Pinus Strobiformis Research Articles

Species delimitation using multiple sources of evidence from the Pinus strobiformis-Pinus ayacahuite Species Complex

Background: The Trans-Mexican Volcanic Belt (TMVB) in central Mexico is characterized by peaks of high altitude and geologic instability. In this zone, Pinus strobiformis and Pinus ayacahuite form a contact zone with Pinus veitchii. The taxonomical circumscription of white pines in Central Mexico has been unstable, especially regarding the status of P. veitchii.
 Questions: What are the species boundaries of the montane Mexican white pines species complex? Is Pinus veitchii a hybrid or an independently evolving lineage?
 Studied species: Pinus strobiformis, Pinus veitchii and Pinus ayacahuite species complex.
 Study site and dates: United States of America and Mexico from 2003 to 2022.
 Methods: We performed multivariate analyses on 10 morphological characters and characterized the climatic niche divergence and the genetic differentiation using SNPs.
 Results: Our results showed that P. veitchii is morphologically similar to P. strobiformis, but does not have intermediate morphological values with P. ayacahuite. The ecological niche differentiation was not significant. Genetic analyses showed P. veitchii as an independent lineage with evidence of admixture with P. ayacahuite, suggesting a gene flow but not a hybrid origin.
 Conclusions: Two of the three lines of evidence support three independent lineages. Environmental information showed niche conservatism, morphology and genetic structure showed differentiation of all three taxa, with a greater morphological similarity between P. strobiformis and P. veitchii, and genetic analyses recovered evidence of introgression, suggesting a complex demographic history in the Trans Mexican Volcanic Belt.

Drought-induced growth phenotypes are associated with genetic variation across a white pine hybrid zone

Understanding relationships among warming climate, increased drought severity, and the genetic architecture of hybrid drought resilience is necessary for forest conservation and management. We calculated three drought-related tree-ring-growth indices (dendrophenotypes) using tree-ring data from hybrid Pinus strobiformis–Pinus flexilis study trees at nine sites across Colorado, New Mexico, Arizona, and Texas. Along with hybrid index (percentage of P. strobiformis ancestry inherited by a single tree) and climate variables, we used dendrophenotypes to (Q1) examine relationships among climate and hybrid index, (Q2) examine relationships between dendrophenotypes and hybrid index, and (Q3) conduct a genotype–phenotype analysis. We observed a significant correlation between hybrid index and dendrophenotypes resulting from high-temperature drought in addition to a significant correlation between those dendrophenotypes and our dataset of single-nucleotide polymorphisms. We conclude that P. strobiformis–P. flexilis trees exhibiting higher hybrid indices are more resilient to high-temperature drought events and encourage future research that identifies a genetic linkage between relevant loci and their conferred physiological benefits.

Natural durability of timber species exposed to xylophagous fungi in southern Durango, Mexico.

Wood is a natural resource used for construction and the manufacture of many products. This material is exposed to damage due to biotic and abiotic factors. An important biotic factor is wood-degrading fungi that generate large economic losses. The objectives of this study were to determine the effect of xylophagous fungi (Coniophora puteana and Trametes versicolor) on the natural durability of six timber species in southern Durango, Mexico, and to establish differences between fungal effects on each tree species. Samples of Pinus durangensis, P. cooperi, P. strobiformis, Juniperus deppeana, Quercus sideroxyla, and Alnus acuminata were exposed to fungi for 4 months under laboratory conditions according to European Standard EN350-1. Samples of Fagus sylvatica were used as control. Durability was determined as the percentage of wood mass loss for each species. Welch ANOVA tests were performed to establish differences among tree species. Welch t-tests were used to prove loss mass differences between fungi for each tree species. The most resistant species to C. puteana were P. durangensis, J. deppeana, P. cooperi and P. strobiformis, showing mean mass losses lower than 8.08%. The most resistant species to T. versicolor were J. deppeana, P. strobiformis and P. durangensis (mean mass losses lower than 7.39%). Pinus strobiformis and Q. sideroxyla were more susceptible to C. puteana effect; in contrast, P. durangensis and P. cooperi showed more damage due to T. versicolor degradation. Woods of P. durangensis, P. cooperi, P. strobiformis and Juniperus deppeana are well adapted to infection by these xylophagous fungi and are therefore highly recommended for commercial use in southern Durango, Mexico.

Planted seedling survival in a post-wildfire landscape: From experimental planting to predictive probabilistic surfaces

Across the southwestern United States, high-severity wildfire is causing increasingly large areas of tree mortality and removing the seed sources required for the natural regeneration of these formerly conifer-dominated landscapes. Planting tree seedlings can accelerate reforestation, but in the semi-arid southwestern US, the survival of planted conifer seedlings is typically low. Our research examined how post-fire planting success is influenced by climate, topographic, biotic, and microclimate factors. We present data on a seedling planting experiment within the footprint of the 2011 Las Conchas Fire in northern New Mexico. We planted 768 tree seedlings of four species: ponderosa pine (Pinus ponderosa), piñon (P. edulis), southwestern white pine (P. strobiformis), and Douglas-fir (Pseudotsuga menziesii) in an area burned at high-severity and densely populated by New Mexico locust (Robinia neomexicana) and other shrub species. We established experimental plots stratified by aspect, either northerly or southerly, and cover, either planted under New Mexico locust or in the open, and collected topographical and microclimate measurements over three years. Mean survival over the 3-year period for all species in all treatments was 20%. Using microclimate variables and site-level topographical indices in a piecewise exponential model, we first determined how these factors influenced seedling survival of four conifer tree species, finding that topographical indices describing incoming solar radiation, variables related to vapor pressure deficit, i.e., seasonal maximums, and presence of New Mexico locust increased hazard for all species while variables related to shade, moisture availability, and slope reduced hazard. Following our planting experiment, an additional 1145 ponderosa pine seedlings, planted by USFS, were surveyed for survival and the topographical indices at their locations were recorded. Adding these seedlings' survival data to our experimentally planted ponderosa pine seedlings, we used boosted regression tree models to determine survival probability for ponderosa pine as a product of topographical indices, then extrapolated these findings to the wider landscape, producing a spatial projection of probabilistic seedling survival as a function of readily available topographical data, with a mean AUC value of 0.63. Both sets of analyses highlight the importance of landscape heterogeneity in shaping microclimatic environments and affecting seedling survival in a predictable manner, with areas receiving less solar radiation and more moisture promoting seedling survival. Our results demonstrate that by using fine-scale microtopography that shapes microclimatic environments, future plantings can increase conifer tree seedling survival in high-severity post-wildfire landscapes.

Variabilidad de la precipitación (1660-2018) para el oeste de Chihuahua inferida con anillos de árboles

Introduction: Tree rings play a significant role for the reconstruction of climate variables on century scales. Objective: To reconstruct the variability of precipitation for the western part of the state of Chihuahua, based on tree rings of Pseudotsuga menziesii (Mirb.) Franco, Pinus arizonica Engelm.and Pinus strobiformis Engelm. Materials and methods: Samples were extracted with a Pressler drill, dated and growth indexes were generated based on dendrochronological techniques. A correlation analysis was run between regional chronology and observed precipitation data. A regression model was used to reconstruct precipitation. A spectral analysis determined the recurrence of droughts and the influence of El Niño Southern Oscillation (ENSO) on precipitation variability. Results and discussion: The relationship between the chronologies was statistically significant and a regional series of 359 years was developed. October-June precipitation had the highest impact on growth (r = 0.73, P < 0.01), so the variability of precipitation for that period was reconstructed for the last 359 years. Severe droughts were detected in the periods 1751-1768, 1807-1810 and 1945-1956 and a recurrence of droughts every 50 years was identified. The reconstructed precipitation variability is significantly modulated by ENSO at different time scales and frequencies. Conclusion: Paleoclimatic series help us to spread the knowledge of climate in specific geographic regions and to analyze the recurrence of extreme events (droughts).

Comparative Association Mapping Reveals Conservation of Major Gene Resistance to White Pine Blister Rust in Southwestern White Pine (Pinus strobiformis) and Limber Pine (P. flexilis).

All native North American white pines are highly susceptible to white pine blister rust (WPBR) caused by Cronartium ribicola. Understanding genomic diversity and molecular mechanisms underlying genetic resistance to WPBR remains one of the great challenges in improvement of white pines. To compare major gene resistance (MGR) present in two species, southwestern white pine (Pinus strobiformis) Cr3 and limber pine (P. flexilis) Cr4, we performed association analyses of Cr3-controlled resistant traits using single nucleotide polymorphism (SNP) assays designed with Cr4-linked polymorphic genes. We found that ∼70% of P. flexilis SNPs were transferable to P. strobiformis. Furthermore, several Cr4-linked SNPs were significantly associated with the Cr3-controlled traits in P. strobiformis families. The most significantly associated SNP (M326511_1126R) almost colocalized with Cr4 on the Pinus consensus linkage group 8, suggesting that Cr3 and Cr4 might be the same R locus, or have localizations very close to each other in the syntenic region of the P. strobiformis and P. flexilis genomes. M326511_1126R was identified as a nonsynonymous SNP, causing amino acid change (Val376Ile) in a putative pectin acetylesterase, with coding sequences identical between the two species. Moreover, top Cr3-associated SNPs were further developed as TaqMan genotyping assays, suggesting their usefulness as marker-assisted selection (MAS) tools to distinguish genotypes between quantitative resistance and MGR. This work demonstrates the successful transferability of SNP markers between two closely related white pine species in the hybrid zone, and the possibility for deployment of MAS tools to facilitate long-term WPBR management in P. strobiformis breeding and conservation.

Post-fire early successional vegetation buffers surface microclimate and increases survival of planted conifer seedlings in the southwestern United States

Climate change and fire exclusion have increased the flammability of western United States forests, leading to forest cover loss when wildfires occur under severe weather conditions. Increasingly large high-severity burn patches limit natural regeneration because of dispersal distance, increasing the chance of conversion to non-forest. Post-fire planting can overcome dispersal limitations, yet warmer and drier post-fire conditions can still reduce survival. We examined how two shrub species with different structures affect below-shrub microclimate and survival rates of planted tree seedlings (Pinus ponderosa Lawson & C. Lawson, Pinus edulis Engelm., Pinus strobiformis Engelm., Pseudotsuga menziesii (Mirb.) Franco) following a high-severity fire in northern New Mexico. We expected that Gambel oak (Querus gambelii Nutt.), with its denser canopy, would buffer below-shrub climate causing higher survival rates of planted seedlings more than the lower canopy density New Mexico locust (Robinia neomexicana A. Gray). Seedlings planted under Gambel oak had survival rates 10% to 35% greater than those planted under New Mexico locust. Higher light availability beneath New Mexico locust corresponded to higher temperatures, lower humidity, and higher vapor pressure deficit, impacting the mortality of planted tree seedlings. These results indicate that by waiting for post-fire shrub establishment, selective use of shrubs can buffer microclimate and increase post-fire planting success in the southwestern United States.

Model selection and timing of acquisition date impacts classification accuracy: A case study using hyperspectral imaging to detect white pine blister rust over time

Hyperspectral imaging is useful in identifying plant stress over large areas or with large numbers of individuals. The vast data sets make machine learning indispensable, but the choice of machine-learning model, the accuracy of models in extrapolation over time (dynamic data), and timing of measurements require further elucidation. We assessed two metrics of performance for selection of classification model: the predicted accuracy (PA); and the area under the receiver-operating characteristic curve (AUC), both from a 10-fold cross-validation. These metrics were calculated for 22 models that were trained to track white pine blister rust disease in seedlings of southwestern white pine (Pinus strobiformis) on 16 dates. In static data (training and testing data are randomly picked from all dates) PA was comparable with AUC at ranking the models for tested accuracy (Spearman’s rank correlation coefficient, hereafter referred to as Spearman’s ρ, were 0.58 and 0.54, respectively). However, for dynamic data (training and testing data came from different dates) AUC was more successful at ranking the models for tested accuracy compared to PA (Spearman’s ρ were 0.37 and 0.31, respectively). Classification accuracies were 74.3 % and 75.8 % for the top PA and AUC models when applied to dynamic data. However, using a heterogeneous ensemble output, the accuracies increased to 77.3% (PA) and 77.6% (AUC). In comparison, if we selected the models based on the tested accuracies (which would not be possible in a real-life application), the best accuracy was 77.7% for a support-vector machine with a linear kernel. Classification accuracy was affected by the size of the time gap between training and testing dates as well as the timing of training and test date. The decline in accuracy with time lag was asymmetric, being more pronounced in classifying retrospectively, i.e., when the testing date came before the training date, than vice versa. Thus, for this system training a model on an early date resulted in higher accuracies than training a model on a later date. As for the timing, the highest average accuracies were obtained with a classifier trained on data acquired during the onset of the disease, which in this study was on DOY 116.

Quantitative Disease Resistance to White Pine Blister Rust at Southwestern White Pine’s (Pinus strobiformis) Northern Range

White pine blister rust, caused by the non-native, invasive fungal pathogen Cronartium ribicola, is a significant cause of mortality in white pines (Pinus subgenus Strobus) in North America. Along with climate-driven range contraction, mortality from blister rust can seriously impact the abundance and distribution of the nine white pine species native to the United States and Canada. Very little evaluation of this disease in southwestern white pine (Pinus strobiformis) has been previously undertaken, but genetic resistance to the disease has been documented, including major gene resistance (MGR) conferred by a dominant R gene. Data is emerging suggesting that the species also has quantitative disease resistance (QR). Our results suggest QR occurs at low frequency, with perhaps 10% of trees having a moderate level (> 35% survival). We assessed progeny arrays from 40 P. strobiformis families (1873 seedlings), originating from three populations, inoculated with C. ribicola. Subsequently, the seedlings were assessed for signs, symptoms and resulting impact in a common garden trial over a 7.5-year period to determine the types and frequency of resistance in a portion of this species’ range. There was a high incidence of both stem symptoms and mortality in the P. strobiformis families tested, and families ranged in survival from 0 to 84.6%. Three families had > 70% survival, representing perhaps the highest documented QR to date in a North American white pine species. Approximately 29.1% of the 441 surviving seedlings showed no stem symptoms, and of the approximately 70.8% of seedlings surviving with infections only few (24 of 316) had infections of moderate to high severity. QR traits associated with improved survival were primarily related to lower severity of infection, a reduced number of stem symptoms, and an increased number of bark reactions. Despite the high overall susceptibility, the presence of QR appears to be at a frequency and level useful to forest managers involved in restoration and reforestation efforts.

Plant developmental stage influences responses of Pinus strobiformis seedlings to experimental warming.

Seedling emergence, survival, morphological and physiological traits, and oxidative stress resistance of southwestern white pine (Pinus strobiformis Engelm.) were studied in response to warming treatments applied during embryogenesis, germination, and early seedling growth. Daytime air temperature surrounding cones in tree canopies was warmed by +2.1°C during embryo development. Resulting seeds and seedlings were assigned to three thermal regimes in growth chambers, with each regime separated by 4°C to encompass the wide range of temperatures observed over space and time across the species' range, plus the effect of heat waves coupled with a high carbon emissions scenario of climate warming. The embryo warming treatment reduced percent seedling emergence in all germination and growth environments and reduced mortality of seedlings grown in the warmest environment. Warm thermal regimes during early seedling growth increased subsequent seedling resistance to oxidative stress and transpirational water use. Experimental warming during seed development, germination, and seedling growth affected seedling emergence and survival. Oxidative stress resistance, morphology, and water relations were affected only by warming imposed during germination and seedling growth. This work explores potential outcomes of climate warming on multiple dimensions of seedling performance and uniquely illustrates that plant responses to heat vary with plant developmental stage in addition to the magnitude of temperature change.

DIFFERENCES IN CONE AND SEED MORPHOLOGY OF PINUS STROBIFORMIS AND PINUS AYACAHUITE

For decades there has been confusion and uncertainty on how to clearly identify the two distinct species, Pinus strobiformis Engelm. and Pinus ayacahuite Ehrenberg. Pinus ayacahuite is further defined as two varieties, var. ayacahuite and var. veitchii. These species are of ecological importance throughout much of Mexico because they offer valuable ecosystem services. The objective in this work was to examine the morphological characteristics of cones and seeds from parent trees from six sites in northern Mexico and three sites in southern Mexico. The results show that the mean seed width and length per tree, mean cone weight per tree, and the 100-seed weight per tree were the best variables to accurately separate P. strobiformis from P. ayacahuite. Using these criteria, we found that P. ayacahuite var. veitchii is more similar to P. strobiformis than to P. ayacahuite var. ayacahuite.

Assessment and Models of Insect Damage to Cones and Seeds of Pinus strobiformis in the Sierra Madre Occidental, Mexico.

Insect damage to cones and seeds has a strong impact on the regeneration of conifer forest ecosystems, with broader implications for ecological and economic services. Lack of control of insect populations can lead to important economic and environmental losses. Pinus strobiformis is the most widespread of the white pines in Mexico and is widely distributed throughout the mountains of northern Mexico. Relatively few studies have examined insect damage to the cones and seeds of these pines, especially in Mexico. In this study, we therefore analyzed insect damage to cones and seeds of P. strobiformis in Mexico by using X-ray and stereomicroscopic analysis. The specific objectives of the study were (a) to characterize insect damage by measuring external and internal cone traits, (b) to assess the health of seeds and cones of P. strobiformis in the Sierra Madre Occidental, Mexico, and (c) to estimate the relative importance of the effects of different environmental variables on cone and seed damage caused by insects. We found that 80% of P. strobiformis seeds and 100% of the tree populations studied had damage caused by insects. Most seeds were affected by Leptoglossus occidentalis, Tetyra bipunctata, Megastigmus albifrons, and the Lepidoptera complex (which includes Apolychrosis synchysis, Cydia latisigna, Eucosma bobana, and Dioryctria abietivorella). The cones of all tree populations were affected by some type of insect damage, with Lepidoptera causing most of the damage (72%), followed by Conophthorus ponderosae (15%), the hemipteran L. occidentalis (7%), and the wasp M. albifrons (6%). The proportion of incomplete seeds in P. strobiformis at the tree level, cone damage by M. albifrons and seed damage in L. occidentalis were associated with various climate and soil variables and with crown dieback. Thus, cone and seed insect damage can be severe and potentially impact seed production in P. strobiformis and the reforestation potential of the species. The study findings will enable managers to better identify insects that cause damage to cone and seeds. In addition, identification of factors associated with damage may be useful for predicting the levels of insect predation on seeds and cones.

Adaptive evolution in a conifer hybrid zone is driven by a mosaic of recently introgressed and background genetic variants

Extant conifer species may be susceptible to rapid environmental change owing to their long generation times, but could also be resilient due to high levels of standing genetic diversity. Hybridisation between closely related species can increase genetic diversity and generate novel allelic combinations capable of fuelling adaptive evolution. Our study unravelled the genetic architecture of adaptive evolution in a conifer hybrid zone formed between Pinus strobiformis and P. flexilis. Using a multifaceted approach emphasising the spatial and environmental patterns of linkage disequilibrium and ancestry enrichment, we identified recently introgressed and background genetic variants to be driving adaptive evolution along different environmental gradients. Specifically, recently introgressed variants from P. flexilis were favoured along freeze-related environmental gradients, while background variants were favoured along water availability-related gradients. We posit that such mosaics of allelic variants within conifer hybrid zones will confer upon them greater resilience to ongoing and future environmental change and can be a key resource for conservation efforts.

Using Hyperspectral Imagery to Detect an Invasive Fungal Pathogen and Symptom Severity in Pinus strobiformis Seedlings of Different Genotypes

Finding trees that are resistant to pathogens is key in preparing for current and future disease threats such as the invasive white pine blister rust. In this study, we analyzed the potential of using hyperspectral imaging to find and diagnose the degree of infection of the non-native white pine blister rust in southwestern white pine seedlings from different seed-source families. A support vector machine was able to automatically detect infection with a classification accuracy of 87% (κ = 0.75) over 16 image collection dates. Hyperspectral imaging only missed 4% of infected seedlings that were impacted in terms of vigor according to expert’s assessments. Classification accuracy per family was highly correlated with mortality rate within a family. Moreover, classifying seedlings into a ‘growth vigor’ grouping used to identify the degree of impact of the disease was possible with 79.7% (κ = 0.69) accuracy. We ranked hyperspectral features for their importance in both classification tasks using the following features: 84 vegetation indices, simple ratios, normalized difference indices, and first derivatives. The most informative features were identified using a ‘new search algorithm’ that combines both the p-value of a 2-sample t-test and the Bhattacharyya distance. We ranked the normalized photochemical reflectance index (PRIn) first for infection detection. This index also had the highest classification accuracy (83.6%). Indices such as PRIn use only a small subset of the reflectance bands. This could be used for future developments of less expensive and more data-parsimonious multispectral cameras.

Influence of Climate on Carbon Sequestration in Conifers Growing under Contrasting Hydro-Climatic Conditions

Research Highlights: Analyzing the contrasting ecological gradients makes it easier to understand the influence of climate on carbon accumulation. Background and Objectives: The increasing climatic variability has implications for vegetation, impacting on its ecological functions, among which carbon accumulation stands out. In the present study, we used climate-dendrochronology relationships to evaluate carbon accumulation in two conifer species that grow in contrasting humidity sites: Pinus strobiformis Engelm (mesic sites) and Pinus leiophylla var. chihuahuana (Engelm.) Shaw (arid sites). Materials and Methods: Using a dendrochronological approach, we estimated the correlation of biomass and carbon accumulation of each species with some climatic variables (temperature, precipitation, and a drought index) and generated a linear mixed model. Results: The response in carbon accumulation between species with respect to climate was significantly different. P. strobiformis showed a positive correlation with the climatic variables analyzed, while in P. leiophylla the correlation was negative, except with precipitation. Conclusions: These results show that forests in both mesic and arid sites are prone to climate changes, although their responses are different, impacting the productivity and carbon cycles of forest ecosystems.

Morphological Differences in Pinus strobiformis Across Latitudinal and Elevational Gradients.

The phenotype of trees is determined by the relationships and interactions among genetic and environmental influences. Understanding the patterns and processes that are responsible for phenotypic variation is facilitated by studying the relationships between phenotype and the environment among many individuals across broad ecological and climatic gradients. We used Pinus strobiformis, which has a wide latitudinal distribution, as a model species to: (a) estimate the relative importance of different environmental factors in predicting these morphological traits and (b) characterize the spatial patterns of standing phenotypic variation of cone and seed traits across the species’ range. A large portion of the total variation in morphological characteristics was explained by ecological, climatic and geographical variables (54.7% collectively). The three climate, vegetation and geographical variable groups, each had similar total ability to explain morphological variation (43.4%, 43.8%, 51.5%, respectively), while the topographical variable group had somewhat lower total explanatory power (36.9%). The largest component of explained variance (33.6%) was the four-way interaction of all variable sets, suggesting that there is strong covariation in environmental, climate and geographical variables in their relationship to morphological traits of southwest white pine across its range. The regression results showed that populations in more humid and warmer climates expressed greater cone length and seed size. This may in part facilitate populations of P. strobiformis in warmer and wetter portions of its range growing in dense, shady forest stands, because larger seeds provide greater resources to germinants at the time of germination. Our models provide accurate predictions of morphological traits and important insights regarding the factors that contribute to their expression. Our results indicate that managers should be conservative during reforestation efforts to ensure match between ecotypic variation in seed source populations. However, we also note that given projected large range shift due to climate change, managers will have to balance the match between current ecotypic variation and expected range shift and changes in local adaptive optima under future climate conditions.

Water relations and drought response of Pinus strobiformis

Southwestern white pine (Pinus strobiformis Engelm.) faces dual threats of climate change shifting its environmental niche and mortality due to a nonnative, invasive fungal pathogen. To inform efforts to sustain this species, we established experimental field trials in three common gardens along an elevational gradient with drought treatments to assess trait responses in southwestern white pine. We measured predawn and midday water potential on 44 maternal families from 10 populations at each garden. We used regression between predawn and midday water potentials to estimate hydroscape area, an index of stomatal regulation of transpiration. We measured leaf carbon isotope ratio and estimated carbon isotope discrimination and leaf mass per area to understand the effects of gardens and treatments on stomatal aperture and leaf structure. Water stress caused by experimental drought and temperature decreased leaf carbon isotope discrimination and leaf mass per area, indicating formation of thin leaves with low stomatal conductance in response to heat and drought. The hydroscape area of southwestern white pine suggests tight control of transpiration via stomatal closure, similar to other isohydric pines. Families with greater stomatal closure (inferred from carbon isotope ratio) at the warm, dry garden had higher survival than other families, suggesting an important role of isohydry in acclimation of southwestern white pine to expected habitat drying and warming.

Augmenting size models forPinus strobiformisseedlings using dimensional estimates from unmanned aircraft systems

In forestry, common garden experiments traditionally require manual measurements and visual inspections. Unmanned aircraft systems (UAS) are a newer method of monitoring plants that is potentially more efficient than traditional techniques. This study had two objectives: to assess the size and mortality of Pinus strobiformis Engelm. seedlings using UAS and to predict the second-year seedling size using manual measurements from the first year and from UAS size estimates. Raised boxes containing 150 seedlings were surveyed twice, one year apart, using multispectral UAS. Seedling heights and diameters at root collar (DRC) were measured manually in both years. We found that size estimates made using a vegetation mask were suitable predictors for size, while spectral indices were not. Furthermore, we provided evidence that inclusion of UAS size estimates as predictors improves the fit of the models. Our study suggests that common variables used in forest monitoring are not necessarily best suited for seedlings. Therefore, we created a new variable, called the longitudinal area (height × DRC), which proved to be a significant predictor for both height and DRC. Finally, we demonstrate that seedling mortality can be effectively measured from remotely sensed data, which is useful for common garden and regeneration studies.

Crecimiento en diámetro, altura, área basal y volumen para tres especies de pino en Chihuahua, México

La estimación del crecimiento y rendimiento de las especies forestales maderables es clave para planear y proyectar la cosecha de manera sustentable. El objetivo de la presente investigación fue ajustar cuatro modelos de crecimiento en diámetro, altura, área basal y volumen para Pinus leiophylla, Pinus lumholtzii y Pinus strobiformis de la región de Guadalupe y Calvo, Chihuahua. Mediante un muestreo selectivo se recolectaron 26 árboles de P. lumholtzii, 26 de P. strobiformis y 30 árboles de P. leiophylla para generar 219, 249 y 385 perfiles de cada una de las especies, respectivamente. Los modelos de crecimiento evaluados fueron los de Chapman-Richards, Schumacher, Hossfeld I y Weibull. Los criterios de selección de los mejores modelos fueron el coeficiente de determinación, la raíz del error medio cuadrático, la significancia de los parámetros estimados y las tendencias del crecimiento. Se determinó que todos los modelos presentaron ajustes significativos; sin embargo, por las tendencias del crecimiento que generan, los que mejor representaron el comportamiento biológico de las variables analizadas fueron los de Chapman-Richards, Hossfeld I y Schumacher. Con base en las edades a las que ocurre el máximo incremento en volumen y el turno, se infiere que las tres especies presentan lento crecimiento.

Impacts of 21st‐century climate change on montane habitat in the Madrean Sky Island Archipelago

AbstractAimThe Madrean Sky Island Archipelago is a North American biodiversity hotspot composed of ~60 isolated mountains that span the Cordilleran Gap between the Rocky Mountains and the Sierra Madre Occidental. Characterized by discrete patches of high‐elevation montane habitat, these “sky islands” serve as stepping stones across a “sea” of desert scrub/grassland. Over this coming century, the region is expected to shift towards a warmer and drier climate. We used species distribution modelling to predict how the spatial distribution of montane habitat will be affected by climate change.LocationMadrean Sky Island Archipelago, south‐west United States and north‐west Mexico (latitude, 29–34°N; longitude, 107–112°W).MethodsTo approximate the current distribution of montane habitat, we built species distribution models for five high‐elevation species (Ceanothus fendleri, Pinus strobiformis, Quercus gambelii, Sciurus aberti, and Synuchus dubius). The resulting models were projected under multiple climate change scenarios—four greenhouse gas concentration trajectories (RCP 2.6, 4.5, 6.0, and 8.5) for each of three climate models (CCSM4, MPI‐ESM‐LR, and NorESM1‐M)—to generate predicted distributions for the years 2050 and 2070. We performed chi‐squared tests to detect any future changes to total montane habitat area, and Conover–Iman tests to evaluate isolation among the discrete montane habitat patches.ResultsWhile the climate models differ with respect to their predictions as to how severe the effects of future climate change will be, they all agree that by as early as year 2050, there will be significant montane habitat loss and increased montane habitat patch isolation across the Madrean Archipelago region under a worst‐case climate change scenario (RCP 8.5).Main conclusionsOur results suggest that under 21st‐century climate change, the Madrean Sky Islands will become increasingly isolated due to montane habitat loss. This may affect their ability to serve as stepping stones and have negative implications for the region's biodiversity.