Protecting landscape connectivity: multi-node selection of key habitat patches based on fragmentation and reachability

<div><div>Oral presentation at the 1st International Conference on Community Ecology, September 28-29, 2017, Budapest</div><div><br></div><div>Abstract:</div><div>Habitat connectivity is of major importance in biodiversity conservation, and is one of the key aspects to be taken into consideration in the spatial design of networks of protected areas. Network analyses provide efficient tools for modelling habitat connectivity and defining priority areas for protecting it [1]. Widespread prioritization approaches are based on rankings of the centrality (or importance) of individual habitat patches. However, it has been noted that the set of nodes selected as key for conservation through individual ranking may depart from the optimal or most efficient group of nodes [2]. Multi-node analyses calculate the combined centrality of a set of n habitat patches in order to identify groups of patches that maximally complement each other in order to increase the protection of connectivity for the whole network. We apply multi-node analyses to the prioritization of habitat patches for five vulnerable bird species in Catalonia, Spain, using two different approaches to connectivity, based on fragmentation and reachability. Groups of patches based on fragmentation are usually concentrated on core areas, while reachability groups are widely spread. Fragmentation sets have higher centrality value for low-mobility species, and reachability sets for long distance dispersers. The protection of the networks against fragmentation requires fewer patches, allows for more gradual implementation and is currently better accounted for by the Natura 2000 network of protected areas, while the protection of reachability is less costly and more efficient in terms of area requirements. Our work contributes to the inclusion of multi-node approaches in landscape graph analysis for reserve design.</div><div><br></div><div>References</div><div>1. D.L. Urban, E.S. Minor, E.A. Treml and R.S. Schick, “Graph models of habitat mosaics”, Ecology Letters, 12(3), 260–273, 2009</div><div>2. S.P. Borgatti, “The Key Player Problem”, Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers (eds R. Breiger, K. Carley & P. Pattison), pp. 241-252. Committee on Human Factors, National Research Council, 2003</div></div><div><br></div

Abiotic variables (turbidity in (a) and temperature in (b)) followed by biotic ones (<i>I_H(M)</i> for OMNI in (a) and TERR in (b)).

<p>To help visual comparability, values have been transformed in such a way that the minimum and the maximum value be equal to 0 and 1, respectively. The <i>x</i> axis is the series of study sites.</p

The food web of the pristine river (site 1), size of nodes is proportional to six measures of importance: <i>D</i> (a), <i>nBC</i> (b), <i>K</i> (c), <i>TI³</i> (d), <i>I_H(V)</i> (e) and <i>K_H(V)</i> (f).

<p>Network drawn by COSBILAB Graph <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040280#pone.0040280-Valentini1" target="_blank">[17]</a>.</p

The <i>I_H(V)</i> value for four selected trophic groups at each site.

<p>The top-down effects of fish on the dynamical variability of other groups in increasing in the more human-influenced site.</p

Importance ranks of trophic groups in the food web of the pristine river (site 1).

<p>Ranking is based on topological (<i>D</i>, <i>nBC</i>, <i>K</i>, <i>TI³</i>) and dynamical (<i>I_H(M)</i>, <i>I_H(V)</i>) measures, as well as keystone indices considering also population size (<i>K_H(M)</i>, <i>K_H(V)</i>). The <i>I_H(M)</i> and <i>I_H(V)</i> indices for all groups in each of the six sites are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040280#pone.0040280.s005" target="_blank">Appendix S5</a>.</p

Control Strategy Scenarios for the Alien Lionfish <i>Pterois volitans</i> in Chinchorro Bank (Mexican Caribbean): Based on Semi-Quantitative Loop Analysis

<div><p>Ecological and eco-social network models were constructed with different levels of complexity in order to represent and evaluate management strategies for controlling the alien species <i>Pterois volitans</i> in Chinchorro bank (Mexican Caribbean). Levins´s loop analysis was used as a methodological framework for assessing the local stability (considered as a component of sustainability) of the modeled management interventions represented by various scenarios. The results provided by models of different complexity (models 1 through 4) showed that a reduction of coral species cover would drive the system to unstable states. In the absence of the alien lionfish, the simultaneous fishing of large benthic epifaunal species, adult herbivorous fish and adult carnivorous fish could be sustainable only if the coral species present high levels of cover (models 2 and 3). Once the lionfish is added to the simulations (models 4 and 5), the analysis suggests that although the exploitation or removal of lionfish from shallow waters may be locally stable, it remains necessary to implement additional and concurrent human interventions that increase the holistic sustainability of the control strategy. The supplementary interventions would require the implementation of programs for: (1) the restoration of corals for increasing their cover, (2) the exploitation or removal of lionfish from deeper waters (decreasing the chance of source/sink meta-population dynamics) and (3) the implementation of bans and re-stocking programs for carnivorous fishes (such as grouper) that increase the predation and competition pressure on lionfish (i.e. biological control). An effective control management for the alien lionfish at Chinchorro bank should not be optimized for a single action plan: instead, we should investigate the concurrent implementation of multiple strategies.</p></div

Model 4.

<p>Benthic-pelagic ecological model 4, including the alien lionfish (LF) into the benthic-pelagic system of the Chinchorro bank (México). The baseline community matrix with the semi-quantitative effect of <i>j</i> variable to <i>i</i> variable is also shown. The parenthesis shows the kind of intervention. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130261#sec002" target="_blank">Methods</a> for more details.</p

Routh-Hurwitz and Levins´s stability criteria (as sustainability measure) for the different models and scenarios simulated.

<p>Local stability measures Routh-Hurwitz and Levins (<i>F</i>_<i>n</i>) criteria in the models and scenarios simulated. First criterion (1°C) describes stability condition, and the second criterion (2°C) determines asymptotic or oscillation condition. The Levins’s (<i>F</i>_<i>n</i>) criterion can be used as an approach for holistic sustainability. The assumptions considered were changes in the self-dynamics (damped ´-´and/or enhanced ´+´) for the variables in each model^aa The names of the variables are described with details in Methods section.</p><p>Routh-Hurwitz and Levins´s stability criteria (as sustainability measure) for the different models and scenarios simulated.</p

Models 1 and 2.

<p>Ecological models 1 and 2 for the coral benthic system of Chinchorro bank (México). The baseline community matrices with the nominal effect of <i>j</i> variable to <i>i</i> are also shown. The parenthesis shows the kind of intervention. For more explanation of the name of variables and interactions see the text.</p

Model 5.

<p>Ecological and social model 5 for the Chinchorro bank (México). The lionfish is separated in two meta-populations (from shallow and deeper waters) and two kinds of fishers and the demand (from the market) are also integrated. The baseline community matrix with the semi-quantitative effect of <i>j</i> variable to <i>i</i> variable is also shown. The parenthesis shows the kind of intervention. For more details of the variables and interactions see the text (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130261#sec002" target="_blank">Methods</a>).</p