Do not downplay biodiversity loss

And the stars look down: science beyond the finite : From prehistorical science to postscience

Modern science has brought undisputable welfare to mankind, but also harmful consequences, and it has to face great challenges to find a way out of the current global crisis.

Mathematical biases in the calculation of the Living Planet Index lead to overestimation of vertebrate population decline

The Living Planet Index (LPI) measures the average change in population size of vertebrate species over recent decades and has been repeatedly used to assess the changing state of nature. The LPI indicates that vertebrate populations have decreased by almost 70% over the last 50 years. This is in striking contrast with current studies based on the same population time series data that show that increasing and decreasing populations are balanced on average. Here, we examine the methodological pipeline of calculating the LPI to search for the source of this discrepancy. We find that the calculation of the LPI is biased by several mathematical issues which impose an imbalance between detected increasing and decreasing trends and overestimate population declines. Rather than indicating that vertebrate populations do not substantially change, our findings imply that we need better measures for providing a balanced picture of current biodiversity changes. We also show some modifications to improve the reliability of the LPI.

Piccadilly full of people and other foul things : On heroism and perversion in the post-pandemic era

Science gifts us the tools to solve the pressing humanitarian and ecological challenges of our time. But ignorance and selfishness prevent us from using science to the best effect.

Revealing uncertainty in the status of biodiversity change

Biodiversity faces unprecedented threats from rapid global change1. Signals of biodiversity change come from time-series abundance datasets for thousands of species over large geographic and temporal scales. Analyses of these biodiversity datasets have pointed to varied trends in abundance, including increases and decreases. However, these analyses have not fully accounted for spatial, temporal and phylogenetic structures in the data. Here, using a new statistical framework, we show across ten high-profile biodiversity datasets2-11 that increases and decreases under existing approaches vanish once spatial, temporal and phylogenetic structures are accounted for. This is a consequence of existing approaches severely underestimating trend uncertainty and sometimes misestimating the trend direction. Under our revised average abundance trends that appropriately recognize uncertainty, we failed to observe a single increasing or decreasing trend at 95% credible intervals in our ten datasets. This emphasizes how little is known about biodiversity change across vast spatial and taxonomic scales. Despite this uncertainty at vast scales, we reveal improved local-scale prediction accuracy by accounting for spatial, temporal and phylogenetic structures. Improved prediction offers hope of estimating biodiversity change at policy-relevant scales, guiding adaptive conservation responses.

Forecasting insect dynamics in a changing world

Predicting how insects will respond to stressors through time is difficult because of the diversity of insects, environments, and approaches used to monitor and model. Forecasting models take correlative/statistical, mechanistic models, and integrated forms; in some cases, temporal processes can be inferred from spatial models. Because of heterogeneity associated with broad community measurements, models are often unable to identify mechanistic explanations. Many present efforts to forecast insect dynamics are restricted to single-species models, which can offer precise predictions but limited generalizability. Trait-based approaches may offer a good compromise that limits the masking of the ranges of responses while still offering insight. Regardless of the modeling approach, the data used to parameterize a forecasting model should be carefully evaluated for temporal autocorrelation, minimum data needs, and sampling biases in the data. Forecasting models can be tested using near-term predictions and revised to improve future forecasts.

Global food trade alleviates transgressions of planetary boundaries at the national scale

Food systems are among the leading causes for transgression of planetary boundaries globally, which define the safe operating space for humanity. We quantify unsustainable environmental impacts of food systems, indicated by the transgression of national-scale planetary boundaries (i.e., the safe operating space for food production in each country), from both production and consumption perspectives of 189 countries/regions around the world. A multi-regional input-output model is used to map the global transfers of the national-scale transgression of planetary boundaries, including freshwater use, land change, and biogeochemical flows (nitrogen and phosphorus). Our results show that China is a major global unsustainable water and nitrogen exporter and an unstable land and phosphorus importer. This means that water and nitrogen uses in China are used to support food demands in other countries, and food consumption in China requires unsustainable land and phosphorus uses elsewhere. In contrast, the US is a major exporter of unsustainable water, land, and nitrogen uses but only an importer of unsustainable phosphorus for food consumption. Globally, compared to a counterfactual scenario where there is no food trade among any countries, food trade saves massive transgressions of planetary boundaries (270 km3 of water, 18 million tons of nitrogen, 7 million tons of phosphorus, and 5,431 million km2 of land). Alleviation of national-scale planetary boundary transgression has been achieved primarily in the US, China, Saudi Arabia, etc., while aggravation was incurred in Pakistan, Australia, Argentina, and so forth.

More losers than winners: investigating Anthropocene defaunation through the diversity of population trends

The global-scale decline of animal biodiversity ('defaunation') represents one of the most alarming consequences of human impacts on the planet. The quantification of this extinction crisis has traditionally relied on the use of IUCN Red List conservation categories assigned to each assessed species. This approach reveals that a quarter of the world's animal species are currently threatened with extinction, and ~1% have been declared extinct. However, extinctions are preceded by progressive population declines through time that leave demographic 'footprints' that can alert us about the trajectories of species towards extinction. Therefore, an exclusive focus on IUCN conservation categories, without consideration of dynamic population trends, may underestimate the true extent of the processes of ongoing extinctions across nature. In fact, emerging evidence (e.g. the Living Planet Report), reveals a widespread tendency for sustained demographic declines (an average 69% decline in population abundances) of species globally. Yet, animal species are not only declining. Many species worldwide exhibit stable populations, while others are even thriving. Here, using population trend data for >71,000 animal species spanning all five groups of vertebrates (mammals, birds, reptiles, amphibians and fishes) and insects, we provide a comprehensive global-scale assessment of the diversity of population trends across species undergoing not only declines, but also population stability and increases. We show a widespread global erosion of species, with 48% undergoing declines, while 49% and 3% of species currently remain stable or are increasing, respectively. Geographically, we reveal an intriguing pattern similar to that of threatened species, whereby declines tend to concentrate around tropical regions, whereas stability and increases show a tendency to expand towards temperate climates. Importantly, we find that for species currently classed by the IUCN Red List as 'non-threatened', 33% are declining. Critically, in contrast with previous mass extinction events, our assessment shows that the Anthropocene extinction crisis is undergoing a rapid biodiversity imbalance, with levels of declines (a symptom of extinction) greatly exceeding levels of increases (a symptom of ecological expansion and potentially of evolution) for all groups. Our study contributes a further signal indicating that global biodiversity is entering a mass extinction, with ecosystem heterogeneity and functioning, biodiversity persistence, and human well-being under increasing threat.

Understanding 'it depends' in ecology: a guide to hypothesising, visualising and interpreting statistical interactions

Ecologists routinely use statistical models to detect and explain interactions among ecological drivers, with a goal to evaluate whether an effect of interest changes in sign or magnitude in different contexts. Two fundamental properties of interactions are often overlooked during the process of hypothesising, visualising and interpreting interactions between drivers: the measurement scale - whether a response is analysed on an additive or multiplicative scale, such as a ratio or logarithmic scale; and the symmetry - whether dependencies are considered in both directions. Overlooking these properties can lead to one or more of three inferential errors: misinterpretation of (i) the detection and magnitude (Type-D error), and (ii) the sign of effect modification (Type-S error); and (iii) misidentification of the underlying processes (Type-A error). We illustrate each of these errors with a broad range of ecological questions applied to empirical and simulated data sets. We demonstrate how meta-analysis, a widely used approach that seeks explicitly to characterise context dependence, is especially prone to all three errors. Based on these insights, we propose guidelines to improve hypothesis generation, testing, visualisation and interpretation of interactions in ecology.

Perspective: sustainability challenges, opportunities and solutions for long-term ecosystem observations

As interest in natural capital grows and society increasingly recognizes the value of biodiversity, we must discuss how ecosystem observations to detect changes in biodiversity can be sustained through collaboration across regions and sectors. However, there are many barriers to establishing and sustaining large-scale, fine-resolution ecosystem observations. First, comprehensive monitoring data on both biodiversity and possible anthropogenic factors are lacking. Second, some in situ ecosystem observations cannot be systematically established and maintained across locations. Third, equitable solutions across sectors and countries are needed to build a global network. Here, by examining individual cases and emerging frameworks, mainly from (but not limited to) Japan, we illustrate how ecological science relies on long-term data and how neglecting basic monitoring of our home planet further reduces our chances of overcoming the environmental crisis. We also discuss emerging techniques and opportunities, such as environmental DNA and citizen science as well as using the existing and forgotten sites of monitoring, that can help overcome some of the difficulties in establishing and sustaining ecosystem observations at a large scale with fine resolution. Overall, this paper presents a call to action for joint monitoring of biodiversity and anthropogenic factors, the systematic establishment and maintenance of in situ observations, and equitable solutions across sectors and countries to build a global network, beyond cultures, languages, and economic status. We hope that our proposed framework and the examples from Japan can serve as a starting point for further discussions and collaborations among stakeholders across multiple sectors of society. It is time to take the next step in detecting changes in socio-ecological systems, and if monitoring and observation can be made more equitable and feasible, they will play an even more important role in ensuring global sustainability for future generations. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Theory and application of an improved species richness estimator

Species richness is an essential biodiversity variable indicative of ecosystem states and rates of invasion, speciation and extinction both contemporarily and in fossil records. However, limited sampling effort and spatial aggregation of organisms mean that biodiversity surveys rarely observe every species in the survey area. Here we present a non-parametric, asymptotic and bias-minimized richness estimator, Ω by modelling how spatial abundance characteristics affect observation of species richness. Improved asymptotic estimators are critical when both absolute richness and difference detection are important. We conduct simulation tests and applied Ω to a tree census and a seaweed survey. Ω consistently outperforms other estimators in balancing bias, precision and difference detection accuracy. However, small difference detection is poor with any asymptotic estimator. An R-package, Richness, performs the proposed richness estimations along with other asymptotic estimators and bootstrapped precisions. Our results explain how natural and observer-induced variations affect species observation, how these factors can be used to correct observed richness using the estimator Ω on a variety of data, and why further improvements are critical for biodiversity assessments. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Drivers of the changing abundance of European birds at two spatial scales

Detecting biodiversity change and identifying its causes is challenging because biodiversity is multifaceted and temporal data often contain bias. Here, we model temporal change in species' abundance and biomass by using extensive data describing the population sizes and trends of native breeding birds in the United Kingdom (UK) and the European Union (EU). In addition, we explore how species' population trends vary with species' traits. We demonstrate significant change in the bird assemblages of the UK and EU, with substantial reductions in overall bird abundance and losses concentrated in a relatively small number of abundant and smaller sized species. By contrast, rarer and larger birds had generally fared better. Simultaneously, overall avian biomass had increased very slightly in the UK and was stable in the EU, indicating a change in community structure. Abundance trends across species were positively correlated with species' body mass and with trends in climate suitability, and varied with species' abundance, migration strategy and niche associations linked to diet. Our work highlights how changes in biodiversity cannot be captured easily by a single number; care is required when measuring and interpreting biodiversity change given that different metrics can provide very different insights. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Species life-history strategies affect population responses to temperature and land-cover changes

Human-induced environmental changes have a direct impact on species populations, with some species experiencing declines while others display population growth. Understanding why and how species populations respond differently to environmental changes is fundamental to mitigate and predict future biodiversity changes. Theoretically, species life-history strategies are key determinants shaping the response of populations to environmental impacts. Despite this, the association between species life histories and the response of populations to environmental changes has not been tested. In this study, we analysed the effects of recent land-cover and temperature changes on rates of population change of 1,072 populations recorded in the Living Planet Database. We selected populations with at least 5 yearly consecutive records (after imputation of missing population estimates) between 1992 and 2016, and for which we achieved high population imputation accuracy (in the cases where missing values had to be imputed). These populations were distributed across 553 different locations and included 461 terrestrial amniote vertebrate species (273 birds, 137 mammals, and 51 reptiles) with different life-history strategies. We showed that populations of fast-lived species inhabiting areas that have experienced recent expansion of cropland or bare soil present positive populations trends on average, whereas slow-lived species display negative population trends. Although these findings support previous hypotheses that fast-lived species are better adapted to recover their populations after an environmental perturbation, the sensitivity analysis revealed that model outcomes are strongly influenced by the addition or exclusion of populations with extreme rates of change. Therefore, the results should be interpreted with caution. With climate and land-use changes likely to increase in the future, establishing clear links between species characteristics and responses to these threats is fundamental for designing and conducting conservation actions. The results of this study can aid in evaluating population sensitivity, assessing the likely conservation status of species with poor data coverage, and predicting future scenarios of biodiversity change.

Assessing the representation of species included within the Canadian Living Planet Index

To effectively combat the biodiversity crisis, we need ambitious targets and reliable indicators to accurately track trends and measure conservation impact. In Canada, the Living Planet Index (LPI) has been adapted to produce a national indicator by both World Wildlife Fund-Canada (Canadian Living Planet Index; C-LPI) and Environment and Climate Change Canada (Canadian Species Index) to provide insight into the status of Canadian wildlife, by evaluating temporal trends in vertebrate population abundance. The indicator includes data for just over 50% of Canadian vertebrate species. To assess whether the current dataset is representative of the distribution of life history characteristics of Canadian wildlife, we analyzed the representation of species-specific biotic variables (i.e., body size, trophic level, lifespan) for vertebrates within the C-LPI compared to native vertebrates lacking LPI data. Generally, there was considerable overlap in the distribution of biotic variables for species in the C-LPI compared to native Canadian vertebrate species lacking LPI data. Nevertheless, some differences among distributions were found, driven in large part by discrepancy in the representation of fishes—where the C-LPI included larger-bodied and longer-lived species. We provide recommendations for targeted data collection and additional analyses to further strengthen the applicability, accuracy, and representativity of biodiversity indicators.