Jeronimo Barbosa
email: jeronimo.costa@mail.mcgill.ca

Idmil Cirmmt

Marcelo M Wanderley
email: marcelo.wanderley@mcgill.ca

Stéphane Huot
email: stephane.huot@inria.fr

ZenStates: Easy-to-Understand Yet Expressive Specifications for Creative Interactive Environments

Keywords: Human-computer interaction, hierarchical finite state machines, creativity-support tools, interactive environments, end-user programmers

Much progress has been made on interactive behavior development tools for expert programmers. However, little effort has been made in investigating how these tools support creative communities who typically struggle with technical development. This is the case, for instance, of media artists and composers working with interactive environments. To address this problem, we introduce ZenStates: a new specification model for creative interactive environments that combines Hierarchical Finite-States Machines, expressions, off-the-shelf components called Tasks, and a global communication system called the Blackboard. Our evaluation is three-folded: (a) implementing our model in a direct manipulation-based software interface; (b) probing ZenStates' expressive power through 90 exploratory scenarios; and (c) performing a user study to investigate the understandability of ZenStates' model. Results support ZenStates viability, its expressivity, and suggest that ZenStates is easier to understand-in terms of decision time and decision accuracycompared to two popular alternatives.

I. INTRODUCTION

Over the last years, several advanced programming tools have been proposed to support the development of rich interactive behaviors: The HsmTk [START_REF] Blanch | Programming rich interactions using the hierarchical state machine toolkit[END_REF] and SwingStates [START_REF] Appert | SwingStates: adding state machines to Java and the Swing toolkit[END_REF] toolkits replace the low-level event-based paradigm with finite-states machines; ConstraintJS [START_REF] Oney | ConstraintJS: Programming Interactive Behaviors for the Web by Integrating Constraints[END_REF] introduces constraints declaration and their implicit maintenance as a way to describe interactive behaviors; InterState [START_REF]InterState: A Language and Environment for Expressing Interface Behavior[END_REF] and Gneiss [START_REF] Chang | Creating interactive web data applications with spreadsheets[END_REF] are dedicated programming languages and environments. These advances are primarily focused on programmers and are important because:

• They can make interactive behavior easier to understandsometimes even by non-experts programmers. This is the case, for instance, of the SwingStates toolkit [START_REF] Appert | SwingStates: adding state machines to Java and the Swing toolkit[END_REF]. SwingStates was successfully used by graduate-level HCI students to implement advanced interaction techniques despite of their limited training, when other students with similar skills were unsuccessful in implementing the same techniques with standard toolkits. In addition, better understanding of the implementation of interactive behaviors can make it easier to reuse and modify [START_REF] Blanch | Programming rich interactions using the hierarchical state machine toolkit[END_REF]; • These tools do not sacrifice expressiveness to make programing faster or understanding easier. Examples such as [START_REF] Oney | ConstraintJS: Programming Interactive Behaviors for the Web by Integrating Constraints[END_REF] and [START_REF] Chang | Creating interactive web data applications with spreadsheets[END_REF] illustrate how such tools can potentially implement a wide variety of complex interactive behaviors, which would have been more costly in existing alternatives. Despite these advantages, little effort has been made to investigate how these advances could support end-user programmers (EUP) [START_REF] Ko | The state of the art in enduser software engineering[END_REF], [START_REF]New Perspectives in End-User Development[END_REF] from creative communities who typically struggle with coding such as artists and designers [START_REF] Bailey | Supporting Multimedia Designers: Towards more Effective Design Tools[END_REF], [START_REF] Myers | How designers design and program interactive behaviors[END_REF]. Making these behaviors easier to understand could make them easier to learn, reuse, and extend. At the same time, addressing expressiveness (i.e., going beyond standard and well-defined behaviors) could improve the diversity of creative outcomes, helping in the exploration of alternatives. All in all, these characteristics have the potential to foster one's creative process [START_REF] Shneiderman | Creativity support tools: accelerating discovery and innovation[END_REF].

One example of such community is composers and media artists working with creative interactive environments [START_REF] Krueger | Responsive environments[END_REF]. These environments are immersive pieces that react to the presence of visitors, based on a wide diversity of input sensors (eg. video cameras) and actuators (eg. sound, lightning systems, video projection, haptic devices). Creating easy to understand and expressive development tools for these environments is relevant and challenging for two reasons. First, interactive environments' setups are often more complex than standard interactive systems (such as desktop or mobile computers), as they (i) need to deal with multiple advanced input/output devices and multiple users that both can connect/disconnect/appear/disappear dynamically; (ii) need to be dynamic, flexible and robust. Therefore, by tackling more complex setups, some of its unique features could potentially transfer to more standard setups (e.g. desktop). Secondly, because programming directly impacts on the artistic outcomes, increasing programming abilities and possibilities can likely yield finer artistic results, by reducing the gap between artistic and technical knowledge.

These are the context and the challenge we address in this paper. Here, we investigate innovations brought by powerful development tools for expert programmers [START_REF]InterState: A Language and Environment for Expressing Interface Behavior[END_REF], [START_REF] Chang | Creating interactive web data applications with spreadsheets[END_REF], [START_REF] Harel | Statecharts: a visual formalism for complex systems[END_REF], aiming at bringing them to the context of creative interactive environments. The result is ZenStates: an easy to understand yet expressive specification model that allows creative EUPs to explore these environments using Hierarchical Finite-States Machines, expressions, off-the-shelf components called tasks, and a global communication system called the blackboard. This model has been implemented in a visual direct manipulation-based interface that validates our model (Fig. 1). Finally, as an evaluation, we also report: (a) 90 exploratory scenarios to probe ZenStates' expressive power; and (b) a user study comparing ZenStates' ease of understanding against the specification model used by two popular interactive environments development tools: Puredata and Processing.

II. RELATED WORK

One of the most basic approaches for interactive environments development is trigger-action programming [START_REF] Ur | Practical trigger-action programming in the smart home[END_REF]. This approach-used, for instance, in the context of smart homesdescribes simple conditional "if-then-else" behaviors that can be easily customized by users. Despite being intuitive and effective, this approach limits interactive environments to simple one-level behaviors. For instance, any example involving temporal actions cannot be implemented.

Other approaches can be found within the context of creative communities. This is the case of the visual "Max paradigm" [START_REF] Puckette | Max at Seventeen[END_REF], found in musical tools such as Max/MSP, and Puredata. These dataflow-inspired software environments have become widely adopted over the years by creative EUPs. They allow users to build multimedia prototypes by visually combining elementary building blocks, each performing a specific real-time operation. However, because everything is designed for real-time, little support is provided for managing the flow of control of application (e.g. conditionals, loops, routines) [START_REF] Puckette | Max at Seventeen[END_REF].

Another approach is the case of textual programming environments and libraries [START_REF] Noble | Programming Interactivity: A Designer's Guide to Processing[END_REF], such as Processing, openFrame-works, and Cinder. However, although these tools lower the floor required to get started in programming, they still require users to deal with abstract concepts whose meaning is not often transparent, especially to novices [START_REF] Victor | Learnable programming[END_REF].

To overcome this understandability issue, direct manipulation [START_REF] Shneiderman | Direct Manipulation: A Step Beyond Programming Languages[END_REF] has been applied in this context to make programming less abstract and therefore more tangible to creative users. Examples include Sketch-N-Sketch [START_REF] Hempel | Semi-Automated SVG Programming via Direct Manipulation[END_REF]-where direct manipulation is combined with textual programming language-and Para [19]-direct manipulation combined with constraint-based models. While the strategy is helpful, the solution is kept on the interface level (i.e., that could potentially be applied to every specification model), whereas the specificion model itself remains unexplored. Furthermore, both examples are limited to static artistic results (i.e., not capable of reacting to inputs over time).

A. Non-programmers expressing interactive behaviors

Given our interest in exploring more accessible specification models, we need to understand first how non-programmers deal with expressing interactive behaviors. A few works have dealt with this topic.

In [START_REF] Pane | Studying the language and structure in non-programmers' solutions to programming problems[END_REF] for instance, two studies focused on understanding how non-programmers express themselves in solving programming-related problems. In one study, 10-11 years old children were asked to describe how they would instruct a computer to behave in interactive scenarios of the Pac-man game. In another, university-level students were asked to do the same in the context of financial & business analytical problems. Results suggest that participants tended to use an event-based style (e.g., if then else) to solve their problems, with little attention to the global flow of the control (typical in structured imperative programming languages, for example). This approach to problem-solving arguably has similarities to the approach that state machines have in problem-solving.

Some work also presented practices and challenges faced by professional multimedia designers in designing and exploring rich interactive behaviors derived from series of interviews and a survey [START_REF] Bailey | Supporting Multimedia Designers: Towards more Effective Design Tools[END_REF]. The results suggest that in the case of designing interactive behaviors: a) current tools do not seem to fulfill the needs of designers, especially in the early stages of the design process (i.e., prototyping); b) texts, sketches, and several visual "arrow-centered" techniques (e.g. mind map, flowcharts, storyboards) are among the most used tools to communicate ideas; and c) designers prefer to focus on content rather than "spending time" on programming or learning new tools. These findings resulted in a new system, DEMAIS, which empowers designers to communicate and do lo-fi sketch-based prototypes of animations via interactive storyboards.

Similar findings were reported by [START_REF] Myers | How designers design and program interactive behaviors[END_REF]. In a survey with 259 UI designers, the authors found that a significant part of participants considered that prototyping interactive behaviors was harder than prototyping appearance (i.e., the "look and feel"). Participants reported struggling with communicating interactive behaviors to developers-although this communication was necessary in most of the projects-when compared to communicating appearance. In addition, participants reported necessity for iteration and exploration in defining these behaviors, which generally involved dealing with changing states. The authors conclude by reporting the need for new tools that would allow quicker and easier communication, design and prototyping of interactive behaviors.

These works suggest that state machines could be suited to the development of interactive behavior by non-programmers, and, we believe, by creative end-user programmers who struggle with technical development.

B. Experts programming interactive behaviors

Several tools have been developed to support expert programming of interactive behaviors [START_REF] Cuenca | Graphical Toolkits for Rapid Prototyping of Multimodal Systems: A Survey[END_REF]. Examples include Gneiss [START_REF] Chang | Creating interactive web data applications with spreadsheets[END_REF], ICon [START_REF] Dragicevic | Support for input adaptability in the ICON toolkit[END_REF], and OpenInterface [START_REF] Lawson | An open source workbench for prototyping multimodal interactions based on off-the-shelf heterogeneous components[END_REF]. Among these, a significant number of tools use state machines to specify such interactive behaviors. A complete survey is beyond the scope of this research. Here, we focus on works we consider more closely related to our research.

Perhaps one of the most well-known example is [START_REF] Harel | Statecharts: a visual formalism for complex systems[END_REF], which introduced StateCharts: a simple yet powerful visual-based formalism for specifying reactive systems using enriched hierarchical state machines. StateCharts' formalism was later implemented and supported via a software tool called State-Mate [START_REF] Harel | STATEMATE: a working environment for the development of complex reactive systems[END_REF], and is still used (more than 30 years later) as part of IBM Rational Rhapsody systems for software engineers 1 .

Examples are also notable in the context of GUIs, for instance: HsmTk [START_REF] Blanch | Programming rich interactions using the hierarchical state machine toolkit[END_REF], a C++ toolkit that incorporates state machines to the context of rich interaction with Scalable Vector Graphics (SVG); SwingStates [START_REF] Appert | SwingStates: adding state machines to Java and the Swing toolkit[END_REF], that extends the Java's Swing toolkit with state machines; and FlowStates [START_REF] Appert | Flow-States: Prototypage d'applications interactives avec des flots de données et des machines à états[END_REF], a prototyping toolkit for advanced interaction that combines state machines for describing the discrete aspects of interaction, and data-flow for its continuous parts.

More recently, research has been done on how to adapt state machines to the context of web applications. ConstraintJS [START_REF] Oney | ConstraintJS: Programming Interactive Behaviors for the Web by Integrating Constraints[END_REF] proposed an enhanced model of state machines that could be used to control temporal constraints, affording more straightforward web development. This idea is further developed by the authors in [START_REF]InterState: A Language and Environment for Expressing Interface Behavior[END_REF], resulting in InterState, a new full programming language and environment that supports live coding, editing and debugging.

These works introduce advances that make interactive behaviors programming faster and easier to understand. However, as a drawback, these tools are hardly accessible for creative EUPs who would still need to develop strong programming skills before benefiting from them. To address this problem, we have built upon these works, aiming at making them accessible to creative EUPs. The result, a new specification model called ZenStates, is introduced in the next section.

III. INTRODUCING ZENSTATES

ZenStates is a specification model centered on the idea of State machines. A State Machine is defined as a set of abstract 1 https://www.ibm.com/us-en/marketplace/rational-rhapsody

States to which users might add Tasks that describe (in terms of high-level parameters) what is going to happen when that particular state is being executed. These states are connected to one another via a set of logical Transitions. Execution always starts at the "Begin" state, following these transitions as they happen until the end. At any moment, inside a Task or a Transition, users can use Blackboard variables to enrich behaviors (e.g., use the mouse x position to control the volume, or to trigger certain transitions).

A. Enriched state machines as specification model

ZenStates borrows features from the enriched state machines model proposed by StateChart [START_REF] Harel | Statecharts: a visual formalism for complex systems[END_REF] and StateMate [START_REF] Harel | STATEMATE: a working environment for the development of complex reactive systems[END_REF]. These works overcome typical problems of state machines-namely, the exponential growth of number of states, and its chaotic organization-by introducing:

• Nested state machines (clustering): One state could potentially contain other state machines; • Orthogonality (parallelism): Nested state machines need to be able to execute independently and in parallel whenever their parent state is executed; • Zooming-in and zooming-out: A mechanism athat allows users to navigate between the different levels of abstraction introduced by the nesting of state machines; • Broadcast communication: That allows simple event messages to be broadcasted to all states, having the potential to trigger other states inside the machine. When combined, these features result in a powerful hierarchical model of state machines. This model provides improved organization (i.e., state machines are potentially easier to understand), modularity (i.e., subparts of a system could be independently designed and later merged into a larger structure), and expressiveness (broadcast communication allows enhanced description of complex behaviors) when compared to the traditional states machine approach.

B. Key features

Building upon this model, ZenStates proposes five key features described in the following subsections.

1) Extending communication: the Blackboard The blackboard-in the top-right of Figure 2-is a global repository of variables that can be defined and reused anywhere inside a state machine (i.e., inside states, nested states, tasks or transitions). Therefore, we extend the notion of broadcast communication introduced by [START_REF] Harel | Statecharts: a visual formalism for complex systems[END_REF] because variables can be used to other functionalities, and not only triggering transitions. In addition, because the blackboard is always visible on the interface, users can easily infer what inputs are available on the environment, as well as their updated values.

Users can interact with the blackboard using pull and push operations. Pull operations are accessed by using the variable's name (as in Gneiss [START_REF] Chang | Creating interactive web data applications with spreadsheets[END_REF]). Push operations can be performed by tasks (see next subsection). Some useful context-dependent variables can be automatically added to the blackboard and become directly accessible to users. In interactive environments, examples include mouse coordinates, key presses, various sensor inputs, incoming Open Sound Control (OSC2 ) messages, etc.

2) Making behaviors concrete: the Tasks One challenge we needed to address concerns specifying concrete behaviors to happen inside the states. In the case of tools for developers, this behavior could be easily specified via programming language. But how could we make this easier for creative EUPs?

We solve the issue by introducing the notion of tasks: simple atomic behaviors representing actions (if it happens only once) or activities (if it keeps occurring over time) and that can be attached to states as off-the-shelf components [START_REF] Lawson | An open source workbench for prototyping multimodal interactions based on off-the-shelf heterogeneous components[END_REF].

Tasks work in the following way: Once a certain state is executed, all associated tasks are run in parallel. Each individual task also has its own set of idiosyncratic highlevel parameters, that allow users to fine-tune its behaviors. In Figure 1, for instance, these high-level parameters are the intensity of the vibration, and the panning of a stereo audiodriven bass shaker. The UI controls to edit these parameters can be easily hidden/shown by clicking on the task, allowing users to focus their attention on the tasks they care the most.

Tasks are normally context-dependent, and need to be changed according to the domain of application. In creative interactive environments, for example, potential tasks could be: sound-related tasks (e.g., start sound, control sound, stop sound), light-related tasks (start, control, and stop light), and haptics related tasks (start, control, and stop haptics)-as shown in Figure 3.

There are however two categories of tasks which are not context dependent: the blackboard-tasks, and the meta-tasks.

Blackboard-tasks relate to creating new variables within the blackboard so that they can be later used anywhere inside the state machine. Our motivation is to increase reuse by providing users with a set of recurrent functionalities often found in interactive environments. Examples include oscillators, ramps, and random numbers.

Meta-tasks relate to extending ZenStates in situations where currently-supported functionalities are not enough. For example, OSC tasks allow communication with external media tools via the OSC protocol. JavaScript tasks allow custom JavaScript code to be incorporated to states. Finally, we have State Machine tasks, that allows nesting as shown in Figure 3.

3) Enriching transitions We enrich transitions by incorporating two functionalities.

First, transitions make use of priorities that define the order they are going to be checked. This means that one state can have multiple transitions evaluated one after the other according to their priority (see Fig. 4). This allows users to write complex logical sentences similar to cascades of "ifthen-else-if" in imperative languages. It also avoids potential logical incoherences raised by concurrent transitions.

Second, transitions support any Javascript expression as guard conditions, expressed as transition and constraint events as in [START_REF]InterState: A Language and Environment for Expressing Interface Behavior[END_REF]. In practice, this functionality combines logical operators (e.g. '&&', '||', '!'), mathematical expressions, and blackboard variables used either as events (e.g. '$mousePressed') or inside conditions (e.g. '$mouseX > 0.5'). For instance, it is possible to set that if someone enters a room, the light should go off. Or if the mouse is pressed on a certain x and y coordinates, another page should be loaded. 4) Self-awareness Self-awareness describes a set of meta characteristics belonging to states and tasks that are automatically added to the blackboard and become available to users. For example, states can have a status (e.g., is it running? Is it inactive?), sound tasks can have the current play position, the volume, and the audio pan as properties, etc. This feature can be useful in several ways. For example, we can set a transition to occur when all tasks within a certain state are completed (e.g. '$State.Done'). Or yet, it is possible to have the volume of an audio file to increase as its playback position increases.

5) Live development & Reuse

Finally, ZenStates also borrows two additional features from [START_REF]InterState: A Language and Environment for Expressing Interface Behavior[END_REF] and [START_REF] Chang | Creating interactive web data applications with spreadsheets[END_REF]:

• Live development: Any element (e.g. tasks, transitions, and states) can be modified at runtime, allowing quicker process of experimentation and prototyping; • Reuse: Previously defined interactive behaviors can easily be reused via nested state machines (that can be saved into files, exchanged, and then later imported). Here, we also expect to align with the principle of reuse as introduced by [START_REF] Beaudouin-Lafon | Reification, polymorphism and reuse[END_REF].

IV. IMPLEMENTATION

The design process of ZenStates has been iterative and user-centered with media artists. Steps included: a) analysis Fig. 4. Transitions have priorities attached to them. In this case, the blackboard variable '$my_random' generates a random number (between 0 and 1) which is then used to select a random path. The first transition to be checked is '$my_random > 0.9' because of its priority '1'. If false, transition with priority '2' would then be checked. This process goes on until all transitions are checked. In case none is satisfied, the current state is executed once again before the next round of checking (repeat button is enabled). Transitions can be added, edited, and deleted via direct manipulation.

of existing alternatives; b) interviews with expert users; c) paper prototypes; d) development of scenarios to assess the potential of the tools in solving problems; e) observing the compositional process of two new media works; f) functional prototypes; and g) user-interface refinement over the course of think-aloud protocol sections with novice and expert users. While a full description of this process is beyond the scope of this paper, its direct result is the specification model as presented in this paper.

To validate this model, we implemented all features described here in a functional software prototype. In this prototype, abstract elements (namely the state machine, states, tasks, transitions, and the blackboard) are reified-according to the principle of reification introduced in [START_REF] Beaudouin-Lafon | Reification, polymorphism and reuse[END_REF]-to graphical objects that can be directly manipulated by the user [START_REF] Shneiderman | Direct Manipulation: A Step Beyond Programming Languages[END_REF]. These visual representations become the core of the user interaction and also allow users to infer the current state of the system at any time during execution: the current running state is painted green; states already executed are red; inactive states are gray (see Fig. 2). All images presented on this paper are actual screenshots of this functional prototype, also demonstrated in the supplementary video.

The prototype has been implemented in Java, using Processing 3 as an external library for the graphics. The project is open-source and the source code is available online 4 . We stress that, as a prototype, this system is sill under development and its usability needs improvement.

V. EVALUATION

We argue ZenStates proposes an expressive (i.e., allow to develop a wide diversity of scenarios) yet easy-to-understand specification model for creative interactive environments. We have tested these claims in two steps. First, we have probed ZenStates' expressive power by designing 90 exploratory scenarios. Second, we have conducted a user study investigating ZenStates specification model in terms of its capacity to quickly and accurately describe interactive environments.

A. Exploratory scenarios

To explore the expressive power of ZenStates, we have developed 90 unique exploratory scenarios. These scenarios implement atomic audiovisual behaviors with different levels of complexity, based on a constrained set of inputs (either mouse, keyboard, or both), outputs (either background color of the screen, the sound of a sinewave, or both), and blackboard variables. The chosen behaviors are often used in the context of music/media arts. Examples include: Sinusoidal sound generators with user-controlled frequency (c.f., the project Reactable5 ) as implemented in the scenario 'mouse click mute mousexy freq amp'; and contrasting slow movements abrupt changes to create different moments in a piece (c.f., 'Test pattern' by Ryoji Ikeda 6 ) implemented in the scenario 'random flickering random wait silence') . The full list of exploratory scenarios-with implementation and video demonstration-is available as supplementary material 7 .

While small, these atomic scenarios can be further combined to one another via hierarchical state machines and transitions. Therefore, it is possible to create a potentially infinite number of new scenarios-much more complex than the atomic ones. This diversity illustrates the expressive power of ZenStatesespecially considering the constrained set of input, outputs and blackboard variables that were used.

B. User study

We investigated if ZenState's specification model makes the development of interactive environments easier to understand. This model was compared to the specification model used by two popular interactive environments development tools: Puredata (hereafter, the dataflow model), and Processing (hereafter, the structured model).

1) Hypothesis: Our hypothesis is that Zenstates allows users to understand interactive environments specifications more accurately-that is, ZenStates would reduce the number of code misinterpretations by users-and faster-that is, ZenStates would reduce the amount of time necessary to understand the code-compared to the alternatives.

2) Subjects and Materials: We recruited 12 participants (10 male, 1 female, and 1 not declared), aged 29 years old on average (min = 22, max = 46, median = 26, SD = 7.98). Participants were all creative EUPs with previous experience with interactive environments tools (e.g. media artists, composers, designers, and technologists), either professionals or students. Their expertise on computer programming ranged from novices to experts (min = 2 years, max = 23 years, mean = 7.67, median = 6, SD = 5.48). The most familiar languages for them were Python and Max/MSP (both with 4 people each), followed by Processing (2 people).

Regarding the experimental material, we have selected 26 of our exploratory scenarios representing a wide diversity of usage scenarios (i.e., either using blackboard variables; single input; and multimodal input). Each scenario was then specified using the three evaluated specification models (ZenStates, dataflow, and structured), resulting in 78 specifications. All these scenarios and their specifications are available online 8 .

3) Procedure: Our experimental procedure is based on [START_REF] Kin | Proton++: A Customizable Declarative Multitouch Framework[END_REF], adapted and fine-tuned over a preliminary pilot with 6 participants. The resulting procedure is composed of 3 blocksone block per specification model tested-of 6 trials.

In each block, participants were introduced to a specification model as presented in Figure 5. Participants were also given a small printed cheatsheet containing all possible inputs (i.e., mouse and keyboard), actuators (i.e., screen background color, and a sinewave), and language specific symbols that could appear over the trials. At this point, participants were allowed to ask questions for clarification, and were given some time to get used to the model.

After this introduction, participants were introduced to one interactive environment specification-either ZenStates, dataflow, or a structured language-and to six different interactive environments videos showing real behaviors. Their task was to choose which video they thought that most accurately corresponded to the specification presented, as shown in Figure 6. Participants were instructed to be the most accurate, and to chose a video as quick as they couldwithout sacrificing accuracy. Only one answer was possible. Participants were allowed two practice trials and the cheatsheet could be consulted anytime.

Participants repeated this procedure for all three evaluated alternatives. Presentation order of the models was counterbalanced to compensate for potential learning effects. Similarly, the order of the six videos was randomized at each trial.

Our measured dependent variables were the decision accuracy (i.e., the percentage of correct answers), and the decision time (i.e., the time needed to complete the trial). As in [START_REF] Kin | Proton++: A Customizable Declarative Multitouch Framework[END_REF], the decision time was computed as the trial total duration minus the time participants spent watching the videos. The whole procedure was automatized via a web application 9 . Finally, participants were asked about the specification models they had considered the easiest and the hardest to understand, followed by a short written justification.

4) Results: Data from HCI experiments has often been analyzed by applying null hypothesis significance testing (NHST) in the past. This form of analysis of experimental data is increasingly being criticized by statisticians [START_REF] Baker | Statisticians issue warning over misuse of P values[END_REF], [START_REF] Cumming | The New Statistics[END_REF] and within the HCI community [START_REF] Dragicevic | Fair Statistical Communication in HCI[END_REF], [START_REF] Dragicevic | Running an HCI experiment in multiple parallel universes[END_REF]. Therefore, we report our analysis using estimation techniques with effect sizes 10 and confidence intervals (i.e., not using p-values), as recommended by the APA [START_REF] Vandenbos | APA dictionary of psychology[END_REF].

Regarding decision time, there is a strong evidence for ZenStates as the fastest model (mean: 40.57s, 95% CI: [35.07,47.27]) compared to the dataflow (mean: 57.26s, 95% CI: [49.2,67.5]), and the structured model (mean: 70.52s, 10 Effect size refers to the measured difference of means-we do not make use of standardized effect sizes which are not generally recommended [START_REF] Baguley | Standardized or simple effect size: What should be reported?[END_REF]. 95% CI: [59.16,85.29]), as shown in Figure 7. We also computed pairwise differences between the models (Fig. 8) and their associated confidence intervals. Results confirm that participants were making their decision with ZenStates about 1.4 times faster than with the dataflow and 1.8 times faster than with the structured model. Since the confidence interval of the difference between dataflow and structured models overlaps 0, there is no evidence for differences between them.

Regarding decision accuracy, participants achieved 91.67% (95% CI: [81.89,95.83]) accuracy with ZenStates, 90.28% (95% CI: [80.55,94.44]) with the Dataflow model, and 88.89% (95% CI: [76.39,93.05]) with the structured model (see Fig. 7(right)). These results show quite high accuracy with all the specification models overall, although there is no evidence for one of them being more accurate than the other.

Finally, regarding the final questionnaire data, ZenStates was preferred by participants as the easiest model to understand (8 people), followed by the structured (3 people), and the dataflow (1 person) models. Participants written justifications reported aspects such as "graphic display", "code compartmentalization", and "abstraction of low-level details" as responsible for this preference. Similarly, dataflow (8 people) was considered the hardest model to understand, followed by structured (3 people), and ZenStates (1 person).

VI. LIMITATIONS

Our studies also revealed limitations in our specification model and its software interface, namely: fulfills its goals (i.e., enhancing communication), it has limitations. A first limitation deals with representing a large amount of sensor data in the screen. For example, if a 3D depth camera is attached to the system (tracking x, y, and z points for all body joints), all detected joints would be added to the blackboard. For users interested in specific information (e.g. hand x position), the amount of visual data can be baffling. Another limitation concerns lack of support to high-level features (e.g. derivatives, and averages), and filtering, which are often as useful as raw sensor data. Further research is needed to improve the blackboard on these directions;

• Physical environment alignment: ZenStates assumes that the physical environment (i.e., sensor input, hardware for output media) and the tasks it supports (i.e., soundrelated, light-related) is static and consistent, and that it would remain consistent along the execution. This assumption is reasonable when dealing with standard interaction techniques (e.g. WIMP tools for desktop, as in SwingStates [START_REF] Appert | SwingStates: adding state machines to Java and the Swing toolkit[END_REF]). However, because we are dealing with potentially more complex setups, it is possible that the assumption is no longer possible in certain cases. For example, in a certain artistic performance, some sensors might be added, or some light strobes removed during the performance. How to maintain this environmentsoftware consistency in these dynamic cases? How should ZenStates react? These are open questions that need to be addressed in future developments; • Interface usability and stability: The evaluation performed so far focuses only on readability of our specification model, not addressing ease of use or usability of the prototype interface that implements the model. We reason that ease of use and usability are not as relevant in such prototype stage as already-known problems would show up, limiting the evaluation of our specification model. At this stage, readability seems more effective as it could make specifications easier to understand, and potentially easier to learn, reuse, and extend. Nevertheless, we highlight that the usability of such interface would play a significant role in the effectiveness of our model.

Examples to be improved include the obtuse expression syntax, using '$' to instantiate variables, and the small font size;

In addition to addressing these problems, we also plan to explore the usage of ZenStates in other creative contexts and to implement principles that could improve general support to creativity inside ZenStates (see [START_REF] Shneiderman | Creativity support tools: accelerating discovery and innovation[END_REF] for examples).

VII. CONCLUSION

In this paper, we have analyzed the state of the art of development tools for programming rich interactive behaviors, investigating how these tools could support creative end-user programmers (e.g., media artists, designers, and composers) who typically struggle with technical development. As a solution, we introduced a simple yet powerful specification model called ZenStates. ZenStates combines five key contributions-1) the blackboard, for communication; 2) the tasks, for concrete fine-tunable behaviors; 3) the prioritized guard-conditionbased transitions; 4) self-awareness; and 5) live development & reuse-, exploring those in the specific context of interactive environments for music and media arts.

Our evaluation results suggest that ZenStates is expressive and yet easy to understand compared to two commonly used alternatives. We were able to probe ZenStates' expressive power by the means of 90 exploratory scenarios typically found in music/media arts. At the same time, our user study revealed that ZenStates model was on average 1.4 times faster than dataflow model, 1.8 times faster then the structured model in terms of decision time, and had the highest decision accuracy. Such results were achieved despite the fact participants had no previous knowledge of ZenStates, whereas alternatives were familiar to participants. In the final questionnaire, 8 out of 12 participants judged ZenStates as the easiest alternative to understand.

We hope these contributions can help making the development of rich interactive environments-and of interactive behaviors more generally-more accessible to developmentstruggling creative communities.

Fig. 1 .

 1 Fig. 1. ZenStates allows users to quickly prototype interactive environments by directly manipulating States connected together via logical Transitions. Tasks add concrete actions to states and can be fine-tuned via high-level parameters (e.g. 'intensity' and 'pan'). Blackboard global variables (prefixed with the '$' sign) can enrich tasks and transitions.

Fig. 2 .

 2 Fig. 2. ZenStates' components: (a) the state machine name; (b) control buttons; (c) tasks associated with a state; (d) the initial state (in this case, also the one which is currently running, represented in green); (f) the blackboard; and transitions, composed by a guard condition (g) and its execution priority (e).

Fig. 3 .

 3 Fig. 3. Tasks inside states are reified with a contextual pie menu, as shown in the sequence above-(a), (b), (c), and (d). High-level parameters related to each task can be found by clicking on the task-as shown in (e).

Fig. 5 .

 5 Fig. 5. The three specification models presented to the participants: dataflow (top-left), structured (bottom-left), and ZenStates (right).

Fig. 6 .

 6 Fig.6. Being introduced to one specification, participants needed to choose which one among six videos they thought that most accurately corresponded to the specification presented.

Fig. 7 .Fig. 8 .

 78 Fig. 7. Decision time (left) and Accuracy (right) per specification model. Error Bars: Bootstrap 95% CIs.

http://opensoundcontrol.org/

http://processing.org/

https://github.com/jeraman/zenstates-paper-vlhcc2018

https://www.youtube.com/watch?v=n1J3b0SY JQ

https://www.youtube.com/watch?v=JfcN9Qhfir4

https://github.com/jeraman/zenstates-paper-vlhcc2018/tree/master/ scenarios

https://github.com/jeraman/zenstates-paper-vlhcc2018/tree/master/data% 20collection/html/scenarios

https://github.com/jeraman/zenstates-paper-vlhcc2018/tree/master/data% 20collection

• The blackboard: Currently represented as a twocolumns table on the top right of the screen, containing variable name and its value. While this initial approach

ACKNOWLEDGMENT

The authors would like to thank Sofian Audry and Chris Salter for their support and numerous contributions, and everyone involved in the project 'Qualified Self' for their time.

This work was partially supported by the NSERC Discovery Grant and the Fonds de recherche du Québec-Société et culture (FRQSC) research grant. Authors' version. Final version published in 2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC'18).


Maëlle Le Berre

Virgile Noble

Mathias Pires

Gabriele Casazza

Luigi Minuto

Mauro Mariotti

Sylvain Abdulhak

Noémie Fort

Frederic Medail

Katia Diadema
email: k.diadema@cbnmed.fr

Frédéric Médail

Applying a hierarchisation method to a biodiversity hotspot: Challenges and perspectives in the South-Western Alps flora

Keywords:

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

For many years, biodiversity decline has been a global concern; thereby the conservation of threatened taxa has become a major issue [START_REF] Cardinale | Biodiversity loss and its impact on humanity[END_REF][START_REF] Mace | Prioritizing choices in conservation[END_REF]Millennium Ecosystem Assessment, 2005;[START_REF] Vitousek | Beyond global warming: Ecology and global change[END_REF]. However, protection of all the taxa or ecosystems is not an achievable goal owing to wildlife's extreme diversity and finite allocated budgets. Setting up a hierarchisation of highest conservation concerns taxa is needed to define priority goals and to rationalise the means to implement conservation actions [START_REF] Coates | Priority setting and the conservation of Western Australia's diverse and highly endemic flora[END_REF][START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF][START_REF] Marsh | Optimizing allocation of management resources for wildlife[END_REF]. In fact, biodiversity conservation in a given area requires different steps. The first step is usually risk or threats assessment, for example setting up red lists of threatened species developed by the International Union for Conservation of Nature (IUCN). Setting up a hierarchisation is often a second step [START_REF] Henle | Priorities for biodiversity monitoring in Europe: A review of supranational policies and a novel scheme for integrative prioritization[END_REF][START_REF] Pullin | Conservation priorities: Identifying need, taking action and evaluating success[END_REF][START_REF] Wilson | Setting conservation priorities[END_REF]; it could target geographical assets (e.g. [START_REF] Rodrigues | Global Gap analysis: Priority regions for expanding the global protected-area network[END_REF] or biological assets, as habitats (e.g. [START_REF] Berg | Red lists and conservation prioritization of plant communitiesa methodological framework[END_REF], species (e.g. [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF] or populations (e.g. [START_REF] Bonin | Population adaptive index: A new method to help measure intraspecific genetic diversity and prioritize populations for conservation[END_REF]. The next step is usually conservation projects or actions priority-setting (e.g. [START_REF] Joseph | Optimal allocation of resources among threatened species: A project prioritization protocol[END_REF]. Finally, the last step consists in conservation actions success assessment.

Current conservation needs rarely follow administrative areas, regulatory lists or threat status defined by red lists, especially in a relatively narrow area which includes regional biodiversity hotspots in which territory responsibility is highest [START_REF] Keller | From red lists to species of conservation concern[END_REF][START_REF] Schmeller | Determination of national conservation responsibilities for species conservation in regions with multiple political jurisdictions[END_REF]. Red lists of threatened animal and plant species developed with IUCN criteria constitute an objective assessment of extinction risk in a given area, but do not constitute a priority list for species long term conservation, because they were not created for this purpose (IUCN, 2012). However, red lists are often mistakenly considered as a hierarchical list of priorities for conservation actions, and thus conservation priorities are mainly or even only based on extinction risk. Although extinction risk is a critical component of priority-setting systems, it is important to take into account other factors to maximise conservation actions efficiency [START_REF] Fitzpatrick | Building on IUCN regional red lists to produce lists of species of conservation priority: A model with Irish bees[END_REF][START_REF] Miller | Extinction risk and conservation priorities[END_REF]. Therefore, resource allocation based only on IUCN categories is not the most efficient way to help species recovery or to minimise extinction rates [START_REF] Marsh | Optimizing allocation of management resources for wildlife[END_REF]. Likewise, regulatory lists are not directly applicable to select priority species because they often depend on policy resolutions, are subject to uncertainty of expert assessment and are spatially restricted [START_REF] Jiménez-Alfaro | A comparison of pointscoring procedures for species prioritization and allocation of seed collection resources in a mountain region[END_REF]. However, priority lists can be used to set up protection lists (e.g. [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF][START_REF] Martín | Using taxonomically unbiased criteria to prioritize resource allocation for oceanic island species conservation[END_REF][START_REF] Schatz | A decision tool for listing species for protection on different geographic scales and administrative levels[END_REF].

A hierarchisation classifies assets according to selected criteria. Many approaches choose a great number of criteria, up to 30 criteria (e.g. [START_REF] Millsap | Setting priorities for the conservation of fish and wildlife species in Florida[END_REF][START_REF] Reece | Prioritizing species by conservation value and vulnerability: A new index applied to species threatened by sea-level rise and other risks in Florida[END_REF][START_REF] Gaiarsa | Setting conservation priorities within monophyletic groups: An integrative approach[END_REF]. Usually, these criteria can be gathered in 3 main groups: threats (or vulnerability), which is often assessed as taxa IUCN status, rarity (or local distribution), and territorial responsibility (or endemism or international importance) (e.g. [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF][START_REF] Schatz | A decision tool for listing species for protection on different geographic scales and administrative levels[END_REF]. Beside these main criteria, other criteria are sometimes used, e.g. taxonomic distinctiveness, ongoing management, protection status, economic and social values, ecological feature… (e.g. [START_REF] Freitag | Relative occupancy, endemism, taxonomic distinctiveness and vulnerability: Prioritizing regional conservation actions[END_REF][START_REF] Carter | Setting conservation priorities for landbirds in the United States: the partners in flight approach[END_REF][START_REF] Pärtel | Grouping and prioritization of vascular plant species for conservation: Combining natural rarity and management need[END_REF][START_REF] Bacchetta | A new method to set conservation priorities in biodiversity hotspots[END_REF]. Among the methods for targeting species, we can distinguish focal species selection methods and setting priorities methods, and among the latter we can distinguish « point-scoring » methods (or cumulative systems) and « rule-based » methods (or categorical systems) [START_REF] Jiménez-Alfaro | A comparison of pointscoring procedures for species prioritization and allocation of seed collection resources in a mountain region[END_REF][START_REF] Mace | Prioritizing choices in conservation[END_REF]. Point-scoring methods are widely known, quantitative, reproducible and objective methods, and are based on readily measurable variables [START_REF] Jiménez-Alfaro | A comparison of pointscoring procedures for species prioritization and allocation of seed collection resources in a mountain region[END_REF]. In this study, we adapted the point-scoring method developed by [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF], a method which uses a small number of criteria, relatively easy to assess for a great number of taxa, and embodying the three main kinds of criteria. This method is easily reproducible and can be adapted to different administrative or biogeographical areas, different scales, and different plant groups. Different applications of the [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF] method [START_REF] Gauthier | Quantifying habitat vulnerability to assess species priorities for conservation management[END_REF][START_REF] Kricsfalusy | Prioritizing regionally rare plant species for conservation using herbarium data[END_REF][START_REF] Maciel | Prioritizing rare tree species of the Cerrado-Amazon ecotone: warnings and insights emerging from a comprehensive transitional zone of south America[END_REF][START_REF] Schatz | A decision tool for listing species for protection on different geographic scales and administrative levels[END_REF] all used the three same criteria, but assessed them in different ways, according to their particular context.

The South-Western Alps, located at the interface between the Alps mountains and the Mediterranean region, host many endemic plants, with very restricted distribution areas but shared between two countries, France and Italy. Therefore, a hierarchisation of taxa not applied to an administrative area but to a biogeographical area is a consistent approach with global conservation concerns. In fact, the biogeographical conservation approach (e.g. [START_REF] Ladle | Conservation biogeography[END_REF] enables to improve the definition of protection issues which is often biased by approaches reduced to administrative areas and whose methods and objectives can vary from an area to another [START_REF] Pärtel | Grouping and prioritization of vascular plant species for conservation: Combining natural rarity and management need[END_REF]. Inside the Mediterranean basin, one of the 35 biodiversity hotspots on a global scale [START_REF] Médail | Mediterranean basin[END_REF], Maritime and Ligurian Alps (which are an integrative part of South-Western Alps) constitute one of the 10 regional biodiversity hotspots. Biodiversity hotspots are defined as areas where exceptional concentrations of endemic species undergo exceptional loss of habitat [START_REF] Myers | Biodiversity hotspots for conservation priorities[END_REF]. They are both an endemism centre and a glacial refuge for Mediterranean and alpine flora [START_REF] Casazza | Ecological and historical factors affecting distribution pattern and richness of endemic plant species: The case of the Maritim and Ligurian Alps hotspot[END_REF][START_REF] Médail | Glacial refugia influence plant diversity patterns in the Mediterranean basin[END_REF][START_REF] Noble | La flore des Alpes-Maritimes et de la Principauté de Monaco. Originalité et diversité[END_REF]. The South-Western Alps have a great originality of flora with more than 150 endemic and subendemic taxa [START_REF] Aeschimann | Analyse de la flore des Alpes. 1: historique et biodiversité[END_REF]. Moreover, with the population increase and tourism boom, many low altitude taxa are critically threatened of extinction [START_REF] Médail | Ecological characteristics and rarity of endemic plants from southeast France and Corsica: Implications for biodiversity conservation[END_REF][START_REF] Noble | Liste Rouge de la flore vasculaire de Provence-Alpes-Côte d[END_REF][START_REF] Salanon | La flore littorale des Alpes-Maritimes : Evolutions depuis le XIXe siècle et bilan actuel[END_REF]. Refuge areas, containing a great biodiversity, are also threatened by human impacts because they are submitted to important pressures [START_REF] Médail | Biodiversité végétale méditerranéenne et anthropisation: Approches macro et micro-régionales[END_REF].

The purpose of this work is to rank patrimonial taxa of the South-Western Alps flora, a biodiversity hotspot, based on a limited number of standardised criteria readily available, aiming to prioritise their conservation concerns, and to compare this hierarchisation results with red lists and protection lists status.

Study area and taxa

Study area

The study area corresponds to the definition of the South-Western Alps according to [START_REF] Aeschimann | Analyse de la flore des Alpes. 1: historique et biodiversité[END_REF], extended to Provençal peripheral mountains, because it matches the distribution ranges of many endemic species (e.g. Berardia subacaulis, Campanula rotundifolia subsp. macrorhiza, Fritillaria involucrata, Helictotrichon sempervirens, Sempervivum calcareum etc.). In order to implement an efficient conservation, the study area must reflect the real distribution of species, not administrative boundaries. This geographical unit is not strictly homogeneous from a biogeographical point of view, because it is located at the limit between temperate Europe and the Mediterranean basin [START_REF] Takhtajan | Floristic regions of the world[END_REF], but it is a consistent ensemble in terms of geomorphology, in relation to its geological history, and reflects the reality of biological processes. This territory is a continuum from Mediterranean to alpine environments, going from sea level to more than 4000 m above the sea level. This particular location is one of the explanatory components of diversity and originality of the flora of this area [START_REF] Noble | La flore des Alpes-Maritimes et de la Principauté de Monaco. Originalité et diversité[END_REF]. The study area (Fig. 1) extends on about 43,000 km²:5000 km² in Italy (12%) and 38,000 km² in France (88%). 80% of Provence-Alpes-Côte d'Azur region (PACA, France) and 50% of Liguria region (Italy) are included in the study area. Two other administrative regions are also marginally included: Auvergne-Rhône-Alpes (France) and Piemonte (Italy).

Taxonomic targets

This work targets patrimonial taxa (vascular plants and mosses) which include: (i) endemic or subendemic taxa in the study area, (ii) threatened taxa, and (iii) taxa protected by law.

Endemic taxa distribution is entirely included in the study area and subendemic taxa distribution is included at least at 80% in the study area. Threatened taxa are classified in IUCN categories: CR (critically endangered), EN (endangered) or VU (vulnerable) in the national red lists in France and in Italy, or in the regional red lists in Liguria, Piemonte and Provence-Alpes-Côte d'Azur (PACA) [START_REF] Arillo | Lista rossa regionale delle specie presenti in Liguria incluse nell'allegato II della direttiva CEE 43/92 e nell[END_REF][START_REF] Noble | Liste Rouge de la flore vasculaire de Provence-Alpes-Côte d[END_REF][START_REF] Rossi | Lista Rossa della Flora Italiana. 1. Policy Species e altre specie minacciate. Italia[END_REF]UICN France, FCBN, MNHN, 2012). Protected taxa have a protection status at European, national (France or Italy) or regional (Liguria, Piemonte, PACA or Auvergne-Rhône-Alpes) levels. Exogenous taxa were excluded from this analysis, just as those not found since 1990. In total, 913 taxa are ranked, which represents about a quarter of the indigenous flora of the study area.

The occurrence data come (i) from the database SILENE-Flore of the Conservatoire botanique national méditerranéen de Porquerolles (CBNMed) and the Conservatoire botanique national alpin (CBNA) (http://flore.silene.eu) for PACA region, (ii) from the flora database of CBNA for Auvergne-Rhône-Alpes region, (ii) from the Libios database of the Agenzia Regionale per la Protezione dell'Ambiante Ligure (ARPAL) and of the Parco Naturale del Marguareis for Liguria region, and (iv) from the database of the Parco Naturale Alpi Marittime for Piemonte region. These geo-localised data were combined through a web-service developed in the framework of European program Alcotra n°192 BIODIVAM (http://biodivam.eu) based on a shared taxonomic reference document adapted for the study from TAXREF V5 [START_REF] Gargominy | TAXREF v5.0, référentiel taxonomique pour la France : mise en oeuvre et diffusion[END_REF] for France and from [START_REF] Pignatti | Flora d'Italia[END_REF] for Italy. In total almost 400,000 occurrence data were used in this work.

Methods and results

Selection and quantification of criteria

This hierarchisation method for taxa is adapted from the point-scoring method developed by [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF]. The three selected criteria are biogeographical rarity (adapted from the regional responsibility criterion), local rarity and potential threats to the taxa. This last criterion is assessed through two sub-criteria, habitat vulnerability and populations occurring in artificialised areas. Each criterion or sub-criterion is divided in 5 classes ranked from 1 to 5, 5 representing the score for the rarest or most threatened taxa (Table 1).

Biogeographical rarity criterion aims to prioritise taxa with a restricted global distribution [START_REF] Gauthier | Quantifying habitat vulnerability to assess species priorities for conservation management[END_REF]. It is assessed using chorology, a typology of global distribution of taxa [START_REF] Aeschimann | Analyse de la flore des Alpes. 1: historique et biodiversité[END_REF][START_REF] Pignatti | Flora d'Italia[END_REF][START_REF] Tison | Flora Gallica[END_REF][START_REF] Tison | Turriers: Naturalia Publications[END_REF]. Endemic taxa were defined as their distribution area is entirely included in the study area, whereas subendemic taxa were defined as 80% of their distribution area is included in the study area. Among widely distributed taxa (scoring 1 or 2) a bonus point is assigned to those reaching the limit of their distribution area, and those which have a disjointed distribution area.

Local rarity criterion aims to prioritise locally rare taxa in the study area, because they have a greater probability of going extinct because of stochastic factors [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF], even though the link between intrinsic rarity and extinction is not systematic (cf. [START_REF] Gaston | Rarity[END_REF]. This criterion is assessed as the number of occurrence grid cells (5 km × 5 km) of taxa in the study area. To limit bias of the grid position, the average number of occurrences obtained from 100 randomly placed grids was calculated (software R 3.0.2). The quantile method was used to split local rarity scores into 5 equal size classes.

Potential threats criterion aims to prioritise taxa threatened by extrinsic factors which can lead to a fast population decline and local extinction [START_REF] Kricsfalusy | Prioritizing regionally rare plant species for conservation using herbarium data[END_REF]. Two factors are taken into account for the assessment: habitat vulnerability and artificialisation. For each taxon, threats score was calculated as the average of habitat vulnerability score and artificialisation score.

Habitat vulnerability assesses the risk of habitat loss (in terms of surface or functionality) including both natural and artificial causes [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF]. It is defined as its sensitivity to pressures or threats and its capacity to face the damages caused by these pressures or threats [START_REF] Bensettiti | Evaluation de l'état de conservation des habitats et des espèces d'intérêt communautaire -Guide méthodologique[END_REF]. This assessment was carried out in 5 steps (Fig. 2) and based on EUNIS typology (EUropean Nature Information System) [START_REF] Louvel | EUNIS, European nature information system[END_REF]Bajjouk et al., 2015a,b vol. 1 and 2). To limit potential bias ensuing from expert opinion, we used the Delphi technique [START_REF] Hsu | The Delphi technique: making Sens of consensus[END_REF][START_REF] Mukherjee | The Delphi technique in ecology and biological conservation: Applications and guidelines[END_REF]. 33 EUNIS habitats (level 2) were assessed. We assigned one or two habitat types to taxa: in most cases we can consider that they have one or two main habitats, even if they can be found in others.

Soil artificialisation assessment aims to prioritise taxa whose populations occur in artificial areas [START_REF] Vimal | Detecting threatened biodiversity by urbanization at regional and local scales using an urban sprawl simulation approach: Application on the French Mediterranean region[END_REF]. We chose to add artificialisation sub-criterion because in this biodiversity hotspot, it represents a major threat to taxa through habitat loss (e.g. [START_REF] Médail | Biodiversité végétale méditerranéenne et anthropisation: Approches macro et micro-régionales[END_REF]. The vectorial shape from CORINE Land Cover, 2012 (level 1) was used to extract artificial lands: « artificial surfaces » (code 1), « arable land » (code 21) and « permanent crops » (code 22) were considered as artificial (software QGIS 2.6.1). For each taxon, an artificialisation percentage was calculated as the average artificialisation rate of all of its occurrence grid cells. The quantile method was used to split artificialisation scores into 5 equal size classes.

Hierarchisation of taxa

The final score was calculated using the sum of scores summarisation method (e.g. [START_REF] Millsap | Setting priorities for the conservation of fish and wildlife species in Florida[END_REF][START_REF] Sapir | Constructing red numbers for setting conservation priorities of endangered plant species: Israeli flora as a test case[END_REF][START_REF] Zhang | Extinction risk and conservation priority analyses for 64 endemic fishes in the upper Yangtze River, China[END_REF]: the final score is equal to the sum of biogeographical rarity score, local rarity score and threats score (Table 2). The equivalent class discretisation method was used to gather taxa into four priority levels (Table 3). Only one taxon obtained the maximum score of 15, Artemisia molinieri, and two taxa obtained the minimum score of 3, Huperzia selago and Ranunculus glacialis. More than 80% of taxa obtained a final score between 5.5 and 11. Only 4% of the taxa are classified as very high concern, and 15% as low concern. Very high and high concern taxa represent a little less than half of the taxa (44%) (Table 3).

Criteria determining conservation concerns

Taxa distribution is presented for each selected criterion and each conservation concern group (Fig. 3). For very high concern taxa (Fig. 3a), local rarity criterion is determining: all the taxa obtained a score of 5 for this criterion (less than 5 occurrence grid cells), except one that obtained a score of 4. Other criteria are also important, with about two thirds of taxa occurring in more than 30% of artificialised areas, about half being endemic of the study area, and about 40% occurring in threatened habitats. Two groups of locally rare and artificialised areas occurring taxa can be distinguished: (i) endemic taxa of the study area (17 taxa) with very narrow distributions (e.g. Acis fabrei), and (ii) taxa with wider global distribution but occurring in very threatened habitats (e.g. Cyperus capitatus).

For high concern taxa (Fig. 3b), local rarity is also a determining criterion: more than 70% of taxa obtained a score of 4 or 5 (less than 12 occurrence grid cells), and only one taxon obtained a score of 1 (Santolina decumbens, endemic of Provence). Artificialisation criterion is also important with about one third of taxa occurring in more than 30% artificialised areas. Biogeographical rarity and habitat vulnerability are quite evenly distributed. However, more than half of endemic taxa of the study area are classified as high concern. Two groups of locally rare taxa can be distinguished: (i) endemic taxa of the study area (e.g. Ballota frutescens), and (ii) taxa with wider global distribution but threatened by habitat vulnerability or soil artificialisation (e.g. Hydrocotyle vulgaris).

For moderate concern taxa (Fig. 3c), the four criteria are important, with about 70% of taxa occurring in moderately vulnerable habitats, about 60% relatively common in the study area (more than 34 occurrence grid cells), and more than half not occurring in artificial areas (less than 4% of populations in artificial areas) and having a wide distribution (e.g. Dracocephalum austriacum).

For low concern taxa (Fig. 3d), local rarity criterion is also determining: 97% of taxa obtained a score of 1 or 2 (more than 34 occurrence grid cells), and none obtained a score of 4 or 5 for this criterion. Biogeographical rarity and habitat vulnerability are also important: more than 85% of taxa obtained a score of 1 or 2, and none endemic or subendemic taxa was classified in this group. Habitat vulnerability is the only criterion for which some taxa obtained a score of 5 (Juncus filiformis, Pinguicula vulgaris, Primula farinosa and Triglochin

Table 1

Assigning scores ranging from 1 to 5 for each criterion or sub-criterion. Criteria Fig. 2. Assessment of the sub-criterion habitat vulnerability in 5 steps. One or two habitats were assigned to each taxon according to its known ecological preferences. Then the assessment was carried out independently by eight experts using a list of 13 pressures and threats (appendix 7 in [START_REF] Bensettiti | Evaluation de l'état de conservation des habitats et des espèces d'intérêt communautaire -Guide méthodologique[END_REF]. The final assessment was constructed using the Delphi technique, an information return process which enables and encourage participants to review their initial judgments in order to reach an opinion consensus (De Lange, Sala, Vighi, & Faber, 2010; [START_REF] Hsu | The Delphi technique: making Sens of consensus[END_REF]. Habitat vulnerability was calculated as the average of the 5 most important threats on each habitat, then turned into scores using the quintile method. palustre). Finally, about two thirds of the taxa occur in moderately artificial areas.

Tools

Comparison of hierarchisation results to red lists and protection lists

Taxa IUCN status in PACA [START_REF] Noble | Liste Rouge de la flore vasculaire de Provence-Alpes-Côte d[END_REF] and in Liguria [START_REF] Arillo | Lista rossa regionale delle specie presenti in Liguria incluse nell'allegato II della direttiva CEE 43/92 e nell[END_REF] red lists and legal status (European, national or regional protection) were compared to taxa conservation concerns in the present approach (Table 4). These two regional red lists were chosen because they cover administrative areas included for more than a half in the study area. Others red lists cover areas are too different to make a relevant comparison.

PACA red list taxa distribution shows a quite important consistency with conservation concerns defined by the hierarchisation (Table 4). In fact, very high and high concern taxa include 87% of the critically endangered taxa (CR), 78% of the endangered taxa (EN), 64% of the vulnerable taxa (VU) and 53% of the near-threatened taxa (NT). Only Liguria red list taxa distribution shows a low correlation with concerns defined in our hierarchisation (Table 4). In fact, 75% of critically endangered and endangered taxa, and 70% of vulnerable taxa are classified moderate or low concern in this hierarchisation. No Liguria red list taxon is classified very high concern.

Taxa distribution according to their conservation concern is not correlated to their legal status. In fact, about 30% of very high and high concern taxa do not have a protection status, and conversely, all low concern taxa but two (Corallorhiza trifida and Scutellaria alpina) have a protection status in France and/or in Italy. More than 40% of protected taxa in Italy are classified low concern taxa, and no very high concern taxon is protected in Italy. In this study, about 80% of taxa benefit from one or several protections statuses. Protected taxa are thus present in all concern groups, as a direct consequence of the initial selection of patrimonial taxa.

Discussion

Methodological choices

Results from hierarchisation methods can be very different between two different areas, even geographically close, so the area choice is critical. It should be defined in a consistent way either on a biogeographical approach or according to the chosen conservation strategy. The hierarchisation of all patrimonial species in a biogeographical area has the advantage of being consistent with the current challenges for plant conservation, particularly in a biodiversity hotspot where both endemism and threats are high and should be considered together.

Several hierarchisation or classification methods for fauna or flora exist; they can be point-scoring methods or categorical methods. To assess the different criteria, point-scoring methods use either directly the values of criteria (measured or calculated) (e.g. [START_REF] Freitag | Relative occupancy, endemism, taxonomic distinctiveness and vulnerability: Prioritizing regional conservation actions[END_REF][START_REF] Redding | Incorporating evolutionary measures into conservation prioritization[END_REF][START_REF] Gaiarsa | Setting conservation priorities within monophyletic groups: An integrative approach[END_REF], or discrete values (scores) with usually the same range for all criteria (e.g. [START_REF] Dunn | Priority-setting tool applied to Canada's landbirds based on concern and responsibility for species[END_REF][START_REF] Sapir | Constructing red numbers for setting conservation priorities of endangered plant species: Israeli flora as a test case[END_REF][START_REF] Jiménez-Alfaro | A comparison of pointscoring procedures for species prioritization and allocation of seed collection resources in a mountain region[END_REF][START_REF] Crain | Categorizing locally rare plant taxa for conservation status[END_REF][START_REF] Bacchetta | A new method to set conservation priorities in biodiversity hotspots[END_REF]. The advantage of

Table 4

Number of taxa in each concern group according to their IUCN status in PACA and Liguria red lists and according to their protection status in France and in Italy. the first approach is a better accuracy of scores, and the advantage of the second one is an easier use for methods including both qualitative and quantitative criteria, and whose values do not follow a normal distribution, as it is the case in this study. To combine the different scores, most of the methods calculate the sum or the average of scores, which lead to the same ranking, weighted or not (e.g. [START_REF] Millsap | Setting priorities for the conservation of fish and wildlife species in Florida[END_REF][START_REF] Sapir | Constructing red numbers for setting conservation priorities of endangered plant species: Israeli flora as a test case[END_REF][START_REF] Reece | Prioritizing species by conservation value and vulnerability: A new index applied to species threatened by sea-level rise and other risks in Florida[END_REF][START_REF] Zhang | Extinction risk and conservation priority analyses for 64 endemic fishes in the upper Yangtze River, China[END_REF]. Other calculations are possible, such as multiplication of scores (e.g. [START_REF] Rodríguez | Setting priorities for the conservation of Venezuela's threatened birds[END_REF][START_REF] Redding | Incorporating evolutionary measures into conservation prioritization[END_REF] or factorial summarisation of scores (e.g. [START_REF] Jiménez-Alfaro | A comparison of pointscoring procedures for species prioritization and allocation of seed collection resources in a mountain region[END_REF]. Another method to combine criteria is possible, ranking by criteria: all taxa are ranked with a first order criterion, then with a second order criterion, and so on until the last criterion (e.g. [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF][START_REF] Bacchetta | A new method to set conservation priorities in biodiversity hotspots[END_REF]. Combining scores in an only priority index is subject to methodological uncertainties because many different mathematical processes are possible. Selected criteria, their weighting, different ways to assess and combine scores can give very different outcomes [START_REF] Carter | Setting conservation priorities for landbirds in the United States: the partners in flight approach[END_REF][START_REF] Jiménez-Alfaro | A comparison of pointscoring procedures for species prioritization and allocation of seed collection resources in a mountain region[END_REF][START_REF] Reece | Prioritizing species by conservation value and vulnerability: A new index applied to species threatened by sea-level rise and other risks in Florida[END_REF], so we must be attentive in the method choice according to the study goal.

Four different applications of the Gauthier et al. ( 2010) method were already published [START_REF] Gauthier | Quantifying habitat vulnerability to assess species priorities for conservation management[END_REF][START_REF] Kricsfalusy | Prioritizing regionally rare plant species for conservation using herbarium data[END_REF][START_REF] Maciel | Prioritizing rare tree species of the Cerrado-Amazon ecotone: warnings and insights emerging from a comprehensive transitional zone of south America[END_REF][START_REF] Schatz | A decision tool for listing species for protection on different geographic scales and administrative levels[END_REF], and all of them adapted criteria assessment to their specific context. Our approach was also adapted to match our specific aims and constraints, which are distinctive features of regional biodiversity hotspots. Regional responsibility is here called biogeographical rarity and takes into account endemism [START_REF] Gauthier | Quantifying habitat vulnerability to assess species priorities for conservation management[END_REF], and distribution disjunctions and limits. Taking into account peripheral populations should not be neglected because they can potentially present local adaptations enabling them to better face global changes [START_REF] Bonin | Population adaptive index: A new method to help measure intraspecific genetic diversity and prioritize populations for conservation[END_REF][START_REF] Crain | Categorizing locally rare plant taxa for conservation status[END_REF][START_REF] Papuga | Comparative studies of ecological niche variation among central and peripheral populations of mediterranean endemic plants[END_REF]. Knowledge improvement through geo-localised observation data and connecting databases enables a more accurate assessment of the local rarity criterion. Using a randomly placed uniform grid reduces bias. The habitat vulnerability criterion of [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF] was turned into a threat criterion, adding an artificialisation criterion, which has a significant impact on the study area [START_REF] Lhotte | Are there contrasted impacts of urbanization and land uses on population persistence? The case of Teucrium pseudochamaepitys, an endangered species in Southern France[END_REF][START_REF] Vimal | Detecting threatened biodiversity by urbanization at regional and local scales using an urban sprawl simulation approach: Application on the French Mediterranean region[END_REF], and whose exponential increase these last decades is a major concern in urban planning policies in the European Union [START_REF] Meiner | The european environment, state and outlook 2010: land use[END_REF][START_REF] Virely | Artificialisation : de la mesure à l'action[END_REF]. In fact, land consumption due to urban development is a major concern because they mostly are non-renewable resources: land use changes to build houses or roads are usually permanent, or reversible only at very high costs [START_REF] Ludlow | Urban sprawl in europe: the ignored challenge[END_REF]. Other studies based on this method chose to use two or three sub-criteria to assess habitat vulnerability [START_REF] Gauthier | Quantifying habitat vulnerability to assess species priorities for conservation management[END_REF][START_REF] Kricsfalusy | Prioritizing regionally rare plant species for conservation using herbarium data[END_REF]. Assessment of habitat vulnerability remains delicate and needs an expert assessment which can be subjective, but bias can be reduced using the Delphi technique [START_REF] Hsu | The Delphi technique: making Sens of consensus[END_REF][START_REF] Mukherjee | The Delphi technique in ecology and biological conservation: Applications and guidelines[END_REF]. Finally, we used the sum of scores summarisation method to give the same weight to the different rarity and threat criteria, enabling to highlight in very high and high concerns locally rare taxa, or biogeographically rare taxa, or threatened taxa.

Hierarchisation contribution for taxa conservation

This hierarchisation draws up a typology of high conservation concern taxa, to better understand risks for taxa according to their rarity kind and threats, in order to implement adapted conservation actions [START_REF] Pärtel | Grouping and prioritization of vascular plant species for conservation: Combining natural rarity and management need[END_REF]. In fact, criteria scores reflect rarity or vulnerability of taxa, giving us a first idea about what to do to preserve them. The great majority of very high and high concern taxa are locally rare (94% of these taxa obtained a score of 4 or 5 for local rarity criterion), so this criterion is determining. Nevertheless, other criteria enable to distinguish two kinds of rarity: some taxa are naturally scarce, usually adapted to live in reduced and isolated populations (e.g. Acis nicaeensis), whereas others became rarer following disturbing events due to human impacts (e.g. Limonium sp.) [START_REF] Gaston | Rarity[END_REF]. Besides being locally rare, taxa of very high concern are generally threatened by surface artificialisation. The study area suffered these last decades from deep socio-economic changes which substantially modified ecosystemic dynamic tendencies (i.e. [START_REF] Barbero | Changes and disturbances of forest ecosystems caused by human activities in the western part of the Mediterranean basin[END_REF]. These serious environment changes led to the rarefaction or even extinction of several populations. Scores obtained for each criterion will enable us to target conservation or monitoring actions adapted for each taxon, taking into account the need for conservation actions, the expected benefit, the success probability and the cost of conservation actions [START_REF] Joseph | Optimal allocation of resources among threatened species: A project prioritization protocol[END_REF].

An approach complementing red lists and protection lists

Differences between red lists status and our hierarchisation results are mainly due to differences between chosen criteria and between application areas. Red lists of threatened species are developed to assess extinction risks of taxa in a given area, and are based on five criteria: (A) population size reduction, (B) extent of occurrence or area of occupancy, (C) small population size and decline, (D) very small or restricted population, and (E) quantitative analysis (IUCN, 2012). However, neither of these criteria report biogeographical rarity (except in the case of a global IUCN assessment) nor habitat vulnerability. Although threats and local rarity criteria seem quite close to IUCN criteria, hierarchisation results are noticeably different from red lists outcomes. This difference is more significant for the Liguria red list. In fact, if 869 taxa (95%) assessed in our hierarchisation are also assessed in the PACA red list, only 90 taxa (9%) assessed in our hierarchisation are also assessed in the Liguria red list, due to the geographical distribution of the study area, shared unevenly between France and Italy. Consequently, many common taxa in the South-Western Alps reach their distribution limit in Liguria, where they tend to be rather rare and threatened. Red lists have the advantage of taking into account the edge effect and to anticipate taxonomic sensitivity using a data deficient (DD) category, for little known taxa or controversial taxonomic value taxa. A hierarchisation carried out in a biogeographical territory, even as heterogeneous as the South-Western Alps, enables to provide components required to implement a long term biogeographical conservation, whereas red lists face urgency. Finally, red lists cannot be used directly, but they embody a critical first step before conservation actions priority-setting [START_REF] Fitzpatrick | Building on IUCN regional red lists to produce lists of species of conservation priority: A model with Irish bees[END_REF][START_REF] Rodríguez | Setting priorities for the conservation of Venezuela's threatened birds[END_REF].

These hierarchisation results are not correlated to national or regional protection lists of species in France and in Italy. [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF] also noticed a low consistency between the results of their hierarchisation and regional protection lists in Languedoc-Roussillon. In this study, the major part of assessed taxa is already protected, so this hierarchisation is especially important to define priorities between those taxa. Conversely, more than half of non-protected taxa are classified as very high or high concern: highlighting these taxa will enable to implement efficient conservation measures. The divergence between protection lists and taxa concern in our study can be explained for different reasons. Firstly, protection lists were set up more than 20 years ago, and knowledge improved greatly since then, especially in terms of computing technology, which highlighted the rarity status of all species. Secondly, protection lists were set up using expert opinion, whereas our approach was based a standard method. Thirdly, some species were obviously put on protection lists to protect their habitat, even if they were not especially rare. Fourthly, protection lists usually don't include species growing in agricultural systems. Fifthly, protection lists considered administrative areas and not a biogeographical area as we did. Therefore, a lot high or very high concern are not protected.

If administrative approaches enable to ensure populations' protection in a given area, they do not incorporate the global distribution of taxa. The weakness of administrative approaches is mostly felt around the borders, and when study areas are not equally divided between countries (here for example, 88% of the study area is located in France). Thus, red lists and protection lists do not provide information about taxa conservation priorities, because they were not developed for this purpose. Therefore, hierarchisation of taxa is a complementary approach which enables to orientate conservation strategies in a transparent way.

Conclusion

To focus on a regional biodiversity hotspot matching the distribution of numerous endemic species, and submitted to high artificialisation levels, the hierarchisation method must be improved in order to take into account the two most important parameters. In this context, we classified taxa into concern priorities to best allocate available resources for conservation actions for patrimonial taxa. This hierarchisation is versionable and progressive with knowledge improvement and land cover changes, and will be regularly updated. The discrepancy between our approach and red lists and protection lists highlights a strong requirement to implement a strategy taking into account the cross-border context, with shared information and data standards. In this context, our results show an important need for a collaborative work between countries and regions for an efficient conservation of patrimonial flora, especially those not listed in the red lists and protection lists. It is important to keep in mind that no hierarchisation system can give the « right answer » for all taxa or all users, whatever the number of included criteria or the way to combine them. Differences between categorisation systems are less important than the need to implement these processes, as long as objectives are well defined, to develop strategies to make conservation actions more efficient [START_REF] Dunn | Priority-setting tool applied to Canada's landbirds based on concern and responsibility for species[END_REF]. In this way, we used a standard and robust method, already used in different contexts around the world, and strengthened it in considering the parameters enabling to define a biodiversity hotspot: endemic species richness and habitat loss risk.

Fig. 1 .

 1 Fig. 1. Study area: the South Western Alps. It includes parts of four different administrative regions of two different countries, France and Italy.

  Abbreviations: biogeo. = biogeographical, vuln. = vulnerability, artif. = artificialisation, nb. = number, stenomed. = stenomediterranean.

Fig. 3 .

 3 Fig. 3. Distribution of the scores of taxa in the different concern groups. For each concern group, this figure shows how many taxa were scored 1, 2, 3, 4 or 5 for the different criteria. Abbreviations: biogeo. = biogeographical, vuln. = vulnerability.

Abbreviations:

  Abbreviations: CR = Critically endangered, EN = Endangered, VU = Vulnerable, NT = Near Threatened, LC = Least Concern, RE = Regionally Extinct, NA = non-practical, DD = Data Deficient, LR = Low Risk, Fr = France, It = Italy.

Table 2

 2 Hierarchisation of taxa according to their final scores, which is the sum of biogeographical rarity score, local rarity score and threats score (which is the average of habitat vulnerability score and artificialisation score), for the 50 top-ranked taxa (see the hierarchisation of all taxa in the appendix).

	Taxa names	Biogeo. rarity score	Local rarity score	Habitat vuln. score	Artif. score	Threats score	Final score	Rank	Concern
	Artemisia molinieri	5	5	5	5	5	15	1	Very high
	Romulea arnaudii	5	5	3	5	4	14	2	Very high
	Armeria arenaria subsp. pradetensis	5	5	2	5	3.5	13.5	3	Very high
	Acis fabrei	5	5	2	4	3	13	4	Very high
	Centaurea paniculata subsp. gallinariae	5	5	2	4	3	13	4	Very high
	Centaurea pseudocineraria	5	5	1	5	3	13	4	Very high
	Molineriella minuta	3	5	5	5	5	13	4	Very high
	Romulea florentii	5	5	2	4	3	13	4	Very high
	Scrophularia canina subsp. ramosissima	3	5	5	5	5	13	4	Very high
	Senecio leucanthemifolius subsp. crassifolius	5	4	3	5	4	13	4	Very high
	Teucrium dunense	3	5	5	5	5	13	4	Very high
	Verbena supina	3	5	5	5	5	13	4	Very high
	Armeria arenaria subsp. peirescii	5	5	2	3	2.5	12.5	5	Very high
	Armeria belgenciensis	5	5	2	3	2.5	12.5	5	Very high
	Bellevalia trifoliata	3	5	4	5	4.5	12.5	5	Very high
	Iberis linifolia subsp. stricta	5	5	1	4	2.5	12.5	5	Very high
	Matthiola tricuspidata	3	5	4	5	4.5	12.5	5	Very high
	Taraxacum leucospermum	5	5	2	3	2.5	12.5	5	Very high
	Achillea maritima	2	5	5	5	5	12	6	Very high
	Anthyllis cytisoides	3	5	3	5	4	12	6	Very high
	Aristolochia paucinervis	3	5	3	5	4	12	6	Very high
	Artemisia insipida	5	5	2	2	2	12	6	Very high
	Catapodium hemipoa	2	5	5	5	5	12	6	Very high
	Centaurea jordaniana subsp. aemilii	5	5	2	2	2	12	6	Very high
	Centaurea jordaniana subsp. balbisiana	5	5	1	3	2	12	6	Very high
	Cutandia maritima	2	5	5	5	5	12	6	Very high
	Cyperus capitatus	2	5	5	5	5	12	6	Very high
	Elatine alsinastrum	2	5	5	5	5	12	6	Very high
	Erodium rodiei	5	5	2	2	2	12	6	Very high
	Malcolmia ramosissima	2	5	5	5	5	12	6	Very high
	Myosotis pusilla	2	5	5	5	5	12	6	Very high
	Ranunculus millefoliatus	3	5	4	4	4	12	6	Very high
	Riella notarisii	2	5	5	5	5	12	6	Very high
	Rumex hydrolapathum	2	5	5	5	5	12	6	Very high
	Silene petrarchae	5	5	2	2	2	12	6	Very high
	Stachys maritima	2	5	5	5	5	12	6	Very high
	Viola arborescens	3	5	3	5	4	12	6	Very high
	Centaurium favargeri	3	5	3.5	4	3.75	11.75	7	High
	Leucojum aestivum subsp. aestivum	2	5	4.5	5	4.75	11.75	7	High
	Ranunculus garganicus	5	4	2.5	3	2.75	11.75	7	High
	Silene badaroi	3	5	3.5	4	3.75	11.75	7	High
	Teucrium polium subsp. purpurascens	5	4	2.5	3	2.75	11.75	7	High
	Acis nicaeensis	5	3	2	5	3.5	11.5	8	High
	Allium tenuiflorum	3	5	2	5	3.5	11.5	8	High
	Anacamptis longicornu	3	5	2	5	3.5	11.5	8	High
	Aquilegia ophiolitica	5	5	2	1	1.5	11.5	8	High
	Astragalus epiglottis	3	5	2	5	3.5	11.5	8	High
	Cistus crispus	2	5	4	5	4.5	11.5	8	High
	Elatine hydropiper subsp. macropoda	2	5	5	4	4.5	11.5	8	High
	Genista linifolia	3	4	4	5	4.5	11.5	8	High
	Abbreviations: biogeo. = biogeographical, vuln. = vulnerability, artif. = artificialisation.

Table 3

 3 Determination of taxa conservation concerns according to their final scores.

	Final score	Rank	Conservation	Number of
			concern	taxa
	12 ≤ final score ≤ 15	From rank 1 to	Priority 1: very high	37
		rank 6
	9 ≤ final score ≤ 11.75	From rank 7 to	Priority 2: high	366
		rank 18
	6 ≤ final score ≤ 8.75	From rank 19	Priority 3: moderate	374
		to rank 30
	3 ≤ final score ≤ 5.75	From rank 31	Priority 4: low	136
		to rank 42

one very high concern taxon is a PACA red list least concern taxa (LC): Senecio leucanthemifolius subsp. crassifolius, a strictly coastal taxon. Low and moderate concern taxa include 87% of the least concern taxa. However, an endangered taxon (Diphasiastrum alpinum) and 4 vulnerable taxa (Allium victorialis, Kalmia procumbens, Lappula deflexa and Lunaria rediviva) were classified as low concern in our hierarchisation. They are widely distributed taxa (boreal or Eurasian) occurring in moderately threatened habitats and moderately artificialised areas. An edge effect is noticed in our results for strictly coastal taxa, which are present only at the border of the study area and so obtained high local rarity and artificialisation scores.

Journal for Nature Conservation 42 (2018) [19][20][21][22][23][24][25][26][27]

Acknowledgements

This work was supported by FEDER funds from European program Alcotra n°258 Natura 2000 ADM Progres, the Provence-Alpes-Côted'Azur (PACA) region, and the Direction Régionale de l'Environnement, de l'Aménagement et du Logement Provence-Alpes-Côte d'Azur (DREAL PACA). The authors thank Benoît Offerhaus, Chiara Montagnani, Francesca Magillo and Fulvio Dente for habitat assessment; Olivier Gavotto, Guilhem Debarros, Henri Michaud, Jérémie Van Es and Jean-Charles Villaret for data processing and validation; Guillaume Papuga for reviewing the manuscript; and Benoît Strauss for English language improvement.