Institut für Landschafts- und Pflanzenökologie

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/11

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Automatic classification of submerged macrophytes at Lake Constance using laser bathymetry point clouds
(2024) Wagner, Nike; Franke, Gunnar; Schmieder, Klaus; Mandlburger, Gottfried; Stateczny, Andrzej
Submerged aquatic vegetation, also referred to as submerged macrophytes, provides important habitats and serves as a significant ecological indicator for assessing the condition of water bodies and for gaining insights into the impacts of climate change. In this study, we introduce a novel approach for the classification of submerged vegetation captured with bathymetric LiDAR (Light Detection And Ranging) as a basis for monitoring their state and change, and we validated the results against established monitoring techniques. Employing full-waveform airborne laser scanning, which is routinely used for topographic mapping and forestry applications on dry land, we extended its application to the detection of underwater vegetation in Lake Constance. The primary focus of this research lies in the automatic classification of bathymetric 3D LiDAR point clouds using a decision-based approach, distinguishing the three vegetation classes, (i) Low Vegetation, (ii) High Vegetation, and (iii) Vegetation Canopy, based on their height and other properties like local point density. The results reveal detailed 3D representations of submerged vegetation, enabling the identification of vegetation structures and the inference of vegetation types with reference to pre-existing knowledge. While the results within the training areas demonstrate high precision and alignment with the comparison data, the findings in independent test areas exhibit certain deficiencies that are likely addressable through corrective measures in the future.
Drought impacts on plant–soil carbon allocation - integrating future mean climatic conditions
(2025) Leyrer, Vinzent; Blum, Juliette; Marhan, Sven; Kandeler, Ellen; Zimmermann, Telse; Berauer, Bernd J.; Schweiger, Andreas H.; Canarini, Alberto; Richter, Andreas; Poll, Christian
Droughts affect soil microbial abundance and functions—key parameters of plant–soil carbon (C) allocation dynamics. However, the impact of drought may be modified by the mean climatic conditions to which the soil microbiome has previously been exposed. In a future warmer and drier world, effects of drought may therefore differ from those observed in studies that simulate drought under current climatic conditions. To investigate this, we used the field experiment ‘Hohenheim Climate Change,’ an arable field where predicted drier and warmer mean climatic conditions had been simulated for 12 years. In April 2021, we exposed this agroecosystem to 8 weeks of drought with subsequent rewetting. Before drought, at peak drought, and after rewetting, we pulse‐labelled winter wheat in situ with 13CO2 to trace recently assimilated C from plants to soil microorganisms and back to the atmosphere. Severe drought decreased soil respiration (−35%) and abundance of gram‐positive bacteria (−15%) but had no effect on gram‐negative bacteria, fungi, and total microbial biomass C. This pattern was not affected by the mean precipitation regime to which the microbes had been pre‐exposed. Reduced mean precipitation had, however, a legacy effect by decreasing the proportion of recently assimilated C allocated to the microbial biomass C pool (−50%). Apart from that, continuous soil warming was an important driver of C fluxes throughout our experiment, increasing plant biomass, root sugar concentration, labile C, and respiration. Warming also shifted microorganisms toward utilizing soil organic matter as a C source instead of recently assimilated compounds. Our study found that moderate shifts in mean precipitation patterns can impose a legacy on how plant‐derived C is allocated in the microbial biomass of a temperate agroecosystem during drought. The overarching effect of soil warming, however, suggests that how temperate agroecosystems respond to drought will mainly be affected by future temperature increases.
The importance of individual movement and feeding behaviour for long-distance seed dispersal by red deer: a data-driven model
(2020) Wright, Stephen J.; Heurich, Marco; Buchmann, Carsten M.; Böcker, Reinhard; Schurr, Frank M.
Background: Long-distance seed dispersal (LDD) has strong impacts on the spatiotemporal dynamics of plants. Large animals are important LDD vectors because they regularly transport seeds of many plant species over long distances. While there is now ample evidence that behaviour varies considerably between individual animals, it is not clear to what extent inter-individual variation in behaviour alters seed dispersal by animals. Methods: We study how inter-individual variation in the movement and feeding behaviour of one of Europe’s largest herbivores (the red deer, Cervus elaphus) affects internal seed dispersal (endozoochory) of multiple plant species. We combine movement data of 21 individual deer with measurements of seed loads in the dung of the same individuals and with data on gut passage time. These data serve to parameterize a model of passive dispersal that predicts LDD in three orientations (horizontal as well as upward and downward in elevation). With this model we investigate to what extent per-seed probabilities of LDD and seed load vary between individuals and throughout the vegetation period (May–December). Subsequently, we test whether per-seed LDD probability and seed load are positively (or negatively) correlated so that more mobile animals disperse more (or less) seeds. Finally, we examine whether non-random associations between per-seed LDD probability and seed load affect the LDD of individual plant species. Results: The studied deer dispersed viable seeds of at least 62 plant species. Deer individuals varied significantly in per-seed LDD probability and seed loads. However, more mobile animals did not disperse more or less seeds than less mobile ones. Plant species also did not differ significantly in the relationship between per-seed LDD probability and seed load. Yet plant species differed in how their seed load was distributed across deer individuals and in time, and this caused their LDD potential to differ more than twofold. For several plant species, we detected non-random associations between per-seed LDD probability and seed load that generally increased LDD potential. Conclusions: Inter-individual variation in movement and feeding behaviour means that certain deer are substantially more effective LDD vectors than others. This inter-individual variation reduces the reliability of LDD and increases the sensitivity of LDD to the decline of deer populations. Variation in the dispersal services of individual animals should thus be taken into account in models in order to improve LDD projections.
Quantifying patch‐specific seed dispersal and local population dynamics to estimate population spread of an endangered plant species
(2021) Zhu, Jinlei; Hrušková, Karolína; Pánková, Hana; Münzbergová, Zuzana
Aim: Habitat loss and fragmentation impose high extinction risk upon endangered plant species globally. For many endangered plant species, as the remnant habitats become smaller and more fragmented, it is vital to estimate the population spread rate of small patches in order to effectively manage and preserve them for potential future range expansion. However, population spread rate has rarely been quantified at the patch level to inform conservation strategies and management decisions. To close this gap, we quantify the patch-specific seed dispersal and local population dynamics of Minuartia smejkalii, which is a critically endangered plant species endemic in the Czech Republic and is of urgent conservation concern. Location: Želivka and Hrnčíře, Czechia. Methods: We conducted demographic analyses using population projection matrices with long-term demographic data and used an analytic mechanistic dispersal model to simulate seed dispersal. We then used information on local population dynamics and seed dispersal to estimate the population spread rate and compared the relative contributions of seed dispersal and population growth rate to the population spread rate. Results: We found that although both seed dispersal and population growth rate in M. smejkalii were critically limited, the population spread rate depended more strongly on the maximal dispersal distance than on the population growth rate. Main conclusions: We recommend conservationists to largely increase the dispersal distance of M. smejkalii. Generally, efforts made to increase seed dispersal ability could largely raise efficiency and effectiveness of conservation actions for critically endangered plant species.
Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology
(2025) Gould, Elliot; Berauer, Bernd J.; Ernst, Ulrich Rainer; Zitomer, Rachel A.
Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus , to compare sibling number and nestling growth) and one from conservation ecology ( Eucalyptus , to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.
Seed dispersal by wind decreases when plants are water‐stressed, potentially counteracting species coexistence and niche evolution
(2021) Zhu, Jinlei; Lukić, Nataša; Rajtschan, Verena; Walter, Julia; Schurr, Frank M.
Hydrology is a major environmental factor determining plant fitness, and hydrological niche segregation (HNS) has been widely used to explain species coexistence. Nevertheless, the distribution of plant species along hydrological gradients does not only depend on their hydrological niches but also depend on their seed dispersal, with dispersal either weakening or reinforcing the effects of HNS on coexistence. However, it is poorly understood how seed dispersal responds to hydrological conditions. To close this gap, we conducted a common‐garden experiment exposing five wind‐dispersed plant species (Bellis perennis, Chenopodium album, Crepis sancta, Hypochaeris glabra, and Hypochaeris radicata) to different hydrological conditions. We quantified the effects of hydrological conditions on seed production and dispersal traits, and simulated seed dispersal distances with a mechanistic dispersal model. We found species‐specific responses of seed production, seed dispersal traits, and predicted dispersal distances to hydrological conditions. Despite these species‐specific responses, there was a general positive relationship between seed production and dispersal distance: Plants growing in favorable hydrological conditions not only produce more seeds but also disperse them over longer distances. This arises mostly because plants growing in favorable environments grow taller and thus disperse their seeds over longer distances. We postulate that the positive relationship between seed production and dispersal may reduce the concentration of each species to the environments favorable for it, thus counteracting species coexistence. Moreover, the resulting asymmetrical gene flow from favorable to stressful habitats may slow down the microevolution of hydrological niches, causing evolutionary niche conservatism. Accounting for context‐dependent seed dispersal should thus improve ecological and evolutionary models for the spatial dynamics of plant populations and communities.

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