Development and parametrization of robust home range connectivity models for planning urban green infrastructure beneficial to urban animals

Dr Anne Mimet – University of Angers, France (anne.mimet @ univ-angers.fr (anne.mimet @ univ-angers.fr)) 
Key-words: Landscape connectivity, Ecological modeling, Urban ecology, Urban planning, Landscape ecology, Landscape dynamics

Google Scholar: https://scholar.google.fr/citations?user=i9CrTMoAAAAJ&hl=fr & Researchgate: https://www.researchgate.net/profile/Anne-Mimet 

Objective of this summary : To find a collaborator in the EU Green network willing to collaborate with me on the supervision of the PhD student:

• Joint supervision of the PhD student (eg connectivity modeling, statistical analyses, GIS, remote sensing)
• Data collection in the city of the collaborator’s university

I would be happy to find someone bringing knowledge and skills on one or more of these topics :

• biodiversity monitoring by audio-recorders and/or footprints
• Remote sensing and spatial analyses
• Connectivity modeling (Conscape)
• Statistical modeling for heterogeneous datasets

We would be able to apply to 1 or 2 funding calls from the EU Green network :

• 6th of May 2024 (short deadlien, but who know, it might work)
• Fall 2024

Summary of the PhD thesis proposal

State of the art

Ecological connectivity  plays an essential role of in maintaining ecosystems and the services they provide to human beings in anthropogenic landscapes. Defined as "the degree to which a landscape facilitates or hinders movement between resource patches", ecological connectivity supports biodiversity and ecological processes from the level of the individual (e.g. resource allocation within home ranges) to the metapopulation (e.g. dispersal and gene flow between subpopulations). In cities, policies focus their support on ecological connectivity through the development and planning of urban green infrastructure (UGI) aimed at improving the habitability of the city for humans, but also for plants and animals.
UGI are defined as “vegetated green surfaces, such as parks, trees and small forests, grasslands, but also private gardens or cemeteries [...] [that] contribute to supporting biodiversity, pollinators, carbon sequestration, flood protection and protection against excess heat events” (European Environmental Agency, https://www.eea.europa.eu/data-and-maps/dashboards/urban-green-infrastructure-2018). Defining UGI for urban planning remains a challenge, especially because the scientific fields of urban ecology and connectivity are still in their infancy and have not yet provided urban planners with easy-to-handle, empirically-based and generalizable tools to include ecological requirements into planning processes. The development of the necessary IGU planning tools lacks solid, generalizable scientific knowledge of the ecology of species living in cities, as well as standardized approaches that would make the tools widely usable in all cities and contexts. For instance, we don’t know if and how much buildings or traffic act as barriers to the movements of birds flying from their nest to foraging areas.

Connectivity modeling is a promising approach to defining IGUs. The most widespread approaches are based on graph and circuit theory. These modelling approaches have shown potential for the creation of conservation networks, the assessment of population fragmentation, and the design of urban green spaces and infrastructure beneficial to both wildlife and humans. However, the application of these models is hampered by a lack of consistency in the scales and processes modeled, and of reliable parameter values, thus compromising confidence in their results and limiting their general applicability. 

We identify three bottlenecks to overcome for the development of robust IGU planning tools based on those tools:
(i)    Build modeling frameworks that respect scale consistency : the applications of connectivity models lack consistency of scale between the ecological processes modeled and the definition of the spatial units serving as nodes in the ecological network. This is because animals do not perceive their environment in the same way when carrying out these different processes. The way in which a habitat patch is defined (eg in terms of surface area, composition, or geographical location) must therefore correspond to the type of movement targeted by the modeling (eg foraging or dispersal). 
(ii)    Lack of empirical estimation of the model parameters – habitat or resource requirements, resistance of landscape elements, maximum isolation distance between habitat patchs, degree of directionality versus randomness of the walk: The assessment of the connectivity models parameters is often based on expertise and literature reviews rather than empirical data. Well-parameterized connectivity models sometimes use individual tracking data to estimate resistances, but this approach is limited to a restricted number of species due to significant financial and time constraints. A systematic approach to parameterization is therefore needed to accurately model connectivity networks.
(iii)    Lack of methodological frameworks for modeling home range connectivity: The scale of the home range, defined as "the area or volume over which [an individual] normally moves as part of his or her routine activities", is very rarely the focus of connectivity analyses, which preferentially target the dispersal process. However, connectivity is essential for daily movements and influences home range size, formation and shape. In highly fragmented landscapes, such as urban or agricultural landscapes, connectivity becomes crucial for home range establishment and for explaining species distribution. What's more, limited-area territories (such as cities) are quite small in relation to the size of the home ranges of the vertebrate species they harbor. Their size corresponds more to that of one or a few small sub-populations than to that of a metapopulation, which means that the dispersal process will ultimately explain little about the distribution of the species. In other words, a study looking at the connectivity of a small territory has good reason to focus on connectivity at the home range scale rather than at the dispersal scale.

Recent studies by Merkens et al. (2023) propose a solution to these challenges by introducing a methodological modeling framework for building and parameterizing home range connectivity models, thus improving the applicability and reliability of ecological modeling approaches for ecological planning and biodiversity conservation. This two-stage modeling framework is inspired by the habitat selection hierarchy. The habitat selection hierarchy distinguishes between the lower-order process of selecting a home range within the geographic range and the higher-order process of selecting specific habitat components within the home range based on availability and accessibility. Applying this hierarchical approach, the proposed framework evaluates two critical resource characteristics impacting the occurrence of home ranges: resource availability (sufficient resources for home range establishment) and resource accessibility (accessibility of resources through individual displacement). This framework uses statistical model selection to derive the key parameters for connectivity modeling, namely:

• the type and quantity of resources required to establish a home range
• the resistance values of landscape elements (eg., buildings, streets)
• maximum isolation distances between resource patches
•  the connectivity metrics (derived from graphs and circuits) best suited to the case study

This modeling framework was applied to the connectivity of the blackbird's home range, followed by that of a dozen other bird species, in the city of Munich (Germany). The analyses highlighted the capability of the modelling framework to derive parameters values from movement data, but also to produce similar parameter values by using simple Presence/Absence data (Figure 1). This result demonstrates the approach's ability to evaluate key parameters of connectivity models from a type of data that is widely more available than the movement data usually required.
 
Figure 1: Blackbird home range connectivity map for the city of Munich, based on the methodological framework described above.
Aim of the PhD
This PhD aims to extend and generalize the modeling framework proposed by Merkens et al. (2024) to make it widely applicable accross european cities for the definition of UGI. The specific aims are as follow :

• Integrating a new model parameter defining the degree of randomness versus directionality of the animal home range movements between resource patches.
• Finding the key connectivity parameter values (i.e. minimum home range resource requirement, resistance of landscape elements, maximum isolation between resource patches, and directionlity/randomness of the walk) for a large number of vertebrate species using a large number of published data on vertebrate distribution in cities.
• Test if those key connectivity parameter values can be derived from functional traits (eg., body mass, diet, habitat specialization), which would make it possible to derive them from existing data, and therefore to compute connectivity maps from existing data for most species.