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Anthropogenic pressures are causing the widespread loss of wildlife species and populations, with adverse consequences for ecosystem functioning. This phenomenon has been widely but inconsistently referred to as defaunation. A cohesive, quantitative framework for defining and evaluating defaunation is necessary for advancing biodiversity conservation. Likening defaunation to deforestation, we propose an operational framework for defaunation that defines it and related terms, situates defaunation relative to intact communities and faunal degradation, and encourages quantitative, ecologically reasonable, and equitable measurements. We distinguish between defaunation, the conversion of an ecosystem from having wild animals to not having wild animals, and faunal degradation, the process of losing animals or species from an animal community. The quantification of context-relevant defaunation boundaries or baselines is necessary to compare faunal communities over space and time. Situating a faunal community on the degradation curve can promote Global Biodiversity Framework targets, advancing the 2050 Vision for Biodiversity.

 

Anthropogenic disturbances are changing the structure and composition of tropical forests worldwide. Multiple disturbances often occur simultaneously in forests: for example, hunting and logging are within-forest disturbances that impact vast areas of seemingly intact rainforests. Despite recent work on the individual effects of these disturbances, our understanding of how they interact to influence tree communities is still limited. In northern Republic of Congo, we explored the effects of hunting and logging on tree communities. Over an 8-year period, we monitored 12,552 tree stems (≥ 10 cm diameter-at-breast height) spread over 30 1-ha plots along a gradient of human disturbance to compare the tree diversity between hunted and logged forest, once-logged forest, and protected forest free of both disturbances. Tree density, species richness, and community composition were affected by both hunting and logging. Forest close to human settlements was richer, more heterogenous, and more dynamic in species composition across censuses. In hunted and logged forest, fast-growing secondary species with low shade tolerance replaced old growth species. Comparatively, the once-logged forest had the greatest stem density and intermediate species richness with an increased density of shade-bearing species over time. Both tree species spatial turnover and tree recruitment were greatly affected by proximity to human settlements. A shift towards abiotically dispersed trees and increasing seed predation by rodents near villages can partly explain the differences in tree recruitment across the forest types. The combination of hunting and logging seems to have a greater impact on tree communities than either single disturbance, especially with nearness to villages. 

By dispersing seeds long distances, large, fruit-eating animals influence plant population spread and community dynamics. After fruit consumption, animal gut passage time and movement determine seed dispersal patterns and distances. These, in turn, are influenced by extrinsic, environmental variables and intrinsic, individual-level variables. We simulated seed dispersal by forest elephants ( Loxodonta cyclotis ) by integrating gut passage data from wild elephants with movement data from 96 individuals. On average, elephants dispersed seeds 5.3 km, with 89% of seeds dispersed farther than 1 km. The longest simulated seed dispersal distance was 101 km, with an average maximum dispersal distance of 40.1 km. Seed dispersal distances varied among national parks, perhaps due to unmeasured environmental differences such as habitat heterogeneity and configuration, but not with human disturbance or habitat openness. On average, male elephants dispersed seeds farther than females. Elephant behavioral traits strongly influenced dispersal distances, with bold, exploratory elephants dispersing seeds 1.1 km farther than shy, idler elephants. Protection of forest elephants, particularly males and highly mobile, exploratory individuals, is critical to maintaining long distance seed dispersal services that shape plant communities and tropical forest habitat. 

Individual motivation for the rural use of common‐pool resources (CPRs) can be fluid, with the line between subsistence and commercial often unclear and in flux.

Implications of fluid motivation are understudied yet important for social–ecological systems (SESs), such as bushmeat hunting throughout Central Africa that is essential to local protein/nutrition, income and culture.

Making locally informative predictions of multiple SESs nested within a landscape‐scale SES has been historically difficult, but community‐driven participatory approaches provide new kinds and quantities of data, opening previously inaccessible doors for research and governance.

We apply hierarchical Bayesian structural equation modelling to a novel dataset of 910 hunts from 111 gun and trap hunters across nine villages in Gabon, generated in a participatory process whereby hunters conducted GPS self‐follows in conjunction with paraecologist surveys of their motivation, behaviour and offtake. We (i) establish the human behaviour driving gun‐hunting and trapping success and predict its effect on offtake across villages and (ii) link fluid motivation of gun hunters to their behaviour, number of animals hunted, biomass yielded and income earned.

Gun hunts across villages yielded more animals during the night than the day, and when hunters brought high amounts of ammunition and walked far distances from villages. Gun hunts were less successful when coupled with trapping while per‐hunt success of trapping itself was generally low and difficult to predict. Fluid gun hunters hunted fewer animals when motivated strictly by subsistence, despite no reduction in ammunition brought or distance walked, while offtake from strictly commercial versus mixed motivation was the same. Numbers of animals hunted, biomass and income were tightly linked. We discuss the implications of these results for the ecological sustainability of hunting and participatory forecasting in bushmeat research and policy.

Read the freePlain Language Summaryfor this article on the Journal blog.

 

Abstract Although dispersal is generally viewed as a crucial determinant for the fitness of any organism, our understanding of its role in the persistence and spread of plant populations remains incomplete. Generalizing and predicting dispersal processes are challenging due to context dependence of seed dispersal, environmental heterogeneity and interdependent processes occurring over multiple spatial and temporal scales. Current population models often use simple phenomenological descriptions of dispersal processes, limiting their ability to examine the role of population persistence and spread, especially under global change. To move seed dispersal ecology forward, we need to evaluate the impact of any single seed dispersal event within the full spatial and temporal context of a plant’s life history and environmental variability that ultimately influences a population’s ability to persist and spread. In this perspective, we provide guidance on integrating empirical and theoretical approaches that account for the context dependency of seed dispersal to improve our ability to generalize and predict the consequences of dispersal, and its anthropogenic alteration, across systems. We synthesize suitable theoretical frameworks for this work and discuss concepts, approaches and available data from diverse subdisciplines to help operationalize concepts, highlight recent breakthroughs across research areas and discuss ongoing challenges and open questions. We address knowledge gaps in the movement ecology of seeds and the integration of dispersal and demography that could benefit from such a synthesis. With an interdisciplinary perspective, we will be able to better understand how global change will impact seed dispersal processes, and potential cascading effects on plant population persistence, spread and biodiversity. 

Despite its importance for forest regeneration, food webs, and human economies, changes in tree fecundity with tree size and age remain largely unknown. The allometric increase with tree diameter assumed in ecological models would substantially overestimate seed contributions from large trees if fecundity eventually declines with size. Current estimates are dominated by overrepresentation of small trees in regression models. We combined global fecundity data, including a substantial representation of large trees. We compared size–fecundity relationships against traditional allometric scaling with diameter and two models based on crown architecture. All allometric models fail to describe the declining rate of increase in fecundity with diameter found for 80% of 597 species in our analysis. The strong evidence of declining fecundity, beyond what can be explained by crown architectural change, is consistent with physiological decline. A downward revision of projected fecundity of large trees can improve the next generation of forest dynamic models.

 

Accurate estimations of animal populations are necessary for management, conservation, and policy decisions. However, methods for surveying animal communities disproportionately represent specific groups or guilds. For example, transect surveys can provide robust data for large arboreal species but underestimate cryptic or small‐bodied terrestrial species, whereas camera traps have the inverse tendency. The integration of information from multiple methodologies would provide the most complete inference on population size or responses to putative covariates, yet a simple, robust framework that allows integration and comparison of multiple data sources has been lacking. We use 27,813 counts of 35 species or species groups derived from concurrent visual transects, dung transects, and camera trap surveys in tropical forests and compare them within a generalized joint attribute modeling framework (GJAM) that both compares and integrates field‐collected dung, visual, and camera trap data to quantify the species‐ and trait‐specific differences in detection for each method. The effectiveness of survey method was strongly dependent on species, as well as animal traits. These differences in effectiveness contributed to meaningful differences in the reported strength of a known important covariate for animal communities (distance to nearest village). Data fusion through GJAM allows clear and unambiguous comparisons of the counts provided from each different methodology, the incorporation of trait information, and fusion of all three data streams to generate a more complete estimate of the effects of an anthropogenic disturbance covariate. Research and conservation resources are extremely limited, which often means that field campaigns attempt to maximize the amount of information gathered especially in remote, hard‐to‐access areas. Advances in these understudied areas will be accelerated by analytical methods that can fully leverage the total body of diverse biodiversity field data, even when they are collected using different methods. We demonstrate that survey methods vary in their effectiveness for counting species based on biological traits, but more importantly that generative models like GJAM can integrate data from multiple sources in one cohesive statistical framework to make improved inference in understudied environments.

 

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.