Find research datasets worth reusing

opencc-by-4.0Nov 2018View details →

Figure 3 in Do disturbed environments affect density of the tunnel-web spider Acanthogonatus centralis (Mygalomorphae: Nemesiidae) from native grasslands in Argentina?

Figure 3. Relationship between the density of potential shelters and the density of spiders.

Figure 7 in Substratum stability and coral reef resilience: insights from 90 years of disturbances on a reef in American Samoa

Figure 7. Acropora muricata colony having stability by being wedged into the loose substratum.

Figure 5 in Substratum stability and coral reef resilience: insights from 90 years of disturbances on a reef in American Samoa

Figure 5. Density of Acropora spp. along the Aua transect from 1917 to 2007.

Figure 6 in Substratum stability and coral reef resilience: insights from 90 years of disturbances on a reef in American Samoa

Figure 6. Acropora nana recruited abundantly to the solid reef crest in the late 1990s.

Figure 4 in Substratum stability and coral reef resilience: insights from 90 years of disturbances on a reef in American Samoa

Figure 4. Density of Porites cylindrica colonies along the Aua transect from 1917 to 2007.

opencc-by-4.0Aug 2024View details →

Lower ionospheric disturbances due to geomagnetic storms of March & April 2023: inferred from VLF navigational signals and numerical simulations

This is VLF data used in the research paper as per title

opencc-by-4.0Aug 2024View details →

Pound Hill disturbance timing experiment, Silwood Park

The composition of plant communities is in part determined by seedling recruitment, which depends on seed germination and seedling survival.  Because species differ in the optimal environmental conditions for germination it is expected that variations in timing and severity of disturbances have an effect on the relative abundance of plant species and the composition of the seed bank. The Pound Hill experiment aims to assess the effect of the timing of cultivation and soil disturbance on grasslands diversity and biomass. It was established in 1991 in an area of Silwood Park that had been maintained for the conservation of arable weeds through an annual cultivation at various times of the year for at least a decade.  This regime transformed a wheat-cultivated land into a species-rich community of ruderal plants, mostly annuals. The experimental area, which is protected from rabbits' damage, is divided in plots that since October 1992 have been cultivated in March, May or October. Two data sets are available for this experiment:  1. Data of aboveground standing biomass of each plant species present in all plots collected in July 2003 (PoundHillDist_biomass.csv) 2. Data of percentage of cover of each plant species collected in 2014, 2016, 2017, 2019-2021 (PoundHillDist_cover.csv).

opencc-by-sa-4.0Sep 2024View details →

Illustrations for 'Disturbances in the evergreen boreal forest and their impact on 21st century vegetation and climate dynamics - A stochastic modeling approach' (Doctoral thesis)

This repository contains all the original illustrations I created for my doctoral thesis at the Technical University of Munich. This work is published under a Creative Commons CC-BY-SA license, which means that you are free to use and adapt this work under the same license for commercial and non-commercial applications as long as you credit the original work. To credit, please cite this repository as well as my doctoral thesis.

opencc-by-4.0Sep 2024View details →

Forest Regrowth Carbon Gains Data for publication: The key role of forest disturbance in reconciling estimates of the northern carbon sink

'Space for time' regrowth carbon gains based on forest age map (Besnard et al. 2021; https://doi.org/10.5194/essd-13-4881-2021) and ESA-CCI Biomass v4 (Santoro et al. 2023; <a href="https://dx.doi.org/10.5285/af60720c1e404a9e9d2c145d2b2ead4e">https://dx.doi.org/10.5285/af60720c1e404a9e9d2c145d2b2ead4e</a>). Gridded cumultiave carbon gains 2001-2021 at 1km spatial resolution are provided for the four study regions. Regional total carbon gains from forest regrowth are provided for each year 2001-2021. See O'Sullivan et al. 2024 () for full details.

opencc-by-4.0Oct 2024View details →

source data of "Enhanced vegetation drought resistance induced by elephant disturbance in Africa"

Open the record for dataset details and reuse information.

opencc-by-4.0Oct 2024View details →

Data from: Assessing the effect of tissue and fire-response traits on plant growth rates post-disturbance in Eastern Australia

Here is the necessary code and data to reproduce results published in 'Assessing the effect of tissue and fire-response traits on plant growth rates post-disturbance in Eastern Australia'.

opencc-by-4.0Oct 2024View details →

Virtual Reality Balance Disturbance Dataset

Background and Purpose: There are very few publicly available datasets on real-world falls in scientific literature due to the lack of natural falls and the inherent difficulties in gathering biomechanical and physiological data from young subjects or older adults residing in their communities in a non-intrusive and user-friendly manner. This data gap hindered research on fall prevention strategies. Immersive Virtual Reality (VR) environments provide a unique solution. This dataset supports research in fall prevention by providing an immersive VR setup that simulates diverse ecological environments and randomized visual disturbances, aimed at triggering and analyzing balance-compensatory reactions. The dataset is a unique tool for studying human balance responses to VR-induced perturbations, facilitating research that could inform training programs, wearable assistive technologies, and VR-based rehabilitation methods.   Dataset Content: The dataset includes: <ul> <li>Kinematic Data: Captured using a full-body Xsens MVN Awinda inertial measurement system, providing detailed movement data at 60 Hz.</li> <li>Muscle Activity (EMG): Recorded at 1111 Hz using Delsys Trigno for tracking muscle contractions.</li> <li>Electrodermal Activity (EDA)*: Captured at 100.21 Hz with a Shimmer GSR device on the dominant forearm to record physiological responses to perturbations.</li> <li>Metadata: Includes participant demographics (age, height, weight, gender, dominant hand and foot), trial conditions, and perturbation characteristics (timing and type).</li> </ul> The files are named in the format "ParticipantX_labelled", where X represents the participant's number. Each file is provided in a .mat format, with data already synchronized across different sensor sources. The structure of each file is organized into the following columns: <ul> <li>Column 1: Label indicating the visual perturbation applied. 0 means no visual perturbation.</li> <li>Column 2: Timestamp, providing the precise timing of each recorded data point.</li> <li>Column 3: Frame identifier, which can be cross-referenced with the MVN file for detailed motion analysis.</li> <li>Columns 4 to 985: Xsens motion capture features, exported directly from the MVN file.</li> <li>Columns 986 to 993: EMG data - Tibialis Anterior (R&L), Gastrocnemius Medial Head (R&L), Rectus Femoris (R), Semitendinosus (R), External Oblique (R), Sternocleidomastoid (R).</li> <li>Columns 994 to 1008: Shimmer data: Accelerometer (x,y,z), Gyroscope (x,y,z), Magnetometer (x,y,z), GSR Range, Skin Conductance, Skin Resistance, PPG, Pressure, Temperature.</li> </ul> In addition, we are also releasing the .MVN and .MVNA files for each participant (1 to 10), which provide comprehensive motion capture data and include the participants' body measurements, respectively. This additional data enables precise body modeling and further in-depth biomechanical analysis.   Participants & VR Headset: Twelve healthy young adults (average age: 25.09 ± 2.81 years; height: 167.82 ± 8.40 cm; weight: 64.83 ± 7.77 kg; 6 males, 6 females) participated in this study (Table 1). Participants met the following criteria: i) healthy locomotion, ii) stable postural balance, iii) age ≥ 18 years, and iv) body weight < 135 kg. Participants were excluded if they: i) had any condition affecting locomotion, ii) had epilepsy, vestibular disorders, or other neurological conditions impacting stability, iii) had undergone recent surgeries impacting mobility, iv) were involved in other experimental studies, v) were under judicial protection or guardianship, or vi) experienced complications using VR headsets (e.g., motion sickness). All participants provided written informed consent, adhering to the ethical guidelines set by the University of Minho Ethics Committee (CEICVS 063/2021), in compliance with the Declaration of Helsinki and the Oviedo Convention. To ensure unbiased reactions, participants were kept unaware of the specific protocol details. Visual disturbances were introduced in a random sequence and at various locations, enhancing the unpredictability of the experiment and simulating a naturalistic response. The VR setup involved an HTC Vive Pro headset with two wirelessly synchronized base stations that tracked participants’ head movements within a 5m x 2.5m area. The base stations adjusted the VR environment’s perspective according to head movements, while controllers were used solely for setup purposes.   Table 1 - Participants' demographic information <table> <tbody> <tr> <td>Participant</td> <td>Height (cm)</td> <td>Weight (kg)</td> <td>Age</td> <td>Gender</td> <td>Dom. Hand</td> <td>Dom. Foot</td> </tr> <tr> <td>1</td> <td>159</td> <td>56.5</td> <td>23</td> <td>F</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>2</td> <td>157</td> <td>55.3</td> <td>28</td> <td>F</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>3</td> <td>174</td> <td>67.1</td> <td>31</td> <td>M</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>4</td> <td>176</td> <td>73.8</td> <td>23</td> <td>M</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>5</td> <td>158</td> <td>57.3</td> <td>23</td> <td>F</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>6</td> <td>181</td> <td>70.9</td> <td>27</td> <td>M</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>7</td> <td>171</td> <td>73.3</td> <td>23</td> <td>M</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>8</td> <td>159</td> <td>69.2</td> <td>28</td> <td>F</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>9</td> <td>177</td> <td>57.3</td> <td>22</td> <td>M</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>10</td> <td>171</td> <td>75.5</td> <td>25</td> <td>M</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>11</td> <td>163</td> <td>58.1</td> <td>23</td> <td>F</td> <td>Right</td> <td>Right</td> </tr> <tr> <td>12</td> <td>168</td> <td>63.7</td> <td>25</td> <td>F</td> <td>Right</td> <td>Right</td> </tr> </tbody> </table>   Data Collection Methodology: The experimental protocol was designed to integrate four essential components: (i) precise control over stimuli, (ii) high reproducibility of the experimental conditions, (iii) preservation of ecological validity, and (iv) promotion of real-world learning transfer. <ul> <li>Participant Instructions and Familiarization Trial: Before starting, participants were given specific instructions to (i) seek assistance if they experienced motion sickness, (ii) adjust the VR headset for comfort by modifying the lens distance and headset fit, (iii) stay within the defined virtual play area demarcated by a blue boundary, and (iv) complete a familiarization trial. During this trial, participants were encouraged to explore various virtual environments while performing a sequence of three key movements—walking forward, turning around, and returning to the initial location—without any visual perturbations. This familiarization phase helped participants acclimate to the virtual space in a controlled setting.</li> <li>Experimental Protocol and Visual Perturbations: Participants were exposed to 11 different types of visual perturbations as outlined in Table 2, applied across a total of 35 unique perturbation variants (Table 3). Each variant involved the same type of perturbation, such as a clockwise Roll Axis Tilt, but varied in intensity (e.g., rotation speed) and was presented in randomized virtual locations. The selection of perturbation types was grounded in existing literature on visual disturbances. This design ensured that participants experienced a diverse range of visual effects in a manner that maintained ecological validity, supporting the potential for generalization to real-world scenarios where visual perturbations might occur spontaneously.</li> <li>Protocol Flow and Randomized Presentation: Throughout the experimental protocol, each visual perturbation variant was presented three times, and participants engaged repeatedly in the familiarization activities over a nearly one-hour period. These activities—walking forward, turning around, and returning to the starting point—took place in a 5m x 2.5m physical space mirrored in VR, allowing participants to take 7–10 steps before turning. Participants were not informed of the timing or nature of any perturbations, which could occur unpredictably during their forward walk, adding a realistic element of surprise. After each return to the starting point, participants were relocated to a random position within the virtual environment, with the sequence of positions determined by a randomized, computer-generated order.</li> </ul>   Table 2 - Visual perturbations' name and parameters (L - Lateral; B - Backward; F - Forward; S - Slip; T - Trip; CW- Clockwise; CCW - Counter-Clockwise) <table> <tbody> <tr> <td>Perturbation [Fall Category]</td> <td> Parameters </td> </tr> <tr> <td>Roll Axis Tilt - CW [L]</td> <td>[10º, 20º, 30º] during 0.5s</td> </tr> <tr> <td>Roll Axis Tilt – CCW [L]</td> <td>[10º, 20º, 30º] during 0.5s</td> </tr> <tr> <td>Support Surface ML Axis Translation - Bidirectional [L]</td> <td>Discrete Movement (static pauses between movements) – 1 m/s</td> </tr> <tr> <td>AP Axis Translation - Front [F]</td> <td>1 m/s</td> </tr> <tr> <td>AP Axis Translation - Backwards [B]</td> <td>1 m/s</td> </tr> <tr> <td>Pitch Axis Tilt [S]</td> <td>0º-25º, 60º/s</td> </tr> <tr> <td>Virtual object with lower height than a real object [T]</td> <td>Variable object height</td> </tr> <tr> <td>Roll-Pitch-Yaw Axis Tilt [Syncope]</td> <td>Sum of sinusoids drive each axis rotation</td> </tr> <tr> <td>Scene Object Movement [L]</td> <td>Objects fly towards the subject’s head. Variable speeds</td> </tr> <tr> <td>Vertigo Sensation [F/L]</td> <td>Walk at a comfortable speed. With and without avatar. House’s height</td> </tr> <tr> <td>Axial Axis Translation [F/B/L]</td> <td>Free fall</td> </tr> </tbody> </table>   Table 3 - Label Encoding <table> <tbody> <tr> <td>Visual Perturbation</td> <td>Label</td> <td>Visual Perturbation</td> <td>Label</td> <td>Visual Perturbation</td> <td>Label</td> </tr> <tr> <td>Roll Indoor 1 CW10</td> <td>1</td> <td>Roll Indoor 1 CW20</td> <td>2</td> <td>Roll Indoor 1 CW30</td> <td>3</td> </tr> <tr> <td>Roll Indoor 1 CCW10</td> <td>4</td> <td>Roll Indoor 1 CCW20</td> <td>5</td> <td>Roll Indoor 1 CCW30</td> <td>6</td> </tr> <tr> <td>Roll Indoor 2 CW10</td> <td>7</td> <td>Roll Indoor 2 CW20</td> <td>8</td> <td>Roll Indoor 2 CW30</td> <td>9</td> </tr> <tr> <td>Roll Indoor 2 CCW10</td> <td>10</td> <td>Roll Indoor 2 CCW20</td> <td>11</td> <td>Roll Indoor 2 CCW30</td> <td>12</td> </tr> <tr> <td>Roll Outdoor CW10</td> <td>13</td> <td>Roll Outdoor CW20</td> <td>14</td> <td>Roll Outdoor CW30</td> <td>15</td> </tr> <tr> <td>Roll Outdoor CCW10</td> <td>16</td> <td>Roll Outdoor CCW20</td> <td>17</td> <td>Roll Outdoor CCW30</td> <td>18</td> </tr> <tr> <td>ML-Axis Trans. - Kitchen</td> <td>19</td> <td>AP-Axis Trans. - Corridor Forward</td> <td>20</td> <td>AP-Axis Trans. - Corridor Backward</td> <td>21</td> </tr> <tr> <td>Pitch Indoor - Bathroom (wet floor)</td> <td>22</td> <td>Pitch Indoor - Near Fridge (wet floor)</td> <td>23</td> <td>Roof Beam Walking - Vertigo</td> <td>24</td> </tr> <tr> <td>Roof Beam Walking - Vertigo No Avatar</td> <td>25</td> <td>Simple Roof - Vertigo</td> <td>26</td> <td>Simple Roof - Vertigo No Avatar</td> <td>27</td> </tr> <tr> <td>Pitch Outdoor - Near Car Oil</td> <td>28</td> <td>Trip - Sidewalk / Trip Shock</td> <td>29/290</td> <td>Bedroom Syncope</td> <td>30</td> </tr> <tr> <td>Garden - Object Avoidance</td> <td>31</td> <td>Electricity Pole - Vertigo</td> <td>32</td> <td>Electricity Pole - No Avatar</td> <td>33</td> </tr> <tr> <td>Free Fall</td> <td>34</td> <td>Climbing Virtual Stairs</td> <td>35</td> <td> </td> <td> </td> </tr> </tbody> </table>     * Some data from Shimmer device was collected but not used or checked by the research team.

opencc-by-4.0Dec 2023View details →

Alarming decline in the carbon sink of European forests driven by disturbances

This repository includes the dataset and figures associated with the following paper: Ritter, F., Ciais, P., Senf, C., Santoro, M., Xu, Y., Pelissier-Tanon, A., Schwartz, M., Fayad, I., Carvalhais, N., Brandt, M., Fensholt, R., Besnard, S. & Avitabile, V.. Alarming decline in the carbon sink of European forests driven by disturbances

opencc-zeroJun 2021View details →

Landslide age, elevation and residual vegetation determine tropical montane forest canopy recovery and biomass accumulation after landslide disturbances in the Peruvian Andes

Landslides are common natural disturbances in tropical montane forests. While the geomorphic drivers of landslides in the Andes have been studied, factors controlling post-landslide forest recovery across the steep climatic and topographic gradients characteristic of tropical mountains are poorly understood. Here we use a LiDAR-derived canopy height map coupled with a 25-year landslide time series map to examine how landslide, topographic, and biophysical factors, along with residual vegetation, affect canopy height and heterogeneity in regenerating landslides. We also calculate aboveground biomass accumulation rates and estimate the time for landslides to recover to mature forest biomass levels. We find that age and elevation are the biggest determinants of forest recovery, and that the jump-start in regeneration that residual vegetation provides lasts for at least 18 years. Our estimates of time to biomass recovery (31.6-37.1 years) are surprisingly rapid, and as a result we recommend that future research pair LiDAR with hyperspectral imagery to estimate forest aboveground biomass in frequently disturbed landscapes. Synthesis: Using a high-resolution LiDAR dataset and a time-series inventory of 608 landslides distributed across a wide elevational gradient in Andean montane forest, we show that age and elevation are the most influential predictors of forest canopy height and canopy variability. Other features of landslides, in particular the presence of residual vegetation, shape post-landslide regeneration trajectories. LiDAR allows for a detailed analysis of forest structural recovery across large landscapes and numbers of disturbances, and provides a reasonable upper bound on aboveground biomass accumulation rates. However, because this method does not capture the effect of compositional change through succession on aboveground biomass, wherein high-wood density species gradually replace light-wooded pioneer species, it overestimates aboveground biomass. Given previously estimated stem turnover rates along this elevational gradient, we posit that aboveground biomass recovery takes at least three times as long as our recovery time estimates based on LiDAR-derived structure alone.

opencc-zeroJul 2021View details →

Data from: Tropical understory herbaceous community responds more strongly to hurricane disturbance than to experimental warming

The effects of climate change on tropical forests may have global consequences due to the forests' high biodiversity and major role in the global carbon cycle. In this study, we document the effects of experimental warming on the abundance and composition of a tropical forest floor herbaceous plant community in the Luquillo Experimental Forest, Puerto Rico. This study was conducted within Tropical Responses to Altered Climate Experiment (TRACE) plots, which use infrared heaters under free-air, open-field conditions, to warm understory vegetation and soils +4 °C above nearby control plots. Hurricanes Irma and María damaged the heating infrastructure in the second year of warming, therefore, the study included one pre-treatment year, one year of warming, and one year of hurricane response with no warming. We measured percent leaf cover of individual herbaceous species, fern population dynamics, and species richness and diversity within three warmed and three control plots. Results showed that one year of experimental warming did not significantly affect the cover of individual herbaceous species, fern population dynamics, species richness, or species diversity. In contrast, herbaceous cover increased from 20% to 70%, bare ground decreased from 70% to 6%, and species composition shifted pre- to post-hurricane. The negligible effects of warming may have been due to the short duration of the warming treatment or an understory that is somewhat resistant to higher temperatures. Our results suggest that climate extremes that are predicted to increase with climate change, such as hurricanes and droughts, may cause more abrupt changes in tropical forest understories than longer-term sustained warming.

opencc-zeroJul 2021View details →

Data from: Disturbance history is a key driver of tree lifespan in temperate primary forests

AIMS We examined differences in lifespan among the dominant tree species (spruce (Picea abies (L.) H. Karst.), fir (Abies alba Mill.), beech (Fagus sylvatica L.), and maple (Acer pseudoplatanus L.)) across primary mountain forests of Europe. We ask how disturbance history, lifetime growth patterns, and environmental factors influence lifespan. LOCATIONS Balkan mountains, Carpathian mountains, Dinaric mountains. METHODS Annual ring widths from 20,600 cores from primary forests were used to estimate tree life spans, growth trends, and disturbance history metrics. Mixed models were used to examine species-specific differences in lifespan (i.e. defined as species-specific 90th percentiles of age distributions), and how metrics of radial growth, disturbance parameters, and selected environmental factors influence lifespan. RESULTS While only a few beech trees surpassed 500 years, individuals of all four species were older than 400 years. There were significant differences in lifespan among the four species (beech > fir > spruce > maple), indicating life history differentiation in lifespan. Trees were less likely to reach old age in areas affected by more severe disturbance events, whereas individuals that experienced periods of slow growth and multiple episodes of suppression and release were more likely to reach old age. Aside from a weak but significant negative effect of vegetation season temperature on fir and maple lifespan, no other environmental factors included in the analysis influenced lifespan. CONCLUSIONS Our results indicate species-specific biological differences in lifespan, which may play a role in facilitating tree species coexistence in mixed temperate forests. Finally, natural disturbances regimes were a key driver of lifespan, which could have implications for forest dynamics if regimes shift under global change.

opencc-zeroSep 2021View details →

Disentangling effects of disturbance severity and frequency: does bioindication really work?

Ecological disturbances are recognized as a crucial factor influencing the attributes of ecological communities. Depending on the specific adaptation or life cycle, plant species show different responses to disturbances of different magnitudes. Herben et al. (2016) proposed disturbance indicator values (DIVs) that describe the niche of each Central-European plant species along gradients of disturbance frequency and severity. Here we ask if the DIVs can be used in community ecology for bioindication of disturbance regime? We used a dataset of riparian forests sampled within mountain catchments (the Sudetes, SW Poland). As the regime of disturbance is driven by changes in floods from the spring towards the mouth, we calculated the position of every plot along longitudinal (upstream-downstream) gradient and used it as a proxy for the disturbance severity and frequency. We then calculated the community-weighted means (CWMs) for each of the six indices for each plot and analyzed whether these indices reflected the position of the plots along the rivers. We expected an increase in the severity indices and a decrease in the frequency indices downstream along the rivers. Moreover, we analyzed relationships between disturbance indices and species optima along longitudinal gradient. Surprisingly, means for all analyzed indices increased along the rivers. Severity indices showed the strongest association with the longitudinal gradient. The disturbance severity index for herbs was the only index that differed significantly among species with different responses along longitudinal gradient. On these results, we identified a strong correlation between the severity and frequency indices as the main problem. We conclude that the DIVs have considerable applicative potential; however, the determination of ecological niches separately for disturbance severity and frequency is difficult because different components interact to shape the realized niche of each species. All analyzed indices encompass different attributes of the disturbance regime including both severity and frequency.

opencc-zeroNov 2021View details →

Temporal biodiversity change following disturbance varies along an environmental gradient

Aim The diversity and composition of natural communities are rapidly changing due to anthropogenic disturbances. Magnitude of this compositional reorganization varies across the globe, but reasons behind the variation remain largely unknown. Disturbances induce temporal turnover by stimulating species colonizations, causing local extinctions, altering dominance structure, or all of these. We test which of these processes drive temporal community changes, and whether they are constrained by natural environmental gradients. Moreover, we assess to what degree identity shifts translate to changes in dominance structure. Location Finland Time period Observations 1985-2006, disturbance history >140 years. Major taxa studied Vascular plants. Methods We investigated temporal turnover of boreal forest understory in response to disturbance, here forest management, along a soil fertility gradient. We disentangle the roles of species gains, losses and abundance changes in driving temporal turnover in response to and after disturbance by comparing turnover rates in different forest age categories along fertility gradient. We quantify temporal turnover richness-based complement of Jaccard's similarity index and proportional-abundance based dissimilarity index. We also test whether disturbance history or fertility influence the relationship between identity shifts and dominance structure. Results We found that the impact of disturbance on temporal turnover depends on soil fertility. The greatest turnover occurred in most fertile forests immediately after disturbance. There, species gains and losses strongly altered dominance structure leading to high turnover, whereas undisturbed old forests and nutrient-poor habitats were characterized by stable dominant species even when the majority of species shifted their identity. Main conclusions Our results suggest that human impacts on temporal biodiversity change vary along environmental gradients. In boreal forests, the fertile habitats have higher probability than nutrient-poor sites to change their composition in response to anthropogenic disturbances. Resource availability and disturbance history may thus influence consequences of temporal turnover for ecosystem functioning.

opencc-zeroOct 2021View details →

Local canopy disturbance as an explanation for long-term increases in liana abundance

Canopy disturbance explains liana abundance and distribution within tropical forests and thus may also explain the widespread pattern of increasing liana abundance; however, this hypothesis remains untested. We used a 10-year study (2007 – 2017) of 117,100 rooted lianas in an old-growth Panamanian forest to test whether local canopy disturbance explains increasing liana abundance. We found that liana density increased 29.2% and basal area 12.5%. The vast majority of these increases were associated with clonal stem proliferation following canopy disturbance, particularly in liana-dense, low-canopy gaps, which had far greater liana increases than did undisturbed forest. Lianas may be ecological niche constructors; arresting tree regeneration in gaps and thus creating a high-light environment that favors sustained liana proliferation. Our findings demonstrate that liana abundance is increasing rapidly and their ability to proliferate via copious clonal stem production in canopy gaps explains much of their increase in this and possibly other tropical forests.