Robert D. Holt’s research while affiliated with University of Florida and other places

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Publications (355)


Metapopulations, the Inflationary Effect, and Consequences for Public Health
  • Article

November 2024

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12 Reads

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2 Citations

The American Naturalist

Nicholas Kortessis

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Andrew Gonzalez

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[...]

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Robert D. Holt

Figure 3
Figure 4
The Prominent Role of the Matrix in Ecology, Evolution, and Conservation
  • Article
  • Full-text available

August 2024

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525 Reads

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2 Citations

Annual Review of Ecology Evolution and Systematics

As the Anthropocene proceeds, the matrix in which remaining habitats are embedded is an increasingly dominant component of altered landscapes. The matrix appears to have diverse and far-reaching effects, yet our understanding of the causes and consequences of these effects remains limited. We first synthesize the broad range of perspectives on the matrix, provide a generalized framing that captures these perspectives, and propose hypotheses for how and why the matrix matters for ecological and evolutionary processes. We then summarize evidence for these hypotheses from experiments in which the matrix was manipulated. Nearly all experiments revealed matrix effects, including changes in local spillover, individual movement and dispersal, and use of resources in the matrix. Finally, we discuss how the matrix has been, and should be, incorporated into conservation and management and suggest future issues to advance research on and applications of the matrix in ecology, evolution, and conservation.

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Figure 3. The probability of population persistence, up to generation 500. The environmental step change is equal to 3. The developmental limit is represented as the fraction of the step change covered by D/2. In all graphs, the solid black line represents the average persistence with no plasticity (b = 0). (A) Developmental limits only for different plasticity parameters (b). (B) Developmental limits plus a cost of plasticity for different plasticity parameters (b). (C) Developmental limits plus developmental noise for different amounts of noise (s), (b = 0.6). (D) Developmental limits plus within-and among-generation environmental variation for different noise parameters (τ). The within-generation variation was autocorrelated (ρ = 0.5, b = 0.6).
Figure 4. The average relative plasticity for populations persisting to generation 500, assuming an environmental step change of 3. The developmental limit is scaled as the fraction of the step change covered by D/2. (A) Developmental limits assume only different plasticity parameters (the parameter b). (B) Developmental limits plus a cost of plasticity, for different values of b. (C) Developmental limits plus different amounts of developmental noise (s), for a fixed plasticity parameter (b = 0.6). (D) Developmental limits plus different amounts of within-and among-generation environmental variation (τ). The within-generation variation was autocorrelated (ρ = 0.5, b = 0.6).
Figure 5. The average relative plasticity as a function of time since the environmental change (step change = 3), for populations persisting up to 500 generations. The developmental limit is represented as the fraction of the step change covered by D/2: (A) developmental limit = 0.33, (B) developmental limit = 0.67, (C) developmental limit = 1.0, (D) developmental limit = 1.33. The plasticity parameter was the same in all cases (b = 0.6). Each panel shows the four scenarios: developmental limits only (solid line), developmental limits plus a cost of plasticity (dotted line), developmental limits plus developmental noise (dashed line), developmental limits plus within-and among-generation environmental variation (dash-dotted line). (b = plasticity parameter, c = cost of plasticity, s = developmental noise, τ = environmental variation, ρ = environmental autocorrelation).
The genetics of phenotypic plasticity. XVIII. Developmental limits restrict adaptive plasticity

August 2024

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68 Reads

Evolution

After environmental change, the trait evolution needed to rescue a population depends on the functional form of the plastic change (reaction norm) of that trait. Nearly all previous models of plasticity evolution for continuous traits have assumed that the functional form is linear, i.e., no limits on the range of plasticity. This paper examines the effect of developmental limits, modeled as a sigmoidal reaction norm, on evolutionary rescue after an abrupt environmental change and the subsequent evolution of plasticity, including genetic assimilation. We examined four different scenarios: (1) developmental limits only, (2) developmental limits plus a cost of plasticity, (3) developmental limits with developmental noise, and (4) developmental limits plus environmental variation. The probability of evolutionary rescue increased with an increase in phenotypic variation allowed by plastic development. With a smaller limit to the range of the plastic phenotype, the evolution of adaptive plasticity was limited, meaning the evolution of non-plastic genes was necessary. The addition of developmental constraints to the model did not speed up genetic assimilation, suggesting new theory is needed to understand empirical observations. The modeling framework presented here could be extended to different ecological and evolutionary conditions, alternative reaction norm shapes, the evolution of additional reaction norm parameters such as the range or the location of the inflection point on the environmental axis, or other function-valued traits.


Figure 3. Results of six cases for different initial spatial invading species distribution, with six simulations each. Examples of the starting conditions are shown in Figures 1 and 2. All 200 invading (non-native) trees distributed as follows: (a) case 1 (0-5 m), (b) case 2 (0-10 m), (c) case 3 (0-15 m), Figure 3. Results of six cases for different initial spatial invading species distribution, with six simulations each. Examples of the starting conditions are shown in Figures 1 and 2. All 200 invading (non-native) trees distributed as follows: (a) case 1 (0-5 m), (b) case 2 (0-10 m), (c) case 3 (0-15 m), (d) case 4 (0-20 m), (e) case 5 (0-30 m), (f) case 6 (0-40 m) along the left edge and across the y-axis from 0 to 120.
Figure 4. Cont.
Figure 5. Cont.
Parameter values for reproduction, seedling dispersal, and litter suppression of seedlings.
Modeling the Effects of Spatial Distribution on Dynamics of an Invading Melaleuca quinquenervia (Cav.) Blake Population

July 2024

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17 Reads

Forests

To predict the potential success of an invading non-native species, it is important to understand its dynamics and interactions with native species in the early stages of its invasion. In spatially implicit models, mathematical stability criteria are commonly used to predict whether an invading population grows in number in an early time period. But spatial context is important for real invasions as an invading population may first occur as a small number of individuals scatter spatially. The invasion dynamics are therefore not describable in terms of population level state variables. A better approach is spatially explicit individual-based modeling (IBM). We use an established spatially explicit IBM to predict the invasion of the non-native tree, Melaleuca quinquenervia (Cav.) Blake, to a native community in southern Florida. We show that the initial spatial distribution, both the spatial density of individuals and the area they cover, affects its success in growing numerically and spreading. The formation of a cluster of a sufficient number and density of individuals may be needed for the invader to locally outcompete the native species and become established. Different initial densities, identical in number and density but differing in random positions of individuals, can produce very different trajectories of the invading population through time, even affecting invasion success and failure.


The evolution of passive dispersal versus habitat selection have differing emergent consequences in metacommunities

June 2024

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45 Reads

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2 Citations

Dispersal among local communities is fundamental to the metacommunity concept but is only important to the metacommunity structure if dispersal causes distortions of species abundances away from what local ecological conditions favour. We know from much previous work that dispersal can cause such abundance distortions. However, almost all previous theoretical studies have only considered one species alone or two interacting species (e.g. competitors or predator and prey). Moreover, a systematic analysis is needed of whether different dispersal strategies (e.g. passive dispersal versus demographic habitat selection) result in different abundance distortion patterns, how these distortion patterns change with local food web structure, and how the dispersal propensities of the interacting species might evolve in response to one another. In this article, we show using computer simulations and analytical models that abundance distortions occur in simple food webs with both passive dispersal and habitat selection, but habitat selection causes larger distortions. Additionally, patterns in the evolution of dispersal propensity in interacting species are very different for these two dispersal strategies. This study identifies that the dispersal strategies employed by interacting species critically shape how dispersal will influence metacommunity structure. This article is part of the theme issue ‘Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics’.


Figure 2. A schematic view of how intentional (left column) and incidental (right column) human hunting impacts the behavioral responses of different species. The intentional hunting of fish [22-24] and incidental hunting of cliff swallows [25-27] can ultimately impact future generations in similar yet contrasting ways.
Ecology of Fear: Acclimation and Adaptations to Hunting by Humans

January 2024

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302 Reads

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2 Citations

Sustainability

Humans greatly influence the ecosystems they live in and the lives of a wide range of taxa they share space with. Specifically, human hunting and harvesting has resulted in many species acclimating via diverse behavioral responses, often quite rapidly. This review provides insights into how hunting and harvesting can elicit behavioral changes. These responses emerge from a species’ previous and evolving ability to assess risk imposed by hunters and respond accordingly; a predator–prey game thus ensues, where both players may change tactics over time. If hunting is persistent, and does not result in the taxa’s extirpation, species are expected to develop adaptations to cope with hunting via natural selection by undergoing shifts in morphology and behavior. This review summarizes the various ways that human hunting intentionally and incidentally alters such evolutionary changes. These changes in turn can influence other species interactions and whole ecosystems. Additionally, alterations in behaviors can provide useful indicators for conservation and evolutionarily enlightened management strategies, and humans should use them to gain insights into our own socio-economic circumstances.


Neglected consequences of spatio-temporal heterogeneity and dispersal: Metapopulations, the inflationary effect, and real-world consequences for public health

November 2023

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37 Reads

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1 Citation

The metapopulation perspective is an important conceptual framework in ecology, biogeography, and evolutionary ecology. Metapopulations are spatially distributed populations linked by dispersal. Both metapopulation models and their community and ecosystem level analogues, metacommunity and meta-ecosystem models, tend to be more stable regionally than locally and display an enhancement in abundance because of the interplay of spatio-temporal heterogeneity and dispersal (an effect that has been called the "inflationary effect"). We highlight the essential role of spatio-temporal heterogeneity in metapopulation biology, sketch empirical demonstrations of the inflationary effect, and provide a mechanistic interpretation of how the inflationary effect arises and impacts population growth and abundance. The spread of infectious disease is used to illustrate how this effect, emerging from the interplay of spatiotemporal variability and dispersal, can have serious real-world consequences. Namely, failure to recognize the full possible effects of spatio-temporal heterogeneity likely enhanced the spread of COVID-19, and a comparable lack of understanding of emergent population processes at large scales may hamper the control and eradication of other infectious diseases. We finish by noting how the effects of spatio-temporal heterogeneity, including the inflationary effect, have implicitly played roles in many traditional themes in the history of ecology. The inflationary effect is implicit in processes explored in subdisciplines as far ranging as natural enemy-victim dynamics, species coexistence, and conservation biology. Seriously confronting the complexity of spatiotemporal heterogeneity has the potential to push many of these subdisciplines forward.


Conceptual depiction of the theoretical effect of dispersal rate on different diversity metrics in a mass‐effects metacommunity. Solid lines depict the effect of dispersal rate when the dispersal rate is temporally constant (Mouquet and Loreau 2002, 2002). Dashed lines depict the effect of dispersal rate when dispersal is temporally variable (Matias et al. 2013). The gray arrow shows the effect of increasing temporal variation in dispersal.
Ecological and evolutionary consequences of temporal variation in dispersal

August 2023

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143 Reads

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14 Citations

The importance of dispersal rates and distances has long been appreciated by ecologists and evolutionary biologists. An emerging field of research is revealing how temporal variation in dispersal can substantially influence ecological and evolutionary outcomes. We review how dispersal rates can temporally vary substantially in many ecosystems, a pattern that is particularly well‐documented for aquatic organisms but is likely pervasive in terrestrial ecosystems as well. We then synthesize the effects of temporal variation in dispersal on five key ecological and evolutionary processes: 1) metapopulation dynamics, 2) local adaptation, 3) range limits and range expansions, 4) species coexistence and 5) metacommunity dynamics. Our review demonstrates that temporal variation in dispersal is more than just statistical ‘noise' but can in fact lead to different outcomes than expected were dispersal temporally constant. For example, increasing the magnitude of temporal variation in dispersal can lead to lower metapopulation growth rates, permit greater local adaptation, facilitate and accelerate range expansion, increase regional coexistence, and alter local and regional species diversity. These effects of temporal variation in dispersal can inform conservation and natural resource management decisions such as prioritization in spatial planning, management of spillover from domesticated or captive populations into native populations, and the design of effective control strategies for invasive species.


Within hosts, a nonmonotonic R0 can arise from an interplay of resource impacts on among‐cell pathogen transmission and cell mortality. Within‐host pathogen persistence for the model given in Box 2, Equations 2.4 and 2.5. The solid line is the infected cell production rate when the pathogen is rare; the dotted line is the rate of loss of infected cells due to background cell death and a resource‐dependent immune response; the dashed line shows R0. Parameters are d = 1, β′ = 0.01, λ(R) = 1000/(1 + 5R), and aR) = 0.2e0.75R. The region between the vertical dotted lines represents the range of R where the criterion for pathogen persistence is met.
Within hosts, multiple equilibria and alternative states can occur across a continuous gradient of resources. (a) Isoclines of the model in Box 2 (Equations 2.4 and 2.5) with d = 1, m = 2, β' = 0.01, and λ=100+8I/1+0.01I$$ \lambda =\left(100+8I\right)/\left(1+0.01I\right) $$ produce multiple equilibria. Here, resources are implicit, in that host production of healthy cells (U) may require greater resource inputs to support higher cell division rates (see Box 2). The blue dot, a locally unstable equilibrium, indicates the location of simulations shown in panels (b) and (c) when the equations are solved, starting U at its equilibrium. The other equilibrium is locally stable. (b) When I is initially 29, just below its lower equilibrium (blue dot, panel a), the pathogen cannot persist (the no‐infection equilibrium). (c) When I is initially 30, just above its lower equilibrium, the pathogen persists within the host.
Among hosts, a nonmonotonic R0 can arise when resource supply increases pathogen transmission and host mortality. SI model (see Box 3) with constant total population (K = S + I) and abiotic resource (nutrients, N), so dI/dt=βS−dI=βK−I−dI$$ \mathrm{d}I/\mathrm{d}t=\left(\beta S-d\right)I=\left[\beta \left(K-I\right)-d\right]I $$, where β$$ \beta $$ is the transmission rate and d is the removal rate (mortality and, if applicable, recovery). When R0 is less than 1 (thin solid horizontal line), the pathogen cannot persist. (a) K = 1, β=max0,0.5R−1/1+0.5R−1$$ \beta =\max \left\{0,0.5\left(R-1\right)/\left[1+0.5\left(R-1\right)\right]\right\} $$ (solid curve) and d = 0.1 + 0.R (dotted line). Also shown is R0=βK/d$$ {R}_0=\beta K/d $$ (dashed line). If N is in the region where R0 > 1 (here, approximately 1.8 to 6.1), the pathogen can increase when rare, and I grows logistically to KR0−1/R0$$ K\left({R}_0-1\right)/{R}_0 $$, which is its stable equilibrium; otherwise, the pathogen cannot increase when rare and declines to 0. (b) Same as (a) except β=0.8/1+exp−0.8R−5$$ \beta =0.8/\left(1+\exp \left[-0.8\left(R-5\right)\right]\right) $$ and d=0.6/1+exp−2.2R−5$$ d=0.6/\left(1+\exp \left[-2.2\left(R-5\right)\right]\right) $$.
Alternative stable states can arise when transmission depends on resource quantity. In a model (see Box 4) with a biological resource (R), a host that consumes that resource (S) and can become infected by a pathogen (I), and predation (or other density‐independent mortality), an external shock can send the system into an alternative stable state. Here, we illustrate the system initiated at equilibrium with the pathogen present, where R = 6. At t = 0, an external shock reduces R to 2. Susceptible hosts increase and, concurrently, reduced transmission causes a decline in infected hosts. Infected and susceptible hosts cycle briefly, before infection is eliminated. Here, r = 1, K = 10, a = 0.2, b = 1, m = 0.1, α = 3, β = γR, γ = 0.35.
Feeding the fever: Complex host‐pathogen dynamics along continuous resource gradients

July 2023

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103 Reads

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2 Citations

Food has long been known to perform dual functions of nutrition and medicine, but mounting evidence suggests that complex host-pathogen dynamics can emerge along continuous resource gradients. Empirical examples of nonmonotonic responses of infection with increasing host resources (e.g., low prevalence at low and high resource supply but high prevalence at intermediate resources) have been documented across the tree of life, but these dynamics, when observed, often are interpreted as nonintuitive, idiosyncratic features of pathogen and host biology. Here, by developing generalized versions of existing models of resource dependence for within- and among-host infection dynamics, we provide a synthetic view of nonmonotonic infection dynamics. We demonstrate that where resources jointly impact two (or more) processes (e.g., growth, defense, transmission, mortality, predation), nonmonotonic infection dynamics, including alternative states, can emerge across a continuous resource supply gradient. We review the few empirical examples that concurrently measured resource effects on multiple rates and pair this with a wide range of examples in which resource dependence of multiple rates could generate nonmonotonic infection outcomes under realistic conditions. This review and generalized framework highlight the likely generality of such resource effects in natural systems and point to opportunities ripe for future empirical and theoretical work.



Citations (80)


... Compared with the other types of matrices considered in this study, urban matrices not only have a worse quality index but also have the smallest area of habitats available for species. Thus, the urban matrices in our landscape may have caused homogenisation of communities, possibly through changes in species migration and by reducing the colonisation-extinction dynamics between fragments (Fletcher et al., 2024). In addition, the more urbanized the matrix, the greater is the effect on specialist species due to fragmentation (Clavel et al., 2011;Ramirez-Delgado et al., 2022), which is in agreement with the results of the functional composition (tolerance matrix and body mass) observed in the present study. ...

Reference:

Environmental determinants of the taxonomic and functional alpha and beta diversity of small mammals in forest fragments in southwestern Amazonia, Brazil
The Prominent Role of the Matrix in Ecology, Evolution, and Conservation

Annual Review of Ecology Evolution and Systematics

... McPeek et al. [57] utilize computer simulations and analytical models to illustrate that dispersal strategies employed by interacting species profoundly impact the extent of mass effects in meta-food webs. Additionally, different dispersal rules have varied effects on the emergence of spatial patterns in population abundances. ...

The evolution of passive dispersal versus habitat selection have differing emergent consequences in metacommunities

... They also provide insights into the management of overabundant populations through hunting. In such instances, a better grasp of behavioural responses to management actions can help design strategies that take into account the ability of species to adjust their spatial distribution and diel rhythms to the threat posed by management measures (Williams et al., 2008;Potratz et al., 2024). A better understanding of the ramifications of consequences triggered in prey by the return of their predators will also help better address the challenges posed by high deer populations in parts of Europe and North America to human activities, such as farming, livestock husbandry, forestry (Kuijper et al., 2013(Kuijper et al., , 2016Raynor, 2017;Martin et al., 2020) or road safety (Gilbert et al., 2017;Raynor et al., 2021;Bell et al., 2024). ...

Ecology of Fear: Acclimation and Adaptations to Hunting by Humans

Sustainability

... Thus, assuming fixed growth under average conditions, increasing environmental variability lowers long-term population growth [11], and the same nonlinear averaging effects apply at the level of demographic rates (see [12] for a graphical application of this idea). This effect has been demonstrated empirically in the growth rate of experimental populations of green algae (Tetraselmis tetrahele) [13], in herbivore feeding rates [14] and in predator feeding rates [15] (although, in some cases, environmental variability can elevate average population growth, especially when the environment has some predictability [16] or populations are spatially distributed [17,18]). ...

Neglected consequences of spatio-temporal heterogeneity and dispersal: Metapopulations, the inflationary effect, and real-world consequences for public health

... Thus, the data obtained fit into a metapopulation model. At the population level, barriers to dispersal and regional selection play a crucial role in shaping the metapopulation configuration, thereby influencing evolutionary dynamics [80]. ...

Ecological and evolutionary consequences of temporal variation in dispersal

... Yet insects commonly experience multiple infections with two or more pathogen species, which effectively converts a host into an arena in which competing pathogens vie for possibly limiting resources (Zilio and Koella, 2020). Low-or poor-quality resources can increase pathogen competition, reduce successful host reproduction, and accelerate resource consumption (Borer et al., 2023). The presence of increased within-host resources can increase pathogen replication and/or limit the effects of pathogen competition (Zilio et al., 2023). ...

Feeding the fever: Complex host‐pathogen dynamics along continuous resource gradients

... Some hybrids produce seeds, but whether these seeds can germinate successfully remains untested, indicating a need for future studies. There is a possibility that over time, what are currently rare occurrences of singular triploids and hexaploids may breach the F2 barrier and undergo further evolutionary changes, possibly via the Leucanthemum partial clonality (Orive, Barfield, and Holt 2023). Whatever scenario will prevail is uncertain, but one certainty is that it will bring change. ...

Partial Clonality Expands the Opportunity for Spatial Adaptation

The American Naturalist

... Syntheses of studies on fragmentation per se in conservation have shown that having more but smaller patches is often equal-and sometimes better-for biodiversity than having fewer larger patches of the same total area, although there are cases where fewer larger patches are better (Fahrig 2017). Studies have also shown that responses to fragmentation per se are contextual, and researchers are trying to understand when species fare worse in landscapes with large numbers of small patches than a few larger patches of equal total area (Fahrig et al. 2022;Fletcher Jr et al. 2023a, 2023bRiva & Fahrig 2023; Gal an-Acedo & Fahrig 2024). ...

Landscape experiments unlock relationships among habitat loss, fragmentation, and patch‐size effects

... Given such pronounced effects on the demography and density of host populations, stage-structured interactions among hosts should strongly impact disease dynamics, and vice versa. Despite the potentially far-reaching consequences of stage structure on both food webs and epidemiological dynamics, these interactions have traditionally been overlooked in classical theory [14][15][16]). Epidemiological theory in particular has traditionally made a number of simplifying assumptions that omit important components of stage structure in host populations. ...

When growing pains and sick days collide: infectious disease can stabilize host population oscillations caused by stage structure

Theoretical Ecology

... While prior literature has highlighted the reduction in pathogenic fungi following fungicide application in these experimental plots (with consequent beneficial effects on host plants; Borer et al., 2015;Seabloom et al., 2017;Kohli et al., 2021), there has been less investigation into the consequences for foliar fungal communities as a whole. In other experimental systems, fungicide application was not found to reduce overall fungal diversity, richness, and colonization rate (Lane et al., 2023;Chen et al., 2020). In the absence of definitive evidence of the impact of our fungicidal treatment on the foliar community abundance and composition, in this work we consider this treatment as a temporary disruption of the foliar fungal community, with possible consequences for plant health and resource allocation. ...

Fungicide-Mediated Shifts in the Foliar Fungal Community of an Invasive Grass

Phytobiomes Journal