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108 results for “riparian forest”
Riparian forests shape trophic interactions in detrital stream food webs
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Riparian buffers provide refugia during secondary forest succession
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Riparian forests and macroinvertebrates support multiple ecosystem processes across temperate and tropical streams
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Tropical riparian forests in danger from large savanna wildfires
<p>1. Tropical savannas are known for the fire-prone ecosystems, yet, riparian evergreen forests are another important landscape feature. These forests usually remain safe from wildfires in the wet riparian zones. With global changes, large wildfires are now more frequent in savanna landscapes, exposing riparian forests to unprecedented impact.</p> <p>2. In 2017, a large wildfire spread across the Chapada dos Veadeiros National Park, an iconic UNESCO site in central Brazil, raising concerns about its impact on the fire-sensitive ecosystems. By combining remote sensing analysis of Google Earth images (2003-2019) with detailed field information from 36 sites, we assessed wildfire impacts on riparian forests. For this, we measured the structure of trees, saplings and herbaceous plants, as well as topsoil variables.</p> <p>3. Since 2003, all riparian forests had canopy cover above 90 %, but after 2017, canopy cover dropped to 20 % in some forests, indicating large variation in wildfire damage. A closer look in the field revealed that, on average, the wildfire killed 52 % of adult trees and 87 % of tree saplings in flooded forests. In non-flooded forests, impacts on adult trees were negligible, but fire killed 75 % of tree saplings. Opportunistic vines and the invasive grass Melinis minutiflora were already present in severely disturbed flooded forests. In all forests, impacts on many ecosystem variables were related to canopy damage, a variable measurable from satellite. Overall, seasonally flooded riparian forests were the most severely impacted, possibly due to the relatively thinner barks of their trees.</p> <p>4. Synthesis and applications. Our findings reveal how riparian forests embedded in tropical savanna landscapes are in danger from large wildfires. The destruction of some forests has opened space for new plant species that may propel a shift to an alternative ecosystem state. Riparian forests are habitat of large savanna animals and their loss could affect entire trophic networks. Managing wildfires and invasive grasses locally is probably the best strategy to maintain riparian forests resilient. As wildfire regimes intensify in tropical savanna landscapes, our findings stress the need for an integrated management that considers riparian forests as a vulnerable element of the system.</p>
Fig. 7 in The Diversity Of Cuculiform And Piciform Species In Partly Transformed Riparian Zambezi Forest
Fig. 7. Distribution of breeding pairs of woodpeckers in Zambezi riparian forest.
Fig. 5 in The Diversity Of Cuculiform And Piciform Species In Partly Transformed Riparian Zambezi Forest
Fig. 5. Distribution of occupied male territories of cuckoos in Zambezi riparian forest.
Fig. 2 in The Diversity Of Cuculiform And Piciform Species In Partly Transformed Riparian Zambezi Forest
Fig. 2. Zambezi forest dominated by Lonchocarpus trees.
Fig. 6 in The Diversity Of Cuculiform And Piciform Species In Partly Transformed Riparian Zambezi Forest
Fig. 6. Distribution of occupied male territories of coucals in Zambezi riparian forest.
Relationship of woody species composition with edaphic characteristics in threatened riparian Atlantic Forest remnants in the upper Rio Doce basin, Brazil
<p class="MsoNormal"><span>Studies on the composition, richness, and diversity of plant species in <span>tropical</span> communities are essential for understanding relevant ecological processes and for developing appropriate conservation policies. </span><span>Considering that areas subject to direct impacts due to dam breach may in the long-term present changes in species composition and in soil parameters, we evaluated the composition of the flora, described the current vegetation profile, and evaluated whether differences in species composition was influenced by soil variables of three areas along the Gualaxo River, in Minas Gerais State, Brazil. In addition, we identified important plant species through occurrence and phytosociological parameters for ecological restoration projects in the affected region, serving as reference areas. We sampled plant species with DBH ≥ 5 cm (diameter at breast height – measured 1.30 m above ground level) in 77 plots distributed in three riparian forest areas. We calculated phytosociological parameters and related them to edaphic factors. </span><span>A total of 1579 individual plants belonging to 53 botanical families and 227 species were sampled in the three areas. The Fabaceae family was the most representative with 46 species. </span><span>Species composition and diversity among the sampled areas was similar and was associated with edaphic factors. Furthermore, some species (e.g. <em>Xylopia sericea</em>, <em>Cupania emarginata</em> and <em>Ocotea pulchalla</em>) showed an important relation with soil variables. Some species of the genera (e.g., <em>Byrsonima</em>, <em>Xylopia</em>, <em>Ocotea</em>, and <em>Croton</em>) and families (e.g., Fabaceae and Myrtaceae) found here, can be important species in the restauration process for the local and regional maintenance of floristic identity in the Rio Doce river.</span></p>
Soil greenhouse gas fluxes along transects from oil palm to riparian forests in the SAFE landscape
<b>Description: </b><p>Riparian greenhouse gas fluxes measured by the static chamber method including associated environmental parameters and river water </p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/126"><b>Characterising soil microbial communities and measuring associated biogeochemical fluxes</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC HMTF (Research Programme, (NE/K016091/1), <a href=" http://lombok.nerc-hmtf.info/"> http://lombok.nerc-hmtf.info/</a>)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2/2 JLD.5 (79))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3258079">here</a></p><p><b>Files: </b>This consists of 1 file: 1_HJ_river_water_riparian.xlsx</p><p><b>1_HJ_river_water_riparian.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>river_water</b> (described in worksheet river_water)</p><p>Description: river water measurments</p><p>Number of fields: 17</p><p>Number of data rows: 63</p><p>Fields: </p><ul><li><b>site</b>: location sample was taken (Field type: Location)</li><li><b>location</b>: habitat (Field type: Categorical)</li><li><b>replicate</b>: water sample replicate number (Field type: Replicate)</li><li><b>sampling_occasion</b>: date of sample collection (Field type: Date)</li><li><b>date</b>: date of sample analysis (Field type: Date)</li><li><b>TDS</b>: Total Desolved Solids (Field type: Numeric)</li><li><b>pH</b>: water pH (Field type: Numeric)</li><li><b>conductivity</b>: water conductivity (Field type: Numeric)</li><li><b>Temp</b>: tempreture of river water (Field type: Numeric)</li><li><b>air_CH4</b>: air concentration of CH4 (Field type: Numeric)</li><li><b>water_CH4</b>: water concentration of CH4 (Field type: Numeric)</li><li><b>air_N2O</b>: air concentration of N2O (Field type: Numeric)</li><li><b>water_N2O</b>: water concentration of N2O (Field type: Numeric)</li><li><b>air_CO2</b>: air concentration of CO2 (Field type: Numeric)</li><li><b>water_CO2</b>: water concentration of CO2 (Field type: Numeric)</li><li><b>NH4-N</b>: concentration of NH4-N in water (Field type: Numeric)</li><li><b>NO3-N</b>: concentration of NO3-N in water (Field type: Numeric)</li></ul></li><li><p><b>data_one_off_field</b> (described in worksheet data_one_off_field)</p><p>Description: soil and littter property measurements</p><p>Number of fields: 12</p><p>Number of data rows: 48</p><p>Fields: </p><ul><li><b>Location</b>: location of chamber (Field type: Location)</li><li><b>chamber_id</b>: chamber ID (Field type: ID)</li><li><b>site</b>: Site ID (Field type: ID)</li><li><b>landuse</b>: land use type (Field type: Categorical)</li><li><b>pH</b>: soil pH (Field type: Numeric)</li><li><b>soil_N</b>: soil nitrogen content (Field type: Numeric)</li><li><b>soil_C</b>: soil carbon content (Field type: Numeric)</li><li><b>litter_N</b>: litter nitrogen content (Field type: Numeric)</li><li><b>litter_C</b>: litter carbon content (Field type: Numeric)</li><li><b>C_N</b>: soil C:N ratio (Field type: Numeric)</li><li><b>Latitude</b>: GPS co-ordinate that the sample was taken (Field type: Latitude)</li><li><b>Longitude</b>: GPS co-ordinate that the sample was taken (Field type: Longitude)</li></ul></li><li><p><b>data_repeated_measures</b> (described in worksheet data_repeated_measures)</p><p>Description: repeated soil measures</p><p>Number of fields: 16</p><p>Number of data rows: 336</p><p>Fields: </p><ul><li><b>chamber_id</b>: Chamber ID (Field type: ID)</li><li><b>site</b>: Site ID (Field type: ID)</li><li><b>landuse</b>: land use type (Field type: Categorical)</li><li><b>sampling_occasion</b>: date of sample collection (Field type: Date)</li><li><b>date</b>: date of sample analysis (Field type: Date)</li><li><b>time</b>: Time the measurement was taken (Field type: Time)</li><li><b>flux_CH4-C</b>: Soil CH4 flux (Field type: Numeric)</li><li><b>flux_CO2-C</b>: Soil CO2 flux (Field type: Numeric)</li><li><b>flux_N2O-N</b>: Soil N2O flux (Field type: Numeric)</li><li><b>NH4-N_H2O</b>: Soil NH4 concentration (Field type: Numeric)</li><li><b>NO3-N_H2O</b>: Soil NO3 concentration (Field type: Numeric)</li><li><b>NH4-N_KCl</b>: Soil NH4 concentration (Field type: Numeric)</li><li><b>NO3-N_KCl</b>: Soil NO3 concentration (Field type: Numeric)</li><li><b>air_temp</b>: Air temperature around the flux chamber (Field type: Numeric)</li><li><b>soil_temp</b>: Soil temperature around the flux chamber (Field type: Numeric)</li><li><b>soil_moisture</b>: Soil moisture around the flux chamber (Field type: Numeric)</li></ul></li></ol><p><b>Date range: </b>2016-11-01 to 2017-11-30</p><p><b>Latitudinal extent: </b>4.3960 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p>
Modelling riparian forest distribution and composition to entire river networks
<p><strong>Aim: </strong>Developing a methodology to map the distribution of riparian forests to entire river networks and determining the main environmental factors controlling their spatial patterns.</p> <p><strong>Location: </strong>Cantabrian region, northern Spain.</p> <p><strong>Methods: </strong>We mapped the riparian forests at a physiognomic and phytosociological levels by delimiting riparian zones and generating vegetation distribution models based on remote sensing data (Landsat 8 OLI and LiDAR PNOA). We built virtual watersheds to define a spatial framework where the catchment environmental information can be routed to each river reach, jointly with the vegetation map. In order to determine the drivers playing a significant role on the observed spatial patterns in the riparian forest we modelled interactions between these datasets of environmental information and riparian vegetation by using the Random Forest algorithm.</p> <p><strong>Results: </strong>The modelling results obtained reproduced a reliable variation of riparian forest structure and composition across Cantabrian watersheds. The produced maps were highly accurate, with more than a 70% overall accuracy for the forest occurrence. A clear differentiation between Eurosiberian (91E0 and 9160 habitats) and Mediterranean (92E0) riparian forests was shown on both sides of the mountain range. Topography and land use were the main drivers defining the distribution of riparian forest as a physiognomic unit. In turn, altitude, climate and percentage of pasture were the most relevant factors determining their composition (phytosociological approach).</p> <p><strong>Conclusions: </strong>Our study confirms that the anthropic control ultimately defines the distribution of the vegetation in the riparian area at a regional to local scale. Human disturbances constrain the extension of forest patches across their potential distribution defined by topoclimatic boundaries, which establish a clear limit between Mediterranean and Eurosiberian biogeographical regions.</p>
FIGURE 1 in Riparian and valley-margin hardwood species of pre-colonial Piedmont forests: A preliminary study of subfossil leaves from White Clay Creek, southeastern Pennsylvania, USA
FIGURE 1. Location of the White Clay Creek leaf mat site, Chester County, Pennsylvania.
Stuck between the mandibles of an insect and of a rodent: where does the fate of ash-dominated riparian temperate forests lie?
<p>The beaver (<em>Castor canadensis</em> Khul) is a key species that is known to shape the composition of riparian forests. Ash trees (<em>Fraxinus</em> spp.) can be abundant in these forests. However, invasion by the emerald ash borer (<em>Agrilus planipennis </em>Fairmaire) in North America threatens their survival. The disappearance of ash will have a large impact on the riparian forest composition in itself. It is not known what the consequences would be for the remaining forest if ash plays an important role in the beaver diet. Inventory plots across a ash gradient were measured in Plaisance National Park, Quebec, Canada, to collect data and to establish if (1) trees and saplings of this genus were selected or avoided by beavers, (2) if other genera had a lower or a greater probability of being consumed compared to ash, and (3) if ash density could affect the probability of consumption of other genera. Of all genera present in the park, ash trees were selected in the highest number of plots. Only two genera, <em>Carpinus</em> and <em>Populus</em>, had a higher probability of being consumed than ash. These genera are not abundant in the park, and neither in riparian forests of the temperate biome, and thus are not good candidates to replace ash as a staple for beavers. The most abundant genus in riparian temperate forests, along with ash, is <em>Acer</em>. In this study, <em>Acer</em> trees were not selected, and as for <em>Acer</em> saplings, were less likely to be consumed than ash. Mixed results were obtained about genera that could become more likely to be consumed as ash density decreases. It would seem that the disappearance of ash would not cause a switch to a single or a few genera in the future, which may be due to the high diversity of genera present in temperate riparian forests. However, ash may not disappear completely due to its capacity to sprout following the death of the aboveground portion of ash trees. This scenario is discussed in light of the susceptibility of intermediate-sized ash stems to be colonized by the emerald ash borer and of the greater likelihood of beavers to feed on these same-sized stems.</p>
Floristic composition, structure and diversity of riparian forests in southwestern Nigeria: Conservation is inevitable
<p>The Nigerian riparian forest ecosystems had declined in extent and distribution and this had been attributed mainly to land use change. This study intended to provide an understanding of the links between plant diversity, composition, structures, and disturbances both anthropogenic and natural processes inducing the vegetation dynamics. Nine study sites were used for this study, within each site, five (5) plots (0.25 ha in size) were marked out and placed systematically at an interval of 10 m along the transect. A complete enumeration of plant species was carried out and identified at the species level. Diversity indices and structural parameters were determined and anthropogenic activities were ranked. A total number of 233 plant species were identified, belonging to 80 families; out of which, Euphorbiaceae and Apocynaceae were dominant families The density and basal area ranged from 2,200-6,000 ha<sup>-1</sup> and 2.59-17.58 m<sup>2</sup> ha<sup>-1</sup> respectively across the study sites. <em>Pterocarpus santalinoides</em>, <em>Alchornea cordiflora</em>, <em>Chassalia kolly</em>, <em>Tetracera</em> spp,<em> Fimbristylis</em>, <em>Bambusa vulgaris</em> and <em>Cyrtosperma senegalense</em> were the dominant species. The Shannon diversity index ranged from (1.38-3.49), Simpson (0.66-0.97), and Evenness diversity (0.43-0.84). Fisher alpha (10.03-30.21) and Whittaker beta diversity (0.36-0.89) values were highest in Ipetumodu (site VIII) and lowest in Ilesha (site II). Seventy-three (73%) of the species in this study had a low important value index (IVI). The dominance of some lianas and herbaceous species in the riparian forest sites showed disturbances, stages of ecological succession, and regeneration of the vegetation. Conservation is inevitable towards maintaining and protecting species diversity, ecosystem roles, and services of these forests in Nigeria.</p>
Soil nutrient dissimilarity and litter nutrient limitation as major drivers of home field advantage in riparian tropical forests
<p><span>Decomposition is a key process driving carbon and nutrient cycling in ecosystems worldwide. The home field advantage effect (HFA) has been found to accelerate decomposition rates when litter originates from "home" when compared to other ("away") sites. It is still poorly known how HFA plays out in tropical, riparian forests, particularly in forests under restoration. We carried out three independent reciprocal litter transplant experiments to test how litter quality, soil nutrient concentrations and successional stage (age) influenced HFA in tropical riparian forests. These experimental areas formed a wide gradient of soil and litter nutrients, which we used to evaluate the more general hypothesis that HFA varies with dissimilarity in soil nutrients and litter quality. We found that HFA increased with soil nutrient dissimilarity, suggesting that litter translocation uncouples relationships between decomposers and litter characteristics; and with litter N:P, indicating P limitation in this system. We also found negative HFA effects at a site under restoration that presented low decomposer ability, suggesting that forest restoration does not necessarily recover decomposer communities and nutrient cycling. Within each of the independent experiments, the occurrence of HFA effects was limited and their magnitude was not related to forest age, nor soil and litter quality. Our results imply that HFA effects in tropical ecosystems are influenced by litter nutrient limitation and soil nutrient dissimilarity between home and away sites, but to further disentangle major HFA drivers in tropical areas, a gradient of dissimilarity between litter and soil properties must be implemented in future experimental designs.</span></p>
Data from: Restoration of riparian forest cover increases carbon stocks in the Pacific Northwest
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Relationship of woody species composition with edaphic characteristics in threatened riparian Atlantic Forest remnants in the upper Rio Doce basin, Brazil
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Stuck between the mandibles of an insect and of a rodent: where does the fate of ash-dominated riparian temperate forests lie?
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Tropical riparian forests in danger from large savanna wildfires
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Data from: Unraveling the taxonomic, functional and phylogenetic diversity of lizard assemblages in riparian forest areas in the Amazon–Pantanal ecotone
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OpenNeuro
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