ABSTRACT
Biological insurance theory predicts that, in a variable environment, aggregate ecosystem properties will vary less in more diverse communities because declines in the performance or ...abundance of some species or phenotypes will be offset, at least partly, by smoother declines or increases in others. During the past two decades, ecology has accumulated strong evidence for the stabilising effect of biodiversity on ecosystem functioning. As biological insurance is reaching the stage of a mature theory, it is critical to revisit and clarify its conceptual foundations to guide future developments, applications and measurements. In this review, we first clarify the connections between the insurance and portfolio concepts that have been used in ecology and the economic concepts that inspired them. Doing so points to gaps and mismatches between ecology and economics that could be filled profitably by new theoretical developments and new management applications. Second, we discuss some fundamental issues in biological insurance theory that have remained unnoticed so far and that emerge from some of its recent applications. In particular, we draw a clear distinction between the two effects embedded in biological insurance theory, i.e. the effects of biodiversity on the mean and variability of ecosystem properties. This distinction allows explicit consideration of trade‐offs between the mean and stability of ecosystem processes and services. We also review applications of biological insurance theory in ecosystem management. Finally, we provide a synthetic conceptual framework that unifies the various approaches across disciplines, and we suggest new ways in which biological insurance theory could be extended to address new issues in ecology and ecosystem management. Exciting future challenges include linking the effects of biodiversity on ecosystem functioning and stability, incorporating multiple functions and feedbacks, developing new approaches to partition biodiversity effects across scales, extending biological insurance theory to complex interaction networks, and developing new applications to biodiversity and ecosystem management.
When and where to protect forests Luby, Ian H.; Miller, Steve J.; Polasky, Stephen
Nature (London),
09/2022, Volume:
609, Issue:
7925
Journal Article
Peer reviewed
Ongoing deforestation poses a major threat to biodiversity1,2. With limited resources and imminent threats, deciding when as well as where to conserve is a fundamental question. Here we use a dynamic ...optimization approach to identify an optimal sequence for the conservation of plant species in 458 forested ecoregions globally over the next 50 years. The optimization approach includes species richness in each forested ecoregion, complementarity of species across ecoregions, costs of conservation that rise with cumulative protection in an ecoregion, the existing degree of protection, the rate of deforestation and the potential for reforestation in each ecoregion. The optimal conservation strategy for this formulation initially targets a small number of ecoregions where further deforestation leads to large reductions in species and where the costs of conservation are low. In later years, conservation efforts spread to more ecoregions, and invest in both expanded protection of primary forest and reforestation. The largest gains in species conservation come in Melanesia, South and Southeast Asia, the Anatolian peninsula, northern South America and Central America. The results highlight the potentially large gains in conservation that can be made with carefully targeted investments.
Abstract
Successful agricultural adaptation to extreme heat has the potential to avert large crop losses and improve food security. Because adaptation is costly, accurate weather forecasts have the ...potential to improve targeting of adaptation efforts. To understand the role of short-term (1–7 day) forecasts in reducing heat-related yield loss, we analyze a novel dataset combining corn yields, short-term weather forecasts, and weather realizations in the United States from 2008 to 2021. We find no evidence that forecasts facilitate avoidance of heat-related yield losses on average, and only limited benefits when we allow for forecast benefits to vary with irrigation prevalence. While our results paint a pessimistic picture of in-season adaptation to heat, forecasts may be more valuable for other crops and regions, especially given continuing investment in adaptation technologies.
Territorial use rights in fisheries (TURFs) are coastal territories assigned to fishermen for the exclusive extraction of marine resources. Recent evidence shows that the incentives that arise from ...these systems can improve fisheries sustainability. Although research on TURFs has increased in recent years, important questions regarding the social and ecological dynamics underlying their success remain largely unanswered. In particular, in order to create new successful TURFs, it is critical to comprehend how fish movement over different distances affects the development of sustainable fishing practices within a TURF. In theory, excessive spillover outside a TURF will generate incentives to overharvest. However, many TURFs have proven successful even when targeted species move over distances far greater than the TURF’s size. A common attribute among some of these successful systems is the presence of inter-TURF cooperation arrangements. This raises the question of how different levels and types of cooperation affect the motivations for overharvesting driven by the movement of fish outside the TURF. In this paper, we examine equilibrium yields under different levels of inter-TURF cooperation (from partial to full) and varying degrees of asymmetry across TURFs of both biological capacity and benefit-sharing. We find that partial cooperation can improve yields even with an unequal distribution of shared benefits and asymmetric carrying capacity. However, cooperation arrangements are unstable if the sharing agreement and biological asymmetries are misaligned. Remarkably, we find that asymmetry in the system can lead to the creation of voluntary no-take zones.
Temperature variability and extremes can have profound impacts on populations and ecological communities. Predicting impacts of thermal variability poses a challenge, because it has both direct ...physiological effects and indirect effects through species interactions. In addition, differences in thermal performance between predators and prey and nonlinear averaging of temperature-dependent performance can result in complex and counterintuitive population dynamics in response to climate change. Yet the combined consequences of these effects remain underexplored. Here, modelling temperature-dependent predator-prey dynamics, we study how changes in temperature variability affect population size, collapse and stable coexistence of both predator and prey, relative to under constant environments or warming alone. We find that the effects of temperature variation on interacting species can lead to a diversity of outcomes, from predator collapse to stable coexistence, depending on interaction strengths and differences in species' thermal performance. Temperature variability also alters predictions about population collapse-in some cases allowing predators to persist for longer than predicted when considering warming alone, and in others accelerating collapse. To inform management responses that are robust to future climates with increasing temperature variability and extremes, we need to incorporate the consequences of temperature variation in complex ecosystems. This article is part of the theme issue 'Integrative research perspectives on marine conservation'.
Abstract
Background
Older age is a risk factor for tuberculosis (TB) in low incidence settings. Using data from the US National TB Surveillance System and American Community Survey, we estimated ...trends and racial/ethnic differences in TB incidence among US-born cohorts aged ≥50 years.
Methods
In total, 42 000 TB cases among US-born persons ≥50 years were reported during 2001–2019. We used generalized additive regression models to decompose the effects of birth cohort and age on TB incidence rates, stratified by sex and race/ethnicity. Using genotype-based estimates of recent transmission (available 2011–2019), we implemented additional models to decompose incidence trends by estimated recent versus remote infection.
Results
Estimated incidence rates declined with age, for the overall cohort and most sex and race/ethnicity strata. Average annual percentage declines flattened for older individuals, from 8.80% (95% confidence interval CI 8.34–9.23) in 51-year-olds to 4.51% (95% CI 3.87–5.14) in 90-year-olds. Controlling for age, incidence rates were lower for more recent birth cohorts, dropping 8.79% (95% CI 6.13–11.26) on average between successive cohort years. Incidence rates were substantially higher for racial/ethnic minorities, and these inequalities persisted across all birth cohorts. Rates from recent infection declined at approximately 10% per year as individuals aged. Rates from remote infection declined more slowly with age, and this annual percentage decline approached zero for the oldest individuals.
Conclusions
TB rates were highest for racial/ethnic minorities and for the earliest birth cohorts and declined with age. For the oldest individuals, annual percentage declines were low, and most cases were attributed to remote infection.
Among US-born individuals aged 50 and over, estimated tuberculosis incidence rates are highest for racial/ethnic minorities and for the earliest birth cohorts. Within birth cohorts, incidence rates decline with age for almost all groups.
Wildlife conservation strategies focused on one season or population segment may fail to adequately protect populations, especially when a species' habitat preferences vary among seasons, ...age-classes, geographic regions, or other factors. Conservation of golden eagles (Aquila chrysaetos) is an example of such a complex scenario, in which the distribution, habitat use, and migratory strategies of this species of conservation concern vary by age-class, reproductive status, region, and season. Nonetheless, research aimed at mapping priority use areas to inform management of golden eagles in western North America has typically focused on territory-holding adults during the breeding period, largely to the exclusion of other seasons and life-history groups. To support population-wide conservation planning across the full annual cycle for golden eagles, we developed a distribution model for individuals in a season not typically evaluated-winter-and in an area of the interior western U.S. that is a high priority for conservation of the species. We used a large GPS-telemetry dataset and library of environmental variables to develop a machine-learning model to predict spatial variation in the relative intensity of use by golden eagles during winter in Wyoming, USA, and surrounding ecoregions. Based on a rigorous series of evaluations including cross-validation, withheld and independent data, our winter-season model accurately predicted spatial variation in intensity of use by multiple age- and life-history groups of eagles not associated with nesting territories (i.e., all age classes of long-distance migrants, and resident non-adults and adult "floaters", and movements of adult territory holders and their offspring outside their breeding territories). Important predictors in the model were wind and uplift (40.2% contribution), vegetation and landcover (27.9%), topography (14%), climate and weather (9.4%), and ecoregion (8.7%). Predicted areas of high-use winter habitat had relatively low spatial overlap with nesting habitat, suggesting a conservation strategy targeting high-use areas for one season would capture as much as half and as little as one quarter of high-use areas for the other season. The majority of predicted high-use habitat (top 10% quantile) occurred on private lands (55%); lands managed by states and the Bureau of Land Management (BLM) had a lower amount (33%), but higher concentration of high-use habitat than expected for their area (1.5-1.6x). These results will enable those involved in conservation and management of golden eagles in our study region to incorporate spatial prioritization of wintering habitat into their existing regulatory processes, land-use planning tasks, and conservation actions.
Functional trait analysis is an appealing approach to study differences among biological communities because traits determine species' responses to the environment and their impacts on ecosystem ...functioning. Despite a rapidly expanding quantitative literature, it remains challenging to conceptualize concurrent changes in multiple trait dimensions (“trait space”) and select quantitative functional diversity methods to test hypotheses prior to analysis. To address this need, we present a widely applicable framework for visualizing ecological phenomena in trait space to guide the selection, application, and interpretation of quantitative functional diversity methods. We describe five hypotheses that represent general patterns of responses to disturbance in functional community ecology and then apply a formal decision process to determine appropriate quantitative methods to test ecological hypotheses. As a part of this process, we devise a new statistical approach to test for functional turnover among communities. Our combination of hypotheses and metrics can be applied broadly to address ecological questions across a range of systems and study designs. We illustrate the framework with a case study of disturbance in freshwater communities. This hypothesis‐driven approach will increase the rigor and transparency of applied functional trait studies.
Birds are often obligate to specific habitats which can result in study areas with complex boundaries due to sudden changes in vegetation or other features. This can result in study areas with ...concave arcs or that include holes of unsuitable habitat such as lakes or agricultural fields. Spatial models used to produce species' distribution and density estimates need to respect such boundaries to make informed decisions for species conservation and management. The soap film smoother is one model for complex study regions which controls the boundary behaviour, ensuring realistic values at the edges of the region. We apply the soap film smoother to account for boundary effects and compare it with thin plate regression spline (TPRS) smooth and design-based conventional distance sampling methods to produce abundance estimates from point-transect distance sampling collected data on Hawai'i 'Ākepa
in the Hakalau Forest Unit of the Big Island National Wildlife Refuge Complex, Hawai'i Island, USA. The soap film smoother predicted zero or near zero densities in the northern part of the domain and two hotspots (in the southern and central parts of the domain). Along the boundary the soap film model predicted relatively high densities where 'Ākepa occur in the adjacent forest and near zero elsewhere. The design-based and soap film abundance estimates were nearly identical. The width of the soap film confidence interval was 16.5% and 0.8% wider than the width of the TPRS smooth and design-based confidence intervals, respectively. The peaks in predicted densities along the boundary indicates leakage by the TPRS smooth. We provide a discussion of the statistical methods, biological findings and management implications of applying soap film smoothers to estimate forest bird population status.
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