Devenirs militants:Introduction

Présenter un dossier sur l’engagement qui mette sur le même plan les pratiques militantes dans les partis politiques, les organisations syndicales, le monde associatif et plus généralement les entreprises de mouvement social, pourra paraître osé. C’est que, pendant longtemps, le militantisme a été pensé sous les seules espèces du travail partisan et syndical, dans un contexte où la définition de la participation politique demeurait étroitement cantonnée à l’action dite « conventionnelle ». [Premier paragraphe de l'article

Appendix B. A set of equations showing asymptotic speed of invasion.

A set of equations showing asymptotic speed of invasion

Danthonioideae Occurrences

Data with geographic locations for the 40,331 Danthoniodieae occurrences. Column names as follows: species name ('species'), longitude ('long') and latitude ('lat'), bioclimatic variables ('bio_1' to 'bio_19'), as extracted from the 'WorldClim' database (definitions see: http://www.worldclim.org/bioclim). Further information about WorldClim at Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978. http://dx.doi.org/10.1002/joc.127

Response of spatial vegetation distribution in China to climate changes since the Last Glacial Maximum (LGM)

<div><p>Analyzing how climate change affects vegetation distribution is one of the central issues of global change ecology as this has important implications for the carbon budget of terrestrial vegetation. Mapping vegetation distribution under historical climate scenarios is essential for understanding the response of vegetation distribution to future climatic changes. The reconstructions of palaeovegetation based on pollen data provide a useful method to understand the relationship between climate and vegetation distribution. However, this method is limited in time and space. Here, using species distribution model (SDM) approaches, we explored the climatic determinants of contemporary vegetation distribution and reconstructed the distribution of Chinese vegetation during the Last Glacial Maximum (LGM, 18,000 ¹⁴C yr BP) and Middle-Holocene (MH, 6000 ¹⁴C yr BP). The dynamics of vegetation distribution since the LGM reconstructed by SDMs were largely consistent with those based on pollen data, suggesting that the SDM approach is a useful tool for studying historical vegetation dynamics and its response to climate change across time and space. Comparison between the modeled contemporary potential natural vegetation distribution and the observed contemporary distribution suggests that temperate deciduous forests, subtropical evergreen broadleaf forests, temperate deciduous shrublands and temperate steppe have low range fillings and are strongly influenced by human activities. In general, the Tibetan Plateau, North and Northeast China, and the areas near the 30°N in Central and Southeast China appeared to have experienced the highest turnover in vegetation due to climate change from the LGM to the present.</p></div

Hindcasted past distribution of natural vegetation during (A) the Last Glacial Maximum (LGM) and (B) the Mid-Holocene (MH) and (C) the proportion (%) of each vegetation type (LGM: dark blue line; MH: orange line; modeled: dark gray line).

<p>In (C), the proportion (%) of a vegetation type was calculated as the ratio of its distribution range relative to the terrestrial area of China.</p

The AUC values of the Generalized Linear Models (GLMs) and MaxEnt for each vegetation type.

<p>The AUC values of the Generalized Linear Models (GLMs) and MaxEnt for each vegetation type.</p

Comparison between model-based and pollen-based vegetation reconstructions during the Mid-Holocene (MH).

<p>Panels (A) to (G) map the hindcasted climatic suitability of the shown vegetation types, while panels (H) to (N) map the hindcasted binary distribution of each vegetation type. The blue dots in the maps represent the pollen sites for which the same vegetation type was identified for the MH.</p

Appendix B. A table showing the expected number of detections based on model-assisted sampling for Pseudocyphellaria rainierensis and Nephroma laevigatum from the classification tree model of Lobaria pulmonaria.

A table showing the expected number of detections based on model-assisted sampling for Pseudocyphellaria rainierensis and Nephroma laevigatum from the classification tree model of Lobaria pulmonaria

Appendix A. A table showing the expected number of detections on model-assisted sampling for Pseudocyphellaria rainierensis from the classification tree model of Lobaria oregana.

A table showing the expected number of detections on model-assisted sampling for Pseudocyphellaria rainierensis from the classification tree model of Lobaria oregana

Kappa values between model-based and pollen-based vegetation reconstructions in the LGM and the MH for seven major vegetation types in both LGM and MH.

<p>Kappa values between model-based and pollen-based vegetation reconstructions in the LGM and the MH for seven major vegetation types in both LGM and MH.</p