Complementary allometric model of understory tree biomass in the semi-deciduous rainforest of Cameroon

Ntonmen, Amandine Flore Yonkeu; Zapfack, Louis; Chimi, Cédric Djomo; Kabelong, Louis-Paul Roger Banoho; Zekeng, Jules Christian; Nfornkah, Barnabas Neba; Tsopmejio, Ingrid Temfack; Nanfack, Arsel D’Estaing; Tchoupou, Mireil Carol Votio; Madountsap, Nadège Tagnang; Ngoukwa, Guylene; Mounmemi, Hubert Kpoumie; Tabue, Roger Bruno Mbobda

doi:10.1590/0102-33062020abb0475

Brasil

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Original Article • Acta Bot. Bras. 36 • 2022 • https://doi.org/10.1590/0102-33062020abb0475 linkcopy

Complementary allometric model of understory tree biomass in the semi-deciduous rainforest of Cameroon

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ABSTRACT

Forest understorey contains remarkable plant diversity, contributing to the heterogeneous environments for other biotic gatherings and soil supplement aggregations. Nonetheless, the biomass of the understorey vegetation is neglected because of the lack of appropriate allometric equations without which there are uncertainties in biomass estimation. This study was aimed at developing multispecies allometric equations that will be used to estimate the aboveground biomass of different compartments (trunk, crown, and leaves) of understorey trees in the semi-deciduous rainforest of Cameroon. Understorey tree diameter (1.0-10.0 cm), height, and crown diameter were measured on 1023 trees as biomass predictors. The results showed that the fit of the model improves with more predictive variables, four of which were considered in all studied compartments (trunk, crown, and leaves). Existing specific and pantropic allometries based on diameter tend to overestimate the aboveground biomass of understorey trees when compared to the allometry developed in this study. This study highlighted the importance of a specific aboveground biomass allometric equation for understorey trees. Furthermore, the multispecies allometric equation developed for understorey trees complements those recently developed for overstorey trees, thereby contributing to the total aboveground woody biomass estimation in semi-deciduous forest in the Congo Basin.

Keywords: understorey trees; multispecies allometric equations; aboveground biomass; predictive variables; semi-deciduous rainforest; Cameroon

Statistics	Diameter (cm)	Height (m)	Wood density (g.cm^-3)	Crown diameter (cm)	Leaves biomass (kg)	Branches biomass (kg)	Trunk biomass (kg)	Aboveground biomass (kg)
Mean	3.15	4.00	0.561	1.49	0.141	0.755	1.43	2.228
SD	2.19	2.50	0.100	0.92	0.193	1.586	2.625	3.981
Min	1.00	0.86	0.156	0.19	0.002	0.003	0.002	0.008
Max	9.99	15.55	0.914	7.55	1.274	16.788	20.877	35.549
Number	1023	1023	1023	1010	311	1023	1023	1023

Models	Model parameters					Performance criteria
Models	N	a	b	c	d	RRMSE	RSE	Adj.R²	AIC	CF	Average error (%)
1≤ diameter ≤5 cm (seedlings)
lnM= a + b × ln(D)	793	-2.785^***	2.416^***			0.243	0.483	0.816	1101	0.12	1.68
lnM= a + b × ln(D) + c × ln(H)	793	-3.180^***	1.599^***	0.954^***		0.219	0.432	0.853	926	0.09	1.86
lnM= a + b × ln(D) + c × ln(ρ)	793	-2.145^***	2.451^***	1.120^***		0.200	0.433	0.852	928	0.09	0.22
lnM= a + b × ln(D) + c × ln(C)	793	-2.527^***	0.593^***	1.989^***		0.308	0.447	0.844	967	0.10	-15.12
lnM= a + b × ln(D² × H) + c × ln(ρ)	793	-2.529^***	0.860^***	1.077^***		0.185	0.381	0.886	723	0.07	0.65
lnM= a + b × ln(D) + c × ln(H) + d × ln(C)	793	-2.924^***	1.400^***	0.807^***	0.452^***	0.197	0.410	0.868	835	0.08	1.44
lnM= a + b × ln(D² × H) + c × ln(ρ) + d × ln(C)	793	-2.377^***	0.767^***	0.997^***	0.365^***	0.170	0.364	0.896	648	0.07	0.61
5< diameter ≤10 cm (saplings)
lnM= a + b × ln(D)	230	-1.768^***	1.944^***			0.577	0.432	0.394	271	0.09	19.74
lnM= a + b × ln(D) + c × ln(H)	230	-2.576^***	1.371^***	0.937^***		0.434	0.382	0.527	215	0.07	14.54
lnM= a + b × ln(D) + c × ln(ρ)	230	-1.494^***	2.206^***	1.247^***		0.479	0.357	0.587	184	0.06	13.45
lnM= a + b × ln(D) + c × ln(C)	230	-1.643^***	1.602^***	0.555^***		0.496	0.389	0.485	218	0.08	16.45
lnM= a + b × ln(D² × H) + c × ln(ρ)	230	-2.230^***	0.836^***	1.151^***		0.356	0.308	0.692	116	0.05	10.23
lnM= a + b × ln(D² × H) + c × ln(C)	230	-2.464^***	0.671^***	0.509^***		0.394	0.341	0.605	159	0.06	11.73
lnM= a + b × ln(D² × H) + c × ln(ρ) + d × ln(C)	230	-2.151^***	0.738^***	1.088^***	0.473^***	0.889	0.266	0.760	49	0.04	70.06
All (1 ≤ diameter < 10 cm)
lnM= a + b × ln(D)	1023	-2.811^***	2.474^***			0.199	0.475	0.918	1384	0.11	0.11
lnM= a + b × ln(D) + c × ln(H)	1023	-3.215^***	1.665^***	0.958^***		0.192	0.423	0.935	1149	0.09	2.45
lnM= a + b × ln(D) + c × ln(ρ)	1023	-2.144^***	2.505^***	1.164^***		0.184	0.419	0.936	1126	0.09	1.16
lnM= a + b v ln(D) + c × ln(C)	1023	-2.550^***	2.041^***	0.595^***		0.187	0.437	0.930	1196	0.10	2.16
lnM= a + b × ln(D² × H) + c × ln(ρ)	1023	-2.554^***	0.880^***	1.100^***		0.158	0.367	0.951	854	0.07	1.10
lnM= a + b × ln(D² × H) + c × ln(C)	1023	-2.924^***	0.750^***	0.473^***		0.167	0.397	0.942	1005	0.08	1.99
lnM= a + b × ln(D² × H) + c × ln (ρ) + d × ln(C)	1023	-2.385^***	0.779^***	0.779^***	0.392^***	0.373	0.346	0.956	728	0.06	13.36

Models	Model parameters						Performance criteria
Models	N	a	b	c	d	e	RRMSE	RSE	Adj.R²	AIC	CF	Average error (%)
Leaves
lnM= a + b × ln(D)	311	-4.158^***	1.436^***				0.168	0.781	0.553	730	030	0.21
lnM= a + b × ln(C)	311	-3.229^***	1.679^***				0.170	0.785	0.550	729	0.31	-0.44
lnM= a + b × ln(D² × H)	311	-4.371^***	0.505^***				0.165	0.772	0.563	723	0.30	0.36
lnM= a + b × ln(D) + c × ln(ρ)	311	-3.507^***	1.474^***	1.111^***			0.166	0.743	0.593	701	0.28	0.19
lnM= a + b × ln(D) + c × ln(C)	311	-3.833^***	0.826^***	0.917^***			0.165	0.724	0.618	680	0.26	0.02
lnM= a + b × ln(D² × H)+ c × ln (ρ)	311	-3.755^***	0.515^***	1.047^***			0.164	0.739	0.600	696	0.27	0.28
lnM= a + b × ln(D² × H)+ + c × ln (C)	311	-3.700^***	0.299^***	0.878^***			0.149	0.722	0.620	679	0.26	1.65
lnM= a + b × ln(D) + c × ln(H) + d × ln(ρ) + e × ln(C)	311	-3.505^***	0.817^***	0.160^ns	0.895^***	0.779^***	0.105	0.698	0.645	659	0.24	12.99
Crown (branches+leaves)
lnM= a + b × ln(D)	1021	-3.630^***	2.239^***				0.574	0.772	0.775	2374	0.30	12.87
lnM= a + b × ln(C)	1021	-2.147^***	2.515^***				0.502	0.801	0.758	2415	0.32	13.97
lnM= a + b × ln(D² × H)	1021	-3.958^***	0.786^***				0.589	0.756	0.785	2330	0.29	13.46
lnM= a + b × ln(D) + c × ln(ρ)	1021	-2.807^***	2.278^***	1.439^***			0.552	0.721	0.804	2234	0.26	10.01
lnM= a + b × ln(D) + c × ln(C)	1021	-3.060^***	1.296^***	1.300^***			0.548	0.651	0.841	1997	0.21	8.23
lnM= a + b × ln(D) + c × ln(H) + d × ln (ρ)	1021	-3.099^***	1.745^***	0.629^***	1.392^***		0.574	0.707	0.812	2196	0.25	10.42
lnM= a + b × ln(D) + c × ln(H) + d × ln(C)	1021	-3.235^***	1.035^***	0.356^***	1.247^***		0.554	0.646	0.843	1984	0.21	8.60
lnM = a + b × ln(D) + c × ln(H) + d × ln(ρ) + e × ln(C)	1021	-2.603^***	1.162^***	0.318^***	1.145^***	1.155^***	0.507	0.606	0.861	1864	0.18	6.69
Trunk
lnM= a + b × ln(D)	1023	-3.532^***	2.633^***				1.279	0.537	0.908	1633	0.14	3.44
lnM= a + b × ln(D)+ c × ln(H)	1023	-4.014^***	1.667^***	1.143^***			1.335	0.471	0.929	1367	0.11	3.33
lnM= a + b × ln(D) + c × ln(ρ)	1023	-2.972^***	2.659^***	0.978^***			1.230	0.502	0.919	1500	0.13	2.53
lnM= a + b × ln(D) + c × ln(C)	1023	-3.454^***	2.504^***	0.175^***			1.209	0.534	0.909	1602	0.14	3.60
lnM= a + b × ln(D)+c × ln(H) + d × ln(ρ)	1023	-3.480^***	1.731^***	1.096^***	0.897^***		1.318	0.438	0.939	1220	0.10	2.44
lnM= a + b × ln(D) + c × ln(H) + d × ln (ρ)+ e ×ln(C)	1023	-3.509^***	1.766^***	1.113^***	0.912^***	-0.067^ns	1.209	0.438	0.939	1206	0.10	2.31

Models	Forest type	N	D(cm)	RMSE	RRMSE	Average error (%)	Total (kg)	Mean (kg)	Ratio (% of difference to total or mean)
Aboveground biomass
Comparison of existing and applicable models for tropical moist forest which considered trees diameter>1 cm
Our study (measured AGB; trees≥1 cm)	moist	1023	1-9.9	-	-	-	2279.415	2.228	-
Djomo et al. (2010)	moist	71	1-10	2.027	1.676	105.42	2744.763	2.683	20
Djomo et al. (2010)	Pan tropical	274	1-138	3.295	0.991	66.97	3647.510	3.566	60
Djomo et al. (2016)	Pan tropical	570	1-212	2.951	0.875	59.71	3576.602	3.496	57
Djomo and Chimi (2017)	moist	237	1-121	2.628	0.879	55.13	3317.026	3.242	46
Comparison of existing and applicable models for tropical moist forest which considered trees diameter >5 cm
Our study (measured AGB; trees>5 cm)	moist	230	5-9.9				1821.356	7.908
Chave et al. (2005)	pan tropical	2410	5-315	7.386	1.251	93.51	3137.456	13.616	72
Fayolle et al. (2013)	moist	133	5-193	7.667	1.312	100.21	3227.529	14.001	77
Chave et al. (2014)	pan tropical	4004	5-315	5.987	0.830	64.99	2809.971	12.179	54
Compartments biomass
Our study (leaves biomass measured)	moist	309	1-9.9	-	-	-	35.017	0.304	-
Djomo et al. (2010)	moist	71	1-79	0.129	1.178	30.45	31.264	0.136	-11
Henry et al. (2010)	Dry forest	109	3-180	0.140	1.190	23.27	41.562	0.181	19
Our study (trunk biomass measured)	moist	286	4-9.9	-	-	-	1068.183	4.646	-
Henry et al. (2010)	Dry forest	109	3-180	2.141	0.603	25.24	1150.987	5.010	8
Djomo and Chimi (2017)	moist	96	4-121	5.438	1.414	105.93	2182.506	9.500	104

Our study (crown biomass measured)	moist	286	4-9.9	-	-	-	569.580	2.487	-
Djomo and Chimi (2017)	moist	96	4-121	1.926	3.431	60.14	451.251	1.965	-21

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[TFN1] Note: The statistical analyses are significant at 95% confidence interval. ***p <0.001; **p <0.01; *p <0.05. P-value of all models: <0.0001; D: diameter of trees analysed (in DBH); H: height of trees; ρ: wood density; C: crown diameter; N: sample size; a, b, c and d are the model’s fitted parameters; RRMSE: Relative Root mean error; RSE: residual standard error of the estimation; AdjR2: adjusted coefficient of determination; AIC: Akaike Information Criterion and CF: correction factor.