Diogo Alagador

Climate change threatens European conservation areas

Europe has the worlds most extensive network of conservation areas. Conservation areas are selected without taking into account the effects of climate change. How effectively would such areas conserve biodiversity under climate change? We assess the effectiveness of protected areas and the Natura 2000 network in conserving a large proportion of European plant and terrestrial vertebrate species under climate change. We found that by 2080, 58 ± 2.6% of the species would lose suitable climate in protected areas, whereas losses affected 63 ± 2.1% of the species of European concern occurring in Natura 2000 areas. Protected areas are expected to retain climatic suitability for species better than unprotected areas (P<0.001), but Natura 2000 areas retain climate suitability for species no better and sometimes less effectively than unprotected areas. The risk is high that ongoing efforts to conserve Europes biodiversity are jeopardized by climate change. New policies are required to avert this risk.

Making decisions to conserve species under climate change

Severe impacts on biodiversity are predicted to arise from climate change. These impacts may not be adequately addressed by conventional approaches to conservation. As a result, additional management actions are now being considered. However, there is currently limited guidance to help decision makers choose which set of actions (and in what order) is most appropriate for species that are considered to be vulnerable. Here, we provide a decision framework for the full complement of actions aimed at conserving species under climate change from ongoing conservation in existing refugia through various forms of mobility enhancement to ex situ conservation outside the natural environment. We explicitly recognize that allocation of conservation resources toward particular actions may be governed by factors such as the likelihood of success, cost and likely co-benefits to non-target species in addition to perceived vulnerability of individual species. As such, we use expert judgment of probable tradeoffs in resource allocation to inform the sequential evaluation of proposed management interventions.

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.

Short communication: Linking habitats for multiple species

The establishment of linkages between habitats is of great importance to avert the detrimental impacts of land fragmentation and climate change on biodiversity. Linkages need to be cost-efficient, and should account for specific dispersal requirements of species. Since cost-efficient linkages defined independently for each individual species are more costly than linkages optimised for multiple species, there is need for methods specifically designed to retrieve efficient linkages for multiple species. MulTyLink (Multiple Type Linkages) is a C++ open source program that defines cost-efficient linkages free of barriers for the species considered, and that allows species-specific dispersal requirements to be considered. Here we present, discuss and illustrate the algorithms used by MulTyLink to identify cost-efficient linkages for multiple species.

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.

Cost‐effective monitoring of biological invasions under global change: a model‐based framework

1. Ecological monitoring programmes are designed to detect and measure changes in biodiversity and ecosystems. In the case of biological invasions, they can contribute to anticipating risks and adaptively managing invaders. However, monitoring is often expensive because large amounts of data might be needed to draw inferences. Thus, careful planning is required to ensure that monitoring goals are realistically achieved. 2. Species distribution models (SDMs) can provide estimates of suitable areas to invasion. Predictions from these models can be applied as inputs in optimization strategies seeking to identify the optimal extent of the networks of areas required for monitoring risk of invasion under current and future environmental conditions. A hierarchical framework is proposed herein that combines SDMs, scenario analysis and cost analyses to improve invasion assessments at regional and local scales. We illustrate the framework with Acacia dealbata Link. (Silver-wattle) in northern Portugal. The framework is general and applicable to any species. 3. We defined two types of monitoring networks focusing either on the regional-scale management of an invasion, or management focus within and around protected areas. For each one of these two schemes, we designed a hierarchical framework of spatial prioritization using different information layers (e.g. SDMs, habitat connectivity, protected areas). We compared the performance of each monitoring scheme against 100 randomly generated models. 4. In our case study, we found that protected areas will be increasingly exposed to invasion by A. dealbata due to climate change. Moreover, connectivity between suitable areas for A. dealbata is predicted to increase. Monitoring networks that we identify were more effective in detecting new invasions and less costly to management than randomly generated models. The most cost-efficient monitoring schemes require 18% less effort than the average networks across all of the 100 tested options. 5. Synthesis and applications. The proposed framework achieves cost-effective monitoring networks, enabling the interactive exploration of different solutions and the combination of quantitative information on network performance with orientations that are rarely incorporated in a decision support system. The framework brings invasion monitoring closer to European legislation and management needs while ensuring adaptability under rapid climate and environmental change.

Dynamic models in research and management of biological invasions

Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales.

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.

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.