Jamoneau A, Sonnier G, Chabrerie O, Closset-Kopp D, Saguez R, Gallet-Moron E, Decocq G. Drivers of plant species assemblages in forest patches among contrasted dynamic agricultural landscapes. Journal of Ecology 2011 ; 99 : 1152-1161.
Jamoneau A, Chabrerie O, Closset-Kopp D, Decocq G. Fragmentation alters patterns of beta-diversity within forest metacommunities. Ecography 2012 ; 35 : 124-133.Chabrerie O, Jamoneau A, Saguez R, Decocq G. 2013 Maturation of forest edges is constrained by neighbouring agricultural landscape management Journal of Vegetation Science ; 24: 58-69.
Le Mitouard, E., A. Bellido, A. Guiller & L. Madec (2010). “Spatial structure of shell polychromatism in Cepaea hortensis in relation to a gradient of landscape fragmentation in Western France.” Landscape Ecology 25(1): 123-134.
Sonnier G, Jamoneau A, Decocq G. 2014 Evidence for a direct effect of age and isolation on functional plant diversity in forest fragments. Landscape Ecology ; 29: 857-866.
Bernhardt-Römermann M, Baeten L, Craven D, De Frenne P, Hedl R, Lenoir J, Bert D, Brunet J, Chudomelova M, Decocq G, Dierschke H, Dirnböck T, Dörfler I, Heinken T, Hermy M, Hommel P, Jaroszewicz B, Keczynski A, Kelly DL, Kirby KJ, Kopecký M, Macek M, Malis F, Mirtl M, Mitchell FJG, Naaf T, Newman M, Peterken G, Petrik P, Schmidt W, Standovar T, Toth Z, Van Calster H, Verstraeten G, Vladovic J, Vild O, Wulf M, Verheyen K. 2015 Drivers of temporal changes in temperate forest plant diversity vary across spatial scales. Global Change Biology
Other relevant publications (max 1 page, Arial font, 11 pts, single spaced, margins of 1.27 cm)
By the applying research group:
Fieuzal, R. & F. Baup (2015). Estimation of sunflower yield using multi-spectral satellite data (optical or radar) in a simplified agro-meteorological model. Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International, IEEE.
Bergerot, B., Tournant, P., Moussus, J-P., Stevens, V. M., Julliard, R., Baguette, M., Foltête, J-C. 2013. Coupling inter-patch movement and landscape graph to assess functional connectivity. Population Ecology55: 193-203
Lausche, B., Farrier, D., Verschuuren, J., La Viña, A.G.M., Trouwborst, A., Born, Ch.-H., Aug L., 2013. The Legal Aspects of Connectivity Conservation. A Concept Paper, IUCN, Gland, Switzerland. xxiv + 190 pp.
Mateo-Sánchez, M.C., Balkenhol, N., Cushman, S., Pérez, T., Domínguez, A., Saura, S. 2015. A comparative framework to infer landscape effects on population genetic structure: are habitat suitability models effective in explaining gene flow? Landscape Ecology30, 1405-1420.
Other references relevant to the application:
Adriaensen, F., et al2003. The application of ‘least-cost’ modelling as a functional landscape model. Landscape and Urban Planning 64, 233–247..
Biber, 2013. Adaptive Management and the Future of Environmental Law, Akron Law Review, vol. 46-4, pp. 933-962.
Coulon, A., et al(2015). “A stochastic movement simulator improves estimates of landscape connectivity.” Ecology96(8): 2203-2213.
De Sadeleer, N., 2002. Environmental Principles, Oxford, OUP, 482 pp.
Macfadyen, S., et al(2015). “Temporal change in vegetation productivity in grain production landscapes: linking landscape complexity with pest and natural enemy communities.” Ecological Entomology40(S1): 56-69.
Marcus, T., S. et al(2014). “Living in Heterogeneous Woodlands-Are Habitat Continuity or Quality Drivers of Genetic Variability in a Flightless Ground Beetle?” PLoS ONE10(12): e0144217-e0144217.
McRae, B.H., Dickson, B.G., Keitt, T.H., Shah, V.B. 2008. Using circuit theory to model connectivity in ecology, evolution, and conservation. Ecology89, 2712–2724.
Naim-Gesbert, E., 1999. Les dimensions scientifiques du droit de l’environnement, Bruxelles, Bruylant, 808 pp.
Panzacchi, M., et al2015. Predicting the continuum between corridors and barriers to animal movements using Step Selection Functions and Randomized Shortest Paths. Journal of Animal Ecology, online in advance of print. http://dx.doi.org/10.1111/1365-2656.12386
Pettorelli, N., H. Nagendra, R. Williams, D. Rocchini & E. Fleishman (2015). “A new platform to support research at the interface of remote sensing, ecology and conservation.” Remote Sensing in Ecology and Conservation1(1): 1-3
Rose, R. A., et al(2015). “Ten ways remote sensing can contribute to conservation.” Conservation Biology29(2): 350-359.
Ruhl, J.B., 2006. Regulation by Adaptive Management—Is It Possible? Minn. J.L. Sci. & Tech., vol. 7-1, pp. 21-57.
Schellhorn, N. A.,et al(2015). “Connecting scales: Achieving in‐field pest control from areawide and landscape ecology studies.” Insect Science 22(1): 35-51.
Truilhe-Marengo, E., 2015. How to cope with the unknown, A few things about scientific uncertainty, precaution and adaptive management in Born Ch.-H., et al., The Habitats Directive in its Environmental Law Context. European Nature’s Best Hope ?, London, Routledge, pp. 336-347.
Verschuuren, J., 2015. Connectivity: is Natura 2000 only an ecological network on paper ?, in Born Ch.-H., et al., The Habitats Directive in its Environmental Law Context. European Nature’s Best Hope ?, London, Routledge, pp. 285-302.
Zeller, K. A., K. McGarigal & A. R. Whiteley (2012). “Estimating landscape resistance to movement: a review.” Landscape Ecology 27(6): 777-797.