Costs of dispersal Bonte, Dries; Van Dyck, Hans; Bullock, James M. ...
Biological reviews of the Cambridge Philosophical Society,
20/May , Letnik:
87, Številka:
2
Journal Article
Recenzirano
Dispersal costs can be classified into energetic, time, risk and opportunity costs and may be levied directly or deferred during departure, transfer and settlement. They may equally be incurred ...during life stages before the actual dispersal event through investments in special morphologies. Because costs will eventually determine the performance of dispersing individuals and the evolution of dispersal, we here provide an extensive review on the different cost types that occur during dispersal in a wide array of organisms, ranging from micro‐organisms to plants, invertebrates and vertebrates. In general, costs of transfer have been more widely documented in actively dispersing organisms, in contrast to a greater focus on costs during departure and settlement in plants and animals with a passive transfer phase. Costs related to the development of specific dispersal attributes appear to be much more prominent than previously accepted. Because costs induce trade‐offs, they give rise to covariation between dispersal and other life‐history traits at different scales of organismal organisation. The consequences of (i) the presence and magnitude of different costs during different phases of the dispersal process, and (ii) their internal organisation through covariation with other life‐history traits, are synthesised with respect to potential consequences for species conservation and the need for development of a new generation of spatial simulation models.
Machine learning (ML) expands traditional data analysis and presents a range of opportunities in ecosystem service (ES) research, offering rapid processing of ‘big data’ and enabling significant ...advances in data description and predictive modelling. Descriptive ML techniques group data with little or no prior domain specific assumptions; they can generate hypotheses and automatically sort data prior to other analyses. Predictive ML techniques allow for the predictive modelling of highly non-linear systems where casual mechanisms are poorly understood, as is often the case for ES. We conducted a review to explore how ML is used in ES research and to identify and quantify trends in the different ML approaches that are used. We reviewed 308 peer-reviewed publications and identified that ES studies implemented machine learning techniques in data description (64%; n = 308) and predictive modelling (44%), with some papers containing both categories. Classification and Regression Trees were the most popular techniques (60%), but unsupervised learning techniques were also used for descriptive tasks such as clustering to group or split data without prior assumptions (19%). Whilst there are examples of ES publications that apply ML with rigour, many studies do not have robust or repeatable methods. Some studies fail to report model settings (43%) or software used (28%), and many studies do not report carrying out any form of model hyperparameter tuning (67%) or test model generalisability (59%). Whilst studies use ML to analyse very large and complex datasets, ES research is generally not taking full advantage of the capacity of ML to model big data (1138 medium number of data points; 13 median quantity of variables). There is great further opportunity to utilise ML in ES research, to make better use of big data and to develop detailed modelling of spatial-temporal dynamics that meet stakeholder demands.
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•Machine learning (ML) is increasingly being used in ecosystem service research.•ML is used for describing data and predictive modelling.•Many ecosystem service (ES) studies lack rigour in how ML is used.•Capacity to use ML on big ES data has not been fully realised.•We highlight best practice for ongoing use of machine learning in ES research.
Human-mediated dispersal is known as an important driver of long-distance dispersal for plants but underlying mechanisms have rarely been assessed. Road corridors function as routes of secondary ...dispersal for many plant species but the extent to which vehicles support this process remains unclear. In this paper we quantify dispersal distances and seed deposition of plant species moved over the ground by the slipstream of passing cars. We exposed marked seeds of four species on a section of road and drove a car along the road at a speed of 48 km/h. By tracking seeds we quantified movement parallel as well as lateral to the road, resulting dispersal kernels, and the effect of repeated vehicle passes. Median distances travelled by seeds along the road were about eight meters for species with wind dispersal morphologies and one meter for species without such adaptations. Airflow created by the car lifted seeds and resulted in longitudinal dispersal. Single seeds reached our maximum measuring distance of 45 m and for some species exceeded distances under primary dispersal. Mathematical models were fit to dispersal kernels. The incremental effect of passing vehicles on longitudinal dispersal decreased with increasing number of passes as seeds accumulated at road verges. We conclude that dispersal by vehicle airflow facilitates seed movement along roads and accumulation of seeds in roadside habitats. Dispersal by vehicle airflow can aid the spread of plant species and thus has wide implications for roadside ecology, invasion biology and nature conservation.
Dispersal is fundamental in determining biodiversity responses to rapid climate change, but recently acquired ecological and evolutionary knowledge is seldom accounted for in either predictive ...methods or conservation planning. We emphasise the accumulating evidence for direct and indirect impacts of climate change on dispersal. Additionally, evolutionary theory predicts increases in dispersal at expanding range margins, and this has been observed in a number of species. This multitude of ecological and evolutionary processes is likely to lead to complex responses of dispersal to climate change. As a result, improvement of models of species' range changes will require greater realism in the representation of dispersal. Placing dispersal at the heart of our thinking will facilitate development of conservation strategies that are resilient to climate change, including landscape management and assisted colonisation.
Niche shifts of nonnative plants can occur when they colonize novel climatic conditions. However, the mechanistic basis for niche shifts during invasion is poorly understood and has rarely been ...captured within species distribution models. We quantified the consequence of between-population variation in phenology for invasion of common ragweed (Ambrosia artemisiifolia L.) across Europe. Ragweed is of serious concern because of its harmful effects as a crop weed and because of its impact on public health as a major aeroallergen. We developed a forward mechanistic species distribution model based on responses of ragweed development rates to temperature and photoperiod. The model was parameterized and validated from the literature and by reanalyzing data from a reciprocal common garden experiment in which native and invasive populations were grown within and beyond the current invaded range. It could therefore accommodate between-population variation in the physiological requirements for flowering, and predict the potentially invaded ranges of individual populations. Northern-origin populations that were established outside the generally accepted climate envelope of the species had lower thermal requirements for bud development, suggesting local adaptation of phenology had occurred during the invasion. The model predicts that this will extend the potentially invaded range northward and increase the average suitability across Europe by 90% in the current climate and 20% in the future climate. Therefore, trait variation observed at the population scale can trigger a climatic niche shift at the biogeographic scale. For ragweed, earlier flowering phenology in established northern populations could allow the species to spread beyond its current invasive range, substantially increasing its risk to agriculture and public health. Mechanistic species distribution models offer the possibility to represent niche shifts by varying the traits and niche responses of individual populations. Ignoring such effects could substantially underestimate the extent and impact of invasions.
Question
Human‐mediated dispersal (HMD) comprises human‐vectored dispersal (HVD; direct movement of organisms by people) and human‐altered dispersal (HAD; indirect change in dispersal patterns ...through human alteration of ecosystems). In the vegetation dynamics literature, human influence has primarily been studied in terms of perturbations to natural communities. Except for non‐native invasions, the role of HMD in vegetation dynamics has rarely been considered. Given the increasing human population and its pervasive impacts across the world, it is necessary to understand the different ways in which HMD drives changes in vegetation dynamics. Importantly how large are these influences and how do they disrupt natural processes?
Method
We reviewed studies examining aspects of HMD in relation to vegetation dynamics and used the broader literature to inform a conceptual synthesis of the impacts of HMD on vegetation dynamics.
Results & Conclusions
The propensity to be affected by HMD varies among species, and this is related to seed and plant traits. Together, these effects combine to determine whether HMD disrupts or enhances seed dispersal into a community. The ultimate consequences of changed arrival of seeds into a community are determined by the strength of the environmental and biotic filters, which govern the establishment and persistence of species. The effect of accidental HVD depends whether it follows the same rules as for natural dispersal; indeed humans might replace lost natural dispersers and thus enhance community resilience. Intentional HVD through sowing or planting will generally be highly disruptive especially as it often involves associated management. Traditionally, HAD has been considered to disrupt vegetation dynamics through, e.g., fragmentation or loss of natural dispersers. However, an HMD perspective can inform actions related to HAD that increase resilience, e.g., green infrastructure or vegetation management. Our framework encourages researchers to consider HMD holistically, to understand how the increasing human footprint might affect vegetation dynamics and resilience under future change.
The role of human‐mediated dispersal (HMD) in vegetation dynamics has rarely been considered, despite the increasing human population and its pervasive impacts across the world. Different HMD processes can either disrupt or enhance dispersal, depending on the species, its traits, and the socio‐ecological landscape. An HMD approach can provide insights into how the dispersal filter drives vegetation dynamics, and also inform actions which will increase vegetation resilience under anthropogenic environmental change.
•We undertook a meta-analysis to assess impacts of tropical selective logging.•This focused on stand damage, aboveground biomass and tree species richness.•Higher logging intensity increased damage, ...and reduced biomass and species richness.•Reduced impact logging reduces damage, this was not true for biomass or richness.•More research is needed to determine impact of reduced impact logging on carbon.
Over 400 million hectares of tropical forest are currently designated as logging concessions. This practice is an important source of timber, but there are concerns about its long-term sustainability and impacts on biodiversity and carbon storage. However, logging impacts vary widely, making generalisation and, consequently, policy implementation, difficult. Recent syntheses of animal biodiversity have indicated that differences in logging intensity – the volume of wood removed ha−1 – might help to explain some of these disparities. In addition, it has widely been assumed that reduced impact logging (RIL) might minimise some of the negative effects of logging; though in practice, this has rarely been tested. To test the hypothesis that RIL reduces negative impacts of selective logging once intensity is controlled for, we used meta-analyses of selective logging impact studies, focusing specifically on (1) residual tree damage, (2) aboveground biomass and (3) tree species richness. Our results indicate that RIL appears to reduce residual tree damage when compared to conventional methods. However, changes in aboveground biomass were negatively related to logging intensity. Any effect of RIL, independent of logging intensity, was difficult to discern since it was carried out at relatively low intensities. Tree richness appeared to increase at low intensities but decreased at higher intensities and any effect of RIL was difficult to detect. Our results tentatively support the hypothesis that RIL reduces the negative impacts of logging on tree damage, but do not support suggestions that RIL reduces loss of aboveground biomass or tree species richness. However, this lack of support may be a result of the relative paucity of data on the topic. Based on our results, we suggest that better evidence is needed to assess the differences between the impacts of RIL and conventional logging. Studies that consider plot-level differences in logging intensity are required to fill this knowledge gap. In addition, there must be clarification of whether RIL is an inherently low intensity practice so that this can be factored into management.
Natural succession of vegetation on abandoned farmland provides opportunities for passive rewilding to re-establish native woodlands, but in Western Europe the patterns and outcomes of vegetation ...colonisation are poorly known. We combine time series of field surveys and remote sensing (lidar and photogrammetry) to study woodland development on two farmland fields in England over 24 and 59 years respectively: the New Wilderness (2.1 ha) abandoned in 1996, and the Old Wilderness (3.9 ha) abandoned in 1961, both adjacent to ancient woodland. Woody vegetation colonisation of the New Wilderness was rapid, with 86% vegetation cover averaging 2.9 m tall after 23 years post-abandonment. The Old Wilderness had 100% woody cover averaging 13.1 m tall after 53 years, with an overstorey tree-canopy (greater than or equal to 8 m tall) covering 91%. By this stage, the structural characteristics of the Old Wilderness were approaching those of neighbouring ancient woodlands. The woody species composition of both Wildernesses differed from ancient woodland, being dominated by animal-dispersed pedunculate oak Quercus robur and berry-bearing shrubs. Tree colonisation was spatially clustered, with wind-dispersed common ash Fraxinus excelsior mostly occurring near seed sources in adjacent woodland and hedgerows, and clusters of oaks probably resulting from acorn hoarding by birds and rodents. After 24 years the density of live trees in the New Wilderness was 132/ha (57% oak), with 390/ha (52% oak) in the Old Wilderness after 59 years; deadwood accounted for 8% of tree stems in the former and 14% in the latter. Passive rewilding of these 'Wilderness' sites shows that closed-canopy woodland readily re-established on abandoned farmland close to existing woodland, it was resilient to the presence of herbivores and variable weather, and approached the height structure of older woods within approximately 50 years. This study provides valuable long-term reference data in temperate Europe, helping to inform predictions of the potential outcomes of widespread abandonment of agricultural land in this region.
Abstract Agri-environmental schemes (AES) are the main policy tool to counteract farmland biodiversity declines in Europe, but their biodiversity benefit varies across sites and is likely moderated ...by landscape context. Systematic monitoring of AES outcomes is lacking, and AES assessments are often based on field experiments encompassing one or few study sites. Spatial analysis methods encompassing broader areas are therefore crucial to better understand the context dependency of species’ responses to AES. Here, we quantified red-backed shrike ( Lanius collurio ) occurrences in relation to AES adoption in three agricultural regions: Catalonia in Spain, the Mulde River Basin in Germany, and South Moravia in the Czech Republic. We used pre-collected biodiversity datasets, comprising structured and unstructured monitoring data, to compare empirical evidence across regions. Specifically, in each region we tested whether occurrence probability was positively related with the proportion of grassland-based AES, and whether this effect was stronger in simple compared to complex landscapes. We built species distribution models using existing field observations of the red-backed shrike, which we related to topographic, climatic, and field-level land-use information complemented with remote sensing-derived land-cover data to map habitats outside agricultural fields. We found a positive relationship between AES area and occurrence probability of the red-backed shrike in all regions. In Catalonia, the relationship was stronger in structurally simpler landscapes, but we found little empirical support for similar landscape-moderated effects in South Moravia and the Mulde River Basin. Our results highlight the complexity of species’ responses to management across different regional and landscape contexts, which needs to be considered in the design and spatial implementation of future conservation measures.
Drought can induce phenotypic plasticity in a range of plant root and shoot traits. These traits have been shown to explain differences in root and shoot litter decomposability between species. ...However, it is unknown how drought‐induced plasticity of root and shoot traits alters their decomposability.
To investigate this issue across a range of species, we grew a grass Lolium perenne, a forb Plantago lanceolata and a legume Trifolium repens common to European temperate grasslands and subjected them to a 5‐week moderate drought treatment. We compared morphological and chemical root and shoot traits of the droughted plants to well‐watered controls. We then conducted a decomposition assay of the senesced root and shoot material over 16 weeks, with mass loss measurements at five timepoints.
Drought had significant and sometimes strong effects on morphological and chemical root and shoot traits of all three species, sometimes similar to differences between species and generally in line with a shift to a more resource‐conservative strategy. Drought also increased the labile litter fraction in roots of Lolium perenne, which was associated with a substantial increase in non‐structural carbohydrates. Drought decreased the labile litter fraction in shoots of Plantago lanceolata, but this could not be explained by the traits we measured. Drought effects on litter decomposability were weaker than on plant traits.
Our results suggest that plant trait‐mediated effects of drought on litter decomposability can either increase or decrease vegetation feedbacks to climate change. They also show that drought‐induced plasticity in root and shoot traits does not automatically translate into equivalent changes in litter decomposability.
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Zusammenfassung
Trockenheit kann phänotypische Plastizität in einer Reihe von Wurzel‐ und Sprossmerkmalen hervorrufen. Es ist bekannt, dass sich mit den gleichen Pflanzenmerkmerkmalen auch Unterschiede in der Zersetzbarkeit von Wurzel‐ und Sprossstreu zwischen Spezies erklären lassen. Jedoch wurde bislang kaum untersucht, wie sich durch Trockenheit hervorgerufene Plastizität von Wurzel‐ und Sprossmerkmalen auf die Zersetzbarkeit der Wurzel‐ und Sprossstreu auswirkt.
Um diese Frage in einigen in europäischem temperierten Grünland häufig vorkommenden Spezies zu untersuchen, zogen wir ein Gras (Lolium perenne), ein Kraut (Plantago lanceolata) und eine Leguminose (Trifolium repens), und setzten sie einer fünfwöchigen mäßig intensiven Trockenperiode aus. Wir verglichen morphologische und chemische Wurzel‐ und Sprossmerkmale zwischen den Pflanzen, die Trockenheit ausgesetzt waren, und den Pflanzen der Kontrollgruppe ohne Trockenheit. Um die Zersetzbarkeit des verwelkten Wurzel‐ und Sprossmaterials zu bestimmen, führten wir einen 16‐wöchigen Zersetzbarkeitsassay durch, mit Messung des Masseverlust zu fünf Zeitpunkten.
Trockenheit hatte signifikante und teilweise starke Auswirkungen auf morphologische und chemische Wurzel‐ und Sprossmerkmale aller drei Spezies, teilweise so groß wie Unterschiede zwischen Spezies, und generell im Einklang mit einer Verschiebung der Pflanzenstrategie in Richtung einer effizienteren Ressourcennutzung. Trockenheit erhöhte außerdem den labilen Streuanteil der Wurzeln von Lolium perenne, was mit einer Zunahme der nicht‐strukturellen Kohlenhydrate einherging. Trockenheit verminderte den labilen Streuanteil in den Sprossen von Plantago lanceolata, aber dies ließ sich nicht mit den gemessenen Pflanzenmerkmalen erklären. Die Effekte von Trockenheit auf die Streuzersetzbarkeit waren schwächer als die Effekte auf Pflanzenmerkmale.
Unsere Ergebnisse legen nahe, dass Vegetationsfeedbacks auf den Klimawandel durch die Auswirkungen von Trockenheit auf die Streuzersetzbarkeit entweder verstärkt oder geschwächt werden können. Sie zeigen außerdem, dass durch Trockenheit hervorgerufene Plastizität von Wurzel‐ und Sprossmerkmalen nicht automatisch äquivalente Veränderungen in der Streuzersetzbarkeit hervorruft.
Read the free Plain Language Summary for this article on the Journal blog.
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