| Literature DB >> 32795318 |
Graziela Dias Blanco1, Rafael Barbizan Sühs2, Escarlet Brizola2, Patrícia Figueiredo Corrêa3, Mari Lucia Campos4, Natalia Hanazaki2.
Abstract
BACKGROUND: Mining activities have environmental impacts due to sediment movement and contamination of areas and may also pose risks to people's food security. In Brazil, the majority of coal mining activities are in the south, in the Santa Catarina carboniferous region. In this region, previously mined areas contaminated with heavy metals frequently occur nearby inhabited zones. Mining is part of the daily lives of local communities, and its environmental impacts are visible in the landscape; however, plants with medicinal and food use from these areas can be still consumed. Heavy metals are contaminants that do not have odor, color, or taste, and are therefore difficult to detect. We aimed to verify whether people use plants from contaminated mine areas, and understand which factors can influence the use of these resources, even from areas visibly impacted.Entities:
Keywords: Coal mining; Ethnoecology; Food security; Local communities
Mesh:
Substances:
Year: 2020 PMID: 32795318 PMCID: PMC7427890 DOI: 10.1186/s13002-020-00398-w
Source DB: PubMed Journal: J Ethnobiol Ethnomed ISSN: 1746-4269 Impact factor: 2.733
Fig. 1Study area. Each number corresponds to a mining community: 1, Barreiros; 2, Guaitá; 3, Rio Carvão; 4, Volta Redonda; 5, Rio Morozini; 6, Vila Funil; 8, Vila São Jorge; 9, Rio Fiorita; 10, Santa Luzia; 11, São Sebastião Alto; 12, Santa Augusta; 13, São Sebastião; and 14, Cidade Alta
General information of localities, total rural population of each municipality, total number of families per community living nearby mining areas, and number of interviews
| Municipality | Total rural population of the municipality | Locality | No. of families per mining community | No. of interviews |
|---|---|---|---|---|
| Siderópolis | 2944 | Vila Funil | 35 | 16 |
| Vila São Jorge | 20 | 7 | ||
| Rio Fiorita | 36 | 20 | ||
| Lauro Muller | 3261 | Barreiros | 27 | 16 |
| Guaitá | 21 | 19 | ||
| Criciúma | 2678 | Santa Luzia | 37 | 8 |
| Vila Visconde | 35 | 11 | ||
| São Sebastião Alto | 25 | 8 | ||
| Santa Augusta | 14 | 10 | ||
| São Sebastião | 25 | 12 | ||
| Treviso | 1694 | Volta Redonda | 24 | 11 |
| Rio Morozini | 26 | 16 | ||
| Urussanga | 8818 | Rio Carvão | 32 | 25 |
| Forquilhinha | 4122 | Cidade Alta | 23 | 16 |
Summary of the variables raised during the interviews and used in the GLM analysis as tested variables
| Variable | Explanation |
|---|---|
| Perception | Observing environmental changes where you live. |
| 1 Positive—has observed positive changes over time in the landscape, such as increased plants and animals. | |
| 2 Neutral—not observed any change. | |
| 3 Negative—has observed negative changes over time in the landscape, such as species loss. | |
| Locality | Local community. |
| Gender | Men and woman. |
| These areas | In which mined context the interviewee lives. |
| Mined and abandoned area: these areas are visibly degraded and with exposed tailings. | |
| Mined and abandoned area partially restored: these are greener areas with soil covered by a layer of clay and grass. | |
| Residence time | How many years have residents lived in this community. |
Species cited exclusively as collected by 195 interviewees, number of citations per species, uses, and salience (Smith’s index)
| Species | Smith index | Salience | No. of citations | Use |
|---|---|---|---|---|
| 0.12 | 0.00 | 30 | F | |
| 0.09 | 0.00 | 25 | F | |
| 0.07 | 0.00 | 18 | F | |
| 0.06 | 0.00 | 14 | F | |
| 0.05 | 0.01 | 12 | M | |
| 0.01 | 0.04 | 7 | M | |
| 0.01 | 0.01 | 6 | M | |
| 0.01 | 0.02 | 4 | F | |
| 0.00 | 0.00 | 3 | M | |
| 0.00 | 0.00 | 3 | M | |
| 0.00 | 0.00 | 3 | M | |
| 0.00 | 0.00 | 21 | F/M | |
| 0.02 | 0.28 | 16 | M | |
| 0.03 | 0.42 | 12 | F | |
| 0.04 | 0.16 | 11 | M | |
| 0.01 | 0.08 | 9 | M | |
| 0.01 | 0.08 | 6 | F | |
| 0.01 | 0.06 | 4 | F |
F food; M medicinal
Summary of models and variables tested with GLM
| Mod. | Int. | Loc | Tip | Perc. | Gend. | Time | df | LogLik | AIC | Delta | Weight |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 2.074 | + | + | 0.004711 | 17 | 677.842 | 1389.7 | 0 | 0.276 | ||
| 30 | 2.089 | + | + | + | 0.004885 | 18 | 677.064 | 1390.1 | 0.44 | 0.221 | |
| 6 | 2.231 | + | + | 16 | 683.686 | 1399.4 | 9.69 | 0.002 | |||
| 14 | 2.245 | + | + | + | 17 | 683.281 | 1400.6 | 10.88 | 0.001 | ||
| 18 | 1.93 | + | 0.006767 | 15 | 693.262 | 1416.5 | 26.84 | 0 | |||
| 26 | 1.941 | + | + | 0.006944 | 16 | 692.789 | 1417.6 | 27.89 | 0 | ||
| 2 | 2.148 | + | 14 | 706.557 | 1441.1 | 51.43 | 0 | ||||
| 10 | 2.152 | + | + | 15 | 706.524 | 1443 | 53.36 | 0 | |||
| 31 | 2.206 | + | + | + | 0.005626 | 6 | 769.991 | 1552 | 162.3 | 0 | |
| 23 | 2.19 | + | + | 0.005439 | 5 | 771.065 | 1552.1 | 162.5 | 0 | ||
| 29 | 2.163 | + | + | 0.005814 | 5 | 771.186 | 1552.4 | 162.7 | 0 | ||
| 21 | 2.145 | + | 0.005621 | 4 | 772.312 | 1552.6 | 162.9 | 0 | |||
| 17 | 2.016 | 0.006696 | 2 | 781.196 | 1566.4 | 176.7 | 0 | ||||
| 25 | 2.029 | + | 0.006896 | 3 | 780.429 | 1566.9 | 177.2 | 0 | |||
| 19 | 2.045 | + | 0.006546 | 3 | 780.473 | 1566.9 | 177.3 | 0 | |||
| 27 | 2.057 | + | + | 0.006744 | 4 | 779.747 | 1567.5 | 177.8 | 0 | ||
| 7 | 2.366 | + | + | 4 | 779.804 | 1567.6 | 177.9 | 0 | |||
| 15 | 2.382 | + | + | + | 5 | 779.256 | 1568.5 | 178.8 | 0 | ||
| 5 | 2.318 | + | 3 | 781.676 | 1569.4 | 179.7 | 0 | ||||
| 13 | 2.335 | + | + | 4 | 781.111 | 1570.2 | 180.5 | 0 | |||
| 3 | 2.264 | + | 2 | 794.521 | 1593 | 203.4 | 0 | ||||
| 1 | 2.23 | 1 | 796.017 | 1594 | 204.4 | 0 | |||||
| 11 | 2.271 | + | + | 3 | 794.403 | 1594.8 | 205.1 | 0 | |||
| 9 | 2.238 | + | 2 | 795.888 | 1595.8 | 206.1 | 0 |
Mod. model number, Int. intercept value, Loc. locality, Tip type of area (i.e., either abandoned or partially restored), Perc. perception of landscape changes, Gend. gender, Time residence time, df degrees of freedom, LogLik likely distribution of observed data, AIC Akaike Information Criterion, Delta difference of each model in relation to the model selected by AIC, Weight model weight
Fig. 2Graphical representation of the explanatory variables of the selected GLM model in relation to the number of species citations according to locality (1 to 14), residence time, and perception of landscape changes (i.e., 1, positive; 2, neutral; and 3, negative)