Bryan Finegan

Pattern and process in neotropical secondary rain forests: the first 100 years of succession

More and more areas of deforested wet tropical lands are being handed back to nature as their erstwhile owners abandon attempts to farm them. The resulting secondary successions offer hope that some of the unique characteristics of the original rain forests may be recovered and conserved. However, most of our understanding of what secondary tropical rain forests are and how and why they develop is limited to the first decade of a process that may last for centuries. A longer-term view indicates that the causes of change in neotropical secondary successions are similar to those operating in temperate forests, but yields sobering conclusions for conservation.

Rates of change in tree communities of secondary Neotropical forests following major disturbances

Rates of change in tree communities following major disturbances are determined by a complex set of interactions between local site factors, landscape history and structure, regional species pools and species life histories. Our analysis focuses on vegetation change following abandonment of agricultural fields or pastures, as this is the most extensive form of major disturbance in Neotropical forests. We consider five tree community attributes: stem density, basal area, species density, species richness and species composition. We describe two case studies, in northeastern Costa Rica and Chiapas, Mexico, where both chronosequence and annual tree dynamics studies are being applied. These case studies show that the rates of change in tree communities often deviate from chronosequence trends. With respect to tree species composition, sites of different ages differ more than a single site followed over time through the same age range. Dynamic changes in basal area within stands, on the other hand, generally followed chronosequence trends. Basal area accumulation was more linked with tree growth rates than with net changes in tree density due to recruitment and mortality. Stem turnover rates were poor predictors of species turnover rates, particularly at longer time-intervals. Effects of the surrounding landscape on tree community dynamics within individual plots are poorly understood, but are likely to be important determinants of species accumulation rates and relative abundance patterns.

Integrating agricultural landscapes with biodiversity conservation in the Mesoamerican hotspot.

CELIA A. HARVEY,∗‡‡‡ OLIVER KOMAR,† ROBIN CHAZDON,‡ BRUCE G. FERGUSON,§ BRYAN FINEGAN,∗∗ DANIEL M. GRIFFITH,†† MIGUEL MARTINEZ-RAMOS,‡‡ HELDA MORALES,§ RONALD NIGH,§§ LORENA SOTO-PINTO,§ MICHIEL VAN BREUGEL,∗∗∗ AND MARK WISHNIE††† ∗Department of Agriculture and Agroforestry, CATIE, Apdo 7170, Turrialba, Costa Rica †Programa de Ciencias para la Conservacion, SalvaNATURA, Colonia Flor Blanca, 33 Avenida Sur #640, San Salvador, El Salvador ‡Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT 06268-3043, U.S.A. §Departamento de Agroecoloǵia, El Colegio de la Frontera Sur, Carretera Panamericana y Periferico Sur s-n, San Cristobal de Las Casas, Chiapas, Mexico ∗∗Department of Natural Resources and Environment, CATIE, Apdo 7170, Turrialba, Costa Rica ††Biodiversity of BOSAWAS Biosphere Reserve, Saint Louis Zoo, Managua, Nicaragua ‡‡Centro de Investigaciones en Ecosistemas, UNAM, AP 27-3 Santa Maŕia de Guido, CP 58089, Morelia, Michoacan, Mexico §§Centro de Investigaciones y Estudios Superiores en Antropoloǵia Social, San Cristobal de las Casas, Chiapas, Mexico ∗∗∗Centre for Ecosystem Studies, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands †††Equator Environmental, LLC, 250 Park Avenue South, New York, NY 10003, U.S.A.

Linking functional diversity and social actor strategies in a framework for interdisciplinary analysis of nature's benefits to society

The crucial role of biodiversity in the links between ecosystems and societies has been repeatedly highlighted both as source of wellbeing and as a target of human actions, but not all aspects of biodiversity are equally important to different ecosystem services. Similarly, different social actors have different perceptions of and access to ecosystem services, and therefore, they have different wants and capacities to select directly or indirectly for particular biodiversity and ecosystem characteristics. Their choices feed back onto the ecosystem services provided to all parties involved and in turn, affect future decisions. Despite this recognition, the research communities addressing biodiversity, ecosystem services, and human outcomes have yet to develop frameworks that adequately treat the multiple dimensions and interactions in the relationship. Here, we present an interdisciplinary framework for the analysis of relationships between functional diversity, ecosystem services, and human actions that is applicable to specific social environmental systems at local scales. We connect the mechanistic understanding of the ecological role of diversity with its social relevance: ecosystem services. The framework permits connections between functional diversity components and priorities of social actors using land use decisions and ecosystem services as the main links between these ecological and social components. We propose a matrix-based method that provides a transparent and flexible platform for quantifying and integrating social and ecological information and negotiating potentially conflicting land uses among multiple social actors. We illustrate the applicability of our framework by way of land use examples from temperate to subtropical South America, an area of rapid social and ecological change.

The management potential of neotropical secondary lowland rain forest

Abstract The management potential of neotropical secondary lowland rain forests is reviewed in the light of the increasing land area occupied by them and the continuing destruction of primary forests. The ecological group of long-lived intolerant trees, or big pioneers, is shown to consist almost exclusively of commercial or utilizable trees which are abundant and fast-growing in secondary rain forests throughout the neotropics. The timbers are relatively light and lack natural durability but these factors do not constitute problems for utilization. The Trinidad Shelterwood System is analysed, demonstrating the technical and economic feasibility of secondary forest management in situations in which markets accept timbers of long-lived intolerant species. It is concluded that while the biological management potential of secondary forests is general in the neotropics, favourable market conditions are not, but the growing demand for and shrinking supply of forest products should change this in the future. A population-based model of secondary succession is used as the framework for a simple preliminary sequence of silvicultural treatments, based upon a monocyclic approach. The ecological sustainability of secondary forest management is considered to depend on the maintenance of ecosystem function which, on poor soils, may be broken down by the relatively intensive interventions of a monocyclic system. This is by no means certain, however, and research is needed. Secondary forests usually constitute habitat islands and this must be taken into account in their management, especially with respect to natural regeneration from seed. The relatively high productivity of secondary forests and their potential for management through simple operations, in combination with certain crops if desired, are considered to suit them for incorporation into small and medium farm production systems.

Successional dynamics in Neotropical forests are as uncertain as they are predictable

Significance Although forest succession has been approached as a predictable process, successional trajectories vary widely, even among nearby stands with similar environmental conditions and disturbance histories. We quantified predictability and uncertainty during tropical forest succession using dynamical models describing the interactions among stem density, basal area, and species density over time. We showed that the trajectories of these forest attributes were poorly predicted by stand age and varied significantly within and among sites. Our models reproduced the general successional trends observed, but high levels of noise were needed to increase model predictability. These levels of uncertainty call into question the premise that successional processes are consistent over space and time, and challenge the way ecologists view tropical forest regeneration. Although forest succession has traditionally been approached as a deterministic process, successional trajectories of vegetation change vary widely, even among nearby stands with similar environmental conditions and disturbance histories. Here, we provide the first attempt, to our knowledge, to quantify predictability and uncertainty during succession based on the most extensive long-term datasets ever assembled for Neotropical forests. We develop a novel approach that integrates deterministic and stochastic components into different candidate models describing the dynamical interactions among three widely used and interrelated forest attributes—stem density, basal area, and species density. Within each of the seven study sites, successional trajectories were highly idiosyncratic, even when controlling for prior land use, environment, and initial conditions in these attributes. Plot factors were far more important than stand age in explaining successional trajectories. For each site, the best-fit model was able to capture the complete set of time series in certain attributes only when both the deterministic and stochastic components were set to similar magnitudes. Surprisingly, predictability of stem density, basal area, and species density did not show consistent trends across attributes, study sites, or land use history, and was independent of plot size and time series length. The model developed here represents the best approach, to date, for characterizing autogenic successional dynamics and demonstrates the low predictability of successional trajectories. These high levels of uncertainty suggest that the impacts of allogenic factors on rates of change during tropical forest succession are far more pervasive than previously thought, challenging the way ecologists view and investigate forest regeneration.

A novel statistical method for classifying habitat generalists and specialists

We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, our method minimizes bias due to differences in sampling intensities between two habitat types as well as bias due to insufficient sampling within each habitat. The method permits a robust statistical classification of habitat specialists and generalists, without excluding rare species a priori. Based on a user-defined specialization threshold, the model classifies species into one of four groups: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest class (40.6%), followed by generalist tree species (36.7%) and SG specialists (22.7%). The multinomial model was more sensitive than indicator value analysis or abundance-based phi coefficient indices in detecting habitat specialists and also detects generalists statistically. Classification of specialists and generalists based on rarefied subsamples was highly consistent with classification based on the full sample, even for sampling percentages as low as 20%. Major advantages of the new method are (1) its ability to distinguish habitat generalists (species with no significant habitat affinity) from species that are simply too rare to classify and (2) applicability to a single representative sample or a single pooled set of representative samples from each of two habitat types. The method as currently developed can be applied to no more than two habitats at a time.

Consequences of Environmental Service Payments for Forest Retention and Recruitment in a Costa Rican Biological Corridor

Compensation to landowners for forest-derived environmental services has gained international recognition as a mechanism to combat forest loss and fragmentation. This approach is widely promoted, although there is little evidence demonstrating that environmental service payments encourage forest stewardship and conservation. Costa Rica provides a unique case study in which a 1996 Forestry Law initiated environmental service payments and prohibited forest conversion to other land uses. We examined these novel policies to determine their influence on landowner decisions that affect forest change, carbon services, and connectivity in a 2425 km² biological corridor. We used Landsat images to compare land-cover changes before and after 1996, and linked these data to landowner surveys investigating land-use decisions. Carbon stocks and storage in secondary forests were also examined. Forest change observations were corroborated by landowner survey data, indicating that the 1996 Forestry Law and environmental service payments contributed positively to forest retention and recruitment. Socioeconomic conditions also favored forest protection. Rates of natural forest loss declined from -1.43% to -0.10%/yr after 1996. Forest cover and connectivity were maintained through tree plantations and secondary forest recruitment, although forest heterogeneity increased as these forest types sometimes replaced natural forest. Carbon storage in secondary forest approached levels in primary forest after 25-30 yr of succession, although few landowners retained natural regeneration. Secondary forests will persist as minor landscape components without legal or financial incentives. The Costa Rican experience provides evidence that environmental service payments can be effective in retaining natural forest and recruiting tree cover within biological corridors.

Does functional trait diversity predict above-ground biomass and productivity of tropical forests? Testing three alternative hypotheses

Summary 1. Tropical forests are globally important, but it is not clear whether biodiversity enhances carbon storage and sequestration in them. We tested this relationship focusing on components of functional trait biodiversity as predictors. 2. Data are presented for three rain forests in Bolivia, Brazil and Costa Rica. Initial above-ground biomass and biomass increments of survivors, recruits and survivors + recruits (total) were estimated for trees ≥10 cm d.b.h. in 62 and 21 1.0-ha plots, respectively. We determined relationships of biomass increments to initial standing biomass (AGBi), biomass-weighted community mean values (CWM) of eight functional traits and four functional trait variety indices (functional richness, functional evenness, functional diversity and functional dispersion). 3. The forest continuum sampled ranged from ‘slow’ stands dominated by trees with tough tissues and high AGBi ,t o‘fast’ stands dominated by trees with soft, nutrient-rich leaves, lighter woods and lower AGBi. 4. We tested whether AGBi and biomass increments were related to the CWM trait values of the dominant species in the system (the biomass ratio hypothesis), to the variety of functional trait values (the niche complementarity hypothesis), or in the case of biomass increments, simply to initial standing biomass (the green soup hypothesis). 5. CWMs were reasonable bivariate predictors of AGBi and biomass increments, with CWM specific leaf area SLA, CWM leaf nitrogen content, CWM force to tear the leaf, CWM maximum adult height Hmax and CWM wood specific gravity the most important. AGBi was also a reasonable predictor of the three measures of biomass increment. In best-fit multiple regression models, CWM Hmax was the most important predictor of initial standing biomass AGBi. Only leaf traits were selected in the best models for biomass increment; CWM SLA was the most important predictor, with the expected positive relationship. There were no relationships of functional variety indices to biomass increments, and AGBi was the only predictor for biomass increments from recruits. 6. Synthesis. We found no support for the niche complementarity hypothesis and support for the green soup hypothesis only for biomass increments of recruits. We have strong support for the biomass ratio hypothesis. CWM Hmax is a strong driver of ecosystem biomass and carbon storage and CWM SLA, and other CWM leaf traits are especially important for biomass increments and carbon sequestration.

The multispectral separability of Costa Rican rainforest types with support vector machines and Random Forest decision trees

Estimating the extent of tropical rainforest types is needed for biodiversity assessment and carbon accounting. In this study, we used statistical comparisons to determine the ability of Landsat Thematic Mapper (TM) bands and spectral vegetation indices to discriminate composition and structural types. A total of 144 old-growth forest plots established in northern Costa Rica were categorized via cluster analysis and ordination. Locations for palm swamps, forest regrowth and tree plantations were also acquired, making 11 forest types for separability analysis. Forest types classified using support vector machines (SVM), a theoretically superior method for solving complex classification problems, were compared with the random forest decision tree classifier (RF). Separability comparisons demonstrate that spectral data are sensitive to differences among forest types when tree species and structural similarity is low. SVM class accuracy was 66.6% for all forest types, minimally higher than the RF classifier (65.3%). TM bands and the Normalized Difference Vegetation Index (NDVI) combined with digital elevation data notably increased accuracies for SVM (84.3%) and RF (86.7%) classifiers. Rainforest types discriminated here are typically limited to one or two categories for remote sensing classifications. Our results indicate that TM bands and ancillary data combined via machine learning algorithms can yield accurate and ecologically meaningful rainforest classifications important to national and international forest monitoring protocols.