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Article

Dendroclimatology of Cedrela fissilis Vell. and Copaifera langsdorffii Desf. in an Urban Forest Under Cerrado Domain

by
Larissa da Silva Bueno dos Santos
1,
Letícia Seles de Carvalho
1,
José Guilherme Roquette
2,
Matheus Marcos Xavier de Souza
3,
Gabriel Bazanela de Agostini
3,
Ronaldo Drescher
3,
Jaçanan Eloisa de Freitas Milani
3,* and
Cyro Matheus Cometti Favalessa
3
1
Faculty of Forestry Engineering, Federal University of Mato Grosso—UFMT, Cuiabá 78060-900, MT, Brazil
2
Public Prosecutor’s Office of Mato Grosso, Cuiabá 78050-900, MT, Brazil
3
Postgraduate Program in Forestry and Environmental Sciences, Federal University of Mato Grosso—UFMT, Cuiabá 78060-900, MT, Brazil
*
Author to whom correspondence should be addressed.
Forests 2025, 16(2), 289; https://doi.org/10.3390/f16020289
Submission received: 8 January 2025 / Revised: 31 January 2025 / Accepted: 6 February 2025 / Published: 8 February 2025
(This article belongs to the Special Issue Abiotic and Biotic Stress Responses in Trees Species)
Browse Figures
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Abstract

:
The study is about the influence of climate change on tree growth in urban forests in Cuiabá, Mato Grosso, Brazil, using dendrochronology. The study focuses on two species, Cedrela fissilis Vell. and Copaifera langsdorffii Desf., both with dendrochronological potential. Samples were collected from an urban forest fragment, and local (temperature and precipitation) and global (ocean surface temperature—SST and Niño 3.4 index) meteorological data were analyzed to correlate with ring width. The methodology involved collecting, preparing, polishing, and marking the rings. The data series were analyzed using the COFECHA, Arstan, and CooRecorder programs to verify the accuracy of ring dating and SAS program for correlations with climatic variables. Both species exhibited good correlations between growth rings and climatic conditions. Cedrela fissilis and Copaifera langsdorffii were positively correlated with precipitation during the dry season and generally negatively correlated with temperatures. Negative correlations were identified with SST and Niño 3.4 for both species. These results are important for understanding how urban forests respond to climate change and how the study of growth rings can be used to predict the future impacts of these changes on plant species.

Graphical Abstract

1. Introduction

Climate change, resulting from human actions, has been progressively accelerated since the Industrial Revolution, with potentially serious consequences for the planet [1,2]. In general, not only the average temperature has changed, but there was also a decrease in precipitation and an increase in the frequency of extreme weather events [3]. These climate changes influence the intensification of storms, droughts, and heat waves [4]. Such events act as modulators on the current ecological landscape, and the consequences extend from local to global levels [5,6].
Moreover, with the advance of the urbanization process, an increase in the intensity and frequency of rainfall in large urban centers has also been observed [7,8]. This phenomenon is associated with the formation of heat islands, which raise local temperatures and aggravate the severity of precipitation events in these regions [9,10].
In this scenario, past or present climate changes can be identified in the development of tree species through the study of their growth rings, which reflect their responses to environmental conditions [11,12,13]. The dating of each growth ring allows for the construction of a historical series that can be correlated with climate, in addition to allowing for the definition of growth forecast, which is essential for forest management and conservation studies [14,15,16].
Thus, urban areas are valuable for dendrochronological studies, which have been neglected historically [17,18]; on the other hand, dendroclimatology is an important tool for the identification and reconstruction of past climatic events [12], such as natural environmental changes [19] and the availability of water resources [20]. In this view, the use of growth rings as biomarkers is a promising way to assess changes in tree flora in anthropogenic environments [21].
Furthermore, urban forests also play an important role in the dynamics of ecosystems, being sensitive to environmental changes and also acting on the carbon cycle, which contributes to the mitigation of climate change in urban environments [22,23,24].
Cedrela fissilis Vell. (Meliaceae) is a neotropical species found in several South and Central American countries [25]. Its habitat ranges from tropical and subtropical humid and dry forests to cloud/mountain ecosystems and savannas [26]. In Brazil, the species occurs in all biomes [25]. Mature C. fissilis trees can reach approximately 30 m in height and 1.5 m in diameter [27], occupying the forest canopy and classified as late secondary [28]. Regarding its vegetative phenology, the species is deciduous, losing its leaves during the dry season and renewing them at the beginning of the rainy season [27,29].
Copaifera langsdorffii Desf. (Fabaceae) is a native but not endemic species of Brazil, with a broad distribution in South America [30]. In Brazil, it is found in various phytophysiognomies of the Savannah, Amazon, Atlantic Forest, and Caatinga biomes [30,31,32]. In the adult phase, the species can reach approximately 35 m in height [33] and exhibits a semi-deciduous vegetative behavior, with more pronounced leaf loss during the dry season [34]. The species is also classified as late secondary [30].
Both species selected for this study, Cedrela fissilis and Copaifera langsdorffii, have consolidated dendrochronological potential [35,36]. This study aimed to address the influence of local and global meteorological variables on the width of growth rings of urban forest species in Cuiabá, Mato Grosso, Brazil, considering the hypotheses that climate change may limit diameter increase, reducing the provision of ecosystem services.

2. Materials and Methods

2.1. Description of the Study Area

The study was conducted in an urban forest fragment (Figure 1) located at the Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA) seat, in Cuiabá, Mato Grosso, Brazil. The area is characterized by flat topography, with altitudes ranging from 146 m to 250 m [37].
The climate of the region is Aw type, characterized by a regime of concentrated rain from October to April, followed by a dry season from May to September [38], as shown in Figure 2.
Brazilian savannah is the biome that covers the study area, where two soil conditions, one with well-drained soil (lytic neosol) and another with poorly drained soil (gleisol), result in high floristic diversity [40].

2.2. Studied Species

Cedrela fissilis—Meliaceae, stands out as a potential species for dendrochronological studies because it has identifiable and distinct annual growth rings [36,41,42,43,44], characterized by the presence of a semi-porous axial parenchymal band [41,45,46]. It is a widely distributed species in Brazil [25].
Copaifera langsdorffii—Fabaceae, is a species with visible growth rings [35,47], which are distinct, defined by marginal parenchyma bands containing axial channels; another observed feature is the presence of false growth rings, which are distinguished by the absence of axial channels, discontinuity, and/or the low thickness of the parenchyma band [35,47,48]. The species is widely used in traditional medicine due to its oil–resin, which has anti-inflammatory and anti-microbial properties, as well as being recommended for degraded area reforestation by its capacity to fix nitrogen in the soil [49,50,51].

2.3. Sample Collection and Preparation

In 2023, 20 tree ring cores with two repetitions (radius) per tree [17,52], at 1.3 m height from the ground, were collected by the non-destructive method using an increment borer Ø5 mm (Haglöfs, Bromma, Sweden), in perpendicular positions. The extracted samples were transported in a plastic holder to the laboratory and fixed on a wooden holder for drying at room temperature. Subsequently, the samples were glued onto a wooden holder with elongated grooves with adequate thickness and depth. The surface polishing of the cross-section was performed with a manual sander and water sandpaper of different granulometries (from 80 grains/cm2 to 2000 grains/cm2) and, during polishing, the samples were exposed to an air jet for residual powder removal.

2.4. Ring Marking

The sample collection was conducted in 2023, so the base year for the analysis was 2022. The growth rings were delimited (Figure 3) with the help of a table magnifying glass (10×) and a stereoscopic magnifying glass (8–50×), and, after manual marking, the samples were scanned by an HP Scanjet G2710 Scanner (Hewlett Packard Development Company, L.P., Palo Alto, CA, USA) with 1200 dpi resolution to enable the measurement of the ring width by means of the program CooRecorder & Cdendro (v7.8) [53], and to build the collections in the extension Rwl and to enable statistical analysis with the programs COFECHA (v6.06) [54] and Arstan (v40c) [55,56].

2.5. Data Analysis

The data were processed by the COFECHA program [54] for dating quality control. The accuracy in growth ring cross-dating helped to determine whether to include or reject a part of the series in the chronology [57,58]. It also signaled unusual correlations as possible errors requiring a visual review of the original markings to ensure the accuracy of the dating [59] and to provide the statistical parameter of mean intercorrelation (R-bar).
Additionally, the Express Population Signal (EPS) was calculated for both species, because it reflects how much a master chronology explains a theoretically infinite population, through finite samples, and it depends on the R-bar [60]. Values greater than 0.85 indicate that the number of samples is enough for a climatic reconstruction [61,62].
In order to remove the non-climate-related growth variations [63], an Arstan program was used, in which a 20% cubic spline was applied, with 20-year moving windows in 10-year segments, resulting in res (residual) chronology, which corresponds to the average of residual indices [64,65,66,67].
Then, the Pearson Correlation Test was applied among the res series indices and the monthly average values of minimum, average, and maximum temperatures and the monthly accumulated rainfall value, obtained from the conventional weather station in Cuiabá (15°37′12″ S 56°06′32″ W), which is located 9 km from the study area. Furthermore, it was also correlated with El Niño-Southern Oscillation 3.4 index, obtained from the National Oceanic and Atmospheric Administration (NOAA) website (https://psl.noaa.gov/data/correlation, accessed on 23 January 2025). Considering that climatic factors of previous years may influence the changing activity, the correlation tests were applied with time lags of zero (current year) and one year.
The Pearson correlation test at the 5% significance level between the residual indices and the variables was performed using the SAS® OnDemand for Academics (2023) program (https://welcome.oda.sas.com, accessed on 27 January 2025) [68].
Additionally, growth ring widths were also correlated with ocean temperature, given by Koninklijk Nederlands Meteorologisch Instituut (KNMI), bimonthly. The monthly data were obtained from the Climate Explorer platform (https://climexp.knmi.nl/start.cgi, accessed on 23 January 2025) by KNMI (2024), from the database by Hadley Centre Sea Ice and Sea Surface Temperature Data Set—HadISST (2024), with a 95% confidence interval.

3. Results

From a total of 20 samples for each species, 15 series were obtained for Cedrela fissilis and 18 for Copaifera langsdorffii, in which the values of the final intercorrelations were 0.384 and 0.421, respectively (Table 1).
The ages of Cedrela fissilis trees ranged from 18 to 39 years old, with the most advanced age being dated to 1984, and EPS reached the value of 0.88. For Copaifera langsdorffii, the ages were from 11 to 37 years old (1986–2022), and the EPS reached the value of 0.83. For both species, it was necessary to remove samples to improve data quality, according to procedures performed at COFECHA [54]. Multiple or false growth rings were identified and were also excluded from the final chronology, resulting in 15 samples of C. fissilis and 18 of C. langsdorffii (Figure 4).
The correlations between the residual chronology for C. fissilis and the meteorological variables were relevant both without a time lag and with a one-year lag, as was the case for C. langsdorffii (Figure 5). As for the precipitation data, the highest observed correlation for C. fissilis was in December (−0.40; p < 0.05), whereas for C. langsdorffii it was in July (0.47; p < 0.05), both for the current year. For the maximum temperature, C. fissilis obtained the highest correlation in November (−0.36; p < 0.05), while C. langsdorffii reached it in May of the previous year (−0.30; p < 0.05). Check significance values in Table S1.
For the mean temperature, the highest correlations for C. fissilis were in June (0.31; p < 0.05) and for C. langsdorffii in July of the previous year (−0.48; p < 0.05). Finally, for the minimum temperature the highest correlations were obtained in July of the previous year for C. fissilis (−0.31; p < 0.05) and in June for C. langsdorffii (0.43; p < 0.05).
Regarding the ocean temperature for C. fissilis (Figure 6a), negative spatial correlations were observed with the temperature in the Atlantic Ocean (Equatorial and South), reaching values of up −0.5 to −0.6 (p < 0.05), while for the one-year lag for the same period, no significant correlations were observed.
The residual chronology for C. langsdorffii (Figure 6b), negative spatial correlations with the temperature in the South Pacific Ocean, were observed with a one-year lag, reaching values above −0.6 (p < 0.05), while no relevant correlations were observed in that current year.
For the other two-month period and for both species, no higher correlations were obtained other than those shown in Figure 6.
The Niño 3.4 atmospheric circulation index also showed relationships with the residual chronology of C. fissilis and C. langsdorffii (Figure 7), reaching −0.3166 (p < 0.05) for C. fissilis and −0.5323 (p < 0.05) for C. langsdorffii, both for the dry period of the previous year.

4. Discussion

In the study at hand, the average intercorrelation values (R-bar), for the species Cedrela fissilis and Copaifera langsdorffii, were similar to those found in other surveys with these species and other tropical ones [36,47,65,69], which suggests that the methods used to calculate ring width may be applicable in different contexts and other tropical regions. EPS values greater than 0.85 indicate that the number of samples was enough for climatic reconstruction, and an average sensitivity greater than 0.30 reveals that the time series were suitable for cross-dating [57,61,62].
From another perspective, the evaluated climatic signs influence the ring width of the species studied in an urban environment. These signs, such as temperature and precipitation, are captured by the tree growth layers, which serve as highly reliable natural records in dating, which are capable of capturing about 60% of the weather condition’s annual variation [70,71].
The response from the species to climatic variables demonstrated interesting aspects. Both species showed positive correlation with precipitation in the dry period, especially in July for C. fissilis and in July and August for C. langsdorffii. This behavior can be attributed to the adaptive strategies of these trees, which, in water scarcity conditions, reduce their changing activity, which helps mitigate the effects of water stress [72,73]. C. langsdorffii, with its ecological plasticity, and C. fissilis, with wide geographical distribution in Brazil, are examples of how different species can present diverse adaptations to variable climatic conditions [25,30].
The species considered in this study responded similarly to the temperatures evaluated, generally achieving negative correlations, especially with the values of maximum and average ones. This result can be explained because high temperature is one of the factors responsible for stomatal closure, which reduces CO2 assimilation and consequently growth [74,75].
Moreover, ocean temperature variation showed, at a level of 5% significance, a negative correlation with temperature in the Equatorial and South Atlantic Ocean in the dry period (winter) in regions that cover the Intertropical Convergence Zone (ITCZ) and the South Atlantic Convergence Zone (SACZ). These atmospheric systems have great influence on the state of Mato Grosso, Brazil [76]. The ITCZ, when moved to the south during the summer, favors precipitation, while in winter, when moving north, it results in low rainfall [77]. In turn, the SACZ appears less favorable to precipitation in winter due to the change of atmospheric circulation and the action of systems such as the Atlantic Tropical Anticyclone [78].
In contrast, the residual chronology for Copaifera lagsdorffii, also at 5% significance, showed a negative correlation with the temperature variation in the South Pacific Ocean.
This result is similar to that found for Handroanthus heptaphyllus in the Pantanal, near the city of Cuiabá, Mato Grosso, Brazil [79], and for Macrolobium acaciifolium in the Amazon during drought [80].
This behavior can be explained by the occurrence of El Niño–Southern Oscillation (ENSO) events, which are corroborated by the correlation of the residual chronology of the species with the Niño 3.4 index, which were the most pronounced negative values between the months of May and August, as well as for C. fissilis, although with less intensity.
ENSO events are related to reduced precipitation in the Midwest region [81,82,83,84], due to the change in the position of the Walker circulation cell, weakening of the trade winds, and the reduced action of the SACZ on the continent [84,85,86,87,88,89,90,91]. Previous studies indicate that water stress caused by drought results in the decreased growth of tropical trees [92]. An aggravating factor is climate change, which is associated with an increase in the frequency and intensity of El Niño events [93].
This relationship between tree growth and climatic variables, in other words, indicates an interaction between the environment and favorable conditions for plant development, such as resource or competition conditions [94]. However, this response was not uniform among the species, since each one presented a distinct genotype–environment interaction [95,96].
Thus, the influence of the climate, especially precipitation, affects the species considered in this study not only in terms of their growth and development over the years, but also with regard to tropical ecosystem operation [97], especially urban ecosystems. This is because climate, especially the temperature, influences the extent and distribution of species [98] and, along with physical barriers, defines the geographical limits of their occurrence [99,100].
In this context, considering the results obtained, it is possible to state that climate, both on a regional and global scale, affects the growth rings width variation of the species studied. In addition, it is important to highlight other variables not tested in this study that also influence this aspect, such as soil nutrients, competition between trees, and urban pollution. Finally, it is worrying to evaluate future predictions related to climate change, which affects climate on various scales [3,93], and which may compromise the future development of species.

5. Conclusions

  • Dendrochronological studies in urban areas of the Brazilian savannah show promise for detecting the influence of meteorological variables on the growth rings widht of the species in this study.
  • In general, local precipitation and temperature variables correlate both positively and negatively with the width of the species growth rings, depending on the time of year, while only negative correlations were identified for ocean temperature and the Niño 3.4 index.
  • This study is limited to the analysis of meteorological variables and climate anomalies, which partially affect the development of the species. However, more in-depth studies are needed to understand the role of eco-physiological variables.
  • The results obtained here are promising for guiding new studies that consider urban forests and their importance in relation to climate change.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f16020289/s1, Table S1: Correlation coefficients and significance of the correlation for Cedrela fissilis in Cuiabá, Mato Grosso, Brazil.; Table S2: Correlation coefficients and significance of the correlation for Copaifera langsdorffii in Cuiabá, Mato Grosso, Brazil.

Author Contributions

Conceptualization, J.G.R.; formal analysis, L.d.S.B.d.S.; investigation, L.d.S.B.d.S.; data curation, L.S.d.C., J.G.R. and M.M.X.d.S.; writing—original draft preparation, L.d.S.B.d.S.; writing—review and editing, J.E.d.F.M., G.B.d.A. and C.M.C.F.; supervision, C.M.C.F.; project administration, J.G.R. and R.D.; funding acquisition, J.G.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Banco de Projetos do Ministério Público do Estado de Mato Grosso (BAPRE-MT), Brazil.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

The authors thank Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA) for authorizing the development of research used in this project in an urban forest in the superintendence of IBAMA in Cuiabá, Mato Grosso, Brazil.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript.
IBAMABrazilian Institute of Environment and Renewable Natural Resources (in English)—Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (in Portuguese)
R-barAverage intercorrelation
EPSExpress Population Signal
Resresidual
KNMIKoninklijk Nederlands Meteorologisch Instituut
ITCZIntertropical Convergence Zone
SACZSouth Atlantic Convergence Zone
ENSOEl Niño–Southern Oscillation

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Figure 1. Study area at Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA) in Cuiabá, Mato Grosso, Brazil.
Figure 1. Study area at Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA) in Cuiabá, Mato Grosso, Brazil.
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Figure 2. Climatological normal data about Cuiabá, Mato Grosso, Brazil (1991–2020). Source: Instituto Nacional de Meteorologia [39].
Figure 2. Climatological normal data about Cuiabá, Mato Grosso, Brazil (1991–2020). Source: Instituto Nacional de Meteorologia [39].
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Figure 3. True growth rings (black triangles) and false ones (white triangles) in Cedrela fissilis Vell. (A) and Copaifera langsdorffii Desf. (B). Source: Authors.
Figure 3. True growth rings (black triangles) and false ones (white triangles) in Cedrela fissilis Vell. (A) and Copaifera langsdorffii Desf. (B). Source: Authors.
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Figure 4. Residual chronology for Cedrela fissilis Vell. from 1984 to 2022 (a) and Copaifera langsdorffii Desf. from 1986 to 2022 (b) in an urban forest area in Cuiabá, Mato Grosso, Brazil. Note: Gray lines correspond to the residual indices of each sample, and the red line corresponds to the mean residual indice.
Figure 4. Residual chronology for Cedrela fissilis Vell. from 1984 to 2022 (a) and Copaifera langsdorffii Desf. from 1986 to 2022 (b) in an urban forest area in Cuiabá, Mato Grosso, Brazil. Note: Gray lines correspond to the residual indices of each sample, and the red line corresponds to the mean residual indice.
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Figure 5. Pearson’s Correlations between residual chronology for Cedrela fissilis Vell. (a) and Copaifera langsdorffii Desf. (b) and the monthly variables for precipitation, maximum, average and minimum temperatures. [Notes: color bars: correlation coefficient; dotted lines: statistical significance (p = 0.05); (−1): one-year lag].
Figure 5. Pearson’s Correlations between residual chronology for Cedrela fissilis Vell. (a) and Copaifera langsdorffii Desf. (b) and the monthly variables for precipitation, maximum, average and minimum temperatures. [Notes: color bars: correlation coefficient; dotted lines: statistical significance (p = 0.05); (−1): one-year lag].
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Figure 6. Spatial Correlation between the ocean temperature and residual chronology for Cedrela fissilis Vell. (a) and Copaifera langsdorffii Desf. (b) in May–June, June–July and July–August, with and without one-year time lag.
Figure 6. Spatial Correlation between the ocean temperature and residual chronology for Cedrela fissilis Vell. (a) and Copaifera langsdorffii Desf. (b) in May–June, June–July and July–August, with and without one-year time lag.
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Figure 7. Pearson’s Correlations between the Niño 3.4 index and residual chronology for Cedrela fissilis Vell. and Copaifera langsdorffii Desf. [Notes: color bars: correlation coefficient; dotted lines: statistical significance (p = 0.05); (−1): one-year lag].
Figure 7. Pearson’s Correlations between the Niño 3.4 index and residual chronology for Cedrela fissilis Vell. and Copaifera langsdorffii Desf. [Notes: color bars: correlation coefficient; dotted lines: statistical significance (p = 0.05); (−1): one-year lag].
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Table 1. Descriptive statistics of the chronology of individuals of Cedrela fissilis Vell. and Copaifera langsdorffii Desf.
Table 1. Descriptive statistics of the chronology of individuals of Cedrela fissilis Vell. and Copaifera langsdorffii Desf.
DescriptionSpecies
Cedrela fissilisCopaifera langsdorffii
Observed period 1984–20221986–2022
Number of dated series (from the total of)15 (20)18 (20)
Individuals1010
Total of rings in all the samples377432
Total of checked rings376432
Intercorrelation0.3840.421
Average sensitivity0.3960.513
Average correlation among the series
(R-bar) ± standard deviation 		0.325 ± 0.227 10.216 ± 0.182 2
Express populational signal (EPS)0.880.83
1 R-bar of the dated series; 2 R-bar of the total series.
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Santos, L.d.S.B.d.; Carvalho, L.S.d.; Roquette, J.G.; Souza, M.M.X.d.; Agostini, G.B.d.; Drescher, R.; Milani, J.E.d.F.; Favalessa, C.M.C. Dendroclimatology of Cedrela fissilis Vell. and Copaifera langsdorffii Desf. in an Urban Forest Under Cerrado Domain. Forests 2025, 16, 289. https://doi.org/10.3390/f16020289

AMA Style

Santos LdSBd, Carvalho LSd, Roquette JG, Souza MMXd, Agostini GBd, Drescher R, Milani JEdF, Favalessa CMC. Dendroclimatology of Cedrela fissilis Vell. and Copaifera langsdorffii Desf. in an Urban Forest Under Cerrado Domain. Forests. 2025; 16(2):289. https://doi.org/10.3390/f16020289

Chicago/Turabian Style

Santos, Larissa da Silva Bueno dos, Letícia Seles de Carvalho, José Guilherme Roquette, Matheus Marcos Xavier de Souza, Gabriel Bazanela de Agostini, Ronaldo Drescher, Jaçanan Eloisa de Freitas Milani, and Cyro Matheus Cometti Favalessa. 2025. "Dendroclimatology of Cedrela fissilis Vell. and Copaifera langsdorffii Desf. in an Urban Forest Under Cerrado Domain" Forests 16, no. 2: 289. https://doi.org/10.3390/f16020289

APA Style

Santos, L. d. S. B. d., Carvalho, L. S. d., Roquette, J. G., Souza, M. M. X. d., Agostini, G. B. d., Drescher, R., Milani, J. E. d. F., & Favalessa, C. M. C. (2025). Dendroclimatology of Cedrela fissilis Vell. and Copaifera langsdorffii Desf. in an Urban Forest Under Cerrado Domain. Forests, 16(2), 289. https://doi.org/10.3390/f16020289

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