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Axioms in Model-based Planners

Axioms can be used to model derived predicates in domain- independent planning models. Formulating models which use axioms can sometimes result in problems with much smaller search spaces and shorter plans than the original model. Previous work on axiom-aware planners focused solely on state- space search planners. We propose axiom-aware planners based on answer set programming and integer programming. We evaluate them on PDDL domains with axioms and show that they can exploit additional expressivity of axioms.

Introduction
Currently, in the most commonly studied classical planning models, all changes to the world are the direct effects of some operator. However, it is possible to model some effects as indirect effects which can be inferred from a set of basic state variables. Such derived predicates can be expressed in modeling languages such as PDDL and formalisms such as SAS+ as axioms, which encode logical rules defining how the derived predicates follow from basic variables. Planners have supported various forms of derived predicates since relatively early systems (Manna and Waldinger 1987;Barrett et al. 1995), and PDDL has supported axioms which specify derived predicates as a logic program with negationas-failure semantics since version 2.2 (Edelkamp and Hoffmann. 2004) Consider, for example, the well-known single-agent puzzle game Sokoban, in which the player pushes stones around in a maze. The goal is to push all the stones to their destinations. The standard PDDL formulation of Sokoban used in the International Planning Competition(IPC) consists of two kinds of operators, push and move. push lets the player push a box in one direction, while move moves the player into an unoccupied location. Ivankovic and Haslum (2015a) proposed a new formulation of Sokoban with axioms and showed that this leads to a problem with a smaller search space and shorter plan (Ivankovic and Haslum 2015b). They remove the move operators entirely, and introduce axioms to check whether the player can reach a box to push it. The reformulated push operators now have a derived predicate reachable(loc) instead of at-player=loc as their precondition. The values of the derived predicates are determined by the following axioms: 1. reachable(loc) ← at-player=loc 2. reachable(loc) ← reachable(from), clear(loc), connected (from,loc) Intuitively, the first axiom means that the current location of the player is reachable. The second axiom means a location next to a reachable location is also reachable. With axioms, the search space only has the transitions caused by push operators, resulting in smaller search space and shorter plan.
Previous work on derived predicates and axioms for planning has focused on the advantages of expressivity (compactness) of domain modeling using axioms, (Thiébaux, Hoffmann, and Nebel 2005), as well as forward state-space search algorithms which are aware of axioms (Coles and Smith 2007;Gerevini, Saetti, and Serina 2011;Ivankovic and Haslum 2015b).
While previous work focused solely on axiom-aware state search planners, to our knowledge, little to no work has been done to evaluate model-based planners on PDDL domains with axioms. A standard approach to model-based planning is to translate a planning problem instance into a k-step model of other formalisms such as SAT and Integer Programming (IP), where a feasible solution to the k-step model corresponds to a solution to the original planning problem with n < k "steps".
We propose two axiom-aware model-based planners called ASPlan and IPlan, which are based on answer set programming (ASP) and integer programming (IP) respectively, and show that additional expressivity of axioms help modelbased planners as well.
Answer set programming (ASP) is a form of declarative programming based on answer set semantics of logic programming, and thus is a natural candidate for integrating axioms. Early attempts to apply ASP to Planning (Subrahmanian and Zaniolo 1995) and (Dimopoulos, Nebel, and Koehler 1997a) predated PDDL, and were not evaluated on large sets of benchmarks. To our knowledge, the first ASP-based planner compatible with PDDL is plasp (Gebser, Kaufmann, and Schaub 2012). However, plasp does not handle axioms. We developed ASPlan based on plasp, but used PDDL to SAS+ translator of FastDownward (Helmert 2006) to make it compatible with larger sets of IPC domains including domains with axioms.
IPlan is an IP-based planner based on Optiplan (van den Briel and Kambhampati 2005). We integrated axioms into IPlan by using the ASP to IP translation method by (Liu, Janhunen, and Niemelä 2012). To our knowledge, ASPlan and IPlan are the first model-based planners which handle axioms.

Normal Logic Problem
We introduce a normal logic problem, adopting the notations used in (Liu, Janhunen, and Niemelä 2012).
Definition 1. A normal logic problem (NLP) P consists of rules of the form where each a, b i , c j is a ground atom.
Given a rule r ∈ P , we denote the head of the rule a by H(r), the body {b 1 , ..., b m , notc 1 , ..., notc n } as B(r) , the positive body literals {b 1 , ..., b m } by B + (r) and the negative body literals {notc 1 , ..., notc n } by B − (r). We use At(P ) for the set of atoms which appear in P .
A set of atoms M satisfies an atom a if a ∈ M and a negative literal not a if a ∈ M , denoted M a and M nota, respectively; M satisfies a set of literals L, denoted M L, if it satisfies each literal in L; M satisfies a rule r, An answer set of a program is defined through the concept of reduct.
Definition 2. For a normal logic program P and a set of atoms M , the reduct P M is defined by Definition 3 (Gelfond and Lifschitz 1988). A model M of a normal logic program P is an answer set iff M is the minimal model of P M .
We are particularly interested in a class of logic programs called locally stratifed programs, which disallow negation through recursions. Locally stratified programs were originally introduced in Przymusinski (1988).
Definition 4. A normal logic program P is locally stratified if and only if there is a mapping l from At(P ) to {1, ..., | At(p) |} such that: • for every rule r with H(r) = a and every b ∈ B + (r) , l(b) ≤ l(a) • for every rule r with H(r) = a and every c ∈ C − (r), l(c) < l(a) With stratifications the unique model, called a perfect model can be computed by a stratified fixpoint procedure (Apt, Blair, and Walker 1988). It is known that the perfect model for a locally stratified program coincides with the unique answer set of the program (Eiter, Ianni, and Krennwallner 2009).

SAS+ and Axioms
We adopt the definition of axiom-enhanced SAS+ used in Helmert (2009) and Ivankovic and Haslum (2015b). Definition 5. An SAS+ problem with axioms Π is a tuple ( V , O, I, G, U, A) where -V is a set of primary variables. Each variable v i has a finite domain of values D(v i ).
-O is a set of operators. Each operator o has a precondition (pre(o)), which consists of variable assignments of the form v i =x where x∈D(v i ). We abbreviate v i =1 as v i when we know the variable is binary. An operator o is applicable in a state s iff s satisfies pre(o).
Each operator o also has a set of effects (eff(o)). Each effect e∈eff(o) consists of a tuple (cond(e),affected(e)) where cond(e) is possibly empty variable assignments and affected(e) is a single variable and value pair. Applying an operator o with an effect e to a state s where cond(e) is satisfied results in a state (o(s)) where affected(e) is true.
cost(o) is the associated cost of the operator o. -I is an initial assignment over primary variables.
-G is a partial assignment over variables that specifies the goal conditions. -U is a set of secondary variables. Secondary variables are binary and do not appear in operator effects. Their values are determined by axioms after each operator execution.
-A is a set of rules of the form (1). Axioms and primary variables form a locally stratified logic program. At each state, axioms are evaluated to derive the values of secondary variables. We denote the result of evaluating a set of axioms A in a state s as A(s). Note that A(s) is guaranteed to be unique due to the uniqueness of the model for locally stratified logic programs.
A solution (plan) to Π is an applicable sequence of operators o 0 , ..., o n that maps I into a state where the G holds.

∀ vs. sequential (seq-) semantics
A standard, sequential search strategy for a mode-based planner first generates a 1-step model (e.g., SAT/IP model), and attempts to solve it. If it has a solution, then the system terminates. Otherwise, a 2-step model is attempted, and so on (Kautz and Selman 1992). Adding axioms changes the semantics of a "step" in the k-step model. As noted by Dimopoulos et al (1997b) and Rintanen et al (2006), most model-based planners, including the base IPlan/ASPlan planners we evaluate below, use ∀ semantics, where each "step" in a k-step model consists of a set of actions which are independent of each other and can therefore be executed in parallel. In contrast, sequential semantics (seq-semantics) adds exactly 1 action at each step in the iterative, sequential search strategy. In general, ∀ semantics is faster than seqsemantics, since ∀ semantics significantly decreases the # of iterations of the sequential search strategy. For the domains with axioms, however, we add a constraint which restricts the number of actions executed at each step to 1, imposing seq-semantics. This is because a single operator can have far-reaching effects on derived variables, and establishing independence with respect to all derived variables affected by multiple operators is nontrivial (future work).
We describe our answer set programming based planner AS-Plan. ASPlan adapts the encoding of plasp (Gebser, Kaufmann, and Schaub 2012) to the multi-valued semantics of SAS+. While plasp directly encodes PDDL to ASP, ASPlan first obtains the grounded SAS+ model from PDDL using the FastDownward translator, and then encodes the SAS+ to ASP. Using the FastDownward translator makes it easier to handle more advanced features like axioms and conditional effects.

Baseline Implementation
We translate a planning instance to a normal logic program with k steps. Having k-steps means that we have k + 1 states or "layers" to consider.
const n = k. step 1..n. layer 0..n. ( For each v i =x∈I, we introduce the following rule which specifies the initial state.
Likewise, for each v i =x∈G, we have the following rule.
The next rule (6) makes sure that all of the goals are satisfied at the last step.
← goal(F), not holds(F,n) For each operator o∈O and each v i =x and v j =y in o's preconditions and effects respectively, we introduce the following rules.
Rules (8) and (9) require that applied operators' preconditions and effects must be realized.
Inertial axioms (unchanged variables retain their values) are represented by rules (10)-(11). An assignment v=x to a SAS+ variable is mapped to an atom f(v,x).
inertial(f(X,Y)), not changed(X,I) (11) Note that every primary variable v is marked as inertial with the following rule.
With the sequential semantics, the rule (13) ensures that only one operator is applicable in each step.
On the other hand, with ∀-semantics, (14)-(16) requires that no conflicting operators are applicable at the same step. Since variables in SAS+ cannot take different values at the same time, we introduce the mutex constraint (17).

Integrating Conditional Effects
We describe how to integrate conditional effects into AS-Plan. For each operator o and its effect e∈eff(o), we introduce the following rule fired(E,I) ← apply(A,I), holds(f(v 1 ,x),I), ..., holds(f(v n ,z),I), step(I) (21) where v 1 =x,...,v n =z are in cond(e). With conditional effects, applying operators does not necessarily mean their effects get triggered. We replace the rules (10) and (11)

Baseline Implementation
We describe our baseline integer-programming planner IPlan, which is based on Optiplan (van den Briel and Kambhampati 2005). Optiplan, in turn, extends the statechange variable model (Vossen et al. 1999), and the Optiplan model is defined for af propositional (STRIPS) framework. IPlan adapts the Optiplan model for the multi-valued SAS+ framework, exploiting the FastDownward translator (Helmert 2006).
An assignment v=x to a SAS+ variable is mapped to a fluent f . For all fluents f and time step t, Optiplan has the following state change variables. pre f , add f and del f denote a set of operators that might require, add, or delete f respectively. Intuitively, state change variables represent all possible changes of fluents at time step t.
x maintain For all operators o and time step t, Optiplan has the operator variables The constraints (30) and (31) represent the initial states constraints.
The constraint (32) ensures that the goals are satisfied at the last step T .
For all fluents f and time step t, Optiplan has the following constraints to make sure the state change variables have the intended semantics.
The constraints (40) and (41) restrict certain state changes from ocurring in parallel.
The constraint (42) represents the backward chaining requirement.
x preadd New Mutex Constraints IPlan augments the Optiplan model with a new set of mutex constraints. In addition to the above variables and constraints which are from Optiplan, IPlan introduces a set of auxiliary binary variables x sat f,t with the following constraints. x sat f,t corresponds to the value of the fluent f at the time step t.
x sat f,t ≤x add f,t + x preadd x sat f,t ≥x add f,t x sat f,t ≥x preadd f,t x sat f,t ≥x maintain f,t Using x sat f,t , mutex constraints can be implemented as follows. For every mutex group g (at most one fluent in g can be true at the same time) found by the FastDownward (Helmert 2006) translator, IPlan adds the following constraint.
f ∈g

Integrating Axioms
We describe how to integrate axioms into an IP-based model. For each time step t, axioms form the corresponding normal logic program (NLP) P t . The models for P t correspond to the truth values for the derived variables. We translate each NLP P t to an integer program (IP) using the method by Liu, Janhunen, and Niemelä (2012), and add these linear constraints to the IPlan model.
Level Rankings Translation from a NLP to an IP by (Liu, Janhunen, and Niemelä 2012) relies on characterizing answer sets using level rankings. Intuitively, a level ranking of a set of atoms gives an order in which the atoms are derived. Definition 6 (Niemelä 2008). Let M be a set of atoms and P a normal program. A function lr:M →N is a level ranking of M for P iff for each a∈M , there is a rule r∈P M such that H(r)=a and for every b∈B + (r), lr(a) − 1≥lr(b). Note that P M is the set of support rules, which are essentially the rules applicable under M . Definition 7 (Niemelä 2008). For a program P and I⊂ At(P ), P I ={r∈P |I B(r)} is the set of support rules.
The level ranking characterization gives the condition under which a supported model is an answer set. Definition 8 (Apt, Blair, and Walker 1988). A set of atoms M is a supported model of a program P iff M P and for every atom a∈M there is a rule r∈P such that H(r)=a and M B(r). Theorem 1 (Niemelä 2008). Let M be a supported model of a normal program P . Then M is an answer set of P iff there is a level ranking of M for P .
Components and Defining Rules Liu, Janhunen, and Niemelä (2012) defines a dependency graph of a nomal logic program to be used for the translation to IP. Definition 9 (Liu, Janhunen, and Niemelä 2012). The dependency graph of a program P is a directed graph G = V, E where V = At(P ) and E is a set of edges a, b for which there is a rule r∈P such that H(r) = a and b∈B + (r). Definition 10 (Liu, Janhunen, and Niemelä 2012). For a program P and an atom a∈At(P ), respective sets of defining rules, externally defining rules, and internally defining rules are defined as follows: Def P (a)={r∈P |H(r)=a} (48) Ext P (a)={r∈Def P (a)|B + (r) ∩ SCC(a)=φ} (49) Int P (a)={r∈Def P (a)|B + (r) ∩ SCC(a) =φ} (50) The set of internally supporting atoms is defined as IS(a, r)=SCC(a) ∩ B + (r).
Translation We are now ready to describe how to translate a normal logic program P t formed by axioms to linear constraints based on the method by Liu, Janhunen, and Niemelä (2012). The translation consists of linear constraints develeped below. 1. For each secondary variable u∈U , introduce a binary variable x sat u,t . 2. For each secondary variable u∈U , include the following constraint where bd r t is a binary variable for each r∈Def P (u) and step t. Intuitively, bd r t represents whether the body of r is satisfied at step t. The constraint ensures that when one of the rules defining u (Def P (u)) is satisfied, x sat u,t must be true (x sat u,t =1).
3. For each axiom r∈A, include the following constraints.
b∈B + (r) x sat c,t − bd r t ≤|B + (r)| − 1 (54) Constraints (53) and (54) express the fact that the body of rule r is satisfied iff each literal in B(r) is satisfied. 4. For each secondary variable u∈U , include the constraint where s r t is a binary variable for each r∈Int P (u) and each step t. Intuitively, the binary variable s r t represents whether the respective ranking constraints for the rule r are satisfied in addition to its body. The constraint requires x sat u,t to be true when one of its externally defining rules is satisfied or one of its internally defining rules is satisfied while respecting the ranking constraints. 5. For each secondary variable u∈U and each r∈Int P (u), include the constraints where gt ub t is a binary variable for each b∈IS(u, r), which represents whether the rank of u is greater than tha of b. 6. For each secondary variable u∈U and each r∈Int P (u), and each b∈IS(u, r), include the constraint z a,t − z b,t − |SCC(u)| · gt ab t ≥1 − |SCC(u)| (58) where z a,t and z b,t are integer variables representing level rankings for a and b respectively. The constraint (58) guarantees that if gt ab t =1 then z a,t ≥z b,t . With the above constraints, x sat u,t corresponds to the values of a secondary variable u at time step t. Since secondary variables only appear in operators' preconditions, we only need to make sure applied operators' preconditions are satisfied.
y u,t ≤x sat u,t ∀a∈pre f \ del f (59) For the reasons described earlier, with domains with axioms, we need to add the following constraint to restrict the number of operators executed at each time step to 1.

Experimental Results
All experiments are performed on a Xeon E5-2670 v3, 2.3GHz with 2GB RAM and 5 minutes limit. In all experiments, the runtime limits include all steps of problem solving, including translation/parsing, and search. We use clingo4.5.4, a state-of-the-art ASP solver (Potassco 2016) to solve the ASP models produced by ASPlan. The IP models produced by IPlan are solved using Gurobi Optimizer 6.5.0, single-threaded. The rules and constraints used in each of our planner configurations are summarized in Table 2.

Baseline Evaluation on PDDL Domains without Axioms
We first evaluated ASPlan and IPlan on PDDL domains without axioms to compare them against existing planners.
A thorough comparison of model-based planners is nontrivial because of the multitude of combinations possible of translation schemes, solvers, and search strategies. The purpose of this experiment is to show that the baseline AS-Plan and IPlan planners perform reasonably well compared to similar, existing model-based planners which (1) use a simple search strategy which iteratively solves k-step models, and (2) use models which are solved by "off-the-shelf" solver algorithms, i.e., this excludes planners that such as Madagascar (Rintanen, Heljanko, and Niemelä 2006), which uses a more sophisticated search strategy and customized solver algorithm, as well as the flow-based IP approaches (van den Briel, Vossen, and Kambhampati 2008). We compared the following: (1) APlanS (ASPlan with seq-semantics) (2) plasp 1 (3) IPlanS (IPlan with seqsemantics) (4) IPlan (IPlan with ∀-semantics) (5) ASPlan (ASPlan with ∀-semantics) (6) The state of the art CSPbased planner TCPP (Ghooshchi et al. 2015).
Since plasp uses incremental grounding, we used iClingo 2 (Gebser et al. 2008) as an underlying solver. As for TCPP, we could not obtain the souce code from the authors as of this writing, so we use the results from the original paper. The results are shown in Table 1.
ASPlanS dominated plasp in every domain, indicating that ASPlan is a reasonable, baseline ASP-based solver. This is to be expected, since ASPlanS is based on the plasp model. Among ∀-semantics solvers ASPlan, IPlan and TCPP, ASPlan and IPlan are highly competitive with TCPP despite the fact that the results for TCPP were obtained with a significantly longer (30min. vs. 5min) runtime limit (on a different machine).

Evaluation on PDDL Domains with Axioms
We evaluated ASPlan and IPlan on PDDL domains with axioms.
The results are shown in Table 3. About the domains used in experimental evaluations, Sokoban has been discussed already. The new domains are discussed below. 3 Verification Domains by Ghosh, Dasgupta, andRamesh (2015) Ghosh, Dasgupta, andRamesh (2015) proposed a modeling formalism for capturing high level functional specifications and requirements of reactive control systems. The formulation consits of two agents, namely the environment which distubs the system, and the controller which tries to return the system to safe state. If there is a sequence 1 plasp was sourced from (https://sourceforge.net/p/potassco/code/7165/tree/trunk/plasp-2.0/releases).
2 iClingo was obtained from (https://sourceforge.net/projects/potassco/files/iclingo/3.0.5/iclingo-3.0.5-x86-linux.tar.gz/download) 3 The benchmarks are available with more detailed descriptions from (https://github.com/dosydon/axiom benchmarks). 2GB, 5min # A S P la n S p la sp IP la n S IP la n A S P la n T C P P   of operators for the environment that leads to an unsafe state, the control system has vulnerability. We used two compiled versions of the formulation: compilation into STRIPS proposed by (Ghosh, Dasgupta, and Ramesh 2015): and compilation into STRIPS with axioms discussed in (Ivankovic and Haslum 2015b).
The Adaptive Cruise Control (ACC) is a well known driver assistance feature present in many high end automotive systems. The ACC is designed to take away the burden of adjusting the speed of the vehicle from the driver, mostly under light traffic conditions. ACC is a verification domain for the ACC.
The GRID domain is a synthetic planning domain loosely based on cellular automata and incorporates a parallel depth first search protocol for added variety. Note that this domain is completely different from grid used in IPC. Kominis and Geffner (2015) Kominis and Geffner (2015) proposed a framework for handling beliefs in multiagent settings, building on the methods for representing beliefs for a single agent. Computing linear multiagent plans for the framework can be mapped to a classical planning problem with axioms.

Multi-Agent Domains by
Muddy Children, originally from Fagin et al. (2004), is a puzzle in which n children player together. During their play, k of the children get mud on their forheads. Each can see the mud on the others, but not their own. The goal for a child is to know if he or she has mud by sensing the beliefs of the others. Muddy Child is a rerfomulation of Muddy Children.
In Collaboration through Communication, the goal for an agent is to know a particular block's location. Two agents volunteer information to each other to accomplish a task faster than that would be possible individually.
In Sum, there are three agents, each with a number on their forehead. It is known that one of the numbers equals the sum of the other two. The goal is for one or two selected agents to know their numbers.
Wordrooms is a variant of Collaboration through Communication where two agents must find out a hidden word from a list of n possible words.
PROMELA IPC-4 benchmarks contain another domain with axioms called PROMELA aside from PSR. The task is to validate properties in systems of communicating processes (often communication protocols). , encoded in the Promela language. Edelkamp (2003) developed an automatic translation from Promela into PDDL, which was extended to generate the competition examples.
We used verification domains for Dining Philosophers problem, and the so-called Optical Telegraph protocol.
PSR The task of PSR (power supply restoration) is to reconfigure a faulty power distribution network so as to resupply customers affected by the faults. The network consists of electronic lines connected by switched and power sources with circuit breaker. PSR has been investigated by the AI community, including the works such as Bonet, Thiébaux, and others (2003). We used the version of PSR used in IPC-4, which is a simplified version of Bonet, Thiébaux, and others (2003) with full observability of the world and no numeric optimization.
It is interesting to note that in Sokoban, acc, psr-middle, and philosophers ASPlan (and sometimes IPlan) solved more instances from the formulations with axioms than the compiled formulations without axioms. This is because compiled instances tend to have longer plans, which modelbased planners such as ASPlan and IPlan had difficulty in handling.

Conclusion
We proposed axiom-aware model-based planners ASPlan and IPlan. ASPlan is an ASP-based planner, which is able to handle axioms and conditional effects. IPlan is an IP-based planner based on Optiplan (van den Briel and Kambhampati 2005). We integrated axioms into IPlan using the ASP to IP translation method by (Liu, Janhunen, and Niemelä 2012). We evaluated ASPlan and IPlan on PDDL domains with axioms and showed that axiom-aware model-based planners can exploit shorter plan with fomulations with axioms.
2GB, 5min # A S P la n S IP la n S A x io m s Domains from Ivankovic and Haslum (2015b)


How to Succeed as an International Horticultural Consultant

Although the term consultant is used extensively, the duty of an international horticultural consultant (IHC) lacks precision. We propose that the job of an IHC has many attributes similar to an extension agent in the United States. Accordingly, we highlight the responsibilities of an IHC and put them in a historic and organizational context. Subsequently, we give advice about how to act and behave adequately when going to a new country. We bring in experience from successful IHC and a synopsis of specialist literature. Because we stress the importance of the credibility of an IHC within the farming community he is working with, we emphasize interaction with her/his professional and social environment. An IHC must have a genuine interest in the people being served and their challenges and adequate competence to provide a genuine contribution. Many call themselves an IHC or are labeled this way by their employers. The American Society of Horticultural Science (ASHS) has used the term IHC since the early 1990s and refers to both full-time consulting and part-time jobs. Accordingly, IHCs are employed by individual producers, commodity groups, governments, international agencies, or universities (Albrijo, 1993). The term nongovernmental organization (NGO) was still rare in the 1990s, but is indispensable for a contemporary list of employers of IHC. The question of what an IHC actually does remains. There is little ambiguity regarding the first two words of this profession: an IHC works at least partially abroad, and his job is related to horticulture. A consultant is a person who professionally provides expert advice (Oxford English Dictionary, 2010). According to a representative post, typical activities of a horticultural consultant include visiting horticultural clients on site; identifying their business or technical problems; analyzing yields and financial returns; formulating technical solutions; planning and organizing trials to assess their technological options; preparing operational strategies and business plans; and supporting the infrastructure for processing, storage, and transport. Frequently, an IHC is also expected to write publications, hold presentations, and provide advice regarding regulations (Reed, 2009). This description, undoubtedly, is in line with what a horticultural consultant does in a developed country; indeed, most IHC would state that their daily routine is similar to this characterization. However, because IHC commonly work in developing countries, they would also interpret that their responsibilities go beyond giving advice. This is caused by the socioeconomic, educational, and political particularities of farmer communities in developing countries. Thus, the versatile requirements for an IHC depend on the environment where he is working and on the mission. Considering the technical, didactic, and administrative skills an IHC needs to succeed, their profile is close to those of an extension agent in the United States Cooperative Extension System. Extension is traditionally considered the organized exchange of information and the purposive transfer of skills (Nagel, 1997). The term was born around 1850 in the British universities of Oxford and Cambridge with the intention of reaching broader audiences beyond the students on campus (Jones and Garforth, 1997). Views of agricultural extension have changed over time (Davis and Heemskerk, 2012). Today, it describes all kinds of support for people engaged in agriculture by helping them to make the best possible use of their productive resources (Anderson, 2007; Muyanga and Jayne, 2006). Historically, farmers have received education, training, and advice from 1) informal communication, 2) individual innovators, 3) nonstate organizations, such as farmers’ associations, scientific societies, and universities, 4) commercial enterprises, and 5) the state (Garforth, 2011). Organized advice for farmers already existed in ancient Mesopotamia, Egypt, Greece, Phoenicia, and China. The first modern agricultural extension service was founded in England as the result of the disastrous consequences of the outbreak of the potato blight in the 1840s. In the second half of the 19th century, legislation was passed to improve the state of agriculture through education throughout much of Europe, the United States, Canada, Australia, Japan, and many British colonies. Numerous other countries followed this example in the early 20th century. Extension became then a vehicle for fighting starvation through improving yields. At the end of the century, environmental issues as well as socioeconomic guidance of farmers also became concerns of extension. After a period of neglect, extension regained importance with the economic crisis of 2008 (Anderson, 2007; Azadi and Filson, 2009; Jones and Garforth, 1997). For decades, the research-extensionfarmer linkage was based on a simple model: ‘‘Modern’’ research results had to be transferred to the ‘‘backward’’ farmer (Nagel, 1997). Nowadays, apart from providing knowledge to improve productivity, extension services are expected to cover a variety of new functions, such as support for smallholder farmers, the management of production and marketing chains, food safety, environmentally sustainable production techniques, multifunctional land use, food security, and the facilitation of learning and negotiation processes (Azadi and Filson, 2009; Leeuwis, 2004a, 2004b). This is particularly true for developing countries, where more than 90% of the world’s nearly one million extension personnel are located (Anderson, 2007). The most common reason for a government to employ an extension service is to guarantee the food security of its nation. A subsequent purpose is the stimulation of agricultural exports. As of the end of the 20th century, public extension was criticized for being irrelevant to the real needs of farmers and for being too expensive (Azadi and Filson, 2009). A further criticism is that conventional extension ignores nonfarm stakeholders of a food system (Christoplos, 2008). Although women constitute 60% of the rural population worldwide, only 5% were receiving extension services (Davis and Heemskerk, 2012). One answer to ineffective extension has been decentralization, handing over federal authority to branch offices and institutes and/or delegating control to lower levels of government (Rivera and Qamar, 2003). Received for publication 11 May 2017. Accepted for publication 11 July 2017. This paper is included in conjunction with the papers presented during the 2016 ASHS Annual Conference, Atlanta, GA, as part of the Workshop titled ‘‘Seize Your Future Internationally: New Opportunities in Horticultural Consulting.’’ The authors wish to thank Candace Shock who assisted in the review of the manuscript. Corresponding author. E-mail: roland.ebel@gmx. com. HORTSCIENCE VOL. 52(9) SEPTEMBER 2017 1151 Nonetheless, for example in Mexico, decentralized extension continues to be criticized for largely ignoring marginalized farmers (Uscanga and Edwards, 2016). A more radical idea is the total privatization: adapting to market demands, extension would supposedly respond more effectively to the needs of farmers and other value chain actors as if guided by the government (Christoplos, 2008). However, the experience so far shows that for gaining access to rural communities and for helping poor farmers, a central role of the public sector is indispensable to set extension priorities (Azadi and Filson, 2009). In addition, private consultants may consider farmers passive recipients of extension (diffusionist approach) rather than following the now prevailing constructivist concept, where famers learn by building on their own experience (van Mele et al., 2010). The still practiced top-down training and visit model (T&V) of extension does not fit the constructivist zeitgeist. It was promoted by the World Bank from 1975 to 1995 and consists in the transfer of technical advice through temporary community visits, where extension agents train selected contact farmers, who in turn are expected to educate the rest of the community (Anderson and Feder, 2004; Stewart et al., 2014). The standardized T&V curriculum largely fails to take into consideration that farmers continuously learn independently, solve problems, and identify new ones (Leeuwis, 2004a). Given the limitations of T&V, the concept of farmer field schools (FFSs) emerged. FFSs consider the needs of the farmers and train them in participatory research and agroecosystems appraisals. A key drawback of FFS is their high cost (Anderson, 2007). Raintree (1999) notes that all participative approaches to extension cannot entirely substitute classic knowledge transfer, since this would mean withholding relevant information from the farmers and, consequently, limit a community’s right to make its own evaluation of available infor mation. At present, there is a considerable diversity of agricultural extension around the world; but the extension is still absent in many regions. Most countries sustain a centralized governmental approach (eventually with a regional or semiautonomous orientation). Except for the United States, current public extension systems are prevailingly organized under governments rather than under universities (Swanson and Rajalahti, 2010); and the national Departments of Agriculture and Higher Education in these countries commonly do not work intensively with each other, either for rivalry or for legal restrictions. Although extension has become an object of constant reform (Rivera and Sulaiman, 2009), adoption rates remain relatively low in developing countries (Aker, 2011). Thus, the effectivity of extension is being continuously questioned. A study in the Ivory Coast, for example, indicates that extension had no effect on farmer revenue (Romani, 2003). Apart from a lack of money and infrastructure in many developing countries (which has to be best possible compensat

Many call themselves an IHC or are labeled this way by their employers. The American Society of Horticultural Science (ASHS) has used the term IHC since the early 1990s and refers to both full-time consulting and part-time jobs. Accordingly, IHCs are employed by individual producers, commodity groups, governments, international agencies, or universities (Albrijo, 1993). The term nongovernmental organization (NGO) was still rare in the 1990s, but is indispensable for a contemporary list of employers of IHC.
The question of what an IHC actually does remains. There is little ambiguity regarding the first two words of this profession: an IHC works at least partially abroad, and his job is related to horticulture. A consultant is a person who professionally provides expert advice (Oxford English Dictionary, 2010). According to a representative post, typical activities of a horticultural consultant include visiting horticultural clients on site; identifying their business or technical problems; analyzing yields and financial returns; formulating technical solutions; planning and organizing trials to assess their technological options; preparing operational strategies and business plans; and supporting the infrastructure for processing, storage, and transport. Frequently, an IHC is also expected to write publications, hold presentations, and provide advice regarding regulations (Reed, 2009). This description, undoubtedly, is in line with what a horticultural consultant does in a developed country; indeed, most IHC would state that their daily routine is similar to this characterization. However, because IHC commonly work in developing countries, they would also interpret that their responsibilities go beyond giving advice. This is caused by the socioeconomic, educational, and political particularities of farmer communities in developing countries. Thus, the versatile requirements for an IHC depend on the environment where he is working and on the mission.
Considering the technical, didactic, and administrative skills an IHC needs to succeed, their profile is close to those of an extension agent in the United States Cooperative Extension System. Extension is traditionally considered the organized exchange of information and the purposive transfer of skills (Nagel, 1997). The term was born around 1850 in the British universities of Oxford and Cambridge with the intention of reaching broader audiences beyond the students on campus (Jones and Garforth, 1997). Views of agricultural extension have changed over time (Davis and Heemskerk, 2012). Today, it describes all kinds of support for people engaged in agriculture by helping them to make the best possible use of their productive resources (Anderson, 2007;Muyanga and Jayne, 2006).
Historically, farmers have received education, training, and advice from 1) informal communication, 2) individual innovators, 3) nonstate organizations, such as farmers' associations, scientific societies, and universities, 4) commercial enterprises, and 5) the state (Garforth, 2011). Organized advice for farmers already existed in ancient Mesopotamia, Egypt, Greece, Phoenicia, and China. The first modern agricultural extension service was founded in England as the result of the disastrous consequences of the outbreak of the potato blight in the 1840s. In the second half of the 19th century, legislation was passed to improve the state of agriculture through education throughout much of Europe, the United States, Canada, Australia, Japan, and many British colonies. Numerous other countries followed this example in the early 20th century. Extension became then a vehicle for fighting starvation through improving yields. At the end of the century, environmental issues as well as socioeconomic guidance of farmers also became concerns of extension. After a period of neglect, extension regained importance with the economic crisis of 2008 (Anderson, 2007;Azadi and Filson, 2009;Jones and Garforth, 1997).
For decades, the research-extensionfarmer linkage was based on a simple model: ''Modern'' research results had to be transferred to the ''backward'' farmer (Nagel, 1997). Nowadays, apart from providing knowledge to improve productivity, extension services are expected to cover a variety of new functions, such as support for smallholder farmers, the management of production and marketing chains, food safety, environmentally sustainable production techniques, multifunctional land use, food security, and the facilitation of learning and negotiation processes (Azadi and Filson, 2009;Leeuwis, 2004aLeeuwis, , 2004b. This is particularly true for developing countries, where more than 90% of the world's nearly one million extension personnel are located (Anderson, 2007).
The most common reason for a government to employ an extension service is to guarantee the food security of its nation. A subsequent purpose is the stimulation of agricultural exports. As of the end of the 20th century, public extension was criticized for being irrelevant to the real needs of farmers and for being too expensive (Azadi and Filson, 2009). A further criticism is that conventional extension ignores nonfarm stakeholders of a food system (Christoplos, 2008). Although women constitute 60% of the rural population worldwide, only 5% were receiving extension services (Davis and Heemskerk, 2012).
One answer to ineffective extension has been decentralization, handing over federal authority to branch offices and institutes and/or delegating control to lower levels of government (Rivera and Qamar, 2003).
Nonetheless, for example in Mexico, decentralized extension continues to be criticized for largely ignoring marginalized farmers (Uscanga and Edwards, 2016). A more radical idea is the total privatization: adapting to market demands, extension would supposedly respond more effectively to the needs of farmers and other value chain actors as if guided by the government (Christoplos, 2008). However, the experience so far shows that for gaining access to rural communities and for helping poor farmers, a central role of the public sector is indispensable to set extension priorities (Azadi and Filson, 2009). In addition, private consultants may consider farmers passive recipients of extension (diffusionist approach) rather than following the now prevailing constructivist concept, where famers learn by building on their own experience (van Mele et al., 2010).
The still practiced top-down training and visit model (T&V) of extension does not fit the constructivist zeitgeist. It was promoted by the World Bank from 1975 to 1995 and consists in the transfer of technical advice through temporary community visits, where extension agents train selected contact farmers, who in turn are expected to educate the rest of the community (Anderson and Feder, 2004;Stewart et al., 2014). The standardized T&V curriculum largely fails to take into consideration that farmers continuously learn independently, solve problems, and identify new ones (Leeuwis, 2004a). Given the limitations of T&V, the concept of farmer field schools (FFSs) emerged. FFSs consider the needs of the farmers and train them in participatory research and agroecosystems appraisals. A key drawback of FFS is their high cost (Anderson, 2007). Raintree (1999) notes that all participative approaches to extension cannot entirely substitute classic knowledge transfer, since this would mean withholding relevant information from the farmers and, consequently, limit a community's right to make its own evaluation of available infor mation.
At present, there is a considerable diversity of agricultural extension around the world; but the extension is still absent in many regions. Most countries sustain a centralized governmental approach (eventually with a regional or semiautonomous orientation). Except for the United States, current public extension systems are prevailingly organized under governments rather than under universities (Swanson and Rajalahti, 2010); and the national Departments of Agriculture and Higher Education in these countries commonly do not work intensively with each other, either for rivalry or for legal restrictions.
Although extension has become an object of constant reform (Rivera and Sulaiman, 2009), adoption rates remain relatively low in developing countries (Aker, 2011). Thus, the effectivity of extension is being continuously questioned. A study in the Ivory Coast, for example, indicates that extension had no effect on farmer revenue (Romani, 2003). Apart from a lack of money and infrastructure in many developing countries (which has to be best possible compensated by individual IHC and the organizations behind them), there is also skepticism regarding the knowledge and skills of local extension agents. This is related to poor agent training by the respective governments (Halim and Mozahar, 1997).
To understand the various environments for a job as an IHC, we also must consider the ways to organize and implement extension. Nagel (1997) distinguishes between approaches that target all farmers of an area ( Table 1) and those that select clientele following specific criteria (Table 2). In addition, extension can target individual farmers or collectively target the entire community (Labarthe, 2009). We also distinguish three procedures to select the goals of an intervention and/or to validate its achievement: 1) the traditional approach, where the extension agents design the teaching objectives, contents, techniques, and evaluation; 2) the experiential approach, which stresses real or simulated situations in the field; and 3) the performance-based approach, where goals are measured through the attainment of a given level of proficiency (Halim and Mozahar, 1997). Finally, the institution that offers extension is usually also responsible for its operation. In contrast, in self-organization approaches (Klerkx et al., 2010), the implementation of extension depends on the target community. The goal is to enhance the capability of a community to find innovative solutions for future problems and to be able to apply them. This way, the facilitation of learning becomes more relevant than the content itself (Leeuwis, 2004a). Extension can also be directed by close cooperation between an extension agent and growers' association representatives in setting priorities and the growers' associations partially funding the research and extension objectives. The growers' associations then also facilitate education opportunities. Local groups of influential clientele can represent other interests than growers' associations.
Considering now the individual tasks of an IHC, there are two initial assumptions we would like to make: First, whether they accept it or not, beside their role as technical experts, IHC are also communication and community workers (Leeuwis, 2004a;Nagel, 1997;World Bank, 2007). Second, the tasks as IHC are no longer limited to the transfer of technologies but consist in the facilitation of innovation (Holding, 2002;Klerkx et al., 2010;van Beek, 1997).
An IHC may assume different communication roles (Table 3). The required role depends on the mission, and it can also change depending on local needs. The mission also determines the general purpose of an IHC to interact with farmers: 1) providing advice where farmers consciously request counseling or expertise, 2) supporting horizontal (farmer-to-farmer) knowledge exchange, 3) facilitating conflict management, 4) organizing capacity building, or 5) initiating innovation (Leeuwis, 2004a). Regarding the latter, innovation can be stimulated by technology-oriented (TIA) and systemsoriented (SIA) innovation approaches. TIAs are generated by formal research that is transferred to farmers (who play a passive role in the development of innovations). Conversely, SIA are technological and socioorganizational processes to enhance a community's capacity to respond to change. The facilitated skills are discovery based and originate from a joint learning process (Schut et al., 2016).

MATERIALS AND METHODS
Our recommendations for succeeding as an IHC are based on a study of relevant literature and on the experiences of IHC. This information is based on our own work as IHCs, interactions with other IHC all over the world, and with active members of the International Consultants Working Group (ICON) of the ASHS.

RESULTS AND DISCUSSION
Results involve 1) requirements to succeed as an IHC, 2) suggestions for implementing the job as an IHC, and 3) recommendations for behavior outside of the work environment.

REQUIREMENTS FOR A SUCCESSFUL IHC
Some consultants think they have the answers to all the farmers' problems. Unfortunately, their perceptions may not be true (Holding, 2002). The same applies for their role as communicators and innovation facilitators. Although numerous employers emphasize participation and community development, there is a considerable discrepancy between what extension agents eventually do and what they say they do (van Beek, 1997).
To be fair, it must be mentioned that working conditions of extension personnel have deteriorated within the last three decades, while their duties are increasing (Nagel, 1997). These days, extension agents must be technically excellent and highly proficient as educational practitioners, creating an infrastructure that promotes innovation and continuous learning (Davis and Heemskerk, 2012;Liles and Mustian, 2004). The challenge is to offer an expertise that adds to the one that the farmers already have (Leeuwis, 2004a) and fits their needs. Although it is impossible for a single person to meet all the ideal IHC characteristics, we would like to present the most frequently mentioned attributes of a successful IHC (Anderson, 2007;Davis and Heemskerk, 2012;Leeuwis, 2004a;Liles and Mustian, 2004) and group them in four categories.

SUGGESTIONS FOR IMPLEMENTING THE JOB AS AN IHC
There is excellent specialist advice available about didactic tools an IHC can use to succeed as an innovation facilitator (Garforth, 2011;Klerkx et al., 2010;Labarthe, 2009;Leeuwis, 2004aLeeuwis, , 2004bvan Beek, 1997;van Mele et al., 2010;World Bank, 2007). Therefore, we present suggestions in this regard, which are based on our own experience.

A successful IHC is an observer. Since
crops develop differently in other climates and soils, not everything that works at home will be a success abroad. Instead, a good IHC contemplates the new ecosystem and learns from local farmers. Farmers around the world are good observers and often do independent research to improve their crop production and postharvest handling skills. 2. As an IHC in a developing country, you work with crops familiar to you, but you will always lack the full technology you are accustomed to. Hence, you will learn to improvise. Thanks to this challenge, you usually leave your assignment learning more than what you have provided. 3. The target of innovative change (individual or collective), the procedure to determine goals, and strategies, as well as the approach to generate innovation, do not depend on the IHC, but on the interests and perceptions of her/his employer and the community served (Table 4). 4. An IHC needs to define goals and activities jointly with the farming community, and the broader purpose of innovative change must be clear from the outset. Otherwise, efforts to educate and introduce change can become, at best, a series of group dynamics that entertain farmers, but that do not conclude in a meaningful impact. 5. Print and online publications may contain relevant information for the target Table 3. Role of consultants and extension agents depending on the needs for innovative change and the goals and respective roles of client (adapted from Leeuwis, 2004a community-and farmers can understand them. Yet, they may need professional support in terms of structuring and ''translating'' the respective content to their jargon and learning style. Occasionally, a cultural and linguistic diversity within a target audience may require special attention in this regard (Leeuwis, 2004a). 6. A successful IHC is also a very good listener. Despite manifold available didactic resources, person-to-person communication is still the most important form of information transfer (Nagel, 1997). Local growers and technicians have a wealth of locally pertinent knowledge and through listening, the IHC better understands the local clientele and the realities and constraints within which they operate. An IHC should not only pay attention to official sessions but also listen to what is discussed during casual conversations and at markets, in bars, or during social events (Leeuwis, 2004a). 7. Joint fieldwork or other outdoor activities are one of the best ways to get to know the farmers personally and to learn about their needs and skills. 8. Locations are not neutral: For specific audiences, it may not be practically, culturally, or politically feasible to attend activities in certain locations (Leeuwis, 2004a). 9. The temporal agenda must fit the availability of the target community. Consultant activities should not interfere with indispensable crop management activities or with social events of a farmer community. 10. Good financial planning is essential.
Suggested innovative change must be compatible with local farming practices, financial resources, and credit and marketing constraints. Recommendations by an IHC often require (temporal and financial) investments by local farmers and other stakeholders. An IHC should be prepared to demonstrate that such potential investments will provide an adequate return on investment. Yet, it is not necessary for IHC to invest their own money. 11. The selection of cooperating staff is key.
The best participative approach becomes discredited through cooperating with ignorant, arrogant, or even discriminating persons. This also applies for partnering organizations. 12. An IHC can stimulate networks using horizontal coordination teams (Chowa et al., 2013). In similar fashion, an IHC needs a developed network of international contacts for input, advice, feedback and, eventually, even support. Networks are generally essential for starting and continuing working as an IHC. Counting on a great curriculum vitae, experience, and solid references is not an adequate ticket for succeeding as IHC: Most NGO and consulting companies value people they know and trust. 13. Sometimes, an IHC may become involved in a conflict of interests between members of the target community and their employer. Under such circumstances, loyalty to one's own organization is usually the adequate position. In any case, one should reflect on the situation thoroughly before articulating an opinion-if needed. 14. Only constant feedback and learning allows continuous improvement of work as an IHC.

ADEQUATE BEHAVIOR OUTSIDE THE WORKING ENVIRONMENT
We mentioned credibility as a principal trait of a successful IHC. Credibility is earned not only in the workplace. Especially, when working in a small, rural community, one should be aware of an almost permanent observation by the farmer families. Therefore, adequate behavior outside the working environment is as important as doing the job with dedication. We consequently suggest the following: Where another language is spoken, it is highly recommended to learn and practice it. This is not only a professional advantage (even if clients understand English, one can also understand the hallway conversations), it is also an act of intercultural respect. There is a strong tendency in developing countries to exalt foreign specialists. Newcomers face a high risk of (unconsciously) fitting into the role of a ''superior creature.'' Nonetheless, modesty is the appropriate attitude.
An IHC should never complain about poor infrastructure. There is no doubt that developing countries are economically worse off than the Western world, which is often visible at their farms, universities, and research stations. Thus, local people do not need to be reminded of short comings. Similarly, one should be prepared to face less than ideal housing accommodations from the outset. Once arriving at the work site, it is too late to complain. Public discussions on politics and religion should be avoided. If at all, they can take place among very good friends away from work. ''Doing well by doing good often'' makes it attractive for horticultural scientists to engage in IHC activities. However, an IHC cannot solve all problems of a developing country and should focus on her/ his responsibilities. One should adapt to the new cultural context but never try to assimilate. Enjoying the new environment (e.g., going for local food) is a prerequisite for a successful stay. Trying to imitate the local culture might turn out ridiculous and does not lend to one's credibility. Flexibility is essential. If someone cannot accept changes in proposed game plans and schedules, she/he maybe should look for a different job. Finally, the most important rule of all: Keep your private life private! One should always keep in mind that foreigners are judged more strictly in moral matters than locals.


Mainstreaming Nature-based Solutions for Climate Change Adaptation in Urban Governance and Planning

The concept of mainstreaming climate change adaptation to foster sustainable urban development and resilience is receiving increasing interest. In particular, the need to mainstream ecosystem- or nature-based solutions into urban governance and planning is widely advocated by both academic and governmental bodies.

Introduction
Climate change and related hazards are an increasing threat to urban development, which, in turn, is increasing vulnerability to these hazards by inconsiderate development choices (OECD 2009;UNISDR 2008). This trend is expected to continue. Climate change is projected to magnify the frequency and intensity of weatherrelated hazards, which already account for the majority of annual losses from disasters (IPCC 2012(IPCC , 2014UNISDR 2010).
Consequently, resilience has emerged as a central concept in international and national development policy together with the concept of mainstreaming (Pervin et al. 2013;Wilkinson et al. 2014). Today, increasing resilience through the mainstreaming (or integration) of climate risk considerations into sector work is a unifying goal for the domains of climate change adaptation and disaster risk reduction (Andrade et al. 2011;Wamsler 2014). Resilience, i.e., "[T]the ability of a system, community or society exposed to hazards to resist, absorb, accommodate to and recover from their effects (…)" (UNISDR 2009(UNISDR , 2015, is also a feature of related global agendas, including the Sendai Framework for Disaster Risk Reduction 2015-2030, Sustainable Development Goals (SDGs) and the Paris Climate Agreement.
Against this background, the objective of this chapter is to present the key principles that show how adaptation mainstreaming can be achieved in urban governance and planning, 1 and discuss its role in fostering nature-based solutions and resilience. It should be noted that the term 'climate change adaptation' 2 denotes here an approach that integrates risk reduction and adaptation considerations.

What Is Adaptation Mainstreaming?
Adaptation mainstreaming refers to the inclusion of adaptation considerations into all sector policy and practice in order to reduce climate risk. The concept has two principal origins. One strand has developed from risk reduction mainstreaming, which has been strongly supported since the World Conference on Disaster Risk Reduction in Kobe, Japan in 2005(UNISDR 2005, and which itself builds on mainstreaming experience in cross-cutting domains such as HIV/Aids and gender (Daly 2005;Holden 2004;Mazey 2002). The second has its roots in environmental policy integration (United Nations 1987;Lenschow 2002;Van Asselt et al. 2015), and more specifically climate policy mainstreaming, which has been promoted since around 1997 (Collier 1997). The initial objective of climate policy mainstreaming was to integrate the objective of reducing greenhouse gas emissions into other sectoral policies. Over time, the focus has gradually broadened and currently it also explicitly includes adaptation considerations (Berkhout et al. 2015;Wamsler and Pauleit 2016).

Why Is Adaptation Mainstreaming Relevant?
Adaption mainstreaming is particularly relevant in the context of nature-based solutions. Although climate adaptation in general, and nature-based solutions in particular are widely advocated (Daily and Matson 2009;Gaffin et al. 2012;Ojea 2015;Pasquini and Cowling 2014), they have not been systematically implemented (Andrade et al. 2011;IPCC 2014;Sitas et al. 2014;Vignola et al. 2009;Wamsler et al. 2014;Wamsler 2015a). Many local authorities and other urban stakeholders are unsure about what they can do to change this situation. The problem remains: how can climate adaptation be systematically mainstreamed into urban governance and planning, and ultimately increase resilience?
To answer this question, this chapter provides an integrated framework for adaptation mainstreaming. It builds upon frameworks that have been developed for mainstreaming environmental policy, climate adaptation, disaster risk reduction and other cross-cutting domains. The framework was empirically developed and tested between 2003 and 2016 in close collaboration with governmental and nongovernmental organizations, in both developed and so-called developing countries (e.g., Germany, Sweden, the United Kingdom, Central America, Brazil), a process that has involved theoretical developments, analyses and the elaboration of practical guidelines. For more detailed information on the methodology, related case studies etc., see Wamsler (2006Wamsler ( /2007Wamsler ( , 2007Wamsler ( , 2009Wamsler ( , 2014Wamsler ( , 2015a; Wamsler et al. (2014); and Wamsler and Pauleit (2016).

The Framework: Adaptation Mainstreaming at the Local Level
At the local level, adaptation mainstreaming requires the consideration and combination of four approaches to comprehensively reduce climate risk. All four approaches aim to reduce risk, but in different ways. They can be illustrated by the example of a potential landslide. The first approach aims to reduce (current and future) hazard exposure, which can be achieved by moving away from the landslide hazard or by reducing exposure on-site. The second approach aims to reduce vulnerability of the landslide-exposed area. Here, the aim is to create an environment that can withstand hazard impacts, without losing any of the community's main functions. The third aims to ensure an effective response post-landslide. Here the goal is to prepare response mechanisms and structures, before potential hazard impacts. Finally, the fourth approach aims to ensure effective recovery. Here, the aim is to prepare recovery mechanisms and structures, again, before potential hazard impacts. The specific activities that are associated with each approach vary as a function of the hazard. Nevertheless, the principles do not change. For example, if the hazard is a flood rather than a landslide, the four approaches can be applied: reduce exposure, reduce vulnerability, prepare an effective response and prepare an effective recovery. Whenever possible, both multi-hazard and multi-purpose measures (i.e., measures that address both adaptation and other municipal objectives) should be implemented.
Nature-based solutions can be applied in the context of all four approaches: For example, exposure to flood can be reduced through beach nourishment, restoring or managing mangroves, or improved water management on the outskirts of urban areas. To reduce exposure to landslides, slopes can be stabilized through planting or the use of retention walls, which can combine elements of grey and green infrastructure. Careful urban planning, for example in the form of protected natural environments, can help to distance residential areas or critical infrastructure from a hazard, or at least ensure that settlements do not develop into hazard-prone areas.
With respect to reducing vulnerability, creating redundancy through naturebased solutions is an important element. Green infrastructure can help to reduce vulnerability by reducing dependency on only one system e.g. for heating, cooling, transportation or drainage. In addition, in the case of flood risk, measures for vulnerability reduction include the creation of buffer zones, retention ponds or increased permeable surfaces, for instance through the promotion of green roofs or urban agriculture. In the case of heat, measures include drought-resistant plants and improved insulation (e.g. through green walls).
In the context of response preparedness, typical measures include early warning systems and preparations for temporary refuge. In this context, nature-based solutions include well-designed green areas that can provide space for temporary shelter or protection (e.g., use of elevated green platforms during flash floods). Another example is the preparation of cooling mechanisms or structures. These include mobile planting systems or fountains, which can be used during heatwaves.
Recovery preparedness measures through nature-based solutions can include the use of materials or green infrastructure elements that can be easily recovered or replaced, along with preparations for post-disaster assistance. Examples are designated green areas that can be used for accommodation during reconstruction, preparations for the clearing or re-use of rubble (including green materials), or the provision of health and psychological support. The latter can include the support for greening private lots, being a multi-purpose measure with positive impacts on health and well-being. Other preparedness measures are awareness-raising campaigns and guidance on what to do after certain hazards, which can be linked to nature-based solutions (e.g. environmental learning parks). Although the contribution of naturebased solutions is often more indirect and contingent on other factors when it comes to preparedness measures, they are equally important.
It is crucial to understand and, ultimately, implement all four approaches, since local resilience is a function of inclusiveness and flexibility, rather than the effectiveness of a single approach (or measure) (Inderberg et al. 2015;Wamsler and Brink 2014;Wamsler and Pauleit 2016). Inclusiveness refers to the use of not just one or two, but all of the four risk-reducing approaches. Hence, whenever possible, measures that combine two, three or possibly all four approaches within a single activity should be preferred (e.g., in the creation of a climate park; cf., Box 15.1). Flexibility relates to the number and diversity of activities implemented for each approach, which must include both grey and green infrastructure together with socio-economic and political/institutional measures. This is crucial not only to identify multi-purpose solutions, but to also address the root causes of risk and, in turn, achieve sustainable change.
Appropriate activities for each approach must be identified for each individual context. Consideration must here be given to: (i) urban-rural linkages; (ii) urban characteristics (i.e., the urban fabric, the environment, economic and governance systems); and (iii) inter-area differences 3 (Wamsler, 2014;Wamsler and Brink 2016a). The latter can be characterized in terms of inclusion-exclusion, integrationmarginalization, wealth-poverty, equality-inequality, and formality-informality. 4 All of the above approaches/measures and considerations only apply to mainstreaming at the local or operational level. However, also organizations themselves need to change (procedures, organizational structures, policies and regulations, etc.), rather than simply 'mainstreaming' change into selected on-the-ground activities (Persson and Klein 2009;Van Asselt et al. 2015;Wamsler and Pauleit 2016).

Box 15.1 Magdalenenpark -A Climate Park for Munich, Germany
In 2013-2014, the NGO 'BUND Naturschutz' and the City of Munich, in cooperation with a team of landscape architects from the Technical University of Munich developed the design for a climate park. What is a climate park? It is an urban green space that: (i) is adapted to climate change; (ii) positively influences the microclimate; and (iii) stimulates citizens' adaptive awareness and behaviour (Brandl et al. 2014). Consistent with the four risk-reducing approaches introduced in this chapter, holistic adaptation measures were developed to address risk, and the microclimate modelling tool EnviMet was used to evaluate the design. This highlighted several features. First, increased vegetation improves thermal comfort and can reduce exposure to heat (Approach 1). Second, a variety of plants (e.g., drought-resistant species) increases the diversity of flora and reduces its vulnerability to heat stress (Approach 2). Third, it is important to select plants and materials (e.g., for benches) that can easily recover from heat or precipitation events (Approach 4). Finally, the park provides nearby residents from large housing estates with a place of refuge and temporary shelter during strong winds, precipitation or heat (Approach 3). The design is complemented by a pedagogical concept, related to all four risk-reducing approaches (Strategy VI). This includes providing information on adaptive behaviour, climate change and climate variability, and demonstrating the influence of different types of surfaces and vegetation covers. It also provides an opportunity to study the phenology of seasonal vegetation (e.g. bulbs that flower in early spring along hedges and in woodland, flowering cherries and meadows in summer, and fruit harvesting in autumn). The climate park is planned for an existing open green space in the western suburb of Neuaubing, but its implementation requires further negotiation with the landowner. Land ownership issues are a common challenge and highlight the importance of linking on-the-ground measures with mainstreaming strategies at institutional and interinstitutional level to ensure their sustainable implementation as described in this chapter.

The Framework: Adaptation Mainstreaming at the (Inter)Institutional Levels
Mainstreaming needs to take place at the local (operational), institutional and the interinstitutional 5 level in order to achieve sustainable change and to unite top-down and bottom-up efforts that together create a holistic and distributed governance system for climate adaptation (Fig. 15.1). To assure the sustainable implementation of the local approaches/measures presented in the previous section, there must also be changes at the institutional and interinstitutional levels in order to: • Institutionalize adaptation so that its integration at local level becomes standard procedure, which also includes the creation of mechanisms and structures for monitoring and learning 6 ; • Ensure that organizations themselves can continue to function during climate change impacts; • Cooperate in creating a multilevel governance system for climate adaptation that also includes citizens and, where possible; • Drive improved education on adaptation mainstreaming and science-policy integration.

Mainstreaming at institutional level
In sum, six mainstreaming strategies operate at the three levels (local, institutional and interinstitutional). 7 They are illustrated in Fig. 15.1 and Boxes 15.1, 15.2, 15.3 and 15.4. The first two (Strategies I-II) focus on the local or household level and relate to the way the four risk-reducing approaches (outlined above) are included in on-theground initiatives (either integrated or added on). Three strategies focus on the institutional level and address issues of internal organization (Strategy III) and cooperation (Strategy IV), together with policies and regulations (Strategy V). For example, it is crucial to ensure that organizational procedures and routines foster, rather than hamper (cf. Uittenbroek 2016), the implementation of nature-based solutions. The sixth strategy (Strategy VI) focuses on the interinstitutional level, external cooperation with other organizations (local, regional, national and international) and citizens. It addresses sector work, professional training and society in general.
At the institutional and interinstitutional level, mainstreaming involves both targeted and implicit integration. At the institutional level, municipalities' mainstreaming strategies can include the development of standalone adaptation strategies, the creation of interdepartmental working groups for climate change adaptation, and the integration of adaptation objectives into sectoral policies and instruments (e.g. green structure plans), comprehensive or detailed planning (cf. Wamsler 2015a; cf., Boxes 15.1, 15.2, 15.3 and 15.4). Strategies addressing the interinstitutional level can include municipal participation in regional innovation platforms that aim to create new business and cooperation models for financing nature-based solutions for climate adaptation, or the creation of city-citizen collaboration (cf. Wamsler 2015a). Unlike other mainstreaming frameworks that address targeted and implicit integration separately (cf. Uittenbroek 2016), the framework that is presented here includes both since related actions and processes are fluent and mutually supportive.
Politics and power must be explicitly addressed at all three mainstreaming levels, as they are a potential root cause of risk and represent avenues (or barriers) to transformation (cf., Boxes 15.1 and 15.4). The analysis of power (relations) is thus a precondition to sustainable change and to understand how transformation can be achieved or be hindered (Daly 2005;Digeser 1992;Partzsch 2015). This should include an evaluation of shared power (power with, cooperation and learning), the exercise of power (power to, resistance and empowerment) and power over others (coercion and manipulation) in potential mainstreaming approaches and strategies (cf. Allen 1998; Verloo 2005). Issues related to power need to be fundamentally challenged whenever and wherever modernity and globalization lead societies down an unsustainable road (Manuel-Navarrete 2010).

Box 15.2 Urban River Restoration -The 'Isarplan' Project in Munich, Germany
The river Isar is the most important green corridor in the city of Munich. Since the beginning of the 19th century this pre-alpine river has been increasingly regulated, both to reduce the risk of flooding and for power generation. However, flood risk and legal requirements related to flood protection necessitated its fundamental redesign. The Isarplan project was implemented in 2000-2011, and the main objectives were: (i) to improve flood control; (ii) to restore the river's ecological functions; and (iii) to improve recreational opportunities for the city's population. The city of Munich and the Regional Office for Water Management were responsible for its planning and implementation. The obvious solution was to continue to elevate the river's dams. However, the project provided an opportunity to explore a novel approach to ecological restoration, which would meet all three objectives. Consequently, the river bed was widened into surrounding flood plains, existing embankments were removed, and a naturalistic system of riverbed rock ramps was implemented that allowed fish to move upstream. (Oppermann 2005;Pauleit 2005;Pauleit and Kollmann 2015).
The Isarplan project is a good example of mainstreaming nature-based solutions for climate adaptation in urban planning at local and institutional levels. At the local level, the restoration of natural river banks and the widening of its channel reduced exposure to flood risk (Approach 1, Strategy I). The expansion of flood plains within the city created buffer zones that reduced vulnerability (Approach 2, Strategy I). Nature-based solutions are now also being planned for adjacent neighbourhoods, e.g., more greened routes that reduce risk and improve multipurpose recreation facilities (Approaches 2-4, Strategies I-II). Finally, water quality has been improved to the point where it is now possible to swim in the river. This was achieved by modernising sewage treatment plants in upstream municipalities. At the institutional level, an interdepartmental working group was responsible for coordinating the project; this group provided support and fostered a multi-benefit approach (Strategies III-IV). In addition, the project was designed by an interdisciplinary group of engineers, landscape architects, city planners and biologists, both internal and external to the city administration (Strategy VI). Today, the river Isar has been successfully transformed-not only into an appealing green space-but also into a support for comprehensive flood protection and management.

Box 15.3 Mainstreaming Climate Adaptation into Settlement Development in Bonn, Germany
The City of Bonn uses a four-step approach to advance mainstreaming of nature-based solutions for climate change adaptation in the development of new residential areas (Helbig and Gädker 2015): 1. Cross-departmental information events on climate change (involving urban planning, urban drainage, environment, urban greening and health departments) and follow-up events to discuss options, strategies and tradeoffs with regional actors (politicians, scientists and public utility companies) (Strategy VI). 2. Educational events moderated by scientists that broaden the knowledge base of city administrators and council members in terms of climate modeling, exceptional rain events and heat stress (Strategy IV). 3. The launch of an integrated climate protection concept, which includes a section on adaptation measures (science, management and administration) (Strategy V). 4. Mainstreaming of climate adaptation into municipal working routines and local settlement development (Strategies II and III).
These four steps include a broad range of actors and decision-makers from sectors that are both internal and external to the city administration. Whilst the first two steps aim to build a shared knowledge base about the impacts of climate change, the third and fourth aim to sustainably mainstream climate change adaptation at the local and institutional levels (internal cooperation and policies). In order to enrich the discussion and provide insights into the options for implementing nature-based solutions in residential areas, the municipality has also asked the University of Bonn (the Department of Urban Planning and Real Estate Development) to develop prototype scenarios for a potential infill site (Kötter et al. 2014). These scenarios, which were developed in the context of student seminars, focus on vulnerability reduction for local residents (Approach 2), while other types of risk-reducing approaches and their anchoring at institutional levels are excluded.

Box 15.4 The Lisbon Metropolitan Area's Ecological Network
The Lisbon Metropolitan Area (LMA) in Portugal is considered to be highly vulnerable to global climate change (Giorgi and Lionello 2008). As the region with the biggest population concentration, climate adaptation is a pressing issue for spatial and environmental planning.
The 2002 LMA Regional Spatial Plan defined a Metropolitan Ecological Network (MEN), which created a knowledge base of nature-based solutions for adaptation. The MEN defines areas and ecological corridors, which are organised into three hierarchical levels according to their importance for the environmental structure. Each level includes strategic guidelines and concrete climate change adaptation measures (mainly vulnerability reduction; Approach 2), as well as management requirements that ensure mainstreaming at the institutional level (e.g., policy and regulations -Strategy V, municipal responsibilities and financial resources -Strategy III). A noteworthy feature of the MEN is that it provides an integrated and consistent overview of designated nature conservation areas (Natura 2000 sites, natural parks, nature reserves, protected landscapes) and other ecologically-relevant areas. The lowest hierarchical level includes compact or fragmented urban areas that carry out important functions. The aim is to integrate these areas, designated as urban green zones, into municipal adaptation planning (Strategy V).
Whilst the MEN is expected to contribute to adaptation mainstreaming at the local level, it mainly addresses changes at the institutional and interinstitutional levels of governance. It can also be seen as a multi-purpose measure; although it is principally aimed at nature conservation, at the same time it supports ecosystem services that are relevant for climate change adaptation.
Its implementation highlights the potential for a governance framework with an expanded focus-from preventing or resisting climate hazards, to broader systems thinking. In 2013-2014, a participatory exercise was conducted in the LMA with stakeholders from local authorities, the national environmental authority and academia, who identified the MEN, and urban green space in general, as important drivers for sustainable planning (Mascarenhas et al. 2016).
Numerous challenges remain for mainstreaming nature-based solutions into planning practice in LMA. In addition to a fragmented institutional structure and power struggles, there is still insufficient knowledge about existing ecosystem services, how they affect human well-being and how they are, in turn, affected by planning decisions.

From Theory to Practice: Gaps and Synergies
In practice, mainstreaming can create synergy effects by promoting innovation in sector-specific policies, linking and aligning sector-specific and adaptation objectives, and encouraging more efficient use of human, physical and financial resources (Lafferty and Hovden 2003;Adelle and Russel 2013;Rauken et al. 2014;Runhaar et al. 2014;Dewulf et al. 2015;Persson et al. 2015). The framework presented here can support such developments, guide an organization's mainstreaming process and hold decision-makers accountable for any promises they may make in their endeavours. It provides an overall context for action and can be applied in combination with other frameworks that target particular mainstreaming levels, strategies or approaches, such as financial integration or internal risk management (CDKN 2015;Pervin et al. 2013;UNDP 2010;UNDP-UNEP 2011).
The mainstreaming framework presented here formed the cornerstone for the development of three operational guidelines that translate the mainstreaming theory into practice. The guidelines were developed for different urban stakeholders, including non-governmental organizations (Wamsler 2006(Wamsler /2007(Wamsler , 2009) and local authorities (Wamsler 2015b;Wamsler and Brink 2016b). The latter aim to assist municipal officials and local politicians to both assess and progress the mainstreaming of climate change adaptation into planning and governance mechanisms.
The first step in this process is to categorize existing and planned activities relevant for climate adaptation according to the mainstreaming level and the strategy they address. Questions include: What kind of activities are implemented at the local, institutional or interinstitutional level? Do activities at the institutional level address the integration of climate adaptation into the overall planning vision, comprehensive planning, detailed planning, related planning instruments, the internal organizational structure, and human and financial assets? In the second and third steps, existing and planned activities are assessed against established benchmarks. This includes an assessment of the use of the four risk-reducing approaches and related synergy creation, whether a single or multi-hazard approach is adopted, and whether physical, socio-economic, environmental and political/ institutional measures are implemented at different levels. The outcome of this assessment provides a clear overview of current progress and helps to identify gaps or ways to improve (for further details, see the operational guidelines presented in Wamsler 2015b; Wamsler and Brink 2016b).
Both the mainstreaming theory and the related guidelines have proven to be very useful, and their application has helped cities in the identification of various gaps. These gaps also highlight how mainstreaming and resilience are interlinked. Here, we focus on three specific examples: (i) the lack of systematic mainstreaming of nature-based solutions; (ii) the focus on municipal self-reliance or governing; and (iii) fragmented climate policy mainstreaming.
The first gap, the lack of systematic mainstreaming of nature-based solutions (which requires a combination of the presented approaches and strategies), is illustrated by the following statement by a member of staff from a German municipality: "We deal with the issue of adaptation in a very broad or general sense, and the differentiation between constructive and other types of adaptation measures [i.e., nature-based solutions] is, in practice, not yet a topic. We are not there yet [...] We have a smörgasbord of ideas, we still don't have an overview. This will come with further conceptualization (Wamsler 2015a). These words provide a link back to the starting point of this chapter. Specifically, they refer to the need for a better understanding and the systematic implementation of nature-based solutions to increase resilience (e.g. to overcome the current focus on grey infrastructure solutions in on-the-ground initiatives) .
The second gap is a lack of cooperation with other stakeholders to support nature-based solutions. This is illustrated by the following statement by a member of staff from a German municipality, "The first step now is [...] we are focusing on what we can do [...] what we can implement ourselves. And then we will look, after that, further afield, and try to involve others [e.g. private actors or citizens]" (Wamsler 2015a). This statement illustrates the widespread phenomenon of municipal self-reliance in climate adaptation. At the same time the importance of involving other stakeholders is generally acknowledged, especially in the context of naturebased solutions, "We are more and more dependent […] on everybody, every citizen must become active and get engaged, because the city cannot handle it [climate hazards] by itself anymore. The city depends on citizens' support" (Wamsler 2015a).
The third gap is fragmented climate policy mainstreaming, also regarding naturebased solutions. Specifically, it concerns the failure to integrate climate mitigation and climate adaptation mainstreaming. This is illustrated by the following statement from a staff member from a German municipality responsible for climate adaptation, "I am not sure who is responsible for climate mitigation [...] and related mainstreaming processes. It is dealt with separately" (Wamsler 2015a). This fragmented approach can hamper progress, as sustainable urban development requires integrated planning policy and practice. In addition, research has shown that adaptation mainstreaming can be spurred by an organization's experience with mainstreaming climate change mitigation (Wamsler and Pauleit 2016).

Conclusions
The mainstreaming of nature-based solutions for climate change adaptation can support incremental and transformative changes that address the root causes of risk and lead to sustainable development. Its implementation requires the consideration of four key principles. First, at the local level, all four approaches/ measures aimed at reducing climate risk on the ground have to be addressed, with nature-based solutions offering a broad range of applications. Second, mainstreaming strategies must be implemented at the local, institutional and interinstitutional levels in order to ensure the sustainable implementation of on-the-ground measures, and challenge current practice and procedures at multiple levels of governance. Third, measures and strategies can only lead to sustainable change in combination. Finally, previous experience in mainstreaming other cross-cutting issues (in particular climate change mitigation) can help to create synergies and progress adaptation mainstreaming.
Adaptation mainstreaming is a potentially effective way to foster urban resilience. In fact, the concept of mainstreaming is inherently linked to the concept of resilience, as it aims to challenge familiar ideas, attitudes, or activities and change dominant paradigms at multiple levels of governance. It can help to increase resilience by expanding the focus -from preventing or resisting hazards -to a broader systems framework in which the different stakeholders learn to live and cope with an ever-changing, and sometimes risky, environment. It can also lead to a more inclusive planning and risk governance system, which translates into the ability to change in response to altered circumstances and to carry on functioning even when individual parts fail. This can be achieved by including and linking physical, social, economic, environmental and political/ institutional aspects, different risk-reduction approaches and sector work, together with climate adaptation and mitigation considerations. Finally, the issue of power structures must be considered in any current (or potential) mainstreaming approaches or strategies.
As it stands today, practice remains characterised by individual measures, the creation of bolted-on structures, and related actions that are often seen purely as managerial governance exercises. A more systematic approach to mainstreaming nature-based solutions (as presented in this chapter), which also explicitly considers power structures, is urgently needed in order to ensure that root causes of risk and any avenues (or barriers) to transformation are addressed.