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Altitudinal assisted migration of Mexican pines as an adaptation to climate change D. CASTELLANOS-ACUNÃ,1 R. LINDIG-CISNEROS,2,3

AND

C. SAÉNZ-ROMERO1,4,

1

Instituto de Investigaciones Agropecuarias y Forestales, Universidad Michoacana de San Nicola´s de Hidalgo, Morelia, Michoacań 58330 Me´xico 2 Laboratorio de Ecologıá de Restauracioń, Centro de Investigaciones en Ecosistemas, Universidad Nacional Autońoma de Me´xico, Morelia, Michoacań 58091 Me´xico Citation: Castellanos-Acunã, D., R. Lindig-Cisneros, and C. Saénz-Romero. 2015. Altitudinal assisted migration of Mexican pines as an adaptation to climate change. Ecosphere 6(1):2. http://dx.doi.org/10.1890/ES14-00375.1

Abstract. Since shifts in altitudinal range are expected in response to climate change, we explored the effect on survivorship and growth of moving populations of three Mexican pine species (Pinus devoniana, P. leiophylla and P. pseudostrobus) to higher altitude, aiming to realign the populations to projected future climates in an experimental assisted migration. Twelve populations were collected across an altitudinal gradient (1650–2520 m above sea level [asl]) in a mountainous zone in the central-west region of the Mexican Trans-Volcanic Belt, and were planted in common garden tests at three forest sites of different altitudes (low: 2110, medium: 2422 and upper: 2746 m asl). Climate was estimated using a spline climatic model at the seed source and test sites and also measured using in situ data loggers. Survivorship and seedling height were evaluated in the field during the second and third growing seasons. Results were analyzed using mixed models to include the effect of climatic transfer distances (difference in climate between seed source and test site). Significant differences were found in seedling growth among Pinus devoniana, P. pseudostrobus and P. leiophylla, and among populations within the former two species. These were associated primarily with climatic transfer distances of extreme temperatures (minimum temperature in the coldest month and mean temperature in the warmest month). There was a significant decrease in growth in P. devoniana when the transfer exceeded 650 m of upward altitudinal shift or a reduction of 1.58C with transfer to colder sites. There was also a decrease of growth in P. pseudostrobus when transfer exceeded 400 m of upward altitudinal shift or 1.58C, with a significant decrease in survivorship. Pinus leiophylla, however, exhibited similar growth at all altitudes tested, probably due to phenotypic plasticity. Although further research is required with field tests using commercial spacing and trees of older ages, the results suggest that an assisted upwards migration of 300 m in altitude, in order to approach a realignment of the populations to the climate projected for the decade centered around the year 2030, appears to be a viable strategy with which to accommodate the effects of climate change. Key words: assisted migration; climatic change; Pinus devoniana; Pinus leiophylla; Pinus pseudostrobus; population realignment; upwards altitudinal shift. Received 10 October 2014; accepted 22 October 2014; final version received 2 December 2014; published 14 January 2015. Corresponding Editor: J. Weltzin. Copyright: Ó 2015 Castellanos-Acunã et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. http://creativecommons.org/licenses/by/3.0/ 3

Present address: University of California Institute for Mexico and the United States (UC MEXUS), Riverside, California

92521-0147 USA. 4

Present address: Institut National de la Recherche Agronomique (INRA), Unite´ Mixte de Recherche 1202 Biodiversite´ Ge`nes & Communaute´s (UMR 1202 BIOGECO), F-33610 Cestas, France & Universite´ de Bordeaux, UMR 1202 BIOGECO, F-33615 Pessac, France. E-mail: [email protected]

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January 2015 v Volume 6(1) v Article 2

˜ A ET AL. CASTELLANOS-ACUN

species are naturally distributed, overlapping across altitudinal gradients (Saeńz-Romero et al. 2010). The dominant species, from the upper (2900 m above sea level [asl]) to lower (1650 m asl) elevations are: Pinus pseudostrobus, P. leiophylla, and P. devoniana (also known as P. michoacana) (Medina-Garcıá et al. 2000), where P. pseudostrobus is the pine species of highest economic value (Lo´pez-Upton 2002). We collected seeds from natural stands and planted them in common garden tests at different altitudes. There is an underlying assumption that common garden test results at early ages can be a good predictor of the growth at later ages in field sites under optimum conditions (Rehfeldt 1984), as demonstrated for P. sylvestris, comparing 2year-old seedling heights to 13-year-old tree height in several field sites (Rehfeldt et al. 2004). The use of transfer distances to specifically understand the effects of climate change, by planting a number of populations in sites with different environmental conditions and characterizing their response, is a recent development and has proved useful in determining the adaptive limits of tree populations (Ma´tya´s 1994, 1996, Schmidtling 1994, Carter 1996, Rehfeldt et al. 1999, Rehfeldt et al. 2003, Tchebakova et al. 2005, Wang et al. 2006, Thomson and Parker 2008, Thomson et al. 2009, Schreiber et al. 2013). Under current climate change trends, it is increasingly relevant to establish common garden tests, including field experiments located outside the natural distribution of the species, in order to model growth responses in contrasting environments, imitating the effects of climatic change in the warmer sites and, at the opposite extreme, measuring the short term effects on colder environments when genotypes migrate to higher altitudes or pole-ward latitudes, anticipating climate change (StClair et al. 2013, Richardson et al. 2014).

INTRODUCTION Climate change represents a new challenge for reforestation and ecological restoration programs. Matching genotypes to the environments to which they are adapted becomes a complex task when the location of an appropriate climate is a moving target (Lavendel 2003, Harris et al. 2005). It has been projected in Mexico that, by the decade centered on the year 2030, there will be an increase in mean annual temperature of 1.58C, and a decrease of 7% in precipitation, compared to the average of the period 1961–1990 (Saénz-Romero et al. 2010). These changes will cause a gradual uncoupling between forest populations and the climate to which they are adapted. As has already been observed in various parts of the world (Breshears et al. 2005, Jump et al. 2006, Pen˜uelas et al. 2007, Rehfeldt et al. 2009, Allen et al. 2010, Ma´tya´s 2010), this uncoupling will induce a gradual decay of natural forest populations, particularly at the lower altitudinal limits (or at the southern edge of the Northern Hemisphere) of their natural distribution. This decay will initially cause a decrease in productivity and then produce severe deterioration in the forest cover, with serious negative ecological and economic consequences. Since there is no evidence at all of a substantial worldwide reduction of greenhouse-effect gas emissions (Hansen et al. 2012), it would be needed a human-assisted realignment of forest tree populations to the climate to which they are adapted (called assisted migration, assisted colonization, assisted relocation or facilitated migration) (Ledig and Kitzmiller 1992, Rehfeldt et al. 2002, Tchebakova et al. 2005, Aitken et al. 2008, Hewitt et al. 2011). In general, in mountain regions assisted migration requires an upward shift in altitude (Jump et al. 2009, Saénz-Romero et al. 2010, Rehfeldt et al. 2012), because elevation is mainly a surrogate variable for temperature (Rehfeldt et al. 1999, Loya-Rebollar et al. 2013). In this study, we aimed to answer the following question: what is the effect on survivorship and growth of moving forest tree populations to higher altitudes? To answer this question, we chose a mountainous region in the central-west part of the Mexican Trans-Volcanic Belt where several pine v www.esajournals.org

METHODS Seed collection Open-pollinated seeds from 11 randomly selected trees from four populations of each of the species P. pseudostrobus, P. leiophylla, and P. devoniana were collected along an altitudinal transect, from 2500 m asl -near the upper 2


˜ A ET AL. CASTELLANOS-ACUN Table 1. Collection sites along an altitudinal gradient of Pinus devoniana, P. leiophylla and P. pseudostrobus populations at Nuevo San Juan Parangaricutiro, Michoacań, central-western Me´xico. Collection site

Latitude (N)

Longitude (W)

Altitude (m)

Species collected

1 2

19827 0 34.400 19826 0 50.100

102811 0 43.600 102811 0 00.500

2520 2422

3

19826 0 24.600

102810 0 29.600

2310

4

0

19826 05.1

5 6 7

P. pseudostrobus (M) P. pseudostrobus (ML), P. leiophylla (UL) P. pseudostrobus (L) P. leiophylla (M) P. pseudostrobus (LL) P. leiophylla (M) P. devoniana (U)à P. leiophylla (LL) P. devoniana (M) P. devoniana (M) P. devoniana (LL)

00

0

00

2217

19825 0 42.100

102809 0 34.600

2110

19825 0 28.900 19823 0 03.900

102808 0 57.800 102804 0 47.400

2034 1650

102810 08.3

Approximate location of the sampled population regarding its natural altitudinal range distribution is indicated in parenthesis: UL ¼ upper limit, U ¼ upper, M ¼ medium, ML ¼ Middle-low, L ¼ lower, LL ¼ lower limit. à Actually we collected one population more of P. devoniana at higher altitude, that represent the true altitudinal upper limit (at 2310 m), but their seed production was so poor that we did not have enough seedlings to adequately represent the population on the three field test sites.

distribution limit of P. leiophylla and constituting the middle-altitudinal distribution of P. pseudostrobus-, down to an altitude of 1650 m asl, which is the extreme lowest limit of P. devoniana (Table 1; it should be noted that it was not possible to find all three species at all altitudes sampled). All the sites had the same aspect (southeast). The sampled populations were distributed at altitudinal intervals of 100 m, except for the P. devoniana populations, which were sampled at 2034 and 1650 m asl, where the natural forest has been almost completely removed in the region to establish avocado (Persea sp.) orchards. In this study, the trees represented by these samples are termed populations, while the location of a population is known as the provenance. The sampling design aimed to capture as much as possible of the among-population variation of Pinus devoniana along the altitudinal gradient in the studied region. In case of an eventual upward assisted migration, P. devoniana would have to replace the decaying populations at the lower altitudinal limit of P. pseudostrobus (at approximately 2300 m asl). Since the year 2010, numerous individuals of these low-altitude populations have already exhibited signs of decay, apparently due to climate change related stresses; in sites with shallow soils and southern aspects, unusual dry season heat waves have caused severe defoliation, accumulation of dead branches and death in some individuals (C. Saénz-Romero, personal observation). v www.esajournals.org

Nursery stage The identity of the parent trees was recorded for all seeds. Seeds were germinated in Petri dishes and seedlings maintained in a nursery shade house for six months in 380 cm2 pots (Plastics Beaver de Me´xico), at the Centro de Investigacioń en Ecosistemas, Universidad Nacional Autońoma de Me´xico, in Morelia, Michoacań state, Mexico. During this nursery stage, seedlings were arranged in a randomized complete block design, where the plots were 9seedling rows, and each seedling was randomly selected from among the 11 open-pollinated trees collected per population in order to obtain an equal representation of the half-sib families per population. We did not aim to evaluate amongfamily variation within population, but only to prevent bias produced by over or under-representation of families within the populations. For more details of the nursery stage see CastellanosAcunã et al. (2013).

Field tests At the beginning of the rainy season of 2011, seedlings from the three species and all the provenances were planted in common garden tests established in three field sites, at intervals of approximately 300 m asl: 2746 m asl (upper altitude site, Fig. 1; average slope 5%), 2422 m asl (medium altitude; average slope 3%) and 2110 m asl (lower altitude; average slope 1%) (Table 2). The 300-m step difference in altitude follows the suggested general guideline that in order to 3



Fig. 1. Common garden tests at the upper altitude site (2746 m; Table 2), located at the medium-upper altitude of the natural altitudinal range distribution of Pinus pseudostrobus, and outside the upper altitudinal limit of P. devoniana and P. leiophylla, Nuevo San Juan Parangaricutiro region, Michoacań state, central-west Mexico.

realign genotypes to the climate predicted to occur in the decade centered on the year 2030, an upwards shift in altitude of 300 m is required to compensate for the expected 1.58C increase in average temperature (average lapse rate in Mexican mountains is 0.58C per 100 m of altitudinal difference; Saénz-Romero et al. 2010). All sites had an eastern aspect. The upper altitude site explores the limits of an extreme upward assisted migration for P. devoniana (a transfer of nearly 1050 m in altitude for the population originated at the lowest altitude), meanwhile the site at nearly 2100 m (low altitude site) allows us to evaluate the growth response of P. pseudostrobus and P. leiophylla to a warmer and dryer environment (simulating the effects of the climate projected for the decade centered on the year 2030). v www.esajournals.org

Due to the fact that each field site has its own history of perturbation, ecological succession and management that may generate confounded effects, in addition to the main effect of altitude (which was our main field ‘‘treatment’’), the field common garden tests were conducted in wooden raised beds, imitating the infrastructure normally adopted in common garden tests in certain experimental forest stations (Fig. 1). Additionally, we ensured equal light conditions in all three field sites by manipulating the standing tree cover by removing some adult trees and pruning others. The three sites also had similar slope conditions. The wooden raised beds were 7.8 m long 3 1.5 m wide 3 0.4 m high (Fig. 1), and were filled with a mix (proportion 2:1) of Andosol forest soil and the upper organic layer of the same soil 4


˜ A ET AL. CASTELLANOS-ACUN Table 2. Location of field test sites for a species/provenance test along an altitudinal gradient at Nuevo San Juan Parangaricutiro, Michoacań, central-western Me´xico. Test site

Latitude (N)

Longitude (W)

Altitude (m)

Local name of the site

Upper Medium Low

19828 0 15.600 19826 0 50.100 19825 0 42.100

102810 0 40.800 102811 0 00.500 102809 0 34.600

2746 2422 2110

Cerro de Pario La Pila El Rosario

(approximately 20 cm of Andosol soil mixed with litter—mostly of oak leaves—in decomposition). The soil and the upper organic layer were extracted from a single pine-oak site near the middle altitude field site (La Pila, 2400 m of altitude; Table 2), homogenized, and used for filling the raised beds in all three field sites. A metal mesh was placed below the soil in each bed to prevent underground intrusion by gophers. The sites were also fenced off with barbed wire to prevent the access of cattle and deer. In each of the three sites (Table 2), seedlings of four populations of each of the three species (P. devoniana, P. leiophylla and P. pseudostrobus; Table 1) were placed in a randomized complete block design, featuring six blocks (two blocks per raised bed) and five seedlings per plot in a row. Each seedling of each population in each block was randomly selected from among the 11 openpollinated trees collected per population, again aiming to obtain an equal representation of the half-sib families per population, rather than aiming to evaluate among-family variation within populations. Seedlings were spaced at 0.3 m within plots 0.3 m apart. The first and the last plots of each wooden structure were flanked by a row of randomly selected seedlings to minimize potential edge effects. Populations of the same species were placed together (e.g., species as large plots and populations as small plots). The seedlings received no irrigation or fertilization.

seedling height across the sites was 35 cm, 69 cm and 86 cm for P. devoniana, P. leiophylla and P. pseudostrobus, respectively. We estimated the net increase in height (final seedling height initial seedling height), and relative growth [(net increase in height/initial seedling height) 3 100]. Estimating relative growth enabled the direct comparison of performance among species, considering the early stage growth habit of P. devoniana, which presented a moderate grass stage at the beginning of the experiment.

Climatic data In order to translate the elevation of the sites to climatic variables and then to climatic transfer distances (CTD ¼ climate at the test site climate at the seed source), as well as to interpret differences among populations as the result of an adaptive process to the environmental gradient, we estimated a series of climatic variables for each population (seed source) and test site (Table 3). Those climatic variables have been shown to be primary factors controlling the distribution of biomes and plant species (see Tuhkanen 1980, Rehfeldt et al. 2006, Rehfeldt et al. 2012). Climate estimates were obtained from spline climate surfaces fitted from monthly average temperatures (mean, maximum and minimum) and monthly precipitation data from numerous weather stations in what was considered the ‘‘contemporary climate,’’ i.e., the average for the period 1961–1990 (see Saénz-Romero et al. 2010). The spline climate model was interrogated using a website interface (http://forest.moscowfsl.wsu. edu/climate/; Crookston and Rehfeldt 2011). We assumed these climatic estimates to be a proxy of the climate that molded the adaptive process of each population at the site where they are naturally distributed (Leites et al. 2012b). In order to confirm the effect of the actual climate during the experiment, we recorded temperature hourly in the field using Hobo data

Field measurements Once established, we measured survival every month and seedling height at the beginning (6 months of age; in August, one month after planting in the field) and end of each of the following two growing seasons when the plants were two and three years old, respectively. Although this may seem a relatively young age, it is sufficient to show the growth potential in field-based common garden tests for these species at these latitudes. Average 3-year-old v www.esajournals.org

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˜ A ET AL. CASTELLANOS-ACUN Table 3. Estimated climatic variables for each population (seed source) and test site. Code

Unit

Definition

MAT MAP GSP DD5 MINDD0 MTCM MMIN MTWM MMAX SDAY FDAY FFP GSDD5 D100 SMRPB

8C mm mm 8C 8C 8C 8C 8C 8C day day days 8C day ratio

AAI

index

Mean annual temperature. Mean annual precipitation. Total precipitation in the growing season (April to September). Degree-days above 58C. Negative degree-days calculated from minimum temperature. Mean temperature in the coldest month. Mean minimum temperature in the coldest month. Mean temperature in the warmest month. Mean maximum temperature in the warmest month. Julian date of last spring frost. Julian date of first fall frost. Length of frost-free season (FDAY–SDAY). Degree-days above 58C in the frost-free season. Julian date on which DD5 sums to 100. Summer precipitation balance [SMRPB ¼ (July þ August þ September precipitation)/(April þ May þ June precipitation)]. Annual aridity index (AAI ¼ DD50.5/MAP).

loggers (Onset, model h08 001 02, USA), placing three loggers in each field site (one beside each wooden frame), 30 cm above ground, during the second year of the experiment only. The recorded temperatures allowed us to identify the most relevant temperature variables: MAT, DD5, MTCM, MMIN, MTWM, and MMAX (Table 3). We then estimated climatic transfer distances as the difference between the climate (only variables related to temperature, precipitation was not estimated) at the test site (recorded with the data loggers) and that at the seed source (estimated using the spline climate models).

partly account for the genetic differences among populations. By including a population level random effect, we provide structure for population level variation that is not explained by the climate at seed source (see Leites et al. 2012b). To identify the climatic variable that best describes the effect of climatic transfer distance on population performance, we screened each variable in turn in order to identify those that best fitted the data (using Akaike Information Criterion, AIC; lower values are better). We then ran the analysis once more, incorporating those climatic variables as more significant fixed effects (random effects were not subject to selection in the model), including quadratic terms and interactions. We removed nonsignificant terms in turn, rerunning the model after discarding each term, using P 0.25 as the threshold for removal (Verbeke and Molenberghs 1997). Finally, we selected the model with the lowest AIC value. In order to determine whether a specific random effect was significant, we performed a likelihood ratio test (Littell et al. 1996, Saenz-Romero et al. 2001). We performed this sequence initially with a combined analysis of the three species and then conducted separate analyses for each species. To determine which pattern of experimental climatic transfer distance or altitudinal transfer distance, considered as an assisted migration, follows the growth response of each species, we performed regression analyzes between

Statistical analysis We followed Leites et al. (2012b) in their approach of modeling plant response as a function of climate transfer distance, using a mixed effects model (SAS Institute 2004). With the fixed effects, we were able to test for the effect of climatic transfer distance (the difference between climate at the test site and at the seed source). With the random effects, we provided structure for potential sources of variation not explained by the fixed effects, and were also were able to accommodate the structure of the data related to experimental design: sites, species, populations, blocks, and their interaction. Thus, differences among populations were accounted for by the joint effect of population as a random effect and climate at seed source as a fixed effect. In other words, the fixed effects provide an observable difference between the populations, which is likely to v www.esajournals.org

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Fig. 2. Response in seedling survivorship (empty symbols denote 2-year-old seedlings; filled symbols denote 3year-old seedlings; data removed due to Chronartium sp. outbreak at the 2400 m site indicated as cross marks) to altitudinal movement of populations of Pinus devoniana (diamond symbols), P. leiophylla (triangle symbols) and P. pseudostrobus (circle symbols). Positive values of altitudinal transfer distance denotes movement towards higher altitude; more negative values denote movement to lower altitudes; zero values indicate populations growing as locals.

relative growth and climatic or elevation transfer distance (elevation transfer distance ¼ elevation of experimental site elevation of seed source). To determine if there are differences between species in terms of response to experimental transfer, we performed an analysis of covariance (ANCOVA), with transfer distance as the covariate (Crawley 2007). During the second year of the field experiment (third year of age in the seedlings), an unusually severe outbreak of Chronartium sp. occurred in an indigenous community forest nursery located nearby (800) m from our intermediate altitude (2400 m asl) field site, causing severe damage to numerous seedlings of P. devoniana and P. pseudostrobus, while P. leiophylla was not infected at all. We removed the infected species at this site only from the analysis. v www.esajournals.org

RESULTS Survival Across the three sites, two-year-old P. pseudostrobus seedlings presented an average of 99.7% survival, while P. devoniana and P. leiophylla presented 98% survival (Fig. 2). This represents an extraordinary and unexpectedly high survivorship. One year later, 3-year-old seedling survivorship had moderately decreased in all sites and for all species. Average survivorship across sites was 83.3%, 79.8% and 75.6% for P. leiophylla, P. pseudostrobus and P. devoniana, respectively (Fig. 2). There is a pattern of increased mortality in the 3-year-old P. pseudostrobus seedlings when provenances are moved to higher altitudes (quadratic regression: r2 ¼ 0.78, P ¼ 0.0230; Fig. 2), where mortality is more severe where the altitudinal 7


˜ A ET AL. CASTELLANOS-ACUN Table 4. Percent of contribution to total variance (%, only from random effects) and significance (P) for random and fixed effects for 2-year-old relative seedling growth (net seedling growth in height divided by initial seedling height) on a combined analysis for three pine species (Pinus devoniana, P.leiophylla and P.pseudostrobus) and four populations within each specie (collected along an altitudinal gradient), tested at three field sites at contrasting altitudes. Random effects

Fixed effects

Source of variation

%

P

Source

NDFà

DDF§

F

P

Site Species Population(Species) Block(Site) Species 3 Site Site 3 Population(Sp) Species 3 Block(Site) Pop. 3 Block(Site 3 Species) Error

1.0 15.2 0.0 5.7 0.0 0.0 12.0 4.9 61.2

1 0.0081 1 0.0455 1 1 0.0001 0.0046

TD_MMIN TD_MTWM TD_MTWM2 TD_MAT TD_SMRPB TD_SMRPB2

1 1 1 1 1 1

974 974 974 974 974 974

7.8 10.1 5.5 13.7 24.9 2.6

0.0053 0.0015 0.0188 0.0002 0.0001 0.1052

AIC}

6166

Climatic transfer distances (TD_): MMIN ¼ Mean minimum temperature in the coldest month, MTWM ¼ Mean temperature in the warmest month, MAT ¼ Mean annual temperature. Summer precipitation balance (July þ August þ September)/(April þ Mayþ June). à Numerator degree of freedom. § Denominator degree of freedom. } Akaike Information Criterion.

variance; P ¼ 0.0081), blocks nested in sites (P ¼ 0.0455) and for the interactions species 3 block (sites) (P , 0.0001) and population 3 block (sites) (P ¼ 0.0046). However, site and population random effects were not significant, probably because the climatic transfer distance fixed terms had already absorbed these effects (Table 4). We found essentially the same results in the 3year-old seedlings: The best model was that which used two climatic transfer distances (both related to temperature): TD_MTWM (P ¼ 0.0001) and TD_MAT (P ¼ 0.0009). Furthermore, when climatic transfer distances were estimated as the difference between the climate at seed source (estimated with the spline climatic models) and that of the test site (estimated in situ with the Hobo data loggers; differences coded as ‘‘TDHS_’’), we found the same results as for the 2-yearold seedlings: TDH-S_MTWM (P ¼ 0.0073) and TDH-S_MAT (P ¼ 0.0007).

movement exceeds 400 m (a provenance moved 450 m upwards had a survivorship of only 56%). Pinus devoniana shows a similar trend, although it was not statistically significant (r2 ¼ 0.52, P ¼ 0.1620; Fig. 2). For P. leiophylla, association with the altitude of origin is very weak and far from significant (r2 ¼ 0.32, P ¼ 0.1715).

Effect of climatic transfer distance on growth performance In the combined analysis (incorporating all three pine species in the same analysis) of relative growth in 2-year-old seedling height (increase in seedling height divided by initial height), we found that the best model (lowest AIC) was that which used a combination of four climatic transfer distances (climatic difference between the seed source and the test site, both climatic values estimated from the spline climatic models, coded as ‘‘TD_’’): mean minimum temperature in the coldest month (TD_MMIN), mean temperature in the warmest month (TD_MTWM), mean annual temperature (TD_MAT), and summer precipitation balance (TD_SMRPB): (July þ August þ September)/(April þ May þ June), as well as a quadratic term for TD_MTWM; all of these fixed effect terms were statistically significant (P , 0.02; Table 4). For the random effects, significant differences were found among species (accounting for 15% of the contribution to total v www.esajournals.org

Differences among populations: analysis per species To explore in more detail the variation among populations within each species, we conducted a mixed model analysis for each species separately. For P. devoniana, the optimum AIC (2041.7) for 2-year-old seedlings was obtained using a combination of two significant climatic transfer distances and their respective quadratic terms: 8



Fig. 3. Response in relative growth of 2-year-old seedlings to transfer distance of mean temperature of the warmest month (estimated as the difference between the temperature recorded in situ with Hobo data loggers and the temperature of the seed source using spline climatic models as a proxy, referred to in the text as TDH-S_MTWM). Positive values of climatic transfer distance denotes movement towards warmer sites; more negative values denotes movement to colder sites; zero values indicate populations growing as locals.

transfer distance of the minimum temperature in the coldest month (TD_MMIN, P , 0.0001; TD_MMIN2, P , 0.0026) and transfer distance of the summer precipitation balance (TD_SMRPB, P ¼ 0.0005; TD_SMRPB2, P ¼ 0.0138). For the random effects, we found differences between sites (P ¼ 0.0319) and blocks within sites (P ¼ 0.0151), although populations and the interactions site 3 population and populations 3 blocks nested in site were not significant. The relevance of the mean temperature of the warmest month (MTWM) was confirmed when climatic transfer distance was estimated using the temperature records taken in situ by data loggers (TDH-S_MTWM: P , 0.0001), and on analysis of the relative growth of the 3year-old seedlings (TD_MTWM: P , 0.0333). For 2-year-old P. leiophylla seedlings, we did not find differences among populations using any of the climatic transfer distances. In the random effects, we found differences only for blocks within sites (P , 0.0001) and the interaction population 3 block nested in site (P , 0.0001), but all of the other random effects were non-significant. A similar result was obtained for 3-year old seedlings (TD_MTWM: P ¼ v www.esajournals.org

0.851). For 2-year-old P. pseudostrobus seedlings, the best AIC (1882.7) was obtained using the transfer distance of mean temperature in the warmest month (TD_MTWM, P ¼ 0.0007) and its quadratic term (TD_MTWM2, P ¼ 0.2597). In the random effects, differences among sites were nearly significant (P ¼ 0.0613), while block within site was highly significant (P , 0.0001). Again, population as a random effect was not significant; the effect of climatic transfer distance appeared to absorb much of the variation among populations. The relevance of MTWM was confirmed by estimating the transfer distance from the in situ Hobo data loggers for the 2-yearold seedlings (TDH-S_MTWM: P ¼ 0.0115) and by using spline climatic data for the 3-year-old seedlings (TD_MTWM: P ¼ 0.0391). The relevance of the MTWM in shaping genetic differences among populations is more evident when the provenance performance of the three species is plotted in a single graph against MTWM transfer distance (estimated using data from the in situ data loggers; Fig. 3). One source of reluctance on the part of forest managers to conduct assisted migration is 9



Fig. 4. Response in relative growth of seedling height (empty symbols denote 2-year-old seedlings; filled symbols denote 3-year-old seedlings) to altitudinal movement of populations of Pinus devoniana (diamond symbols), P. leiophylla (triangle symbols) and P. pseudostrobus (circle symbols). Positive values of altitudinal transfer distance denote movement towards higher altitude; more negative values denote movement to lower altitudes; zero values indicate populations growing as locals. The quadratic regression model is significant for 2year-old seedlings of P. devoniana and P. pseudostrobus (P 0.008), but not for P. leiophylla (P ¼ 0.1033). In the 3year-old seedlings, quadratic regressions are significant only for P. pseudostrobus (P ¼ 0.0031), but not for P. devoniana (P ¼ 0.3933) or P. leiophylla (P ¼ 0.9824).

For all three species, the relative growth response to the experimental altitudinal movement fits a quadratic regression model (Fig. 4), where growth declines as populations are moved away from the climate to which they are adapted (Ma´tya´s et al. 2010). Although the three species present a similar quadratic trend, growth response curves differ significantly among species (analysis of covariance: F ¼ 3.23, P ¼ 0.04), indicating that each responds differently to the altitudinal movement. P. devoniana presents a much more pronounced slope than P. leiophylla or P. pseudostrobus. This may be an artifact of the larger altitudinal shift experienced by P. devoniana: nearly 1100 m upward for the population originally from the lowest altitude. In contrast, the altitudinal movement of P. pseudostrobus and

uncertainty regarding the extent to which growth could decrease when a population is shifted upwards in altitude (in the short term, because in the future sites at higher altitude will be warmer), compared to populations growing at their site of origin (assuming precipitation is not a limiting factor). To address this question in more detail, in this section we examine the patterning of growth depending on altitudinal or climatic transfer distance. To support this, we present a series of graphs where growth response (relative growth in height in 2-year old and 3-year-old seedlings) was plotted against climatic transfer distance in altitude (Fig. 4), or against the climatic transfer distance variable that presented the highest statistical significance in the analysis per species (Figs. 5–7). v www.esajournals.org

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Fig. 5. Response in relative growth (%) of Pinus devoniana seedling height (empty symbols denote 2-year-old seedlings; filled symbols denote 3-year-old seedlings) to a transfer distance in minimum temperature of the coldest month (TD_MMIN, 8C).

P. leiophylla was much more moderate (up to þ500 m and þ600 m of altitudinal difference, respectively; Fig. 4).

ward shift that exceeds þ650 m of altitudinal difference (between seed source and planting site) (Fig. 4), or they undergo a climate transfer to sites that are 1.58C colder (in terms of mean minimum temperature of the coldest month,

Growth in P. devoniana decreases significantly when populations undergo an altitudinal up-

Fig. 6. Response in relative growth (%) of Pinus pseudostrobus seedling height (empty symbols denote 2-yearold seedlings; filled symbols denote 3-year-old seedlings) to a transfer distance in mean temperature of the warmest month (TD_MTWM, 8C).


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Fig. 7. Response in relative growth (%) of Pinus leiophylla seedling height (empty symbols denote 2-year-old seedlings; filled symbols denote 3-year-old seedlings) to a transfer distance in minimum temperature of the coldest month (TD_MMIN, 8C).

been shifted between 300 m and þ 600 m in altitude (Fig. 4) or climatic transfer distances of þ 0.78C (to warmer sites) and up to 1.38C (to colder sites) of mean minimum temperatures of the coldest month. Such a transfer represents a large total interval of 28C, yet there were no significant differences at all (the quadratic regression model for 3-year-old seedlings was meaningless: r2 ¼ 0.01, P ¼ 0.9369; Fig. 7, filled symbols).

MMIN; Fig. 5). The fitted quadratic response function of 3year-old P. pseudostrobus seedlings against mean temperature of the warmest month (MTWM), reaches its maximum growth value near the zero transfer distance value (at approximately þ0.258C of transfer distance); this suggests that populations are located near to their optimum (Fig. 6). When populations are moved to higher altitude, there is a decrease of growth in both 2- and 3-year-old seedlings, compared to the population growing at its site of origin (Fig. 6). If the upward altitudinal transfer is of 450 m or the climatic transfer is to a site that is 1.58C colder (in terms of mean temperature of the warmest month) than the seed source, the decrease in growth in the 3-year-old seedlings is quite pronounced; they present growth that is nearly half (176% of relative growth in seedling height) that predicted as the optimum (280%; Fig. 6, filled symbols). Pinus leiophylla populations growing in their site of origin at the lower (2100 m asl) and medium (2400 m asl) altitude sites were among the best growing populations (populations with a transfer distance ¼ 0 in Figs. 4 and 7). Several other populations presented similar growth to that of the local populations, even if they had v www.esajournals.org

DISCUSSION Survival We expected higher mortality in the P. devoniana that originated at the lowest altitude due to frost damage at the upper elevation site as well as higher mortality in P. pseudostrobus due to drought stress at the low elevation site. However, the average survivorship of 79.6% for 3-year-old seedlings found across the species and sites is an encouraging result that suggests the viability of assisted migration as a management practice, at least in the experimental range explored in this study. This result is promising, since young seedlings are normally the most vulnerable (Anekonda and Adams 2000, Saénz-Romero and Tapia-Olivares 2008). 12



limits of the adaptation plasticity of P. devoniana. An upward shift in altitude of 300 m has been suggested to approach realignment of P. pseudostrobus populations to the climate projected for the decade centered on the year 2030 (Saénz-Romero et al. 2012b). Such an assisted migration would be equivalent to a transfer to a site that is 0.98C colder (in terms of mean temperature of the warmest month) than the seed source. This represents a moderate climate transfer, well below that implied by a move to a site that causes severe growth depression, that would occur only if moved to a site 1.58C colder (Fig. 6). In other words, a climate transfer of 300 m in altitude or 0.98C in MTWM would appear to be a safe and acceptable proposal. The performance of P. leiophylla, that seems to be nearly unaffected by the altitudinal shifts, indicates that differences among populations for this species are probably due to phenotypic plasticity, and that genetic differentiation among populations along the altitudinal gradient had not yet taken place. In the nursery test stage of these same P. leiophylla provenances, we obtained similar results (Castellanos-Acunã et al. 2013). Furthermore, G. E. Rehfeldt (2012; personal communication; unpublished data) found differences barely significant among P. leiophylla populations after a common garden test of P. leiophylla 35 populations collected from the northern extreme of its distribution (Arizona and New Mexico, USA; Rehfeldt et al. 2006). Again, the present results suggest that an altitudinal shift of around þ300 m, to realign to the climate projected for the decade centered on the year 2030, would not cause a severe maladaptation and may thus represent a viable management strategy.

Effect of climatic transfer distance and differences among populations Genetic differentiation among populations appears to be mainly shaped by the selective influence of extreme temperatures; either mean minimum temperature in the coldest month (TD_MMIN) or mean temperature in the warmest month (TD_MTWM). This suggests that populations adapt to the selective pressure imposed by extreme events of low (likely expressed by MMIN) or high (likely expressed by MTWM) temperature. In the case of P. devoniana, the disparity of precipitation between the very wet months of July, August and September and the warm and dry months of April and May also plays an important role. These values are expressed in our study as the summer precipitation balance (SMRPB; to visualize such disparity in precipitation values, see the monthly precipitation data for Michoacań in Saénz-Romero et al. 2012a). The estimated maximum value of relative growth approximately corresponds to the zero value of transfer distance suggesting that, in general, the populations are located in or near to their optimum (Fig. 3).

MANAGEMENT

IMPLICATIONS

Growth decreases when populations move to sites that are colder (at higher elevation) in comparison to their origin. Even while the inherent genetic variability of each population allows some adjustment to new selection pressures, growth response decreases when the limit of tolerance is approached. Similar responses have been observed in Pinus taeda, Picea abies (Schmidtling 1994) and in several species of the genus Larix and Pseudostsuga (Rehfeldt et al. 1999, 2003, Leites et al. 2012a, 2012b, Hamann and Wang 2006). For Pinus devoniana, seems like a shift of þ650 m of altitudinal difference, or to 1.58C of colder mean minimum temperature than the seed source, implies crossing an adaptive threshold that promotes maladaptation. Thus, replacing the decaying low altitudinal limit populations of P. pseudostrobus by planting P. devoniana seedlings originated from a seed source that would be shifted upwards in altitude less than 650 m, seems to be a secure strategy that is within the v www.esajournals.org

Future research required The common substrate used for the three field common garden tests insulated the seedlings from the natural soil effect of each site and left only the altitude and its associate climate as the main effect in each field site. Although that was the objective in this particular study, it is to be expected in large-scale assisted migration that soils may change with altitude; a factor (along with the perturbation history of each microsite) that would interact with the migrated genotypes. Thus, it might be desirable to establish assisted 13


˜ A ET AL. CASTELLANOS-ACUN sabbatical term. We thank Felipe Aguilar, Manuel Echeverrıá, Felipe Lo´pez, Reyes Aguilar (Forestry Office of Nuevo San Juan Parangaricutiro Indigenous Community), Jose´ C. Soto-Correa, Lorena Ruiz-Talonia, Esperanza Loya-Rebollar and others for their help with seed collection and the establishment and maintenance of the field common-garden experiments. Nicholas Crookston, Gerald E. Rehfeldt and Laura Leites provided valuable assistance for the mixed model analysis. Nahum Sańchez-Vargas, Phillipe Lobbit, and Juan Carlos Montero-Castro provided valuable comments throughout the project. The comments of two anonymous reviewers, Jake Weltzin as subject-matter Editor and the assistance of Keith MacMillan as English reviewer significantly improved the manuscript.

migration tests under different field conditions at the same altitudes. In addition, the expression of traits at older ages would be highly desirable. Provenance tests in contrasting environments have shown that the trend of differences among provenances can change with age, with more pronounced shifts observed as field environments become harsher (Ying 1997). Measurement at later ages would imply experimental designs that incorporate commercial spacing (2 m 3 3 m is the common commercial spacing in the studied area for those species).

CONCLUSIONS There were significant differences among Pinus devoniana, P. pseudostrobus and P. leiophylla, and among populations within the former two species, associated primarily with the climatic transfer distances in extreme temperatures (coldest and warmest month). In general, P. devoniana and P. pseudostrobus populations reduce growth when moved to higher altitude (colder sites), while P. leiophylla exhibits similar growth at all the altitudinal transfers tested, suggesting higher phenotypic plasticity of this species. There is a significant decrease in growth when the transfer of P. devoniana exceeds 650 m of upward altitudinal movement and when P. pseudostrobus movement exceeds 400 m of upward altitudinal shift. Thus, assisted migration of 300 m upwards in altitude, in order to approach a realignment of the populations to the climate projected for the decade centered on the year 2030, seems to be a viable strategy by which to accommodate climate change.

LITERATURE CITED Aitken, S. N., S. Yeaman, J. A. Holliday, T. Wang, and S. Curtis-McLane. 2008. Adaptation, migration or extirpation: climate change outcomes for tree populations. Evolutionary Applications 1:95–111. Allen, C. D., A. K. Macalady, H. Chenchouni, D. Bachelet, N. McDowell, M. Vennetier, T. Kizberger, A. Rigling, D. D. Breshears, E. H. Hogg, P. Gonzalez, R. Fensham, Z. Zhang, J. Castro, N. Demidova, J. H. Lim, G. Allard, S. W. Running, A. Semerci, and N. Cobb. 2010. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. Forest Ecology and Management 259:660–684. Anekonda, T. S., and W. T. Adams. 2000. Cold hardiness testing for Douglas-fir tree improvement programs: guidelines for a simple, robust and inexpensive screening methods. Western Journal of Applied Forestry 15(3):129–136. Breshears, D. D., N. Cobb, P. M. Rich, K. P. Price, C. D. Allen, R. G. Balice, W. H. Romme, J. H. Kastens, M. L. Floyd, J. Belnap, J. J. Anderson, O. B. Myers, Meyer, C. W. and C. W. 2005. Regional vegetation die-off in response to global-change-type drought. Proceedings of National Academy of Sciences 102:15144–15148. Carter, K. K. 1996. Provenance tests as indicators of growth response to climate change in 10 north temperate tree species. Canadian Journal of Forest Research 26:1089–1095. Castellanos-Acunã, D., C. Saénz-Romero, R. A. LindigCisneros, N. M. Sańchez-Vargas, P. Lobbit, and J. C. Montero-Castro. 2013. Altitudinal variation among species and provenances of Pinus pseudostrobus, P. devoniana y P. leiophylla; nursery test. Revista Chapingo Serie Ciencias Forestales y del Ambiente 19(3):399–412. Crawley, M. J. 2007. The R book. John Wiley & Sons, Chichester, West Sussex, UK.

ACKNOWLEDGMENTS This paper is an undertaking of the Forest Genetic Resources Working Group/North American Forest Commission/Food and Agricultural Organization of the United Nations. Financial support was provided by the joint research fund between the Mexican Council of Science and Technology and the State of Michoacań (CONACyT-Michoacań-FOMIX-2009127128), the Coordination for Scientific Research of the University of Michoacań (UMSNH-CIC), the PAPIT-UNAM fund (project N202112). Also we thank to CONACyT from a graduate studies fellowship to D. Castellanos-Acunã and a sabbatical year fellowship to C. Saénz-Romero. R. Lindig-Cisneros is grateful to the DGAPA of UNAM for the PASPA grant for a


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