Human-mediated dispersal and disturbance shape the metapopulation dynamics of a long-lived herb.

As anthropogenic impacts on the natural world escalate, there is increasing interest in the role of humans in dispersing seeds. But the consequences of this Human-Mediated Dispersal (HMD) on plant spatial dynamics are little studied. In this paper, we ask how secondary dispersal by HMD affects the dynamics of a natural plant metapopulation. In addition to dispersal between patches, we suggest within-patch processes can be critical. To address this, we assess how variation in local population dynamics, caused by small-scale disturbances, affects metapopulation size. We created an empirically based model with stochastic population dynamics and dispersal among patches, which represented a real-world, cliff-top metapopulation of wild cabbage Brassica oleracea. We collected demographic data from multiple populations by tagging plants over eight years. We assessed seed survival, and establishment and survival of seedlings in intact vegetation vs. small disturbances. We modeled primary dispersal by wind using field data and used experimental data on secondary HMD by hikers. We monitored occupancy patterns over a 14-yr period in the real metapopulation. Disturbance had large effects on local population growth rates, by increasing seedling establishment and survival. This meant that the modeled metapopulation grew in size only when the area disturbed in each patch was above 35%. In these growing metapopulations, although only 0.2% of seeds underwent HMD, this greatly enhanced metapopulation growth rates. Similarly, HMD allowed more colonizations in declining metapopulations under low disturbance, and this slowed the rate of decline. The real metapopulation showed patterns of varying patch occupancy over the survey years, which were related to habitat quality, but also positively to human activity along the cliffs, hinting at beneficial effects of humans. These findings illustrate that realistic changes to dispersal or demography, specifically by humans, can have fundamental effects on the viability of a species at the landscape scale.

Human-mediated dispersal of seeds by the airflow of vehicles.

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.

Human-mediated dispersal of seeds over long distances.

Human activities have fundamental impacts on the distribution of species through altered land use, but also directly by dispersal of propagules. Rare long-distance dispersal events have a disproportionate importance for the spread of species including invasions. While it is widely accepted that humans may act as vectors of long-distance dispersal, there are few studies that quantify this process. We studied in detail a mechanism of human-mediated dispersal (HMD). For two plant species we measured, over a wide range of distances, how many seeds are carried by humans on shoes. While over half of the seeds fell off within 5m, seeds were regularly still attached to shoes after 5 km. Semi-mechanistic models were fitted, and these suggested that long-distance dispersal on shoes is facilitated by decreasing seed detachment probability with distance. Mechanistic modelling showed that the primary vector, wind, was less important as an agent of long-distance dispersal, dispersing seeds less than 250 m. Full dispersal kernels were derived by combining the models for primary dispersal by wind and secondary dispersal by humans. These suggest that walking humans can disperse seeds to very long distances, up to at least 10 km, and provide some of the first quantified dispersal kernels for HMD.

Short-term transformation of matrix into hospitable habitat facilitates gene flow and mitigates fragmentation.

Habitat fragmentation has major implications for demography and genetic structure of natural plant and animal populations as small and isolated populations are more prone to extinction. Therefore, many recent studies focus on spatial fragmentation. However, the temporal configuration of suitable habitat may also influence dispersal and gene flow in fragmented landscapes. We hypothesize that short-term switching of inhospitable matrix areas into suitable habitat can mitigate effects of spatial fragmentation in natural and seminatural ecosystems. To test our hypothesis, we investigated the hairy-footed gerbil (Gerbillurus paeba, Smith 1836), a ground-dwelling rodent, in fragmented Kalahari savannah areas. Here, rare events of high above mean annual rainfall suggest short-term matrix suitability. During the field survey in 'matrix' areas in the Kalahari (shrub encroachment by heavy grazing) we never observed the hairy-footed gerbil in years of average rainfall, but observed mass occurrences of this species during rare events of exceptionally high rainfall. In a second step, we developed an agent-based model simulating subpopulations in two neighbouring habitats and the separating matrix. Our mechanistic model reproduces the mass occurrences as observed in the field and thus suggests the possibly underlying processes. In particular, the temporary improvement in matrix quality allows reproduction in the matrix, thereby causing a substantial increase in population size. The model demonstrates further how the environmental trigger (rainfall) impacts genetic connectivity of two separated subpopulations. We identified seasonality as a driver of fragmentation but stochasticity leading to higher connectivity. We found that our concept of temporal fragmentation can be applied to numerous other fragmented populations in various ecological systems and provide examples from recent literature. We conclude that temporal aspects of fragmentation must be considered in both ecological research and conservation management.

Extinction risk, coloured noise and the scaling of variance.

The impact of temporally correlated fluctuating environments (coloured noise) on the extinction risk of populations has become a main focus in theoretical population ecology. In this study we particularly focus on the extinction risk in strongly correlated environments. Here, we found that, in contrast to moderate auto-correlation, the extinction risk was highly dependent on the process of noise generation, in particular on the method of variance scaling. Such scaling is commonly applied to avoid variance-driven biases when comparing the extinction risk under white and coloured noise. We show that for strong auto-correlation often-used scaling techniques lead to a high variability in the variances of the resulting time series and thus to deviations in the subsequent extinction risk. Therefore, we present an alternative scaling method that always delivers the target variance, even in the case of strong auto-correlation. In contrast to earlier techniques, our very intuitive method is not bound to auto-regressive processes but can be applied to all types of coloured noises. We strongly recommend our method to generate time series when the target of interest is the effect of noise colour on extinction risk not obscured by any variance effects.