Robert J. Holdaway

Scientific Foundations for an IUCN Red List of Ecosystems

An understanding of risks to biodiversity is needed for planning action to slow current rates of decline and secure ecosystem services for future human use. Although the IUCN Red List criteria provide an effective assessment protocol for species, a standard global assessment of risks to higher levels of biodiversity is currently limited. In 2008, IUCN initiated development of risk assessment criteria to support a global Red List of ecosystems. We present a new conceptual model for ecosystem risk assessment founded on a synthesis of relevant ecological theories. To support the model, we review key elements of ecosystem definition and introduce the concept of ecosystem collapse, an analogue of species extinction. The model identifies four distributional and functional symptoms of ecosystem risk as a basis for assessment criteria: A) rates of decline in ecosystem distribution; B) restricted distributions with continuing declines or threats; C) rates of environmental (abiotic) degradation; and D) rates of disruption to biotic processes. A fifth criterion, E) quantitative estimates of the risk of ecosystem collapse, enables integrated assessment of multiple processes and provides a conceptual anchor for the other criteria. We present the theoretical rationale for the construction and interpretation of each criterion. The assessment protocol and threat categories mirror those of the IUCN Red List of species. A trial of the protocol on terrestrial, subterranean, freshwater and marine ecosystems from around the world shows that its concepts are workable and its outcomes are robust, that required data are available, and that results are consistent with assessments carried out by local experts and authorities. The new protocol provides a consistent, practical and theoretically grounded framework for establishing a systematic Red List of the world’s ecosystems. This will complement the Red List of species and strengthen global capacity to report on and monitor the status of biodiversity

Allometric equations for integrating remote sensing imagery into forest monitoring programmes

Abstract Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able – for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed – specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the worlds forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large‐scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.

BAAD: a biomass and allometry database for woody plants

Understanding how plants are constructed—i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals—is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among species adapted to different environments. While a variety of models dealing with biomass allocation exist, we lack a synthetic understanding of the underlying processes. This is partly due to the lack of suitable data sets for validating and parameterizing models. To that end, we present the Biomass And Allometry Database (BAAD) for woody plants. The BAAD contains 259 634 measurements collected in 176 different studies, from 21 084 individuals across 678 species. Most of these data come from existing publications. However, raw data were rarely made public at the time of publication. Thus, the BAAD contains data from different studies, transformed into standard units and variable names. The transformations were achieved using a common workflow for all raw data files. Other features that distinguish the BAAD are: (i) measurements were for individual plants rather than stand averages; (ii) individuals spanning a range of sizes were measured; (iii) plants from 0.01–100 m in height were included; and (iv) biomass was estimated directly, i.e., not indirectly via allometric equations (except in very large trees where biomass was estimated from detailed sub-sampling). We included both wild and artificially grown plants. The data set contains the following size metrics: total leaf area; area of stem cross-section including sapwood, heartwood, and bark; height of plant and crown base, crown area, and surface area; and the dry mass of leaf, stem, branches, sapwood, heartwood, bark, coarse roots, and fine root tissues. We also report other properties of individuals (age, leaf size, leaf mass per area, wood density, nitrogen content of leaves and wood), as well as information about the growing environment (location, light, experimental treatment, vegetation type) where available. It is our hope that making these data available will improve our ability to understand plant growth, ecosystem dynamics, and carbon cycling in the worlds vegetation.

Climate, soil and plant functional types as drivers of global fine‐root trait variation

Summary Ecosystem functioning relies heavily on below-ground processes, which are largely regulated by plant fine-roots and their functional traits. However, our knowledge of fine-root trait distribution relies to date on local- and regional-scale studies with limited numbers of species, growth forms and environmental variation. We compiled a world-wide fine-root trait dataset, featuring 1115 species from contrasting climatic areas, phylogeny and growth forms to test a series of hypotheses pertaining to the influence of plant functional types, soil and climate variables, and the degree of manipulation of plant growing conditions on species fine-root trait variation. Most particularly, we tested the competing hypotheses that fine-root traits typical of faster return on investment would be most strongly associated with conditions of limiting versus favourable soil resource availability. We accounted for both data source and species phylogenetic relatedness. We demonstrate that: (i) Climate conditions promoting soil fertility relate negatively to fine-root traits favouring fast soil resource acquisition, with a particularly strong positive effect of temperature on fine-root diameter and negative effect on specific root length (SRL), and a negative effect of rainfall on root nitrogen concentration; (ii) Soil bulk density strongly influences species fine-root morphology, by favouring thicker, denser fine-roots; (iii) Fine-roots from herbaceous species are on average finer and have higher SRL than those of woody species, and N2-fixing capacity positively relates to root nitrogen; and (iv) Plants growing in pots have higher SRL than those grown in the field. Synthesis. This study reveals both the large variation in fine-root traits encountered globally and the relevance of several key plant functional types and soil and climate variables for explaining a substantial part of this variation. Climate, particularly temperature, and plant functional types were the two strongest predictors of fine-root trait variation. High trait variation occurred at local scales, suggesting that wide-ranging below-ground resource economics strategies are viable within most climatic areas and soil conditions.

Trends in entropy production during ecosystem development in the Amazon Basin

Understanding successional trends in energy and matter exchange across the ecosystem–atmosphere boundary layer is an essential focus in ecological research; however, a general theory describing the observed pattern remains elusive. This paper examines whether the principle of maximum entropy production could provide the solution. A general framework is developed for calculating entropy production using data from terrestrial eddy covariance and micrometeorological studies. We apply this framework to data from eight tropical forest and pasture flux sites in the Amazon Basin and show that forest sites had consistently higher entropy production rates than pasture sites (0.461 versus 0.422 W m−2 K−1, respectively). It is suggested that during development, changes in canopy structure minimize surface albedo, and development of deeper root systems optimizes access to soil water and thus potential transpiration, resulting in lower surface temperatures and increased entropy production. We discuss our results in the context of a theoretical model of entropy production versus ecosystem developmental stage. We conclude that, although further work is required, entropy production could potentially provide a much-needed theoretical basis for understanding the effects of deforestation and land-use change on the land-surface energy balance.

Long-term hurricane damage effects on tropical forest tree growth and mortality

Hurricane winds can have large impacts on forest structure and dynamics. To date, most evaluations of hurricane impacts have focused on short-term responses after a hurricane, often lacked pre-hurricane measurements, and missed responses occurring over longer time scales. Here, we use a long-term data set (1974–2009, 35 years) of tree stems (>3 cm in diameter at 1.3 m aboveground) in four sites (0.35 ha in total) in montane rain forest (∼1600 m elevation) in Jamaica to investigate the patterns of crown damage in individual stems by Hurricane Gilbert in 1988, and how subsequent growth and mortality were affected by hurricane damage, sprouting, and the incidence of multiple stems. Topographical position on a mountain ridge was the best predictor of crown damage, followed by crown size and species identity. The average diameter growth rate of stems that survived the hurricane was greater than that pre-hurricane for the whole 21-yr post-hurricane period. Growth rates of stems with damaged crowns increased les...

Status assessment of New Zealand's naturally uncommon ecosystems.

Globally, ecosystems are under increasing anthropogenic pressure; thus, many are at risk of elimination. This situation has led the International Union for Conservation of Nature (IUCN) to propose a quantitative approach to ecosystem-risk assessment. However, there is a need for their proposed criteria to be evaluated through practical examples spanning a diverse range of ecosystems and scales. We applied the IUCNs ecosystem red-list criteria, which are based on changes in extent of ecosystems and reductions in ecosystem processes, to New Zealands 72 naturally uncommon ecosystems. We aimed to test the applicability of the proposed criteria to ecosystems that are naturally uncommon (i.e., those that would naturally occur over a small area in the absence of human activity) and to provide information on the probability of ecosystem elimination so that conservation priorities might be set. We also tested the hypothesis that naturally uncommon ecosystems classified as threatened on the basis of IUCN Red List criteria contain more threatened plant species than those classified as nonthreatened. We identified 18 critically endangered, 17 endangered, and 10 vulnerable ecosystems. We estimated that naturally uncommon ecosystems contained 145 (85%) of mainland New Zealands taxonomically distinct nationally critical, nationally endangered, and nationally vulnerable plant species, 66 (46%) of which were endemic to naturally uncommon ecosystems. We estimated there was a greater number of threatened plant species (per unit area) in critically endangered ecosystems than in ecosystems classified as nonthreatened. With their high levels of endemism and rapid and relatively well-documented history of anthropogenic change, New Zealands naturally uncommon ecosystems provide an excellent case-study for the ongoing development of international criteria for threatened ecosystems. We suggest that interactions and synergies among decline in area, decline in function, and the scale of application of the criteria be used to improve the IUCN criteria for threatened ecosystems.

Functional Traits Reveal Processes Driving Natural Afforestation at Large Spatial Scales

An understanding of the processes governing natural afforestation over large spatial scales is vital for enhancing forest carbon sequestration. Models of tree species occurrence probability in non-forest vegetation could potentially identify the primary variables determining natural afforestation. However, inferring processes governing afforestation using tree species occurrence is potentially problematic, since it is impossible to know whether observed occurrences are due to recruitment or persistence of existing trees following disturbance. Plant functional traits have the potential to reveal the processes by which key environmental and land cover variables influence afforestation. We used 10,061 survey plots to identify the primary environmental and land cover variables influencing tree occurrence probability in non-forest vegetation in New Zealand. We also examined how these variables influenced diversity of functional traits linked to plant ecological strategy and dispersal ability. Mean annual temperature was the most important environmental predictor of tree occurrence. Local woody cover and distance to forest were the most important land cover variables. Relationships between these variables and ecological strategy traits revealed a trade-off between ability to compete for light and colonize sites that were marginal for tree occurrence. Biotically dispersed species occurred less frequently with declining temperature and local woody cover, suggesting that abiotic stress limited their establishment and that biotic dispersal did not increase ability to colonize non-woody vegetation. Functional diversity for ecological strategy traits declined with declining temperature and woody cover and increasing distance to forest. Functional diversity for dispersal traits showed the opposite trend. This suggests that low temperatures and woody cover and high distance to forest may limit tree species establishment through filtering on ecological strategy traits, but not on dispersal traits. This study shows that ‘snapshot’ survey plot data, combined with functional trait data, may reveal the processes driving tree species establishment in non-forest vegetation over large spatial scales.

Towards robust and repeatable sampling methods in eDNA-based studies

DNA‐based techniques are increasingly used for measuring the biodiversity (species presence, identity, abundance and community composition) of terrestrial and aquatic ecosystems. While there are numerous reviews of molecular methods and bioinformatic steps, there has been little consideration of the methods used to collect samples upon which these later steps are based. This represents a critical knowledge gap, as methodologically sound field sampling is the foundation for subsequent analyses. We reviewed field sampling methods used for metabarcoding studies of both terrestrial and freshwater ecosystem biodiversity over a nearly three‐year period (n = 75). We found that 95% (n = 71) of these studies used subjective sampling methods and inappropriate field methods and/or failed to provide critical methodological information. It would be possible for researchers to replicate only 5% of the metabarcoding studies in our sample, a poorer level of reproducibility than for ecological studies in general. Our findings suggest greater attention to field sampling methods, and reporting is necessary in eDNA‐based studies of biodiversity to ensure robust outcomes and future reproducibility. Methods must be fully and accurately reported, and protocols developed that minimize subjectivity. Standardization of sampling protocols would be one way to help to improve reproducibility and have additional benefits in allowing compilation and comparison of data from across studies.