C1 1.916944 a
B 1.447660 b
attr(,"class")
[1] "group"
> t=aov(dt~Lapdia,data=KL)
> summary(t)
Df Sum Sq Mean Sq F value Pr(>F) Lapdia 1 1.17 1.1657 5.285 0.0228 *
Residuals 164 36.18 0.2206
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
8 observations deleted due to missingness
> t1=LSD.test(t,"Lapdia")
> t1
$statistics
MSerror Df Mean CV 0.220586 164 2.078554 22.5958
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none Lapdia 2 0.05
$means
dt std r LCL UCL Min Max Q25 Q50 Q75
B 2.005213 0.5082581 94 1.909562 2.100864 0.90 3.65 1.7000 1.925 2.31
C1 2.174306 0.4137048 72 2.065014 2.283597 1.25 3.50 1.9225 2.165 2.40
$groups
dt groups C1 2.174306 a
B 2.005213 b
attr(,"class")
[1] "group"
> fix(KL)
> th=aov(Thanchinh~Lapdia,data=KL)
> summary(th)
Df Sum Sq Mean Sq F value Pr(>F) Lapdia 1 3.11 3.1125 4.157 0.0431 *
Residuals 164 122.79 0.7487
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
8 observations deleted due to missingness
> th1=LSD.test(th,"Lapdia")
> th1
$statistics
MSerror Df Mean CV 0.7487261 164 1.975904 43.7921
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none Lapdia 2 0.05
$means
Thanchinh std r LCL UCL Min Max Q25 Q50 Q75 B 2.095745 0.8559614 94 1.919522 2.271968 1 5 2 2 3
C1 1.819444 0.8773582 72 1.618091 2.020798 1 4 1 2 2
$groups
Thanchinh groups B 2.095745 a
C1 1.819444 b
attr(,"class")
[1] "group"
> fix(KL)
> c=aov(c50~Lapdia,data=KL)
> summary(c)
Df Sum Sq Mean Sq F value Pr(>F) Lapdia 1 133 133.4 4.616 0.0331 *
Residuals 164 4739 28.9
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
8 observations deleted due to missingness
> c1=LSD.test(c,"Lapdia")
> c1
$statistics
MSerror Df Mean CV 28.89721 164 13.29518 40.43279
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none Lapdia 2 0.05
$means
c50 std r LCL UCL Min Max Q25 Q50 Q75 B 12.51064 5.134209 94 11.41585 13.60542 4 27 9 12 16
C1 14.31944 5.676307 72 13.06853 15.57036 4 29 10 14 18
$groups
c50 groups C1 14.31944 a
B 12.51064 b
attr(,"class")
[1] "group"
> pt=aov(phth~Lapdia,data=KL)
> summary(pt)
Df Sum Sq Mean Sq F value Pr(>F) Lapdia 1 3.56 3.560 23.18 3.33e-06 ***
Residuals 164 25.19 0.154
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
8 observations deleted due to missingness
> pt1=LSD.test(pt,"Lapdia")
> pt1
$statistics
MSerror Df Mean CV 0.1536138 164 0.7771084 50.43518
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none Lapdia 2 0.05
$means
phth std r LCL UCL Min Max Q25 Q50 Q75 B 0.6489362 0.4798621 94 0.5691154 0.728757 0 1 0 1 1
C1 0.9444444 0.2306689 72 0.8532405 1.035648 0 1 1 1 1
$groups
phth groups
C1 0.9444444 a
B 0.6489362 b
attr(,"class")
[1] "group"
> s=aov(sc~Lapdia,data=KL)
> summary(s)
Df Sum Sq Mean Sq F value Pr(>F) Lapdia 1 0.005 0.00471 0.106 0.745
Residuals 172 7.627 0.04435
> s1=LSD.test(s,"Lapdia")
> s1
$statistics
MSerror Df Mean CV 0.04434578 172 0.954023 22.0733
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none Lapdia 2 0.05
$means
sc std r LCL UCL Min Max Q25 Q50 Q75 B 0.9494949 0.2200991 99 0.9077193 0.9912706 0 1 1 1 1
C1 0.9600000 0.1972788 75 0.9120034 1.0079966 0 1 1 1 1
$groups
sc groups C1 0.9600000 a
B 0.9494949 a
attr(,"class")
[1] "group"
2.4. KEO LÁ LIỀM LẬP ĐỊA C3 TẠI LỆ THỦY
> d=aov(stump_diameter~CTTN,data=LT13)
> summary(d)
Df Sum Sq Mean Sq F value Pr(>F)
CTTN 3 0.45 0.1484 0.339 0.797
Residuals 223 97.76 0.4384
16 observations deleted due to missingness
> library(agricolae)
> d1=LSD.test(d,"CTTN")
> d1
$statistics
MSerror Df Mean CV 0.4383911 223 2.642863 25.05279
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
stump_diameter | std | r LCL UCL | Min | Max Q25 | Q50 Q75 | |
CT 1 | 2.660294 | 0.6693347 | 34 2.436524 2.884065 | 1.72 | 4.81 2.2300 | 2.48 2.9675 |
CT 2 | 2.703971 | 0.5833105 | 68 2.545741 2.862200 | 1.59 | 4.30 2.2525 | 2.58 3.1425 |
CT 3 | 2.606264 | 0.6681844 | 91 2.469484 2.743043 | 1.37 | 5.43 2.1000 | 2.51 2.9300 |
DC | 2.601176 | 0.7784552 | 34 2.377406 2.824947 | 1.46 | 4.62 1.9950 | 2.53 2.9125 |
$groups | ||||||
CT 2 | stump_diameter 2.703971 | groups a | ||||
CT 1 | 2.660294 | a | ||||
CT 3 | 2.606264 | a | ||||
DC | 2.601176 | a | ||||
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Nghiên cứu bổ sung cơ sở khoa học về kỹ thuật trồng rừng phòng hộ trên các dạng lập địa chính vùng cát ven biển các tỉnh Hà Tĩnh, Quảng Bình và Quảng Trị - 21 -
Phân Bố Diện Tích Các Loại Đất Cát Theo Độ Cao Và Theo Đơn Vị Hành Chính Huyện, Thành Phố Khu Vực Nghiên Cứu -
Kết Quả Phi Lao Trên Dạng Lập Địa B -
Nghiên cứu bổ sung cơ sở khoa học về kỹ thuật trồng rừng phòng hộ trên các dạng lập địa chính vùng cát ven biển các tỉnh Hà Tĩnh, Quảng Bình và Quảng Trị - 25
Xem toàn bộ 207 trang tài liệu này.
attr(,"class")
[1] "group"
> h=aov(tree_height~CTTN,data=LT13)
> summary(h)
Df Sum Sq Mean Sq F value Pr(>F)
CTTN 3 0.15 0.05006 0.965 0.41
Residuals 223 11.56 0.05186
16 observations deleted due to missingness
> h1=LSD.test(h,"CTTN")
> h1
$statistics
MSerror Df Mean CV 0.0518596 223 0.9486344 24.00577
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
$means
std r | LCL UCL | Min | Max | Q25 | Q50 | Q75 | |
CT 1 0.9008824 | 0.2211042 34 | 0.8239185 0.9778462 | 0.60 | 1.55 | 0.725 | 0.875 | 1.0375 |
CT 2 0.9652941 | 0.2092023 68 | 0.9108725 1.0197158 | 0.53 | 1.33 | 0.800 | 0.940 | 1.1400 |
CT 3 0.9401099 | 0.2336783 91 | 0.8930658 0.9871540 | 0.43 | 1.92 | 0.795 | 0.940 | 1.1000 |
DC 0.9858824 | 0.2525400 34 | 0.9089185 1.0628462 | 0.60 | 1.47 | 0.805 | 0.940 | 1.2300 |
$groups
tree_height groups DC 0.9858824 a
CT 2 0.9652941 a
CT 3 0.9401099 a
CT 1 0.9008824 a
attr(,"class")
[1] "group"
> dt=aov(canopy_diameter~CTTN,data=LT13)
> summary(dt)
Df Sum Sq Mean Sq F value Pr(>F)
CTTN 3 0.351 0.11708 1.73 0.162
Residuals 223 15.095 0.06769
16 observations deleted due to missingness
> dt1=LSD.test(dt,"CTTN")
> dt1
$statistics
MSerror Df Mean CV 0.067692 223 1.100441 23.64297
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
$means
canopy_diameter | std r | LCL | UCL Min Max Q25 Q50 Q7 | |
CT 1 | 1.071471 | 0.2543814 34 | 0.9835399 | 1.159401 0.67 1.68 0.915 1.035 1.300 |
CT 2 | 1.158676 | 0.2402045 68 | 1.0965001 | 1.220853 0.75 1.83 0.950 1.145 1.300 |
CT 3 | 1.084615 | 0.2810666 91 | 1.0308677 | 1.138363 0.48 2.03 0.845 1.090 1.305 |
DC | 1.055294 | 0.2452115 34 | 0.9673634 | 1.143225 0.45 1.65 0.935 1.050 1.187 |
$groups
canopy_diameter | groups | |
CT 2 | 1.158676 | a |
CT 3 | 1.084615 | a |
CT 1 | 1.071471 | a |
DC | 1.055294 | a |
attr(,"class")
[1] "group"
> th=aov(main_trunk~CTTN,data=LT13)
> summary(th)
Df Sum Sq Mean Sq F value Pr(>F)
CTTN 3 1.34 0.4463 0.403 0.751
> th1=LSD.test(th,"CTTN")
> th1
$statistics
MSerror Df Mean CV 1.106854 223 2.550661 41.247
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
$means
std r LCL UCL | Min | Max | Q25 | Q50 | Q75 | |
CT 1 2.411765 | 1.0478737 34 2.056201 2.767328 | 1 | 5 | 2 | 2.0 | 3 |
CT 2 2.588235 | 1.0683408 68 2.336814 2.839657 | 1 | 6 | 2 | 3.0 | 3 |
CT 3 2.527473 | 0.9468152 91 2.310134 2.744811 | 1 | 5 | 2 | 3.0 | 3 |
DC 2.676471 | 1.2725681 34 2.320907 3.032034 | 1 | 6 | 2 | 2.5 | 3 |
$groups
main_trunk groups DC 2.676471 a
CT 2 2.588235 a
CT 3 2.527473 a
CT 1 2.411765 a
attr(,"class")
[1] "group"
> c=aov(bough_50_cm~CTTN,data=LT13)
> summary(c)
Df Sum Sq Mean Sq F value Pr(>F)
CTTN 3 2.78 0.9261 1.251 0.292
Residuals 223 165.09 0.7403
16 observations deleted due to missingness
> c1=LSD.test(c,"CTTN")
> c1
$statistics
MSerror Df Mean CV 0.7403125 223 1.903084 45.21158
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
$means
std r | LCL | UCL | Min | Max | Q25 Q50 | Q75 | |
CT 1 1.647059 | 0.7739060 34 | 1.356269 | 1.937849 | 0 | 4 | 1 2 | 2 |
CT 2 1.985294 | 0.9540588 68 | 1.779674 | 2.190914 | 1 | 6 | 1 2 | 2 |
CT 3 1.934066 | 0.8406637 91 | 1.756321 | 2.111811 | 0 | 4 | 1 2 | 3 |
DC 1.911765 | 0.7926804 34 | 1.620975 | 2.202555 | 1 | 4 | 1 2 | 2 |
$groups
bough_50_cm groups CT 2 1.985294 a
CT 3 1.934066 a
DC 1.911765 a
CT 1 1.647059 a
attr(,"class")
[1] "group"
> pt=aov(phan_than~CTTN,data=LT13)
> summary(pt)
Df Sum Sq Mean Sq F value Pr(>F)
CTTN 3 0.47 0.1560 0.814 0.487
Residuals 223 42.71 0.1915
16 observations deleted due to missingness
> pt1=LSD.test(pt,"CTTN")
> pt1
$statistics
MSerror Df Mean CV 0.1915366 223 0.2555066 171.2868
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
$means
std r LCL | UCL | Min | Max | Q25 | Q50 | Q75 | |
CT 1 0.2058824 | 0.4104256 34 0.05797222 | 0.3537925 | 0 | 1 | 0 | 0 | 0 |
CT 2 0.2647059 | 0.4444566 68 0.16011762 | 0.3692941 | 0 | 1 | 0 | 0 | 1 |
CT 3 0.2307692 | 0.4236593 91 0.14035918 | 0.3211793 | 0 | 1 | 0 | 0 | 0 |
DC 0.3529412 | 0.4850713 34 0.20503104 | 0.5008513 | 0 | 1 | 0 | 0 | 1 |
$groups phan_than | groups | ||||||
DC 0.3529412 CT 2 0.2647059 CT 3 0.2307692 CT 1 0.2058824 | a a a a |
attr(,"class")
[1] "group"
> s=aov(song_chet~CTTN,data=LT13)
> summary(s)
Df Sum Sq Mean Sq F value Pr(>F)
CTTN 3 0.423 0.14103 2.321 0.0759 .
Residuals 239 14.523 0.06077
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> s1=LSD.test(s,"CTTN")
> s1
$statistics
MSerror Df Mean CV 0.06076742 239 0.9341564 26.38857
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
$means
std | r LCL | UCL | Min | Max | Q25 | Q50 | Q75 | |
CT 1 1.0000000 | 0.0000000 | 34 0.9167184 | 1.0832816 | 1 | 1 | 1 | 1 | 1 |
CT 2 0.9189189 | 0.2748228 | 74 0.8624678 | 0.9753700 | 0 | 1 | 1 | 1 | 1 |
CT 3 0.9009901 | 0.3001650 | 101 0.8526700 | 0.9493102 | 0 | 1 | 1 | 1 | 1 |
DC 1.0000000 | 0.0000000 | 34 0.9167184 | 1.0832816 | 1 | 1 | 1 | 1 | 1 |
$groups song_chet | groups | |||||||
CT 1 1.0000000 DC 1.0000000 CT 2 0.9189189 CT 3 0.9009901 | a a ab b |
attr(,"class")
[1] "group"
> sk=aov(sk_tong~CTTN,data=LT13)
> summary(sk)
Df Sum Sq Mean Sq F value Pr(>F)
CTTN 3 5.3 1.778 0.339 0.797
Residuals 223 1169.7 5.245
16 observations deleted due to missingness
> sk1=LSD.test(sk,"CTTN")
> sk1
$statistics
MSerror Df Mean CV 5.245419 223 5.482555 41.7741
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
$means
std | r LCL UCL Min | Max | Q25 | Q50 | Q75 | |
CT 1 5.545000 | 2.316262 | 34 4.770962 6.319038 2.28 | 12.97 | 4.0500 | 4.930 | 6.6075 |
CT 2 5.693529 | 2.016537 | 68 5.146202 6.240857 1.84 | 11.21 | 4.1325 | 5.260 | 7.2125 |
CT 3 5.354835 | 2.311448 | 91 4.881705 5.827966 1.07 | 15.12 | 3.6100 | 5.040 | 6.4700 |
DC 5.340000 | 2.693313 | 34 4.565962 6.114038 1.40 | 12.31 | 3.2525 | 5.095 | 6.4150 |
$groups sk_tong | groups | |||||
CT 2 5.693529 CT 1 5.545000 CT 3 5.354835 DC 5.340000 | a a a a | |||||
attr(,"class") [1] "group" |
> fix(LT13)
> v=aov(litter_fall~CTTN,data=LT13)
> summary(v)
Df Sum Sq Mean Sq F value Pr(>F)
CTTN 3 0.00134 0.0004463 0.363 0.78
Residuals 223 0.27390 0.0012282
16 observations deleted due to missingness
> v1=LSD.test(v,"CTTN")
> v1
$statistics
MSerror Df Mean CV 0.001228234 223 0.1254185 27.94339
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
$means
std r LCL | UCL | Min Max Q25 | Q50 Q75 | |
CT 1 0.1261765 | 0.03481681 34 0.1143321 | 0.1380209 | 0.08 0.24 0.1000 | 0.12 0.1400 |
CT 2 0.1288235 | 0.03098047 68 0.1204483 | 0.1371988 | 0.07 0.21 0.1075 | 0.12 0.1525 |
CT 3 0.1232967 | 0.03537278 91 0.1160568 | 0.1305366 | 0.06 0.27 0.1000 | 0.12 0.1400 |
DC 0.1235294 | 0.04155189 34 0.1116850 | 0.1353738 | 0.06 0.23 0.0900 | 0.12 0.1400 |
$groups
litter_fall groups CT 2 0.1288235 a
CT 1 0.1261765 a
DC 0.1235294 a
CT 3 0.1232967 a
attr(,"class")
[1] "group"
> v=aov(litter_fall~CTTN,data=LT23)
> summary(v)
Df Sum Sq Mean Sq F value Pr(>F) CTTN 3 0.0865 0.02884 9.273 7.43e-06 ***
Residuals 268 0.8335 0.00311
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
27 observations deleted due to missingness
> v1=LSD.test(v,"CTTN")
> v1
$statistics
MSerror Df Mean CV 0.00310996 268 0.2072794 26.90427
$parameters
test p.ajusted name.t ntr alpha Fisher-LSD none CTTN 4 0.05
$means
std r LCL UCL Min Max | Q25 | Q50 Q75 | |
CT 1 0.1867164 | 0.05214746 67 0.1733026 0.2001303 0.07 0.33 | 0.15 | 0.18 0.21 |
CT 2 0.1992500 | 0.05566116 80 0.1869743 0.2115257 0.11 0.34 | 0.16 | 0.19 0.24 |
CT 3 0.2338667 | 0.06573685 75 0.2211884 0.2465450 0.10 0.40 | 0.19 | 0.23 0.27 |
DC 0.2078000 | 0.04272790 50 0.1922723 0.2233277 0.12 0.31 | 0.18 | 0.20 0.23 |
$groups
litter_fall groups CT 3 0.2338667 a
DC 0.2078000 b
CT 2 0.1992500 bc
CT 1 0.1867164 c
attr(,"class")
[1] "group"
III. PHÂN TÍCH KHẢ NĂNG CHẮN GIÓ CỦA CÁC ĐAI RỪNG
> md=escalc(n1i = N,n2i = N,m1i=Vt,m2i = Vs,sd1i=st,sd2i=ss,data=CG,measure = " SMD",append=TRUE)
> summary(md)
Models | Year | Dairung | N | Vt | st | Vs | ss | E | se | K | sk | |
1 | Que | 2008 | Bach dan | 1 | 3.10 | 0.00 | 2.70 | 0.00 | 0.13 | 0.00 | 1.10 | 0.00 |
2 | Que | 2008 | Keo chiu han | 2 | 3.35 | 0.21 | 2.90 | 0.14 | 0.14 | 0.01 | 1.15 | 0.07 |
3 | Thuyet & Hung | 2005 | Keo chiu han | 3 | 5.50 | 0.00 | 1.27 | 0.21 | 0.77 | 0.04 | 4.43 | 0.67 |
4 | LA | 2018 | Keo la liem | 116 | 2.62 | 0.53 | 1.24 | 0.77 | 0.53 | 0.27 | 4.00 | 4.96 |
5 | Lieu | 2017 | Keo la liem | 9 | 7.16 | 0.11 | 5.53 | 0.81 | 0.23 | 0.11 | 1.31 | 0.19 |
6 | Que | 2008 | Keo la tram | 6 | 3.40 | 0.17 | 2.65 | 0.20 | 0.22 | 0.04 | 1.28 | 0.04 |
7 | Thuyet | 2004 | Keo la tram | 14 | 2.19 | 1.53 | 0.78 | 0.22 | 0.49 | 0.28 | 3.02 | 2.55 |
8 | Que | 2008 | Klt + Kll | 1 | 3.70 | 0.00 | 2.50 | 0.00 | 0.32 | 0.00 | 1.50 | 0.00 |
9 | Que | 2008 | Keo tai tuong | 1 | 3.00 | 0.00 | 2.20 | 0.00 | 0.27 | 0.00 | 1.40 | 0.00 |
10 | Que | 2008 | Phi lao | 4 | 3.40 | 0.29 | 2.35 | 0.29 | 0.31 | 0.03 | 1.48 | 0.05 |
11 | Thuyet | 2004 | Phi lao | 41 | 4.84 | 1.28 | 2.18 | 0.91 | 0.54 | 0.17 | 2.51 | 1.03 |
12 | Thuyet & Hung | 2005 | Phi lao | 1 | 5.50 | 0.00 | 1.60 | 0.00 | 0.71 | 0.00 | 3.40 | 0.00 |
13 | Que | 2008 | Xoan AD | 2 | 3.40 | 0.14 | 2.75 | 0.07 | 0.19 | 0.01 | 1.25 | 0.07 |
yi vi sei zi pval ci.lb ci.ub
1 NA NA NA NA NA NA NA 2 1.4226 1.2530 1.1194 1.2709 0.2038 -0.7713 3.6165 3 22.7288 43.7165 6.6118 3.4376 0.0006 9.7698 35.6878 4 2.0810 0.0266 0.1630 12.7655 <.0001 1.7615 2.4005 5 2.6854 0.4225 0.6500 4.1312 <.0001 1.4113 3.9594 6 3.7286 0.9126 0.9553 3.9031 <.0001 1.8563 5.6010 7 1.2524 0.1709 0.4134 3.0298 0.0024 0.4422 2.0626
8 NA NA NA NA NA NA NA
9 NA NA NA NA NA NA NA 10 3.1450 1.1182 1.0574 2.9742 0.0029 1.0725 5.2176 11 2.3727 0.0831 0.2883 8.2305 <.0001 1.8077 2.9378
12 NA NA NA NA NA NA NA 13 3.3134 2.3723 1.5402 2.1512 0.0315 0.2946 6.3322