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412 results for “temperate forests”
Data from: Accounting for predator species identity reveals variable relationships between nest predation rate and habitat in a temperate forest songbird
<p><strong>Abstract</strong></p> <p>Nest predation is the primary cause of nest failure in most ground-nesting bird species. Investigations of relationships between nest predation rate and habitat usually pool different predator species. However, such relationships likely depend on the specific predator involved, partly because habitat requirements vary among predator species. Pooling may therefore impair our ability to identify conservation-relevant relationships between nest predation rate and habitat. We investigated predator-specific nest predation rates in the forest-dependent, ground-nesting wood warbler <em>Phylloscopus sibilatrix </em>in relation to forest area and forest edge complexity at two spatial scales, and to the composition of the adjacent habitat matrix. We used camera traps at 559 nests to identify nest predators in five study regions across Europe. When analysing predation data pooled across predator species, nest predation rate was positively related to forest area at the local scale (1,000 m around nest), and higher where proportion of grassland in the adjacent habitat matrix was high but arable land low. Analyses by each predator species revealed variable relationships between nest predation rates and habitat. At the local scale, nest predation by most predators was higher where forest area was large. At the landscape scale (10,000 m around nest), nest predation by buzzards <em>Buteo buteo</em> was high where forest area was small. Predation by pine martens Martes martes was high where edge complexity at the landscape scale was high. Predation by badgers <em>Meles meles </em>was high where the matrix had much grassland but little arable land. Our results suggest that relationships between nest predation rates and habitat can depend on the predator species involved and may differ from analyses disregarding predator identity. Predator-specific nest predation rates, and their relationships to habitat at different spatial scales, should be considered when assessing the impact of habitat change on avian nesting success.</p>
Urbanization and fragmentation have opposing effects on soil nitrogen availability in temperate forest ecosystems.
Nitrogen (N) availability relative to plant demand has been declining in recent years in terrestrial ecosystems throughout the world, a phenomenon known as N oligotrophication. The temperate forests of the northeastern U.S. have experienced a particularly steep decline in bioavailable N, which is expected to be exacerbated by climate change. This region has also experienced rapid urban expansion in recent decades that leads to forest fragmentation, and it is unknown whether and how these changes affect N availability and uptake by forest trees. Many studies have examined the impact of either urbanization or forest fragmentation on nitrogen (N) cycling, but none to our knowledge have focused on the combined effects of these co-occurring environmental changes. We examined the effects of urbanization and fragmentation on oak-dominated (Quercus spp.) forests along an urban to rural gradient from Boston to central Massachusetts (MA). At eight study sites along the urbanization gradient, plant and soil measurements were made along a 90 m transect from a developed edge to an intact forest interior. Rates of net ammonification, net mineralization, and foliar N concentrations were significantly higher in urban than rural sites, while net nitrification and foliar C:N were not different between urban and rural forests. At urban sites, foliar N and net ammonification and mineralization were higher at forest interiors compared to edges, while net nitrification and foliar C:N were higher at rural forest edges than interiors. These results indicate that urban forests in the northeastern U.S. have greater soil N availability and N uptake by trees compared to rural forests, counteracting the trend for widespread N oligotrophication in temperate forests around the globe. Such increases in available N are diminished at forest edges, however, demonstrating that forest fragmentation has the opposite effect of urbanization on coupled N availability and demand by trees.
Data in Support of Effects of Urbanization and Forest Fragmentation on Atmospheric Nitrogen Inputs and Ambient Nitrogen Oxide and Ozone Concentrations in Mixed Temperate Forests.
Urban ecosystems around the globe experience greater atmospheric nitrogen (N) deposition compared to rural areas and are particularly vulnerable to fragmentation due to land-use change. However, while the influences of urbanization and forest fragmentation on atmospheric inputs to temperate forests have been determined separately, the combined effects of the two changes on temperate forest ecosystems have yet to be assessed. To investigate these combined effects, we deployed throughfall collectors to measure atmospheric N inputs and passive samplers to measure nitrogen oxides (NOx) and ozone (O3) throughout the 2018 and 2019 growing seasons in seven temperate forest sites along an urbanization gradient from Boston to central Massachusetts. We found a positive relationship between the amount of impervious surface area surrounding each site (% ISA) and throughfall nitrate (NO3-) inputs at the forest edge, with urban edge NO3- inputs nearly double the rate at rural edge sites. There were higher rates of NO3- inputs in the rural forest interior than edge sites. Urban sites experienced significantly higher concentrations of NOx and O3 both in the interior and at the edge compared to rural sites. Atmospheric N inputs were significantly elevated in the early (May-July) compared to the late (August-November) growing season and concentrations of NOx and O3 were also elevated in the mid-growing season (June-September). Our results demonstrate that together, urbanization and forest fragmentation lead to greater rates of atmospheric N inputs and ambient pollutant concentrations of NOx and O3 in temperate forests of the northeastern U.S.
Multiple Element Limitation in Northern Hardwood Ecosystems (MELNHE): Nitrogen and phosphorus additions affect fruiting of ectomycorrhizal fungi in a temperate hardwood forest, 2018
The functioning of mycorrhizal symbioses is tied to soil nutrient status, suggesting that nutrient availability should influence the reproduction of mycorrhizal fungi. To quantify the effects of nitrogen (N) and phosphorus (P) availability on ectomycorrhizal fungal fruiting, we collected > 4,000 epigeous sporocarps representing 19 families during the course of a season in a full factorial NxP addition experiment in six replicate forest stands. Nutrient effects on fruiting shifted as the season progressed, with early fruiting species responding more to P and late-fruiting species responding more to N. The composition of species fruiting in young successional forests differed more with nutrient addition than in mature forests. Sporocarp abundance and species richness were suppressed by N addition. This work shows that N and P availability affect ectomycorrhizal fungal fruiting, with these effects taking place within a context defined by stand age and the progression of fruiting across the season. The data table in this data package contains the sprorocarp observation counts and biomass. Corresponding DNA sequences can be found in GenBank at: https://www.ncbi.nlm.nih.gov/nuccore/?term=MT345178%3AMT345282%5Baccn%5D Additional detail on the MELNHE project, including a datatable of site descriptions and a pdf file with the project description and diagram of plot configuration can be found in this data package: https://portal.edirepository.org/nis/mapbrowse?packageid=knb-lter-hbr.344.2 These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Tree Growth Data in support of "Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems", Conrad-Rooney et al. PNAS 2025
Data associated with the publication: Conrad-Rooney E, AB Reinmann, PH Templer. Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems. Proceedings of the National Academy of Sciences, 2025. This dataset includes cumulative stem biomass carbon data (from pre-treatment in 2012 until 2022) and annual stem biomass growth rates (not cumulative) for 2015-2022 for the red maple trees at the Climate Change Across Seasons Experiment. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Soil Temperature, Soil Frost, and Snow Depth Data in support of "Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems", Conrad-Rooney et al. PNAS 2025
Data associated with the publication: Conrad-Rooney E, AB Reinmann, PH Templer. Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems. Proceedings of the National Academy of Sciences, 2025. This dataset includes soil temperature (winter 2021-2022) and snow depth and frost depth (winter 2022-2023) at the Climate Change Across Seasons Experiment. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Data from: A new approach to map landscape variation in forest restoration success in tropical and temperate forest biomes
1. A high level of variation of biodiversity recovery within a landscape during forest restoration presents obstacles to ensure large scale, cost-effective, and long-lasting ecological restoration. There is an urgent need to predict landscape variation in forest restoration success at a global scale. 2. We conducted a meta-analysis comprising 135 study landscapes to predict and map landscape variation in forest restoration success in tropical and temperate forest biomes. Our analysis was based on the amount of forest cover within a landscape – a key driver of forest restoration success. We contrasted 17 generalized linear models measuring forest cover at different landscape sizes (with buffers varying from 5 to 200 km radii). We identified the most plausible model to predict and map landscape variation in forest restoration success. We then weighted landscape variation by the amount of potentially restorable areas (agriculture and pasture land areas) within the same landscape. Finally, we estimated restoration costs of implementing Bonn Challenge commitments in three specific temperate and tropical forest biome types in USA, Brazil and Uganda. 3. Landscape variation decreased exponentially as the amount of forest cover increased in the landscape, with stronger effects within a 5 km radius. Thirty-eight percent of forest biomes have landscapes with more than 27% of forest cover and showed levels of landscape variation below 10%. Landscapes with less than 6% of forest cover showed levels of variation in forest restoration success above 50%. 4. At the biome level, Tropical and Subtropical Moist Broadleaf Forests had the lowest (12.6%), while Tropical and Subtropical Dry Broadleaf Forests had the highest (22.9%) average of weighted landscape variation in forest restoration success. Our approach can lead to a reduction in implementation costs for each Bonn Challenge commitment between US$ 973 Mi and 9.9 Bi. 5. Policy implications. Our approach identifies landscape characteristics that increase the likelihood of biodiversity recovery during forest restoration – and potentially the chances of natural regeneration and long-term ecological sustainability and functionality. Identifying areas with low levels of landscape variation can help to reduce the risks and financial costs associated with implementing ambitious restoration commitments.
Risk response towards roads is consistent across multiple species in a temperate forest ecosystem
<p>Roads can have diverse impacts on wildlife species, and while some species may adapt effectively, others may not. Studying multiple species' responses to the same infrastructure in a given area can help understand this variation and reveal the effects of disturbance on the ecology of wildlife communities. This study investigates the behavioural responses of four species with distinctive ecological and behavioural traits to roads in the protected Bohemian Forest Ecosystem in Central Europe: European roe deer (<em>Capreolus capreolus), </em>a<em> </em>solitary herbivore; red deer (<em>Cervus elaphus</em>) a gregarious herbivore; wild boar (<em>Sus scrofa</em>), a gregarious omnivore and Eurasian lynx (<em>Lynx lynx</em>), a solitary large carnivore. We used GPS data gathered from each species to study movement behaviour and habitat selection in relation to roads using an integrated step selection analysis. For all species and sexes, we predicted increased movement rates in response to roads, selection of vegetation cover near roads and open areas after road crossings, and increased road avoidance during the day. We found remarkably similar behavioural responses towards roads across species. The behavioural adaptations to road exposure, such as increased movement rates and selection for vegetation cover, were analogous to responses to natural predation risk. Roads were more strongly avoided during daytime, when traffic volume was high. Road crossings were more frequent at twilight and at night within open areas offering food resources. Gregarious animals exposed to roads favoured stronger road avoidance over faster movements. Ungulates crossed roads more at twilight, coinciding with commuter traffic during winter. Despite differences in the ecology and behaviour of the four species, our results showed similar adaptations towards a common threat. These insights can be used by managers to promote safer road crossings where roads interfere with animals' natural behaviour. The continuous expansion of the global transportation network should be accompanied by efforts to understand and minimise the impact of roads on wildlife to assist wildlife management and ensure conservation.</p>
Mapping Tree Species Fractions in Temperate Mixed Forests Using Sentinel-2 Time Series and Synthetically Mixed Training Data
<p>This dataset contains the latest version of a selection of result data of the paper "Mapping Tree Species Fractions in Temperate Mixed Forests Using Sentinel-2 Time Series and Synthetically Mixed Training Data" (DOI: https://doi.org/10.1016/j.rse.2025.114740 )</p> <p>The dataset contains:</p> <ol> <li>A geopackage of training points of pure tree species</li> <li>The resulting 12-band tree species fraction map of Rhineland-Palatinate</li> <li>HSV-colored map of dominant tree species. For information which tree species are represented by the different colors, refer to the Supplemental in the original paper.</li> <li>CSV-table of predicted and reference propotion of the tree species in the validation polygon (the original polygon data can not be published due to data privacy regulations) </li> </ol> <p> </p>
Data from: Context matters: the landscape matrix determines the population genetic structure of temperate forest herbs across Europe
<p>Context. Plant populations in agricultural landscapes are mostly fragmented and their functional connectivity often depends on seed and pollen dispersal by animals. However, little is known about how the interactions of seed and pollen dispersers with the agricultural matrix translate into gene flow among plant populations.</p> <p>Objectives. We aimed to identify effects of the landscape structure on the genetic diversity within, and the genetic differentiation among, spatially isolated populations of three temperate forest herbs. We asked, whether different arable crops have different effects, and whether the orientation of linear landscape elements relative to the gene dispersal direction matters.</p> <p>Methods. We analysed the species' population genetic structures in seven agricultural landscapes across temperate Europe using microsatellite markers. These were modelled as a function of landscape composition and configuration, which we quantified in buffer zones around, and in rectangular landscape strips between, plant populations.</p> <p>Results. Landscape effects were diverse and often contrasting between species, reflecting their association with different pollen- or seed dispersal vectors. Differentiating crop types rather than lumping them together yielded higher proportions of explained variation. Some linear landscape elements had both a channelling and hampering effect on gene flow, depending on their orientation.</p> <p>Conclusions. Landscape structure is a more important determinant of the species' population genetic structure than habitat loss and fragmentation <i>per se</i>. Landscape planning with the aim to enhance the functional connectivity among spatially isolated plant populations should consider that even species of the same ecological guild might show distinct responses to the landscape structure.</p>
Sapling regeneration within canopy gaps in a temperate montane riparian forest.
<p>This is a dataset of sapling regeneration within canopy gaps in a temperate montane riparian forest.</p> <p>The followings are details of each file.</p> <p><strong>GapSeedlings_v1.0.0.csv</strong></p> <ul> <li><code>Plot</code> Integer. The ID of plots, some plots include more than one gap.</li> <li><code>Gap</code> Factor. The ID of gaps.</li> <li><code>Quadrat</code> Integer. The ID of quadrats within a gap.</li> <li><code>stemID</code> Character. The ID of stems.</li> <li><code>Sp.</code> Factor. The species names.</li> <li><code>Family</code> Factor. The family name of the species.</li> <li><code>Substrate</code> Factor. Established substrates. NA means that it was not recorded.</li> <li><code>Heightyyyy</code> Numeric. Vertical heights of trees (cm) in yyyy. The individuals with <code>CensusIn2020</code> = 0, their <code>Height2020</code> is NA because they had not been censused in 2020.</li> <li><code>Lengthyyyy</code> Numeric. Length of trees (cm) in yyyy. The individuals with <code>CensusIn2020</code> = 0, their <code>Length2020</code> is NA because they had not been censused in 2020.</li> <li><code>DBH1_yyyy</code>, <code>DBH2_yyyy</code> Numeric. Diameter at breast height (mm) in yyyy. DBH1 and DBH2 were measured to cross at right angles. The individuals with <code>CensusIn2020</code> = 0, their <code>DBH2020_1</code> and <code>DBH2020_2</code> are NA because they had not been censused in 2020.</li> <li><code>Cmtyyyy</code> Character. Comments in yyyy.</li> <li><code>CensusIn2020</code> Factor. 1 means that the plot was censused in 2020, 0 does not.<br> </li> </ul> <p><strong>Map_Gaps.pdf</strong><br> <code>p. 1</code>: The overall picture of the positional relations between each gap.<br> <code>pp. 2-19</code>: The details of gaps.</p> <p> </p> <p><strong>Metadata_GapSeedlings.txt</strong><br> Metadata of "<strong>GapSeedlings_v0.1.0.csv</strong>".<br> It is the same as this description.</p>
Seedling recruitment and sapling bank dynamics on fluvial deposits in a temperate montane riparian forest.
<p>This is a dataset of Seedling recruitment and sapling bank dynamics on fluvial deposits in a temperate montane riparian forest.</p> <p>The followings are details of each file.</p> <p><strong>Saplings_inFluvialDepositsv1.0.0.csv</strong></p> <ul> <li><code>Plot_x</code> Factor. X coordinates of plots.</li> <li><code>Plot_y</code> Factor. Y coordinates of plots.</li> <li><code>x</code> Integer. X coordinates in plots.</li> <li><code>y</code> Integer. Y coordinates in plots.</li> <li><code>Substrate</code> Factor. Established substrates. NA means that it was not recorded.</li> <li><code>stemID</code> Character. The ID of individual trees.</li> <li><code>Sp.</code> Factor. The species names.</li> <li><code>Family</code> Factor. The family name of the species.</li> <li><code>Heightyyyy</code> Numeric. Vertical heights of trees (cm) in yyyy. Height2007ad is the heights after disturbance in 2007.</li> <li><code>Lengthyyyy</code> Numeric. Length of trees (cm) in yyyy. Length2007ad is the length after disturbance in 2007.</li> <li><code>DBH1_yyyy</code>, <code>DBH2_yyyy</code> Numeric. Diameter at breast height (mm) in yyyy. DBH1 and DBH2 were measured to cross at right angles.</li> <li><code>Noteyyyy</code> Character. Comments in yyyy.</li> </ul> <p> </p> <p><strong>Seedlings_inFluvialDepositsv1.0.0.csv</strong></p> <ul> <li><code>Plot</code> Factor. The plot ID.</li> <li><code>ID</code> Character. The individual ID.</li> <li><code>Sp.</code> Factor. The species names.</li> <li><code>Family</code> Factor. The family names of species.</li> <li><code>Hyyyy</code> Numeric. Vertical height of trees (cm) in yyyy.</li> <li><code>Ageyyyy</code> Numeric. The years of trees (cm) in yyyy.</li> <li><code>noteyyyy</code> Character. Comment in yyyy.</li> </ul> <p> </p> <p><strong>Map_FluvialDeposits.pdf</strong></p> <ul> <li><code>p. 1</code>: The overall picture of the positional relations between each gap.</li> <li><code>p. 2</code>: The details of seedling quadrats.</li> </ul> <p> </p> <p><strong>Metadata_Saplings_inFluvialDeposits.txt</strong><br> Metadata of "<strong>Saplings_inFluvialDepositsv1.0.0.csv</strong>".<br> It is the same as this description.</p> <p> </p> <p><strong>Seedlings_inFluvialDepositsv1.0.0.csv</strong><br> Metadata of "<strong>Seedlings_inFluvialDepositsv1.0.0.csv</strong>".<br> It is the same as this description.</p>
Data from: Different taxonomic and functional indices complement the understanding of herb-layer community assembly patterns in a southern-limit temperate forest
<p><span>The efficient conservation of vulnerable ecosystems in the face of global change requires a complete understanding of how plant communities respond to various environmental factors. We aim to demonstrate that a combined use of different approaches, traits, and indices representing each of the taxonomic and functional characteristics of plant communities will give complementary information on the factors driving vegetation assembly patterns. We analyzed variation across an environmental gradient in taxonomic and functional composition, richness, and diversity of the herb-layer of a temperate beech-oak forest that was located in northern Spain. We measured species cover and four functional traits: leaf dry matter content (LDMC), specific leaf area (SLA), leaf size, and plant height. We found that light is the most limiting resource influencing herb-layer vegetation. Taxonomic changes in richness are followed by equivalent functional changes in the diversity of leaf size but by opposite responses in the richness of SLA. Each functional index is related to different environmental factors even within a single trait (particularly for LDMC and leaf size). To conclude, each characteristic of a plant community is influenced by different and even contrasting factors or processes. Combining different approaches, traits, and indices simultaneously will help us understand how plant communities work.</span></p>
Phosphorous fertilization and soil pH affect the growth of deciduous trees in a temperate hardwood forest
<p>To better understand how a forest’s response to P limitation and acidic deposition can change over time, we added P, limestone to raise pH, and a cross-treatment where both P and limestone were added to 3 different northeastern Ohio forest stands over a 12-year period. Internally, we call this experiment APEX, which stands for Acid Precipitation EXperiment. We tracked diameter at breast height (DBH) of the trees annually, conducted foliar nutrient analyses, and collected tree roots to assess treatment impacts on mycorrhizal colonization. We analyzed our dataset in three sections: the first 6 years after manipulation, the latter 6 years, and the entire 12-year period. These sections allowed us to compare differences between early responses to manipulation and later responses. The R code included here shows how these sections of data were analyzed using linear mixed effect models and Tukey post hoc tests (with the R packages lme4 and multcomp, respectively) and graphed (with the package ggplot2). The three R code files include analyses of 1) litter biomass and chemistry (APEX_leaf_litter_R_code.R), 2) ectomycorrhizal (EM) and arbscular mycorrhizal (AM) fungal colonization and root biomass estimates from trees associated with these mycorrhizal types (APEX_mycorrhizal_roots_R_code.R), and 3) relative basal area increment that was calculated for different tree species and mycorrhizal association types using DBH measurements (APEX_RBAI_R_code.R). All input csv files are included here.</p>
Adaptive forest management improves stand-level resilience of temperate forests under multiple stressors: Dataset
<p>This dataset is linked to the paper “Adaptive forest management improves stand-level resilience of temperate forests under multiple stressors" submitted to Science of The Total Environment.</p>
Figure 7 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 7. Lichen thallus color in old (oldgrowth), middle (middleaged) and young broadleaved forest stands.
Figure 6 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 6. Lichen growth forms in old (oldgrowth), middle (middleaged) and young broadleaved forest stands.
Figure 9 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 9. Lichen photobiont type in old (oldgrowth), middle (middleaged) and young broadleaved forest stands.
Figure 8 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 8. Lichen reproduction type in old (oldgrowth), middle (middleaged) and young broadleaved forest stands.
Figure 2 in Application Of Lichen Functional Traits In Identification Of Temperate Old-Growth Broad-Leaved Forests
Figure 2. Sample plot. Abbreviations: S – South, N – North. Arrow shows the direction of the sampling in transect. Tree number shows the order of surveyed trees.
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