ABSTRACTMediterranean forests of Aleppo pine (Pinus halepensis Mill.) have a crucial role in climate change, as they are extremely adaptive and provide valuable timber or carbon stocks. However, ...greater detail quantifying those attributes is needed: although National Forest Inventories are acceptable, continuous cover maps are normally lacking. Here, we use the public Spanish low-density LiDAR flights to model above-ground biomass, volume, tree density, basal area and dominant height of naturally regenerated Mediterranean Aleppo pine forests, comparing individual-tree detection and area-based approach. We found R2 and RRMSE among 0.51–0.66 and 40–34% for above-ground biomass, 0.54–0.70 and 34–28% for volume, 0.23–0.45 and 33–28% for tree density, 0.48–0.62 and 32–27% for basal area, and 0.70–0.69 and 11–11% for dominant height. In all cases but dominant height, the area-based approach outperformed the individual-tree detection. Neither time difference between LiDAR flight and ground measurement or past land use affected the area-based approach models, yet the latter had a strong effect on observed productivity. The different definitions of dominant height were equivalent and did not influence the dominant height models. We believe these models, and their corresponding maps, will be a great asset for policymakers and different stakeholders for Aleppo pine forests throughout the Mediterranean basin.
Connectivity assessments and corridor delineation are key contributions to landscape management and biodiversity conservation. We examined the influence of three potentially crucial factors on the ...results of connectivity analyses, using the two subpopulations of the endangered brown bear in the Cantabrian Range (NW Spain) as a case study. First, we evaluated the spatial resolution of vegetation data, using three types of datasets ranging from coarse resolution land-cover maps to high-resolution LiDAR data. Second, the seasonal variation in the distribution of habitat resources and in the species use of the landscape. Third, multi-annual periods with different population status. The estimates of subpopulation isolation (effective distances) and the trajectory of the identified corridors were substantially influenced by (i) the spatial resolution of vegetation data; the more robust results were obtained when incorporating fine-scale LiDAR data; (ii) the season over which species occurrence data and landscape characteristics were considered; the spring mating season yielded higher connectivity estimates than any other season; (iii) the status of the populations, with higher landscape connectivity estimated for expanding populations. Our study reveals that the use of coarse-resolution data may underestimate the resistance of the non-habitat landscape matrix to species movements. The use of year-round estimates of habitat connectivity may miss the key seasonal temporal windows for species movements. Landscape resistance may be overestimated when data from periods with declining or restricted populations are used. We recommend carefully disentangling the effects of demography and landscape heterogeneity on realized species dispersal movements for improving the insights from connectivity modelling.
Abstract
Background and aims
Decline in tree species is a complex phenomenon involving multiple factors, among edaphic conditions are assumed to play an important role as factor of predisposition of ...forests to this process. In this regard, scarce information exists on the effects of the internal variability of the soil with depth on the predisposition to decline, an aspect that requires further evaluation.
Methods
Characterization of the internal variability of soil was carried out at 20 sites (10 with evidence of decline and 10 with no signs of decline) and the results analyzed to determine their role in modulating the effect of drought, which is the main cause of the observed decline in Aleppo pine stands in the Comunidad Valenciana (Spain).
Results
The soil properties found to be the most explanatory were those associated with soil quality in terms of available space for root exploration, which is vital for nutrition and, above all, water uptake. Episodes of decline are associated with stands where soils have a shallow effective depth due to a low degree of profile development or through marked textural anisotropy because of particularly clayey horizons that cause abrupt changes in permeability and aeration.
Conclusion
The internal variability of the soil, closely linked to the degree of pedogenetic development, is identified as a factor that plays an important role in predisposing the vegetation to the effects of drought.
Context
Corridors are usually delineated as areas of minimum cumulative resistance to movement through a resistance surface and characterized by their effective distance (accumulated resistance along ...the least-cost path). The results of these assessments depend on resistance values, which are typically derived from the inverse of habitat suitability models or from presence data of individuals within their home ranges, rather than from data on dispersal or exploratory movements.
Objective
Evaluate the extent to which corridor delineation and effective distance estimates may vary depending on whether home range locations or dispersal data are used to characterize species habitat selection and landscape resistance to movement.
Methods
We analyzed a large telemetry dataset (GPS collars) for the endangered Iberian lynx. We modeled corridors and effective distances three ways: (1) considering only GPS locations within home ranges, (2) considering only locations in dispersal or exploratory movements outside home ranges, and (3) considering all locations together.
Results
Delineated least-cost corridors followed similar trajectories and sometimes overlapped in the three models. The estimated effective distances were 42 % lower in the dispersal-based model than in the model based solely on home range use.
Conclusions
Models derived exclusively from locations within home ranges may provide lower connectivity estimates than models derived from dispersal locations, affecting estimates of resistance to move between habitat areas, even when the most likely movement routes are similar. Although dispersal data are costly to gather, they potentially provide more realistic assessments of the actual isolation of populations in heterogeneous landscapes.
Landscape connectivity has traditionally been studied for animal species rather than for plants, especially under a multispecies approach. However, connectivity can be equally critical for both fauna ...and flora and, thus, an essential point in the selection of key management areas and measures. This paper explores a spatially explicit framework to assess the contribution of habitat patches in the conservation and enhancement of plant functional connectivity and habitat availability in a multispecies context. It relies on graph theory and a habitat availability index and differentiates between two management scenarios: (i) conservation; and (ii) restoration, by considering current and potential species distribution based on species distribution models together with a vegetation survey. The results mapped at high spatial resolution priority target areas to apply management measures. We found that intervening in a small proportion of the study area may lead to double the average overall landscape connectivity of the studied species. This study aimed at proposing an innovative methodology that allows studying connectivity for multiple plant species at landscape scale while integrating their individual characteristics. The proposed framework is a step toward incorporating connectivity concerns into plant biodiversity management, based on a better understanding of landscape structure and functionality. Here, we illustrated its significant potential for local conservation and restoration planning and resource optimization.
•The bulk of ecological modelling methods do not integrate different spatial scales.•Theoretical and methodological implications of hierarchical modelling approaches.•Reliable and high-resolution ...predictions at landscape scale.•Addressing hierarchical approaches is vital to produce reliable conservation plans.
Ecological niche models are powerful tools in ecology. Factors operating at different spatial scales are known to jointly influence species distributions, but their integration in meaningful and reliable niche models is still methodologically complex and requires further research and validation. Here, we compare six different hierarchical niche models (HNMs): two ensemble, two Bayesian, and two penalized logistic regression approaches. The six HNMs were applied to produce high-resolution (25 m) predictions for five tree species in a Biosphere Reserve in Central Spain, combining information from two spatial scales. At the regional scale (mainland Spain) climatic variables were used as predictors, and presence/absence data were derived from the Spanish Forest Inventory (76,347 plots). At the landscape scale (Biosphere Reserve) environmental variables were used as predictors while presence/absence data were derived from a local vegetation sampling (346 plots). We compared and evaluated the six HNMs using the AUC, MaxKappa, and MaxTSS statistics and the Pearson’s correlation coefficient. We obtained reliable high-resolution HNMs at the landscape scale (AUC values were greater than 0.8), although with variable performance and scope of application. Ensemble approaches delivered reliable models particularly when the sample size was not a limiting modelling factor. However, Bayesian modelling allowed considering a spatially correlated random effect that outperformed the results of all other approaches for species with a low sample size, possibly derived from a strong spatial structure in their distribution. HNMs succeeded in generating high-resolution predictions and manage to identify a significantly greater part of the climatic niche of the species than non-hierarchical models. This allows more accurate projections both in space and time, which is essential in climate change and invasive species modelling projections. The usefulness of these models for decision support in local conservation programs is therefore highlighted. Our methodological comparison is valuable to inform modellers and decision makers of the performance and implications of these approaches regarding the support they can provide for the implementation of conservation management measures at the landscape scale.
•Species distribution models (SDMs) are powerful tools in forest management.•Validation of SDMs at landscape scale is vital for more reliable forestry strategies.•The majority of SDM approaches do ...not address the question of resources optimization.•Opportunistic sampling outperformed systematic sampling in predicting woody plant SDMs.•Opportunistic sampling strategies could be a key cost-effective solution for supporting management.
Forest management increasingly needs the support of species distribution models (SDMs). However, different challenges remain to be addressed before the practical use and generalization of these models in the design of management measures in forest ecosystems. Due to the limited resources that are typically available for forest management, including the forest inventory phase, it is necessary to optimize the sampling approaches. Opportunistic sampling may be one strategy to reduce sampling costs, but the accuracy and suitability of the assessments derived from this sampling remain yet poorly addressed, particularly in forest landscapes. On the other hand, different forestry applications require landscape-wide estimates but still with fine resolution (ideally meters) as to guide management interventions. We, here, assess in detail the performance of the classical regular (systematic) sampling strategy and three different opportunistic samplings approaches along roads and tracks in a forest-dominated Biosphere Reserve (≈15,000 ha) in central Spain. We use specifically gathered field data in different inventories with sampling intensities of about 1–2 plots/km2. We compare, for each sampling strategy, the resultant consensus species distribution models for 28 woody plant species (trees and shrubs) developed at a spatial resolution of 25 m. We found that SDMs were reliable (AUC > 0.75) for 20 species out of 28 using either an opportunistic or/and systematic sampling. In general, opportunistic sampling was more efficient than systematic sampling, resulting in SDMs with a comparable accuracy for a lower inventory cost or in more accurate SDMs for the same sampling effort. This was mainly because the four sampling strategies adequately captured the environmental variability of the study area, and because plots in the opportunistic sampling were located at a sufficient distance from tracks to avoid potential edge effects. The minimum sample size and the species ecology should, however, be evaluated with caution in each case. We conclude that opportunistic sampling along tracks may be a practical and cost-effective option for SDMs in forest landscapes, as long as the density and spatial arrangement of tracks are sufficient to cover the full range of environmental conditions. This prerequisite could be evaluated, before the inventory phase, using available statistical approaches and spatial layers, potentially allowing for a remarkable saving of sampling resources in forest management planning. Species distribution models calibrated at the landscape extent with fine resolution could hence become ever more powerful and cost-effective tools for forest management and planning in both planted and natural forests.
► Penalised logistic regression outperformed standard logistic regression. ► Penalised logistic regression equalled the performance of Maxent. ► We encourage further use of penalised regression for ...species distribution modelling.
An important aspect of species distribution modelling is the choice of the modelling method because a suboptimal method may have poor predictive performance. Previous comparisons have found that novel methods, such as Maxent models, outperform well-established modelling methods, such as the standard logistic regression. These comparisons used training samples with small numbers of occurrences per estimated model parameter, and this limited sample size may have caused poorer predictive performance due to overfitting. Our hypothesis is that Maxent models would outperform a standard logistic regression because Maxent models avoid overfitting by using regularisation techniques and a standard logistic regression does not. Regularisation can be applied to logistic regression models using penalised maximum likelihood estimation. This estimation procedure shrinks the regression coefficients towards zero, causing biased predictions if applied to the training sample but improving the accuracy of new predictions. We used Maxent and logistic regression (standard and penalised) to analyse presence/pseudo-absence data for 13 tree species and evaluated the predictive performance (discrimination) using presence–absence data. The penalised logistic regression outperformed standard logistic regression and equalled the performance of Maxent. The penalised logistic regression may be considered one of the best methods to develop species distribution models trained with presence/pseudo-absence data, as it is comparable to Maxent. Our results encourage further use of the penalised logistic regression for species distribution modelling, especially in those cases in which a complex model must be fitted to a sample with a limited size.
•A new method to validate SDMs applied to plant species selection for revegetation.•We test the ability to discriminate present from absent species in plant assemblages.•We validated SDMs for woody ...plant species selection in revegetation projects.
We propose an evaluation approach to validate stacked species distribution models applied to plant species selection in ecological restoration. The evaluation method does not assess the accuracy of individual species models, but focuses on the ability of the stacked models to discriminate between present and absent species in a vegetation relevé. We measured the discriminative ability using the area under the ROC curve (AUC) to avoid the drawbacks of converting occurrence probabilities into binary predictions. Using the proposed method, we compared competing sets of predictors and validated stacked species distribution models for plant species selection in ecological restoration projects in Spain. 120,938 vegetation relevés included in the Forest Map of Spain were used to train models for 188 species and an independent set of 100 vegetation relevés was used for validation. The best performing set of predictors included climate and soil related predictors derived from coarse resolution datasets. The model performance was acceptable on average (mean AUC: 0.88, sd: 0.07) and high (AUC>0.9) in 42% of the relevés evaluated. We recommend the proposed evaluation approach to validate stacked species distribution models used to support species selection in ecological restoration projects.
Developing plant identification skills is an important part of the curriculum of any botany course in higher education. Frequent practice with dried and fresh plants is necessary to recognize the ...diversity of forms, states, and details that a species can present. We have developed a web-based assessment system for mobile devices that is able to pose appropriate questions according to the location of the student. A student's location can be obtained using the device position or by scanning a QR code attached to a dried plant sheet in a herbarium or to a fresh plant in an arboretum. The assessment questions are complemented with elaborated feedback that, according to the students' responses, provides indications of possible mistakes and correct answers. Three experiments were designed to measure the effectiveness of the formative assessment using dried and fresh plants. Three questionnaires were used to evaluate the system performance from the students' perspective. The results clearly indicate that formative assessment is objectively effective compared to traditional methods and that the students' attitudes towards the system were very positive.
