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.
Given the rise of remote‐sensing, up‐to‐date and clear guidance on measuring complexity is urgently needed. 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 demonstrate the pros and cons of various complexity metrics particularly focusing on popular ones; we provide a modern critical examination of fractal dimension and show how and why it is untenable despite its appeal. We discuss informational metrics of complexity, and their potential benefits and chart a path forward for research on measuring complexity in ecology.
Carbon sequestration by afforestation can help mitigate global climate change but may have adverse environmental and economic impacts in some regions. For example, economic incentives for carbon ...sequestration may encourage the expansion of
Pinus radiata timber plantations in the Fynbos biome of South Africa, with negative consequences for water supply and biodiversity. I built a dynamic ecological–economic model to investigate whether afforestation of a Fynbos catchment with
Pinus radiata is economically viable when the potential benefits of carbon sequestration and timber production are balanced against the losses to water supply. I found that afforestation appears viable to the forestry industry under current water tariffs and current carbon accounting legislation, but would appear unviable if the forestry industry were to pay the true cost of water used by the plantations. I also found that under various plausible future economic scenarios, afforestation can be associated with either large future economic gains or losses, suggesting a need for future analyses based on branches of decision theory that deal with severe uncertainty. I conclude with a general recommendation that climate legislation should be explicit about the conditions under which afforestation for carbon sequestration of native vegetation is a legitimate climate mitigation strategy.
Mapping forest species is highly relevant for many ecological and forestry applications. In Australia, the classification of native forest species using remote sensing data remains a particular ...challenge since there are many eucalyptus species that belong to the same genus and, thus, exhibit similar biophysical characteristics. This study assessed the potential of using hyperspectral remote sensing data and state-of-the-art machine-learning classification algorithms to classify Australian forest species at the leaf, canopy and community levels in Beecroft Peninsula, NSW, Australia. Spectral reflectance was acquired from an ASD spectrometer and airborne Hymap imagery for seven native forest species over an Australian eucalyptus forest. Three machine-learning classification algorithms: Support Vector Machine (SVM), AdaBoost and Random Forest (RF) were applied to classify the species. A comparative study was carried out between machine-learning classification algorithms and Linear Discriminant Analysis (LDA). The classification results show that all machine-leaning classification algorithms significantly improve the results produced by LDA. At the leaf level, RF achieved the best classification accuracy (94.7%), and SVM outperformed the other algorithms at both the canopy (84.5%) and community levels (75.5%). This study demonstrates that hyperspectral remote sensing and machine-learning classification has substantial potential for the classification of Australian native forest species.
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.
Intimate partner violence is a significant public health problem in our society, affecting women disproportionately. Intimate partner violence takes many forms, including physical violence, sexual ...violence, stalking, and psychological aggression. While the scope of intimate partner violence is not fully documented, nearly 40% of women in the United States are victims of sexual violence in their lifetimes and 20% are victims of physical intimate partner violence. Other forms of intimate partner violence are likely particularly underreported. Intimate partner violence has a substantial impact on a woman’s physical and mental health. Physical disorders include the direct consequences of injuries sustained after physical violence, such as fractures, lacerations and head trauma, sexually transmitted infections and unintended pregnancies as a consequence of sexual violence, and various pain disorders. Mental health impacts include an increased risk of depression, anxiety, posttraumatic stress disorder, and suicide. These adverse health effects are amplified in pregnancy, with an increased risk of pregnancy outcomes such as preterm birth, low birthweight, and small for gestational age. In many US localities, suicide and homicide are leading causes of pregnancy-associated mortality. We herein review the issues noted previously in greater depth and introduce the basic principles of intimate partner violence prevention. We separately address current recommendations for intimate partner violence screening and the evidence surrounding effectiveness of intimate partner violence interventions.
Abstract
Purpose
The purpose of this review is to (1) provide information concerning the opioid crisis including origins, trends, and some important related laws/policies; and (2) summarize the ...current involvement and impact of pharmacists in helping to address the crisis, as well as examine practices in other healthcare disciplines from which pharmacists might derive guidance and strategies.
Summary
Contributors to the opioid crisis included campaigns to treat pain as a fifth vital sign and to use opioids in treatment of non-cancer-related pain, as well as aggressive marketing of opioid analgesics by pharmaceutical companies. To address the crisis, numerous strategies have been implemented at the policy/legislative, health-system, and patient levels, such as prescription drug monitoring programs (PDMPs), increased regulation of pain clinics, and expanded use of naloxone. Pharmacists have a critical role to play in interventions to address opioid misuse and reduce harm resulting from misuse. Such interventions include patient screening and risk stratification, patient and community education and outreach concerning appropriate pain management, medication reviews/medication therapy management, education on safe storage and disposal, distribution of naloxone/opioid rescue kits and training on their proper use, and referral of patients to addiction treatment, among other strategies.
Conclusion
Pharmacists have multiple, complex roles in addressing the opioid crisis. Outcomes of several studies provide substantial evidence that pharmacists can make an impact through appropriate pain management, use of PDMPs, opioid overdose prevention training, and medication reviews and counseling, among other interventions.
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.
To estimate species loss from habitat destruction, ecologists typically use species–area relationships, but this approach neglects the spatial pattern of habitat fragmentation. Here, we provide new, ...easily applied, analytical methods that place upper and lower bounds on immediate species loss at any spatial scale and for any spatial pattern of habitat loss. Our formulas are expressed in terms of what we name the ‘Preston function’, which describes triphasic species–area relationships for contiguous regions. We apply our method to case studies of deforestation and tropical tree species loss at three different scales: a 50 ha forest plot in Panama, the tropical city‐state of Singapore and the Brazilian Amazon. Our results show that immediate species loss is somewhat insensitive to fragmentation pattern at small scales but highly sensitive at larger scales: predicted species loss in the Amazon varies by a factor of 16 across different spatial structures of habitat loss.
Abstract
Noise-assisted transport phenomena highlight the nontrivial interplay between environmental effects and quantum coherence in achieving maximal efficiency. Due to the complexity of ...biochemical systems and their environments, effective open quantum system models capable of providing physical insights on the presence and role of quantum effects are highly needed. In this paper, we introduce a new approach that combines an effective quantum microscopic description with a classical stochastic one. Our stochastic collision model (SCM) describes both Markovian and non-Markovian dynamics without relying on the weak coupling assumption. We investigate the consequences of spatial and temporal heterogeneity of noise on transport efficiency in a fully connected graph and in the Fenna–Matthews–Olson (FMO) complex. Our approach shows how to meaningfully formulate questions, and provide answers, on important open issues such as the properties of optimal noise and the emergence of the network structure as a result of an evolutionary process.
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