Agent-based models reveal limits of mark-release-recapture estimates for the rare butterfly, Bhutanitis thaidina (Lepidoptera: Papilionidae)

Insect diversity and abundance are in drastic decline worldwide, but quantifying insect populations to better conserve them is a difficult task. Mark-release-recapture (MRR) is widely used as an ecological indicator for insect populations, but the accuracy of MRR estimates can vary with factors such as spatial scale, sampling effort and models of inference. We conducted a 3-year MRR study of B. thaidina in Yanzigou valley, Mt. Gongga but failed to obtain sufficient data for a robust population estimate. This prompted us to integrate B. thaidina life history information to parameterize agent-based models and evaluate the conditions under which successful MRR studies could be conducted. We evaluated: (1) the performance of MRR models under different landscape types, and (2) the influence of experimental design on the accuracy and variance of MRR-based estimates. Our simulations revealed systematic underestimates of true population parameters by MRR models when sampling effort was insufficient. In a total of 2772 simulations, subjective decisions in sampling protocol (e.g., frequency, number of sampling locations, use of spatially explicit models, type of estimands) accounted for nearly half of the variation in estimates. We conclude that MRR-based estimates could be improved with the addition of more field-specific parameters.

A New Method Based on the von Mises-Fisher Distribution Shows that a Minority of Liver-Localized CD8 T Cells Display Hard-To-Detect Attraction to Plasmodium-Infected Hepatocytes

Malaria is a disease caused by Plasmodium parasites, resulting in over 200 million infections and 400,000 deaths every year. A critical step of malaria infection is when sporozoites, injected by mosquitoes, travel to the liver and form liver stages. Malaria vaccine candidates which induce large numbers of malaria-specific CD8 T cells in mice are able to eliminate all liver stages, preventing fulminant malaria. However, how CD8 T cells find all parasites in 48 h of the liver stage lifespan is not well understood. Using intravital microscopy of murine livers, we generated unique data on T cell search for malaria liver stages within a few hours after infection. To detect attraction of T cells to an infection site, we used the von Mises-Fisher distribution in 3D, similar to the 2D von Mises distribution previously used in ecology. Our results suggest that the vast majority (70-95%) of malaria-specific and non-specific liver-localized CD8 T cells did not display attraction towards the infection site, suggesting that the search for malaria liver stages occurs randomly. However, a small fraction (15-20%) displayed weak but detectable attraction towards parasites which already had been surrounded by several T cells. We found that speeds and turning angles correlated with attraction, suggesting that understanding mechanisms that determine the speed of T cell movement in the liver may improve the efficacy of future T cell-based vaccines. Stochastic simulations suggest that a small movement bias towards the parasite dramatically reduces the number of CD8 T cells needed to eliminate all malaria liver stages, but to detect such attraction by individual cells requires data from long imaging experiments which are not currently feasible. Importantly, as far as we know this is the first demonstration of how activated/memory CD8 T cells might search for the pathogen in nonlymphoid tissues a few hours after infection. We have also established a framework for how attraction of individual T cells towards a location in 3D can be rigorously evaluated.

Global economic costs of aquatic invasive alien species

Much research effort has been invested in understanding ecological impacts of invasive alien species (IAS) across ecosystems and taxonomic groups, but empirical studies about economic effects lack synthesis. Using a comprehensive global database, we determine patterns and trends in economic costs of aquatic IAS by examining: (i) the distribution of these costs across taxa, geographic regions and cost types; (ii) the temporal dynamics of global costs; and (iii) knowledge gaps, especially compared to terrestrial IAS. Based on the costs recorded from the existing literature, the global cost of aquatic IAS conservatively summed to US$345 billion, with the majority attributed to invertebrates (62%), followed by vertebrates (28%), then plants (6%). The largest costs were reported in North America (48%) and Asia (13%), and were principally a result of resource damages (74%); only 6% of recorded costs were from management. The magnitude and number of reported costs were highest in the United States of America and for semi-aquatic taxa. Many countries and known aquatic alien species had no reported costs, especially in Africa and Asia. Accordingly, a network analysis revealed limited connectivity among countries, indicating disparate cost reporting. Aquatic IAS costs have increased in recent decades by several orders of magnitude, reaching at least US$23 billion in 2020. Costs are likely considerably underrepresented compared to terrestrial IAS; only 5% of reported costs were from aquatic species, despite 26% of known invaders being aquatic. Additionally, only 1% of aquatic invasion costs were from marine species. Costs of aquatic IAS are thus substantial, but likely underreported. Costs have increased over time and are expected to continue rising with future invasions. We urge increased and improved cost reporting by managers, practitioners and researchers to reduce knowledge gaps. Few costs are proactive investments; increased management spending is urgently needed to prevent and limit current and future aquatic IAS damages.

Three-dimensional random walk models of individual animal movement and their application to trap counts modelling

BACKGROUND

Random walks (RWs) have proved to be a powerful modelling tool in ecology, particularly in the study of animal movement. An application of RW concerns trapping which is the predominant sampling method to date in insect ecology and agricultural pest management. A lot of research effort has been directed towards modelling ground-dwelling insects by simulating their movement in 2D, and computing pitfall trap counts, but comparatively very little for flying insects with 3D elevated traps.

METHODS

We introduce the mathematics behind 3D RWs and present key metrics such as the mean squared displacement (MSD) and path sinuosity, which are already well known in 2D. We develop the mathematical theory behind the 3D correlated random walk (CRW) which involves short-term directional persistence and the 3D Biased random walk (BRW) which introduces a long-term directional bias in the movement so that there is an overall preferred movement direction. In this study, we focus on the geometrical aspects of the 3D trap and thus consider three types of shape; a spheroidal trap, a cylindrical trap and a rectangular cuboidal trap. By simulating movement in 3D space, we investigated the effect of 3D trap shapes and sizes and of movement diffusion on trapping efficiency.

RESULTS

We found that there is a non-linear dependence of trap counts on the trap surface area or volume, but the effect of volume appeared to be a simple consequence of changes in area. Nevertheless, there is a slight but clear hierarchy of trap shapes in terms of capture efficiency, with the spheroidal trap retaining more counts than a cylinder, followed by the cuboidal type for a given area. We also showed that there is no effect of short-term persistence when diffusion is kept constant, but trap counts significantly decrease with increasing diffusion.

CONCLUSION

Our results provide a better understanding of the interplay between the movement pattern, trap geometry and impacts on trapping efficiency, which leads to improved trap count interpretations, and more broadly, has implications for spatial ecology and population dynamics.

Reconstructing the Intrinsic Statistical Properties of Intermittent Locomotion Through Corrections for Boundary Effects

Locomotion characteristics are often recorded within bounded spaces, a constraint which introduces geometry-specific biases and potentially complicates the inference of behavioural features from empirical observations. We describe how statistical properties of an uncorrelated random walk, namely the steady-state stopping location probability density and the empirical step probability density, are affected by enclosure in a bounded space. The random walk here is considered as a null model for an organism moving intermittently in such a space, that is, the points represent stopping locations and the step is the displacement between them. Closed-form expressions are derived for motion in one dimension and simple two-dimensional geometries, in addition to an implicit expression for arbitrary (convex) geometries. For the particular choice of no-go boundary conditions, we demonstrate that the empirical step distribution is related to the intrinsic step distribution, i.e. the one we would observe in unbounded space, via a multiplicative transformation dependent solely on the boundary geometry. This conclusion allows in practice for the compensation of boundary effects and the reconstruction of the intrinsic step distribution from empirical observations.

Animal intermittent locomotion: A null model for the probability of moving forward in bounded space

We present a null model to be compared with biological data to test for intrinsic persistence in movement between stops during intermittent locomotion in bounded space with different geometries and boundary conditions. We describe spatio-temporal properties of the sequence of stopping points r₁,r₂,r₃,… visited by a Random Walker within a bounded space. The path between stopping points is not considered, only the displacement. Since there are no intrinsic correlations in the displacements between stopping points, there is no intrinsic persistence in the movement between them. Hence, this represents a null-model against which to compare empirical data for directional persistence in the movement between stopping points when there is external bias due to the bounded space. This comparison is a necessary first step in testing hypotheses about the function of the stops that punctuate intermittent locomotion in diverse organisms. We investigate the probability of forward movement, defined as a deviation of less than 90° between two successive displacement vectors, as a function of the ratio between the largest displacement between stops that could be performed by the random walker and the system size, α=Δℓ/L_max. As expected, the probability of forward movement is 1/2 when α→0. However, when α is finite, this probability is less than 1/2 with a minimum value when α=1. For certain boundary conditions, the minimum value is between 1/3 and 1/4 in 1D while it can be even lower in 2D. The probability of forward movement in 1D is calculated exactly for all values 0<α⩽1 for several boundary conditions. Analytical calculations for the probability of forward movement are performed in 2D for circular and square bounded regions with one boundary condition. Numerical results for all values 0<α⩽1 are presented for several boundary conditions. The cases of rectangle and ellipse are also considered and an approximate model of the dependence of the forward movement probability on the aspect ratio is provided. Finally, some practical points are presented on how these results can be utilised in the empirical analysis of animal movement in two-dimensional bounded space.

Flower power in the city: Replacing roadside shrubs by wildflower meadows increases insect numbers and reduces maintenance costs

Massive declines in insect biodiversity and biomass are reported from many regions and habitats. In urban areas, creation of native wildflower meadows is one option to support insects and reduce maintenance costs of urban green spaces. However, benefits for insect conservation may depend on previous land use, and the size and location of new wildflower meadows. We show effects of conversion of roadside plantings-from exotic shrubs into wildflower meadows-on (1) the abundance of 13 arthropod taxa-Opiliones, Araneae, Isopoda, Collembola, Orthoptera, Aphidoidea, Auchenorrhyncha, Heteroptera, Coleoptera, Nematocera, Brachycera, Apocrita, Formicidae-and (2) changes in maintenance costs. We assessed the influence of vegetation type (meadow vs. woody), meadow age, size, location (distance to city boundary), and mowing regime. We found many, but not all, arthropod taxa profiting from meadows in terms of arthropod activity abundance in pitfall traps and arthropod density in standardized suction samples. Arthropod number in meadows was 212% higher in pitfall traps and 260% higher in suction samples compared to woody vegetation. The increased arthropod number in meadows was independent of the size and isolation of green spaces for most taxa. However, mowing regime strongly affected several arthropod taxa, with an increase of 63% of total arthropod density in unmown compared to mown meadow spots. Costs of green space maintenance were fivefold lower for meadows than for woody vegetation. Our study shows that (1) many different arthropod taxa occur in roadside vegetation in urban areas, (2) replacement of exotic woody vegetation by native wildflower meadows can significantly increase arthropod abundance, especially if meadow management permits temporarily unmown areas, and (3) maintenance costs can be considerably reduced by converting woody plantings into wildflower meadows. Considering many groups of arthropods, our study provides new insights into possible measures to support arthropods in urban environments.