# Altitude and community traits explain rain forest stand dynamics over a 2370-m altitudinal gradient in Costa Rica

Alba Loren Hernández Gordillo, Sergio José Vilchez Mendoza, Marie-Ange

Ngo Bieng, Diego Delgado, Bryan Finegan

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Alba Loren Hernández Gordillo, Sergio José Vilchez Mendoza, Marie-Ange Ngo Bieng, Diego Delgado, Bryan Finegan. Altitude and community traits explain rain forest stand dynamics over a 2370-m altitudinal gradient in Costa Rica. Ecosphere, 2021, 12 (12), pp.e03867. 10.1002/ecs2.3867. hal-05179939

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# Altitude and community traits explain rain forest stand dynamics over a 2370-m altitudinal gradient in Costa Rica

ALBA LORENA HERNÁNDEZ GORDILLO<sup>1,†</sup> SERGIO VILCHEZ MENDOZA,<sup>1</sup> MARIE ANGE NGO BIENG,<sup>1,2</sup> DIEGO DELGADO,<sup>1</sup> AND BRYAN FINEGAN<sup>1</sup>

<sup>1</sup>CATIE-Centro Agronómico Tropical de Investigación y Enseñanza, Turrialba, Costa Rica

<sup>2</sup>CIRAD, UR Forêts et Sociétés, CIRAD Campus International de Baillarguet, Montpellier Cedex 5, France

**Citation:** Hernández Gordillo, A. L., S. Vilchez Mendoza, M. A. Ngo Bieng, D. Delgado, and B. Finegan. 2021. Altitude and community traits explain rain forest stand dynamics over a 2370-m altitudinal gradient in Costa Rica. Ecosphere 12(12):e03867. 10.1002/ecs2.3867

**Abstract.** Stand dynamic rates in Earth's vitally important tropical mountain rain forests are a central component of the response of these forests to global change, but their relationships to environmental gradients are poorly understood. We worked in mature forests on a 440–2810 m asl altitudinal gradient on Costa Rica's Talamanca Cordillera, making five censuses of 29 0.25-ha permanent sample plots during 2012–2019. We determined mortality and recruitment rates, as well as basal area (G) increments, for individuals ≥10 cm diameter at breast height. Our main hypothesis was that stand dynamic rates decrease with altitude (therefore temperature); we also tested the hypotheses that rates increase with plot community-weighted mean specific leaf area (CWM SLA) and decrease with CWM wood specific gravity (WSG). We developed regressions using generalized additive models to test our hypotheses. Mortality and recruitment rates decreased with altitude in line with our main hypothesis, though the strongly non-linear mortality trend may be driven by extreme weather and temperature. Also, the best model for recruitment rates included plot CWM SLA with a negative relationship. Gross basal area increment $\Delta G_{gross}$, the annual basal area increment of trees that survived the study period, had a hump-shaped relationship to altitude, possibly related to the low CWM WSG of mid-altitude forests. $\Delta G_{gross}$ was indeed negatively related to CWM WSG. However, net basal area growth ($\Delta G_{net}$, the annualized difference between initial and final plot basal areas) was positively related to altitude due to low mortality in montane forests, in a model with CWM WSG with a negative relationship. $\Delta G_{net}$ was negative in nine of the 29 plots at <1500 m asl. Patterns of rain forest stand dynamics on this long altitudinal gradient go beyond a direct response to temperature, and further work is required to improve scenarios of forest response to climate change. CWM traits should be measured to improve understanding. The effects of storms and lightning on low- and middle-altitude forest and the potentially high resilience of montane Fagaceae-dominated forests require attention. Diversity, not generality, should be expected on comparing tropical forest altitudinal transects.

**Key words:** climate change; Fagaceae; lightning; mortality; recruitment; specific leaf area; stand growth; wood specific gravity.

**Received** 9 November 2020; revised 19 March 2021; accepted 20 July 2021. Corresponding Editor: Joseph A. LaManna.

**Copyright:** © 2021 The Authors. Ecosphere published by Wiley Periodicals LLC on behalf of The Ecological Society of America. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

† **E-mail:** Alba.Hernandez@catie.ac.cr

## INTRODUCTION

Tropical mountain rain forests (rain forests at altitudes >300 m asl; Körner 2007) are highly

vulnerable to the effects of climate change (Malhi et al. 2010, Delgado et al. 2016, Feeley et al. 2020). Thermophilization, through which the composition of a forest stand changes toward a greater
representation of species adapted to higher tem-
peratures (Feeley et al. 2020), is a possible conse-
quence of climate change in these forests. If
thermophilization represents the natural adapta-
tion of the stand to rising temperatures, it seems
plausible that adaptation rates are positively cor-
related with stand dynamic rates (Duque et al.
2015). However, the relationship between forest
stand dynamic rates and altitude, as a surrogate
of temperature, is not well documented. Nor are
the relationships of rates to factors other than
temperature.

Plausible hypotheses about dynamic rates in
tropical mountain rain forests can be derived
from knowledge of latitudinal patterns of ecolog-
ical processes in forests. Globally, there is strong
support for a negative relationship between lati-
tude and forest net primary productivity, in
models that besides latitude include the length of
a growing season, mean annual temperature
(MAT), mean annual precipitation, and mean
growing season temperature and precipitation
(Gillman et al. 2015, Chu et al. 2016). Inferred
declines in productivity with altitude, therefore
temperature, in tropical mountain rain forests
(Malhi et al. 2010) may involve several factors
reviewed by Malhi et al. (2017) and Muller-
Landau et al. (2021). As water availability is not
limiting in these forests (Malhi et al. 2010, Clark
et al. 2015), these factors include declining photo-
synthetic rates and changes in carbon use effi-
ciency. Positive correlations between altitude and
belowground allocation of net primary produc-
tivity have been observed in some studies (e.g.,
Leuschner et al. 2007). The factor most strongly
supported by a study in the Andean mountain
rain forest was declining gross primary produc-
tivity (Malhi et al. 2017). Notably, however, in
some places, AGB on long altitudinal gradients
peaks in montane rain forests (Venter et al. 2017).
This may occur because specific combinations of
climatic variables—high water availability, mod-
erate temperatures, and small intra-annual tem-
perature variations—and natural disturbance
regimes favor the development of very large
trees (Keith et al. 2009, Venter et al. 2017).
Indeed, basal area peaks in old-growth montane
rain forests at altitudes >2000 m asl on our Costa
Rican gradient (Muñoz Mazón et al. 2020) as it
does at 2800 m on another Costa Rican Cordillera
(Heaney and Proctor 1990, Clark et al. 2015).

Phylogenetic and biogeographical factors may
also play a role: Culmsee et al. (2010) found that
the dominance of Fagaceae species—in the case
of Central America, Quercus spp.—is also associ-
ated with high AGB and basal area in high-
elevation tropical rain forests (see also Whitmore
1984). Finally, litter decomposition rates decline
with altitude on our gradient (Esquivel et al.
2020). This slowdown of process rates, if demon-
strated at the forest stand level, may be associ-
ated with reduced mortality rates and long basal
area residence times (Clark et al. 2015).

But do stand dynamic rates in tropical moun-
tain rain forests decline with altitudes such as
NPP and decomposition rates? What factors other
than altitude drive dynamic rates? These are key
questions because climate-driven changes in for-
est ecosystem functional properties, structure,
and composition (Feeley et al. 2013, Duque et al.
2015) are all in some way linked to the underlying
stand dynamic rates: first, of recruitment and
mortality of individuals of the tree species that
make up the stand, and second, of stand growth,
which can be estimated in terms of increments of
AGB or measured in terms of basal area incre-
ments. It is well known that the composition and
taxonomic diversity of rain forest stands change
markedly over the long altitudinal gradients that
characterize the mountain ranges of Central and
South America (Tello et al. 2015, Veintimilla et al.
2019). But the ways in which forest stand dynam-
ics vary over these gradients have only recently
come to the attention of researchers. On a rain
forest transect in Costa Rica, Clark et al. (2015)
found that individual and basal area turnover
rates decreased with altitude, while Báez et al.
(2015) found declines in mortality and recruit-
ment rates with altitude across north Andean
sites under a wide range of precipitation regimes.
Net increases of aboveground carbon predomi-
nated between 1991 and 2017 in forests across an
Andean plot network covering a 500–3500 m asl
altitudinal range (Duque et al. 2021), suggesting
that these forests are currently acting as strong
carbon sinks. Aboveground carbon dynamics
were not related to altitude in that study,
however.

In tropical American lowland rain forest, the
possible effect of climatic and non-climatic
drivers on stand dynamic rates is relatively
well documented. Tree mortality rates are
substantially higher than in temperate or boreal
forests but are increasing due to climate variabil-
ity in all these biomes, with a major effect on
aboveground carbon storage (McDowell et al.
2018). In lowland Neotropical forests, biomass
productivity and stocks are positively related to
climatic water availability (Poorter et al. 2015)
and are well predicted by community-weighted
mean values of functional traits (Finegan et al.
2015, Poorter et al. 2015). Yet, while these tropical
lowland studies illustrate the important relation-
ship of climate and forest functional properties to
forest stand growth, they cover only short tem-
perature gradients and in terms of climate pri-
marily illustrate precipitation effects on stand
dynamics.

Temperature changes markedly over short geо-
graphical distances on tropical altitudinal gradi-
ents, often under quite uniform water availability
regimes, thus permitting testing of hypotheses
about temperature effects on forest ecological pro-
cesses (Malhi et al. 2010, Clark et al. 2015). How-
ever, although community-weighted mean leaf
trait values can also vary strongly and predictably
over altitudinal gradients in tropical mountain
rain forests (Asner et al. 2015), it is not known
whether they are correlated with ecological pro-
cess rates as in lowland forests. Finally, strong
correlations between climate and other environ-
mental factors, especially soil, continue to repre-
sent a major challenge to understanding the
response of forest vegetation to altitude (Grubb
1977, Malhi et al. 2010, Asner et al. 2015).

Here, we explore the variation of rates of
recruitment, basal area growth, and mortality of
tropical rain forests over a long altitudinal gradi-
ent in the Costa Rican tropical mountain rain for-
est. We ask how this variation is associated with
altitude (as a temperature surrogate), forest func-
tional properties, and other predictors. Our data
set includes five censuses of individuals ≥10 cm
dbh carried out over a seven-year period (2012–
2019) in 29 permanent sample plots of 0.25 ha.
We characterize forest functional properties
using community-weighted mean values of func-
tional traits that are expected to be correlated
with stand dynamic rates: specific leaf area
(SLA), with a hypothesized positive correlation,
and wood specific gravity (WSG), with a hypoth-
esized negative correlation (cf. Unger et al. 2012,
Finegan et al. 2015, Poorter et al. 2015). Leaf-level

SLA tends to decrease with altitude in a tropical
mountain rain forest, perhaps representing
increased leaf conservatism due to decreasing
temperatures and solar radiation (Grubb 1977,
Asner et al. 2015), which would be linked to
declining photosynthetic rates (Malhi et al. 2017).
Altitudinal trends of wood specific gravity
(WSG), on the contrary, are not well known.

To determine stand dynamic rates, we mea-
sured a total of 4008 trees belonging to 450 spe-
cies over the seven-year study period. We
measured community-weighted mean (CWM)
functional trait values for a total of 162 dominant
tree species, selected on the basis of their contri-
bution to the total stand basal area.

Our main hypothesis was that rates of recruit-
ment, basal area growth, and mortality decrease
with altitude, therefore temperature, over the
gradient. Given the expected variation of CWM
traits over the gradient, complementary hypothe-
ses were that stand dynamic rates show a nega-
tive relationship to CWM WSG and a positive
relationship to CWM SLA.

METHODS

Study area and permanent sample plots

This study was conducted in an old-growth
forest on the Caribbean slope of the Cordillera
de Talamanca, Costa Rica (plot locations are
shown in Appendix S1: Fig. S1). The altitudinal
gradient sampled goes from 440 m asl in the
north to 2810 m asl in the south close to the
continental divide. We sampled in four Hol-
dridge life zones (Holdridge 1967): tropical wet
forest, and premontane, lower montane and
montane rain forests. Water availability is not a
limiting factor in these forest ecosystems, in
which annual precipitation is greater than
potential evapotranspiration (Holdridge 1967).
Mean annual temperatures from WorldClim cli-
mate surfaces (https://www.worldclim.org/) range from 24.4°C at 440 m asl to ca. 11°C at 2950 m asl. WorldClim mean annual rainfall ranges from 2500 mm at 2810 m asl to 4146 mm at 1635 m asl in Tapantí National Park. Frost can be frequent during January–April in the montane rain forest (personal observations).

Much of the area is underlain by tertiary volca-
nic rock, though there are patches of intrusive
rock of the same geological age, as well as
quaternary glacial sediments in the highlands (Chinchilla et al. 2011). Soils are mainly Ultisols at lower elevations and Inceptisols at higher (Veintimilla et al. 2019). Principally in the montane zone, Andepts have developed in areas covered by ash from the active volcanoes of the Central Volcanic Cordillera of Costa Rica (Chinchilla et al. 2011) and possibly also from Barú Volcano, in the Panamanian sector of the Cordillera (Anchukaitis and Horn 2005).

The Talamanca Cordillera has experienced substantial climatic and possibly also anthropogenic change during the Pleistocene and Holocene periods, and Holocene montane and lowland vegetation became established between 9000 and 8000 B.P. (Islebe and Hooghiemstra 1997, Piperno and Jones 2003). Humans have probably been present in our study area since 7000–4000 ¹⁴C yr B.P. (Anchukaitis and Horn 2005).

For individuals ≥10 cm dbh, forest composition was characterized by Veintimilla et al. (2019) as a lowland zone (tropical wet forest and pre-montane rain forest, 440–1120 m asl), a transitional zone at 1400–1600 m asl (lower montane rain forest), and the Fagaceae (Quercus)-dominated montane rain forest at altitudes >2100 m asl. Alpha diversity on this gradient has a strong negative relationship to altitude (Veintimilla et al. 2019) as do litter decomposition rates (Esquivel et al. 2020). Stand basal area, however, increases linearly with altitude to approach 50 m²/ha in montane forests (Muñoz Mazón et al. 2020).

We analyzed data for individuals ≥ 10 cm dbh from 29 permanent sample plots of 0.25 ha distributed along the altitudinal gradient. The plots are separated from each other by a minimum distance of 300 m. All the plots were measured five times over a seven-year period, 2012–2019. To set up plots, homogeneous areas of primary forests located on hillsides without evidence of recent human intervention were entered. Plots were positioned by walking a transect from the access point in such areas until a site meeting the following criteria was reached: We avoided recent large tree fall gaps and steep slopes, to reduce possible slope effects on the testing of our main hypotheses: median slope of plots measured with a clinometer was 25°, with a minimum of 15° and a maximum of 36°. Understory bamboo (Chusquea spp.) is a characteristic element of

montane rain forest (Kappelle and Brown 2001) and was not taken into account in plot location. Nor were large trees (>60 cm dbh) that are found throughout the gradient. Finally, we maintained a distance >50 m from water bodies.

We measured stem diameter of all trees, palms, and tree ferns ≥10 cm diameter using a metal tape. Stem diameters were measured at breast height (dbh, 1.3 m) or 20 cm above buttresses or deformations. Of the total of 4008 trees evaluated, 82 (2.04%) had two or three stems ≥10 cm dbh. These multiple-stemmed trees were treated as single individuals for mortality and recruitment rate calculations. For basal area increments, the increment of each stem was determined separately. We excluded palms and tree ferns from the analysis of stand dynamics. All individuals were identified as species using procedures described by Veintimilla et al. (2019), who present the full list of species and their distributions across the four life zones (their Appendix 4). Nomenclature is that of the Missouri Botanical Garden (https://www.tropicos.org/). In Appendix S1: Table S1, we provide the response variables analyzed in this study.

### Stand turnover and basal area increment

We calculated mortality rates *m* for each plot following Sheil et al. (1995):

$$m = \left[ 1 - \left( \frac{N_s}{N_0} \right)^{1/t} \right] \times 100 \quad (1)$$

where *m* is the annual percentage mortality, $N_0$ is the number of individuals present at the beginning of the measurement period, $N_s$ is the initial number of individuals minus the number of individuals dying during the 2012–2019 period *M* ($N_s = N_0 - M$), and *t* is the time in years.

The recruitment rate *r* per plot was calculated following Sheil et al. (2000) as follows:

$$r = \left[ 1 - \left( 1 - \frac{R}{N_t} \right)^{1/t} \right] \times 100 \quad (2)$$

where *r* is the recruitment rate expressed as an annual percentage, *R* is the total number of recruits, $N_t$ is the final number of individuals, and *t* is the time interval in years.

For each plot, we calculated gross periodic mean annual increments (ΔG<sub>gross</sub>) of basal area,
in m²·ha⁻¹·yr⁻¹, for the trees that survived the seven-year measurement period, a total of 3209 for the whole data set. Net annual basal area increment (ΔGnet) was calculated for the seven-year period as the annualized difference between initial and final total basal areas, therefore taking into account recruits and their growth, growth of survivors, and mortality.

## Weighted mean trait values and soil variables

We measured functional traits for the species that made up 80% of basal area ≥10 cm dbh in at least one plot; a total of 162 species distributed across the 29 plots. The mean number of species sampled for traits per 0.25-ha permanent sample plot was 17.25 in tropical wet forest, 8.25 in pre-montane rain forest, 10.5 in lower montane rain forest, and 1.3 in montane rain forest. We used well-known procedures (Pérez-Harguindeguy et al. 2013) for measuring the leaf trait specific leaf area (SLA, mm²/mg), leaf concentration of phosphorus (P, mg/g), and nitrogen (N, mg/g). We calculated leaf N/P ratio from these data. For the measurement of leaf traits, we sampled five trees per species. In the field, branches with mature foliage fully exposed to sunlight were selected and cut from the canopy. Samples were transported to the laboratory in a cooler, and five leaves from each tree sampled, free from herbivore damage and evidence of pathogens, were selected for measurements. The key stem trait, wood specific gravity (WSG, unitless), was measured from cores taken using a stem borer following Williamson and Wiemann (2010).

Community-weighted mean (CWM) trait values were estimated for each trait separately for the first measurement of each plot using Fdistversity software (Casanoves et al. 2011). We used the basal area as the weighting variable. The mean number of species per plot used to calculate CWM trait values declined from over 20 in tropical wet forest to 15 in lower montane rain forest and 3.5 in montane rain forest (see Appendix S1: Table S1). In three montane plots with a single species, *Quercus bumelioides*, making up ≥80% of the basal area, the CWM was set as the trait value for this species. We used soil data from the same sample plots measured to 30-cm soil depth by Veintimilla et al. (2019).

Physical and chemical analysis of soil was performed as described by Veintimilla et al. (2019),

who provide summary statistics of variables measured. Soil texture (percent of sand, clay, and silt) was obtained by the Bouyoucos method. Total acidity, Ca, and Mg extractions were obtained in 1 M potassium chloride (KCl). Extractable K, P, Zn, Cu, Mn, and Fe were obtained by the modified Olsen extraction method with a 0.5 N sodium bicarbonate (NaHCO₃) solution at a pH 8.5. The percentages of C and N were determined by the autoanalyzer of C/N by dry combustion.

## Statistical analysis

To test our hypotheses, we developed generalized additive models (GAMs) using the “gam” function of the “mgcv” library in R. Besides the main independent variable, altitude, and the CWM traits, we used initial basal area, soil variables, and slope as predictors in models. To select the best GAMs, we evaluated models with >4 effective degrees of freedom, as well as smoothed graphs (Zuur et al. 2009, Wood 2017). None of the models we selected included initial basal area, CWM N, CWM P, CWM N/P, or soil variables. Plot slope was only significant in one model, as a predictor of ΔGnet (R² adj: 0.12, *P* = 0.03), and we did not select this model. For these reasons, we do not discuss these predictor variables further.

## RESULTS

During the period from 2012 to 2019, the annual mortality rate *m* varied among plots between 0.56 and 5.17% yr⁻¹. Supporting our main hypothesis, the overall trend was a nonlinear decrease in mortality rate with increasing altitude, largely leveraged by low rates in montane forests (GAM, R² adj: 0.44, *P* = 7.34e-06; Fig. 1a). Recruitment rates also varied widely, in the range from 0.42 to 3.31% yr⁻¹, but they showed no significant bivariate relationship to altitude. However, a GAM recruitment rate in relation to altitude and CWM SLA was highly significant (R² adj: 0.30, *P* = 7.34e-06; Fig. 1b, c). Both these predictors had significant negative relationships to recruitment rates in this model, supporting our main hypothesis but not supporting our hypothesis of a positive relationship between dynamic rates and SLA. CWM SLA declines significantly with altitude (Appendix S2: Fig. S1a).
<figure><img src="image_4.png" /><figcaption>Fig. 1. Relationships of annual rates of mortality (m)</figcaption></figure>

(Fig. 1. *Continued*)

and recruitment (r) to altitude and community-
weighted mean (CWM) traits. (a) m-altitude, R² adj: 0.44, P = 0.00023; (b, c) r-altitude and CWM specific
leaf area (SLA) from model including both these pre-
dictors. Model R² adj: 0.30, P = 7.34e-06; altitude, F =
7.23, P = 0.008; CWM SLA, F = 4.64, P = 0.016. Curves
are fitted splines from GAMs, and shaded areas repre-
sent the 95% confidence limits of the spline.

Results for basal area increments did not sup-
port our main hypothesis. AGgross showed a
hump-shaped relationship to altitude (GAM: R²
adj: 0.31, P = 0.0019; Fig. 2a). AGgross tended to be
highest in the altitudinal range of 1100–1660 m
asl and to decrease in tropical wet forest and
montane rain forest at the two extremes of the
altitudinal gradient. This relationship of AGgross
to altitude can possibly be interpreted in terms of
its bivariate negative relationship to CWM WSG
(R² adj = 0.19, P = 0.0096) together with the
valley-shaped relationship of CWM WSG to alti-
tude (R² adj = 0.44, P = 0002; Fig. 2b, c)—AGgross
tended to be highest at middle elevations where
CWM WSG was lowest. CWM WSG was not,
however, significant as a predictor of AGgross in
models that also included altitude.

Also contrary to our main hypothesis, ΔGnet
showed a non-linear *positive* relationship to alti-
tude in a GAM with CWM WSG, with which its
relationship was negative, as in the case of
ΔGgross (R² adj: 0.36, P = 0.0011; Fig. 3a, b). ΔGnet
showed negative values in ten of the 29 plots,
all but one of them located below 1500 m asl,
where basal area lost due to mortality was
greater than gains from growth of survivors and
recruitment.

DISCUSSION

We tested the main hypothesis that stand
dynamic rates in mountain rain forests decrease
with altitude. This hypothesis was supported for
mortality rates and recruitment rates, though the
best model for recruitment included CWM SLA.
It was not supported for stand growth. Gross
basal area increments ΔGgross had a hump-
shaped relationship to altitude, while net basal
area increment ΔGnet *increased* with altitude in a
best GAM that included CWM WSG. We found
<figure><img src="image_5.png" /><figcaption>Fig. 2. (a) Relationship of gross basal area increment</figcaption></figure>

(Fig. 2. Continued)

(growth of survivors + basal area of recruits) to (a) altitude: R² adj: 0.31, *P* = 0.0019 and (b) CWM wood specific gravity (WSG), R² adj = 0.19, *P* = 0.0096; and (c) the relationship of CWM WSG to altitude, R² adj = 0.44, *P* = 0.0002. Curves are fitted splines from GAMs, and shaded areas represent the 95% confidence limits of the spline.

net loss of basal area in ten plots, mainly in the lowland wet and premontane rain forests. Overall, stand dynamic rates in these forests show a range of relationships to altitude and therefore temperature, while they also respond to two key forest functional properties, CWM SLA and CWM WSG. After discussing these results, we evaluate their implications regarding the response of tropical mountain rain forest to rising temperatures under climate change.

## Mortality and recruitment rates

Whole-stand exponential annual mortality rates have been documented in the range from 0.6% to 3% in old-growth lowland tropical forests with “gap” disturbance regimes (Swaine et al. 1987, Lugo and Scatena 1996, Finegan et al. 2001, Lewis et al. 2004). In our study using the improved equation of Sheil et al. (1995), mortality rates were >3.0% in eight plots distributed across tropical wet forest, premontane rain forest, and lower montane rain forest, with a maximum value of 5.2%. However, they declined to 0.56–1.6% at altitudes >2000 m asl. Our sampling protocol was designed to reduce the possibility that steep slopes affect mortality rates (see Methods: statistical analysis). Intense rainfall, high winds, and lightning during the period of our study, associated, for example, with hurricanes Otto (2016) and Nate (2017) and the 2014–2016 el Niño phenomenon (Brenes-Rodriguez et al. 2017), may be the most likely causes of tree mortality in the low and middle elevations of our gradient (cf. Yano-viak et al. 2020). It is notable that although the number of trees ≥60 cm dbh increases with elevation in our plots (Appendix S2: Fig. S1b), seven of nine tree deaths in this size range occurred in plots at <1120 m asl (10.3% of all trees ≥60 cm dbh in this altitudinal range). In contrast, in plots located >2000 m asl only two of 95 trees ≥60 dbh (2.1%) died over the seven years.
<figure><img src="image_6.png" /><figcaption>Fig. 3. Relationships between net basal area increment and (a) altitude, (b) CWM wood specific gravity (WSG), from model including both predictors. Model R² adj: 0.36, *P* = 0.001; altitude, *F* = 15.1, *P* = 0.0006; CWM WSG, *F* = 6.05, *P* = 0.02. Curves are fitted splines from GAMs, and shaded areas represent the 95% confidence limits of the spline.</figcaption></figure>

The decrease in recruitment rates with altitude in a model with CWM SLA gives some support to our main hypothesis and together with the result for mortality rates suggests that turnover rates of individuals decrease as temperature decreases with altitude. The role of CWM SLA in

the determination of recruitment rates requires further work.

## Basal area increments

Basal area increments were best explained by GAMs including altitude and CWM WSG. We measured ΔG_gross as the increments of trees that survived the whole study period. Values overall were in a similar range to those described by Clark et al. (2015) who, however, reported no clear relationship to altitude. The hump-shaped relationship of ΔG_gross to altitude in our study is probably best explained in terms of the contrary, valley-shaped altitudinal pattern of CWM WSG. Stem diameter growth rates increase with decreasing WSG in tropical trees (Hérault et al. 2011), and for lowland forests, negative relationships of CWM WSG to both net and gross biomass increments have been shown by Finegan et al. (2015) and Poorter et al. (2015). ΔG_gross on our gradient is negatively related to CWM WSG, possibly because of the high WSG of dominant species in both tropical wet forest and montane rain forest, and the lower values of dominants in the altitudinal range of 1000–1700 m asl (premontane rain forest and lower montane rain forest; see Appendix 1: Table S2), where ΔG_gross was highest (Appendix S1: Table S1). Although no soil variables were included in our best models, we are investigating the possibility that higher soil fertility over the 1000–1700 m asl altitudinal range contributes to pattern in basal area increment.

ΔG_net was quite well explained by altitude in our model, with a non-linear positive relationship, and CWM WSG, with the expected negative relationship. The relationship of ΔG_net to altitude is the outcome of two factors: first, the decline with altitude of both mortality rates and the total basal area lost due to mortality (Appendix S2: Fig. S1c); and second, the hump-shaped relationship to altitude of ΔG_gross. The improvement of model fit by the incorporation of CWM WSG is probably due to the relationship of this functional property to the higher ΔG_gross in middle-elevation premontane and lower montane rain forest.

## Final comments: a complex forest landscape response to climate change

In the absence of changes in water availability, rising temperatures are expected to bring upslope
species migrations, thermophilization, and
changes in carbon fluxes in tropical mountain rain
forests (Malhi et al. 2017, Feeley et al. 2020). Cli-
mate change is expected to bring increased pre-
cipitation in our study area (Delgado et al. 2016).
What are the implications of our results in relation
to expected consequences of rising temperatures?
We propose the following. First, our study sug-
gests that not all rain forest properties and
processes are controlled by temperature on altitu-
dinal gradients; not all stand dynamic rates
decrease with decreasing temperature. Therefore,
understanding and modeling of forest response to
climate change must take into account additional
predictors. The inclusion of CWM response traits
(Pérez-Harguindeguy et al. 2013) in hypothesis
testing and modeling is recommendable, and
increased understanding of the factors that deter-
mine tree species distributions on altitudinal gra-
dients is necessary: On our gradient, for example,
it is likely that disturbance extends the altitudinal
ranges of tree species (Muñoz Mazón et al. 2019).
The climate responses of montane forests domi-
nated by Fagaceae particularly require further
study: Species of this family are distributed over
broad ranges of altitude and temperature in both
Central American (Kappelle and Brown 2001,
Veintimilla et al. 2019) and Asian (Culmsee et al.
2010) mountain rain forests. This suggests that
montane forests dominated by these species are
resilient to rising temperatures, in line with the
very low contemporary mortality rates and robust
net basal area increments they showed in our
study.

Finally, we recommend that forest change scenarios go beyond thermophilization to include responses to storms and lightning (cf. Yanoviak et al. 2020). We agree with Clark et al. (2015) and Fadrique et al. (2018) in not expecting generality on comparing tropical altitudinal transects. Ecological knowledge of TMRF covering a range of pre-warming response and effect scenarios must urgently be included in the evaluation of risk and uncertainty in climate change (Kunreuther et al. 2014).

ACKNOWLEDGEMENTS

This work was funded by the Inter-American Devel-
opment Bank's Sustainable Energy and Climate
Change Initiative, the National Institute of Forest

Sciences (NIFOS, Republic of Korea), and Scholarship
A-1022018 awarded to Alba Lorena Hernández by the
Colombian Corporation for Research in Agriculture
(AGROSAVIA) and CATIE. We thank the staff of Costa
Rica's National System of Conservation Areas
(SINAC), Barbilla and Tapantí National Parks, Rio
Macho Forest Reserve, and the Esperanza de Atirro
and El Copal Private Reserves, for their support.

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Additional Supporting Information may be found online at: http://onlinelibrary.wiley.com/doi/10.1002/ecs2.3867/full