ARTICLES RIA / Vol. 44 / N.º 2

Production and growth of alba Griseb. plantations in the province of Chaco

KEES, S.M.1; FERRERE, P.2; LUPI, A.M.3; MICHELA, J.F.4; SKOKO, J.J.5

ABSTRACT At present, in Chaco province, there are about 6,000 ha plantations of Prosopis alba Griseb, “Algarrobo Blanco”, not exceeding 30 years of age, located in different site qualities. The purposes of this work were to typify the growth in this species plantations at different ages and site qualities and to adjust non-linear models for age-based diameter projection. A total of 40 plantations were surveyed, with ages ranging between 4 and 23 years, located in 32 settings and different site qualities, where 126 rectangular sampling plots of 1000 m2 were installed. For each plot, the estimations were as follows: basal area (m2.ha-1), density (pl.ha-1), total volume (m3. ha-1), mean normal diameter (cm), mean diameter of dominant trees (cm), mean annual increase in mean normal diameter (cm.year-1), mean annual increase in dominant mean diameter (cm.year-1) and site quality. In general terms, all ages present high density, particularly in the highest quality sites. The increases in mean normal diameter and mean diameter of dominant trees in the highest quality sites are greater than the general average for the sample and generally greater than 1 in cm.year-1. The measured variables are indicative of the productive capacity of the species in the study area. It is highly recommended to correctly select the planting sites to achieve positive results in terms of timber production. The Logistic and Gompertz models allow us to estimate a technological shift, with diameters greater than 30 cm at 25 years of age for the best quality sites.

Keywords: site quality; Models; dasometric parameters.

1Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Agropecuaria (EEA) Sáenz Peña, Campo Anexo Estación Forestal Plaza, Lote IV, Colonia Santa Elena, (3536), Presidencia de la Plaza, Chaco. Correo electrónico: [email protected] 2Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Agropecuaria (EEA) Pergamino, Agencia Extensión Rural. (AER) 9 de Julio, Mitre 857, (6500), 9 de Julio, Buenos Aires. Correo electrónico: [email protected] 3Instituto Nacional de Tecnología Agropecuaria (INTA), Centro de Investigación de Recursos Naturales (CIRN), Instituto de Suelos, Castelar, Nicolás Repetto y de los Reseros s/n. (1686), Hurlingham, Buenos Aires. Correo electrónico: [email protected] 4Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Agropecuaria (EEA) Santiago del Estero, Programa Cambio Rural II, Jujuy N° 850, (4200), Santiago del Estero. Santiago del Estero. Correo electrónico: [email protected] 5Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Agropecuaria (EEA) Sáenz Peña, Programa cambio Rural II, Ruta 95 km 1108, (3700), Presidencia Roque Sáenz Peña, Chaco. Correo electrónico: [email protected]

Received November 6, 2017 // Accepted March 27, 2018 // Published online August 22, 2018

Production and growth of Prosopis alba Griseb. plantations in the province of Chaco August 2018,

INTRODUCTION MATERIALS AND METHODS “Algarrobo Blanco” (Prosopis alba Griseb.) grows na- Characterization of the study area: turally in the eastern Chaco and other subtropical plains The study area covers 15 districts of the province of Cha- of Argentina, Uruguay, , and southern , co (figure 1). up to (Burkart, 1976). It has a very wide geographi- cal distribution area in the central region of the country The Chaco area is a vast sedimentary basin, with an and is part of the hardwood group of the Chaco forest apparent topographic uniformity. It has a general west-to- (Burkart, 1952). east slope that directs water flow from watercourses or floods - caused by excess rainfall - to the Paraguay or Pa- This species is an important forest resource that can be raná rivers, or towards the Salado basin. used in sustainable systems to improve socioeconomic conditions in arid and semi-arid areas where desertification Precipitation and rainfall regimens are the most pronoun- not only leads to productive decline, but also, directly, to the ced differential element between eastern and western Cha- disappearance of resources (Verga, 2000) co. There is greater humidity in Eastern Chaco, as rainfall ranges from 1200 mm in the East, and transitions to 800 In recent years it has also been used in the recovery of towards the West. In turn, Western Chaco is drier and rain- soils degraded by salinization (Ramirez y Torres, 1985; Val- falls decrease from 800 mm to 500 mm, in the same direc- dora and Jaimez, 2000; Taleisnik and Lauenstein, 2011), tion (that is, to the West). either by setting pure plantations, or via its use in like silvo- pastoral systems. All this affects the availability of water that feeds the wa- ter network, the diversification of soils and their vegetation, According to Perez et al. (2016), most of the P. alba affo- a closed forest, an open landscape of parks and savannas, restations in the Parque Chaqueño of Argentina are less and a horizon of estuaries and baths framed by gallery fo- than two decades old. In the province of Chaco there are rests (Bonfanti et al., 2006). 6,000 ha planted with this species (Delvalle, 2006). Accor- ding to data from the Institute of Forestry and Agricultural Research (2013), nearly 3,382 hectares of these 6,000 Forest survey were planted under Law 25.080 for the promotion of culti- We studied 40 plantations, aged between 4 and 23 years, vated forests. most of them pruned, with different initial densities (1111 The field of driven silviculture produces the greatest ad- pl.ha-1 to 400 pl.ha-1), in 32 locations and with site quali- 2 vances in the development of knowledge and management ties. We installed 126 rectangular sampling plots (1000 m ) tools. Delvalle (2006) tested the intensity of thinning in Cha- between 2009 and 2017. co. Pérez (2012) described the use of thinning methods in In each plot, we assessed the following: for all the trees, Formosa. Ewens and Navall (2006) studied planting densi- total height in meters using a Suunto clinometer, and nor- ty and pruning treatment in Santiago del Estero. mal diameter in cm using a dendrometric tape. With these data, we calculated for each plot: basal area (G m2.ha-1), Colonel de Renolfi et al. (2014) tested thinning intensities density (N pl.ha-1), total volume (V m3.ha-1) using a loca- in Santiago del Estero. In Chaco, Atanasio (2014) analyzed lly adjusted shape coefficient of 0.8 on field measurements the influence of pruning on the growth of the plantations, in the surveyed plots, average normal diameter (DN, cm), and Kees and Michela (2016) recommend concentrating average diameter of dominant trees: (DDOM, cm), average the growth of dominant trees. annual increase of the average normal diameter (AAIND, This is because having large individuals is essential for cm.year-1), average annual increase of the average domi- the sawing and furniture industry, that has been long-sett- nant diameter (AAIDDOM, cm.year-1). led in the Chaco. According to Cuadra (2012), since the We used the criteria proposed by Assmann (1970) to se- ‘80s there are sawmills and carpentry mainly focused on lect the dominant trees of each plot. The site quality of each the production of “Algarrobo” furniture and crafts in Macha- plot was estimated from the site index curves estimated by gai, fabrication of doors and windows in Quitilipi, and of di- Kees et al. (2016). fferent products in Presidencia de la Plaza, which supply the regional and national demand. Fitting of the models The cultivation of algarrobo is important for the province’s industry, generates revenues for the province and the re- For the fit,we grouped plots based on site quality. Four gion, and has a significant economic and social importance. dominant average diameter prediction models were adjus- Therefore, it is important to know the productive potential of ted by non-linear regression using the software InfoStat (Di the different sites where this species is planted. Rienzo et al., 2017). DDOM was considered as dependent variable, and age (E) as independent variable for each site The objectives of this study are: 1) to characterize the quality. The adjusted models were: behavior of Prosopis alba plantations, at different ages and in sites with different qualities, and 2) to adjust non-linear = - (1+ 2 )) models for the prediction of diameter based on age. 𝐵𝐵퐵 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝐵𝐵퐵 ∗ 𝑒𝑒𝑒𝑒𝑒𝑒 (−𝐵𝐵 ∗𝐸𝐸 KEES, S.M.; FERRERE, P.; LUPI, A.M.; MICHELA, J.F.; SKOKO, J.J. ARTICLES RIA / Vol. 44 / N.º 2

Figure 1. Location of the plots in the province of Chaco.

could be explained by the lower density observed in those - = 2 specific cases. - = (1 + 1 )^ 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝐵𝐵퐵 ∗ 𝑒𝑒𝑒𝑒𝑒𝑒(−𝐵𝐵퐵 ∗ 𝑒𝑒𝑒𝑒𝑒𝑒−𝐵𝐵 ∗ 𝐸𝐸퐸) Also, values are usually greater than 1 cm.year-1 which - = ) shows the good performance of the species against site 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝐵𝐵퐵 ∗ 𝐵𝐵 ∗ 𝑒𝑒𝑒𝑒𝑒𝑒 (−𝐵𝐵퐵 𝐸𝐸 𝐵𝐵퐵 variations. These are promising results and coincide with 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝐵𝐵퐵 ∗ 𝑒𝑒𝑒𝑒𝑒𝑒 (𝐵𝐵퐵∗ 𝐸𝐸 To select the model with the best performance we used those cited by Senilliani and Navall (2006) and Michela et the following criteria: 1) lower value of Akaike Information al. (2015) for young stages of plantations with this species. Criterion (AIC), 2) lower value of Bayesian Information Cri- When analyzing the growth of this species in the native terion of Schwarz (BIC), 3) lower mean squared prediction forest of the arid Chaco, Juárez de Galindez et al., (2005) error (MSPE) and 4) simplicity of calculation. report lower values than those of our study for the initial pe- riod. However, given the high density of the plantations, the growth in diameter of the dominant trees would reflect with RESULTS AND DISCUSSION greater approximation the potential of each site and age, The observed densities were high for all ages when com- as to estimate timber production for the furniture industry. pared to the observations of Delvalle (2006) in 10 years old plantations, or older. This is important if we take into accou- We observed a noticeable difference in basal area and nt that the goal of plantations is to produce sawtimber. The- total volume (Table 3). The best sites practically doubled refore, growth is likely to be greater if the plantations were the values of the other qualities, and in some cases even subject to management regimes according to site quality exceeded sites with very good quality that were highlighted and production goals. by Senilliani and Navall (2006) as a density limit for the irri- gation area of Santiago del Estero. Although the average annual increase in both ND and DDOM in the best quality sites is equal to or greater than In the 17-year-old plots - that represent all the classes - the general average for the sample (ND: 1.3; DDOM: 1.7), the volume in the very good sites was twice that those of there are values that are smaller such as those that appear the good sites, and 4 times greater than those of the regular at 15 and 17 years in very good quality sites (Table 2). This sites. At 23 years the good site presented twice the volume

Production and growth of Prosopis alba Griseb. plantations in the province of Chaco August 2018, Argentina

Density (pl.ha-1= / site quality Age Average Number of plots Very good Good Regular Bad 4 323 330 326 5 5 533 379 277 351 9 6 480 280 380 2 7 393 450 421 2 8 368 397 372 8 9 320 320 1 10 478 1079 678 3 11 390 390 1 12 334 320 330 10 13 333 320 167 317 14 14 136 279 178 260 222 19 15 410 274 314 300 307 11 16 183 235 240 305 241 11 17 490 270 390 230 313 7 19 190 190 12 23 120 196 161 11 Average site 345 287 285 264 288

Table 1. Mean values of density according to the quality of the site and age.

Mean annual increase (cm) / quality of the site Age Very good Good Regular Bad DN DDOM ND DDOM DN DDOM DN DDOM DN DDOM 4 1,8 2,4 1,7 2,3 1,8 + 0,1 2,4 + 0,1 5 2,2 2,9 1,9 2,3 1,6 2,0 1,8 + 0,3 2,2 + 0,3 6 2,2 2,9 1,1 1,4 1,7 + 0,8 2,1 + 1,1 7 1,5 2,3 1,1 1,8 1,3 + 0,3 2,0 + 0,3 8 1,4 1,8 1,3 1,8 1,4 + 0,1 1,8 + 0.1 9 1,7 2,2 1,7 2,2 10 1,2 1,6 1,3 1,7 1,2 + 0,1 1,6 + 0,1 11 1,3 1,7 1,3 1,7 12 1,5 1,9 1,3 1,6 1,4 + 0,2 1,8 + 0,3 13 1,4 1,7 1,3 1,4 1,2 1,3 1,3 + 0,2 1,6 + 0,2 14 1,7 1,9 1,3 1,7 1,4 1,6 1,1 1,3 1,4 + 0,2 1,6 + 0,2 15 1,3 1,8 1,4 1,7 1,1 1,4 0,8 1,1 1,2 + 0,2 1,5 + 0,3 16 1,6 1,8 1,4 1,6 1,2 1,5 1,1 1,5 1,3 + 0,2 1,6 + 0,2 17 1,0 1,6 1,3 1,6 0,9 1,2 0,9 1,1 1,1 + 0,2 1,5 + 0,2 19 1,2 1,3 1,2 + 0,1 1,3 + 0,1 23 1,2 1,4 1,0 1,1 1,1 + 0,1 1,2 + 0,2 Average site 1,7 2,1 1,4 1,7 1,3 1,6 1,0 1,3 1,3 + 0,3 1,7 + 0,4

Table 2. Mean annual increase in diameter according to age and quality of the site.

KEES, S.M.; FERRERE, P.; LUPI, A.M.; MICHELA, J.F.; SKOKO, J.J. ARTICLES RIA / Vol. 44 / N.º 2

Quality of the site ᵡ±ѕ Very good Good Regular Bad Age Basal Basal Basal Basal Basal Total vol. Total vol. Total vol. Total vol. Total vol. area area area area area (m3*ha-1) (m3*ha-1) (m3*ha-1) (m3*ha-1) (m3*ha-1) (m2*ha-1) (m2*ha-1) (m2*ha-1) (m2*ha-1) (m2*ha-1) 4 1,46 3,6 1,33 3,2 1,41± 0,14 3,4± 0,4 5 8.25 28,8 3,53 10,1 1,38 3,4 3,10± 2,59 9,2± 9,1 6 6,97 27,6 1,02 2,2 4,00± 4,21 14,9± 17,9 7 5,10 17,6 4,10 4,60± 0,71 17,6± 3,4 8 4,07 14,4 4,00 13,3 4,06± 0,89 14,3± 3,3 9 8,03 32,0 8.03 32 10 9,10 41,4 5,62 21,5 7,94± 2,50 34,8± 13,5 11 7,73 28,0 7.73 28 12 8,89 41,8 9,84 37,2 9,17± 3,87 40,4± 18,7 13 8,14 39,3 7,48 32,1 2,73 8,5 7,57± 2,43 35,1± 14,1 14 8,69 52,0 8,02 39,8 5,62 24,3 6,38 21,7 6,83± 1,83 32,2± 11,3 15 32,50 199,7 13,37 64,7 8,11 32,7 7,13 26,2 12,15± 8,59 59,0± 53,2 16 11,58 63,0 13,34 66.9 8,29 37,1 9,28 34,5 9,99± 3,26 40,8± 21,7 17 19,76 124,1 11,00 55,3 7,86 28,8 6,31 20,2 11,13± 4,59 56,3± 34,6 19 6,47 34,6 6,47± 1,79 34,6± 10,6 23 11,15 63,2 5,15 26,7 7,88± 3,99 43,3± 24,9 x + s 14,19±9,15 82,5±61,5 7,76±3,85 37,6±21,4 6,06±3,35 25,4±14,5 6,02±3,47 21,1±13,7 7,44± 4,45 34,4± 26,1

References: χ: mean by age; ѕ: standard deviation for each age. Table 3. Values of basal area and total volume according to the quality of the site and age.

Quality Coefficients Model AIC BIC MSPE of the site B0 B1 B2 B3 Logístico 32,81 4,14 0,17 - 373,58 382,90 7,48 Gompertz 35,67 1,93 0,11 - 372,68 382,00 7,39

Good Richards 39,64 -0,13 0,09 13,54 375,37 387,02 7,57 Exponencial 11,57 0,05 - - 392,32 399,31 9,70 Logístico 25,70 4,65 0,21 - 241,42 249,07 6,64 Gompertz 26,54 2,15 0,16 - 241,52 249,17 7,15 Richards 26,62 -0,13 0,15 15,24 243,54 253,10 6,80 Regular Exponencial 11,17 0,04 - - 265,30 271,04 10,9

Table 4. Statistics and adjusting coefficient of the models.

than the regular one. These results reinforce the idea that it and the classes “good” and “very good” under “good”. The Lo- is highly recommended that in addition to locating the plan- gistics and Gompertz models for both site qualities showed tations in the best stations or sites, density should also be the best fits, considering the lower values of MSPE, AIC, BIC, managed to achieve good results. and the lower quantity of variables (Table 4). In this way, both can be used in the study area to estimate the diameter of the Nonlinear models of diameter - age dominant trees based on plantation age and site quality. Since there are no data on all site qualities and ages, we de- Figure 2 shows the curves of the fitted models for cided to group the classes “regular” and “bad” under the first, each site quality group. On average, the growth gap of

Production and growth of Prosopis alba Griseb. plantations in the province of Chaco August 2018, Argentina

35,0

30,0

25,0

20,0 ( c m )

O M 15,0 D D

10,0

5,0

0,0 0 5 10 15 20 25 30 Age (years)

gompertz_Good logistic_Good gompertz_Regular logistic_Regular

Figure 2. Graph of the selected models for each site quality group.

DDOM at 5 years is 2 cm, while at 23 years it is appro- The Logistics and Gompertz models allowed estimating a ximately 6 cm. technological shift, with diameters above 30 cm at 25 years of age for the best quality sites. Figure 3 shows that the fit was greater in the good quality site for both selected models when compared to the regular quality site. Even though in overall terms lower MSPE va- REFERENCES lues were obtained in the regular quality sites, we observed an overestimation of DDOM at advanced ages. ASSMANN, E. 1970. The Principles of Forest Yield Study. Oxford, UK, Pergamon Press. 506, pp. 24-26. The estimates for good site qualities forecast diameters ATANASIO, M.A. 2014. Influencia de la poda en el crecimien- above 30 cm at ages near 25 years, similar to the estima- to de Prosopis alba Griseb. Quebracho (Santiago del Estero), tes of Senilliani and Navall (2006) for the irrigation area 22(2), 66-78. of Santiago del Estero, and of Kees et al. (2014) for the BONFANTI, F.; MERETZ, L.; MANOILOFF, R.; REY, W. 2006. central west region of the province of Chaco. These values El medio natural de la provincia del Chaco. Comunicaciones could be higher if, in addition to the proper selection of the Científicas y Tecnológicas 2006 Resumen: S-019, Universidad Na- plantation site and silvicultural management, improved ge- cional del Nordeste, Corrientes. netic material is incorporated, as expressed by Felker et al. BURKART, A. 1952. Las Leguminosas Silvestres y (2001), Lopez et al., (2001), Salto (2011) and Verga (2017). Cultivadas. 2.a ed. Acme, Buenos Aires. There is a great potential for improvement using genetic ma- BURKART, A. 1976. A monograph of the genus Prosopis (Legu- minosae, subfam. Mimosoideae). Journal of the Arnold Arboretum nagement, and management practices oriented towards the pro- 57:217-525 duction of quality wood that should be analyzed in future studies. CORONEL DE RENOLFI, M.; CARDONA, G.; MOGLIA, J.; GÓMEZ, A. 2014. Productividad y costos del raleo de algarrobo blan- co (Prosopis alba) en Santiago del Estero, Argentina. Una primera CONCLUSIONS aproximacion Agrociencia Uruguay. Agrociencia Uruguay vol.18 n.o 2. The values of the measured variables are indicative ex- CUADRA, D. 2012. La problematica forestal en la provincia pression of the productive capacity of the species in the del Chaco, Argentina. Un analisis desde la Geografia. Revista study area. Geográfica Digital. IGUNNE. Facultad de Humanidades. UNNE. Ano 9. N.o 18. Resistencia, Chaco. We recommend to carefully select the places to this DELVALLE, P. 2006. Raleos selectivos en forestacion joven de species, as well as to carefully manage density, to achieve algarrobo blanco Prosopis alba Griseb. ii Jornadas Forestales en good results in terms of timber production. Santiago del Estero: “El arbol. Forestacion y aprovechamiento in-

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Logistic Model SQ= Good Gompertz Model SQ= Good

35 35

30 30

25 25

20 20

15 15 Estimates Estimates 10 10

5 5

0 0 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 Observed Observed

Logistic Model SQ= Regular Gompertz Model SQ= Regular

35 35

30 30

25 25

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15 15 Estimates Estimates 10 10

5 5

0 0 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 Observed Observed

Figura 3. Valores de DDOM observados y estimados de los modelos seleccionados para ambos grupos de calidad de sitio.

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KEES, S.M.; FERRERE, P.; LUPI, A.M.; MICHELA, J.F.; SKOKO, J.J.