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In natural plant populations, the spatial genetic structure (SGS) is occasionally associated with evolutionary and ecological features such as the mating system, individual fitness, inbreeding depression and natural selection of the species of interest. The very rare Mexican P. chihuahuana tree community covers an area no more than 300 ha and has been the subject of several studies concerning its ecology and population genetics. The overall aim of most of these studies has been to obtain data to help design preservation and conservation strategies. However, analysis of the fine-scale SGS in this special forest tree community has not yet been conducted, which might help enrich the above mentioned conservation programs. In this study, we examined the SGS of this community, mostly formed by P. chihuahuana Martínez, Pinus strobiformis Ehrenberg ex Schlechtendah, Pseudotsuga menziesii (Mirb.) Franco, and Populus tremuloides Michx, in 14 localities at both the fine and large scales, with the aim of obtaining a better understanding of evolutionary processes. We observed a non-significant autocorrelation in fine-scale SGS, suggesting that the genetic variants of all four tree species are randomly distributed in space within each sampled plot of 50 x 50 m. At the larger scale, the autocorrelation was highly significant for P. chihuahuana and P. menziesii, probably as a result of insufficient gene flow due to the extreme population isolation and small sizes. For these two species our results provided strong support for the theory of isolation by distance.

Aim The 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. Location Madrean Sky Island Archipelago, south‐west United States and north‐west Mexico (latitude, 29–34°N; longitude, 107–112°W). Methods To 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. Results While 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 conclusions Our 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.

A lack of optimal gene combinations, as well as low levels of genetic diversity, is often associated with the formation of species range margins. Conservation efforts rely on predictive modelling using abiotic variables and assessments of genetic diversity to determine target species and populations for controlled breeding, germplasm conservation and assisted migration. Biotic factors such as interspecific competition and hybridization, however, are largely ignored, despite their prevalence across diverse taxa and their role as key evolutionary forces. Hybridization between species with well‐developed barriers to reproductive isolation often results in the production of offspring with lower fitness. Generation of novel allelic combinations through hybridization, however, can also generate positive fitness consequences. Despite this possibility, hybridization‐mediated introgression is often considered a threat to biodiversity as it can blur species boundaries. The contribution of hybridization towards increasing genetic diversity of populations at range margins has only recently gathered attention in conservation studies. We assessed the extent to which hybridization contributes towards range dynamics by tracking spatio‐temporal changes in the central location of a hybrid zone between two recently diverged species of pines: Pinus strobiformis and P. flexilis. By comparing geographic cline centre estimates for global admixture coefficient with morphological traits associated with reproductive output, we demonstrate a northward shift in the hybrid zone. Using a combination of spatially explicit, individual‐based simulations and linkage disequilibrium variance partitioning, we note a significant contribution of adaptive introgression towards this northward movement, despite the potential for differences in regional population size to aid hybrid zone movement. Overall, our study demonstrates that hybridization between recently diverged species can increase genetic diversity and generate novel allelic combinations. These novel combinations may allow range margin populations to track favourable climatic conditions or facilitate adaptive evolution to ongoing and future climate change.

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.

Abstract Mesophication has reduced fuel-bed flammability in the Mid-Southern US, limiting the effectiveness of fire alone in promoting disturbance-adapted woody species. We applied combinations of thinning (none, 7, and 14 m2 ha–1 residual basal area) and seasonal fire (none, October, and March) at three sites and monitored understory woody response from 2008 to 2016. In combination, thinning and burning had strong negative effects on some mesophytic species (Pinus strobus, Ostrya virginiana, and Fagus grandifolia) and positively affected many shade-intolerant and fire-tolerant species formerly suppressed under closed canopies. Such compositional shifts were greatest at our most xeric site, and were related to treatment effects on overstory and midstory density. Seedling density of Quercus spp. nearly doubled (+2,256 stems ha–1) from pre- to postmanagement. Sapling response was less dramatic; however, indicator and ordination analyses often associated mesophytic and disturbance-dependent saplings with unmanaged and managed treatments, respectively. Fire-season effects were subtle, but more species and greater understory densities were associated with March relative to October burning. Although some mesophytic species (Acer rubrum and Liriodendron tulipifera) responded positively to thinning and resprouted aggressively after fire, our results demonstrate how thinning and burning can initiate the reversal of mesophication’s effects on understory woody vegetation.

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.

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 ( and ) 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 , and were exposed to fungi for 4 months under laboratory conditions according to European Standard EN350-1. Samples of 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 were , and , showing mean mass losses lower than 8.08%. The most resistant species to were , and (mean mass losses lower than 7.39%). and were more susceptible to effect; in contrast, and showed more damage due to degradation. Woods of and are well adapted to infection by these xylophagous fungi and are therefore highly recommended for commercial use in southern Durango, Mexico.

Background Wildfire size and severity have been increasing in the southwestern US since the mid-1980s as a direct result of anthropogenic climate change and land management practices. Large, high severity wildfire, including reburns, combined with two decades of drought, may result in ecosystem reorganization, as some areas dominated by conifer forest are no longer able to recover, and are replaced or outcompeted by oaks or shrubs. We apply a unifying resilience framework distinguishing post-fire processes of persistence, recovery, and reorganization of mixed conifer and pine-oak forests in two southern Arizona Sky Island mountain ranges. The Santa Catalina and Rincon Mountains experienced multiple wildfires in the early 2000s, followed by a large reburn in the Santa Catalina Mountains in 2020. We evaluated conifer radial tree growth as a measure of individual tree persistence, seedling recruitment as a measure of conifer and oak population recovery, and differences in species importance values in burned and unburned areas, to detect potential ecosystem reorganization, including changes in dominant plant trait groups. Results In our tree growth analysis, we found resilience to both drought and wildfire in three dominant conifer species. Ponderosa pines ( Pinus ponderosa ) and southwestern white pines ( Pinus strobiformis ) that survived both high and low severity fire showed non-significant positive growth trajectories following wildfire exposure in 2003. Douglas-fir ( Pseudotsuga menziesii ) growth was more climate-dependent and adversely affected by fire exposure. In areas that burned only once, post-fire conifer recruitment was found in the majority of burned plots that were sampled 18–19 years after fire, although density varied greatly. We found evidence of incipient community reorganization reflecting plant traits (e.g., resprouting species) especially in mixed-conifer communities. Composition analysis indicated some loss of conifer overstory dominance in areas burned at high severity in higher elevations; in general, these were replaced mainly by aspen ( Populus tremuloides ). Conclusions The study landscapes showed evidence of all three post-fire processes of persistence, recovery, and reorganization in the 18–19 years after the initial fire events. The complex mosaic of fire severity and topography promoted landscape-scale recovery, while some high severity areas show evidence of incipient or transient reorganization. Early (1 year) post-fire vegetation responses following the 2020 reburn were highly variable and dependent on sequences of fire severity and plant traits; these constitute initial conditions for future trajectories of change in southwestern forests under the influence of changing climate and fire regimes.

1. Historical reference conditions have long been used to guide the restoration of degraded ecosystems. However, a rapidly changing climate and altered disturbance regimes are calling into question the usefulness of this approach. As a consequence, restoration goals are increasingly focused on creating communities that are resilient to novel environmental Stressors and emphasis is being placed on defining functional targets through the use of plant traits. While changes in forest structure and composition have received much attention, long-term changes in stand-level functional traits are not well understood. 2. We used dendrochronology to reconstruct historical forest structure and composition in 1880, the year immediately following the disruption of the natural fire regime in a mixed conifer forest in Arizona, USA. We analysed the differences in pre-settlement and contemporary forest composition, structure and community-weighted mean (CWM) traits, and functional diversity metrics (Rao's Q and functional richness) for four plant functional traits: leaf nitrogen content (leaf N), specific leaf area (SLA), wood density and bark thickness. 3. We observed significant shifts in forest composition, structure, CWM traits and functional diversity from 1880 to 2011. These changes reflect a reduction in fire and drought tolerance, driven largely by increases in the relative importance of Abies concolor and Pinus strobiformis. Compositional changes were associated with declines in CWM leaf N, SLA, wood density and bark thickness. We found lower multitrait functional diversity (Rao's Q) in contemporary forests driven primarily by leaf N; however, bark thickness variation was greater in contemporary forests than in 1880. 4. Synthesis and applications. Compositional shifts towards reduced average bark thickness and wood density in contemporary forests driven by land-use change have likely reduced forest resilience to both fire and drought. Managers can manipulate forest structure and species composition to achieve functional objectives by increasing stand-level bark thickness to promote fire tolerance and increasing stand-level wood density to promote drought tolerance. Forecasts for extended fire seasons along with declining precipitation are projected for many ecosystems around the planet. A focus on restoring optimal functional trait combinations may be as important as managing ecosystem structure for restoring resilient ecosystems.

It has been suggested that large, high-severity fires historically structured warm–dry mixed conifer forests in the American South-west. To test this, we reconstructed fire regime characteristics of an 1135-ha (11.3 km2) mixed conifer landscape in northern Arizona using complementary approaches. We analysed composite fire intervals, point fire intervals, natural fire rotation, landscape characteristics and forest age structure. Composite analysis of cross-dated fire scars from 133 trees indicated a mean fire interval (MFI) of 2.0–8.5 years between 1670 and 1879. Frequent fires halted abruptly after 1879. Mean point fire interval (MPFI) was 11.8 years and ranged 2–61 years. Mean fire rotation was 14.4 years. Density of most occurring tree species increased dramatically after fire regime disruption, with south-western white pine (Pinus strobiformis) and white fir (Abies concolor) showing large numerical gains. Tree establishment patterns compared with widespread fire dates did not suggest historical high-severity fires at the site level. Although strong evidence of high-severity fire at finer scales was lacking, spatial locations of ‘young’ plots suggested the possibility of historical high-severity disturbances ≤25 ha in size. The historical fire regime on this landscape was one of high-frequency, low-severity fires. Current conditions call for restoration of forest structure and function.