Kurt McLaren

Plant diversity patterns in neotropical dry forests and their conservation implications

Seasonally dry tropical forests are distributed across Latin America and the Caribbean and are highly threatened, with less than 10% of their original extent remaining in many countries. Using 835 inventories covering 4660 species of woody plants, we show marked floristic turnover among inventories and regions, which may be higher than in other neotropical biomes, such as savanna. Such high floristic turnover indicates that numerous conservation areas across many countries will be needed to protect the full diversity of tropical dry forests. Our results provide a scientific framework within which national decision-makers can contextualize the floristic significance of their dry forest at a regional and continental scale.

Plant Species Discrimination in a Tropical Wetland Using In Situ Hyperspectral Data

We investigated the use of full-range (400–2,500 nm) hyperspectral data obtained by sampling foliar reflectances to discriminate 46 plant species in a tropical wetland in Jamaica. A total of 47 spectral variables, including derivative spectra, spectral vegetation indices, spectral position variables, normalized spectra and spectral absorption features, were used for classifying the 46 species. The Mann–Whitney U-test, paired one-way ANOVA, principal component analysis (PCA), random forest (RF) and a wrapper approach with a support vector machine were used as feature selection methods. Linear discriminant analysis (LDA), an artificial neural network (ANN) and a generalized linear model fitted with elastic net penalties (GLMnet) were then used for species separation. For comparison, the RF classifier (denoted as RFa) was also used to separate the species by using all reflectance spectra and spectral indices, respectively, without applying any feature selection. The RFa classifier was able to achieve 91.8% and 84.8% accuracy with importance-ranked spectral indices and reflectance spectra, respectively. The GLMnet classifier produced the lowest overall accuracies for feature-selected reflectance spectra data (52–77%) when compared with the LDA and ANN methods. However, when feature-selected spectral indices were used, the GLMnet produced overall accuracies ranging from 79 to 88%, which were the highest among the three classifiers that used feature-selected data. A total of 12 species recorded a 100% producer accuracy, but with spectral indices, and an additional 8 species had perfect producer accuracies, regardless of the input features. The results of this study suggest that the GLMnet classifier can be used, particularly on feature-selected spectral indices, to discern vegetation in wetlands. However, it might be more efficient to use RFa without feature-selected variables, especially for spectral indices.

Comparing the effects of classification techniques on landscape-level assessments: pixel-based versus object-based classification

Landscape-level assessments, particularly the quantification of forest fragmentation, often involve calculating landscape metrics from classified remotely sensed images. The utility of these derived metrics is often assumed to be dependent on the quality of the classified images. We compared conventional, pixel-based classification and a newer method of object-based classification to determine the effects of these two methods on fragmentation analysis of Cockpit Country, Jamaica, West Indies. Both methods showed similar trends in fragmentation metrics; however, there were significant differences between the methods for the metrics that quantified landscape configuration. The object-based classification allowed for the easy inclusion of roads into the analysis, which produced more accurate maps that showed a significant difference in the size of the largest forest patch. The object-based method also allowed classification of forests to show the location and extent of core forest areas; we were therefore able to identify an area of core forest that had remained consistent over the study period as a significant area for conservation focus. We recommend that the object-based method be the method chosen for landscape analyses, particularly forest-fragmentation studies.

Coppice shoot dynamics in a tropical dry forest after human disturbance.

Coppicing is an important regeneration mechanism in tropical dry forest after disturbance, but little is known about the long-term dynamics and the rate of recovery of the coppice shoots following clearance. This study reports on the growth and dynamics of coppice shoots following experimental cutting in a tropical dry forest in Jamaica. The fate of coppice shoots was tracked on a total of 481 stumps, representing 51 species over 10 y. The number of coppice shoots and the height and dbh of the leading shoots were measured on the tree stumps 14 mo and 10 y after cutting. Coppicing was vigorous for most tree species, but the average number of shoots per stump decreased significantly over the 9 y period, from 25 to 8 shoots per stump. The average height and diameter of the leading shoots after 10 y were 4.5 m and 3.8 cm, respectively, and the average percentage diameter recovered by the shoots varied between 36% and 95% among the species. Coppicing facilitates the long-term persistence of this dry forest, and the rapid growth of coppice shoots contributed to the resilience of most species after cutting.

Use of object-oriented classification and fragmentation analysis (1985–2008) to identify important areas for conservation in Cockpit Country, Jamaica

Forest fragmentation is one of the most important threats to global biodiversity, particularly in tropical developing countries. Identifying priority areas for conservation within these forests is essential to their effective management. However, this requires current, accurate environmental information that is often lacking in developing countries. The Cockpit Country, Jamaica, contains forests of international importance in terms of levels of endemism and overall diversity. These forests are under severe threat from the prospect of bauxite mining and other anthropogenic disturbances. In the absence of adequate, up-to-date ecological information, we used satellite remote sensing data and fragmentation analysis to identify interior forested areas that have experienced little or no change as priority conservation sites. We classified Landsat images from 1985, 1989, 1995, 2002, and 2008, using an object-oriented method, which allowed for the inclusion of roads. We conducted our fragmentation analysis using metrics to quantify changes in forest patch number, area, shape, and aggregation. Deforestation and fragmentation fluctuated within the 23-year period but were mostly confined to the periphery of the forest, close to roads and access trails. An area of core forest that remained intact over the period of study was identified within the largest forest patch, most of which was located within the boundaries of a forest reserve and included the last remaining patches of closed-broadleaf forest. These areas should be given highest priority for conservation, as they constitute important refuges for endemic or threatened biodiversity. Minimizing and controlling access will be important in maintaining this core.

The effects of a hurricane on seedling dynamics and abiotic interactions in a tropical lower montane wet forest

We assessed seedling dynamics and understorey light before and after a hurricane in five randomly selected 5 × 5-m subplots, within 30 permanent sample plots covering a total area of 3750 m2 in a lower montane wet tropical forest, Jamaica over a period of 3 y. Understorey light increased (≈ 60%) following the passage of Hurricane Dean in 2007 but decreased in 2009. Overall, seedling density was positively related to light and survivorship was positively related to both light and density. Mortality was significantly lower and most species recorded their highest growth when the canopy was open (2007–2008). However, lower diversity during this period coincided with higher (average) mortality of uncommon species. The hurricane altered the relative importance of interactions between light, seedling density and dynamics. Consequently, interactions were significant before or 2 y after but not 1 y after the hurricane and their significance varied among the years and species. Periodic changes in the importance of these interactions and the effects of the hurricane were used to separate 12 common species along a continuum of responses, which ranged from positive (lower mortality), neutral to negative (lower growth). Our results indicate that hurricanes have positive and negative effects on seedling dynamics; therefore an increase in the intensity and frequency of hurricanes will likely alter seedling composition, and hence forest structure.

The Ecophysiology of xylem hydraulic constraints by "basal" vessels in Canella winterana (Canellaceae)

Early angiosperms are hypothesized as constrained to wet environments where many of their defining characteristics evolved. A functional capability potentially enforcing the wet habitation of early angiosperms was possession of xylem with low hydraulic capability and drought intolerance. Recent studies indicate that a structural hallmark of these performances is long, steeply angled scalariform perforation plates in extant basal angiosperms. However, Canella winterana (Canellaceae), a magnoliid, appears to have radiated into much drier tropical dry forest habitats despite possessing a wood vasculature structurally similar to hypothesized ancestral wet-adapted system for angiosperms as a whole. Based on a field study of Canella wood hydraulic function, we present ecophysiological data that basal vessels do not necessarily mark low resistance to drought. We found that Canella wood was resistant to drought-induced cavitation. Leaf hydraulic capacity as well as leaf pressure-volume relations and leaf water potential minima found for Canella were comparable to some of the most drought-tolerant tropical dry forest angiosperms. Thus, our results suggest that vessels of an ancestral design can be exported to dry environments. We found that scalariform-plated vessels in Canella were associated with low hydraulic capacities at the xylem and whole shoot-scales as well as limited plasticity of the xylem to varying hydrodynamic demand. Consequently, our results support the hypothesis that evolution of simple perforation plates, not vessels per se, represented a critical adaptation for producing large hydraulic gains during angiosperm evolution across a broader range of environments.

Substrate mapping of three rivers in a Ramsar wetland in Jamaica: a comparison of data collection (hydroacoustic v. grab samples), classification and kriging methods

Most developing countries have failed to adopt hydroacoustics to aid with the management of their aquatic natural resources. We tested the ability of single-beam sonar (SBES) to discern and map substrates in three rivers from the largest wetland in Jamaica, the Black River Lower Morass (BRLM). We used five supervised classification methods (including C5.0; random forest, RF; and naive Bayes, NB) and four interpolation algorithms (indicator kriging (iks), fixed path simulation (fpth), random path simulations (rpth) and multinomial categorical simulation (mcs) based on transitional rates and incorporated into Markov Chain). Irrespective of the classifier used, mcs consistently produced higher overall classification accuracies (OAC) and kappa statistics; however, rpth interpolation produced the lowest balanced error rate (BER) recorded. For all three rivers, OAC, kappa and BER statistics were 49.7–87.1, 32.8–81.0 and 15.3–45.1% respectively. All interpolation algorithms produced maps with higher OAC and kappa indices from data classified using the tree-based classifiers (C5.0 and RF) in the absence of gravel-free substrates. At a lower spatial resolution, comparable maps were obtained by interpolating discrete sample points acquired by grab samples. Given that most of rivers in island states are small, sinuous, shallow and sometimes non-navigable by boat, the use of SBES as the most cost-effective and efficient way of mapping river substrates is questionable, but the interpolation of grab samples might suffice.

Mapping shallow nearshore benthic features in a Caribbean marine-protected area: assessing the efficacy of using different data types (hydroacoustic versus satellite images) and classification techniques

ABSTRACT Various benthic mapping methods exist but financing and technical capacity limit the choice of technology available to developing states to aid with natural resource management. Therefore, we assessed the efficacy of using a single-beam echosounder (SBES), satellite images (GeoEye-1 and WorldView-2) and different image (pixel-based Maximum Likelihood Classifier (MLC), and an object-based image analysis (OBIA)) and hydroacoustic classification and interpolation techniques, to map nearshore benthic features at the Bluefields Bay marine protected area in western Jamaica (13.82 km2 in size). A map with three benthic classes (submerged aquatic vegetation (SAV), bare substrate, and coral reef) produced from a radiometrically corrected, deglinted and water column-corrected WorldView-2 image had a marginally higher accuracy (3%) than that of a map classified from a similarly corrected GeoEye-1 image. However, only one of the two extra WorldView-2 image bands (coastal) was used because the yellow band was completely attenuated at depths ≥3.7 m. The coral reef class was completely misclassified by the MLC and had to be contextually edited. The contextually edited MLC map had a higher overall accuracy (OA) than the OBIA map (86.7% versus 80.4%) and maps that were not contextually edited. But, the OBIA map had a higher OA than a MLC map without edits. Maps produced from the images also had a higher accuracy than the SAV map created from the acoustic data (OAs >80% and kappa >0.67 versus 76.6% and kappa = 0.32). SAV classification was comparable among the classified SBES SAV data points and all the final maps. The total area classified as SAV was marginally larger for satellite maps; however, the total area classified as bare substrate using the images was twice as large. A substrate map with three classes (silt, sand, and coral/hard bottom) produced from the SBES data using a random forest classifier and a Markov chain interpolator had a higher accuracy than a substrate map produced using a fractal dimension classifier and an indicator krig (the default choice) (72.4% versus 53.5%). The coral reef class from the SBES, OBIA, and contextually edited maps had comparable accuracies, but covered a much smaller area in the SBES maps because data points were lost during the interpolation process. The use of images was limited by turbidity levels and cloud cover and it yielded lower benthic detail. Despite these limitations, satellite image classification was the most efficacious method. If greater benthic detail is required, the SBES is more suitable or more effort is required during image classification. Also, the SBES can be operated in areas with turbid waters and greater depths. However, it could not be used in very shallow areas. Also, processing and interpolation of data points can result in a loss of resolution and introduces spatial uncertainty.

The Arctic oscillation, climatic variability and biotic factors influenced seedling dynamics in a Caribbean moist forest

We assessed the influence of the Arctic oscillation (AO) on local climate (using data from 2004 to 2009), their influence and the effects of heterospecific density on seedling dynamics (from January 2006 to August 2009), using data from 120 25-m2 subplots established in a moist tropical forest over limestone in Jamaica. The AO index (AOI) had a positive nonlinear relationship with mean monthly rainfall and the number of days with rain. Also, there was a significant increase in mean monthly atmospheric temperature in 2006, which coincided with a global temperature increase. Overall, at the community level, as temperature increased, mortality increased and then decreased. Also, mortality was significantly lower in plots with higher densities and those that experienced the positive phase of the AO. The effect of the AO on relative growth rate (RGR) of height (RGRh) varied as the AOI increased from negative to positive, while the number of days with rainfall had a positive effect on recruitment. However, these relationships differed during three six-month and two 12-month sample periods. There was a drought during the first period (dry season) during the negative phase of the AO; consequently, mortality was highest during this period. As the AOI increased (negative to positive), both mortality and RGRh declined while recruitment increased, culminating in a high-recruitment event. In addition, as the number of days with rainfall increased, RGR of diameter (RGRd) values were more positive (indicating that moisture stress was alleviated). During the second period (wet season), mortality increased as seedling density increased (possibly due to increased competition). Additionally, elevated temperature had a significant negative effect on RGRh (again, possibly due to increased competition or due to elevated respiratory carbon loss at higher growth temperatures). After the first two censuses, temperature and the AO influenced dynamics marginally, and seedling heterospecific density became increasingly important (lower mortality at higher densities). At the population level, the number of days with rainfall was the most frequent predictor of dynamics followed by temperature, AO, density and rainfall, and they were largely beneficial.