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Stand and environmental data from Pinus halepensis Mill. and Pinus sylvestris L. plantations in Spain

  • Teresa BueisEmail author
  • María-Belén Turrión
  • Felipe Bravo
Open Access
Data Paper
Part of the following topical collections:
  1. Mediterranean Pines

Abstract

Key message

This data set provides valuable environmental information about Pinus halepensis and Pinus sylvestris plantations in Spain. An array of 74 physical, chemical and biochemical soil (organic horizon and 10 cm topsoil), climatic, physiographic and stand variables from 32 P. halepensis and 77 variables from 35 P. sylvestris plantations are provided. Dataset access is at  https://doi.org/10.5281/zenodo.1294607. Associated metadata is available at https://agroenvgeo.data.inra.fr/geonetwork/srv/eng/catalog.search#/metadata/b769554a-2e62-414a-9392-ebd307f0c76f.

Keywords

Soil physical parameters Soil chemical parameters Soil biochemical parameters Climatic parameters Physiographic parameters Stand parameters Site index Forest productivity 

1 Background

Pinus halepensis Mill. and Pinus sylvestris L. were extensively used for reforestation of degraded areas in Castilla y León region during the last century. The knowledge about the relationships between environmental factors and stand data in forest plantations can help forest managers to achieve both protective and productive goals for these plantations and are useful for the understanding of the ecosystem functioning (Bueis et al. 2016, 2017). Environmental parameters including climatic, topographic and soil (physical, chemical and biochemical) parameters have proved useful for estimating forest productivity (Aertsen et al. 2012; Afif-Khouri et al. 2010; Bravo-Oviedo and Montero 2005; Bravo and Montero 2001; Bueis et al. 2016, 2017; Corona et al. 1998; Hagglund and Lundmark 1977; Nieppola and Carleton 1991; Pietrzykowski et al. 2015; Romanya and Vallejo 2004; Sanchez-Rodriguez et al. 2002; Sharma et al. 2012). Forest productivity is usually estimated through stand parameters such as the dominant height (the height of the 100 thickest trees per hectare) at a reference age, because it is strongly correlated to wood production (Skovsgaard and Vanclay 2008). However, some silvicultural practices modify the dominant height of the stands leading to underestimation of forest productivity. In those cases, the methods based on environmental parameters are more appropriate (Bueis et al. 2016, 2017). Besides, soil biochemical parameters reflect the status of the soil biological activity responsible for mineralisation and humification processes and then responsible for nutrient availability in forest ecosystems (Bueis et al. 2018b; Yang et al. 2012) and are also useful indicators of health and quality in forest ecosystems (Bloem et al. 2006).

The plots of the Spanish National Forest Inventory (SNFI) constitute a very valuable source of information to monitor the evolution of the Spanish forest stands. The SNFI permanent plots are located in the intersections of a systematic 1-km × 1-km grid when they coincide with forest areas. The same measurements are carried out every 10 years including the species composition of the stand, the canopy cover, the age, the diameter at breast height (DBH; 1.3 m) and the total height of the trees, among others. Each plot consisted of four concentric circular plots with 25-, 15-, 10- and 5-m radii, where the trees with DBH higher than 42.5, 22.5, 12.5 and 7.5 cm are measured, respectively. Additionally, in the 5-m radius subplots, the trees with DBH between 2.5 and 7.5 cm are counted. The information gathered in each subplot can be extended to the hectare by means of the expansion factor of each subplot calculated as the area of a hectare (10,000 m2) divided into the area of each subplot. Therefore, the expansion factors are 5.09, 14.15, 31.83 and 127.32, respectively, for the 25-, 15-, 10- and 5-m subplots. Detailed information about the forest stand is collected in the NFI. However, environmental information is scarcely gathered in these inventories, especially the data relative to the soil.

The Sustainable Forest Management Research Institute (iuFOR; University of Valladolid and INIA) also has a network of permanent plots in Pinus sylvestris plantations which consisted of rectangular 30 × 20-m plots. These plots have previously been studied to quantify the C sequestration in soils and forest biomass in Pinus sylvestris stands (Herrero and Bravo 2012; Herrero et al. 2016; Herrero de Aza et al. 2011).

2 Methods

2.1 Study sites

The 32 SNFI plots in Pinus halepensis plantations included in this dataset are located in the centre of the region of Castilla y León (Fig. 1). The 35 iuFOR plots located in Pinus sylvestris plantations are located in the north of the region of Castilla y León (Fig. 1). Both Pinus halepensis and Pinus sylvestris are monospecific stands originated from afforestation. The geographical location (latitude and longitude), the altitude above the sea level and the gradient (slope) of each plot are shown in Table 1 (SNFI plots; Pinus halepensis), and Table 2 (iuFOR plots; Pinus sylvestris).
Table 1

Location and main characteristics of the 32 plots in Pinus halepensis plantations

Plot name

UTM_Xa

UTM_Ya

Altitude (m)

Slope (%)

6

333,000

4,640,000

801

15

7

333,000

4,639,000

816

27

8

337,000

4,637,000

836

28

9

333,000

4,635,000

810

15

25

332,000

4,633,000

804

30

43

321,000

4,627,000

827

33

107

322,000

4,618,000

803

20

144

368,000

4,623,000

844

54

156

367,000

4,617,000

835

35

202

330,000

4,605,000

811

24

223

349,000

4,613,000

820

33

228

347,000

4,610,000

775

12

233

370,000

4,608,000

791

39

375

377,000

4,613,000

779

30

376

394,000

4,612,000

801

35

496

412,000

4,604,000

801

35

662

373,000

4,656,000

856

40

664

388,000

4,668,000

861

23

712

367,000

4,585,000

788

38

717

356,000

4,639,000

854

0

718

357,000

4,639,000

856

0

723

353,000

4,638,000

855

0

771

386,000

4,632,000

825

31

786

404,000

4,631,000

915

21

864

360,000

4,575,000

781

17

1237

390,000

4,639,000

860

55

1245

382,000

4,627,000

829

11

2057

357,000

4,629,000

779

20

2063

356,000

4,625,000

776

5

2070

371,000

4,622,000

846

40

2108

378,000

4,617,000

769

25

2136

403,000

4,621,000

881

25

aUnits: m (UTM Projection; Datum ED50)

Fig. 1

Location of the plots (circles: Pinus sylvestris plots; triangles: Pinus halepensis plots)

Table 2

Location and main characteristics of 35 plots in Pinus sylvestris plantations

Plot name

UTM_Xa

UTM_Ya

Altitude (m)

Slope (%)

S1

356,689

4,711,709

1005

0

S2

356,510

4,718,046

1017

12

S3

346,008

4,735,864

1180

0

S4

345,449

4,732,431

1149

0

S5

356,953

4,723,227

1075

0

S6

352,284

4,724,256

1080

5

S7

370,257

4,717,777

926

0

S8

371,299

4,717,225

938

0

S9

371,111

4,716,897

928

0

S10

372,303

4,715,356

931

0

S11

356,791

4,722,980

1069

0

S12

358,125

4,712,512

981

9

S14

356,874

4,723,451

1080

0

S16

353,086

4,733,717

1153

0

S17

353,515

4,736,657

1171

3

S18

347,849

4,728,273

1095

3

S19

374,732

4,715,297

958

5

S20

341,138

4,727,330

1080

10

S21

343,309

4,731,280

1135

2

S22

344,755

4,731,657

1139

3

S23

344,069

4,729,889

1118

5

S24

344,273

4,727,795

1103

2

S25

343,114

4,726,676

1086

0

S26

340,167

4,724,006

1068

2

S27

340,347

4,724,323

1062

0

S28

341,275

4,721,130

995

8

S29

344,662

4,728,832

1106

3

S30

345,725

4,733,054

1180

0

S32

343,620

4,729,463

1103

0

S35

341,554

4,727,760

1041

0

S36

344,540

4,729,354

1103

3

S37

345,010

4,728,213

1076

2

S38

344,987

4,728,181

1080

0

S40

345,075

4,728,213

1078

3

S45

345,080

4,728,126

1070

0

aUnits: m (UTM Projection; Datum ETRS89)

2.2 Sampling and data collection

Soil sampling and stand, climatic and physiographic data collection were done as detailed in Bueis et al. (2016) available at  https://doi.org/10.3832/ifor1600-008, in Bueis et al. (2017) available at  https://doi.org/10.1007/s13595-016-0609-7 and in Bueis et al. (2018b) available at  https://doi.org/10.1007/s13595-018-0720-z.

The height and diameter data in Pinus halepensis plantations come from the Third National Forest Inventory (1997–2007) and in Pinus sylvestris stands were gathered in the field (iuFOR plots) in 2010. Soil sampling and environmental data collection were carried out in Pinus sylvestris plots in autumn 2011 and in Pinus halepensis plots in autumn 2012.

The diameters of the trees included in both Pinus sylvestris and Pinus halepensis plots were determined by means of a tree calliper in two perpendicular directions and the average diameter was recorded for each tree. The local basal area of each plot was determined with the diameters of the trees in each plot. Tree height was determined with the aid of a hypsometer. The age of each stand was determined through the year of plantation provided by the Regional Government of Castilla and León, which is in charge of the management of these stands. The gradient of each plot was measured with a clinometer, and the aspect was determined with a compass.

Soil sampling was carried out in four sampling points per plot, located at a 5-m distance from the centre of the plot in N, S, E and W directions. The forest floor (organic horizon) was sampled in each sampling point in a 20 × 20 quadrant and the 10-cm topsoil was also sampled in each sampling point. Both the forest floor and the mineral soil samples collected in the four sampling points per plot were mixed to get a composite sample per plot.

3 Access to data and metadata description

The data set (Bueis et al. 2018a) is available at Zenodo digital repository:  https://doi.org/10.5281/zenodo.1294607. Associated metadata is available at https://agroenvgeo.data.inra.fr/geonetwork/srv/eng/catalog.search#/metadata/b769554a-2e62-414a-9392-ebd307f0c76f . The data set cover a file whose filename is Dataset.csv.

The file Dataset.csv contains information about the 74 environmental variables studied in the 32 SNFI plots (32 rows) in Pinus halepensis plantations and about the 77 environmental variables studied in the 35 iuFOR plots (35 rows) in Pinus halepensis plantations.

The first column (Plot) of the file Dataset.csv identifies the plot and the second column (Species) identifies the species in each plot (1: Pinus sylvestris; 2: Pinus halepensis). Plot characteristics include the gradient in percentage (Slope), the elevation in metres above the sea level (Altitude) and the geographical coordinates of the plots in degrees (Latitude and Longitude). Stand characteristics include the number of trees per hectare in the plot (Density), the quadratic mean diameter in centimetres (Dg), the mean height in metres (Hm), the dominant height in metres (H0), the basal area in square metres per hectare (BA), the dominant height at the reference age (80 years for Pinus halepensis and 50 years for Pinus sylvestris) in metres (site index (SI)), the site quality (SQ) class and the average age in years of the trees in the plot (age).

The soil physical properties of each plot include available water (AW), coarse particles (CO), porosity (Porosity), clay content (CLAY), silt content following the USDA criteria (SILTUS), silt content following the international criteria (SILTIS), sand content following the USDA criteria (SANDUS) and sand content following the international criteria (SANDIS), all of them in percentage. The organic horizon–related parameters include the organic horizon thickness in the plot (OHT) in centimetres, the total carbon to total nitrogen ratio in the litter fraction of the organic horizon ([C/N]L), the total carbon to total nitrogen ratio in the fragmented plus humified fraction of the organic horizon ([C/N]FH), the amount of litter fraction in the organic horizon (L) in tons per hectare and the amount of fragmented plus humified fraction in the organic horizon (FH) in tons per hectare.

The soil chemical parameters include pH value (pH), cation exchange capacity (CEC) in centimoles of charge per kilogramme of soil, the amount of easily oxidisable C in percentage (EOC), the amount of available phosphorus (AP) in milligrammes per kilogramme of soil, the total N (TN) in percentage, the total organic C to total N ratio (TOC/TN), the amount of exchangeable calcium, magnesium, sodium and potassium (Ca, Mg, Na, K) in centimoles of charge per kilogramme of soil and the water soluble phenols (WSP) in nanomoles of TAE per gramme of soil. Due to the calcareous nature of soils under Pinus halepensis plantations (SNFI plots), the following variables were also studied: the amount of carbonates (Carbonates) in percentage, the amount of reactive carbonates (React_carb) in percentage, the amount of gypsum (Gypsum) in centimoles of charge per kilogramme of soil and the amount of copper, iron, manganese and zinc (Cu, Fe, Mn, Zn) in milligrammes per kilogramme of soil. Similarly, due to the acidic nature of soils under Pinus sylvestris plantations (iuFOR plots), the following variables were also studied: the exchangeable acidity (EA) in centimoles of charge per kilogramme of soil, the base saturation (Sat) in percentage and the amorphous aluminium, iron and manganese (AlA, FeA, MnA), organically bound aluminium, iron and manganese (AlM, FeM, MnM) and exchangeable and inorganic aluminium (AlE, AlI) in centimoles of charge per kilogramme of soil.

The soil biochemical parameters include the amount of microbial biomass carbon, nitrogen and phosphorus (Cmic, Nmic and Pmic, respectively) in milligrammes per kilogramme of soil, the amount of mineralisable carbon (Cmin) in milligrammes per kilogramme of soil, the ratios mineralisable carbon to total organic carbon (Cmin/TOC) and microbial biomass carbon to total organic carbon (Cmic/TOC), the microbial metabolic quotient (Cmin/Cmic; qCO2) in grammes per week and gramme of soil, the fluorescein diacetate hydrolysis reaction (FDA) in nanomoles of fluorescein diacetate per gramme of soil and minute, the dehydrogenase activity (DHA) in nanomoles of triphenyl formazan (TPF) per gramme of soil and minute, the acid and alkaline phosphatase activity (AcPhos and AlkPhos, respectively) in nanomoles of p-nitrophenyl phosphate (PNP) per gramme of soil and minute, the urease activity (Urease) in nanomoles of N per gramme of soil and minute, and the catalase activity (Catalase) in nanomoles of O2 per gramme of soil and minute.

The climatic parameters include mean annual temperature (MAT), mean maximum temperatures of the warmest and coldest month (MMWM and MMCM, respectively) and mean temperature of the warmest and coldest month (MTWM and MTCM, respectively) in degrees centigrade; total precipitation (TP) and winter, spring, summer and autumn precipitation (PW, PSP, PSU and PA, respectively) in millimetres; potential and real evapotranspiration (PET and RET) in millimetres; mean annual hydric deficit (Deficit) and surplus (Surplus) in millimetres; the Annual Hydric Index (AHI); and the Martonne and Lang Indexes (Martonne, Lang).

4 Technical validation

The validation of the datasets was carried out through a first by hand verification and complemented by numerical and graphical analyses. Laboratory equipment was regularly calibrated, and standards were used on each analysis. Soil analyses were conducted in duplicate and mean values are presented. Every record was revised in relation to the normal range of values for each variable. Related variables were examined and tested for inconsistencies basing on their correlations and corrected when necessary.

5 Reuse potential and limits

This original dataset includes forest stand, climate, physiography and soil physical, chemical and biochemical characteristics from Pinus halepensis and Pinus sylvestris plantations in Spain which have already been used to develop discriminant models to predict site index from environmental parameters useful to carry out sustainable forest management for stands. Climatic, physiographic and soil physical and chemical parameters are usually included in this kind of models. However, soil biochemical parameters are seldom included, even when soil microorganisms play a key role in soil quality and productivity (Bueis et al. 2016, 2017; Gartzia-Bengoetxea et al. 2009). They have also been used to assess the differences between the enzyme activities in the contrasting soils under Pinus sylvestris and Pinus halepensis plantations and to trace those differences back to edapho-climatic parameters to determine which environmental factors drive enzyme activities in these soils (Bueis et al. 2018b). This information is useful to state managerial proposals for improving enzyme activities and, as a result, improving nutrient availability in forest soils.

The inclusion of soil information would increase the potential use of the information in the SNFI (Alberdi et al. 2017) and iuFOR networks. Highly remarkable are the synergies between the information contained in this dataset and the information related to the forest stand available for the iuFOR and the SNFI plots. These complementary sources of information present combined interest because of their potential to unveil many aspects or dimensions of forest ecosystem functioning in Pinus plantations in Spain (Alberdi et al. 2017; Bueis et al. 2018b).

Notes

Acknowledgements

The authors thank Cristóbal Ordóñez, Elisa Mellado, Temesgen Desalegn, Olga López and Carlos Alejandro Mendoza for their assistance in the field and Carmen Blanco, Juan Carlos Arranz and Adele Muscolo for their advice in laboratory analysis.

Funding

This work was supported by the University of Valladolid and Banco Santander (predoctoral grant to T. Bueis), the Mediterranean Regional Office of the European Forest Institute (EFIMED; “Short Scientific Visit” grant to T. Bueis) and the Ministry of Economy and Competitiveness of the Spanish Government (AGL2011-29701-C02-02 and AGL2014-51964-C2-1-R).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© The Author(s) 2019

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Sustainable Forest Management Research InstituteUniversity of Valladolid & INIAPalenciaSpain
  2. 2.Departamento de Ciencias Agroforestales, E.T.S. Ingenierías AgrariasUniversidad de ValladolidPalenciaSpain
  3. 3.Departamento de Producción Vegetal y Recursos Forestales. E.T.S. Ingenierías AgrariasUniversidad de ValladollidPalenciaSpain

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