A new method for identifying and mapping areas vulnerable to Covid-19 in an armed conflict zone: Case study north-west Syria.

In the context of the Covid-19 pandemic, a method for identifying and mapping vulnerable areas in an armed conflict zone seems necessary to limit the risk and anticipate the spread of contamination. It may also assist in the preparation of health infrastructures and the development of strategies to manage such infrastructures as this pandemic, which affects the whole world and has created chaos in fragile states, is causing significant problems in armed conflict zones. To achieve these objectives, geographic information technologies, remote sensing and spatial modelling currently offer new potential for anticipating the spread of risk in armed conflict zones and better managing health or natural emergencies. In this paper, we present the Risk of Vulnerability to COVID-19 in War Zones Index "Id_Covid19_WZ". This index was calculated based on several factors and by using spatial data. A risk map was then created from this data developed for the north-west of Syria, an area where there has been intense fighting for several years.•Identify areas vulnerable to the Covid-19 pandemic.•Anticipating the spread of risk in armed conflict zones.•Using remote sensing and spatial modelling to managing health emergencies.

New method for environmental monitoring in armed conflict zones: a case study of Syria.

Today, armed conflict affects some twenty countries, covering an area making up 11% of the surface area of the Earth. Any degradation of nature in these areas represents a harmful depletion of the world's natural heritage. Despite this, environmental issues are neglected during these periods of conflict, considered secondary to the urgency of restoring peace and safeguarding human life. Yet their consequences are potentially severe. In these areas, it is future generations who will suffer the effects of the current devastation for a very long time. In this context, the method developed in this study, named (Geographic Information System) for Environmental Monitoring in Wartime, can be used to calculate a risk indicator for environmental degradation, spatial monitoring and risk management. This will make it possible to identify the main threats to protected areas, catalogue the damage caused to the environment by armed conflicts and create a dynamic risk map. In this paper, GIS-EMW has been applied to calculate a risk indicator for environmental degradation in Syria.

Data maps and method for evaluating the indicator of the risk of propagation of invasive exotic plant species on work zones.

Invasive exotic plant species are considered a serious threat to plant diversity. Creating work zones involves actions that disturb balances existing among species in the ecosystems and thus promote the propagation and the development of invasive plants. In this context, the Gaz Reseau Distribution France «GRDF¼, the major french natural gas distributor, with the support of the French National Museum of Natural History «MNHN¼ and the Research center focused on innovation in gas and new energy sources ENGIE Lab CRIGEN, sought to develop a method for evaluating the risk of propagation of invasive alien plant species in GRDF work zones. When these kind of species are identified, in a woks zone the method calculates the risk of propagation, and depending on the case, specific actions can be recommended. The aim of this paper is to provide data maps and to explain the method developed for the calculation of the risk of propagation of invasive alien plant species in work zones.

Ecological specialization and rarity indices estimated for a large number of plant species in France.

The biological diversity of the Earth is being rapidly depleted due to the direct and indirect consequences of human activities. Specialist or rare species are generally thought to be more extinction prone than generalist or common species. Testing this assumption however requires that the rarity and ecological specialization of the species are quantified. Many indices have been developed to classify species as generalists vs. specialists or as rare vs. common, but large data sets are needed to calculate these indices. Here, we present a list of specialization and rarity values for more than 2800 plant species of continental France, which were computed from the large botanical and ecological dataset SOPHY. Three specialization indices were calculated using species co-occurrence data. All three indices are based on (dis)similarity among plant communities containing a focal species, quantified either as beta diversity in an additive (Fridley et al., 2007 [6]) or multiplicative (Zeleny, 2008 [15]) partitioning of diversity or as the multiple site similarity of Baselga et al. (2007) [1]. Species rarity was calculated as the inverse of a species occurrence.