Interactions between climate and habitat loss effects on biodiversity: a systematic review and meta‐analysis

Climate change and habitat loss are both key threatening processes driving the global loss in biodiversity. Yet little is known about their synergistic effects on biological populations due to the complexity underlying both processes. If the combined effects of habitat loss and climate change are greater than the effects of each threat individually, current conservation management strategies may be inefficient and at worst ineffective. Therefore, there is a pressing need to identify whether interacting effects between climate change and habitat loss exist and, if so, quantify the magnitude of their impact. In this article, we present a meta‐analysis of studies that quantify the effect of habitat loss on biological populations and examine whether the magnitude of these effects depends on current climatic conditions and historical rates of climate change. We examined 1319 papers on habitat loss and fragmentation, identified from the past 20 years, representing a range of taxa, landscapes, land‐uses, geographic locations and climatic conditions. We find that current climate and climate change are important factors determining the negative effects of habitat loss on species density and/or diversity. The most important determinant of habitat loss and fragmentation effects, averaged across species and geographic regions, was current maximum temperature, with mean precipitation change over the last 100 years of secondary importance. Habitat loss and fragmentation effects were greatest in areas with high maximum temperatures. Conversely, they were lowest in areas where average rainfall has increased over time. To our knowledge, this is the first study to conduct a global terrestrial analysis of existing data to quantify and test for interacting effects between current climate, climatic change and habitat loss on biological populations. Understanding the synergistic effects between climate change and other threatening processes has critical implications for our ability to support and incorporate climate change adaptation measures into policy development and management response.     

Exploring the compass of potential changes induced by climate warming in plant communities

New models are required to predict the impacts of future climate change on biodiversity. A move must be made away from individual models of single species toward approaches with synergistically interacting species. The focus should be on indirect effects due to biotic interactions. Here we propose a new parsimonious approach to simulate direct and indirect effects of global warming on plant communities. The methodology consists of five steps: a) field survey of species abundances, b) quantitative assessment of species co-occurrences, c) assignment of a theorised effect of increased temperature on each species, d) creation of a community model to project community dynamics, and e) exploration of the potential range of temperature change effects on plant communities.We explored the possible climate-driven dynamics in an alpine vegetation community and gained insights into the role of biotic interactions as determinants of plant species response to climate change at local scale. The study area was the uppermost portion of Alpe delle Tre Potenze (Northern Apennines, Italy) from 1500 m up to the summit at 1940 m.Our work shows that: 1) unexpected climate-driven dynamics can emerge, 2) interactive communities with indirect effects among species can overcome direct effects induced by global warming; 3) if just one or few species react to global warming the new community configuration could be unexpected and counter-intuitive; 4) timing of species reactions to global warming is an important driver of community dynamics; 5) using simulation models with a limited amount of data in input, it is possible to explore the full range of potential changes in plant communities induced by climate warming.     

Causal mediation analyses with rank preserving models

We present a linear rank preserving model (RPM) approach for analyzing mediation of a randomized baseline intervention's effect on a univariate follow-up outcome. Unlike standard mediation analyses, our approach does not assume that the mediating factor is also randomly assigned to individuals in addition to the randomized baseline intervention (i.e., sequential ignorability), but does make several structural interaction assumptions that currently are untestable. The G-estimation procedure for the proposed RPM represents an extension of the work on direct effects of randomized intervention effects for survival outcomes by Robins and Greenland (1994, Journal of the American Statistical Association 89, 737-749) and on intervention non-adherence by Ten Have et al. (2004, Journal of the American Statistical Association 99, 8-16). Simulations show good estimation and confidence interval performance by the proposed RPM approach under unmeasured confounding relative to the standard mediation approach, but poor performance under departures from the structural interaction assumptions. The trade-off between these assumptions is evaluated in the context of two suicide/depression intervention studies.     

Enabling regional management in a changing climate through Bayesian meta‐analysis of a large‐scale disturbance

Aim Quantifying and predicting change in large ecosystems is an important research objective for applied ecologists as human disturbance effects become increasingly evident at regional and global scales. However, studies used to make inferences about large‐scale change are frequently of uneven quality and few in number, having been undertaken to study local, rather than global, change. Our aim is to improve the quality of inferences that can be made in meta‐analyses of large‐scale disturbance by integrating studies of varying quality in a unified modelling framework that is informative for both local and regional management. Innovation Here we improve conventionally structured meta‐analysis methods by including imputation of unknown study variances and the use of Bayesian factor potentials. The approach is a coherent framework for integrating data of varying quality across multiple studies while facilitating belief statements about the uncertainty in parameter estimates and the probable outcome of future events. The approach is applied to a regional meta‐analysis of the effects of loss of coral cover on species richness and the abundance of coral‐dependent fishes in the western Indian Ocean (WIO) before and after a mass bleaching event in 1998. Main conclusions Our Bayesian approach to meta‐analysis provided greater precision of parameter estimates than conventional weighted linear regression meta‐analytical techniques, allowing us to integrate all available data from 66 available study locations in the WIO across multiple scales. The approach thereby: (1) estimated uncertainty in site‐level estimates of change, (2) provided a regional estimate for future change at any given site in the WIO, and (3) provided a probabilistic belief framework for future management of reef resources at both local and regional scales.     

Using Realistic Evaluation to understand how interventions work on dairy farms

Interventions that aim to help farmers change on-farm practices recommend that advisors communicate effectively with farmers, work collaboratively to set goals and provide farmers with resources that are applicable to the farm context. We developed an intervention that aimed to help farmers modify and use a standard operating procedure (SOP) for colostrum management; failure of passive transfer of immunoglobulins is common on dairy farms and SOPs for colostrum management are increasingly required by farm animal welfare assurance programs. We used Realistic Evaluation to evaluate whether, how and why our intervention to help farmers modify and use SOPs for colostrum management facilitated change and provide recommendations based on our approach that can improve the design and implementation of future interventions. We used a multiple case study on five farms over 8 months, collecting data through interviews, participant observation, document analysis and field notes. We identified three mechanisms that influenced whether participants modified and used their SOP. The purpose mechanism distinguished between participants who thought the aim of the SOP was for farm staff to learn and understand how to complete a task versus those who thought that the SOP was only useful for compliance with assurance programs. The utility mechanism distinguished between participants who thought that the SOP would be helpful for daily use on their farm, versus those who did not. The physical text mechanism distinguished between participants who used the templates we provided to modify and use their SOP, versus those who did not. A key contextual factor on all farms was participant belief of having capable and engaged staff on their farm; modification and use of the SOP did not occur unless this was the case. To facilitate change, intervention developers should actively participate in the intervention to develop an understanding of farmer needs, understand the purpose behind different goals set by farmers and integrate tools, advice and resource demonstrations when possible. We conclude that Realistic Evaluation is a useful framework for evaluating how contexts and mechanisms generate outcomes on farms, and to understand how, and in which contexts, complex interventions facilitate change. We suggest that this approach can improve the success of interventions and help direct the approaches used on different farms.     

Prediction uncertainty of environmental change effects on temperate European biodiversity

Observed patterns of species richness at landscape scale (gamma diversity) cannot always be attributed to a specific set of explanatory variables, but rather different alternative explanatory statistical models of similar quality may exist. Therefore predictions of the effects of environmental change (such as in climate or land cover) on biodiversity may differ considerably, depending on the chosen set of explanatory variables. Here we use multimodel prediction to evaluate effects of climate, land-use intensity and landscape structure on species richness in each of seven groups of organisms (plants, birds, spiders, wild bees, ground beetles, true bugs and hoverflies) in temperate Europe. We contrast this approach with traditional best-model predictions, which we show, using cross-validation, to have inferior prediction accuracy. Multimodel inference changed the importance of some environmental variables in comparison with the best model, and accordingly gave deviating predictions for environmental change effects. Overall, prediction uncertainty for the multimodel approach was only slightly higher than that of the best model, and absolute changes in predicted species richness were also comparable. Richness predictions varied generally more for the impact of climate change than for land-use change at the coarse scale of our study. Overall, our study indicates that the uncertainty introduced to environmental change predictions through uncertainty in model selection both qualitatively and quantitatively affects species richness projections.     

Cascading effects of climate change on plankton community structure

Plankton communities account for at least half of global primary production and play a key role in the global carbon cycle. Warming and acidification may alter the interaction chains in these communities from the bottom and top of the food web. Yet, the relative importance of these potentially complex interactions has not yet been quantified. Here, we examine the isolated and combined effects of warming, acidification, and reductions in phytoplankton and predator abundances in a series of factorial experiments. We find that warming directly impacts the top of the food web, but that the intermediate trophic groups are more strongly influenced by indirect effects mediated by altered top‐down interactions. Direct manipulations of predator and phytoplankton abundance reveal similar strong top‐down interactions following top predator decline. A meta‐analysis of published experiments further supports the conclusion that warming has stronger direct impacts on the top and bottom of the food web rather than the intermediate trophic groups, with important differences between freshwater and marine plankton communities. Our results reveal that the trophic effect of warming cascading down from the top of the plankton food web is a powerful agent of global change.     

A review of influences of land use and land cover change on ecosystems

随着人口的增长和人类社会的发展, 土地利用与土地覆盖变化已经是不可避免。土地利用与土地覆盖变化不仅对生态系统的要素、结构和功能产生深远的影响, 也会对全球变化产生反馈作用。针对土地利用与土地覆盖变化的过程、驱动机制以及在各个方面可能产生的生态环境效应的科学研究已经全面开展。该文综述了土地利用与土地覆盖变化对气候、土壤、生物地球化学循环、生物多样性以及区域生态环境等影响方面的研究进展, 并提出了相关研究的前沿方向展望。随着新技术的不断发展, 学者们将更多地侧重预测未来全球变化背景下的土地利用与土地覆盖变化趋势、合理性以及适应性, 为可持续发展提供基础资料和理论依据。     

Additive effects of temperature and infection with an acanthocephalan parasite on the shredding activity of Gammarus fossarum (Crustacea: Amphipoda): the importance of aggregative behavior

Climate change can have critical impacts on the ecological role of keystone species, leading to subsequent alterations within ecosystems. The consequences of climate change may be best predicted by understanding its interaction with the cumulative effects of other stressors, although this approach is rarely adopted. However, whether this interaction is additive or interactive can hardly be predicted from studies examining a single factor at a time. In particular, biotic interactions are known to induce modifications in the functional role of many species. Here, we explored the effect of temperature on leaf consumption by a keystone freshwater shredder, the amphipod Gammarus fossarum. This species is found at high densities in the wild and relies on aggregation as an antipredator behavior. In addition, gammarids regularly harbor acanthocephalan parasites that are known to induce multiple effects on their hosts, including modifications on their functional role. We thus assessed the cumulative effect of both intraspecific interactions and parasitism. Consumption tests were conducted on gammarids, either naturally infected with Pomphorhynchus tereticollis or uninfected, feeding alone or in groups. Our results show that increased temperatures induced a significant increase in consumption, but only to a certain extent. Interestingly, consumption at the highest temperature depended on amphipod density: Whereas a decrease was observed for single individuals, no such effect on feeding was observed for individuals in groups. In addition, infection by acanthocephalan parasites per se significantly negatively impacted the shredding role of gammarids. Overall, the combined effects of parasitism and temperature appeared to be additive. Thus, future studies focusing on the impact of climate change on the functional role of keystone species may benefit from a multimodal approach under realistic conditions to derive accurate predictions.     

土地利用与土地覆盖变化对生态系统的影响

随着人口的增长和人类社会的发展, 土地利用与土地覆盖变化已经是不可避免。土地利用与土地覆盖变化不仅对生态系统的要素、结构和功能产生深远的影响, 也会对全球变化产生反馈作用。针对土地利用与土地覆盖变化的过程、驱动机制以及在各个方面可能产生的生态环境效应的科学研究已经全面开展。该文综述了土地利用与土地覆盖变化对气候、土壤、生物地球化学循环、生物多样性以及区域生态环境等影响方面的研究进展, 并提出了相关研究的前沿方向展望。随着新技术的不断发展, 学者们将更多地侧重预测未来全球变化背景下的土地利用与土地覆盖变化趋势、合理性以及适应性, 为可持续发展提供基础资料和理论依据。     

Climate change vulnerability of forest biodiversity: climate and competition tracking of demographic rates

Forest responses to climate change will depend on demographic impacts in the context of competition. Current models used to predict species responses, termed climate envelope models (CEMs), are controversial, because (i) calibration and prediction are based on correlations in space (CIS) between species abundance and climate, rather than responses to climate change over time (COT), and (ii) they omit competition. To determine the relative importance of COT, CIS, and competition for light, we applied a longitudinal analysis of 27 000 individual trees over 6–18 years subjected to experimental and natural variation in risk factors. Sensitivities and climate and resource tracking identify which species are vulnerable to these risk factors and in what ways. Results show that responses to COT differ from those predicted based on CIS. The most important impact is the effect of spring temperature on fecundity, rather than any input variable on growth or survival. Of secondary importance is growing season moisture. Species in the genera Pinus, Ulmus, Magnolia, and Fagus are particularly vulnerable to climate variation. However, the effect of competition on growth and mortality risk exceeds the effects of climate variation in space or time for most species. Because sensitivities to COT and competition are larger than CIS, current models miss the most important effects. By directly comparing sensitivity to climate in time and space, together with competition, the approach identifies which species are sensitive to climate change and why, including the heretofore overlooked impact on fecundity.     

Across the grain: Multi-scale map comparison and land change assessment

Changes in the spatial distribution of land cover and land use can have significant impacts on ecological processes at multiple scales; estimating these changes provides critical data for both monitoring and understanding land-use effects on these processes. One approach to mapping landcover changes, particularly useful over longer periods of time, is comparison of existing landcover maps, (post-classification change analysis). The accuracy of these maps is often unknown and varies depending on data sources and interpretation techniques; therefore, separating change on the ground from differences attributable to sensors and methods is both critical and problematic. Through a novel map comparison method applying major axis regression at multiple spatial grains of analysis, this study partitioned accuracy into components of bias and precision in comparing maps, which aided selection of an optimal analytical grain size. Comparisons between contemporaneous maps showed the magnitude and distribution of error alone, while between-period analyses indicated both cumulative map error and change on the ground. These methods enable exploration of the nature of error and identification of differences between maps, while accounting for the imprecision and bias inherent in the source documents. Mapping landcover change delineates landscapes under recent disturbance pressure, and these measures are more effective as performance indicators for broad-scale evaluation of natural heritage policies and habitat restoration initiatives when error in the data is identified and accounted for.     

Novel Approaches to Study Climate Change Effects on Terrestrial Ecosystems in the Field: Drought and Passive Nighttime Warming

This article describes new approaches for manipulation of temperature and water input in the field. Nighttime warming was created by reflection of infrared radiation. Automatically operated reflective curtains covered the vegetation at night to reduce heat loss to the atmosphere. This approach mimicked the way climate change, caused by increased cloudiness and increased greenhouse gas emissions, alters the heat balance of ecosystems. Drought conditions were created by automatically covering the vegetation with transparent curtains during rain events over a 2–5-month period. The experimental approach has been evaluated at four European sites across a climate gradient. All sites were dominated (more than 50%) by shrubs of the ericaceous family. Within each site, replicated 4-m × 5-m plots were established for control, warming, and drought treatments and the effect on climate variables recorded. Results over a two-year period indicate that the warming treatment was successful in achieving an increase of the minimum temperatures by 0.4–1.2°C in the air and soil. The drought treatment resulted in a soil moisture reduction of 33%–82% at the peak of the drought. The data presented demonstrate that the approach minimizes unintended artifacts with respect to water balance, moisture conditions, and light, while causing a small but significant reduction in wind speed by the curtains. Temperature measurements demonstrated that the edge effects associated with the treatments were small. Our method provides a valuable tool for investigating the effects of climate change in remote locations with minimal artifacts.     

Estimating the amount of compositional change in late-Quaternary pollen-stratigraphical data

Detrended canonical correspondence analysis is used to estimate the amount of palynological change or compositional turnover in ten Holocene pollen-stratigraphical sequences from Setesdal, southern Norway. The results, when the analyses are standardised for the same time interval, show that the highest amounts of change occurred at sites in the south of Setesdal where there is a richer tree flora. This primarily methodological study provides a robust approach to answering the question as to how much change is recorded within a pollen sequence, and to summarising the amount of change between sequences.     

Stress synergy between drought and a common environmental contaminant: studies with the collembolan Folsomia candida

The term global change is used predominantly in connection with the global temperature increase and associated changes in weather patterns over the next century. In a broader sense it also covers other anthropogenic impacts on the environment such as habitat fragmentation and pollution. The individual effects of each of these stress types have been extensively studied in the biota. However, organisms will frequently encounter these stress types in combination rather than alone and there is little information available on the effects of stress combinations. Here an examination is made of the interaction between realistic levels of summer drought and a common contaminant of agricultural soil (4‐nonylphenol, NP), on a widespread soil invertebrate, the collembolan Folsomia candida. These stress factors were tested individually and in combination using a full factorial design. This approach revealed the existence of highly significant Bliss type synergistic interaction between the two stress types. Thus, exposure to NP significantly reduced the drought tolerance of this organism and, reciprocally, the toxicity of NP (LC₅₀) during realistic summer drought was more than doubled in comparison to the value obtained under optimal soil moisture conditions. Furthermore, it is shown that NP has a detrimental effect on the physiological mechanisms underlying this animal's drought tolerance, thus providing some explanation for the mechanisms involved in the synergy. It is argued that this type of synergy is unlikely to be confined to this particular combination of stresses and thus there is a need to study the interactions between dominant natural stresses and pollution. The most important implication of these results is that some of the effects of global climate changes can be predicted to be most severe in polluted areas.     

Drivers of protogynous sex change differ across spatial scales

The influence of social demography on sex change schedules in protogynous reef fishes is well established, yet effects across spatial scales (in particular, the magnitude of natural variation relative to size-selective fishing effects) are poorly understood. Here, I examine variation in timing of sex change for exploited parrotfishes across a range of environmental, anthropogenic and geographical factors. Results were highly dependent on spatial scale. Fishing pressure was the most influential factor determining length at sex change at the within-island scale where a wide range of anthropogenic pressure existed. Sex transition occurred at smaller sizes where fishing pressure was high. Among islands, however, differences were overwhelmingly predicted by reefal-scale structural features, a pattern evident for all species examined. For the most abundant species, Chlorurus spilurus, length at sex change increased at higher overall densities and greater female-to-male sex ratios at all islands except where targeted by fishermen; here the trend was reversed. This implies differing selective pressures on adult individuals can significantly alter sex change dynamics, highlighting the importance of social structure, demography and the selective forces structuring populations. Considerable life-history responses to exploitation were observed, but results suggest potential fishing effects on demography may be obscured by natural variation at biogeographic scales.     

Synergistic effects of climate and land‐use change influence broad‐scale avian population declines

Climate and land‐use changes are expected to be the primary drivers of future global biodiversity loss. Although theory suggests that these factors impact species synergistically, past studies have either focused on only one in isolation or have substituted space for time, which often results in confounding between drivers. Tests of synergistic effects require congruent time series on animal populations, climate change and land‐use change replicated across landscapes that span the gradient of correlations between the drivers of change. Using a unique time series of high‐resolution climate (measured as temperature and precipitation) and land‐use change (measured as forest change) data, we show that these drivers of global change act synergistically to influence forest bird population declines over 29 years in the Pacific Northwest of the United States. Nearly half of the species examined had declined over this time. Populations declined most in response to loss of early seral and mature forest, with responses to loss of early seral forest amplified in landscapes that had warmed over time. In addition, birds declined more in response to loss of mature forest in areas that had dried over time. Climate change did not appear to impact populations in landscapes with limited habitat loss, except when those landscapes were initially warmer than the average landscape. Our results provide some of the first empirical evidence of synergistic effects of climate and land‐use change on animal population dynamics, suggesting accelerated loss of biodiversity in areas under pressure from multiple global change drivers. Furthermore, our findings suggest strong spatial variability in the impacts of climate change and highlight the need for future studies to evaluate multiple drivers simultaneously to avoid potential misattribution of effects.     

A simple meta-analytic approach for using a binary surrogate endpoint to predict the effect of intervention on true endpoint

A surrogate endpoint is an endpoint that is obtained sooner, at lower cost, or less invasively than the true endpoint for a health outcome and is used to make conclusions about the effect of intervention on the true endpoint. In this approach, each previous trial with surrogate and true endpoints contributes an estimated predicted effect of intervention on true endpoint in the trial of interest based on the surrogate endpoint in the trial of interest. These predicted quantities are combined in a simple random-effects meta-analysis to estimate the predicted effect of intervention on true endpoint in the trial of interest. Validation involves comparing the average prediction error of the aforementioned approach with (i) the average prediction error of a standard meta-analysis using only true endpoints in the other trials and (ii) the average clinically meaningful difference in true endpoints implicit in the trials. Validation is illustrated using data from multiple randomized trials of patients with advanced colorectal cancer in which the surrogate endpoint was tumor response and the true endpoint was median survival time.     

Cancer risk reduction in the US Affiliated Pacific Islands: Utilizing a novel policy,systems, and environmental (PSE) approach

BackgroundThe Health Directors of the US Affiliated Pacific Islands (USAPI) declared a State of Emergency due to epidemic proportions of lifestyle diseases: cancer, obesity and other non-communicable diseases (NCDs) in 2010. This paper describes the development, implementation, and evaluation of a USAPI policy, system and environment (PSE) approach to address lifestyle behaviors associated with cancer and other NCDs.MethodsEach of USAPI jurisdictions applied the PSE approach to tobacco and nutrition interventions in a local institution, faith based, or community setting. A participatory community engagement process was utilized to: identify relevant deleterious health behaviors in the population, develop PSE interventions to modify the context in which the behavior occurs in a particular setting, implement the PSE intervention through five specified activities, and evaluate the activities and behavior change associated with the intervention.ResultsPSE interventions have been implemented in all USAPI jurisdictions. Current human and financial resources have been adequate to support the interventions. Process and behavior change evaluations have not been completed and is ongoing. Personnel turnover and maintaining the intervention strategy in response due to shifting community demands has been the biggest challenge in one site.ConclusionFrom 2014 through 2016 the PSE approach has been used to implement PSE interventions in all USAPI jurisdictions. The intervention evaluations have not been completed. The PSE intervention is novel and has the potential to be a scalable methodology to prevent cancer and modify NCD risk in the USAPI and small states.