Ecoinformatics: supporting ecology as a data-intensive science

Ecology is evolving rapidly and increasingly changing into a more open, accountable, interdisciplinary, collaborative and data-intensive science. Discovering, integrating and analyzing massive amounts of heterogeneous data are central to ecology as researchers address complex questions at scales from the gene to the biosphere. Ecoinformatics offers tools and approaches for managing ecological data and transforming the data into information and knowledge. Here, we review the state-of-the-art and recent advances in ecoinformatics that can benefit ecologists and environmental scientists as they tackle increasingly challenging questions that require voluminous amounts of data across disciplines and scales of space and time. We also highlight the challenges and opportunities that remain.     

Value of long‐term ecological studies

Long‐term ecological studies are critical for providing key insights in ecology, environmental change, natural resource management and biodiversity conservation. In this paper, we briefly discuss five key values of such studies. These are: (1) quantifying ecological responses to drivers of ecosystem change; (2) understanding complex ecosystem processes that occur over prolonged periods; (3) providing core ecological data that may be used to develop theoretical ecological models and to parameterize and validate simulation models; (4) acting as platforms for collaborative studies, thus promoting multidisciplinary research; and (5) providing data and understanding at scales relevant to management, and hence critically supporting evidence‐based policy, decision making and the management of ecosystems. We suggest that the ecological research community needs to put higher priority on communicating the benefits of long‐term ecological studies to resource managers, policy makers and the general public. Long‐term research will be especially important for tackling large‐scale emerging problems confronting humanity such as resource management for a rapidly increasing human population, mass species extinction, and climate change detection, mitigation and adaptation. While some ecologically relevant, long‐term data sets are now becoming more generally available, these are exceptions. This deficiency occurs because ecological studies can be difficult to maintain for long periods as they exceed the length of government administrations and funding cycles. We argue that the ecological research community will need to coordinate ongoing efforts in an open and collaborative way, to ensure that discoverable long‐term ecological studies do not become a long‐term deficiency. It is important to maintain publishing outlets for empirical field‐based ecology, while simultaneously developing new systems of recognition that reward ecologists for the use and collaborative sharing of their long‐term data sets. Funding schemes must be re‐crafted to emphasize collaborative partnerships between field‐based ecologists, theoreticians and modellers, and to provide financial support that is committed over commensurate time frames.     

Vegetation demographics in Earth System Models: A review of progress and priorities

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real‐world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first‐generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter‐disciplinary communication.     

Ecosystem oceanography for global change in fisheries

Overexploitation and climate change are increasingly causing unanticipated changes in marine ecosystems, such as higher variability in fish recruitment and shifts in species dominance. An ecosystem-based approach to fisheries attempts to address these effects by integrating populations, food webs and fish habitats at different scales. Ecosystem models represent indispensable tools to achieve this objective. However, a balanced research strategy is needed to avoid overly complex models. Ecosystem oceanography represents such a balanced strategy that relates ecosystem components and their interactions to climate change and exploitation. It aims at developing realistic and robust models at different levels of organisation and addressing specific questions in a global change context while systematically exploring the ever-increasing amount of biological and environmental data.     

An evaluation of the state of spatial point pattern analysis in ecology

Over the last two decades spatial point pattern analysis (SPPA) has become increasingly popular in ecological research. To direct future work in this area we review studies using SPPA techniques in ecology and related disciplines. We first summarize the key elements of SPPA in ecology (i.e. data types, summary statistics and their estimation, null models, comparison of data and models, and consideration of heterogeneity); second, we review how ecologists have used these key elements; and finally, we identify practical difficulties that are still commonly encountered and point to new methods that allow current key questions in ecology to be effectively addressed. Our review of 308 articles published over the period 1992–2012 reveals that a standard canon of SPPA techniques in ecology has been largely identified and that most of the earlier technical issues that occupied ecologists, such as edge correction, have been solved. However, the majority of studies underused the methodological potential offered by modern SPPA. More advanced techniques of SPPA offer the potential to address a variety of highly relevant ecological questions. For example, inhomogeneous summary statistics can quantify the impact of heterogeneous environments, mark correlation functions can include trait and phylogenetic information in the analysis of multivariate spatial patterns, and more refined point process models can be used to realistically characterize the structure of a wide range of patterns. Additionally, recent advances in fitting spatially‐explicit simulation models of community dynamics to point pattern summary statistics hold the promise for solving the longstanding problem of linking pattern to process. All these newer developments allow ecologists to keep up with the increasing availability of spatial data sets provided by newer technologies, which allow point patterns and environmental variables to be mapped over large spatial extents at increasingly higher image resolutions.     

Field biology, food web models, and management: challenges of context and scale

Managers are increasingly aware of the need for science to inform the stewardship of natural lands and resources. If ecologists are to address this need, we must increase the scope of our inferences, while maintaining sufficient resolution and realism to predict trajectories of specific populations or ecosystem variables. Food chain and simple food web models, used either as core or component hypotheses, can help us to meet this challenge. The simple mass balance logic of dynamic food chain or food web models can organize our thinking about a range of applied problems, such as evaluating controls over populations of concern, or of biotic assemblages that affect important ecosystem properties. In other applications, a food chain or web may be incorporated as one element in models of regional mass balances affecting resources or environments. Specific predictions of food web models will often fail because of inadequate resolution (e.g., of functionally significant differences among taxa within "trophic levels") or insufficient scope (e.g., of spatio-temporal variation over scales relevant to management). Increasing use of tracers to delimit spatial scales of food web interactions will reduce, but not eliminate, this limitation. If used with skepticism and vigilance to local natural history, however, food chain or simple food web models can promote the iterative feedback between prediction, falsification by observation, and new prediction central to hypothetico-deductive science and adaptive management. Experience argues that this stepwise path is the fastest towards better understanding and control of our impacts on nature.     

Global networks for invasion science: benefits,challenges and guidelines

Much has been done to address the challenges of biological invasions, but fundamental questions (e.g., which species invade? Which habitats are invaded? How can invasions be effectively managed?) still need to be answered before the spread and impact of alien taxa can be effectively managed. Questions on the role of biogeography (e.g., how does biogeography influence ecosystem susceptibility, resistance and resilience against invasion?) have the greatest potential to address this goal by increasing our capacity to understand and accurately predict invasions at local, continental and global scales. This paper proposes a framework for the development of ‘Global Networks for Invasion Science’ to help generate approaches to address these critical and fundamentally biogeographic questions. We define global networks on the basis of their focus on research questions at the global scale, collection of primary data, use of standardized protocols and metrics, and commitment to long-term global data. Global networks are critical for the future of invasion science because of their potential to extend beyond the capacity of individual partners to identify global priorities for research agendas and coordinate data collection over space and time, assess risks and emerging trends, understand the complex influences of biogeography on mechanisms of invasion, predict the future of invasion dynamics, and use these new insights to improve the efficiency and effectiveness of evidence-based management techniques. While the pace and scale of global change continues to escalate, strategic and collaborative global networks offer a powerful approach to inform responses to the threats posed by biological invasions.     

Are there real differences among aquatic and terrestrial food webs?

Recently, aquatic and terrestrial ecologists have put forward several hypotheses regarding similarities and differences in food-web structure and function among these ecosystem types. Although many of these hypotheses explore why strong top-down effects and trophic cascades might be less common in terrestrial than in aquatic ecosystems, there is little theoretical or empirical evidence available to support or refute these hypotheses. Many unanswered questions remain about potential differences across ecosystem types: progress will require empirical studies designed within a broader context that allows for more direct comparisons.     

The big ecological questions inhibiting effective environmental management in Australia

The need to improve environmental management in Australia is urgent because human health, well‐being and social stability all depend ultimately on maintenance of life‐supporting ecological processes. Ecological science can inform this effort, but when issues are socially and economically complex the inclination is to wait for science to provide answers before acting. Increasingly, managers and policy‐makers will be called on to use the present state of scientific knowledge to supply reasonable inferences for action based on imperfect knowledge. Hence, one challenge is to use existing ecological knowledge more effectively; a second is to tackle the critical unanswered ecological questions. This paper identifies areas of environmental management that are profoundly hindered by an inability of science to answer basic questions, in contrast to those areas where knowledge is not the major barrier to policy development and management. Of the 22 big questions identified herein, more than half are directly related to climate change. Several of the questions concern our limited understanding of the dynamics of marine systems. There is enough information already available to develop effective policy and management to address several significant ecological issues. We urge ecologists to make better use of existing knowledge in dialogue with policy‐makers and land managers. Because the challenges are enormous, ecologists will increasingly be engaging a wide range of other disciplines to help identify pathways towards a sustainable future.     

生态系统服务与景观格局集成研究综述

生态系统服务是综合科学和政策应用的有效工具,可用于应对人类干扰下的景观和生态系统服务的快速退化等复杂生态环境问题。综述生态系统服务与景观格局集成的学科发展、基础理论和模型开发的进展与存在的问题,建立可用的集成建模框架,并提出知识集成的概念框架:1)在要素层,"政策-决策—景观—生态系统服务—社会经济系统"的跨学科知识反馈环是集成理论基础; 2)在模型层,结构化、多层次的集成模拟模型是核心方法; 3)在数据层,多源数据集成是模拟模型的数据基础。集成生态系统服务与景观格局为区域生态环境治理实践提供了科学参考,能更好地应对生态系统服务科学与应用的挑战。     

The Future of the Oceans Past: Towards a Global Marine Historical Research Initiative

Historical research is playing an increasingly important role in marine sciences. Historical data are also used in policy making and marine resource management, and have helped to address the issue of shifting baselines for numerous species and ecosystems. Although many important research questions still remain unanswered, tremendous developments in conceptual and methodological approaches are expected to contribute to a comprehensive understanding of the global history of human interactions with life in the seas. Based on our experiences and knowledge from the “History of Marine Animal Populations” project, this paper identifies the emerging research topics for future historical marine research. It elaborates on concepts and tools which are expected to play a major role in answering these questions, and identifies geographical regions which deserve future attention from marine environmental historians and historical ecologists.     

Stable Isotopes and Carbon Cycle Processes in Forests and Grasslands

Abstract: Scaling and partitioning are frequently two difficult challenges facing ecology today. With regard to ecosystem carbon balance studies, ecologists and atmospheric scientists are often interested in asking how fluxes of carbon dioxide scale across the landscape, region and continent. Yet at the same time, physiological ecologists and ecosystem ecologists are interested in dissecting the net ecosystem CO₂ exchange between the biosphere and the atmosphere to achieve a better understanding of the balance between photosynthesis and respiration within a forest. In both of these multiple-scale ecological questions, stable isotope analyses of carbon dioxide can play a central role in influencing our understanding of the extent to which terrestrial ecosystems are carbon sinks. In this synthesis, we review the theory and present field evidence to address isotopic scaling of CO₂ fluxes. We first show that the ¹³C isotopic signal which ecosystems impart to the atmosphere does not remain constant over time at either temporal or spatial scales. The relative balances of different biological activities and plant responses to stress result in dynamic changes in the ¹³C isotopic exchange between the biosphere and atmosphere, with both seasonal and stand-age factors playing major roles influencing the ¹³C biosphere-atmosphere exchange. We then examine how stable isotopes are used to partition net ecosystem exchange fluxes in order to calculate shifts in the balance of photosynthesis and respiration. Lastly, we explore how fundamental differences in the ¹⁸O isotopic gas exchange of forest and grassland ecosystems can be used to further partition terrestrial fluxes.     

Targeted sequence capture as a powerful tool for evolutionary analysis1

Next-generation sequencing technologies (NGS) have revolutionized biological research by significantly increasing data generation while simultaneously decreasing the time to data output. For many ecologists and evolutionary biologists, the research opportunities afforded by NGS are substantial; even for taxa lacking genomic resources, large-scale genome-level questions can now be addressed, opening up many new avenues of research. While rapid and massive sequencing afforded by NGS increases the scope and scale of many research objectives, whole genome sequencing is often unwarranted and unnecessarily complex for specific research questions. Recently developed targeted sequence enrichment, coupled with NGS, represents a beneficial strategy for enhancing data generation to answer questions in ecology and evolutionary biology. This marriage of technologies offers researchers a simple method to isolate and analyze a few to hundreds, or even thousands, of genes or genomic regions from few to many samples in a relatively efficient and effective manner. These strategies can be applied to questions at both the infra- and interspecific levels, including those involving parentage, gene flow, divergence, phylogenetics, reticulate evolution, and many more. Here we provide a brief overview of targeted sequence enrichment, and emphasize the power of this technology to increase our ability to address a wide range of questions of interest to ecologists and evolutionary biologists, particularly for those working with taxa for which few genomic resources are available.     

Evolution of natural history information in the 21st century – developing an integrated framework for biological and geographical data

Threats to marine and estuarine species operate over many spatial scales, from nutrient enrichment at the watershed/estuarine scale to invasive species and climate change at regional and global scales. To help address research questions across these scales, we provide here a standardized framework for a biogeographical information system containing queriable biological data that allows extraction of information on multiple species, across a variety of spatial scales based on species distributions, natural history attributes and habitat requirements. As scientists shift from research on localized impacts on individual species to regional and global scale threats, macroecological approaches of studying multiple species over broad geographical areas are becoming increasingly important. The standardized framework described here for capturing and integrating biological and geographical data is a critical first step towards addressing these macroecological questions and we urge organizations capturing biogeoinformatics data to consider adopting this framework.     

Endangered species and a threatened discipline: behavioural ecology

Behavioural ecologists often see little connection between the current conservation crisis and the future of their discipline. This view is myopic because our abilities to investigate and interpret the adaptive significance and evolutionary histories of behaviours are increasingly being compromised in human-dominated landscapes because of species extinctions, habitat destruction, invasive species, pollution, and climate change. In this review, we argue that many central issues in behavioural ecology will soon become prohibitively difficult to investigate and interpret, thus impeding the rapid progress that characterizes the field. To address these challenges, behavioural ecologists should design studies not only to answer basic scientific questions but also to provide ancillary information for protection and management of their study organisms and habitats, and then share their biological insights with the applied conservation community.     

Modelling nutritional mutualisms: challenges and opportunities for data integration

Nutritional mutualisms are ancient, widespread, and profoundly influential in biological communities and ecosystems. Although much is known about these interactions, comprehensive answers to fundamental questions, such as how resource availability and structured interactions influence mutualism persistence, are still lacking. Mathematical modelling of nutritional mutualisms has great potential to facilitate the search for comprehensive answers to these and other fundamental questions by connecting the physiological and genomic underpinnings of mutualisms with ecological and evolutionary processes. In particular, when integrated with empirical data, models enable understanding of underlying mechanisms and generalisation of principles beyond the particulars of a given system. Here, we demonstrate how mathematical models can be integrated with data to address questions of mutualism persistence at four biological scales: cell, individual, population, and community. We highlight select studies where data has been or could be integrated with models to either inform model structure or test model predictions. We also point out opportunities to increase model rigour through tighter integration with data, and describe areas in which data is urgently needed. We focus on plant‐microbe systems, for which a wealth of empirical data is available, but the principles and approaches can be generally applied to any nutritional mutualism.     

Study design and parameter estimability for spatial and temporal ecological models

The statistical tools available to ecologists are becoming increasingly sophisticated, allowing more complex, mechanistic models to be fit to ecological data. Such models have the potential to provide new insights into the processes underlying ecological patterns, but the inferences made are limited by the information in the data. Statistical nonestimability of model parameters due to insufficient information in the data is a problem too‐often ignored by ecologists employing complex models. Here, we show how a new statistical computing method called data cloning can be used to inform study design by assessing the estimability of parameters under different spatial and temporal scales of sampling. A case study of parasite transmission from farmed to wild salmon highlights that assessing the estimability of ecologically relevant parameters should be a key step when designing studies in which fitting complex mechanistic models is the end goal.     

生态系统途径——生态系统管理的一种新理念

介绍了生态系统途径的概念和内涵．生态系统途径最早由西方生态学家提出。随后得到一系列国际学术组织和国家的认同和支持,其中《生物多样性公约》、世界自然保护联盟和世界野生动物基金发挥了重要作用,．生态系统途径的实质是对土地、水和生物资源进行综合管理,旨在生态系统保护、生物资源可持续利用和共享生物资源三者之间达到平衡．作为生态系统管理的一种方法论,它以生物为核心。将人类及文化的多样性视为生态系统的一个组成部分,2000年《生物多样性公约》缔约国会议上制定的生态系统管理的12条基本原则和5项行动指南,丰富了生态系统途径的内涵,明确了实施的办法,我国在生态系统管理方面有着丰富的学术储备和经验总结。但也存在一定问题。

     

基于能值分析的煤炭矿区复合生态系统评价

煤炭矿区复合生态系统评价是对其进行有效管理及调控的手段之一。研究了煤炭矿区复合生态系统内涵,剖析了煤炭矿区复合生态系统的典型特征,论述了运用能值分析方法评价复合生态系统的特殊性;进而,构建了煤炭矿区复合生态系统及其子系统的能值评价指标。选择山东省龙口矿区北皂煤矿为研究对象,进行了实证研究。应用实际数据,测算了2006—2012年复合生态系统及子系统各个能值评价指标。研究结果表明,能值理论与能值分析是评价煤炭矿区复合生态系统的有效方法,各项指标变化反映了复合生态系统的演进趋势;不可再生煤炭资源的过度消耗、可再资源利用率低是这一系统的典型特征;能值评价指标的测算结果表征环境子系统负荷较小。研究结果可为实施有效的煤炭矿区复合生态系统管理提供智力支持和决策参考依据。