Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity

Context

High-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species’ potential to link patches or populations are of importance.

Objectives

We introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories’ plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range.

Methods

We used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species’ range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature.

Results

Simulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corroborating previous findings for this species.

Conclusions

We show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting migratory connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.

     

Predicting species-habitat relationships: does body size matter?

Context

Allometric scaling laws are foundational to structuring processes from cellular to ecosystem levels. The idea that allometric relationships underlie species characteristic selection scales, the spatial scales at which species respond to landscape features, has recently been investigated, however, supporting empirical evidence is scarce.

Objectives

Lack of pattern can be explained by inaccurate estimation, low power, confounding factors, or absence of a relationship. In this paper, we evaluate the relationship between body size and species characteristic selection scales after overcoming limitations of previous study designs.

Methods

We conducted 1328 avian point counts across the state of Nebraska using the robust sampling design to account for imperfect detection. We used Bayesian latent indicator scale selection with N-mixture models to estimate species’ characteristic selection scales of six habitat features for 86 species. We propagated the uncertainty associated with assigning characteristic scales to a model of the relationship between body size and characteristic spatial scales.

Results

Species characteristic scales varied across habitat predictors, and varied in the uncertainty associated with selecting single characteristic scales. After propagating uncertainty our results do not support a relationship between species’ body size and the spatial scales at which they respond to landscape features.

Conclusions

As species abundance integrates birth, death, immigration, and emigration processes, each of which are influenced by ecological processes manifesting at various scales, we question whether a general allometric relationship should be expected. Our results suggest that selection may act on responses to specific environmental features, rather than responses to spatial scale per se.

     

Effect of connectivity and habitat availability on the occurrence of the Chestnut-throated Huet-Huet (<Emphasis Type="Italic">Pteroptochos castaneus,</Emphasis> Rhinocryptidae) in fragmented landscapes of central Chile

Context

Although small isolated habitat patches may not be able to maintain a minimum viable population, small patches that are structurally isolated may be functionally connected if individuals can cross the gaps between them, in which case, their areas could be added to form a larger habitat patch, eventually surpassing the size threshold for holding a viable population.

Objectives

We studied whether models based on the size and isolation of habitat patches could be used to predict the distribution of the Chestnut-throated Huet-Huet (Pteroptochos castaneus) in fragmented landscapes of the coastal range of the Maule region, central Chile.

Methods

We selected seven 10,000-ha landscapes (8.4–70.7% forest cover). For each habitat patch we made 18 predictions of the presence of the species based on the combination of two thresholds: three critical patch sizes for maintaining a viable population (62.5, 125 and 250 ha) and six critical isolation distances between patches (0, 10, 50, 100, 150 and 200 m). We used playbacks in 59 sampling points to estimate the species’ presence/absence. We used logistic regressions to test whether the output of the patch-matrix models could explain part of the variation in the presence of Pteroptochos castaneus.

Results

The best predictions for the presence of P. castaneus were obtained with the most conservative scenarios (125–250 ha to 0–10 m), including a positive effect of the understory cover and a lack of effect of the forest type (native or exotic).

Conclusions

Our findings suggest that the long term persistence of P. castaneus may depend on the existence of large and/or very connected forest tracts.

     

How does habitat fragmentation affect the biodiversity and ecosystem functioning relationship?

Context

The relationship between biodiversity and ecosystem functioning (BEF) has been a central topic in ecology for more than 20 years. While experimental and theoretical studies have produced much knowledge of how biodiversity affects ecosystem functioning, it remains poorly understood how habitat fragmentation affects the BEF relationship.

Objectives

To develop a framework that connects habitat fragmentation to the BEF relationship from a landscape perspective.

Methods

We reviewed the literature on habitat fragmentation, BEF, and related fields, and developed a framework to analyze how habitat fragmentation affects the BEF relationship through altering biodiversity, environmental conditions, and both, based on the pattern-process-scale perspective in landscape ecology.

Results

Our synthesis of the literature suggests that habitat fragmentation can alter BEF relationship through several processes. First, habitat fragmentation causes the non-random loss of species that make major contributions to ecosystem functioning (decreasing sampling effect), and reduces mutualistic interactions (decreasing complementarity effects) regardless of the changes in species richness. Second, environmental conditions within patches and ecological flows among patches vary significantly with the degree of fragmentation, which potentially contributes to and modulates the BEF relationship.

Conclusions

Habitat fragmentation can affect the BEF relationship directly by altering community composition, as well as indirectly by changing environmental conditions within and among habitat patches on both local and landscape levels. The BEF relationship obtained from small plots and over short time periods may not fully represent that in real landscapes that are fragmented, dynamic, and continuously influenced by myriad human activities on different scales in time and space.

     

Evaluating static and dynamic landscape connectivity modelling using a 25-year remote sensing time series

Context

Despite calls for landscape connectivity research to account for spatiotemporal dynamics, studies have overwhelmingly evaluated the importance of habitats for connectivity at single or limited moments in time. Remote sensing time series represent a promising resource for studying connectivity within dynamic ecosystems. However, there is a critical need to assess how static and dynamic landscape connectivity modelling approaches compare for prioritising habitats for conservation within dynamic environments.

Objectives

To assess whether static landscape connectivity analyses can identify similar important areas for connectivity as analyses based on dynamic remotely sensed time series data.

Methods

We compared degree and betweenness centrality graph theory metric distributions from four static scenarios against equivalent results from a dynamic 25-year remotely sensed surface-water time series. Metrics were compared at multiple spatial aggregation scales across south-eastern Australia’s 1 million km² semi-arid Murray–Darling Basin and three sub-regions with varying levels of hydroclimatic variability and development.

Results

We revealed large differences between static and dynamic connectivity metric distributions that varied by static scenario, region, spatial scale and hydroclimatic conditions. Static and dynamic metrics showed particularly low overlap within unregulated and spatiotemporally variable regions, although similarities increased at coarse aggregation scales.

Conclusions

In regions that exhibit high spatiotemporal variability, static connectivity modelling approaches are unlikely to serve as effective surrogates for more data intensive approaches based on dynamic, remotely sensed data. Although this limitation may be moderated by spatially aggregating static connectivity outputs, our results highlight the value of remotely sensed time series for assessing connectivity in dynamic landscapes.

     

Planning for the future: identifying conservation priority areas for Iberian birds under climate change

Context

Species are expected to shift their distributions in response to global environmental changes and additional protected areas are needed to encompass the corresponding changes in the distributions of their habitats. Conservation policies are likely to become obsolete unless they integrate the potential impacts of climate and land-use change on biodiversity.

Objectives

We identify conservation priority areas for current and future projected distributions of Iberian bird species. We then investigate the extent to which global change informed priority areas are: (i) covered by existing protected area networks (national protected areas and Natura 2000); (ii) threatened by agricultural or urban land-use changes.

Methods

We use outputs of species distributions models fitted with climatic data as inputs in spatial prioritization tools to identify conservation priority areas for 168 bird species. We use projections of land-use change to then discriminate between threatened and non-threatened priority areas.

Results

19% of the priority areas for birds are covered by national protected areas and 23% are covered by Natura 2000 sites. The spatial mismatch between protected area networks and priority areas for birds is projected to increase with climate change. But there are opportunities to improve the protection of birds under climate change, as half of the priority areas are currently neither protected nor in conflict with urban or agricultural land-uses.

Conclusions

We identify critical areas for bird conservation both under current and climate change conditions, and propose that they could guide the establishment of new conservation areas across the Iberian Peninsula complementing existing protected areas.

     

Matrix transformation alters species-area relationships in fragmented coastal forests

Context

Ecological theory suggests that large habitat fragments should harbour more species than small fragments. However, this may depend on the surrounding matrix. Matrices in fragmented landscapes may either amplify or reduce area effects, which could influence predicted extinctions based on species-area relationships (SARs).

Objective

To determine the influence of matrix type on SARs.

Methods

We surveyed birds within 59 coastal forest fragments in two matrix types, anthropogenic (South Africa) and natural (Mozambique). We classified species as forest specialists or habitat generalists and fitted species-area models to compare how SAR slopes differed among matrix types. We also calculated nestedness and evenness to determine if these varied among matrix type and used logistic regressions to identify species-specific responses to matrix type.

Results

For habitat generalists, SARs were weak within both matrices, while for forest specialists it was strong in the anthropogenic but weak in the natural matrix. In the former, the SAR was similar to those recorded for real islands within archipelagos. Forest specialist assemblages were nested by area within anthropogenic, but not natural matrices. Matrix type did not influence evenness. Area only affected the occurrence of one species when the matrix was natural, compared to 11 species when it was anthropogenic.

Conclusions

Forest specialist bird species conformed to island biogeographic predictions of species loss in forest fragments embedded in anthropogenic, but not natural matrices. Extinctions from small forest fragments might be prevented by conserving natural- or restoring anthropogenic matrices, as well as by increasing forest area.

     

Connectivity analysis as a tool for assessing restoration success

Context

Methods for measuring restoration success that include functional connectivity between species’ populations are rare in landscape ecology and restoration practices. We developed an approach that analyzes connectivity between populations of target species and their dispersal probabilities to assess restoration success based on easily accessible input data. Applying this method to landscape development scenarios can help optimize restoration planning.

Objectives

We developed an assessment for restoration success and restoration planning based on functional connectivity between species’ populations and spatially explicit scenarios. The method was used in a case study to test its applicability.

Methods

Based on data on available habitat, species’ occurrence and dispersal ranges, connectivity metrics and dispersal probabilities for target species are calculated using the software Conefor Sensinode. The metrics are calculated for scenarios that reflect possible changes in the landscape to provide a basis for future restoration planning. We applied this approach to floodplain meadows along the Upper Rhine for four plant species and three future scenarios.

Results

In the case study, habitats of the target species were poorly connected. Peucedanum officinale and Sanguisorba officinalis were more successful in recolonizing new habitats than Iris spuria and Serratula tinctoria. The scenarios showed that restoration of species-rich grassland was beneficial for dispersal of the target species. As expected in the agriculturally dominated study area, restoration of former arable land significantly increased dispersal probabilities.

Conclusions

In the case study, the developed approach was easily applicable and provided reasonable results. Its implementation will be helpful in decision-making for future restoration planning.

     

Reading past landscapes: combining modern and historical records,maps, pollen-based vegetation reconstructions,and the socioeconomic background

Context

Anthropogenic and environmental changes are reshaping landscapes across the globe. In this context, understanding the patterns, drivers, and consequences of these changes is one of the central challenges of humankind.

Purpose

We aim to test the possibilities of combining modern multidisciplinary approaches to reconstruct the land-cover and linking the changes in land-cover to socioeconomic shifts in southern Estonia over the last 200 years.

Methods

The historical records from five, and maps from six time periods and 79 pollen-based land-cover reconstructions from four lakes are used to determine the land-cover structure and composition and are thereafter combined with the literature based analyses of socioeconomic changes.

Results

All information sources recorded similar changes in the land-cover. The anthropogenic deforestation was comparable to today’s (approximately 50%) during the nineteenth century. Major political and socioeconomic changes led to the intensification of agriculture and maximal deforestation (60–85%) at the beginning of the twentieth century. The land nationalisation following the Soviet occupation led to the reforestation of the less productive agricultural lands. This trend continued until the implementation of European Union agrarian subsidies at the beginning of the twenty first century.

Conclusions

Pollen-based reconstructions provide a trustworthy alternative to historical records and maps. Accounting for source specific biases is essential when dealing with any data source. The landscape’s response to socioeconomic changes was considerable in Estonia over the last 200 years. Changes in land ownership and the global agricultural market are major drivers in determining the strength and direction of the land-cover change.