| Literature DB >> 24066105 |
Guo-Qi Chen1, Yun-He He, Sheng Qiang.
Abstract
Arable areas are commonly susceptible to alien plant invasion because they experience dramatic environmental influences and intense anthropogenic activity. However, the limited reports on relevant factors in plant invasion of croplands have addressed single or a few invasive species and environmental factors. To elucidate key factors affecting plant invasions in croplands, we analyzed the relationship between 11 effective factors and changes in composition of alien plants, using field surveys of crop fields in Anhui Province conducted during 1987-1990 (historical dataset) and 2005-2010 (recent dataset), when rapid urbanization was occurring in China. We found that in the past few decades, the dominance and richness of alien plant populations approximately doubled, despite differences among the 4 regions of Anhui Province. Among the 38 alien invasive plant species observed in the sites, the dominance values of 11 species increased significantly, while the dominance of 4 species decreased significantly. The quantity of chemical fertilizer and herbicide applied, population density, agricultural machinery use, traffic frequency, and annual mean temperature were significantly related to increased richness and annual dominance values of alien plant species. Our findings suggest that the increase in alien plant invasions during the past few decades is primarily a result of increased application of chemical fertilizer and herbicides.Entities:
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Year: 2013 PMID: 24066105 PMCID: PMC3774639 DOI: 10.1371/journal.pone.0074136
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Sites surveyed during 1987–1990 (Δ) and 2005–2010 (○) in summer crop fields in Anhui Province, China.
Visual scoring method for weed dominance value in crop fields.
| Maximum height in field | |||
| Code | >80 cm | 20cm–80 cm | <20cm |
| 0.1 | 1–3 stems or total coverage <0.1% | <10 stems or total coverage <1% | <15 stems or total coverage <2% |
| 0.5 | 4–10 stems or total coverage 0.2%–0.9% | 11–15 stems or total coverage 1%–2% | 16–30 stems or total coverage 3%–5% |
| 1 | 11–15 stems or total coverage 1%–2% | 16–30 stems or total coverage 3%–5% | 31–60 stems or total coverage 6%–10% |
| 2 | 16–30 stems or total coverage 3%–5% | 31–60 stems or total coverage 6%–10% | 61–100 stems or total coverage 11%–25% |
| 3 | 31–60 stems or total coverage 6%–10% | 61–100 stems or total coverage 11%–25% | 101–200 stems or total coverage 25%–50% |
| 4 | 61–100 stems or total coverage 11%–25% | 101–200 stems or total coverage 25%–50% | 201–500 stems or total coverage 50%–90% |
| 5 | >100 stems or total coverage >25% | >200 stems or total coverage >50% | >500 stems or total coverage >90% |
Mean values of environmental factors of 130 historical sites and 147 recent sites examined in this study.
| Factor | Historic | Recent |
| Crop type (oilseed rape or wheat) | – | – |
| Crop rotation (wet-dry crop or just dry crops) A | – | – |
| Mean temperature of the coldest month (January, °C) | 3.79 | 3.09* |
| Mean temperature of the hottest month (July, °C) | 28.45 | 28.52 |
| Annual mean temperature (°C) | 15.88 | 16.47* |
| Annual mean precipitation (mm) | 1671.02 | 1239.29* |
| Population density (people/km2) | 329.54 | 485.30* |
| Traffic frequency (Freight turnover (104 ton km/km2)) | 7.02 | 341.74* |
| Net cropland agricultural machinery power (kw/ha.) | 4.01 | 12.11* |
| Net cropland chemical fertilizer applied (kg/ha.) | 374.66 | 782.20* |
| Net cropland herbicide applied (kg/ha.) | 0.53 | 9.77* |
For each environmental factor, mean values of historical and recent datasets in 31 grids (see Figure 1) were compared with paired-sample t-tests. Note: A: the preceding crops in fields with wet-dry crop rotation were wet rice, while those in lands with dry crop rotation were dry crops such as soybean, corn, and cotton. “*”: P<0.05 and “”: not significant.
Alien weed species, and their frequencies and change in dominance value (DV), among all sites surveyed between 1987–1992 (historical, 130 sites) and 2005–2010 (recent, 147 sites).
| Species | Frequency recent (%) | Frequency historical (%) | Change in DV |
|
| 90.79 | 22.96 | 0.554* |
|
| 85.53 | 59.26 | 0.152* |
|
| 69.74 | 8.89 | 0.210* |
|
| 65.79 | 65.93 | −0.041 |
|
| 61.84 | 13.33 | 0.022 |
|
| 61.18 | 26.67 | 0.129* |
|
| 58.55 | 47.41 | −0.029* |
|
| 39.47 | 18.52 | 0.152* |
|
| 28.95 | 0.74 | 0.014* |
|
| 26.97 | 4.44 | 0.044* |
|
| 26.97 | 1.48 | 0.086* |
|
| 25.00 | 0 | 0.045* |
|
| 20.39 | 0.74 | 0.060* |
|
| 14.47 | 1.48 | 0.011* |
|
| 12.50 | 34.81 | −0.208* |
|
| 11.18 | 0 | 0.007 |
|
| 11.18 | 5.19 | 0.005 |
|
| 7.24 | 17.04 | 0.019 |
|
| 4.61 | 0.74 | 0.014 |
|
| 3.29 | 0 | 0.005 |
|
| 3.29 | 0 | 0.003 |
|
| 3.29 | 1.48 | 0.004 |
|
| 3.29 | 0 | 0.004 |
|
| 2.63 | 0 | 0.006 |
|
| 2.63 | 0 | 0.012 |
|
| 2.63 | 0 | 0.003 |
|
| 1.97 | 7.41 | −0.006 |
|
| 1.97 | 8.89 | −0.040 |
|
| 1.97 | 0 | 0.000 |
|
| 1.32 | 0 | 0.000 |
|
| 1.32 | 0.74 | 0.003 |
|
| 0.66 | 0 | 0.002 |
|
| 0.66 | 0 | 0.001 |
|
| 0.66 | 0 | 0.000 |
|
| 0.66 | 0 | 0.000 |
|
| 0 | 2.96 | −0.007 |
|
| 0 | 0.74 | 0.000 |
|
| 0 | 9.63 | −0.005* |
Note: “*”: P<0.05 and “”: not significant.
Note: Change in DV for each species in each grid was calculated by the DV in the recent dataset minus that in the corresponding historic dataset.
Figure 2Comparisons between the historic and recent datasets in richness (number of species per site), dominance value, and α-diversity of overall alien weed species in summer crop fields in Anhui Province, China.
Note: “***”: P<0.001.
Figure 3Overall dominance values of alien crop weeds in different groups of summer croplands surveyed in Anhui Province, China.
Figure 4Redundancy analysis (RDA) showing the 8 significant environmental factors and the 31 geographic grids in Anhui Province, China (see Figure 1).
RDA was conducted to analyze the relationship between changes in environmental factors and changes in the dominance values of alien weed species in croplands.
Figure 5Redundancy analysis (RDA) showing the 8 significant environmental factors and alien weed species in croplands in Anhui Province, China.
Note: species with lower correlations with RDA axes are not shown.
Results of the stepwise regression models used to test the relationships between changes in alien weed species richness and dominance, and changes in environmental factors between the 2 datasets surveyed in different time periods.
| Parameter | Estimate | SE |
|
|
|
| ||||
| Net cropland chemical fertilizerapplied | 0.008 | 0.001 | 7.349 | <0.001 |
| Net cropland herbicide applied | −0.004 | 0.001 |
| <0.001 |
| Population density | 0.844 | 0.258 | 3.274 | 0.004 |
| Net cropland agricultural machinery power | 0.023 | 0.007 | 3.057 | 0.006 |
| Annual mean temperature | −0.899 | 0.347 |
| 0.017 |
| Traffic frequency | 0.950 | 0.448 | 2.119 | 0.046 |
| Mean temperature of the coldestmonth | −0.180 | 0.089 |
| 0.057 |
| Mean temperature of the hottestmonth | 0.048 | 0.030 | 1.606 | 0.123 |
| ΔAIC with null model | −60.34 | |||
|
| ||||
| Net cropland herbicide applied | 0.002 | 0.000 | 4.168 | <0.001 |
| Mean temperature of the hottestmonth | −0.137 | 0.054 |
| 0.018 |
| Traffic frequency | −0.446 | 0.188 |
| 0.026 |
| Mean temperature of the coldestmonth | 0.328 | 0.169 | 1.948 | 0.063 |
| ΔAIC with null model | −17.28 |
The changes in Akaike’s information criteria between final and null models are also shown.