Camouflage via leaf mottling among North American Erythronium species increases with forest cover and deer abundance.

Brocket deer inhabit two of the most threatened ecosystems in Mexico: the cloud forest and tropical evergreen forest, due to the lack of studies little is known about their current condition. However it is believed that it is threatened by various factors among them hunting, loss and fragmentation of habitat. In this paper we established a conceptual model a priori about the relationships between deer and their habitat where we included elements of microhabitat and landscape to determine how it affects the abundance and distribution of brocket deer in the mountains of the state of Hidalgo, Mexico. We selected 14 different forested sites, in each we established two transects 250 m long where the relative abundance of tracks was estimated. During April 2011 to March 2012 three sampling visit were made in each transect. In the transects we measured: forest structure, protective cover, low tree and shrub layer. For each site we considered the size and shape of the fragments and their matrix. To determine which variables influenced the abundance of tracks we used general linear regression models. 352 brocket deer tracks were recorded in 21 km of linear transects. The average relative abundance was 16.76 tracks/km. More tracks were found in sites with higher tree density 0.4 trees / m2, 60 % canopy cover, 70 % protection cover for fawns and 50 % for adults, higher linear density 0.5 ind / 25m and shrub richness of more than four species. The abundance of deer had a positive linear relationship with the density of tree coverage to protect adults and brocket deer importance value of edible trees (P < 0.001). The estimated abundance of tracks was higher than the reported in other sites. Our data suggest that the sites C2, C4 and C7 were better suited for deer use and possibly their movements to other sites attracted by some crops, but more specific studies would be necessary like radio-telemetry to test this assumption. This research indicated that brocket deer behaves like a forest specialist, as their abundance and welfare depends on food availability, habitat quality in terms of forest cover and the remoteness of settlements, which are generally the best preserved and most inaccessible fragments.

Long-term variation in white-tailed deer abundance shapes landscape-scale population dynamics of forest-breeding birds

Quaternary History of Deciduous Forests of Eastern North America and Europe

Using plant–herbivore–decomposer trophic chains as an example, we have tried to clarify the key roles of multitrophic interactions in species diversity. The interactions included two‐link (herbivore–decomposer and decomposer–plant) and three‐link (decomposer–herbivore–plant) chains within a community. Specifically, we investigated how sika deer abundance impacted dung beetle populations via dung supply and vegetation changes by surveying deer and beetle abundance and community composition monthly in Japan. The forest sites were similar in canopy cover, but differed in the presence (sites A and B) or absence (sites C) of an understory and in the abundance of deer (rare at site A, moderate at sites B and C, and common at site D). Site D was patchy grassland. Beetle species fell into two groups based on whether they were more abundant at sites with more dung or at sites with an understory. We suspect that the type of dung usage and/or beetle body size affected this finding. First, one beetle group was more strongly affected by vegetation cover than dung supply, and they were mostly dwellers. The other group was affected by dung supply more than vegetation cover and comprised mostly tunnelers. Dwellers may be strongly negatively affected by decreased understory vegetation because of dung drying. Second, large beetle species were positively affected by decreasing vegetation cover and increasing dung supply; understory vegetation may negatively affect mobility in larger species. Our results suggested that increased deer abundance had both positive and negative as well as direct and indirect effects on the dung beetle community by increasing the dung supply and changing the vegetation structure, respectively. Moreover, dung beetle species responded differently depending on their ecological requirements and body sizes.

We examined the ecological factors influencing winter abundance of mammals in the natural deciduous forest and the Japanese larch, Larix leptolepis, plantation in Mount Maehwa, Hongcheon, South Korea. We counted the tracks of five mammal species — the Korean hare, Lepus coreanus; the raccoon dog, Nyctereutes procyonoides; the Siberian weasel, Mustela sibirica; the water deer, Hydropotes inermis and the wild boar, Sus scrofa — in the snow from November 2013 to February 2014. We showed that the mean basal area, canopy cover and shrub cover were significantly higher in the Japanese larch plantation than in the natural deciduous forest. The winter abundances of Korean hares, raccoon dogs and water deer were higher in the Japanese larch plantation than in the natural deciduous forest. The results of stepwise analysis revealed that the winter abundances of four species were significantly correlated with ≥ 1 of the habitat variables. The winter abundances of Korean hares, water deer and wild boars were significantly correlated with shrub cover. The winter abundances of Korean hares, raccoon dogs and wild boars were significantly correlated with fallen logs; and the winter abundance of water deer was significantly correlated with canopy cover. For all of the investigated species, the preferred winter habitat was the Japanese larch plantation, with dense shrub cover and high number of fallen logs. Our results indicate that for planning conservation and forest management strategies for mammal species, the preferred forest habitat variables must be taken into consideration.

Modelling white-tailed deer impacts on forest regeneration to inform deer management options at landscape scales

There is global concern about tropical forest degradation, in part, because of the associated loss of biodiversity. Communities and indigenous people play a fundamental role in tropical forest management and are often efficient at preventing forest degradation. However, monitoring changes in biodiversity due to degradation, especially at a scale appropriate to local tropical forest management, is plagued by difficulties, including the need for expert training, inconsistencies across observers, and lack of baseline or reference data. We used a new biodiversity remote-sensing technology, the recording of soundscapes, to test whether the acoustic saturation of a tropical forest in Papua New Guinea decreases as land-use intensity by the communities that manage the forest increases. We sampled soundscapes continuously for 24 hours at 34 sites in different land-use zones of 3 communities. Land-use zones where forest cover was fully retained had significantly higher soundscape saturation during peak acoustic activity times (i.e., dawn and dusk chorus) compared with land-use types with fragmented forest cover. We conclude that, in Papua New Guinea, the relatively simple measure of soundscape saturation may provide a cheap, objective, reproducible, and effective tool for monitoring tropical forest deviation from an intact state, particularly if it is used to detect the presence of intact dawn and dusk choruses.

We assessed the size and composition of the seed bank in 31 plots representing a range of habitats within an old-growth, temperate deciduous forest at Mont St. Hilaire, Québec, Canada. We identified 49 taxa in the seed bank, with an average of 40 species·m-2 and a median density of 1218 seeds·m-2. The most frequent seeds were species of Carex and Rubus, Diervilla lonicera, and Eupatorium rugosum, while seeds of Carex were the most numerous overall. Of the 12 species in the seed bank not found in the forest, 11 were found growing on the developed landscape surrounding this 10-km2 forest fragment. These nonforest species were numerically only a minor component of the forest seed bank. Vernal herbs were not in the seed bank, and there were only a few tree species. Variation in seed bank richness among habitats was correlated positively with canopy cover, soil moisture, and soil nutrients, but not with the seed bank density or total number of species in the aboveground vegetation. Seed bank density increased with plot soil moisture. Woody species predominated in the seed bank of plots with richer soils, deeper litter, and more closed canopies. Herbaceous species predominated in the seed bank of plots with more open canopies, more mesic water regimes, and greater species richness in the aboveground vegetation. Contrary to earlier results suggesting forest seed banks primarily include shade-intolerant species associated with canopy disturbance or secondary succession, the seed bank in this old-growth, primary forest contains many shade-tolerant forest species.Key words: seed bank, old-growth forest, primary forest, temperate deciduous forest, habitat diversity, seed dispersal.

Drought and insect disturbances have resulted in widespread forest dieback in the forests of Central Europe since 2018. However, the implications of these changes in forest cover on the vertical structure, such as the canopy cover of the overstorey and understorey, have yet to be investigated at a large scale. By making use of the Global Ecosystem Dynamic Investigation (GEDI) spaceborne waveform lidar, we show here that overstorey canopy cover has declined and understorey canopy cover has increased in both coniferous and broadleaved protected forests in Central Europe since 2019. The observed loss of overstorey canopy cover is consistent with results from other remote sensing-based forest monitoring products. However, only GEDI has the capability to detect the increase in understorey canopy cover. For example, in Harz Mountains in Germany, overstorey canopy cover decreases by approximately 4.45 % per year in coniferous forests and by approximately 1.57 % per year in broadleaved forests, while understorey canopy cover increases by approximately 1.18 % and 0.59 %, respectively. For coniferous forests, we find that changes in overstorey canopy cover have a significant negative correlation (r = – 0.78, p < 0.01) with changes in understorey canopy cover. However, this relationship is not significant for broadleaved forests. This implies that canopy mortality in coniferous forests is more likely to trigger succession in the understorey than in broadleaved forests. This study demonstrates a new perspective for monitoring the dynamics of forest overstorey and understorey using spaceborne lidar, which can help improve understanding of feedbacks between forests and climate. • Monitoring the change of forest vertical canopy cover with GEDI. • Decrease in overstorey and increase in understorey canopy cover of protected forests in Central Europe. • Understorey growth rises as overstorey canopy cover declines in coniferous forests.

Impacts of heat and drought on the dynamics of water fluxes in a temperate deciduous forest from 2012 to 2020

Recent studies suggest that fire regimes will be altered in response to climate change, leading to increased frequency and intensity of wildfires in fire-prone areas, as well as expansion into previously unaffected regions. In the Mediterranean region, projected weather conditions, combined with existing vegetation patterns, are expected to contribute to more frequent and severe wildfires. Portugal has already experienced catastrophic consequences of these extreme circumstances in 2003, 2005, and 2017, with large wildfires causing extensive economic, environmental, and human losses. The characterization and mapping of fuels are recognized as critical factors in wildfire prevention and planning. Fuel management is a direct method for reducing fire risk, and fire behavior simulators (e.g., FARSITE, FlamMap) are valuable tools for supporting fire and fuel management decisions. However, the accuracy of simulation outputs depends heavily on the availability of precise fuel data. High-quality information on variables such as canopy height (CH), canopy cover (CC), canopy base height (CBH), canopy bulk density (CBD), and canopy fuel load (CFL) is essential for accurate wildfire management decisions. The overarching objective of this study had two main components: i) evaluating the utility of ICESat-2 data for estimating key fuel-related variables, and ii) creating a comprehensive map of these variables at a 25-meter resolution by integrating ICESat-2 data with other remotely sensed datasets such as Sentinel-1, Sentinel-2, ALOS2/PALSAR2, and SRTM. To achieve the first goal, a three-step approach was implemented: (i) modeling fuel-related variables using field-based vegetation measurements and ALS-derived metrics; (ii) generating ALS-based estimates of key fuel-related variables to provide ground-truth information across the study area; and (iii) assessing the utility of ICESat-2 ATL08 canopy height and cover metrics for estimating key fuel-related variables. An error analysis regarding the ICESat-2 derived estimates for the key fuel-related variables and the ICESat-2 standard CH estimates was performed to understand how different factors (e.g. land cover type, canopy cover, and slope) could affect the performance of the estimates. For the second objective, the Google Earth Engine cloud-computing platform was used to preprocess, mosaic, and retrieve Sentinel-1, Sentinel-2, PALSAR-2, and topographical data. Additionally, it was utilized to compute a suite of vegetation indices and textural metrics (GLCM). The Random Forest machine learning algorithm was then applied to predict each of the fuel-related variables using the aforementioned multisource satellite data. In this presentation, we will discuss the primary strengths and limitations of ICESat-2 data in providing useful and accurate information about key fuel-related metrics in a semi-arid Mediterranean landscape.This presentation will be conducted under the scope of the FUEL-SAT project (PCIF/GRF/0116/2019) as the main findings here reported were collected and processed within this project.

Relative abundance of Roe deer (Capreolus pygargus) related to overstory structure and understory food resources in Northeast China

Temperate forests represent one of the major biomes on Earth. They are most common in eastern North America, western and central Europe, and northeastern Asia, where the climate is defi ned by warm summers, cold winters, and intermediate levels of precipitation. To a lesser extent, they are also present in this same climate in Australia, New Zealand, South America, and South Africa. Temperate forests are dominated by either deciduous or evergreen canopies. In temperate deciduous forests, more commonly found in the Northern Hemisphere, plants drop their leaves in autumn, allowing for high seasonal variation in light availability to the understory. By contrast, in temperate evergreen forests, which are more commonly found in the Southern Hemisphere, plants keep their leaves year round. The temperate forest biome is rich in geologic and anthropocentric history, with much of the land shaped by glacial and human activity. Located in some of the most industrialized places in the world, temperate forests have been instrumental to socioeconomic development in these regions. As a consequence, these forests have been heavily impacted by expanding human populations, which remain the primary continuous threat to the structure and function of these forests.

Breeding bird response to habitat and landscape factors across a gradient of savanna, woodland, and forest in the Missouri Ozarks

Forest canopy cover (CC) and above-ground biomass (AGB) are important ecological indicators for forest monitoring and geoscience applications. This study aimed to estimate temperate forest CC and AGB by integrating airborne LiDAR data with wall-to-wall space-borne SPOT-6 data through geostatistical modeling. Our study involved the following approach: (1) reference maps of CC and AGB were derived from wall-to-wall LiDAR data and calibrated by field measurements; (2) twelve discrete LiDAR flights were simulated by assuming that LiDAR data were only available beneath these flights; (3) training/testing samples of CC and AGB were extracted from the reference maps inside and outside the simulated flights using stratified random sampling; (4) The simple linear regression, ordinary kriging and regression kriging model were used to extend the sparsely sampled CC/AGB data to the entire study area by incorporating a selection of SPOT-6 variables, including vegetation indices and texture variables. The regression kriging model was superior at estimating and mapping the spatial distribution of CC and AGB, as it featured the lowest mean absolute error (MAE; 11.295% and 18.929 t/ha for CC and AGB, respectively) and root mean squared error (RMSE; 17.361% and 21.351 t/ha for CC and AGB, respectively). The predicted and reference values of both CC and AGB were highly correlated for the entire study area based on the estimation histograms and error maps. Finally, we concluded that the regression kriging model was superior and more effective at estimating LiDAR-derived CC and AGB values using the spatially-reduced samples and the SPOT-6 variables. The presented modeling workflow will greatly facilitate future forest growth monitoring and carbon stock assessments for large areas of temperate forest in northeast China. It also provides guidance on how to take full advantage of future sparsely collected LiDAR data in cases where wall-to-wall LiDAR coverage is not available from the perspective of geostatistics.