Jorge Orestes Cerdeira

Shifting protected areas: scheduling spatial priorities under climate change

This research was funded through the European Regional Development Fund Integrated Program IC&DT No1/SAESCTN/ALENT-07-0224-FEDER-001755.

Linking like with like: optimising connectivity between environmentally-similar habitats

Habitat fragmentation is one of the greatest threats to biodiversity. To minimise the effect of fragmentation on biodiversity, connectivity between otherwise isolated habitats should be promoted. However, the identification of linkages favouring connectivity is not trivial. Firstly, they compete with other land uses, so they need to be cost-efficient. Secondly, linkages for one species might be barriers for others, so they should effectively account for distinct mobility requirements. Thirdly, detailed information on the auto-ecology of most of the species is lacking, so linkages need being defined based on surrogates. In order to address these challenges we develop a framework that (a) identifies environmentally-similar habitats; (b) identifies environmental barriers (i.e., regions with a very distinct environment from the areas to be linked), and; (c) determines cost-efficient linkages between environmentally-similar habitats, free from environmental barriers. The assumption is that species with similar ecological requirements occupy the same environments, so environmental similarity provides a rationale for the identification of the areas that need to be linked. A variant of the classical minimum Steiner tree problem in graphs is used to address c). We present a heuristic for this problem that is capable of handling large datasets. To illustrate the framework we identify linkages between environmentally-similar protected areas in the Iberian Peninsula. The Natura 2000 network is used as a positive ‘attractor’ of links while the human footprint is used as ‘repellent’ of links. We compare the outcomes of our approach with cost-efficient networks linking protected areas that disregard the effect of environmental barriers. As expected, the latter achieved a smaller area covered with linkages, but with barriers that can significantly reduce the permeability of the landscape for the dispersal of some species.

Ecological networks: delving into the architecture of biodiversity

In recent years, the analysis of interaction networks has grown popular as a framework to explore ecological processes and the relationships between community structure and its functioning. The field has rapidly grown from its infancy to a vibrant youth, as reflected in the variety and quality of the discussions held at the first international symposium on Ecological Networks in Coimbra—Portugal (23–25 October 2013). The meeting gathered 170 scientists from 22 countries, who presented data from a broad geographical range, and covering all stages of network analyses, from sampling strategies to effective ways of communicating results, presenting new analytical tools, incorporation of temporal and spatial dynamics, new applications and visualization tools.1 During the meeting it became evident that while many of the caveats diagnosed in early network studies are successfully being tackled, new challenges arise, attesting to the health of the discipline.

Climate change, species range shifts and dispersal corridors: an evaluation of spatial conservation models

This research was funded through the Fundac~ao para a Ci^encia e a Tecnologia (FCT) project PTDC/AAG-GLO/3979/2014 led by DA and through Integrated Program of IC&DT Call No 1/SAESCTN/ALENT-07-0224-FEDER- 001755 led by MBA. JOC acknowledges support from the FCT’s project UID/MAT/00297/2013. DA also received support from FEDER through the COMPETE – Programa Operacional Factores de Competitividade – and National funds via FCT with a postdoctoral fellowship SFRH/BPD/104077/ 2014.

A quantitative analysis on the effects of critical factors limiting the effectiveness of species conservation in future time

Abstract The effectiveness of conservation plans depends on environmental, ecological, and socioeconomic factors. Global change makes conservation decisions even more challenging. Among others, the components of most concern in modern‐day conservation assessments are as follows: the magnitude of climate and land‐use changes; species dispersal abilities; competition with harmful socioeconomic activities for land use; the number of threatened species to consider; and, relatedly, the available budget to act. Here, we provide a unified framework that quantifies the relative effects of those factors on conservation. We conducted an area‐scheduling work plan in order to identify sets of areas along time in which the persistence expectancies of species are optimized. The approach was illustrated using data of potential distribution of ten nonvolant mammal species in Iberia Peninsula from current time up to 2080. Analyses were conducted considering possible setups among the factors that are likely to critically impact conservation success: three climate/land‐use scenarios; four species’ dispersal kernel curves; six land‐use layer types; and two planning designs, in which assessments were made independently for each species, or joining all species in a single plan. We identified areas for an array of investments levels capable to circumvent the spatial conflicts with socioeconomic activities. The effect of each factor on the estimated species persistence scores was assessed using linear mixed models. Our results evidence that conservation success is highly reliant on the resources available to abate land‐use conflicts. Nonetheless, under the same investment levels, planning design and climate change were the factors that most shaped species persistence scores. The persistence of five species was especially affected by the sole effect of planning design and consequently, larger conservation investments may retard climatic debts. For three species, the negative effects of a changing climate and of multiple‐species planning designs added up, making these species especially at risk. Integrated assessments of the factors most likely to limit species persistence are pivotal to achieve effectiveness.

A decomposition approach for the p-median problem on disconnected graphs

Abstract The p -median problem seeks for the location of p facilities on the vertices (customers) of a graph to minimize the sum of transportation costs for satisfying the demands of the customers from the facilities. In many real applications of the p -median problem the underlying graph is disconnected. That is the case of p -median problem defined over split administrative regions or regions geographically apart (e.g. archipelagos), and the case of problems coming from industry such as the optimal diversity management problem. In such cases the problem can be decomposed into smaller p -median problems which are solved in each component k for different feasible values of p k , and the global solution is obtained by finding the best combination of p k medians. This approach has the advantage that it permits to solve larger instances since only the sizes of the connected components are important and not the size of the whole graph. However, since the optimal number of facilities to select from each component is not known, it is necessary to solve p -median problems for every feasible number of facilities on each component. In this paper we give a decomposition algorithm that uses a procedure to reduce the number of subproblems to solve. Computational tests on real instances of the optimal diversity management problem and on simulated instances are reported showing that the reduction of subproblems is significant, and that optimal solutions were found within reasonable time.

Introducing Spatio-Temporal Conservation Units: Models for Flexible Optimization of Species Persistence Under Climate Change

Anticipating the effects of climate change on biodiversity and integrating them in planning protocols for the future are fundamental strategies to increase the effectiveness of conservation efforts. With climate change, species require dispersal skills to follow displacements of their suitable climates and therefore, spatial conservation interventions need to consider such dynamics. In general, common planning frameworks identify networks of conservation areas seemed important for species range shifts. However, it is highly unlikely that all the areas in a network present synchronous conservation value. Furthermore, given the continuous (spatial and temporal autocorrelated) nature of threats and ecological processes, the value of each area is largely dependent on the state of the neighboring areas in the recent past. In this study, a family of three models centered on the prioritization (not of single areas but) of temporal chains of areas as conservation units is presented. These models drive the use of financial investments through time in order to maximize the persistence of biodiversity in dynamic environments. Alike the most typical approaches, the here introduced models allow investments to be transferred between areas losing conservation relevancy to the areas that gain relevancy. A fictitious (but plausible) conservation plan for ten mammal species in Iberian Peninsula up to 2080 is used to illustrate the setting-up and outputs of the models. Results evidence that the conservation effectiveness achieved in each model depends on singular spatio-temporal distribution relationships among species and between species and distinct land-uses. Planners should then investigate the sensitivity of their goals to distinct decision-support tools even when driven by similar designs and constraints.

Revisiting niche fundamentals with Tukey depth

1. The first attempts to describe species ecological niches were simple geometric procedures that depict the niche boundaries directly from environmental data. The convex hull was one of such procedures, popular for its simplicity, clear ecological rational and precise definition of the niche. However, it lacked the ability to differentiate areas of the niche with different probabilities of occurrence according to environmental suitability. 2. We incorporate the Tukey depth, a mathematical tool to measure the centrality of a point within a cloud of points on a multidimensional space, in the convex hull approach to (i) propose a new procedure (CH-Tukey) to estimate species’ environmental suitability, and (ii) estimate niche overlap coherently. In addition to a clear ecological rational and simplicity the CHTukey procedure has a number of attractive features: use of presence-only data; independence from background data; invariance to scale; robustness to outliers; and the decomposition of the niche into a finite number of isosuitability levels, permitting the computation of consistent overlap indices. We illustrate the use of CH-Tukey, using occurrence data of the main Quercus species and subspecies from Western Mediterranean Europe, comparing its outputs with BIOCLIM and MAXENT. 3. Results showed distinct niche geometries among the different approaches. BIOCLIM produced rectilinear niches reflecting the assumption that ecological variables are independent in their action on the species. CHTukey, relaxing this assumption, adjusts niche outer boundary and the inner suitability levels to the known occurrences. MAXENT produced unbounded niche geometries, showing abrupt shifts in the species response to the environmental variables. 4. The niche predictions obtained with geometric approaches, BIOCLIM and CH Tukey, are simpler but better aligned with Hutchinson’s niche concept than those obtained with MAXENT, this latter showing ecologically implausible relationships with the environmental variables. CH-Tukey and the related overlap measures provide an adequate tool to explore niche properties and species-environment relationships.

A Model to Minimize Costs and Promote Species Persistence under Climate Change

Biodiversity is severely threatened by the effects of changing climates that cause species to readjust their spatial ranges. But species are limited in their capacity to follow suitable climates, as these rearrange in space along time. Therefore, the identification of the areas to support spatial readjustments of species is a pivotal step that should be made thoroughly given the limited budgets available. We propose a two-stage mixed integer linear programming to formalize this issue, present a heuristic and report results comparing optimal and heuristic solutions.