Forest Diversity Research Articles

Mosquito (Diptera: Culicidae) diversity and arbovirus detection across an urban and agricultural landscape

Fragmented landscapes in Mexico, characterized by a mix of agricultural, urban, and native vegetation cover, presents unique ecological characteristics that shape the mosquito community composition and mosquito-borne diseases. The extent to which landscape influences mosquito populations and mosquito-borne diseases is still poorly understood. This work assessed the effect of landscape metrics -agriculture, urban, and native vegetation cover- on mosquito diversity and arbovirus presence in fragmented tropical deciduous forests in Central Mexico during 2021. Among the 21 mosquito species across six genera we identified, Culex quinquefasciatus was the most prevalent species, followed by Aedes aegypti, Ae. albopictus, and Ae. epactius. Notably, areas with denser native vegetation cover displayed higher mosquito species richness, which could have an impact on phenomena such as the dilution effect. Zika and dengue virus were detected in 85% of captured species, with first reports of DENV in several Aedes species and ZIKV in multiple Aedes and Culex species. These findings underscore the necessity of expanding arbovirus surveillance beyond Ae. aegypti and advocate for a deeper understanding of vector ecology in fragmented landscapes to adequately address public health strategies.

Assessment of Species Composition, Diversity and Carbon Stock in a Community Managed Forest of Udaypur District of Nepal

Species composition, diversity, and carbon sock of forests are all critical factors that affect the ability of forests to provide various important ecosystem services. However, there is a notable dearth of research regarding these factors in the community forests of Udaypur district. Therefore, this research was undertaken to assess species composition, and biodiversity and quantify the carbon stock potential of the Sringar community forest (CF) of the Udaypur district of Eastern Nepal. A total of 57 circular plots of 500m2 were inventoried using a systematic random sampling method with 0.5 % sampling intensity. In the CF, 17 tree species from 15 genera and 11 families were identified. The dominant tree species, Shorea robusta observed with a maximum importance value index (IVI) (176.15). According to our study, the total biomass and carbon stock in Sringar CF were 276.98 ton ha-1 and 138.18 ton ha-1, respectively. Accurate estimation of soil carbon stocks is crucial for long-term forest management and climate change mitigation, and the integration of advanced monitoring techniques and predictive models to enhance accuracy and account for future climate projections is needed.

Tree species diversity in managed Acadian forests of Eastern Canada

Maintaining forest diversity is an important value in long range management planning. This study was conducted in the ecologically diverse Acadian forest region in the Province of New Brunswick, Canada across 1.65 million hectares of publicly owned (Crown) and privately owned (Freehold) land. Tree species diversity using Hill numbers was evaluated across 21 forest type/age class combinations (groups) using 1691 sample plots to assess tree species richness (0D), typical species (1D), and abundant species (2D). Across the entire study area there were 0D = 31.0 total tree species observed, 1D = 11.5 typical species, and 2D = 7.0 abundant species. Among the 21 forest types/age class combinations, the Hill numbers ranged from 0D = 16.0–28.3, 1D = 5.6–11.5, and 2D = 3.5–8.4. A comparison of public and private land ownerships showed minor differences in tree species diversity at the landscape level. More intensively managed forest types (e.g., planted stands and naturally regenerated stands with silvicultural interventions) had similar levels of landscape-scale tree species diversity as comparable forest stands receiving no silvicultural interventions. This suggests that current management practices are maintaining tree species diversity across the landscape and highlights the importance of tailored management regimes for different forest types to support this diversity.

Socioeconomic Disparities in Urban Forest Diversity and Structure in Green Areas of Santiago de Chile.

Urban trees enhance biodiversity, provide ecosystem services, and improve quality of life in cities. Despite their benefits, trees are not distributed equitably, and many cities exhibit a "luxury effect". Given the importance of public green space for providing access to urban tree benefits, we investigated the relationship between socioeconomic level and tree diversity and structure in 60 green areas in Santiago de Chile. Species richness and total tree abundance did not significantly vary among socioeconomic levels; however, a differential effect was found according to species origin. Introduced tree species exhibited similar abundance and species richness across socioeconomic levels, but native tree species were more abundant and richer in higher socioeconomic level areas compared to lower ones. Tree cover was higher in the high and medium socioeconomic level areas than in the low socioeconomic level area. A higher average DBH was found in the medium socioeconomic level area, which may be explained by older neighborhoods and a legacy of the luxury effect. Our findings reveal that socioeconomic groups are associated with differences in tree cover, width, and the number of native species in public green areas. Consequently, urban residents have different provisions of ecosystem services and opportunities to interact with natural heritage. Increasing the amount of tree cover and native species available to vulnerable groups will reduce disparities.

Natural forests support higher mycological diversity and more edible mushroom species than plantation forests in Ethiopia

Abstract To identify measures to protect and conserve macrofungal communities in Ethiopian forests, we need a more comprehensive understanding of macrofungal diversity, functions, and fruiting body production. In this study, we assessed macrofungal communities in three forest types in Gambo Forest District, South-Central Ethiopia. We surveyed 18 plots (each 1000 m2) located in a clear-cut and replanted plantation forest, an old plantation forest, and a natural forest. We identified a total of 132 macrofungal species, of which 75% were saprotrophic, 16% were ectomycorrhizal, and 9% were plant pathogens. We identified 40 edible species, including economically important species, such as those from the genus of Agaricus, Morchella, Cantharellus, Suillus, and Termitomyces. The three forests were significantly different (P < .001) in terms of their macrofungal community composition, with natural forest having the highest species richness and unique community assemblages. In total, 86 macrofungal species were collected from natural forest, of which 28 species were edible. The macrofungal diversity of clear-cut and old plantation forests did not differ significantly. Our findings suggest that prioritizing the restoration or preservation of fragmented natural forests rather than the expansion of exotic tree plantations would be a more effective strategy for conserving and enhancing macrofungal species diversity and the production of economically valuable edible species.

Assessment of Mycological Possibility Using Machine Learning Models for Effective Inclusion in Sustainable Forest Management

The integral role of wild fungi in ecosystems, including provisioning, regulating, cultural, and supporting services, is well recognized. However, quantifying and predicting wild mushroom yields is challenging due to spatial and temporal variability. In Mediterranean forests, climate-change-induced droughts further impact mushroom production. Fungal fruiting is influenced by factors such as climate, soil, topography, and forest structure. This study aims to quantify and predict the mycological potential of Lactarius deliciosus in sustainably managed Mediterranean pine forests using machine learning models. We utilize a long-term dataset of Lactarius deliciosus yields from 17 Pinus pinaster plots in Soria, Spain, integrating forest-derived structural data, NASA Landsat mission vegetation indices, and climatic data. The resulting multisource database facilitates the creation of a two-stage ‘mycological exploitability’ index, crucial for incorporating anticipated mycological production into sustainable forest management, in line with what is usually done for other uses such as timber or game. Various Machine Learning (ML) techniques, such as classification trees, random forest, linear and radial support vector machine, and neural networks, were employed to construct models for classification and prediction. The sample was always divided into training and validation sets (70-30%), while the differences were found in terms of Overall Accuracy (OA). Neural networks, incorporating critical variables like climatic data (precipitation in January and humidity in November), remote sensing indices (Enhanced Vegetation Index, Green Normalization Difference Vegetation Index), and structural forest variables (mean height, site index and basal area), produced the most accurate and unbiased models (OAtraining = 0.8398; OAvalidation = 0.7190). This research emphasizes the importance of considering a diverse array of ecosystem variables for quantifying wild mushroom yields and underscores the pivotal role of Artificial Intelligence (AI) tools and remotely sensed observations in modeling non-wood forest products. Integrating such models into sustainable forest management plans is crucial for recognizing the ecosystem services provided by them.

Drivers of wood-inhabiting fungal diversity in European and Oriental beech forests.

The hyperdiverse wood-inhabiting fungi play a crucial role in the global carbon cycle, but often are threatened by deadwood removal, particularly in temperate forests dominated by European beech (Fagus sylvatica) and Oriental beech (Fagus orientalis). To study the impact of abiotic drivers, deadwood factors, forest management and biogeographical patterns in forests of both beech species on fungal composition and diversity, we collected 215 deadwood-drilling samples in 18 forests from France to Armenia and identified fungi by meta-barcoding. In our analyses, we distinguished the patterns driven by rare, common, and dominant species using Hill numbers. Despite a broad overlap in species, the fungal composition with focus on rare species was determined by Fagus species, deadwood type, deadwood diameter, precipitation, temperature, and management status in decreasing order. Shifting the focus on common and dominant species, only Fagus species, both climate variables and deadwood type remained. The richness of species within the deadwood objects increased significantly only with decay stage. Gamma diversity in European beech forests was higher than in Oriental beech forests. We revealed the highest gamma diversity for old-growth forests of European beech when focusing on dominant species. Our results implicate that deadwood retention efforts, focusing on dominant fungi species, critical for the decay process, should be distributed across precipitation and temperature gradients and both Fagus species. Strategies focusing on rare species should additionally focus on different diameters and on the conservation of old-growth forests.

Pest categorisation of Monema flavescens.

The EFSA Panel on Plant Health performed a pest categorisation of Monema flavescens (Lepidoptera, Limacodidae), following the commodity risk assessment of Acer palmatum plants grafted on A. davidii from China, in which M. flavescens was identified as a pest of possible concern to the European Union. This species can be identified by morphological taxonomic keys and by barcoding. The adults of the overwintering generation emerge from late June to late August. The eggs are laid in groups on the underside of the host-plant leaves, on which the larvae feed throughout their six to eight larval instars. Pupation occurs in ovoid cocoons at the junction between twigs and branches, or on the trunk. Overwintering occurs as fully grown larvae or prepupae in their cocoon. There are one or two generations per year. M. flavescens is polyphagous and feeds on broadleaves; it has been reported on 51 plant species belonging to 24 families. It mainly occurs in Asia (Bhutan, China, the Democratic People's Republic of Korea, Japan, Nepal, the Republic of Korea), Russia (Eastern Siberia) and Taiwan. It is also present in the USA (Massachusetts). The pest's flight capacities are unknown. The main pathway for entry and spread is plants for planting with cocoons attached. This is partially closed by prohibition of some hosts. In several EU member states climatic conditions are conducive for establishment and many host plants are widespread. Introduction of M. flavescens may result in defoliations influencing tree health and forest diversity. The caterpillars also have urticating spines affecting human health. Phytosanitary measures are available to reduce the likelihood of entry, establishment and spread, and there is a definite potential for classical biological control. Recognising that natural enemies prevent M. flavescens being regarded as a pest in Asia, there is uncertainty regarding the magnitude of potential impact in EU depending on the influence of natural enemies. All criteria assessed by EFSA for consideration as a potential quarantine pest are met.

Discriminating woody species assemblages from National Forest Inventory data based on phylogeny in Georgia.

Classifications of forest vegetation types and characterization of related species assemblages are important analytical tools for mapping and diversity monitoring of forest communities. The discrimination of forest communities is often based on β-diversity, which can be quantified via numerous indices to derive compositional dissimilarity between samples. This study aims to evaluate the applicability of unsupervised classification for National Forest Inventory data from Georgia by comparing two cluster hierarchies. We calculated the mean basal area per hectare for each woody species across 1059 plot observations and quantified interspecies distances for all 87 species. Following an unspuervised cluster analysis, we compared the results derived from the species-neutral dissimilarity (Bray-Curtis) with those based on the Discriminating Avalanche dissimilarity, which incorporates interspecies phylogenetic variation. Incorporating genetic variation in the dissimilarity quantification resulted in a more nuanced discrimination of woody species assemblages and increased cluster coherence. Favorable statistics include the total number of clusters (23 vs. 20), mean distance within clusters (0.773 vs. 0.343), and within sum of squares (344.13 vs. 112.92). Clusters derived from dissimilarities that account for genetic variation showed a more robust alignment with biogeographical units, such as elevation and known habitats. We demonstrate that the applicability of unsupervised classification of species assemblages to large-scale forest inventory data strongly depends on the underlying quantification of dissimilarity. Our results indicate that by incorporating phylogenetic variation, a more precise classification aligned with biogeographic units is attained. This supports the concept that the genetic signal of species assemblages reflects biogeographical patterns and facilitates more precise analyses for mapping, monitoring, and management of forest diversity.

A Rapid Assessment of Pronophilina Reuter, 1896 community structure and diversity in the uppermost cloud forests near timberline in Manu National Park, Peru (Lepidoptera: Nymphalidae, Satyrinae)

A Rapid Assessment of Pronophilina Reuter, 1896 community structure and diversity in the uppermost cloud forests near timberline in Manu National Park, Peru (Lepidoptera: Nymphalidae, Satyrinae)

Diversity, structure and dynamics of tropical montane forests: Insights from permanent-plot monitoring in the Venezuelan Andes

Diversity, structure and dynamics of tropical montane forests: Insights from permanent-plot monitoring in the Venezuelan Andes

High-resolution mapping of tree species and associated uncertainty by combining aerial remote sensing data and convolutional neural networks ensemble

Mapping tree species diversity is essential for monitoring and managing forest ecosystems. Automating ecoforestry mapping using remote sensing images remains an important challenge due to the tremendous variability in forest covers and the conditions under which images used for classification are acquired. Deep learning algorithms have been increasingly used over the last few years to analyse remote sensing data for mapping tree species. However, most of these studies focus only on a small number of species or a limited area and avoid providing a spatially explicit representation of the uncertainty related to the predictions, rendering them unsuitable for operational use.In this study, we used an ensemble of convolutional neural networks to map forest species and land cover types across a 10,000 km2 area in Quebec, Canada, spanning mixed and boreal forests. We built a georeferenced label database to train and test nine models, which resulted from the combination of three training datasets and three-commonly used convolutional neural network architectures (VGG16, ResNet50v2, Densenet121). These models were trained on multiband aerial photographs and a canopy height model derived from airborne lidar point clouds and used to map the diversity and distribution of tree species and land cover types. The level of agreement among models was used to generate uncertainty maps. The performance of the super-ensemble using 1311 independent forest inventory plots and assessed the extent to which uncertainty maps could serve as a spatially explicit indicator of model performance.The super-ensemble achieved 90% global accuracy. Our results indicated that the performance of the super-ensemble surpassed that of all individual architectures while also showing a positive effect of the canopy height model on performance. The comparison of the super-ensemble map with the proportion of basal area measured in forest inventory plots confirmed the reliability of the model over the study area. Our results also indicated that mapping the inter-model agreement provides a reliable spatially explicit estimate of model performance. The robustness and reliability of the proposed approach support its use in an operational context while also providing a conceptual framework to evaluate the reliability of uncertainty maps.

A new antshrike (Aves: Thamnophilidae) endemic to the Caatinga and the role of climate oscillations and drainage shift in shaping cryptic diversity of Neotropical seasonal dry forests

AbstractThe Caatinga is the largest patch of Seasonal Dry Tropical Forest in the Neotropics, located in northeastern Brazil and characterized mainly by deciduous vegetation and extreme rainfall seasonality. It has historically been treated as a biologically impoverished domain, but recent studies uncovered new diversification patterns and several new taxa of frogs, mammals, insects, and fishes. Here we employed a dense sampling regime to evaluate whether the São Francisco River (SFR) would have promoted genetic diversification and fixed phenotypic differences and how Quaternary climatic oscillations shaped distribution and population sizes in a Caatinga endemic species, the Silvery‐cheeked Antshrike (Sakesphoroides cristatus). We adopted an integrative approach using multilocus genetic, plumage, vocal data, and ecological niche modelling (ENM) to characterize evolutionary units and niche suitability in past scenarios. We recovered strong genetic structure across the SFR that was congruent with plumage and vocal variation, revealing a yet undescribed species named herein as Sakesphoroides niedeguidonae, sp. nov. (urn:lsid:zoobank.org:act:2B9FC637‐008A‐4E9A‐B92B‐69ED7FE23823s). The splitting time estimated between the newly described species and S. cristatus is consistent with the establishment of the modern course of SFR, with a more recent course shift apparently promoting the secondary contact between the two species in the Raso da Catarina region. After their split, both species experienced increases in population sizes and range sizes at similar times during the Last Glacial Maximum. We expect other Caatinga avian endemic lineages to show similar patterns of genetic differentiation across the SFR that were enhanced by Quaternary climatic oscillations.

STRUKTUR DAN KOMPOSISI HUTAN MANGROVE DI NEGERI HATUSUA KECAMATAN KAIRATU KABUPATEN SERAM BAGIAN BARAT

The aim of this research is to determine the structure and composition of mangrove forests in Hatusua State, Kairatu District, West Seram Regency. And vegetation analysis was carried out by collecting data on the type, number, diameter and height of trees. In this research, the path method was used by carrying out a 100% inventory. The measuring plot area for the vegetation growth level of Seedlings, Saplings and Trees is 20 m x 20 m, a total of 46 plots for a total area of ​​1.84 ha. The research results show that the mangrove forests in Hatusua State can be divided into two from inundation, namely the middle zone and the distal zone, where in this mangrove forest there is no proximal zone because there are no mangroves that face the sea. The stratification of Hatusua State's mangrove forests is simpler than that of mainland natural forests. Mangrove trees in Hatusua Country can reach a tree height of 15 – 25 meters, which are dominated by Rhizophora apiculata, Heritiera littoralis, Parmentiera cereifera, and Intsia bijuga. The Hatusua State mangrove forest diversity index value of 1.37 seedlings, 2.30 saplings and 1.36 trees is categorized as medium because the value 1 <H' < 3.

Short Communication: A rapid survey of herpetofauna diversity in Bama coastal forest at Baluran National Park, Indonesia

Abstract. Siddiq AM, Wimbaningrum R, Sulistiyowati H, Setiawan R, Setiawan A, Wahono ND. 2024. Short Communication: A rapid survey of herpetofauna diversity in Bama coastal forest at Baluran National Park, Indonesia. Biodiversitas 25: 2323-2329. Scientific reports on herpetofauna in Baluran National Park (BNP) are still limited. Meanwhile, several geographical areas, such as the Bama Baluran National Park coastal forest, have potential herpetofauna diversity within this conservation area yet to be reported. Therefore, this study aimed to determine the diversity of herpetofauna species in BNP's Bama coastal forest (BCF). The method was conducted using the Visual Encounter Survey (VES) in three tracks, conducted by combining Time Restricted Search (TRS) or using observation time for five hours during the mid-afternoon (06.00 AM-11.00 AM) and four hours at night (07.00 PM-11.00 PM) on each track. This study recorded 17 herpetofauna species, comprising 6 amphibian and 11 reptile species, in the BCF of Baluran National Park. The diversity index of herpetofauna species in this area was moderate category (H’=2.25). Species Fejervarya limnocharis Gravenhorst 1829 (38 individuals) has the highest abundance in the BCF and was found in track 1 (swamp area). Meanwhile, three species have the lowest abundance, such as Kaloula baleata Müller 1836, Microhyla palmipes Boulenger 1897, and Cryptoblepharus balinensis Barbour 1911, with 1 individual in each species.

Feasibility of using Ku-band helicopter-borne microwave radar for stem volume and biomass estimation in boreal forest

Under the global climate challenges, accurate assessment of forest variables is becoming increasingly important for effective forest management and monitoring. While long-wavelength satellite radar data (P-, L-band) has been widely used for this purpose, the potential of airborne Ku-band microwave radar remains underexplored. In this paper, an airborne Ku-band frequency modulated continuous wave (FMCW) profiling radar data was used to predict forest variables including plot-level basal-area weighted mean canopy height (Hg), mean diameter at breast height (DBHg), stem volume (V) and above ground biomass (AGB) using the random forest method. In addition, the maximum canopy heights were computed from the radar-derived results. The estimated results were compared with 55 manually-measured and accurately matched field plots consisting of thousands of trees. The comparison results show that the estimation accuracy is at a good level, with the relative Root Mean Square Errors (RMSE%) and the coefficient of determination (R2) of the four variables were Hg (10.04 %, 0.75), DBHg (17.25 %, 0.63), V (21.11 %, 0.67) and AGB (19.75 %, 0.63), respectively. The estimation of plot-level maximum heights resulted in a relative RMSE of 7.95 % and R2 of 0.89. Through comparing with previous similar studies, the accuracies of estimating the four variables from airborne Ku-band data are comparable to those of high-precision satellite microwave radar data. The study results indicate that the canopy gaps and adequate penetration of airborne Ku-band signals into the canopy enable the characterization of the canopy layer and the ground floor, allowing for accurate estimation of forest variables in boreal forests.

Stand diversity increases pine resistance and resilience to compound disturbance

BackgroundDrought, fire, and insects are increasing mortality of pine species throughout the northern temperate zone as climate change progresses. Tree survival may be enhanced by forest diversity, with growth rates often higher in mixed stands, but whether tree defenses are likewise aided remains in question. We tested how forest diversity-productivity patterns relate to growth and defense over three centuries of climate change, competition, wildfire, and bark beetle attack. We used detailed census data from a fully mapped 25.6-ha forest dynamics plot in California, USA to conduct a spatially explicit, dendroecological assessment of large-diameter Pinus lambertiana survival following fire reintroduction. Our structural equation models investigated direct and indirect pathways by which growth, defense, and forest composition together mediated pine resistance and resilience.ResultsIn the historical era of frequent, mixed-severity fire (pre-1900), trees that were ultimately resistant or susceptible to the post-fire bark beetle epidemic all showed similar growth and defenses, as measured by axial resin duct traits. During the era of fire exclusion (1901–2012), however, susceptible trees had slower growth. Following fire re-entry in 2013, both growth and defense declined precipitously for susceptible trees, resulting in fatal bark beetle attack. Spatial analysis showed that monodominant crowding by shade-tolerant competitors contributed to the long-term stress that prevented susceptible trees from recuperating defenses quickly following fire re-entry. For beetle-resistant trees, however, we found positive feedbacks between diversity, growth, and survival: trees in species-rich communities had higher growth rates pre-fire, which promoted a rapid recuperation of defenses following fire that helped trees resist bark beetle attack. Overall, this associational resistance outweighed associational susceptibility (+8.6% vs. −6.4% change in individual tree survival odds), suggesting a relaxation effect that ultimately allowed 58% of large pines to survive.ConclusionsThough climate change threatens forest biodiversity, biodiversity is key to forest climate adaptation in return. Our findings demonstrate centennial-scale feedbacks by which forest diversity increases pine resistance and resilience to climate-amplified disturbances. The spatially explicit, dendroecological framework provides new insights into diversity-productivity theory, while also informing climate-adaptive forest management by identifying thresholds of tree density and richness that maximize large pine survival.

Diversity, habitat and activity patterns of mesocarnivore assemblages in an Afrotropical protected forest savannah mosaic of Central Cameroon

AbstractLittle is known about the diversity and ecology of mesocarnivores in the Mpem and Djim National Parks in central Cameroon. Therefore, we undertook a rapid assessment using camera traps from September 2021 to December 2021. The main objective of our study was to collect data on the diversity, abundance and relative frequency of mesocarnivores per habitat type and their activity period using camera traps with a distance sampling method. In 1700 trap nights, we recorded 53 events of seven mesocarnivores, all belonging to the family of Viveridae, Herpesdidae and Felidae which yield 3.12 mesocarnivores per 100 days. The black‐legged mongoose (Bdeogale nigripes, Pucheran, 1855) exhibited the highest capture rate (CR, 0.88). The long‐nosed mongoose (Xenogale naso, Winton, 1901) was found in all habitats class and was the more active mesocarnivore. The Shannon‐Weaver diversity index (H) showed a high diversity of species in the community with high diversity in the near primary forest. We obtained a lower dominance of one species over the other, a lower richness and a more even distribution of species between habitats. Our results suggest a possible spatio‐temporal niche partitioning between the species recorded, with blotched genet (Genetta maculata, Gray, 1830), showing no clear peak of activity. However, the rarefaction curve indicates that the effort expended was insufficient, suggesting that additional sampling is required to obtain a reasonable estimate of species richness within our community. The activity patterns of the recorded mesocarnivores were generally similar to those reported elsewhere but suggest some behavioural flexibility. Although all these species are listed as Least Concern by the IUCN, the low number of recorded events may indicate that mesocarnivores may be threatened in this area if effective conservation strategies are not implemented.

Restoring frequent fire to dry conifer forests delays the decline of subalpine forests in the southwest United States under projected climate

Abstract In southwestern US forests, the combined impact of climate change and increased fuel loads due to more than a century of human‐caused fire exclusion is leading to larger and more severe wildfires. Restoring frequent fire to dry conifer forests can mitigate high‐severity fire risk, but the effects of these treatments on the vegetation composition and structure under projected climate change remain uncertain. We used a forest landscape model to assess the impact of thinning and prescribed burns in dry conifer forests across an elevation gradient, encompassing low‐elevation pinyon‐juniper woodlands, mid‐elevation ponderosa pine and high‐elevation mixed‐conifer forests. Our results demonstrated that the treatments decreased the probability of high‐severity fires by 42% in the study area. At low elevation, the treatments did not prevent loss in forest cover and biomass with decreases in Pinus edulis and Juniperus monosperma abundances. At mid‐elevation, changes in fire effects maintained a greater diversity of tree species by favouring the maintenance of cohorts of old trees, in particular Pinus ponderosa which accumulated 5.41 Mg ha−1 more above‐ground biomass than without treatments by late‐century. Treatments in dry conifer forests modified fire effects beyond the treated area, resulting in increased cover and biomass of old Picea englemannii and Abies lasiocarpa cohorts. Synthesis and applications: Our findings indicate that thinning and prescribed burning can enhance tree species diversity in dry conifer forests by protecting old cohorts from stand‐replacing fires. Moreover, our results suggest that treatments mainly implemented in dry pine forests with high risk of high‐severity fires can be beneficial for subalpine species conservation by reducing the chance that high‐severity fire at mid‐elevation is transmitted into high‐elevation forest.

Floral richness drives pollinator diversity after fire in upland forests and meadows of the Sierra Nevada, California

Abstract There are concerns over the effects of increasingly large and high‐severity fires that burn outside the local natural range of variation on ecosystem services and biodiversity. Pollinators provide important ecosystem services in the dry forests of the western United States where they depend on open habitat created or maintained by frequent, low‐ to moderate‐severity fire. We investigated the impact of burn severity on pollinator diversity in upland forest and meadow habitat at local (i.e., at the plot scale) and regional (burn severity class) spatial scales in the Sierra Nevada of California. In meadows, pollinator richness declined with increasing burn severity, but in uplands, there was no significant effect of burn severity on pollinator richness. Absence of pollinators was more likely to occur in unburned or high‐severity uplands. At the regional scale, we found that α was similar among burn classes in both habitats, although communities in burned uplands tended to be less even than unburned uplands. β was significantly higher in moderately burned than unburned upland habitat, but there were no significant differences in β for meadow habitats. Because meadows tend to be both more diverse and more sensitive to the negative impacts of high‐severity fire than uplands, conservation measures for pollinators could prioritise the removal of encroaching conifer species that may increase fire severity in these systems.