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• Tea Bag Index is originally designed to characterise microbial-driven decomposition. • Application of Tea Bag Index in termite-rich habitats greatly reduced sample size. • Using termite-exclusion barrier preserved full sample size in termite-rich habitats. • We also propose extending the Tea Bag Index to incorporate termite-driven mass loss. • Extended Tea Bag Index validated – contribute to pan-tropical decomposition data. The Tea Bag Index (TBI) is a standardised and cheap method to quantify microbial-driven decomposition by measuring the mass loss of tea within tea bags. Termites are known to damage the bags to access the content, rendering the method less suitable for termite-rich ecosystems. Extension of the TBI to accommodate and incorporate the influence of termites would broaden its applicability to include termite-rich ecosystems, such as tropical forests. We extended the original TBI by applying physical and chemical termite-exclusion methods. Tea mass loss and the proportion of tea bags detected by termites in the original TBI were also recorded to infer the role of termites in litter decomposition. TBI estimates derived from the original and extended TBI were compared, benchmarked against global estimates, and validated with time-series mass loss data. Using the original TBI, we found that termites damaged up to 80 % of tea bags and consumed the recalcitrant fraction of tea in several of them, leaving only 20 % of tea bags from which TBI estimates could be retrieved. The physical termite-exclusion treatment completely eliminated termite-infringement, thus preserving the full sample size for estimating TBI parameters. The chemical termite-exclusion treatment also successfully excluded termites, but potentially inhibited microbial decomposition and made TBI estimates unreliable. In the absence of termite-infringement, both the TBI estimates and time-series analysis revealed a low decomposition rate compared to other measurements in tropical and temperate regions. We propose an extended TBI, in which the physical termite-exclusion treatment is used to preserve the retrieval rate of TBI parameters and reliably measure microbial-driven decomposition, while the original TBI is used to incorporate the contribution of termites in driving litter mass loss. By characterising both termite- and microbial-driven decomposition, the extended TBI will provide a comprehensive understanding of decomposition and its drivers in termite-rich ecosystems, and permit global comparisons. [ABSTRACT FROM AUTHOR]

Insects as a group are suffering rapid declines in many parts of the world but are also poorly studied relative to vertebrate taxa. Comprehensive assessments of insect declines must account for both detected and undetected species. We studied extirpations among butterflies, a particularly well-known insect group, in the highly developed and biologically well-surveyed island city-state of Singapore. Building on existing butterfly species lists, we collated museum and naturalist records over the last two centuries and used statistical models to estimate the total extirpation rate since the first major collections in 1854. In addition, we compiled a set of traits for each butterfly species and explored how they relate to species discovery and extirpation. With a database of 413 native species, 132 (32%) of which are recorded as extirpated in Singapore, we used a statistical model to infer that, in addition, 104 unknown species (95% CI 60–162) were likely extirpated before they were ever discovered, suggesting a total extirpation rate of 46% (41–51%). In the trait analyses, we found that butterfly species that were discovered later were weakly associated with rarer larval host plants and smaller wingspans, while species that persisted for longer were weakly associated with higher larval host plant abundance and lower forest-dependence. This exercise is one of the first to offer a holistic estimate of extirpations for a group of insects by accounting for undetected extirpations. It suggests that extirpations among insects, specifically in the tropics, may be higher than naïve estimates based only on known records. [ABSTRACT FROM AUTHOR]

Populations of forest trees exhibit large temporal fluctuations, but little is known about the synchrony of these fluctuations across space, including their sign, magnitude, causes and characteristic scales. These have important implications for metapopulation persistence and theoretical community ecology. Using data from permanent forest plots spanning local, regional and global spatial scales, we measured spatial synchrony in tree population growth rates over sub-decadal and decadal timescales and explored the relationship of synchrony to geographical distance. Synchrony was high at local scales of less than 1 km, with estimated Pearson correlations of approximately 0.6-0.8 between species' population growth rates across pairs of quadrats. Synchrony decayed by approximately 17-44% with each order of magnitude increase in distance but was still detectably positive at distances of 100 km and beyond. Dispersal cannot explain observed large-scale synchrony because typical seed dispersal distances (<100 m) are far too short to couple the dynamics of distant forests on decadal timescales. We attribute the observed synchrony in forest dynamics primarily to the effect of spatially synchronous environmental drivers (the Moran effect), in particular climate, although pests, pathogens and anthropogenic drivers may play a role for some species.

Canopy gaps are widely recognized as being crucial for maintaining the diversity of forest tree communities. But empirical studies have found mixed results because the differences in diversity between individual gaps and non-gaps are often small and statistically undetectable. One overlooked factor, however, is how small individual gap versus non-gap differences may accumulate across sites and potentially have a large effect on forest diversity at the plot scale. Our study investigated sapling richness, density, and composition in 124 treefall gaps, and 200 non-gap sites in the 50-ha tropical forest plot at Barro Colorado Island (BCI), Panama. Additionally, we analyzed species accumulation curves to understand how species richness increases with increasing stem numbers. We observed that sapling richness and density were only slightly higher in gaps 7 years after formation and statistically indistinguishable from non-gaps after 12 years. However, species accumulation curves across multiple gaps were substantially higher than those across non-gaps. Species composition showed small differences between individual gaps and non-gaps but differed significantly between collections of gaps and non-gaps. Specifically, 55 species specialized in 7-year-old gaps compared with 24 in non-gaps; of these, 23 gap-specialized species and zero non-gap species were pioneers. Our results indicate that tree species richness is higher in gaps because of both higher stem density and the presence of gap-specialized species. Our study has finally provided compelling evidence to support the idea that gaps enhance the overall diversity of tropical forest tree communities., (© 2024 The Author(s). Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

Numerous studies have shown reduced performance in plants that are surrounded by neighbours of the same species 1,2 , a phenomenon known as conspecific negative density dependence (CNDD) 3 . A long-held ecological hypothesis posits that CNDD is more pronounced in tropical than in temperate forests 4,5 , which increases community stabilization, species coexistence and the diversity of local tree species 6,7 . Previous analyses supporting such a latitudinal gradient in CNDD 8,9 have suffered from methodological limitations related to the use of static data 10-12 . Here we present a comprehensive assessment of latitudinal CNDD patterns using dynamic mortality data to estimate species-site-specific CNDD across 23 sites. Averaged across species, we found that stabilizing CNDD was present at all except one site, but that average stabilizing CNDD was not stronger toward the tropics. However, in tropical tree communities, rare and intermediate abundant species experienced stronger stabilizing CNDD than did common species. This pattern was absent in temperate forests, which suggests that CNDD influences species abundances more strongly in tropical forests than it does in temperate ones 13 . We also found that interspecific variation in CNDD, which might attenuate its stabilizing effect on species diversity 14,15 , was high but not significantly different across latitudes. Although the consequences of these patterns for latitudinal diversity gradients are difficult to evaluate, we speculate that a more effective regulation of population abundances could translate into greater stabilization of tropical tree communities and thus contribute to the high local diversity of tropical forests., (© 2024. The Author(s).)

There is an urgent need for reliable data on the impacts of deforestation on tropical biodiversity. The city-state of Singapore has one of the most detailed biodiversity records in the tropics, dating back to the turn of the 19th century. In 1819, Singapore was almost entirely covered in primary forest, but this has since been largely cleared. We compiled more than 200 y of records for 10 major taxonomic groups in Singapore (>50,000 individual records; >3,000 species), and we estimated extinction rates using recently developed and novel statistical models that account for "dark extinctions," i.e., extinctions of undiscovered species. The estimated overall extinction rate was 37% (95% CI [31 to 42%]). Extrapolating our Singapore observations to a future business-as-usual deforestation scenario for Southeast Asia suggests that 18% (95% CI [16 to 22%]) of species will be lost regionally by 2100. Our extinction estimates for Singapore and Southeast Asia are a factor of two lower than previous estimates that also attempted to account for dark extinctions. However, we caution that particular groups such as large mammals, forest-dependent birds, orchids, and butterflies are disproportionately vulnerable., Competing Interests: Competing interests statement:The authors declare no competing interest.

Deleterious germ line variants in DDX41 are a common cause of genetic predisposition to hematologic malignancies, particularly myelodysplastic neoplasms (MDS) and acute myeloid leukemia (AML). Targeted next-generation sequencing was performed in a large cohort of sequentially recruited patients with myeloid malignancy, covering DDX41 as well as 30 other genes frequently mutated in myeloid malignancy. Whole genome transcriptome sequencing data was analyzed on a separate cohort of patients with a range of hematologic malignancies to investigate the spectrum of cancer predisposition. Altogether, 5737 patients with myeloid malignancies were studied, with 152 different DDX41 variants detected. Multiple novel variants were detected, including synonymous variants affecting splicing as demonstrated by RNA-sequencing. The presence of a somatic DDX41 variant was highly associated with DDX41 germ line variants in patients with MDS and AML, and we developed a statistical approach to incorporate the co-occurrence of a somatic DDX41 variant into germ line variant classification at a very strong level (as per the American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines). Using this approach, the MDS cohort contained 108 of 2865 (3.8%) patients with germ line likely pathogenic/pathogenic (LP/P) variants, and the AML cohort 106 of 2157 (4.9%). DDX41 LP/P variants were markedly enriched in patients with AML and MDS compared with those in patients with myeloproliferative neoplasms, B-cell neoplasm, and T- or B-cell acute lymphoblastic leukemia. In summary, we have developed a framework to enhance DDX41 variant curation as well as highlighted the importance of assessment of all types of genomic variants (including synonymous and multiexon deletions) to fully detect the landscape of possible clinically relevant DDX41 variants., (© 2023 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Many infectious diseases exist as multiple variants, with interactions between variants potentially driving epidemiological dynamics. These diseases include dengue, which infects hundreds of millions of people every year and exhibits complex multi-serotype dynamics. Antibodies produced in response to primary infection by one of the four dengue serotypes can produce a period of temporary cross-immunity (TCI) to infection by other serotypes. After this period, the remaining antibodies can facilitate the entry of heterologous serotypes into target cells, thus enhancing severity of secondary infection by a heterologous serotype. This represents antibody-dependent enhancement (ADE). In this study, we analyze an epidemiological model to provide novel insights into the importance of TCI and ADE in producing cyclic outbreaks of dengue serotypes. Our analyses reveal that without TCI, such cyclic outbreaks are synchronous across serotypes and only occur when ADE produces high transmission rates. In contrast, the presence of TCI allows asynchronous cycles of serotypes by inducing a time lag between recovery from primary infection by one serotype and secondary infection by another, with such cycles able to occur without ADE. Our results suggest that TCI is a fundamental driver of asynchronous cycles of dengue serotypes and possibly other multi-variant diseases., (© 2023. The Author(s), under exclusive licence to Society for Mathematical Biology.)

A central goal in ecology is to understand what maintains species diversity in local communities. Classic ecological theory 1,2 posits that niches dictate the maximum number of species that can coexist in a community and that the richness of observed species will be below this maximum only where immigration is very low. A new alternative theory 3,4 is that niches, instead, dictate the minimum number of coexisting species and that the richness of observed species will usually be well above this because of ongoing immigration. We conducted an experimental test to discriminate between these two unified theories using a manipulative field experiment with tropical intertidal communities. We found, consistent with the new theory, that the relationship of species richness to immigration rate stabilized at a low value at low immigration rates and did not saturate at high immigration rates. Our results suggest that tropical intertidal communities have low niche diversity and are typically in a dispersal-assembled regime where immigration is high enough to overfill the niches. Observational data from other studies 3,5 suggest that these conclusions may generalize to other ecological systems. Our new experimental approach can be adapted for other systems and be used as a 'niche detector' and a tool for assessing when communities are niche versus dispersal assembled., (© 2023. The Author(s).)

In a critique of our recent review on measuring habitat complexity in ecology, Madin et al. (2023) advocate the use of fractal dimension in ecology and defend their geometric constraint theory of habitat complexity. We explain the flaws in their arguments and highlight points where they misinterpreted our statements., (© 2023 The Authors. Ecology Letters published by John Wiley & Sons Ltd.)

The question of whether biodiversity conservation and carbon conservation can be synergistic hinges on the form of the biodiversity-productivity relationship (BPR), a fundamental ecological pattern. The stakes are particularly high when it comes to forests, which at a global level comprises a large fraction of both biodiversity and carbon. And yet, in forests, the BPR is relatively poorly understood. In this review, we critically evaluate research on forest BPRs, focussing on the experimental and observational studies of the last 2 decades. We find general support for a positive forest BPR, suggesting that biodiversity and carbon conservation are synergistic to a degree. However, we identify several major caveats: (i) although, on average, productivity may increase with biodiversity, the highest-yielding forests are often monocultures of very productive species; (ii) productivity typically saturates at fewer than ten species; (iii) positive BPRs can be driven by some third variable, in particular stem density, instead of a causal arrow from biodiversity to productivity; (iv) the BPR's sign and magnitude varies across spatial grains and extents, and it may be weak at scales relevant to conservation; and (v) most productivity estimates in forests are associated with large errors. We conclude by explaining the importance of these caveats for both conservation programmes focussed on protection of existing forests and conservation programmes focussed on restoring or replanting forests., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Ecology lacks a holistic approach that can model phenomena across temporal and spatial scales, largely because of the challenges in modelling systems with a large number of interacting constituents. This hampers our understanding of complex ecosystems and the impact that human interventions (e.g., deforestation, wildlife harvesting and climate change) have on them. Here we use density functional theory, a computational method for many-body problems in physics, to develop a computational framework for ecosystem modelling. Our methods accurately fit experimental and synthetic data of interacting multi-species communities across spatial scales and can project to unseen data. As the key concept we establish and validate a cost function that encodes the trade-offs between the various ecosystem components. We show how this single general modelling framework delivers predictions on par with established, but specialised, approaches for systems from predatory microbes to territorial flies to tropical tree communities. Our density functional framework thus provides a promising avenue for advancing our understanding of ecological systems., (© 2023. The Author(s).)

Neutral models in ecology assume that all species are demographically equivalent, such that their abundances differ ultimately because of demographic stochasticity rather than selection. In spite of their simplicity, neutral models have been found to accurately reproduce static patterns of biodiversity for diverse communities. However, the same neutral models have been found to exhibit species abundance dynamics that are far too slow compared to reality, resulting in poor fits to temporally dynamic patterns of biodiversity. Here, we show that one of the root causes of these slow dynamics is the additional assumption that a community has reached an equilibrium with a fixed community size, with species that have a net growth rate close to zero. We removed this additional assumption by constructing and analyzing a neutral model with an expected community size that can change over time and is not necessarily at equilibrium, which thus allows the historical formation of a community to be represented explicitly. Our analysis demonstrated that for the general scenario where a small community rapidly grows in size to a carrying capacity, representing recovery from ecological disturbance or assembly of a new community, the model produced much larger changes in species abundances and much shorter species ages than a neutral model at an equilibrium with fixed community size. In addition, the species abundance distribution was biphasic with a subset of abundant species arising from a founder effect. We confirmed these new results in applications of the new model to the specific scenario of recovery of the Amazon tree community after the end-Cretaceous bolide impact, which involved periods of increasing and decreasing community size. We conclude that incorporating transient dynamics in neutral models improves realism by allowing explicit consideration of how a community is formed over realistic time-scales., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Human cooperation (paying a cost to benefit others) is puzzling from a Darwinian perspective, particularly in groups with strangers who cannot repay nor are family members. The beneficial effects of cooperation typically increase nonlinearly with the number of cooperators, e.g., increasing returns when cooperation is low and diminishing returns when cooperation is high. Such nonlinearity can allow cooperation between strangers to persist evolutionarily if a large enough proportion of the population are already cooperators. However, if a lone cooperator faces a conflict between the group's and its own interests (a social dilemma), that raises the question of how cooperation arose in the first place. We use a mathematically tractable evolutionary model to formalise a chronological narrative that has previously only been investigated verbally: given that ancient humans interacted mostly with family members (genetic homophily), cooperation evolved first by kin selection, and then persisted in situations with nonlinear benefits as homophily declined or even if interactions with strangers became the norm. The model also predicts the coexistence of cooperators and defectors observed in the human population (polymorphism), and may explain why cooperators in behavioural experiments prefer to condition their contribution on the contributions of others (conditional cooperation in public goods games)., (© 2022. The Author(s).)

Habitat complexity has been considered a key driver of biodiversity and other ecological phenomena for nearly a century. However, there is still no consensus over the definition of complexity or how to measure it. Up-to-date and clear guidance on measuring complexity is urgently needed, particularly given the rise of remote sensing and advent of technologies that allow environments to be scanned at unprecedented spatial extents and resolutions. Here we review how complexity is measured in ecology. We provide a framework for metrics of habitat complexity, and for the related concept of spatial heterogeneity. We focus on the two most commonly used complexity metrics in ecology: fractal dimension and rugosity. We discuss the pros and cons of these metrics using practical examples from our own empirical data and from simulations. Fractal dimension is particularly widely used, and we provide a critical examination of it drawing on research from other scientific fields. We also discuss informational metrics of complexity and their potential benefits. We chart a path forward for research on measuring habitat complexity by presenting, as a guide, sets of essential and desirable criteria that a metric of complexity should possess. Lastly, we discuss the applied significance of our review., (© 2022 The Authors. Ecology Letters published by John Wiley & Sons Ltd.)

Estimating the total number of species on Earth has been a longstanding pursuit. Models project anywhere between 2 and 10 million species, and discovery of new species continues to the present day. Despite this, we hypothesized that our current knowledge of phylogenetic diversity (PD) may be almost complete because new discoveries may be less phylogenetically distinct than past discoveries. Focusing on birds, which are well studied, we generated a robust phylogenetic tree for most extant species by combining existing published trees and calculated each discovery's marginal contribution to known PD since the first formal species descriptions in 1758. We found that PD contributions began to plateau in the early 1900s, about half a century earlier than species richness. Relative contributions of each phylogenetic order to known PD shifted over the first 150 years, with a growing contribution of the hyper-diverse perching birds (Passeriformes) in particular, but after the early 1900s this has remained relatively stable. Altogether, this suggests that our knowledge of the evolutionary history of extant birds is mostly complete, with few discoveries of high evolutionary novelty left to be made, and that conclusions of studies using avian phylogenies are likely to be robust to future species discoveries.

Half a century ago, Janzen and Connell hypothesized that the high tree species diversity in tropical forests is maintained by specialized natural enemies. Along with other mechanisms, these can cause conspecific negative density dependence (CNDD) and thus maintain species diversity. Numerous studies have measured proxies of CNDD worldwide, but doubt about its relative importance remains. We find ample evidence for CNDD in local populations, but methodological limitations make it difficult to assess if CNDD scales up to control community diversity and thereby local and global biodiversity patterns. A combination of more robust statistical methods, new study designs, and eco-evolutionary models are needed to provide a more definite evaluation of the importance of CNDD for geographic variation in plant species diversity., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

AbstractA goal of ecology is to identify the stabilizing mechanisms that maintain species diversity in the face of competitive exclusion and drift. For tropical forest tree communities, it has been hypothesized that high diversity is maintained via Janzen-Connell effects, whereby host-specific natural enemies prevent any one species from becoming too abundant. Here we explore the plausibility of this hypothesis with theoretical models. We confirm a previous result that when added to a model with drift but no competitive exclusion-that is, a neutral model where intrinsic fitnesses are perfectly equalized across species-Janzen-Connell effects maintain very high species richness that scales strongly with community size. However, when competitive exclusion is introduced-that is, when intrinsic fitnesses vary across species-the number of species maintained by Janzen-Connell effects is substantially reduced and scales much less strongly with community size. Because fitness variation is pervasive in nature, we conclude that the potential of Janzen-Connell effects to maintain diversity is probably weak and that the mechanism does not yet provide a sufficient explanation for the observed high diversity of tropical forest tree communities. We also show that, surprisingly, dispersal limitation can further reduce the ability of Janzen-Connell effects to maintain diversity.

How many species have gone extinct in modern times before being described by science? To answer this question, and thereby get a full assessment of humanity's impact on biodiversity, statistical methods that quantify undetected extinctions are required. Such methods have been developed recently, but they are limited by their reliance on parametric assumptions; specifically, they assume the pools of extant and undetected species decay exponentially, whereas real detection rates vary temporally with survey effort and real extinction rates vary with the waxing and waning of threatening processes. We devised a new, nonparametric method for estimating undetected extinctions. As inputs, the method requires only the first and last date at which each species in an ensemble was recorded. As outputs, the method provides estimates of the proportion of species that have gone extinct, detected, or undetected and, in the special case where the number of undetected extant species in the present day is assumed close to zero, of the absolute number of undetected extinct species. The main assumption of the method is that the per-species extinction rate is independent of whether a species has been detected or not. We applied the method to the resident native bird fauna of Singapore. Of 195 recorded species, 58 (29.7%) have gone extinct in the last 200 years. Our method projected that an additional 9.6 species (95% CI 3.4, 19.8) have gone extinct without first being recorded, implying a true extinction rate of 33.0% (95% CI 31.0%, 36.2%). We provide R code for implementing our method. Because our method does not depend on strong assumptions, we expect it to be broadly useful for quantifying undetected extinctions., (© 2016 Society for Conservation Biology.)

Ecological communities are subjected to stochasticity in the form of demographic and environmental variance. Stochastic models that contain only demographic variance (neutral models) provide close quantitative fits to observed species-abundance distributions (SADs) but substantially underestimate observed temporal species-abundance fluctuations. To provide a holistic assessment of whether models with demographic and environmental variance perform better than neutral models, the fit of both to SADs and temporal species-abundance fluctuations at the same time has to be tested quantitatively. In this study, we quantitatively test how closely a model with demographic and environmental variance reproduces total numbers of species, total abundances, SADs and temporal species-abundance fluctuations for two tropical forest tree communities, using decadal data from long-term monitoring plots and considering individuals larger than two size thresholds for each community. We find that the model can indeed closely reproduce these static and dynamic patterns of biodiversity in the two communities for the two size thresholds, with better overall fits than corresponding neutral models. Therefore, our results provide evidence that stochastic models incorporating demographic and environmental variance can simultaneously capture important static and dynamic biodiversity patterns arising in tropical forest communities.

MacArthur and Wilson's theory of island biogeography predicts that island species richness should increase with island area. This prediction generally holds among large islands, but among small islands species richness often varies independently of island area, producing the so-called 'small-island effect' and an overall biphasic species-area relationship (SAR). Here, we develop a unified theory that explains the biphasic island SAR. Our theory's key postulate is that as island area increases, the total number of immigrants increases faster than niche diversity. A parsimonious mechanistic model approximating these processes reproduces a biphasic SAR and provides excellent fits to 100 archipelago datasets. In the light of our theory, the biphasic island SAR can be interpreted as arising from a transition from a niche-structured regime on small islands to a colonization-extinction balance regime on large islands. The first regime is characteristic of classic deterministic niche theories; the second regime is characteristic of stochastic theories including the theory of island biogeography and neutral theory. The data furthermore confirm our theory's key prediction that the transition between the two SAR regimes should occur at smaller areas, where immigration is stronger (i.e. for taxa that are better dispersers and for archipelagos that are less isolated)., (© 2016 The Author(s).)

Termites are eusocial insects that evolved from solitary cockroaches. It is not known precisely what factors drove the evolution of termite eusociality, that is, skewed reproduction with distinct winged reproductive and wingless worker phenotypes. In other eusocial insects (bees and wasps), reproductive skew evolved first and phenotype differences evolved second. We propose that the reverse pattern occurred in termites, that is, that the winged-wingless diphenism evolved before eusociality. We discuss existing phylogenetic and pheromonal evidence supporting our hypothesis. We provide new experimental evidence from the most basal termite species (Mastotermes darwiniensis), suggesting that the ancestral state was indeed diphenic but presocial. We propose that the mechanism promoting a winged-wingless diphenism-in the absence of eusociality-was greater predation of aerial than terrestrial dispersers, and we support this with a game theoretic model. We augment our hypothesis with a novel explanation for the evolution of the developmental pathways leading to winged and wingless phenotypes in termites. An added benefit of our hypothesis is that it neatly explains the origin of termite eusociality itself: in the pre-eusocial ancestral species, the poor dispersal ability of the wingless phenotype would have led to clustering of relatives around shared resources-a prerequisite for nonparental care of close relatives.

Many problems in ecology require the estimation of rates of dispersal of individuals or propagules across physical boundaries. Such problems arise in invasion ecology, forest dynamics, and the neutral theory of biodiversity. In a forest plot, for example, one might ask what proportion of the seed rain originates from outside the plot. A recent study presented analytical approximations that relate the rate of immigration across a boundary to plot geometry and to the parameters of a dispersal kernel in one- and two-dimensional environments. In this study, we provide a more rigorous derivation of these expressions and we derive a more general expression that applies in environments of arbitrary dimension. We discuss potential applications of the one-, two-, and three-dimensional results to ecological problems.

Info-gap decision theory facilitates decision making for problems in which uncertainty is large and probability distributions of uncertain variables are unknown. The info-gap framework allows the decision maker to maximize robustness to failure in the presence of uncertainty, where uncertainty is in the parameters of the model and failure is defined as the model output falling below some minimally acceptable performance threshold. Info-gap theory has found particular application to problems in conservation biology and ecological economics. In this study, we applied info-gap theory to an ecosystem services tradeoff case study in which a decision maker aiming to maximize ecosystem service investment returns must choose between two alternative land uses: native vegetation conservation or the establishment of an exotic timber plantation. The uncertain variables are the carbon price and the water price. With a "no-information" uncertainty model that assumes equal relative uncertainty across both variables, info-gap theory identifies a minimally acceptable reward threshold above which conservation is preferred, but below which plantation establishment is preferred. However, with an uncertainty model that allows the carbon price to be substantially more uncertain than the water price, conservation of native vegetation becomes an economically more robust investment option than establishing alien pine plantations. We explored the sensitivity of the results to the use of alternative uncertainty models, including asymmetric uncertainty in individual variables. We emphasize the general finding that the results of info-gap analyses can be sensitive to the choice of uncertainty model and that, therefore, future applications to ecological problems should be careful to incorporate all available qualitative and quantitative information relating to uncertainties or should at least justify the no-information uncertainty model.

A fundamental challenge in ecology is to understand the mechanisms that govern patterns of relative species abundance. Previous numerical simulations have suggested that complex niche-structured models produce species abundance distributions (SADs) that are qualitatively similar to those of very simple neutral models that ignore differences between species. However, in the absence of an analytical treatment of niche models, one cannot tell whether the two classes of model produce the same patterns via similar or different mechanisms. We present an analytical proof that, in the limit as diversity becomes large, a strong niche model give rises to exactly the same asymptotic form of SAD as the neutral model, and we verify the analytical predictions for a Panamanian tropical forest data set. Our results strongly suggest that neutral processes drive patterns of relative species abundance in high-diversity ecological communities, even when strong niche structure exists. However, neutral theory cannot explain what generates high diversity in the first place, and it may not be valid in low-diversity communities. Our results also confirm that neutral theory cannot be used to infer an absence of niche structure or to explain ecosystem function.

The importance of incorporating landscape dynamics into population viability analysis (PVA) has previously been acknowledged, but the need to repeat the landscape generation process to encapsulate landscape stochasticity in model outputs has largely been overlooked. Reasons for this are that (1) there is presently no means for quantifying the relative effects of landscape stochasticity and population stochasticity on model outputs, and therefore no means for determining how to allocate simulation time optimally between the two; and (2) the process of generating multiple landscapes to incorporate landscape stochasticity is tedious and user-intensive with current PVA software. Here we demonstrate that landscape stochasticity can be an important source of variance in model outputs. We solve the technical problems with incorporating landscape stochasticity by deriving a formula that gives the optimal ratio of population simulations to landscape simulations for a given model, and by providing a computer program that incorporates the formula and automates multiple landscape generation in a dynamic landscape metapopulation (DLMP) model. Using a case study of a bird population, we produce estimates of DLMP model output parameters that are up to four times more precise than those estimated from a single landscape in the same amount of total simulation time. We use the DLMP modeling software RAMAS Landscape to run the landscape and metapopulation models, though our method is general and could be applied to any PVA platform. The results of this study should motivate DLMP modelers to consider landscape stochasticity in their analyses.